Web-enabled Services Development with Respect to ...

COPYRIGHT

iiSC2011 Proceedings

The International Information Systems Conference (iiSC) 2011 Sultan Qaboos University, Muscat, Sultanate of Oman

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission from iiSC.

iiSC’11, October 11–12, 2011, P. O. Box. 20, P.C. 123, Muscat, Sultanate of Oman. Copyright 2011 iiSC

ISBN: 978-9948-16-253-7

i

TABLE OF CONTENTS


Table of Contents Proceedings of iiSC2011 Preface

vi

iiSC2011 Organization

vii

Keynotes

X

Trends in Information Systems How IT will challenge existing organizational forms and create Ambient organizations Niels-Bjorn-Andersen (Copenhagen Business School, Denmark)

3

Software Solutions Construction: An Approach Based on Information Systems Architecture Principles Sana Guetat (Le Mans University, Le Mans), Salem Ben Dhaou Dakhli (Paris-Dauphine University, Paris)

10

AIS Quality: A Technological Perspective Ahmed A. Mohammad (Sultan Qaboos University, Oman)

18

XML Information Retrieval Systems: A SURVEY Awny Sayed (Ibri College of Applied Science, Oman)

25

E-Commerce and E-Business Challenges An Analysis of Intention to Use Online Group Purchases Yu-Hao Chuang, Chia-Sheng Lin, Wesley Shu (National Central University, Taiwan)

32

A Study of Adoption of Internet Banking in Oman in the Early 2000s, Re-Interpreted Using Innovation Translation Informed by Actor-Network Theory Salim Al-Hajri (Higher College of Technology, Muscat), Arthur Tatnall (Victoria University, Australia)

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TABLE OF CONTENTS


Application Controls: A New Prospect Fatma Mirza, Saqib Ali (Sultan Qaboos University, Oman)

46

Electronic Commerce (E-commerce) Issues, Benefits, Success Factors and Challenges faced by Financial Institutions in Pakistan Syed Rashid Ali (SZABIST, Pakistan), Naeem-ul Hassan Janjua (Bahria University, Pakistan)

54

Trends in Web Technologies Strategic Rating Factors for Finding the Richness of Text in Different formats for Arabic and English Text Boumedyen Shannaq, S.Arockiasamy, John D Haynes (University of Nizwa, Oman)

60

XCORS: a new XML Content-Based Retrieval System Ahmed A.A. Radwan (Minia University, Egypt), Awny Sayed (Ibri College of Applied Sciences, Oman), Mphamed M. Abdallah (Minia University, Egypt)

67

Trends in Web Technologies: Web 1.0 to Web 3.0 & Beyond Mithun Shrivastava, Tahera Paperwala, Komal Dave (Waljat College of Applied Sciences, Oman)

73

Web-enabled Services Development with Respect to Service-Orientation Paradigm Youcef Baghdadi (Sultan Qaboos University, Oman)

80

Knowledge Management and IS Industrial Applications The Role of Technology in Managing and Measuring Non-financial Performance in the Financial Services Industry Mostaq M. Hussain (Sultan Qaboos University, Oman)

87

Organizing information management and IT for tomorrow with the Amsterdam Information Model Theo Thiadens (Fontys University of Applied Sciences, Netherlands), ToonAbcouwer (University of Amsterdam, Netherlands)

96

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TABLE OF CONTENTS


The Application of Rational Unified Process in the Development of Road Traffic Accident Information Systems in the Gulf Region Elfadil A/Alla Mohamed, Nasser Taleb (Alain University of Science and Technology, United Arab Emirates) 105 Theories Used in IS Research – Application in Word of Mouth Research Mithun Shrivastava , S. Manasa (Waljat College of Applied Sciences, Oman)

110

E-Government Issues and Solutions The Victorian Schools Ultranet – an Australian eGovernment Initiative Arthur Tatnall (Victoria University, Australia) Ian Michael (Zayed University, Dubai, UAE), Eva Dakich (Victoria University, Australia)

126

A Comparative Analysis of the Major Issues for Successful Information Technology Transfer in Arab Countries Khalid Al-Mabrouk (Sebha University Marzouk – Fazan, Libya)

131

Information Systems Security and Mobile Computing Developing a Strategic Framework for the Establishment of Mobile Payments: A Canadian Financial Institution Perspective Ernest Johnson, Brian Guillemin (University of Regina, Canada)

152

An investigation into the acceptance of mobile banking in India RajanYadav (Inderprastha Engineering College, Ghaziabad, India), Said Gattoufi, Sujeet Sharma (Sultan Qaboos University, Oman), Jyoti Kumar Chandel (Waljat College of Applied Sciences, Oman)

159

Securing Wireless LAN 802.11: A three tier protection approach Maitham H. Al Lawati, Saqib Ali and Syed J. Naqvi (Sultan Qaboos University, Oman)

SQU Future: From E-Learning to M-Learning Application Development

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167

TABLE OF CONTENTS


Al-Zeidi, A., Al-Kindi, K., Al-Khanjari, Z. A (Sultan Qaboos University, Oman)

173

Short papers A pervasive model for unifying and accessing XML-associated documents in a Web-enabled business environment Charles Robert (University of Ibadan, Nigeria)

179

The Effectiveness and Efficiency of E-Learning Tools (Case Study: CAS-Sohar) Bechir Gattoufi (College of Applied Sciences, Sohar, Oman)

182

Omani E-Government Innovative Trends Sadiq Al-Baghdady (Ibri College of Applied Science, Oman)

185

Routing Optimization for 4-G Device Performance on Ad-hoc Network Raja Waseem Anwar (Arab Open University, Oman)

188

Development of Bluetooth Personal Information Exchange Application Mauth Al Hashli, Salim Fadhil, Al Ajmi, M, Al-Khanjari, Z. (Sultan Qaboos Universit, Omany)

191

On the Convergence of Higher Education, Entrepreneurship, and Open Source Tools Abid Abdelouahab (Tenaga National University, Malaysia), Bechir Gattoufi (College of Applied Sciences, Oman), Ali H. Al-Badi (Sultan Qaboos University, Oman)

195

How To Learn And Simulate UniversalProduct Code – An Information Redundancy Technique Afaq Ahmad (Sultan Qaboos University, Oman)

200

Non-Technical Issues in the Adoption of Electronic Health Records by Doctors in Oman Abeer Al-Sulaima, Muna Salim Al Marhrouqi, Hafedh Al-Shihi, (Sultan Qaboos University, Oman)

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204

TABLE OF CONTENTS


The Uptake of Voting Participation in Oman through E-Voting Munira Al-Siyabi, Noora Al-Jabri, Hafedh Al-Shihi (Sultan Qaboos University, Oman)

208

Differentiated eLearning: the possible approaches Virendra Gawande (Sur College of Applied Sciences, Oman)

212

Predicting Consumer Buying Behavior Pattern using Classification Technique Boumedyen Shannaq, Kaneez Fatima Sadriwala (University of Nizwa, Oman)

215

Author Index Index

223

vi

PREFACE


Preface The International Information Systems conference (iiSC) was organized by Information Systems Department of the College of Commerce and Economics at Sultan Qaboos University during Oct 11-12, 2011. The conference proceedings contain the written version of all the contributions presented during the conference. The conference theme was Information Systems for sustainable business environment. The conference provided a forum for discussing current and future issues and challenges as well as recent developments in a wide variety of areas of Information Systems/Information technologies. More than thirty papers were presented in the following tracks: • • • • • •

Trends in Information Systems E-commerce and E-business Challenges Knowledge Management and IS industrial applications Trends in Web technologies IS Security and Mobile Computing E-Government issues and solutions

The International Information Systems Conference (iiSC) features six key note speakers and one talk on industrial applications including: • • • • • • •

Dr. Janice Sipior, Professor of Management Information Systems, Villanova University, Pennsylvania, USA Dr. Patrick, Brézillon, Professor and Researcher, National Center for the Scientific Research (CNRS), Paris, France Dr. Ray Hackney, Professor, Business Systems, Brunel University, UK Dr. Khaled Ghedira, Professor, University of Tunis Dr. Salim Al-Ruzaiqi, CEO, ITA, Oman Dr. Amer Al-Rawas, CEO, Omantel, Oman Mr. Martin Farhan, Petroleum Development Oman LLC (PDO), Oman

We would like to thank the authors, reviewers, presenters, participants, key note speakers, session chairs, organizing committee members, volunteers, sponsors, students, and all the people who contributed to the success of this conference. We would like to thank Dr. Ali Al-Bemani, Vice Chancellor of Sultan Qaboos University, Dr. Amer AlRawas, Deputy Vice Chancellor, Postgraduate Studies and Research and Dr. Fahim Al-Marhubi, Dean of the College of Commerce and Economics, and sponsors for their generous support. Our special thanks go to Dr. Saqib Ali, Dr. Taisira Al-Belushi, Dr. Hafedh Al-Shihi, Dr. Ali Al-Badi, Dr. Syed Naqvi, Dr. Kamla AlBusaidi, Dr. Khamis Al-Gharbi, Dr. Yousuf Al-Hinai, Dr. Jamil Al-Shaqsi, Mr. Mohammed Al-Fairuz, Mr. Zahran Al-Salti, Mr. Nabil Al-Belushi, Mr. Khalfan Al-Touqi, Ms. Claudia Röthke and Mr. Abdul Rahman for their devoted efforts and support in the overall organization of the conference. Dr. Rafi Ashrafi Conference chair iiSC 2011

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iiSC 2011 ORGANIZATION


iiSC 2011 Organization Organizing Committee Chair Dr. Rafi Ashrafi Program Committee Chair Dr. Hafedh Al-Shihi Co-chair Dr. Taisira Al Belushi and Dr. Saqib Ali Publicity Committee Chair Dr. Taisira Al-Belushi Co-chair Dr. Shahid Mahmoud A Balushi Technical Committee Chair Dr. Saqib Ali Co-chair Dr. Ali Al-Badi Scientific Committee Chair Dr. Ali Al-Badi Co-chair Dr. Syed Jafar Naqvi and Dr. Kamla Al-Busaidi Members • • • • • • • • • • • • • • • • •

Dr. Stephen Burgess Dr. Kevin Grant Prof. Ray Hackney Dr. Ali Medabesh Dr. Lazhar Khriji Dr. Sajjad Mahmood Dr. Noor Hazarina Hashim Dr. Bengisu Tulu Dr. Majed Alshamari Dr. Ali Al-Musawi Dr. Khalid Day Dr. Amar Oukil Dr. Zuhoor Al-Khanjari Dr. Abderezak Touzene Dr. Abdullah Al-Hamdani Dr. Said Gattouffi Dr. Rafi Ashrafi

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iiSC 2011 ORGANIZATION • • • • • • •


Dr. Saqib Ali Dr. Hafedh Al-shihi Dr. Khamis Al-Gharbi Dr. Taisira Al-Belushi Dr. Jamil Al-Shaqsi Dr. Yousuf Al-Hinai Mr. Mohammed Al-Fairuz

International Committee • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • •

Prof. Ray Hackney, Brunel University, UK Prof. Sabah Mohammed Lakehead University, Canada Prof. Michael McGrath, Victoria University, Australia Prof. Wendy Currie, University of Warwick, UK Prof. Lorne Olfman, Claremont Graduate University, USA Prof. Mohini Singh, RMIT University, Australia Prof. Abdul Sattar, Griffith University, Australia Prof. Imtiaz Ahmed, East Michigan University, USA Prof. Jinan Faidi, Lakehead University, Canada Prof. Jamie Murphy, University of Western Australia, Australia Prof. Adil Al-Adwani, Kuwaiti University, Kuwait Prof. Aslam Noor, COMSATS Institute of Information Technology, Pakistan Prof. Ashraf Elnagar, University of Sharjah, UAE Dr. Stephen King, Leeds University, UK Dr. Pam Mayhew, University of East Aglia, UK Dr. Torab Torabi, La Trobe University, Melbourne, Australia Dr. Vishanth Weerakkody, Brunel University, UK Dr. Wafi Al-Karaghouli, Brunel University, UK Dr. Kevin Grant, Glasgow Caledonian University, UK Dr. Stephen Burgess, Victoria University, Australia Dr. Arthur Tatnall, Victoria University, Australia Dr. Ali Medabesh, Jazan University, Saudi Arabia Dr. Bengisu Tulu, Worcester Polytechnic Institute, USA Dr. Farookh Khadeer Hussain, Curtin University of Technology, Australia Dr. Kasper Løvborg Jensen, Aalborg University, Denmark Dr. Karen V. Renaud University of Glasgow, UK Dr. Kevin Desouza, University of Washington Seattle, USA Dr. Mehul Bhatt, Universitate Bremen, Germany Dr. Ali Al-Kinani, King Saud bin Abdulaziz University for Health Sciences, Saudi Arabia Dr. Ali Zolait, University of Bahrain Dr. Majed Al-Mashari, King Saud University, Saudi Arabia Dr. Mazin Ali, University of Bahrain Dr. Noor Hazarina Hashim, Universiti Teknologi, Malaysia Dr. Sajjad Mahmood, King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia

Support staff: • • •

Mr. Nabil Mahmoud Al Balushi Mr. Abdul Rahman Al Huthili Mr. Ishaq Humaid Al Qassabi

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iiSC 2011 ORGANIZATION • • • • • •


Mr. Khalfan Saif Al-Touqi Miss. Maya Mohammed Al Azri Ms. Ebtihal Bader Abdullah Almahremi Miss. Claudia Röthke Mr. Muneer Masuod Al Sulimi Mr. Idris Ibrahim Al Hooti

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KEYNOTES


Keynotes Presenter: Professor Janice C. Sipior Affiliation: Professor of Management Information Systems, Villanova University, Pennsylvania, USA Topic: Organizational Issues of Internet Privacy

Presenter: Professor Patrick Brezillon Affiliation: Professor and Researcher, National Center for the Scientific Research (CNRS), Paris, France Topic: Dealing with practices in business when no procedures exist: a context-oriented approach

Presenter: Professor Khaled Ghedira Affiliation: Professor, University of Tunis, Tunis Topic: Foundations of CSP techniques

Presenter: Professor Raymond A Hackney Affiliation: Professor, Business Systems, Brunel University, UK Topic: Publishing in High Level Information Systems Journals

Presenter: Dr. Salim Al Ruzaiqi Affiliation: CEO, Information Technology Authority, Sultanate of Oman Topic: E-Government in Oman Lessons Learned and Challenges

Presenter: Dr. Amer Awadh Al Rawas Affiliation: CEO, Omantel, Oman Topic: ICT Infrastructure in Oman: The Strategic view

Presenter: Mr. Martin Farhan Affiliation: Petroleum Development Oman LLC (PDO), Oman Topic: Implementing a robust information management strategy

xi

PROCEEDINGS


Proceedings

1

TRENDS IN INFORMATION SYSTEMS


Trends in Information Systems

2



How IT will challenge existing organizational forms and create Ambient organizations Niels Bjørn-Andersen Copenhagen Business School Department of IT Management Howitzvej 60, 2000 Frederiksberg Denmark +45 38 15 44 44 wireless

[email protected]

transaction costs,

ABSTRACT 1

IT is likely to be as important to the way companies will organize in the future as electricity was to the industrial revolution. IT will revolutionize entire industries and markets. IT will create new types of organizations that will surpass and outsmart traditional organizations. This has been predicted for more than a decade. But now it is happening especially in the music, newspaper and publishing industries, and shall see it even more pronounced in these sectors in the future. But it will not be limited to these industries; it will influence all types of industry and government organizations.

1. INTRODUCTION Since the early introduction of IT into organizations, practitioners and researchers have been intrigued by the issues about the impact of IT on individuals and organizations [14, 23, 26]. The tremendous and on most dimensions accelerating advances in the technology over the last 50 years has not decreased this interest in how this technology is contributing to changes in individuals roles, organizational structures/processes, and industry structures. The more extensive discussions of the impact of IT continued over the years [3, 18, 25]. A significant contribution was made by [7], when they proposed nine IT capabilities as shown in table 1s, which they believed would have significant impact.

Already today, we see many examples of innovative organizational designs, enhancing organizational effectiveness and competitiveness. The paper will briefly discuss the potential of future IT developments, and will proceed to give a short theoretical background for why we see a growth in IT-facilitated new organizational forms. A couple of interesting organizational design will be mentioned, before we proceed to making the argument that any business process in principle may be reengineered, centralized or outsourced in one way or other. Interesting examples will be presented.

Table 1 IT Capabilities and their organizational impact (Davenport & Short, 1990)

We suggest that future IT will have such a profound impact on organizational structure going far beyond the traditional ‘virtual organization’ that it calls for a new organizational concept, which we have chosen to label the “Ambient Organization’.

Capability

Organizational impact/Benefit

Transactional

IT can transform unstructured processes into routinized transactions

Geographical

IT can transfer information across distances making processes independent of geography

Automational

IT can replace or reduce human labor

Analytical

IT can bring to bear complex and analytical methods on a process

Categories and Subject Descriptors

Informational

K.4.3 Organizational Impacts, dealing especially with impact of IT on organizational structures.

IT can bring vast amounts of detailed information into a process

Sequential

IT can enable ….. multiple tasks to be carried out simultaneously

Knowledge

IT allows the capture and dissemination of knowledge ... to improve the process

General Terms Management

Management

Keywords Impact, business processes, industry structure, organization, IT, Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission from iiSC. iiSC’11, October 11–12, 2011, Muscat, Sultanate of Oman. Copyright 2011 iiSC ISBN: 978-9948-16-253-7 1

Tracking

IT allows the detailed tracking of task status, inputs and outputs

Dissemination

IT can directly connect two parties that would otherwise communicate through an intermediary

Although the language seems dated today, it is clear that we have experienced all of the above, and more is likely to come.

IT is defined broadly as covering all types of IT and telecommunication technologies including application software.

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In the early 90s, we saw the emergence of a substantial body of research suggesting that IT would lead to new organizational forms, and concepts like, ‘Shamrock’ [13], ‘Boundary-less organization’ (General Electric), and ‘Spaghetti organization’ [5] were proposed.

If we consider these cost types, it is clear that over time, all of these (perhaps with the exception of the two latter ones) have decreased both in the hierarchy and in the market, but they have decreased much more dramatically in market forms or organization. Today and even more in the coming decade, the transaction costs for procuring from the market are going to approach the costs of procuring from own hierarchy. And since the production costs by definition are going to be lower in the market (choosing the most effective supplier) than in one’s own organization, we are going to see a strong tendency towards outsourcing or other sorts of arrangements, where one is not producing in a traditional hierarchy. As Ronald Coase puts it [6], “Costs of a formal contract/hierarchy are lower for frequent transaction than in the market. That is why firms exist”. But to phrase it differently, if transaction costs of frequent transactions in the market drop substantially, firms will not exist according to Coase. In other words, we will see the emergence of new organizational forms that we have chosen to call “Ambient Organizations”.

But in the mid 90’ies, the concept of “virtual organizations” gained a substantial rallying and became the most used concept [9, 13, 20, 21, 27], and many organizations as well as researchers followed the line of outsourcing of those company functions, which were not core. The main theoretical reason is that since transaction costs involved in outsourcing have dropped and will continue to drop, it will become much more advantageous to concentrate on core and source everything else from organizations offering “best-of-breed” at competitive conditions. In order to analyze this, we shall first briefly discuss the main theoretical background why we see the substantial and growing trend towards different types of sourcing and outsourcing arrangements, in other words the Transaction costs economics. Following that, we shall briefly remind ourselves about the significant developments within IT that we have experienced over the last decade, and have a look at what is in stall for the next decade. We will mention the basic technologies and move on to some of those specialized companies now providing (software and organizational) platforms for the future growth in sourcing and outsourcing arrangements. Following that, we shall a more detailed analysis of company functions using a well-known framework of value chain [24]. In this analysis we shall show that all traditional company functions including innovation, which one might argue is not part of the Value Chain, can be outsourced, and that this is very likely to happen due to the substantial drop in transaction costs related to having (part of) the business processes carried out by somebody else. In transaction cost terms, we are likely to see a much more widespread development towards sourcing from the market rather than from own hierarchy. We shall conclude with a section on the new organizational form called an ‘Ambient organization’, which is likely to emerge, when a much more substantial part of the traditional business processes are sourced from somebody else.

Since the analyses related to virtual organizations in the early 90s, we have seen a very substantial development in IT with the invention and use of Internet, World Wide Web, social media and the different types of ambient intelligence technologies. This is not just more of the same; it is a qualitatively different type of technology, which justifies the use of another concept than “virtual organization”. In the words of one of pioneers within Web 1.0 and Web 2.0: The Internet (and other knowledge mobilization technologies) offers an alternative to hierarchy and market: open collaboration with no or minimal investment costs for the relation [2]. The idea of outsourcing started in the late 80s, but today we see how new types of sourcing are taking place from creation of shared service centers over outsourcing to cloud sourcing and even crowdsourcing of everything from sourcing of a product/service to the much more complex phenomenon of “Business Process Outsourcing BPO”. Analyzing the phenomenon of moving away from the traditional hierarchy, we find the following types of buying arrangements for products/services/business processes:

2. Theoretical background Transaction costs economics [6] are one of the important theoretical reasons for why we are going to see new ways of organizing. The original idea is simple. The acquisition of a product or a service can be said to consist of two elements, production costs and transaction cost, and for the sake of simplicity, let’s just consider two ideal types of sourcing forms, either sourcing from the hierarchy (make yourself) or sourcing from the market (buy). Typical transaction costs are •

searching cost to find who can deliver

•

transportation costs to where it is to be used

•

inventory holding costs in case of fluctuations in supply

•

communication costs

•

coordination costs between two independent companies

•

quality assurance costs

•

costs of writing contracts with somebody in market

•

costs of enforcing contracts with somebody in market

•

Shared service center as cost center between SBU’s but owned by organization

•

Profit center, still owned by mother company

•

Outsourcing on-shore, near-shore or off-shore

•

Cloud computing where location of process is not knows to outsourcer

•

Crowdsourcing, where sourcing is done from an initially unknown provider, who is typically rewarded on delivery

In coming to an end of this short theoretical section, we shall in passing point out that there are obvious constraints on the extent which one can procure from outside. These can be explained among others with reference to Agency Theory [11]. The lower transaction costs associated with procuring from others has to be balanced against the agency costs of having others than the principal carry out the business process. However, using their model, we are in no doubt that the overall picture is onedirectional: We shall see a strong increase in outsourcing types.

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iiSC2011 Proceedings available to ‘all of us’ in 2020. This means that individuals will be surrounded by ambient technologies providing ambient intelligence. This development will allow us ‘endless’ possibilities for searching, storing, analyzing, structuring, reproducing and disseminating information in form of figures, text, graphs, sound, and video to anybody anywhere. More important, it will allow us to collaborate with others in new ways, which are likely to be much more effective

3. Future IT development There is little doubt that we have seen tremendous growth in IT since [7] made their predictions. Most significantly, the advances in processor speed, in storage density and in telecommunication speed, which have resulted in an avalanche of different applications, especially within the area of Internet, World Wide Web, e-commerce and e-business. It seems a fair prediction that within a decade we as individuals shall have for our discretionary use 1.

Unlimited processing capacity on our desktop or wireless device

2.

Unlimited storage for whatever we would like to store

3.

Unlimited communication possibility broadcasting in high resolution or 3D

for

The ISTAG committee falls short of discussing any implications above the level of the individual level and the individual in society. Specifically it does not discuss implications for organizations and industry structures, a shortcoming that we shall address here, because we believe that this will have enormous implications, since all (business) processes will potentially be impacted and radically change the way organizations and industry structures will evolve.

video

This does not mean that organizations will not perceive IT bottlenecks, but for the individual pursuing his/her individual tasks, the technology will be available anywhere in whatever form and shape one might wish.

Accordingly, in the following we shall attempt to develop scenarios for what visions for future IT will mean for the way in which companies will chose to organize in the future. We shall define this future organizational model as an “Ambient Organization” indicating that the organization is present ‘everywhere’ and sourcing its resources/capabilities in the shape and form of skills, processes and technologies from ‘everywhere’, notably from other organizations, which are not owned or controlled by them.

In 2000, the EU-commission published a study on the impact of future IT, as part of the Information Society Technology research program (6th research framework program 2002 – 2006) of the EU. In this program the extensive miniaturization, proliferation and distribution of IT was named “Ambient intelligence”. Xerox first named this development as “Ubiquitous computing”, while IBM decided to name it “Pervasive computing”. An issue of CACM was devoted to discuss these two concepts [19].

4. Organizational platform providers The new organizational forms that we shall discuss below are to a very large extent enabled by different types of intermediaries providing IT-based organizational platforms that bring down transaction costs for anybody, who would like to source from 3rd party.

In the 6th Research framework program of the EU it was suggested not to use any of these two US terms, but to use the concept of ambient intelligence for the phenomenon that the computational power is available everywhere. In the report ISTAG Scenarios for Ambient Intelligence 2010 (ISTAG 2001), the concept of Ambient Intelligence is discussed, and scenarios for how this might provide “greater user-friendliness, more efficient services support, user-empowerment, and support for human interactions” are developed. These scenarios describe a future “where people are surrounded by intelligent intuitive interfaces that are embedded in all kind of objects and an environment that is capable of recognizing and responding to the presence of different individuals in a seamless, unobtrusive and often invisible way”.

These intermediaries are the traditional information technology platform providers (Intel, Cisco, Microsoft etc.), but we are also witnessing new entrants like Amazon, who is providing cloud computing in competition with traditional facilities management companies like Microsoft, IBM, Cap Gemini and CSC. In the early days of the dot.com age in the late 90’s we saw a steep growth in so-called marketplaces. Gartner Group even predicted in 2000 that the number would exceed 10.000 by the end of the decade. An overwhelming part of these originally marketplaces, however, have disappeared, because the liquidity simply was not there and did not come. Sellers could not figure out how to avoid a perfect price competition eroding profits for everybody, and the seller often won the contract with a loss giving deal. Buyers were skeptical about quality and reliability of supplied goods/services, and the marketplace itself had a hard time in figuring out a business model that would make buyers and sellers come back, and not trade outside the marketplace.

A more extensive definition of ambient intelligence is found in Wikipedia stating that Ambient Intelligence becomes a reality when we have: • •

• •

•

Unobtrusive hardware (miniaturization, nanotechnology, smart devices, sensors etc.) A seamless mobile/fixed web-based communication infrastructure (interoperability, wired and wireless networks etc.) Dynamic and massively distributed device networks Natural feeling human interfaces (intelligent agents, multi-modal interfaces, models of context awareness etc.) Dependability and security (self-testing and selfrepairing software, privacy ensuring technology etc.)

Today the much fewer market places have matured. For example in the Nordic countries, the company “Gatetrade” (www.Gatetrade.com) was one of the first marketplaces established on the Oracle platform in 2000. After some very turbulent years and several financial reconstructions, the company is now providing procurement solutions to a wide range of public and private companies. However, this success is dwarfed by the Chinese B2B marketplace Alibaba.com. Started in 2003, the now 12.000 employee large company is boosting that at any point in time

Even though in 2011 this is only a reality for a very small elite group or for limited purposes, we shall argue that it will surely be

5



24/7, they have about 6 million transactions between buyers and sellers taking place simultaneously. For an annual fee of $ 300 for Chinese companies and $ 4000 for non-Chinese companies, one might trade as often and as many as one pleases. One might say that Alibaba is to a very high degree enabling China becoming the manufacturing center of the world. But Alibaba is not just connecting buyers and sellers, they are also like Gaterade providing or organizing a number of services facilitating trade like credit rating, logistics and procurement. They do charge for their services, but the amounts are typically trivial for the acquirer of the service, but if there are millions of buyers of a service, the investment and the level of automation of the service can be extremely high and still yield very attractive rents to Alibaba. While the two examples above supports “all” aspects of trading, we have also seen a growth in platforms for supporting innovation to be outsourced to third party using cloud sourcing and crowdsourcing.

Figure 1. The Generic Value Chain, Porter (1995) We acknowledge the fact that most observers and practitioners today do not think in terms of company functions but business processes. However, we believe that the underlying arguments apply both to functions and to processes, and we find it is easier to explain using the very widely acknowledged model from Porter.

On the research front, Albert Angern and his group at INSEAD has developed and is offering the Inno Tube platform with more than twenty tools for supporting the sourcing of innovation from others. More mainstream is the so-called “Mechanical Turk” provided by Amazon since 2005. The Mechanical Turk is designed to enable crowdsourcing by providing a marketplace for exchange of ideas and as one of its web-services on EC2. The Requester place a Human Intelligence Task (HIT) on the site with the use of an API. Workers can browse the HIT’s to find interesting tasks worthy of their energy and solve the tasks. It is even possible for the Requester to demand particular qualifications of workers. Payment will typically accrue as gift certificates for buying on Amazon or workers can receive money via Paypal. This can be used for many purposes.

In this section we shall discuss and present examples of how primary activities, support activities and innovation activities can all be procured from the market. One might even argue that Porter has not included innovation in his Value Chain, or given it a fairly small place as one of the support activities, but the importance of innovation today, we have decided to include it in our analysis on the same level as the primary and support activities. Our intention is to document that all of these activities to an increasing degree are being sourced from the market. We shall structure this discussion based on table 1. In this table we have shown the five main types of sourcing arrangements in the first column and the three types of activities cross the three following columns. For each of the activities, we shall provide examples of

A third example of support of innovation is “Innocentive”, a platform supporting open innovation. Here companies or organizations can crowd source ideas helpful in their innovation process. InnoCentive Challenges gives users access to a Web community of 200,000 experts, which might help companies achieve innovative business results. It also provides the ONRAMP (Open iNnovation Rapid Adoption Methods and Practices), which is a suite of training and implementation services designed to help companies adopt open innovation rapidly and successfully within their organizations.

Table 1. Examples of sourcing from the market Functions

Type of sourcing Own shared (service) center

What we have tried to show here is that the foundational provision of net IT of “unlimited” processing, storing and communication capacities, enabling support of any type of sourcing arrangement, from down to earth simple services to the complex innovation services. We shall now proceed to give a few examples of companies using this opportunities to develop new organizational forms that we have chosen to name “Ambient organizations”.

Standard practice

Proctor & Gamble

Xerox Park

Outsource/

Bestseller or VW auto

Unilever

Bang & Olufsen

Diagnose scans/x-ray in Second Life

IT services to India

Lego

Salesforce.co m

Prediction markets

Crowdsourci ng

eConomic

Intelligence Agency

6

Innovation activity e.g. Basic and applied research

Standard practice

Cloud sourcing

In order to investigate the feasibility and proliferation of sourcing from others, we have chosen the probably most well-known model for organizational functions, the Value chain model by Michel Porter [24]. The Value Chain model does not require further introduction, but it is a rather “complete” description of activities of an organization and accordingly, suitable for our purpose. The Value Chair is for reference provided below in figure 1.

Standard practice

Support activity e.g. Procurement, accounting, HR and IT Carlsberg

Own profit center Off-shore

5. Key examples of sourcing from others

Primary activity, e.g. Produce, sell and service

Andiamo



how large companies are ‘deconstructing’ the traditional organizational hierarchy and is sourcing hitherto typical in-house activities (functions or business processes) from third party specialists within these areas. We do that in the following three sub-sections, but will refrain from commenting on the cells in the table called ‘Standard practices’, which we have named like that to indicate that this type of centralization of functions from SBU’s or Lines of Business (LoB) is now so common place that there is no need to point to any specific companies.

This may seem like a small step, but considering that the group consist of more than 50 previously independent breweries with each their brand, production, local market and own administration, this was hardly easy to do, but has had a huge potential scale advantage.

5.1 Primary activities

But both these two re-organizational efforts are taking place within the same multinational organization. Unilever has taken the reorganization to a higher level, and has outsourced its HR function with all its business processes to Accenture. In a spectacular “throw it over the fence” or “lift and shift” approach, all of HR has been contracted to Accenture “due to mega cultural and technical barriers involved in handling it themselves”.

Along a similar vein, Proctor & Gamble has established a global shared service unit taking care finance, accounting, HR and IT in order to reap the economics of scale and achieve higher effectiveness.

Looking at the five primary activities, there are plenty of examples of how organizations source their inbound logistics. The Danish company ‘Bestseller ‘is in the clothing fashion business. Design is done in the head office in Denmark, and all production is taking place in China. What is more interesting is that all inbound logistics is outsourced to a logistic provider called PrimeCargo, who is taking care of all logistics from manufactures in China to their own warehouse in Denmark, from where they distribute the finished goods to retailers around in Europe. Although PrimeCargo will also supply e-commerce sales of Bestseller goods, the actual web-shop is outsourced to a company called Bootz located in Sweden.

When it comes to cloud sourcing, this is of course a very wellknown phenomenon within IT, and we are so far just at the beginning of cloud sourcing, getting services like operations centers, infrastructure, network an applications in ASP solutions and SaaS. Traditional IT vendors like Microsoft are offering cloud sourcing of IT services on their Azure platform, and new players like Amazon is entering what looks like an almost blue ocean market. An interesting example of a very successful is the Danish company eConomic, who is offering accounting services and basic support of business processes like any ERP-system for SME’s would do. eConomic now approximately 40.000 customers paying from € 25/month, and it is noteworthy that the start-up costs are typically a fraction of the implementation costs of acquiring and implementing a small ERP-package. Almost everybody from Microsoft to Gartner and IDC agrees that there is a huge market in the provision of cloud sourcing IT services, and indeed Microsoft Dynamics, which is now the third largest provider of ERP-services is driving the provision of cloud services very hard.

Operations or manufacturing is also being outsourced left, right and center to relatively low labor cost regions especially in Asia, and China is becoming the manufacturing engine of the world. But BPO can also take place inside a fully owned manufacturing plant. In a spectacular deal, VW has chosen DHL for its internal supply chain handling of in-plant logistics in Bratislava, Slovakia. No less than 800 DHL employees are now managing 50% of all production material including inbound receiving, put away and storage, picking and kitting, sequencing as well as line-side deliveries directly to the Volkswagen production lines. “Logistics are essential in vehicle manufacturing. DHL has convinced us due to its innovative concepts they can provide a supply chain solution tailored exactly to our needs,” Juraj Janá, Head of Logistics with Volkswagen in Bratislava.

Another interesting example of cloud computing was reported by a research team from HP utilizing the Mechanical Turk from Amazon. They collected tweets about 24 films in the week prior to the film opening on a Friday night. Based on this, they developed a prediction model. This was later tested on two films. For these two films they collected 15.000 tweets from Twitter. They had a Sentiment analysis of the tweets done using Mechanical Turk. They got 3000 workers to classify the tweets into positive, neutral or negative about the film, and had each tweet analyzed by three workers, eliminating assessments by workers which were not consistent or who were clearly outliers. The amazing result was that they were able to predict with 5% accuracy the number of tickets sold in the box office in the first week after opening. When one takes into account that the tweets were all from the week prior to the opening and that very few of the people sending the tweets had read any reviews in traditional media, this is going a long way towards documenting the “wisdom of the crowd” as opposed to experts (filmmakers, reviewers, journalists), who would not be able to get anywhere near such accuracy in the prediction.

Other interesting examples of sourcing of primary activities are the cloud sourcing of the examination of different types of scanned pictures in hospitals. Hospitals especially in the US have found that it is much more advantageous to source highly skilled doctors from Second Life than to attempt to hire the same doctors from ‘wherever’ in the world they might live (e.g. India) and bring them on-shore. Finally among the primary activities, we might mention that “Salesforce.com” is offering a state off the art CRM-system off the shelf as a SaaS solution. But it is also interesting that Salesforce.com themselves are crowdsourcing service help as well as ideas for further development of their successful CRM package from “anybody” who signs up of their web-site. In this way they can source help, service and info about new requirements in a much more efficient way than traditional competitors. Furthermore, they can rely on a large community of users to assist each-other in solving problems.

5.2 Support activities

Another more sinister example could be Intelligence agencies, which have difficulties identifying individuals in protesting crowds putting up photographs of the protesters and source suggestions from the crowd as to the identity of the protesters.

There are many examples of large companies going through major transformations of their support activities. The Carlsberg beer group with production and sales in more than one country around the world has decided to centralize their accounting in Poland.

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iiSC2011 Proceedings organizations, who are already sourcing key and some would even say core business processes from outside. This is happening due to the dramatic fall in transaction costs when sourcing from the outside.

5.3 Innovation activities There seems little doubt that innovation is one of the most important business activities, and something that most companies find absolutely critical for long term survival. And many might raise the question whether it is possible or advisable to outsource something so close to core business like outsourcing. We shall provide a couple of examples of how that is happening.

We have developed a short classification of different types of outsourcing arrangements, from shared service centers to crowdsourcing, and we suggest that in principle it is possible to outsource or source practically all types of business processes whether it is production, marketing or innovation from the outside

Many different models have been tried out in practice, and having own R&D departments is of course a common practice. Some companies like Xerox have established a separate research center like Xerox Park, but it is probably fair to say that they have not been too successful in transferring inventions from Xerox Park into innovations in the main company.

If this is the case, we are just at the beginning of the emergence of a new type of organizations that we have proposed to call Ambient Organizations. We have chosen the concept “Ambient” to illustrate that any modern organization needs to be present everywhere, whether it needs procuring of the best raw material, recruiting of the best employees, manufacturing in the most optimal place, marketing via social networks, selling in a range of different markets, servicing for a wide variety of customers, and last but certainly not least innovating with customers and different partners.

The up-scale Hi Fi producer Bang & Olufsen has for many years been a leader in design of Hi Fi equipment based on what is Scandinavian Design. And for many years, the head designer was the Dane Jacob Jensen. However, in recent years, the very exclusive Scandinavian design is actually done by a designer in Palo Alto in California. Bang & Olufsen has outsourced the key core business of Scandinavian design to a US designer.

The Ambient Organization is proposed as a metaphor for organizations utilizing emerging Ambient Intelligence Technologies, and is exploiting virtual resources on a business process level as well as on an individual level. It will in this way redefines/reinvents its organizational structures and its business models through building strongly on contractual and even noncontractual short term relationships (outsourcing, crowdsourcing) in order to deliver enhanced customer value for meeting increasingly complex and ever more competitive and dynamic environments.

Another example is the large pharmaceutical company Lilly, which is using Innocentive actively to achieve crowd sourcing of ideas for innovation. Finally, when it comes to cloud sourcing of ideas, the toy manufacturer Lego originally launched its Mindstorms product in 1998, which is basically a programmable robot. Uses are encouraged to build their own robots and program them to carry out particular tasks. What Lego found in the late 90’s was that users were breaking the code to achieve new functionalities. After the initial dismay, Lego has now embraced users having such wishes, and over the last 12 years, Lego is drawing in subsets of users in developing new robots and toys e.g. in the web-product “Design by me”. In particular Lego has been successful in Japan, where they get a large amount of submissions for new Lego-sets using the new Lego CUUSOO platform. They then do competitions, and if a set gets more than 1000 votes, it goes almost directly into production.

For us as managers and/or researchers, the Ambient Organization will require a totally new set of skills and capabilities in managing and leading growth in the 21st century. This is our challenge.

7. References [1] Airaghi, Angelo, Schuurmans, Martin: ISTAG Scenarios for Ambient Intelligence in 2010, European Commission Community Research 2001

6. Ambient Organization

[2] Benkler, Y. (2006). The Wealth of Networks. Yale University Press

Over the last almost 200 years we have seen the emergence of large hierarchical organizations, mainly based upon the fact that it was an advantage to make one self in the hierarchy rather than buy in the marketplace. The tools and capabilities for coordinating and managing were far superior inside the organization than trying to coordinate and manage with many partners and suppliers in the market.

[3] Bjørn-Andersen, N, Hedberg, B., Mercer, D., Munford, E. & Solé, A.: The Impact of Systems Change in Organisations, Sijthoff & Noordhoff, Alphen aan den Rijn, The Netherlands, 1979 [4] Bjørn-Andersen, N., Eason, K., and Robey, D. Managing Computer Impact: An International Study of Management and Organizations. Norwood, NJ: Ablex Publishing Corp., 1986.

However, the IT developments within almost all areas of business are creating a large number of opportunities for different ways of organizing. We have shown that in a matter of very few years, we shall have unlimited processing capacity, unlimited storage and unlimited communication capabilities available at our fingertips or even available for oral commands. This will dramatically reduce transaction costs of sourcing from the market rather than from one’s own hierarchy, which as Coase [6] originally pointed out, will always be producing at higher costs than the best in the market. In other words, it will be an advantage to source from the “best” in market rather than produce oneself.

[5] Bjørn-Andersen & Turner J.: The Metamorphosis of Oticon, in Galliers. B. & Baets W. (eds.): Information Technology and Organizational Transformation, 1998 [6] Coase, R.: 'The Nature of the Firm' (1937) 4(16) Economica 386–405 [7] Davenport, and Short "The New Industrial Engineering: Information Technology and Business Process Re-design," Sloan Management Review), 1990,

We have then taken one of the most popular models of organizations, that of the value chain of [24], and we have attempted to illustrate that there are today a large number of

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iiSC2011 Proceedings [19] Lyytinen, K. & Yoo, Y.: Issues and challenges in ubiquitous computing, CAM, vol 45, no 12, pp 63-65

[8] De Witt, B., Meyer, R.: ”Strategy, Process, Content, Context – An International Perspective”, Thomson, 3rd Edition, 2004 p. 375-401

[20] Malone, T. & Laubacher R.J.: The Dawn of the E-lance Economy, HBR, September-October, 1998, p 145 - 156

[9] Dubinskas, F. A.: Virtual organizations: Computer Conferencing and Organizational Design, Journal of Organizational Computing & Electronic Commerce, vol. 3, issue 4, 1993

[21] Mandy, C.: Trust and the Virtual Organization, HBR, MayJune 1995, product number 4363

[10] Elliot, S.: Technology enabled innovation, industry transformation and the emergence of ambient organizations, working paper, University of Sydney, 2005

[22] Markus, Lynne. M. & Robey, D.: “Information Technology and Organizational Change: Causal Structure in Theory and Research” Management Science, Vol. 34, No. 5. May 1988, pp. 583-598

[11] Gurbaxani, V. and Whang, S. The impact of information systems on organizations and markets. Commications of the ACM 34, 1 (1991), 59–73.

[23] Mumford, E & Banks, O.: The Computer and the Clerk, Routledge and Kegan Paul, 1967 [24] Porter, M. Competitive Advantage: Creating and Sustaining Superior Performance (1985)

[12] Gore, B.: One Pioneer, 1985, see http://www.context.org /ICLIB/IC11/WholePer.htm

[25] Robey, D. "Computers and Management Structure: Some Empirical Findings Re-examined," Human Relations, 30 (11), November 1977, 963-976.

[13] Handy, C: The Age of Unreason, Drake International, 1989 [14] Hoos, Ida: Automation in the office, Washington D.C. Public Affairs Press, 1961

[26] Whisler, T.L: The Impact of Computers in Organizations, Praeger, 1970

[15] Häcki, R. & Lighton, J.: “The future of the networked company”, McKinsey, Quarterly no. 3, 2001, p. 20-39

[27] Voss, Hans Werner: Virtual Organizations: The future is now, Strategy and Leadership, July August 1996

[16] Hagel J. & Singer. : Unbundling the organization, 1998 [17] ISTAG: Scenarios for Ambient Intelligence, IST program, www.cordis.lu/ist/istag.htm, 2001 [18] Kling, R. (1980). Social analyses of computing: Theoretical perspectives in recent empirical research. Computing Surveys, 12(1), 61-110.

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Software Solutions Construction: An Approach Based on Information Systems Architecture Principles Sana Guetat

Salem Ben Dhaou Dakhli

Le Mans University Avenue Olivier Messaiean 72000 Le Mans +33-2-43833112

Paris-Dauphine University Place du Maréchal de Lattre de Tassigny 75675 Paris +33-1-48972829

[email protected]

[email protected]

ABSTRACT

1. INTRODUCTION

Information has become an essential resource for the survival and sustainable development of modern organizations, which face the constraints of their unstable and continuously changing economic and technological environments. In order to manage effectively this valuable resource, organizations need Information Systems (IS) which play a critical role in information creation, storage, processing, analysis, and distribution. Moreover, IS help organizations reaching various difficult and often conflicting goals through supporting complex organizational processes. In particular, to support innovation processes and, short time-tomarket constraints, organization’s IS must be agile and flexible. The urbanization of IS may be considered as one of the main solutions proposed by researchers since the late 90’s to help organizations build agile IS. Nevertheless, despite the advantages of this concept, it remains too descriptive and presents many weaknesses. In particular, there is no useful approach dedicated to urbanized IS construction. In this paper, we propose a development approach of software solutions which is compliant with the IS urbanization rules characterized by their main dimensions.

Information Systems (IS) play a critical role in modern organizations. They are nowadays a necessary condition for organizations survival within unstable and continuously changing economic and technological environments. Indeed, organizations need IS which help them reaching various difficult and often conflicting goals. Moreover, to support innovation processes and, short time-to-market constraints, organization’s IS must be agile and flexible. The concept of IS urbanization has been proposed since the late 90’s in order to help organizations building agile IS. Nevertheless, despite the advantages of this concept, it remains too descriptive and presents many weaknesses. In particular, there is no useful approach dedicated to the construction of urbanized IS. In this paper, we propose a framework which improves existing work related to IS urbanization and describe a development approach of software solutions which is compliant with the IS urbanization rules. In this proposed framework, we distinguish two main concepts. On the one hand, we define an application as a standalone set of software artifacts aimed at partially supporting at least one organizational process. On the other hand, a software solution is a set of interrelated models which describe the architecture of an application. Therefore an application results from the implementation of a software solution. Furthermore, we point out that the effective use of the proposed IS urbanization framework - while building software solutions – is based on the definition of a repository containing a set of architecture rules to be respected by software architects and developers. This is why we describe, in this work, the characteristics of IS architecture rules through their main dimensions. Our paper is organized as follows. Section 2 presents the foundations of IS urbanization based on the “city landscape” metaphor. Three sections are dedicated to the dimensions of IS architecture rules. In section 3, we present the spatial dimension. The communication dimension is presented in section 4. Section 5 describes the informational and functional dimensions. In section 6, we present a multi-view model which synthesizes and completes the existing contributions to IS urbanization proposed by academics and practitioners. In section 7, we use the concepts and models described previously to present an approach of software solutions construction. Section 8 concludes this paper by listing the encountered problems and the future research directions.

Categories and Subject Descriptors D.2.1 [Requirements/Specifications]: Methodologies H.1.m [Missellaneous]

General Terms Management, Design, Standardization, Theory

Keywords Information System, software solution, application, urbanization, function, informational entity, process, Target Urbanization Plan.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission from iiSC. iiSC’11, October 11–12, 2011, Muscat, Sultanate of Oman. Copyright 2011 iiSC ISBN: 978-9948-16-253-7

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iiSC2011 Proceedings architecture model presented below. The informational (vs. functional) dimension describes data (vs. functions) manipulated and implemented by an IS application. Moreover, the informational and functional dimensions describe the specific characteristics and the portfolio of the IS applications. The roles played by these two dimensions are complementary with the communication dimension role since the exchanges between IS applications or between the organization IS and external IS and end-users are based on the data manipulated and managed by IS applications and the services they offer. The following sections are dedicated to the presentation of the spatial, informational, functional, and communication dimensions of IS architecture rules.

2. FOUNDATIONS OF INFORMATION SYSTEMS URBANIZATION IS urbanization has been studied by many authors [7] [10] [14]. The contributions of these authors have enriched the existing work related to the enterprise architecture concept [1] [2] [5] [6] [8] [11] [12] [17] [18]. All these authors use metaphors to define the foundations of enterprise architecture and IS urbanization. In particular, the “city planning” or “city landscape” metaphor has been proposed by many authors as a foundation of IS urbanization [4]. Guetat and Dakhli [19] propose the information city framework which generalizes the use of the “city planning” metaphor by stating that – within a modern organization – an information system may be considered as a city where the inhabitants are the applications belonging to this information system. In the information city, the common parts are information shared by all the information system applications while the private parts are composed of software artifacts owned by each application. An application belonging to the information city behaves as a master of its own data and artifacts and as a slave regarding shared information and artifacts. That means that an application can use, update or suppress data and artifacts it owns but can only use a copy of shared information. Information stored in the customers and products databases are examples of shared information. Reusable services, frameworks, models and standards are examples of shared artifacts. Comparing an information system to a city extends the use of the “city landscape” beyond the analogy between software and building construction by emphasizing the problem of information system governance. On the one hand, following the example of a city, the relationships between the applications which populate the information city must be managed. That means that a set of architecture principles and rules has to be specified in order to govern exchanges either between application belonging to an information system or between such applications and the external environment like other information systems or end-users. On the other hand, the vast number of application assets in combination with the natural expansion of the application portfolio as well as the increasing complexity of the overall information system, drive a need for the information system governance. Therefore, the “information city” framework permits defining architecture principles and rules which help organizations prioritize, manage, and measure their information systems. The IS architecture rules and principles have five dimensions: a spatial dimension, a communication dimension, a functional dimension, a dynamic dimension, and an informational dimension. The spatial dimension describes the addresses of applications in the information city: This dimension is associated with two important concepts: the Target Information City Plan (TICP) and the Current Information City Plan (CICP). The communication dimension describes the rules which govern exchanges either between the applications belonging to the organization’s IS or between the organization’s IS and the external Information Systems and end-users. The dynamic dimension plays two roles. On the one hand, it describes the roadmap which permits integrating each legacy IS application in the TICP. The integration of an application in the TICP is based on a CICP analysis which defines an action plan to make this application compliant with the TICP requirements. On the other hand, it provides information needed to design and implement new IS applications. Therefore, this dimension refers to the multi-view IS

3. THE SPATIAL DIMENSION OF ARCHITECTURE RULES Using the “information city” framework makes organizations able to apply a structure for classifying information system applications, functions, or services in a coherent way. It defines responsibility plots from coarse to fine-grained into discrete areas, which together form the complete Target Information City Plan (TICP). Developing the TICP of an organization’s information city is a result of a deep understanding of both the business and IT strategy of this organization. One of the central concepts of the TICP is the desire to eliminate the intricacy of the IT environments through the separation of concerns from the applications. Analysis of the principles behind the organization’s and IT strategies leads to the four following architecture principles which help guide the development of the organization’s information city TICP. •

Architecture principle 1: Determine Front-office vs. Backoffice responsibilities

•

Architecture principle 2: Principle Specialize back-office regarding the organization’s processes

•

Architecture principle 3: Identify the components common to the back-office and the front-office.

•

Architecture principle 4: Separate in the front-office the functions related to management of the communication network from those related to management of the relationships with the organization’s customers and partners.

The first architecture principle - Determine front-office vs. backoffice responsibilities – identifies the responsibilities of the organization’s front-office and back-office. The front-office is dedicated to management of the relationships with the organization’s external environment while the back-office is dedicated to the development of products and services. For instance, within an insurance company the back-office manages the insurance and services commitments whatever the distribution channels. The second architecture principle - Specialize back-office regarding the organization’s processes – permits identifying a “Business Intelligence” area, a “Support area”, and at least one business area. A “Policy and Claims area” is an example of a business area within an insurance company.

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iiSC2011 Proceedings area describes the various technology channels used by an organization while exchanging information with external environment. The “Party Relationship area” supports the relationships linking an organization with its customers and partners whatever the communication channel. Another way to identify the TICP areas is to model the organization as a collection of broad homogeneous functions, and associate each function to an area. Let us note that each area of the TICP can be broken down into more discrete areas of functionality. Generally, an area is composed of districts and a district is a set of blocks. A district is a part of an area which represents a set of resources dedicated to the development of products and services to be consumed by the applications populating the information city. A block corresponds to an application i.e. a set of software systems supporting a homogeneous group of interrelated activities to develop one or more products or services. Table

The third architecture principle - Identify the components common to the front-office and the back office – refers to either the components that link the front-office and the back-office or the artifacts shared by the back-office and the front-office. Application of this principle results in identifying two areas: an “Integration area” and a “Shared information area”. The first area allows exchanges of informational flows and services between the back-office and the front-office applications. The second area contains information shared by all the applications of the organization’s information system as well as the applications which manage shared information data. The customers and products repositories are examples of information shared by all the applications of an organization’s information system. The fourth architecture principle - Separate in the front-office the functions managing the communication network from those managing the relationships with the organization’s customers and partners – permits identifying two areas: an “Inbound and Outbound flows Management area” and a “Party Relationships area”. The “Inbound and Outbound flows Management area” is dedicated to the management of the informational flows exchanged by an organization and its external environment. This

The following schema (Figure 1) presents an example of TICP which may be used to illustrate the information city in various service-intensive organizations like banks and insurance companies.

Business area 1 Business Intelligence area Business area 2

Inbound and Outbound Flows Management area

Party Relationships area

Business area 3 Integration area Business area 4

Shared information area

Support area

Figure 1: The Target Information City Plan (TICP)

maintenance, and operation costs of the IS applications. Moreover, exchanges of services and informational flows between applications belonging to different TICIP areas must take place through the Integration area. Concerning the exchanges with applications belonging to external IS, the IS architecture rules associated with the Communication have two goals. The first goal consist in hiding the complexity of an organization’s IS for the external applications who consume services proposed by this IS. While the second goal is related to the IS security constraints. Consequently, exchanges with external applications must take place through the Inbound and Outbound Flows Management area.

4. THE COMMUNICATION DIMENSION OF ARCHITECTURE RULES The Communication dimension of IS architecture rules describes how intra-SI and inter-SI exchanges take place. The goal of the architecture rules associated with the Communication dimension consists on the one hand, in reducing the point-to-point connection exchanges between the SI applications which belong to different areas of the TICP and on the other hand, in facilitating weak coupling between IS applications as well as the reuse of information contained in the exchanged flows. Therefore, applying the architectural rules associated with the Communication dimension results in reducing development,

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iiSC2011 Proceedings organization’s customers. While activities and tasks describe what the organizational actors do while carrying out organizational processes. From an IS perspective, the inputs and outputs of organizational processes are informational flows. Functions don’t describe organizational processes i.e. organizational processes activities and tasks are not decomposed into functions. As stressed by Dakhli [3], functions are orthogonal to organizational processes. They are independent of organizational actors and may be reused by many organizational processes. For instance, business functions related to the customer informational entity are reusable by many organizational processes. We note that there are functions which are specific to a business domain or an organizational process.

5. THE INFORMATIONAL AND FUNCTIONAL DIMENSIONS OF ARCHITECTURE RULES The informational (vs. functional) dimension of the IS architecture rules describes informational entities or data chunks managed (vs. implemented) by each IS application. Functions and informational entities permit defining the scope of a computerization project (i.e. What?). The informational entity and the function concepts enable the description of the computerization problem by using words and sentences understandable by all the stakeholders.

5.1 The informational entities

The concept of function is independent from information technology i.e. a function is independent of the IS applications which implement and manipulate it. It corresponds to a business, support, or decision-making requirement within an organization. Therefore, the concept of function is independent of software solutions. Functions may be supported by software services offered by IS applications. There are two types of services: applicative services, and end-user services. In order to reduce redundancies between IS applications, an elementary function must be implemented by only one software service. So, only one IS application is the master of this service and offers it to the other IS applications. The relationships between functions and software services permit identifying the software services implemented by IS applications and evaluating the IS redundancy level. Moreover, these relationships help organizations in impact analysis, definition of services to be modified or created, and determination of reusable services among the existing ones.

An informational entity is a set of information chunks manipulated (stored, processed, used, etc) by an IS application. An informational entity represents common data, material goods, or concepts used while carrying out organizational processes. A customer and a contract are examples of informational entities within insurance companies and banks. The informational entities and their relationships constitute the business conceptual model which is independent from its implementation in databases. An application is a master of an informational entity if it owns the official copy of this entity. Otherwise, it behaves as a slave of this entity. This means that the creation or the modification of an informational entity must be accepted by the application which is the master of this informational entity. An informational entity has one and only one IS application master. Each IS application proposes read, modification, integrity control, and publication services of the informational entities of which it is the master.

5.2 The functions

6. THE MULTI-VIEW MODEL OF INFORMATION SYSTEMS ARCHITECTURE

A function is a use or transformation action (gathering, creation, processing, edition, storage) over a set of an IS informational entities. We draw on Porter’s typology of organizational processes [13] to identify three types of functions. A function may be a business function, a support function, or a decision-making function. The business functions are manipulated by the organization’s business processes. The support functions are manipulated by the organization’s support processes while the decision-making functions are related to the organization’s decisional processes. Editing insurance contract information and processing a customer claim are examples of functions within an insurance company or a bank. Functions describe the use or transformation of information chunks contained in informational entities manipulated by the organizational processes. Inputs and outputs of functions are informational entities. Functions identified at the beginning of a computerization project determine the project scope. They are used during the evaluation of the alternative software solutions of the computerization problem associated with this project.

In this section, we draw on the work by Dakhli [3] to propose a multi-view model of IS architecture based on six interacting views: the strategy view, the business architecture view, the functional architecture (information system architecture) view, the applicative architecture view, the software architecture view, and the infrastructure view (Figure 2). The strategic view defines the organizational problems to be solved and their organizational solutions. Such problems result from the organization’s external and internal constraints. External constraints may be economic, political, social, legal or related to the evolution of the technology. Internal constraints reflect the impacts of external constraints on the organization’s components: structure, people, production technology, tasks and information technology [9] [15] [16]. The business architecture view has two goals. On the one hand, it identifies the various business events to be managed and the organizational processes aimed at answering them. On the other hand, it describes the organizational actors involved in organizational processes implementation as well as the used documents. We note that the expression “organizational process” addresses the applicable enterprise activities and procedures in charge of the business event management without anticipating their automation using tools. Moreover, this view describes the

The organizational actors manipulate informational entities and execute business, support, or decision-making functions while carrying out the activities of organizational processes in which there are involved. An organizational process task executes at least one function. We note that a function may be decomposed into elementary functions according to the organizational context. Organizational processes focus on structuring and executing their steps in order to produce goods and services required by the

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iiSC2011 Proceedings application while processing information. An application may be considered as a dynamic conjunction of a set of organizational process activities with informational entities and functions in order to contribute to goods and services production. The applicative view results from the interaction between the functional view and the organizational process view which supports the problem and operation spaces. The applicative view delivers a first level description of a software solution as a new or enhanced application which interacts with existing and future applications.

organizational processes architecture at the conceptual and the organizational levels. The organizational processes conceptual architecture models organizational processes as a nexus of activities exchanging and processing information. The organizational processes architecture is the projection of the conceptual organizational processes architecture on the organization. Therefore, it models organizational processes as nexus of operational activities and tasks carried out by organizational actors in order to create value. The organizational processes architecture is updated according to the organizational solutions defined by the strategic view.

The software architecture view describes each software solution as a set of software components and connectors distributed according to a software architecture model (e.g. MVC,…). As stressed above, a software solution is either the architecture of a new application which supports at least partly a new organizational process or the architecture of an existing application which is enhanced in order to take into account the modifications of an existing organizational process. Despite the richness of the existing definitions of the software component concept, we think that these definitions are note appropriate to take into account all the perspectives of information system architecture. So, we propose in this paper a definition of this concept which refers to functions. Our definition states that a software component is an autonomous and homogeneous logical unit which implements a function in order to provide a service either to end users or to other logical units. A software connector is an autonomous and homogeneous logical unit which facilitates interactions between two software components. A software solution is composed of reusable and specific software components and connectors. A reusable software component implements a function used by many organizational processes.

The information system architecture view describes on the one hand, the organization’s functions related to the organizational processes implementation and on the other hand, the informational entities manipulated by these functions. This view models the information system architecture as a nexus of functions and informational entities. As stressed above, an informational entity is a set of information chunks which define a concept used by the organizational actors while carrying out an organizational process. A function is an action which uses and transforms at least one informational entity. An organizational process manipulates informational entities through the use of functions. Informational entities are described in a business repository. A function may be considered as an aggregation of many sub-functions. Functions may be used by many organizational processes. Such functions are called reusable functions. Informational entities manipulated by many organizational processes are called shared information. Because of the invariant and stable nature of functions and informational entities, they are independent of the organizational structure and the roles played by actors within an organization. The architecture of an organization’s information system is defined as a model describing the organization’s functions and informational entities as well as the relationships between these concepts. The business architecture, which describes the organizational processes architecture, is updated by integrating the impacts of the organizational solutions defined by the strategic view on the informational entities and functions.

The infrastructure view describes the technical infrastructure components which supports the IS applications populating the information city. Hardware, networks, administration and monitoring tools, security devices, application servers, and database servers are examples of infrastructure components. We note that a software solution has many facets associated with the views of the IS architecture model presented previously. Each facet corresponds to an architecture metamodel which describes the main concepts characterizing this facet and the relationships between these concepts.

The applicative architecture view provides the inventory of the applications used by the organizational actors to implement the required functions and to automate – partially or totally - the organizational processes in order to develop goods and services. This view defines a map which describes the organization’s applications as well as the information flows they exchange. An application is a set of software systems which computerizes at least partly an organizational process. So, an application provides a software support to the value creation behavior of organizational actors. This behavior consists in carrying out organizational processes activities which manipulate business information by using functions. An application provides two categories of services: service-to-user and service-to-application. A service-touser results from an interaction between and end-user and an application and helps an organizational actor who carries out a set of operational activities. A service-to-application is an intermediate service provided by an application to another

The multi-view of IS architecture is compliant with the Software Global Model proposed by Toffolon and Dakhli [15]. In particular, the business architecture view is associated with the problem space and allows building an organizational solution to an organizational problem. Furthermore, the functional architecture view, the applicative architecture view, the software architecture view, and the infrastructure view contribute to the management of the computerization complexity and thus, facilitate the definition of a computer solution to support an organizational solution.

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Strategy view

Impacts of strategy on business

Impacts of strategy on information system

organizational solution

Business architecture view

Problem space

Information system architecture view

Functions and entities manipulated by the software soltion organ

izatio nal

solut ion

Applicative architecture view

First level description of the software solution

Solution space

Software architecture view

Detailed description of the software solution

Infrastructure view

Detailed description of the computer solution: software solution + Infrastructure components

Construction space

Figure 2: The multi-view model of Enterprise Architecture (Adapted from [3]) associated with the IS architecture views. Therefore, the multifaceted description of software solutions facilitates the management of IS applications complexity. The vertical interpretation highlights that a software solution has a lifecycle whose states and transitions are managed by the construction approach. This interpretation points out that a software solution is a sequence of architecture models such as the model Mn is a more formal version of the model Mn-1 which incorporates the constraints of the architecture view n. In other words, the architecture model Mn-1 is an abstraction of the architecture model Mn. Furthermore, each architecture model belonging to a software

7. THE CONSTRUCTION APPROACH OF SOFTWARE SOLUTIONS The software solution construction approach proposed in this paper is compliant with IS urbanization requirements and constraints. That the construction of a software solution is guided by the multi-view IS architecture model results in two complementary interpretations: horizontal and vertical. The horizontal interpretation refers to the systemic nature of the proposed approach since it assumes that a software solution has many facets which may be considered as levels of abstraction

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iiSC2011 Proceedings Description of the alternative software solutions;

solution is associated with a IS architecture view and may be considered as a state of this software solution. The software solutions construction approach - proposed in this paper - is composed of the following six phases:

Selection of the target software solution. These phases are not necessarily sequential. For instance, the steps et are parallel since the description of the activities and tasks of an organizational process may take place at the same time than the identification of functions and informational entities manipulated by this process. In order to build a satisfying software solution which takes into account the organization constraints, many iterations of the eight steps listed above may be necessary. Table 1 synthesizes the main characteristics of each phase of the proposed approach

Description of the process architecture; Description of the functional and informational architecture; Description of the applicative architecture; Description of the software architecture; Phase

Tasks

Concepts used

Description of the process architecture

- Description of the organizational processes supported by the future software solution - Identification of the activities to be computerized

Description of the functional and informational architecture Description of the applicative architecture

- Identification of the functional architecture rules to be applied - Identification of the functions and informational entities manipulated by the activities and tasks to be computerized - Identification of the reusable functions - Identification of the applicative architecture rules to be applied - Determination of the TICP areas and blocks of the identified functions and informational entities as well as the IS applications which support and own these functions and informational entities - Determination of the TICP areas and the blocks containing the IS application to be developed as well as the IS applications with which it interacts

- Organizational process - Activity - Task - Organizational actor -… - Informational entities - Function -…

Description of the software architecture

- Identification of the software architecture rules to be applied - Description of the software architecture layers - Identification of the components implementing the functions to be computerized - Identification of the reusable services - Description of the data models - Identification of the intra et inter layers communication protocols

Description of the alternative software solutions

- Identification of the alternative software solutions - Identification and description of the software artifacts making up each software solution

Selection of the target software solution

- Identification of the evaluation criteria according to the stakeholders views - Evaluation of the alternative software solutions: cost, benefits, risks, weaknesses, … - Selection of a target computer solution and definition of the roadmap to reach it

- Information flow - Message - Service - Application - User service - Applicative service - TICP area - TICP block -… - Software layer - Software component - Public service - Private serviced - Reusable service - Communication protocol - Data model -… - Component off the shelf - Specific artifact - Reusable artifact -… - Evaluation criteria - Metric - Quality of Service - Security constraints -…

Table 1. The steps of the software solutions construction approach understand the relationships between the main IS urbanization concepts and resources. On the other hand, our paper stresses that organizations may get value from IS urbanization through adaptation of existing software development, evolution and maintenance processes and methods. Finally, the software solutions construction approach proposed in this work help understanding the IS architecture concept and provides IS architects with a new vision of software artifacts reuse based on IS functional architecture. The validation of our framework within a

8. CONCLUSION AND FUTURE RESARCH DIRECTIONS In this paper, we have presented the main concepts of IS urbanization prior to presenting an approach to build software solutions which are compliant with IS urbanization rules and constraints. Our work has three main contributions. On the one hand, it enriches the existing work related to IS urbanization by defining the concept of architecture rules dimensions which help

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iiSC2011 Proceedings [7] Jean, G. 2000. Urbanisation du business et des SI. Paris, Editions Hermès.

French insurance company permitted us identifying many problems which may constitute future research directions. Firstly, the difference between the activity, task, and function concepts is not clear. To solve this problem, we think that a set of discriminating criteria must be defined in order to help IS architects and developers understand the difference between these concepts. Secondly, while validating the proposed approach, we noted that IS architects and developers use ambiguous non standard words and expressions to name functions and informational entities. So, the definition of codification and naming standards of functions and informational entities is needed to avoid design errors, redundancies and inconsistencies which may be an obstacle to reuse. Finally, functions reuse requires the definition of a repository which describes reusable functions and offers an efficient tool to search them easily.

[8] Kaisler, S.H., Armour, F., and Valivullah, M. 2005. Enterprise Architecting. In Proceedings of the 38th HICSS, Hawaï, IEEE Computer Society Press. [9] Leavitt, H.J., (ed.). 1963. The Social Science of Organizations, Four Perspectives, Prentice-Hall, Englewood Cliffs, New Jersey. [10] Longépé, C. 2006. Le Projet d’Urbanisation du SI, Paris, Editions Dunod. [11] Maier, M.W., and Rechtin, E. 2000. The Art of Systems Architecturing. CRC Press. [12] Noran, O. 2003. Analysis of the Zachman Framework for EA from the GERAM Perspective. Annual Reviews in Control, Vol. 27: 163-183, 2003.

9. REFERENCES

[13] Porter, M.E. 1998. Competitive Advantage: Creating and Sustaining Superior Performance. New York, Free Press.

[1] Bernard, S.A. 2004. An Introduction to Enterprises Architecture. Indiana, Author House.

[14] Sassoon, J., 1998. Urbanisation des SI, Paris, Editions Hermès.

[2] Boar, B.H. 1999. Constructing Bluprints for Enterprise Architecture. New York, Wiley Computer Publishing.

[15] Toffolon, C., and Dakhli, S. 2002. The Software Engineering Global Model. In Proceedings of the COMPSAC’2002 Conference, Oxford, United Kingdom,

[3] Dakhli, S.B.D. 2008. The Solution Space Organisation: Linking Information Systems Architecture and Reuse. In Proceedings of the ISD’2008 Conference, Paphos, Cyprus, Springer-Verlag.

[16] Toffolon, C. 1996. L’Incidence du Prototypage dans une Démarche d’Informatisation. Thèse de doctorat, Université de Paris-IX Dauphine, Paris.

[4] Dieberger, D., and Frank, A.U. 1998. A City Metaphor to Support Navigation in Complex Information Spaces. Journal of Visual Languages and Computing, Vol.9: 597-622.

[17] Zachman, J.A. 1987. A Framework for Information Systems Architecture. IBM Systems Journal, Vol. 26: 276-292

[5] Everden R. 1996. The Information Framework. IBM Systems Journal, Vol. 35: 37-38.

[18] Zachman, J.A., and Sowa, J. 1992. Extending and Framework for IS Architecture. IBM Systems Journal, Vol. 31: 590-616.

[6] Fayad M., Henry D., and Bougali, D. 2002. Enterprises Frameworks. Software Practice and Experience, Vol. 32: 735786.

[19] Guetat, S., and Dakhli, S.B.D. 2009. The Information City: A Framework for Information Systems Governance. In Proceedings of the MCIS’2009 conference, Athens, Greece. .

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AIS Quality: A Technological Perspective Ahmed A. Mohammad Department of Accounting, College of Commerce & Economics, Sultan Qaboos University, P.O. Box 20, Al-Khod, Muscat 123, Sultanate of Oman. E-Mail: [email protected] operational and security standards to secure efficiency of AIS, (4) drawn a technological guide to measure the reliability of AIS and the risk associated with it processing cycle. Specifically, the key aim of this paper is to expose the new nature of invisible AIS process and control, and to discover the extent of impact of the technological infrastructure on AIS quality. Monitoring the impact of the sophisticated level of IT infrastructure on quality of banking applications in the JCBs is imperative for this paper. However, addressing the risk associated with use of IT by JCBs is a by product objective of the current paper. The remaining part of this paper is structured as follows: section 2 presenting the background and prior research related to topics of this paper. Section 3 explains the theoretical concepts and philosophy related to theme of this paper. Section 4 presents the methodology and research design. Section 5 exposes the results of the statistical tests adopted by this study. Finally, in section 6 the conclusions have been remarked and drawn.

Abstract: Advances in IT have fuelled the move towards third wave accounting paradigm. Accounting of third wave has an innovative nature, systems, practices, education, and research. In accepting that premise, this paper has three purposes: (1) to advance the knowledge about third wave accounting by applying standards of most recent studies to improve our understanding of AIS quality, (2) to promote awareness among the accountants and bankers community about the new technological perspective of AIS quality, and (3) to survey the 13 Jordanian Commercial Banks (JCBs) about how sophisticated AIS infrastructure drives performance of these banks. It was found from the respondents that the sophisticated infrastructure of AIS can be taken as a quality driver. The study also explored and identified four correlations for AIS quality drivers with parameters of banking performance matrix. Key Words: AIS, Quality, Maintainability, Integrity.

Availability,

2. Prior Research and Background

Security,

AIS researchers have developed rich streams of research that investigate the factors that impact AIS quality. In general, there have been two dominant perspectives employed: business perspective and technology perspective. Both perspectives offer valuable contributions to understand quality of AIS. According to business perspective, research on performance quality of AIS has primarily examined quality dimensions of accounting data and information such as accuracy, timeliness, completeness, and consistency (See Figure 1). Huang, Wang and Xu have found that poor information quality of AIS may have adverse effects on decision making [7],[18]. Redman concluded that inaccurate and incomplete data may adversely affect the competitive success of an organization [12]. Huang et al, cited an example about financial services company absorbed a net loss totalling more than $250 million when interest rates changed dramatically, and the company was caught unawares [7]. Xu, Nord, Nord, and Lin identified human, systems, organizational, and external issues as being very critical for high quality accounting information as a key product of AIS [17]. According to those elite, the organizations did not have a control on these factors, but can actively manage those changes. With the skill of change management, organizations could use external pressures to accelerate the internal information quality management.

1. Introduction IT “tsunami” has forever reshaped businesses and industries. Innovations in enterprise applications software and the emergence of the disruptive technologies (such as Web services, peer services, business process management, real time computing, mobile business, and enterprise security) have created tremendous opportunities to rethink, reengineer, and redesign business processes and applications. The third wave accounting of Elliot is a disruptive technology paradigm. Accounting processes of such paradigm has transformed dramatically to become innovative, automotive, invisible, and real time. According to Amidon, “There is perhaps no functional area of management that has been more affected by the technology and knowledge agenda than accounting and finance [3]. An entire new language has evolved, characterized by heavy debates (pro and con) about the validity of the new view”. The transformation into invisible accounting has obsolete the traditional internal control system (ICS) and increased the risk patterns associated with implementation of accounting process [8]. These aspects of lack and risk have negatively affected the quality of AIS performance. To mitigate the risk and fill the control vacuum, the technological perspective of AIS quality has been developed. The importance of the technological perspective is derived from group of facts that it has: (1) totally changed and reengineered the nature of internal control system of AIS, (2) redesigned control engine of AIS, (3) set up Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission from iiSC. iiSC’11, October 11–12, 2011, Muscat, Sultanate of Oman. Copyright 2011 iiSC ISBN: 978-9948-16-253-7

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iiSC2011 Proceedings In contrast, the quality of AIS in view of the technological perspective has taken different interests and approaches. According to technology perspective, design of AIS drives performance quality in three ways: it minimizes level of threat and risk, standardizes harmony of value chain, and then improves performance parameters. Abu Musa explained that the concept of “information system security” seems to be wider than that of “information security”. Since it covers all the issues concerned with the information security (availability, integrity, confidentiality, authenticity, validity, privacy, and accuracy of information) [5]. Another practical study of Abu Musa to measure the threats of CAIS in Egyptian Banking Industry has shown a number of inadequacies in the security controls implemented in these banks. According to the results obtained, the study suggested: strengthen the restricted access to the banks sensitive data; mandatory vacations of employees should be enforced; and personal policies should include checks of previous background which could reduce the likelihood of banks fraud or embezzlement [4]. Casolaro and Gobbi conducted a study on more than 600 banks belonging to the Italian Banking Industry. Their study has addressed the impact of IT based accounting process on the operational variables of banking cost, banking productivity, and banking profitability. The study concluded with the facts that intensive use of IT inside banking process has reasonable impact on: 1) reduction of banking services cost; 2) expansion of banking services package; 3) increasing banking profit [6]. Raupeliene & Stabingis developed a quantitative model related to the effectiveness of IT based AIS. According to their study, the effectiveness of IT based accounting process is differed according to the sophisticated level of IT infrastructure in one hand, and the environmental development on the other [10]. Weingartner and Burton argued that the big security headaches are perceived from the internal environment of AIS not the external. They have found that the organization’s own employees are potentially its own worst enemies, posing the most serious risk to security [4]. Loch et al.’s have shown that 62.4 percent from the threats of AIS security are coming from the internal sources (human factors). The results of loch et al.’s survey are presented in Table 1 below [5].

Critical Factors DQ in AIS: • AIS Characteristics • DQ Characteristics • Stakeholder’s related factors • Organizational factors • External factors

Stakeholder Groups: Data Quality (DQ) in Accounting Information Systems (AIS)

• Information Producers • Information Custodians • Information Consumers • Data / Database Managers • Internal Auditors

Dimensions of DQ Performance: • • • •

Accuracy Timeliness Completeness Consistency

Feedback

Fig. 1. Theoretical Framework of AIS Quality (Business Perspective) Source: [ Table 1: The Results of Loch et al. 1992 Security Threats Sources

Internal Threat (62.4%)

Total External Threats (37.0%) Total

Perpetrators (Human 71.8%) Accidental Entry of Bad Data Accidental Destruction of Data by Employees Weak/Ineffective physical Control Intent Destruction of Data by Employees Unauthenticated Access by Employees Intent Entry Bad Data by Employees Inadequate Control Over Media Poor Control of I/O Access by Competitors Access by Hackers

Perpetrators Non Human (27.6%) (16.5%) (16.5%) (9.1%) (3.5%) (5.7%) (2.2%) (5.9%) (4.1%) (62.4%) (1.9%) (7.5%)

Natural Disaster (19.8%) Computer Viruses (7.8%)

(9.4%)

(27.6%)

Source: [5]

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TRENDS IN INFORMATION SYSTEMS 3.

iiSC2011 Proceedings the physical branch. This is useful especially in branches catering to a large number of customers base. As a result the banks return on assets employeed increases significantly. However, Internet banking transaction is characterized by individuality, mobility, independence of place and time, and flexibility. According to these new features of banking transaction, Internet banking has become a critical medium which offers strategic advantages in sustaining future growth and profitability. Also, developing Internet activities provide banks with numerous advantages especially in maintaning the customer relationship. The customer can actually be joined wherever an Internet access is possible. In a nutshell, information technology has become an aggressive and offensive strategy for banks to capture a large share of the financial service market.

Theoretical Framework

The technological perspective of AIS quality denotes a broad set of drivers supported by a new nature of accounting process. Intensifying use of IT has altered the traditional approach and measures for measuring quality of AIS. Under the impact of fully computerization, business processes have been transformed and more dimensions are being invented and integrated with the process of measuring the quality of AIS[19]. According to (SysTrust), AIS quality has multidimensional methodology with the dimensions of AIS availability, security, maintainability, and integrity [1] [2]. Control Objectives for Information and related Technology (COBIT) was another model that defined the technological nature of AIS quality. The framework of (COBIT) addresses the issues of AIS control in terms of three dimensions: 1) Business Objectives that combine criteria called business requirements for information. These criteria are divided into seven categories that map into: effectiveness (relevant, pertinent, and timely), efficiency, confidentiality, integrity, availability, compliance with legal requirements, and reliability. 2) IT Resources that includes people, application systems, technology, facilities and data. 3) IT Processes which divided into four domains: planning and organization, acquisition and implementation, delivery and support, and monitoring [13]. The Committee of Sponsoring Organizations (COSO) frameworked the third model that provides guidance for evaluating and enhancing the Internal Control-Integrated AIS [9]. COSO is widely accepted as a prfessional guide that incorporates policies, rules, and regulations of AIS into business activities. COSO’s model has five crucial components: control environment, control activities, risk assessment, information and communication, and monitoring. Later, COSO has more investigated how to effectivelly identify, assess, and manage risk associated with business process. The proposed extension has yieleded corporate governance document called Enterprise Risk ManagementIntegrated Framework (ERM). This paper argues that all the above three models (SysTrust, COBIT, and COSO) in terms of theoritical philosophy, applications, and criteria have the reliability to form concrete theoritical ground to examine the technological perspective of AIS quality (See Figure 2). Put differently, the common and well agreed measures of the above three models have been taken and searched in the banking industry. Competition and changes in technology have changed the style of banking industry. With electronic commerce, banks can increase revenues, decrease opertaions cost, attract new customers, embed existing customer relationships, and develop new offerings. Banking technology infrastructure has emerged as a panacea to address the quality potholes of AIS. Banks are embracing a wealth of new technologies such as ATM, Internet banking, extended-hour call centers and more. By intensive use of a new technology, banks are working 24 hours a day, seven days a week (24/7). Most banks have started looking at setting up secure sites and network architecture. Such architecture involves not just hardware and software tools but also the processes which need to be followed to authenticate and implement banking transactions. On-line banking has emerged as a competitive tool and as a money saver rather than a revenue earner. According to banking literature the cost of an average transaction on the Internet could be as low as, 13 cents, compared to $1.07 through the physical branch, 54 cents through the telephone and 27 cents through the ATM for a similar transaction [14]. The cost of staffing, training, and operating an electronic bank is much less as well. The use of Internet banking helps the bank reduce the load of routine banking transactions at

IT Infrastructure: • • • •

AIS Availability AIS Security AIS Maintainability AIS Integrity

AIS Quality

Performance Matrix: • Market Value Added (MVA) • Return on Investment (ROI) • Net Profit Margin (NPM) • Return on Assets (ROA) • Earning Per Stock (EPS) • Price/Earning

AIS Requirements: • IT Architecture • Knowledge Process • Organizational Design • AIS Alignment • Customers Base • External Factors

Feedback

Fig. 2. The Proposed Technological Perspective of AIS Quality

4.

Methodology and Research Design

Over the past five decades, the business and technology literature have included a large number of empirical tests, comparisons, model variants, and model extensions for AIS quality. In this paper, the adopted methodology was similar to that used by other (Loch et al.’s, 1992; Abu Musa, 2000; Rawani and Gupta, 2002; Casolaro and Gobbi, 2004) [5] [4] [11] [6], which has been based on surveying and analyzing IT infrastructure to determine the exent of avialability and impact of information technology on banking AIS. Accordingly, the quantitative data for the study were gathered through a survey questionniare from both the IT specialists and business managers within each bank. The survey questionnaire comprised 63 items distributed in 4 dimensions (See Table 2). The

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iiSC2011 Proceedings reliability test for security of AIS done by creating 19 parameters. The result of test has shown an acceptable alpha coefficient equal to 0.608. An 8 parameters are used to create data in relate to quality of AIS maintainability. The reliability test of these parameters data has produced coefficient of a=0.638. As for the reliability of integrity data of AIS, 21 parameters have been designed. The collected data has been tested and shown an alpha coefficient of 0.866. Another process to verify the reliability of AIS quality data in JCBs was calculating (Kolmogrove-Smirnovea) coefficients. Statiscally and according to the philosophy of such test, the sample data will be distributed normally if the coefficient of (K-S) ranged between -2 and +2 [15]. Table 3 in below shows that all AIS quality drivers have normal distribution and such result improve the relability of sample data.

questionnaire included Likert type responses on a multilevel scale. Each quality measure was mesured with a five point scale (1=strongly disagree, 2=disagree, 3=neutral, 4=agree, 5=strongly agree). The questionnaire parameters structured according to focus and terms of IS literature about quality of AIS (Availability, Security, Maintainability, and Integrity). The questionnaire was reviewed by academics and practitioners with knowledge of survey AIS design and success. A total of 13 questionnaires were distributed to the targeted commercial banks. All these banks have sophisticated IT infrastructure in terms of using ATM, On-line banking, and Internet banking applications. The statistical techniquics used: mean values, standard deviation, cronbach alfa, kolmogrove-smirnovea coefficients, R seqaure, F-test and T-test. All parameters have tested at the 0.05 level of significnace. Other source of quantitative data has been the financial statements of these commercial banks [20]. The qualititaive data were gathered through in-depth individual interviews and focus groups. Interviews have carfully managed with IT and business managers in these banks to indicate whether AIS quality measures and criteria are really available and followed in the applications of JCBs. The results of statistical analysis have been reviewed with those managers to explain the reasons behinds such results.

Table 3 Cronbach Alfa and Kolmogrove-Smirnove Values for AIS Quality Drivers (K-Sa ) Drivers Cronbach Alfa Availability Security Maintainability Integrity

Table 2 Structure of Survey Questionnaire Drivers WeightedParameters Average Availability 24% 15 Security 30% 19 Maintainability 13% 8 Integrity 33% 21 Total 100% 63

5.

0.765 0.608 0.638 0.866

0.195 0.183 0.189 0.283

5.2. Existance Models As mentioned, the second stage of the analysis has centered on examining the existance of AIS quality infrastructure in JCBs. Preliminary process of AIS quality was carried out through analysis of descriptive statistics. Table 4 portartes the mean scores for AIS quality measures. The same have been tested for any significant difference from the middle value of 5.00. The mean score on availablity of AIS found to be 7.85. This result clearly indicates the existance of AIS availabilty infrastructure in JCBs. Other AIS quality drivers have shown high scores of existance, which were 7.54, 6.92, and 5.7 respectivlly. The reported scores of mean reflects the sophisticeted infrastructure of AIS in JCBs. Comparing the four mean scores shows that the existance of integrity infrastructure has been the lowest. Reasoning such result can be assigned to varaince in coefficient of (K-S) and problems related to calculating the normal distribution for AIS integrity in JCBs (See Table 4 Below).

Analysis & Discussion

To provide more credibility for the results obtained from this paper, the analysis processes of the gatherd data have taken three stages: the first stage has focused on measuring the reliability of AIS quality data in JCBs. In contrast, the second stage of the analysis has centered on examining the existance of AIS quality parameters in JCBs infrastructure. Finally, the third stage of analysis has measured the impact of AIS quality on parameters of banking performance matrix (Market Value Added, Return On Investment, Net Profit Margin, Return On Assets, Earning Per Stock, and Price/Earning). As these parameters usually taken as indicators for success within the banking industry.

Table 4 Mean Scores and t-Statistic coefficients for AIS Quality Drivers Drivers Mean t-statistics Availability 7.85 Security 7.54 Maintainability 6.92 Integrity 5.70 *Tabulated T= 1.782 (Sig.5% & fd=12)

5.1. Reliability Models On the first stage of analysis, data of AIS quality are tested for its reliability, so the data can be taken as relaible and relevant for further analysis. Reliability coefficients such as Cronbach Alfa and kolmogrove-smirnove values have been computed to test the relability of AIS quality data. The reliability tests have produced a desirable alpha reliability coefficient of a=0.84. As shown in (Table 3) below, the relability cofficients for all the AIS quality measures well and above the minimum acceptable value of (0.5). Availability of banking AIS has measured by aggregating average responses from 15 parameters on the questionnaire. The alpha coefficient of 0.765 substantiates the reliability of AIS availability. Similarly, the

24.122 18.990 23.699 12.548

5.3. Structural Models Finally, the third stage of quality analysis has investigated the structural relationship between AIS quality drivers and banking performance matrix. This analysis has undertaken by calculating the multiple linear regression and F tests. The impact of AIS quality on MVA has been found

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significantly low. Only 34% of the variance in MVA is resulted from AIS quality. According to F test, the calculated F value equals to (1.052), which is less than tabulated F (5.32). To provide more statistical acceptance for this level of impact, T value has been calculated for every AIS quality driver. The calculated T test values for all AIS quality drivers have come less than (df=n-5=1.860). The total statistical result of this impact clearly shows that the level of impact is very low and can not be taken as a significant (See Table 5 Below). The possible explanation for such result is that the face to face interviews with business managers of JCBs have indicated that market values of these banks mostly determined according to external factors such as historical data and impresions of investors. The statistical tests of ROI have shown positive relationship and satisfactory level of impact. According to R square test, (45.4%) of improvement in ROI is resulted from AIS quality drivers. The further statistical analysis has indicated that calculated F value is equaled to 6.664 and higher than tabulated F (5.32). Plus, T test values for other AIS quality drivers have shown values higher than (df=n-5=1.860). This total statistical result clearly indicates significant impact of AIS quality on ROI (See Table 6 Below). Such result can be explained in view of the operational necessities and the IT investment policy for JCBs. The statistical tests of NPM have been found positive and reliable. The solid reasons for such fact are derived from values of R square, F test, and T test. R square value for NPM is equaled to (0.51) and calculated F approached (8.60) which is higher than tabulated F (5.32) on df = n-5. T test values for all AIS quality drivers have exceed (df=n-5=1.860). The full automated process of JCBs has increased number of accounts and enhanced profit engine on one

hand and reduced the operational banking costs on the other (See Table 7 Below). As illustrated in Table 8, the statistical tests of ROA have been highly positive. The value of R square is equalled to (0.51). In contrast, the calculated F has equalled (8.60) which is higher than tabulated F (5.32) on df = n-5. T test values for AIS quality drivers have exceed (df=n-5=1.860).This solid impact can be attributed to the fact that fully automated banking processes (as a result for intensive use of IT) have redesigned the internal control system toward more efficient management of banking assets (See Table 8 Below). However, the picture was totally different for the statistical tests of EPS. The level of impact has been very low reflected by the value of R square which equalled (0.17). Plus, the calculated F value (0.416) has come lower than tabulated value F (5.32) on df = n-5. T test values for all AIS quality drivers are lower than (df=n-5=1.860). The results of these tests complement the qualitative data that the investor’s decisions mostly affected by the external factors. Some of these factors are historical while the others are affected by the impressions and evaluations of investors for the ongoing circumstances (See Table 9 Below). Finally, the statistical tests of P/E have been patterned and frameworked. The result of such tests is significantly satisfactory. The R square value scored (0.37), and according to the statistical literature such level of impact can be accepted [15]. In contrast, the calculated F value has scored (7.174) which is higher than the tabulated F value (5.32) on df = n-5. T test values for all AIS quality drivers (except security) are higher than (df=n-5=1.860). Table 10 below shows further evidence supporting the relationship between AIS quality drivers and P/E.

Table 5 Impact of AIS quality drivers on MVA MVA

α

[MVA = α m β 1 χ 1 m β 2 χ 2 m β 3 χ 3 m β 4 χ 4 + l ] R2 0.34

-9,329,202,571 AIS Quality Drivers

Sig 0.4388a T

F 1.052

R 0.59

β

Sig

Avialiabilty Security Maintainability Integrity

1.600 0.482 -0.742 0.865

1289 31.01 -63.7 41.47

0.110 0.642 0.479 0.412

Table 6 Impact of AIS quality drivers on ROI ROI

α

[ROI

= α m β1 χ1 m β 2 χ 2 m β 3 χ 3 m β 4 χ 4 + l] R2 0.45

260 AIS Quality Drivers

Sig 0.0408a T

F 6.664

R 0.67

β

Sig


2.455 1.862 2.363 3.579

1.944 3.467 3.901 1.804

0.021 0.040 0.006 0.009

Table 7 Impact of AIS quality drivers on NPM NPM

α 142

[NPM

= α m β1 χ1 m β 2 χ 2 m β 3 χ 3 m β 4 χ 4 + l]

Sig 0.003a

22

F 8.600

R2 0.51

R 0.71



AIS Quality Drivers

T

β

Sig


2.525 1.870 1.997 2.043

1.226 1.361 0.347 0.014

0.036 0.042 0.047 0.007

Table 8 Impact of AIS quality drivers on ROA ROA

[ROA = α m β 1 χ 1 m β 2 χ 2 m β 3 χ 3 m β 4 χ 4 + l ]

α

R2 0.51

142 AIS Quality Drivers

Sig 0.003a T

F 12.864

R 0.71

β

Sig


2.525 1.870 1.997 2.043

1.226 1.361 0.347 0.014

0.036 0.042 0.047 0.007

Table 9 Impact of AIS quality drivers on EPS EPS

[EPS

α

= α m β1 χ1 m β 2 χ 2 m β 3 χ 3 m β 4 χ 4 + l] R2 0.17

0.50 AIS Quality Drivers

Sig 0.793 T

F 0.416

R 0.41

β

Sig


0.126 1.148 -1.058 0.058

0.001 0.009 -0.011 0.000

0.903 0.284 0.321 0.955

Table 10 Impact of AIS quality drivers on P/E P/E

[P

α

6.

E = α m β1 χ1 m β 2 χ 2 m β 3 χ 3 m β 4 χ 4 + l]

28.63 AIS Quality Drivers

Sig 0.001 T


1.927 0.439 3.550 1.830

Conclusions

This paper is an exploratory study investigating the determinants of AIS quality from the technological perspective. The findings from this paper can be grouped into two parts. At first, the results are in support of the intuitive hypothesis that the technology has become the key driver of AIS quality. But, the technological factors those influencing quality of AIS are not totally identical. The emerging discipline of AIS technologies offers interesting drivers so far as the views and approaches are concerned. At second, by investigating impact of the technological drivers according to the most recent models, the statistical measures of this paper have shown satisfactory rate of acceptance for availability, security, maintainability, and integrity as key drivers for AIS quality. In terms of its impact on banking performance matrix, the results of this paper have shown that four performance metrics positively affected by the

F 7.174

β

R2 0.37

R 0.60 Sig

0.619 0.040 0.127 0.672 0.212 0.036 0.194 0.044 technology drivers of AIS quality. ROI, NPM, ROA, and P/E are all got supported by improvement in AIS quality. This fact provides an opportunity to conclude that the internal engines of profit mostly affected by improvement on AIS quality. The important extension this paper provides is still there is urgent need to exploit IT infrastructure for more adoption, adaptation, and integration with AIS quality infrastructure. A challenge is not to apply technology, but how to develop new ways to integrate the applications and mechanism of such technology with metrics of banking performance matrix. Additional research is needed to develop a solid understanding of the relationships proposed in AIS quality models.

References [1] AICPA, CICA 2006 Trust Services Principles, Criteria, and Illustration. p.7-40. [2] AICPA, CICA 2006 Generally Accepted

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Privacy Principles. p.7-12. [3] Amidon, Debra M. 2003 The Innovation Superhighway. Butterworth-Heinemann, U.S.A. p.49-67. [4] Abu-Musa, Ahmed 2000 Security of Computerized Accounting Information Systems: A Theoretical Framework. Working Paper, BAA-ICAEW Doctoral Colloquium, 18th –20th April. Manchester Business School: The University of Manchester, U.K. p.20-38. [5] Abu-Musa, Ahmed 2001 The Perceived Threats to the Security of Computerized Accounting Information Systems, p.9-20 [6] Casolaro, L.; Gobbi, G. 2004 Information Technology & Productivity Changes in the Italian Banking Industry. Report Published by Bank of Italy Economic Research Department. p.1-26. [7] Huang, Huan-Tsae, Lee, Y.W. and Wang, R.Y. 1999 Quality Information and Knowledge, Prentice Hall PTR. [8] Hollander, Anita Sawyer; Denna, Eric L.; Cherrington, J. Owen. 1996 Accounting, Information Technology, and Business Solutions. Irwin: Times Mirror Higher Education Group Inc. p.1-29. [9] Institute of Internal Auditors. Putting COSO’s 2005 Theory into Practise. NewYork: AITamonte Spring, FL327014201, Nov. 2005; P.1-4. [10] Raupeliene, A., Stabingis, L. 2003 Development of A model for Evaluating Effectiveness of Accounting Information Systems. Efita Conference, EFITA Conference. 2003; p. 339-345.

[11] Rawani, A. M.; Gupta, M. P. 2002 Role of Information Systems in Banks: An Empirical Study in the Indian Context. Ahmedabad, India. Journal for Decision Makers, Vol.27 (4), Octber-December, 2002; p. 69-74. [12] Redman, T.C. 1992 Data Quality: Management and Technology. New York: Bantan Book, p. 63-107. [13] Romney, M.B., Steinbart, P.J. 2006 Accounting Information Systems. New York: Pearson Education, p. 190-224. [14] SCN. 2001 Electronic Banking: The Ultimate Guide to Business and Technology of Online Banking. MBH: Vieweg, Germany; p. 149-167. [15] Vaus, David de. 2002 Surveys in Social Research. Sydeny: Routledge, Austrialia. p. 241-291. [16] Wixom, Barbara H.; Todd, Peter A. 2005 A Theoretical Integration of User Satisfaction and Technology Acceptance. Journal of Information Systems Research, Vol.16 (1), March p. 85-102. [17] Xu, H., Nord, J. H., Nord, G.D., & Lin, B. 2003 Key Issues of Accounting Information Quality Management: Australian Case Studies. Industrial Management and Data Systems, 103/7; p. 461-470. [18] Xu, Hongjiang 2009 Data Quality Issues for Accounting Information Systems Implementation: Systems, Stakeholders, and Organizational Factors, Journal of Technology Research, p.1-11. [19] http://infotech.aicpa.orglresources. [20] www.abj.org.jo.

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XML Information Retrieval Systems: A SURVEY Awny Sayed Information Technology Dept. - Ibri College of Applied Science Sultanate of Oman Mobile Number 00968-98838296,

[email protected] the query}. That principle motivates a retrieval strategy that returns the smallest unit that contains the information sought, but does not go below this level. In our survey, we give an overview of the different XML information systems and classify them according to their storage and indexing strategies. For storage, we will answer the question, what is the best way of storing xml documents. Moreover, we will provide a classification of the different strategies used to store XML documents. The classification is based on the underlying system used for it (e.g., relational systems, object-relational systems, or native systems). For indexing and querying in our survey we will classify indexes into three parts (structured indexes, connection indexes, and path indexes) based on the underlying XML data, its tree-like structure or graph-like. The rest of the paper is organized as follows. Section 2 introduces XML storage techniques. Sections 3 provide the details of the different indexing techniques; Finally, Section 4 concludes the paper and provides some suggestions for possible future research directions on the subject.

ABSTRACT: The continuous growth in the XML information repositories has been matched by increasing efforts in development of XML retrieval systems, in large parts aiming at supporting content-oriented XML retrieval. These systems exploit the available structural information, as market up in XML documents, in order to return documents components- the so called XML elements-instead of the complement documents in repose to the user query. In this paper, we provide an overview of the different XML information retrieval systems and classify them according to their storage and query evaluation strategies.

Keywords:

XML, XML storing, XML indexing, XML querying, Information Retrieval

1. INTRODUCTION Indexing data for efficient search capabilities is a core problem in many domains of computer science. As applications centered on semantic data sources become more common, the need for more sophisticated indexing and querying capabilities arises. In particular, the need to search for specific information in the presence becomes of particular importance, as the information a user seeks may exist as an entailment of the explicit data by means of the terminology. This variant on traditional indexing and search problems forms the foundation of a range of possible technologies for semantic data. In unstructured information retrieval, it is usually clear what the right document unit is: files on your desktop, email messages, web pages on the web etc. While the first challenge in the semistructured information retrieving is that we don’t have such a standard traditional document unit or indexing unit that is could be retrieved as a result to a query. The main profit of the XML which is considered as a new concept in the information retrieval branch is that when we query the XML documents we can dive deeply more than the document level allow to us into more specific units as document fragments (e.g. XML elements) which answer the user’s query. A new decision criterion that has been proposed for selecting the most appropriate and specific part of a document is the structured document retrieval principle [10]: Structured document retrieval principle: states that, {a system should always retrieve the most specific part of a document answering

2.XML STORAGE TECHNIQUES The basic properties of XML data are hierarchical treestructured and semi-structured unlike ordinary relational databases. With this in mind in order to retrieve XML data efficiently we need different types of indexing techniques. An XML document can be modeled as a tree-like or a graph- like depending on the containment of that document to links or not. If the XML document does not contain such global or internal links it is modeled as a tree-like structure, otherwise if the XML document contains whether a global or internal links it is modeled as a graph-like structure. A tree, with nodes representing XML elements or attributes and edges representing parent-children relationships. Boxes with rounded corners represent attribute or text nodes.

2.1 Text Approach The first strategy stores each XML document as a text file. One way to implement a query engine with this approach is to parse the XML file into a memory-resident tree against which the query is then executed. The tree is retained in memory as long as some nodes in the tree are needed for query evaluation. [23] found that the parsing time dominated query execution time and the approach was unacceptably slow. To make this approach competitive they adopted the following indexing strategy. Using the offset off an XML element inside the text file as its id, and build a path index mapping (parent_offset, tag) to child_offset as shown and an inverse path index mapping child_offset to parent_offset. These two indices are used to facilitate navigation through the XML graph. Another index mapping (tagname,


25



value) or (attribute_name, attribute_value) to element offset is built to help evaluate selection predicates. A query engine can use these indices to retrieve segments of an XML file relevant to the query, reducing parsing time dramatically.

2.3 Edge Approach The third strategy is the "EDGE" approach described in The directed graph of an XML file is stored in a single Edge table. Each node in the directed graph is assigned an id . Each tuple in the Edge table corresponds to one edge in the directed graph and contains the ids of the two nodes connected by the edge, the tag of the target node, and an ordinal number that is used to encode the order of children nodes. When an element has only one text child, the text is inlined. TargetlD indicates that the edge points to a TEXT node or ATTRIBUTE node. 0 in ordinal field indicates an attribute edge. As suggested in an index is built on (tag, data) in order to reduce the execution time of selection queries. We found that it was also very important to build indices on (sourceid, ordinal) and (targetID). The former is used to lookup children elements of a given element and the later is used when traversing from a child node to its parent. The clustering strategy on the Edge table has significant impacts on query performance. While we clustered the Edge table on the Tag field, an alternative strategy is to cluster the table according to SourcelD. This strategy has the benefit that sub-elements of one XML element are stored close to each other. The drawback of that Approach is that elements with the same tag name are not clustered. Consequently, queries such as "select all students whose major is Computer Science" will incur a large number of random I/Os. Similar to the EDGE model, the BINARY approach materializes the generic tree structure of XML documents in database tables. Hence, it is a model mapping approach as well

The main disadvantage of this approach is that whenever the XML document is updated, the element offset of preceding tags are also changed, which invalidates the indices and they have to be rebuilt. Regarding concurrency control it is necessary to lock both the XML document and the matching indices when some thread access data (reading/writing) due to data consistency. When a one thread is reading other threads can read as well, but when some thread is updating other threads cannot read or update the whole document since it cannot be considered consistent. The worst case is of course if new threads continue to access the document for reading, then it will not be possible to update any part of the document, unless some sort of prioritizing algorithm is implemented (and updates are given higher priority, of course this could lock out reads).

2.2 The Relational DTD Approach The second strategy is the shared-inclining method proposed in and requires the existence of a Document Type Definitions (DTD). In DTD All element declarations begin with . They include the name of the element being declared followed by the content specification. In this declaration, the content specification is the keyword ANY (again case-sensitive). The element declaration says that a SPEECH element must contain a single SPEAKER element followed by one or more LINE elements, the + quantifier indicates that the LINE must exist at least one time and no limits for the maximum number of its recurrence. An element that can only contain plain text is declared using the keyword #PCDATA in parentheses, like this: This declaration says that a STAGEDIR can contain only parsed character data, that is, text that’s not markup. Like elements, the attributes used in a document must be declared in the DTD for the document to be valid. Attributes are declared by an attribute list in the following form: . A separate table is used to capture the set-containment relationship between an element and a set of children elements with the same tag. Each tuple in a table is assigned an ID and contains a parentlD column to identify its parent, an element that can appear only once in its parent is inline. If the DTD graph contains a cycle, a separate table must be used to break the cycle, the relational schema generated from the DTD and how the document is stored are shown below. When reconstructing the XML document from this approach it is necessary to know how to build the document in terms of layout. Whether it is a partial or a full reconstruction does not matter because the work is the same, only when it is partial it is necessary to make specifications about which part one wishes to reconstruct. There is though a problem of recreating whitespace outside contents because this information is lost when the XML document is uploaded to the database.

2.4 The Object Approach An obvious way of storing XML documents in an object manager is to store each XML element as a separate object. However, since XML elements are usually quite small, all the elements of an XML document are stored in a single object with the XML elements becoming light-weight objects inside the object. [23] [24] use the term LW_object to refer to the lightweight object and file_object to denote the object corresponding to the entire XML document. The offset of the lw_object inside a file_object is used as its identifier (lw_oid). The length field records the total length of the lw_object. The flag field contains bits that indicate whether this lw_object has opt_child, opt_attr, or opt_text fields. The tag field is the tag name of the XML element. The parent field records the lw_oid of the parent node. Opt_child records the lw_oids of the first and last child, if the lw_object has children. The sibling list of a node is implemented as doubly linked list via the prev and next fields. Opt attr records the (name, value) pair of each attribute of the XML element. Text data is in-lined in the opt_text field if the text is the only child of the XML element; otherwise, the text data is treated as a separate lw_object. [23] built a B-Tree index that maps (tag, opt_text) and (attr_name, attr_value) to lw_oid. An element is entered in this index even if the opt_text field is empty so that this index can be used to retrieve all XML elements with a specific tag name. They also built a path index those maps (parent_id, tag) to child lw_oid. This optimized object approach is hard to perform concurrent operations on since the locking has to occur on the object representing the whole document; unless there should be

26



build some extra concurrency control into the lw_objects themselves, but this would be overkill. To when locking anything in this approach means at least locking the whole XML document.

descendant axes) can be evaluated using these numbers. This index based on the following property for evaluating path expressions: For any two given nodes A and B in the tree, an arbitrary node B is a descendant of a node A, if and only if this condition is satisfied:

2.5 Native XML Storage Approach Finally, we should have a look shortly at so-called native XML databases, which are specialized to store and process XML documents. Native storage schemas aim at efficient support for loading and storage complete documents as well as efficient navigation in documents. A native XML storage system store XML documents as flat files, i.e., it uses a text-based mapping. However, evaluation of queries requires reconstructing the complete XML documents, which is not efficient when only parts of the documents are evaluated by the given query. As a result, most native XML storage schemas store XML documents as a tree structures based on the tree data model of XML [12] . These particular approaches are modelmapping approaches. Usually, native XML storage systems rely on the DOM tree representation of XML documents.

pre(A) < pre(B) and post (A) > post(B) If we want to evaluate all descendants of a given node using this schema, then the result is the set of all nodes that satisfies the above condition. The pre-/post-order approach can be determined in a constant time by examining the pre-and post-order variable of the corresponding tree nodes. The [22] stated that the drawback of this approach is its lack of flexibility in case of changes to the structure of the XML-document. That is, the pre-/post-order variables need to be recomputed for the number of tree nodes if any update into the tree whether a new node is inserted or an existing one is deleted.

3.2 Connection Indexes A connection index is the index which supports the XPath axes that are used as wildcards in path expressions (ancestors-or-self, descendants-or-self, ancestors, and descendants). Labeling schemes for rooted trees that support ancestor queries have recently been developed in the following researches. In [4] and [16] they present a tree labeling scheme based on two level partition of the tree, computed by a recursive algorithm called prune&contract algorithm. All these approaches are, so far, limited to trees. We are not aware of any index structure that supports the efficient evaluation of ancestor and descendant queries on arbitrary graphs. The one, but somewhat naive, exception is to pre-compute and store the transitive closure Cx = ) of the complete XML graph Gx = (Vx ,Ex) Cx is a (Vx,

3. INDEXING TECHNIQUES Since the hierarchical nature of the XML documents there is a lot of interesting in a query processing on data that conforms to a labeled- tree or labeled- graph model. To summarize, the structure of such data in the absence of a schema and to support path expressions evaluation, several structure indexes have been proposed for semi-structure data described as follows

3.1 Structure Indexes The structure index I (G) of a data graph G is a summary graph that preserves all the paths in the data graph but contains a fewer number of nodes and edges To summarize the structure of such data in the absence of a schema and to support path expression evaluation, novel structural indexes [14], [19] have been proposed for semi-structured data. Unlike a schema, structure indexes are not prescriptive and thus may change with any update. Generalizations of these structures have gained increasing attention recently, as flexible index structures for XML [9], [16], [18], and size and performance issues in the original proposals have been addressed [18]. Pre/post schema encoding XML tree-structure. In addition, the ideas behind these structure indexes have been used as statistical synopses for estimating path expression selectivity [2],[20]. Moreover, the structure index proposed in[and [13] presents a database index structure designed to support path expressions evaluation on trees. It has the capability to support all XPath axes and start traversal from any arbitrary nodes in an XML document. Building the index takes O (|E|), and space consumption is O (|V|), where V denotes the number of nodes in the XML tree and E the number of edges. The main idea of this index depends on the numbering schema. It computes two numbers for each element name in the XML data tree, one representing the preorder and the other representing the post-order. These numbers are the result of a depth-first search on the XML data tree. Starting with the root element, the pre-order numbers are assigned in the order in which the nodes are visited during this search. The post-order defines the order in which the nodes are left. The authors explain that XPath axes (like ancestor and

very time-efficient connection index, but is wasteful in terms of space. Therefore, its effectiveness with regard to memory usage tends to be poor (for large data that does not entirely fit into memory) which in turn may result in excessive disk I/O and poor response times. To compute the transitive closure, time O(|V|3) is needed using the Floyd- Warshall algorithm. This can be lowered to O(|V|2 + |V|. |E|) using Johnson’s algorithm. Computing transitive closures for very large, disk-resident relations should, however, use diskblock- aware external storage algorithms. [1] [7] [8] implemented the “semi-naive” method [BR86] that needs time O (| | . |V|). Although there are several approaches are proposed to evaluate all the ancestors of a given node and test the reachability between two given nodes. For example, labeling schema proposed in [17] is called a prefixlabeling schema to handle a dynamic XML tree. The nodes in the XML tree are labeled such that the ancestor relationship is determined by whether one label is a prefix of the other. New nodes can be inserted without affecting the labels of the existing nodes. They define an assignment of binary strings to the edges of the tree, such that, the collection of strings associated with the outgoing edges from any node is prefix free, a prefix free assignment. At the first, the simple prefix schema finds a prefix free assignment to the tree. Then, it is label every node v with the concatenation strings assigned to the edges of the path from the root node to v.

27



For every assignment, labels are unique. Node u is ancestor of node v, iff the label of u is a prefix of the label of v. One major problem related to this approach is how to find an assignment that minimizes the sum of the lengths of the labels, unfortunately this problem is NP-hard [17] means no optimal solution to this problem. The main goal of the work in [17] is to find an assignment that minimizes the maximum length of the labels by using Huffman’s algorithm [14]. Several labeling schemes are proposed using the above technique, for example, [4] [6] proposed a labeling schema for rooted trees that supports ancestor queries by assigning to each node in the tree a label which is a binary string. Given the labels of two nodes u and v it can be determined in a constant time whether u is an ancestor of v only by looking at the labels. Another labeling schema proposed on [25], it takes the advantages of the unique property of prime numbers to meet this need. Answering the ancestordescendant queries for a given two nodes by only looking at the labels (based on prime numbers). An analytical study of the size requirements of the prime numbers indicates that this schema is compact and hardly affected.

schema in context of semistructured data management. The DataGuide is a descriptive schema for XML data. While prescriptive schemas (DTD, XML Schema, Relax-NG) act more as a traditional database schema, restricting allowable XML data, a DataGuide infers rather than imposes structure. DataGuide describes actual (rather than possible) structure of XML data extracting the structure from the XML data. It may be used as schema for semistructered data without any explicit schema declaration, such as non-validated XML documents. The dataguide is based on the Object Exchange Model (OEM) which is the simple and flexible data model that originates from the Tsimmis project at Stanford University [PGW95]. OEM itself is not particularly original, and the work presented using OEM adapts easily to any graph-structured data model. A value may be atomic or complex. Atomic values may be integers, reals, strings, images, programs, or any other data considered indivisible. A complex OEM value is a collection of 0 or more OEM subobjects, each linked to the parent via a descriptive textual label. Note that a single OEM object may have multiple parent objects and that cycles are allowed. For more details on OEM and its motivation. [14] Describes the DataGuide that it is, intended to be a concise, accurate, and convenient summary of the structure of a database. They assume that the source database is identified by its root object. To achieve conciseness, they specify that a DataGuide describes every unique label path of a source exactly once, regardless of the number of times it appears in that source. To ensure accuracy, they specify that the DataGuide encodes no label path that does not appear in the source. In addition they require that a DataGuide itself be an OEM object so we can store and access it using the same techniques available for processing OEM databases.

Moreover, the authors introduced several optimization techniques to reduce the size of the schema. Unfortunately, these indexing techniques were supposed to handle tree-structure data. Extension of these techniques to the context of graph data could be very difficult because of the possibly exponential number of paths in the graph. Moreover, it may require a lot of computing power for the creation process and a lot of space to store the index.

3.3 Path Indexes A path index is the index which supports the navigational XPath axes (parent, child, descendants-or-self, ancestors-orself, descendants, and ancestors). Recent work on path indexing is based on structural summaries of XML graphs. Some approaches represent all paths starting from document roots, e.g., Data Guide [14] and Index Fabric [11]. T–indexes [19] support a pre– defined subset of paths starting at the root. APEX [9] is constructed by utilizing data mining algorithms to summarize paths that appear frequently in the query workload. The Index Definition Scheme [16] is based on bisimilarity of nodes. Depending on the application, the index definition scheme can be used to define special indexes (e.g. 1–Index, A(k)–Index, D(k)–Index [QLO03], F&B–Index) where k is the maximum length of the supported paths. Most of these approaches can handle arbitrary graphs or can be easily extended to this end. Most of these indexes are quite efficient in evaluating simple path queries. These indexes widely differ in space utilization, support for paths with wildcards (wildcard means the arbitrary long paths from source point to targets in XML graph). These path indexes depend on the structure summaries of the XML graph. Structure summary is an important technique for indexing XML arbitrary graph, in case the general schema of the information is missing. Using this summary of the data, one can evaluate the path expression queries without looking at the original data. In the following, we will describe these indexes in details.

3.3.2 Indexing Template-compliant Paths: T-index Like DataGuide [14], 1-index [19] is intended to be used by queries that search the database from the root for nodes matching some arbitrary path expressions. 1-index therefore, represents the same set of paths from the root like DataGuide. The main idea behind the index construction is the generation of a non-deterministic automaton (NFA) [22] to get more compact structure than the DataGuide. To construct the 1-index of a data graph, the authors compute for each node the equivalence class using a bisimulation as equivalence relation which is defined in the next definition. Definition 3-2 (Equivalence Relation ““): For each node u in the data graph, let the set Lu= {w a path from the root to node u labeled w}. The set Lu may be infinite when the graph has cycles; however, it is always a regular set. Given two nodes u and v in the data graph we say that they are language-equivalent in notation u v, if Lu= Lv. Definition 3-3 (Bisimilarity): Two nodes in the data graph are bisimilar () if all label paths into them are the same. In other words, if node u’ is parent of node u, node v’ is the parent of node v. If the two nodes u and v have the same label, then, u v if u’v’. Using bisimulation to deal with the index size and the construction cost problems that DataGuide index yields. Where the size of the DataGuide may be large as the database itself, while 1-index is at most linear.

3.3.1 Data Guide DataGuide [14] is a "structural summary" for semistructured data and may be considered as analog of traditional database

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The advantage of 1-index and its family (2-index and T-index [19]) is that, it can be used to evaluate any path expressions accurately without accessing the data graph. However, the size of 1-index can be quit larger for irregular XML data. Moreover, not all structures are interesting and most queries probably only involve short path expressions.

node to be refined also points to data nodes that are irrelevant to the given set of frequently used path expressions. Definition (Index Graph): Index graph means that we reduced the graph that summarized all the paths from the root in the data graph, the nodes that have the same label from root are collected into one node called index node. The index graph is smaller than the data. Path expressions can be directly evaluated from the index graph and can retrieval label-matching nodes without referring to the original data graph. M(k) Index: To overcome these limitations for the D(k)-index, A M(k)-index (for “Mixed-k”) is proposed in [15]. The authors built on the strength of D(k)-index and proposed M(k)-index and M*(k)-index to overcome its limitation. To overcome the limitations of over-refinement of irrelevant index nodes and data nodes, M(k)-index is proposed to target only the data nodes relevant to frequent queries. Like the D(k)-index, the M(k)index uses the k-bisimilarity equivalence relation but allows different k values for different nodes; it is also incrementally refined to support new frequently used path expressions extracted from the query workload. Unlike the D(k)-index, however, M(k)-index is never over-refined for irrelevant index or data nodes. Thus, the M(k)-index has a smaller size without sacrificing support for any frequent used path expressions. To overcome the limitations of over-refinement due to overqualified parents and single resolution each node, M*(k)index is introduced as a collection of M(k)-indexes whose nodes are organized in a partition hierarchy, allowing successively coarser partitioning information to co-exist with the finest partitioning information required. The M*(k)-index maintains kbisimilarity information for all k up to some desired maximum, which can be different across nodes and adjusted dynamically according to the query workload. This feature allows the M*(k)index to avoid over-refinement due to overqualified parents and support both short and long path expression queries over the same data nodes at the same time. Experiments show that although keeping partitioning information at different resolutions requires extra storage space; it is negligible compared to the savings achieved by avoiding over-refinement. The performance gain from query processing further justifies this new approach.

A(k)-index: A(k)-index [18] is a type of approximate structural summary of data graph since it does not reflect whole structure and nodes of XML tree are grouped according to the local structure. With these properties in mind we can think of several issues as follows. • Not all structures are interesting. • Paths longer than k may be never used. • Complex paths may never show up. • Longer path results in large index graph, which takes time to construct and traverse while querying. We can reach to one solution considering above issues, that is, use of local similarity, which is approximate structural summary. We focus on features of A(k)-index in the following sections within the view of implementation issues. Taking advantages of local similarity [3], the A (k)-index can be substantially smaller than 1-index [19]. The parameter k control the “resolution” of the entire A (k)-index; all index nodes have the same local similarity of k. If k is too smaller, the index cannot support long path expressions accurately. If k is too large, the index may become so large. At this case, evaluating any path expression over this index will be expensive. The time required to build the index is O(km) where m is the number of edges in the data graph. Furthermore, not all path expressions of length k are equally common. The A(k)-index lacks the ability to make certain parts have higher resolution than the others do, so it can not be optimized for complex path expressions with wildcards. D(k)-Index: The D(k)-index is an adaptive summary structure for the general graph-structured data proposed recently. It allows different index nodes to have different local similarity requirements that can tailored to support a given set of frequently used path expressions and to avoid the A(k)-index drawbacks. For parts of the data graph targeted only by longer path expressions, a larger k can be used for finer partitioning. For parts targeted only for shorter path expressions, a smaller k can be used for coarser partitions. However, as a generalization of 1-index and A(k)-index, the D(k)-index processes the adaptive ability to adjust its structure according to the current query loads. D(k)-index has a very nice property compared with 1-index and A(k)-index because of dynamics. The author provides an efficient algorithms to update the D(k)-index with changes in the source data . The general approach of the D(k)index is flexible and powerful, but the index design still has several limitations that need to overcome. For example of these limitations, the construction procedure of the D(k)-index forces all index nodes with the same label to have the same local similarity, which is unnecessary and restrictive. The D(k)-index also proposes a promoting procedure that incrementally refines the index to support a given set of frequently used path expressions. This procedure increases the local similarity of an index node if it reached by a given set of frequently used path expressions in the index graph. This index node will be partitioned into smaller nodes, all with the same increased local similarity. However, the problem is that in general the index

4. CONCLUDING REMARKING After reviewing a number of existing XML information and retrieval systems, we can draw some conclusions about the state of the art and general trends in the fields. Our Survey addresses what exactly are the requirements for efficient XML storage management. A storage management schema must cover the following aspects efficiently: lossless storage of XML documents, complete and efficient reconstruction of decomposed XML documents, and support for processing path expressions on the XML document structure, support for processing of precise and vague predicates on XML content, navigation in XML documents, and online updates of XML documents. Moreover, IR community applies with some modification standard IR techniques for focused element-level retrieval. But despite some similarities with unstructured text, XML needs special treatment in terms of relevance of its elements to a user query and in its evaluation. Hence we need a new paradigm in its retrieval techniques and evaluation metrics. On the whole, XML as an research area holds immense prospect

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iiSC2011 Proceedings [9] C. Chung, J. Min, and K,Shim. APEX: An adaptive path index for XML data. SIGMD 2002. [10] D. Chirtopher Manning, P. Raghaven and H. Schuetze. Introduction to information Retrieval. Cambridge University Press. 2007. [11] B. Cooper, N. Sample, M. Franklin, G. Hjaltason et. al. A fast index for semi structured data. In VLDB, 2001. [12] Chenying Wang, Xiaojie Yuan, Shitao Yu, Hua Ning, Huibin Zhang, "A Storage Scheme of Native XML Database Supporting Efficient Updates," Database Technology and Applications, International Workshop on, pp. 522-525, 2009 First International Workshop on Database Technology and Applications, 2009. [13] T. Grust and M. Keuulen, Tree Awareness for Relational DBMS Kernels. In intelligent search on XML data. , Springer Verlag. 2003. [14] R. Goldman and J. Wisdom . DataGuides, Enabling query formulation and optimization in semstructured databases, In VLDB, 1997. [14] D. Huffman. A method for the construction of minimum redundancy codes. In IRE, 40, pages 1098-1101, 1952. [15] H. He and J. Yang. Multisoluation indexing of XML for frequent queries, In ICDE, 2004. [16] H. Kaplan, and T. Milo. Short and simple labels for small distances and other functions. In WADS , 2001. [17] H. Kaplan, T. Milo, and R. Shabo. A Comparison of labeling schemes for ancestor queries. In SODA, 2002, USA. [18] R. Kaushik, P. Shenoy, P. Bohannon, and E. Gudes. Exploiting Local Similarity for indexing paths in graph-structure data. In ICDE , 2002. [19] T. Milo and D. Suciu. Index structures for path Expression. In ICDE, 1999. [NM 10] Natima Mebhaza . Analyzing the Impact of XML Storage Models on the Performance of Native XML Database Systems. In Seventh International Conference on Information Technology Las Vegas, Nevada, USA, 2010. [20] N. Polyzois, and M. Gaeofalakis, Statistical synopses for graph- Structured data. In SIGMD, 2002, USA. [21] J. Shanmugasundaram. K. Tuffe, G. He, C. Zhang el al. Relational databases for querying XML documents. : Limitation and opportunities. In VLDB, 1999. [22] A. sayed, R. Unland. Indexing Collection of XML documents with arbitrary Linnks. Dissertation from DuisburgEssen Uni., Germany, 2005. [23] F. Tain, D. DeWitt, J, Chen, and C. Zhang. The design and performance evaluation of alternative XML Storage strategies. In SIGMD, 2002.

which is not still extensively explored and therefore remains an interesting field of further research. On the other hand, for Indexing and querying XML data our survey introduces a short classification of structures indexes for semistructured data based on the navigational axes they support. Structure index supports all navigational for XPath axes. Connection index supports the XPath axes that are used as wildcards in path expressions (ancestor (descendant)-or-selfrelationship and ancestor-descendant relationship). Path index supports only the following kinds of XPath axes (parent-child relationship, ancestor-descendant relationship, ancestor-or-self relationship, and descendant-or-self relationship). For heterogeneous XML documents in the Web (divided XML documents into several subcollections), a single index structure may not be appropriate. Therefore, it will be investigated whether it makes sense to combine several indexes as building blocks. This would allow for building an index for each subcollection and evaluating the proposed queries by “navigating” through the underlying sub-collection only. Moreover, The most common web technology that will realize Web 3.0 is RDF (resource document Framework) model. The Resource Description Framework (RDF) is a flexible model for representing information about resources in the web. With the increasing amount of RDF data which is becoming available, efficient and scalable management of RDF data has become a fundamental challenge to achieve the Semantic Web vision. So, the most important question is, could we apply the same technologies used to store and retrieval Xml to RRD Data, this is still a very hot topics for research.

5. REFERENCES [1] Awny Sayed , Ahmed A A Radwan, Mohamed masod. "Efficient Evaluation of Relevance Feedback algorithms for XML Content-based Retrieval System". International journal of web information system, 2010. [2] A. Aboulnaga, A. R. Alameldeen, and J. F. Naughton. Estimating the selectivity of XML path expressions for internet scale application. In Proceedings of VLDB, 2001. [3] S. Abiteboul, P. Buneman, and D. Suciu. Data on the WebFrom relation to Semistructured data and XML. San Francisco , Morgan Kaufmann Publishers, 2000. [4] S. Abiteboul, H. Kaplan, and T. Milo. Compact Labeling Schemes for ancestor queries. In ACM/SIAM Symposium on Discrete Algorithms (SODA), 2001. [5] S. Abiteboul, D. Quess, J, McHugh, J. Wisdom, and J. Wiener. The Loral Query Language for Semistrutured Data. In international Journal of Digital Library, 1997. [6] S. Allstruo and T. Rauhe. Improved Labeling schema for ancestor queries. In ACM/SIAM Symposium on Discrete Algorithms (SODA), USA, 2002. [7] Awny Sayed “Fast and efficient computation of connectivity queries over linked XML documents graph. Issue 1, Vol. 4., 2009, International journal of web information system. [8] Awny Sayed. "A prime Number Labeling Scheme for Reachability Queries over Complex XML Collection". the 4th Indian International Conference on Artificial Intelligence (IICAI-09) 2009.

[24] Wenxin Liang, Akihrio Takahashi and Haruo Yokota. A Low-Storage-Consumption XML Labeling Method for Efficient Structural Information Extraction, in DEXA 2009:7-22

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E-COMMERCE AND E-BUSINESS CHALLENGES


E-Commerce and E-Business Challenges

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An Analysis of Intention to Use Online Group Purchases Yu-Hao Chuang

Chia-Sheng Lin

Wesley Shu

Department of Information Management, National Central University No.300, Jhongda Rd., Jhongli City, Taoyuan County 32001, Taiwan +886-3-4227151 #66621



[email protected]

[email protected]

[email protected]

local markets. If a certain number of people sign up, the deal becomes available to all. The discount can be as high as 50%. Customers do not need to know one another or belong to the same organizations; they are simply Internet users who happen to see the same discount information. Thus, collective intelligence becomes collective bargaining power. The company, which began operations in Chicago in November 2008 (Wikipedia, 2011b), has recently been valued at US$4.5 billion (Wei, Straub, & Poddar, 2011).

ABSTRACT Group buying websites have drawn considerable attention in the business world. By improving buyers’ bargaining power, these sites help consumers obtain more of the surplus created by network externality. By employing UTAUT and online group buying (OGB) data from Taiwan, the author identified five reasons why people want to engage in online group buying: perceived risk avoidance, sociability, performance expectancy, effort expectancy, and social influence. The relationship between behavioral intention and use behavior, although in the positive direction, was not significant.

Why is this crowd-empowering particularly important on the Internet? History teaches us that the Internet has long-tail effect, ubiquity, network externality, and the absence of marginal costs for its digital delivery. Due to these features, the Internet has demonstrated that ventures with good business models and timely entrance into the market can enjoy global monopolistic power. Some good examples are eBay, PayPal, Yahoo!, Amazon, Google, Facebook, Wikipedia, Alibaba, Baidu, QQ, and Renren. Sellers who have exploited these Internet idiosyncrasies have become leviathans. Although Web 2.0 has shifted the focus of the Internet from website owners to users, and users can now control website content and form their own social networks, there are no signs that bargaining power on the Internet has shifted from sellers to buyers.

A moderator, conformity, was tested. Females reported that they were influenced more than males in their intention to use OGB services by perceived risk avoidance, sociability, and perceived playfulness. The impact of the intention to use OGB on actual usage was stronger among those who evidenced conformity than those who did not.

Keywords : Group buying 1. INTRODUCTION Group purchase organizations (GPOs) came into being before the advent of the Internet or Web 2.0. For example, hospitals in the US form GPOs to aggregate their buying power and negotiate with vendors for discounts. Friends can have an important effect on group purchases by creating such benefits as enhanced shopping enjoyment and information acquisition (Mangleburg, Doney, & Bristol, 2004). Other benefits of GPOs for customers include increased bargaining power, feelings of empowerment and security, the opportunity to experience social interactions, and enhanced feasibility of the group purchasing process (Ramus & Nielsen, 2005).

Groupon is not the first website to offer group buying; MobShop and Mercata started similar businesses in the late 90’s. However, without Web 2.0 social networks, these companies could not stay in business. It is also worth noting that Groupon was not the first Web 2.0 group-buying website. In March 2004, a Taiwanese telnet-type BBS called PTT launched its group buying department, which currently completes more than 100 group buying transactions a day. Considering that the Taiwanese population is only 24 million, this volume is huge. In 2005, China’s group buying website Tuangou became popular. According to some reports, the company drove unprecedented bargains by combining the reach of the Internet with the power of the masses, and it has spread through China like “wildfire” (Economist, 2006). These Chinese predecessors differ from the American Groupon in the sense that they originated through online chat-rooms or indigenous BBS users rather than from firms or specific Internet platforms. People create the buying groups, become the group leaders, and target specific products. Anyone who reads the initiation notice can join a group. They do not even have to live at the same location or make purchases at the same time. In fact, the members may never meet one another. What brings them together is the grassroots power they can collectively wield to bargain with big firms.

After the Internet started, many businesses added online components as well as opportunities for group buying. Group buying websites use the Internet to provide traditional group buying, but the appearance of Internet social network services has caused group buying to take on new forms. For example, Groupon assembles local companies and offers one "Groupon" (group coupon) per day to customers in each of its


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iiSC2011 Proceedings method that increases the number of buyers who can obtain a given item better than traditional group buying schemes can.

Online group buying also benefits small and medium size sellers who cannot afford to expend large sums of money on the Internet. SMBs do not need to spend their marketing resources upfront. If they cooperate with online group buying sites and find enough interested customers, they can generate sufficient transactions to stay in business.

Kauffman and Wang explored the effects of using auctions as a group buying strategy. They specifically discussed bidding participation externalities (the number of new orders generated from an increase in the quantity of the original order) and the perceived price-drop effect (the increase in the willingness to bid when the bidder predicts that the price will suddenly drop, as opposed to when it actually drops) (R. J. Kauffman & Wang, 2001). There are two possible explanations of this effect: (a) the buying group may create more buyers, and (b) when buyers notice the price drops at previous group-buying sessions, they expect the price to drop in the next session as well; this leads them to join in the group buying.

The aforementioned importance of online group buying motivated us to study what makes it attractive to customers. We accept that equilibrium promotes efficiency in the economy, and we infer from this principle that group buying should be sustainable. Our research is based on a modification of the Unified Theory of Acceptance and Use of Technology (UTAUT). Our application of this model is described in Section Error! Reference source not found.. Section Error! Reference source not found. reports the methods of data collection and analysis, and our conclusions are stated in Section Error! Reference source not found..

In 2008, soon after the group buying business model appeared, Kauffman et al. conducted experiments that focused on three issues: risk, trust, and fairness (R. Kauffman, Lai, & Ho, 2010; R. Kauffman, Lai, & Lin, 2010). These issues are major concerns at the initial development stage of new business models, especially when the businesses are Internet-based (Light, 2001). When such business models become more advanced, they invent specific mechanisms to address these issues. For example, PayPal’s escrow service for online auctions has reduced trust and risk problems to the point that online auction sites such as eBay can prosper. When eBay came online in 1996, there were only 250,000 auctions there (Wikipedia, 2011a), but in 2010 eBay’s sales reached US$9,156.3 million (Hoovers, 2011). This enormous growth demonstrates that auctioneers do not see fairness as a problem that should cause them to avoid making transactions.

2. LITERATURE REVIEW AND MODEL FORMATION In this section, we begin by reviewing the literature on group buying and related topics. Then, we describe the appropriateness of Unified Theory of Acceptance and Use of Technology (UTAUT) for our research and our reasons for modifying it.

2.1 Group Buying The first problem one faces in studying group buying is the paucity of the literature. As Wei et al. stated, “In spite of this rapid growth, IGP (Internet Group Purchase) is nearly completely unstudied in scholarly circles, there being no academic research on how to manage IGP. Limited knowledge from non-academic commercial sources based on anecdotes and stories could mislead those who consider investment in IGP. Investors of this stripe seek more solid foundations for developing and managing IGP.” (Wei et al., 2011) For this exploratory qualitative study, Wei used collective cognition theory (Montealegre, 2002) to identify the cognitive processes that underlie group buying. The first stage of IGP, called the information accumulation stage, involves the creation of a group of consumers who generate, share, perceive, and store information about the product, its price, and its seller. IGP enables consumers to obtain information quickly from other consumers, resulting in more product knowledge and better product use. In the second stage, called the interaction stage, IGP members actively retrieve the information that was shared and stored during the first stage; then they utilize this information to either persuade other members to take certain actions or argue in favor of certain solutions. IGP can greatly reduce the uncertainties or risks associated with online purchasing. In the third stage, called examination stage, participants usually try to achieve consensus by negotiating with other group members or the seller. If they succeed, the group moves to the fourth stage, called the accommodation stage, during which all the information is integrated, and appropriate decisions are made and actions taken.

Whether the group-buying business model is yet sufficiently advanced is an open question. In any case, the rapid growth in recent years of Groupon and other group buying services may require that future research begin with strategies for the promotion of group buying. In particular, businesses want to know what makes people use online group buying so they can develop strategies to attract more users. In the next subsection, we explain how we developed our modified UTAUT model. Then we draw on our literature review to identify the key determinants of how much group buying services are used.

2.2 Research Model and Hypotheses The Unified Theory of Acceptance and Use of Technology (UTAUT) has been widely used in online behavioral research (Venkatesh, Morris, Davis, & Davis, 2003). We use UTAUT for the following reasons. First, the group-buying web services we study are human-computer interfaces; HCWe is the topic of TAM, which is the foundation of UTAUT (F. D. Davis, 1989). Second, the original UTAUT covers a wide variety of platforms including corporate systems and websites. Third, many studies have demonstrated the validity of UTAUT with excellent goodness of fit (R2). Finally, UTAUT has been applied to the study of what drives the acceptance of technologies, which corresponds to our research question: why do people engage in online group buying?

In addition to Wei, Tsvetovat and colleagues have shown how customer coalitions can become groups capable of procuring goods at a volume discount, thereby creating economies of scale among like-minded customers (Tsvetovat & Sycara, 2000). Yamamoto and Sycara cited the benefits of buyer coalitions in emarkets, which also allow buyers to take advantage of volume discounts (Yamamoto & Sycara, 2001). These authors proposed a

However, there are differences between UTAUT and our model:

2.2.1 Sociability When UTAUT was developed, most Internet sites were unidirectional: The site owners provided the content, stipulated the

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iiSC2011 Proceedings Gerard, 1955); (Burnkrant & Alain, 1975). Informational social influence refers to the conformity among team members that results from their belief that others’ interpretations of an ambiguous situation are more accurate than their own, thereby helping them choose an appropriate course of action. Normative social influence refers to "the influence of other people that leads us to conform in order to be liked and accepted by them” (Aronson, Wilson, & Akert, 2009). According to social impact theory, the more important the group, the closer the physical distance between the group and the self. The larger the group, the greater the likelihood that its members will conform to the group's social norms (Latané, 1981). In the group buying situation, if a buyer follows others’ interpretation or decision, and the buyer wants to belong to a certain buying group in order to enjoy steep discounts the next time, we can say that the buyer is trying to narrow the distance between the self and the group; in other words, the buyer is “conforming” to the group.

rules, and initiated the transactions. Today the Internet is composed of social networks. In addition to empowering buyers, the group buying sites in our study also provide for social interaction. Members are allowed to exchange ideas before, during, and after the transaction. Before the transaction they can share search results and recommend sellers, and during the transaction they can discuss what price to offer, how the product is to be delivered, and so on. After the transaction, they can post their reviews of the seller, the product, and the group leader. This social interaction gives buyers a better chance to complete the group formation. These are the reasons we need to include “sociability” in the model. This term, which was proposed by Goerg Simmel, refers to “all the forms of association by which a mere sum of separate individuals are made into a 'society' …. [through associations] the solitariness of the individuals is resolved into togetherness, a union with others[; that is] the free-playing, interacting interdependence of individuals.” (Simmel & Hughes, 1949, p.158) These features, which can be applied to common social network websites, are particularly applicable to group buying sites, where the buyers must depend on one another to achieve large-volume discounts. In other words, the buyers need to interact to increase their bargaining power and share information. They share a common goal, which is why it is necessary for them to unite.

We added conformity to our model as a moderator between intention and behavior. To justify this decision, we turned to Lascu and Zinkhan’s model linking conformity and consumer behavior (Lascu & Zinkhan, 1999). These authors specified three levels of conformity: compliance, identification, and internalization. Compliance is not applicable to our study because it refers to situations in which group members are monitored. Identification, on the other hand, is applicable, because it means that members follow the lead of the buying group to identify with the group so they can participate in group buying the next time. Internalization is also applicable; it means changing one’s behavior after changing one’s mind because of informational social influence.

Preece highlighted the importance of “understand[ing] how technology can support social interaction and design for sociability” for online communities (J. Preece, 2001). She previously identified three key factors that contribute to good sociability (J. Preece, 2000): Purpose: a community’s shared focus on an interest, need, information, service, or support that provides a reason for individual members to belong to the community.

2.2.3 Perceived playfulness The positive relationship between perceived playfulness and use of the Worldwide Web was identified by Atkinson and Kydd (Atkinson & Kydd, 1997). Following Lieberman (Lieberman, Mary, & Mary, 1977), they defined playfulness as “an internal personality trait [defined] as physical, social, and cognitive spontaneity; manifest joy; and a sense of humor.” Moon and Kim identified playfulness as a factor influencing the acceptance of technology on the Worldwide Web (Moon & Kim, 2001). Based on Csikszentimihalyi's flow theory (Csikszentmihalyi, 2000), Moon and Kim defined three dimensions of perceived playfulness: the extent to which the individual (a) perceives that his or her attention is focused on interacting with the WWW; (b) demonstrates curiosity during the interaction; and (c) finds the interaction intrinsically enjoyable or interesting. Enjoyment has also been identified as a factor influencing users’ adoption of a social network on the Internet (Hassanein & Head, 2005; H. Lu & Wang, 2008)(Klimmt, Schmid, & Orthmann, 2009).

People: members of the community who interact with one another and who have individual, social, and organization needs. Policies: the language and protocols that guide people's interactions and contribute to the development of folklore and rituals that bring a sense of history and accepted social norms. More formal policies may also be needed, such as registration policies, and codes of behavior for moderators. Informal and formal policies provide community governance. While analyzing PTT, one of the largest group buying sites in Taiwan, we found these three components to be represented as follows: The purpose of the site was clearly stated at the portal, followed by the policies that users must adhere to. The website is popular and interaction takes place continually. These components created sociability for PTT, and it became our research goal to investigate whether this sociability had an effect on the use of group buying sites.

2.2.4 Perceived risk avoidance Bauer introduced the concept of “perceived risk,” which refers to the fact that consumers characteristically develop decision strategies and ways of reducing risk that enable them to act with relative confidence and ease in situations where their information is inadequate and the consequences of their actions may be drastic (Woodside & Delozier, 1976). Bauer defined two components of the level of perceived risk: (a) the amount at stake in the purchase decision, and (b) one’s feeling of subjective uncertainty that one will win some or all of the amount at stake.

2.2.2 Conformity Asch discovered in an experiment that one third of a team’s members tended to follow the majority regardless of whether the majority decision was correct (Asch & Others, 1951). Allen labeled such effects as “conformity” (Allen, 1965). Although online communities may not impose “public compliance,” “private acceptance” is likely to occur because of “informational social influence” and “normative social influence” (Deutsch &

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iiSC2011 Proceedings Based on the model, we proposed the following hypotheses (see Error! Reference source not found.). In the questionnaire, “group buying” means online group buying.

Virtual stores are perceived to involve greater risk than bricksand-mortar establishments. When e-commerce was just getting started, this perceived risk prevented online stores from making money (Bhatnagar, Misra, & Rao, 2000). One cause of this perceived risk may be consumers’ concern about the security of transmitting credit card information over the Internet. Consumers may also be apprehensive about buying something without touching or feeling it, as well as not being able to return it if it fails to meet their approval.

Table 1. Research Hypotheses

t has been demonstrated that a consumer’s peer groups, reference groups, and significant others can offer social support and legitimize one’s purchasing decisions (Woodside, 1972). In a similar vein, online group buying may reduce the purchasing risks. First, it increases buyers’ bargaining power, enabling them to avoid being “ripped off” by the seller. Second, buyers in a group buying situation have the chance to share information about the product with other group members having the same goals and stakes. They also can ask whether the group leader has a conflict of interest with the seller. Third, the privacy of the group members can be protected; although sellers can identify the group leader, they cannot identify the other members. By adding these factors, we modified the UTAUT model as illustrated in Error! Reference source not found.. The new variables are shown in bold font. Performance Expectancy

H1

Users’ performance expectancy with regard to group buying leads to their intention to engage in group buying.

H2

Users’ low expectancy of effort in group buying leads to their intention to engage in group buying.

H3

Social influence leads to users’ intention to engage in group buying.

H4

Users’ perceived risk avoidance with regard to group buying leads to their intention to engage in group buying.

H5

Sociability on the group-buying site leads to users’ intention to engage in group buying.

H6

Users’ perceived playfulness with regard to group buying leads to their intention to engage in group buying.

H7

Facilitating features of the group buying site lead to users’ intention to engage in group buying.

H8

Users’ intention to engage in group buying leads to their use of group buying.

H8a

The influence of behavioral intention on the use of group buying is moderated by conformity, such that the effect is stronger for users showing the greatest conformity.

H1a

The influence of performance expectancy on intention to use group buying is moderated by gender, such that the effect is stronger for women.

H2a

The influence of effort expectancy on the intention to use group buying is moderated by gender, such that the effect is stronger for women.

H3a

Social influence on the intention to use group buying is moderated by gender, such that the effect is stronger for women.

H4a

The influence of perceived risk avoidance on the intention to use group buying is moderated by gender, such that the effect is stronger for women.

H5a

The influence of sociability on the intention to use group buying is moderated by gender, such that the effect is stronger for women.

H6a

The influence of perceived playfulness on the intention to use group buying is moderated by gender, such that the effect is stronger for women.

Effort Expectancy Social Influence

Behavioral Intention

Use Behavior

Intention to use

Perceived Risk Sociability Perceived Playfulness Conformity Facilitating Conditions Figure 1. Group Buying Acceptance and Use Model. The model has several other noteworthy features besides the new factors. First, the original UTAUT did not emphasize social and emotional factors; perceived risk avoidance, sociability, perceived playfulness, and conformity all have emotional elements. Second, the original UTAUT includes voluntariness as a moderator. These variables are not applicable to our research, as all our survey respondents were using group buying sites voluntarily.

2.3 The Survey The design of the questionnaire and the preliminary selection of items was guided by the literature review. The new variables described in Section Error! Reference source not found., as well as the measures of performance expectancy, effort expectancy, and social influence, were adapted from several sources (F. D. Davis, Bagozzi, & Warshaw, 1989; F. D. Davis, 1989; Moore & and Benbasat, 1991; Thompson, 1991; Venkatesh et al., 2003). The measures of facilitating conditions and behavioral intention

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E-COMMERCE AND E-BUSINESS CHALLENGES were adapted from these sources as well as from (Ajzen, 1991; I. Ajzen & Fishbein, 1975).

iiSC2011 Proceedings 3.4 Reliability and Validity Tests All the measures continued to show good reliability (Cronbach's α) in the main test. To test the validity of the dimensions, we began by applying the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy to determine if the scales were suitable for factor analysis (Kaiser, 1974). A KMO value greater than 0.8 means that the items have low partial correlations with the total scale of which they are a part; the obtained value was 0.83. We also applied Bartlett's sphericity test, which yielded p < 0.05. Thus, the scales are factorable by both criteria.

3. DATA COLLECTION AND ANALYSIS 3.1 Pre-test The questionnaire has three parts. The first part is a general survey on group buying that we used to screen inappropriate respondents from the test sample. Those who did not have online group buying experience were excluded. The second part of the questionnaire is shown in Error! Reference source not found.. The third part consists of demographic items, the data from which were used for F-tests to check the effects of demographic differences.

The factor analysis yielded 9 factors corresponding to the 9 psychological dimensions. This means that the constructs are valid..

The first step in the pre-test was to invite ten scholars with domain knowledge and extensive experience with online group buying to examine the above preliminary version of the questionnaire. Two MIS professors checked the internal validity of the questions, and three Ph.D. candidates helped them evaluate the questionnaire further. Five professionals were invited to check for ecological validity; i.e., whether the questions are really important for online group buying. All ten judges agreed that the questionnaire “can measure what it is supposed to measure” and that “all dimensions are essential to the evaluation of SNS and SNS games.” Thus, face validity and content validity were achieved.

We next conducted tests for convergent and discriminant validity. According to Fornell and Larcker (Fornell & Larcker, 1981), convergent validity is achieved when the following three conditions are met: (a) all the standardized factor loadings exceed 0.5, (b) the composite reliability (CR) is greater than 0.7, and (c) the average variance extracted (AVE) exceeds 0.5 (Fornell & Larcker, 1981). Convergent validity was achieved based on these criteria. According to Fornell and Larcker, discriminant validity is achieved when the square root of the AVE of a construct is greater than the correlation between that construct and another construct (Fornell & Larcker, 1981). Discriminant validity was achieved by this criterion.

We then put the questionnaire on Google Docs for the pre-test. Through personal connections with sites such as MSN, Skype, BBS, personal blogs, and Facebook, we recruited 82 respondents, 14 of whom submitted invalid questionnaires. The reasons for disqualifying the questionnaires were: (a) the same answer was given to each item; (b) at least one question and its reverseworded counterpart had contradictory answers, and (c) more than one questionnaire was submitted (as inferred from the same IP address). The sampling period was March 15 through March 20, 2010.

3.5 Hypothesis Testing Finally, we used maximum likelihood estimation to test the hypotheses listed in Section Error! Reference source not found.. Error! Reference source not found. shows the structural equation model for the path analysis and the results of the hypothesis tests. Table 2. Results of hypothesis tests

Cronbach’s α was used to assess the reliability of the scales composing the questionnaire (Hassanein & Head, 2005; H. Lu & Wang, 2008). Guilford has suggested that an α value greater than 0.7 means that the reliability is adequate (Guilford, 1965). Because reliability for all the scales met this criterion, all the items were retained in the final questionnaire.

Path

Coefficient

Performance Expectancy Behavioral Intention 0.42*** Effort Expectancy H2 Behavioral Intention 0.24*** Social Influence H3 Behavioral Intention 0.14** Perceived Risk H4 Avoidance Behavioral Intention 0.12*** Sociability Behavioral H5 Intention 0.29*** Perceived Playfulness H6 Behavioral Intention 0.02 Facilitating Conditions H7 Use Behavior 0.18 Behavioral Intention H8 Use Behavior 0.13 *** p 0.05), supporting hypothesis 4. In support of hypothesis 5, RA was positively correlated with adoption (r = 0.583, p < 0.05). SN was positively correlated with adoption (r = 0.743, p < 0.05), supporting hypothesis 6. . In support of hypothesis 7, age was positively correlated with adoption but weak (r = 0.15, p > 0.05). Education was positively correlated with adoption (r = 0.637, p < 0.05), supporting hypothesis 8. . In support of hypothesis 9, Income was positively correlated with adoption (r = 0.395, p < 0.05). Gender was positively correlated with adoption (r = 0.486, p < 0.05), supporting hypothesis 10.

6-C: Coefficients Model

Table 6: Summary, ANOVA and Regression Coefficients 6-A: Model Summary

1

R

R Square

Adjusted R Square

.910a

.829

.809

.264

Regression Residual Total

Mean DF Square

32.373

11

2.943

6.700

96

.070

39.073

107

F

Sig.

42.168

.000a

Error

(Constant)

-1.033

.304

Gender

.058

.064

Age

-.002

Income

Beta

t

Sig.

-3.393

.001

.048

.902

.369

.040

-.002

-.041

.967

.064

.032

.097

2.009

.047

Profession

-.007

.027

-.013

-.264

.792

Education

.113

.038

.162

2.958

.004

PU

.329

.062

.288

5.311

.000

PEOU

.092

.070

.075

1.322

.189

PC

.024

.038

.029

.636

.526

PCD

.191

.053

.171

3.631

.000

SN

.371

.061

.353

6.039

.000

RA

.140

.065

.117

2.164

.033

The AVOVA table reports a significant F statistic, which further justifies the appropriateness of the proposed model. The value of R square is 0.829 (see Table 6-A), which means that the proposed model explains approximately 82.9% of the total variance in the adoption of mobile banking. According to the standardized regression coefficients, the relative order of preference of the predictive factors over the adoption of mobile banking can be summarized as follows: Social norms (B= 0.353), Perceived usefulness (B= 0.288), Perceived credibility (B = 0.149), Education(B = 0.162), Relative Advantage (B = 0.117), Income (B = 0.097), and When t - test results pertaining to the significance of regression coefficients was analyzed, it is observed that the explanatory variables and their coefficients, SN (t = 6.039, p 000110101110110001101010001101110110001101111 001011100101010000011000111100101001110

D.

GENERATING A SERIES OF UPC BARCODES This model is developed to generate an itemized series of barcodes for a particular product and manufacturer.

E.

DEPICTION OF BARCODE AND SIGNAL SHAPE

(a)

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This simulation model is realized through a developed MATLAB function based on the theory of UPC technique. This function is developed to result the depiction the barcode and step signal of binary information. The output of this function m-file results as shown in Figure 5.

6. CONCLUSION Through this paper the author summarizes the extensive theory behind the UPC barcode. In the era of eCommerce and eBussiness the knowledge of UPC its application and scalability is essential for the developing countries. Keeping in mind author presents this work. How a prototype UPC system can be developed is the main theme of this paper. The paper discusses all the aspects of UPC methodology. How the binary and decimal symbols are related. How and why they differ with respect to occurrence of right hand and left hand sides. How the even and odd parity system is applied. How an effective modular arithmetic is used to calculate check bit of the information.

7. REFERENCES [1] http://www.uc-council.org/reflib/01302/d36-t.htm. [2] Brady, Thomas, “EAN Survey-” Uniform Code Council Internal Document, 2000. [3] Farighetti, Robert, ed., The World Almanac and Book of Facts 2000, World Almanac Books, 2000. [4] Uniform Code Council (UCC), Uniform Product Code (U.P.C.) Symbol Specification Manual, January 1986. [5] Carl A. Bredbenner, (2010) "Assessing the home food environment nutrient supply using mobile barcode (Universal Product Code) scanning technology", Nutrition & Food Science, Vol. 40 Issue 3, pp.305 – 313

Figure 5. Barcode and Step Signal Generation

[6] Capps, Oral, Jr., 1986. "The Revolutionary And Evolutionary Universal Product Code: The Intangible Benefits," Journal of Food Distribution Research, Food Distribution Research Society, vol. 17(1), February.

5. ACKNOWLEDGMENTS Thanks are due and acknowledged to Sultan Qaboos University (Sultanate of Oman) for providing research support grant (SQUDVC/ PSR/RAID/2010/23).

[7] E. B. Burger, M. Starbird, The Heart of Mathematics, Key College Publishing, 2000, pp. 89-90 [8] http://www.mathworks.com/help/techdoc/index.html

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Non-Technical Issues in the Adoption of Electronic Health Records by Doctors in Oman Abeer Al-Suleima Sultan Qaboos University Al-Khod Sultanate of Oman [email protected]

Muna Al mahrouqi Sultan Qaboos University Al-Khod Sultanate of Oman [email protected]

Hafedh Al-Shihi Sultan Qaboos University Al-Khod Sultanate of Oman [email protected]

Key words:

Oman, 2008). In keeping with His Majesty vision, all ministries in the Sultanate strived to apply information and communication technology in their operations. Ministry of health is one of the ministries that cannot afford not to utilize technology to facilitate its operations. One of the most significant achievements of ministry of health is the adoption of electronic health records in the beginning of the 1990 (Al Farsi and West, 2005). According to UNPAN (2010), several complications has been witnessed during the development and installation of the system. Non-technical barriers to adoption among potential users like doctors and nurses could not be explained since officials at the Ministry of Health thought the urgent needs for the system should drive acceptance. Several awareness and training campaigns has been carried out to smooth transition and users were indirectly forced to use the new e-health system. This study aims to investigate the non-technical barriers faced by doctors now in adopting one of the e-health systems in Oman. Our case study is the electronic health record system of the Hospital of Sultan Qaboos University which is called “Medtrack”. These systems has been applied to improve quality of healthcare, enhance productivity and organizational workflow efficiency, provide better information and improved communications, and protect privacy of patient records and to reduce cost.

Electronic health records (EHR) , ministry of health (MOH) , hospital information system(HIS)

2- LITERATURE REVIEW

ABSTRACT Oman is a developing country, moving rapidly toward a digital society in all government sectors. Health sector is one of the major priorities in e.Oman strategy. Information and communication technologies (ICT) are used mostly in all processes in the health sector. One of the most significant achievements of Ministry of health is the adoption of Electronic Health records system. This research paper addresses the non technical issues in the adoption of electronic health records by doctors in hospital of Sultan Qaboos university, which is the first and the only public university in the sultanate of Oman. Questionnaires and interviews were used as a mean to collect needed data for this research. A total of 100 questionnaires were distributed to patients chosen randomly, but 82% responded completely. In addition, three structured interviews were also conducted. The results indicated that there are considerable non technical issues in the adoption of electronic health records by doctors in Oman. The possible reasons are communication, resistance to change , privacy , security and training. These issues are needed to be properly addressed for the successful implementation of this system.

1- INTRODUCTION “The sultanate of Oman has embarked upon its ambitious journey in transforming Oman through the e. Oman strategy” (UNPAN, 2010) which was launched in 2002 and was implemented in May 2003”. His Majesty Sultan Qaboos`s vision in 2008 reads “Information technology and communications have now become the main elements that move forward the development process in this third millennium; therefore, we have accorded our attention to finding a national strategy to develop the skills and abilities of citizens in this domain with the aim of further developing e-government services. We are closely following the important steps that we have made in this regard. We call upon all government institutions to speedily enhance their performance, and to facilitate their services, by applying digital technology in order to usher the Sultanate into the constantly evolving spheres for applying knowledge” (The Annual Session of the Council of

Many scholars examined the technical issues in the adoption of electronic health records; however, there little attention was paid to the non-technical issues. In Oman, very few researches were done on the electronic health records and most of them discuss electronic health record in general, patients’ satisfaction and barriers to adopt EHR. There is no such research that examines doctors’ perception to electronic health records.

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Definition of electronic health records (EHR): Electronic health records is defined as “electronic record of patient health information generated by one or more encounters in any care delivery setting. Included in this information are patient demographics, progress notes, problems, medications, vital signs, past medical history, immunizations, laboratory data, and radiology reports” (National Center for Research Resources, 2006). Also it was defined as “a system that integrates electronically originated and maintained patient-level clinical information, derived from multiple sources, into one point of access” (Kazley , et al, 2010). It also has many common terms like electronic health records (EHR), electronic medical records (EMR), electronic patient record (EPR), and computerized patient record (CPR) (national center for research resources,


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2006). According to National Center for Research Resources (2006) electronic health record system has six main components. Firstly, Administrative System Components that is used in registration, admissions, discharge, and transfer (RADT) data. A laboratory system uses EHR as interface for its operations. Radiology departments use Radiology information components to match patient radiology data such as patient identification and his/her images. Pharmacy System Components used for filling prescriptions for patients. Computerized Physician Order Entry used to send orders to laboratory component, pharmacy component, and radiology component service. Finally, electronic clinical documentation systems enable clinicians to write notes; patient details; and medical reports (National Center for Research Resources, 2006). Electronic health records have many potential benefits. It plays a strong role in the reduction of operation cost as well as in the medical errors. It may also increase the quality of care (Hiller et al, 2010). Furthermore, it promotes patient safety and improves efficiency (Texas Department of Aging and Disability Services, 2009). Moreover, it improves communication, allow remote access (Zandieh et al, 2008) and productivity (Wilson, 1998).

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History of Electronic health records:

a-

History of EHR in the world The first EHR began to appear in the 1960s. In 1972, the first electronic health record (EHR) developed by Regenstreif Institute (NASBHC, 2010). In 1991, “the Institute of Medicine, a highly respected think tank in the US recommended that by the year 2000, every physician should be using computers in their practice to improve patient care and made policy recommendations on how to achieve that goal” (NASBHC, 2010). History of EHR in Oman MOH introduced the EMR in all health centers in the beginning of 1990 and it was only operated in some departments such as radiology and laboratory medicine (Ganesh et al, 2009). Sur hospital is the first hospital that had a fully integrated Electronic health records in 2000. In same year, the World Health Organization (WHO) categorized Oman as a “country with the most efficient health system in the world in terms of outcome” (Ganesh, et al , 2009).

b-

computer literacy” (Waston, 2006). Medical staffs have different attitudes and levels of satisfaction among these kinds of systems. According to the results of a survey used to asses attitude, knowledge and skills related to EHR, Staff scored a significant improvement in attitudes, knowledge and needs in using EHR over time (Beiter et al, 2008). Another survey was conducted to measure physicians’ willingness to adopt such systems. The result indicated that the physicians’ resistance to adoption has increased during the second period. Based on current levels of adoption, less than half the physicians working in small practices will implement an EHR by 2014 (47.3%) (Ford et al, 2008). The availability of well-trained doctors is another issue in the adoption of electronic health records. “In many developing countries, staff may be available but their skills may not be adequate for the tasks expected of them” (waston, 2006). In- service training is required in this situation to motivate doctors and help them to improve their computer based skills. All of these non -technical issues affect the quality of care. The National Ambulatory Medical Care Survey was carried out in the United States in 2003-2004 and concluded that “as implemented, EHRs were not associated with better quality ambulatory care” (Linder et al, 2007). Therefore, this research reported the non-technical issues in the adoption of Electronic health records by doctors in Oman. The main non-technical issues that will be examined in this research are communication between doctors and other medical staff, relationships between doctors and patients, privacy, resistance to change, security, training, and quality of care.

4- BARRIERS OF ADOPTION ELECTRONIC HEALTH RECORDS

Many barriers face the adoption of electronic health records which could be categorized into two main categories. They are financial barriers, and human-related barriers. In financial barriers, the main and common one is funding (Cherry et al, 2008). This finding is consistent with various studies and reports that identify implementation costs as the number one barrier to EHR adoption (Cherry et al, 2008). Human-related factors can also be an obstacle in the adoption of electronic health record systems. For instance, staff resistance to change, unfamiliarity with computers, and fear of computers and lower education are some of these factors (Cherry et al, 2008). Finally training is also considered an important obstacle in front of the adoption of electronic health records. Medical staff needs training to communicate with electronic health record system to achieve its core purposes.

3- NON- TECHNICAL ISSUES: The adoption of Electronic Health Records (EHR) is largely constrained by some non-technical issues that are hard to be resolved. Communication between medical staff (doctors, clinician, nurses …etc) is translated to communication between systems (Linden et al, 2009). This phenomenon affects communication between healthcare workers as well as relationships between them and their patients. Further, privacy and security are other critical issues. Everyone involved, including the patient, healthcare professional and the general population, needs reassurance that all data generated is maintained in a secure environment (waston, 2006). Authentication, authorization, integrity, confidentiality, semantic interoperability and author responsibility are important processes to ensure that Electronic health records system is secure. Also, patients` privacy should be addressed through Archiving and data retention processes (Linden et al, 2009). Moreover, some medical professionals resist the use of computer technology when attending to a patient. They prefer to write by hand, finding it difficult or uncomfortable using electronic means. “In many cases, however, the issue is not resistance to computer technology as such but a lack of

OF

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Example of EHR practices Implementation of some form of electronic health record has been achieved in a number of countries over recent years. Examples of a two EHR practices are as follows: In South Korea, eleven hospitals have implemented a full Electronic Medical Record. They include all inpatient and outpatient healthcare information. Another three hospitals have partially implemented an EMR system, for inpatients, data is entered at the bedside using a notebook computer and for outpatients, doctors input data at the point of care via computer terminals. Signed consent forms for treatment are scanned immediately after discharge and connected to the EMR as are

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letters from referring practitioners and hospitals. Some test reports which are produced from equipment not yet interfaced to the EHR are also scanned immediately after discharge enabling users to view them via a monitor. A goal of the hospital is to share information with all the national hospitals and public healthcare facilities but at present they can only share data with one branch of the hospital. The Australian Government is funding the implementation of a national health information network, called Health Connect which is a proposed network aimed at improving the flow of information across the Australian health sector. It is a system that includes the electronic collection, storage and exchange of patient health information via a secure network. The objective of this system is to improve the overall delivery and efficiency of healthcare. Also, to achieve better quality care and to achieve better patients` satisfaction. Under this system health related information about a person is documented in a standard format at the point-of-care. The information could then be retrieved online whenever it was needed and exchanged, with the patient’s consent, between authorized healthcare professionals. Other countries such as Singapore, Taiwan, Hong Kong and Thailand have also adopted electronic health records in one form or another with successful implementation.

One hundred questionnaires were distributed to patients from HSQU. However, the response rate was 82%. This sample was selected because they are affected by using this system and their feedbacks and suggestions are crucial. They were found to be from different regions in Oman and also from different ages, income, gender and level of education.

Additionally, the sample is ranked into five levels of education. The vast majority have bachelor degree (63%). Surveys also measured participants knowledge about using computers. The majority (89%) of the sample uses computer and most of them have Diploma degree and above. About 34% of them spend less than one hour daily using computers and only 7% of them spend eight hours and above in using computer every day. In the third section of the survey, non-technical issues in the adoption of electronic health record by doctors in Oman were investigated. About 46% of participants agree that doctors are good and skilled in using computers. His is in agreement with what the interview with HSQU HER expert revealed that doctors are trained to use the system and most of them are good and their technical skills improved over time. In addition, 54% of the patients reported that doctors spend long time in the treatment process mainly because of the electronic procedures in filling the details and treatment prescriptions. The interviewed doctor supported this and he said “EHR has increased the time needed to attend to patients”. Consequently, this has caused delay in receiving drugs from the pharmacy since most of time prescriptions are being printed and handed to patients. Importantly, the majority of survey participants supported the idea that electronic health record decreases the quality of care and distracts doctors’ attention from patients. However, they agree that the patient report and medicine prescription are easy to use and more organized. More than half of the patients see that electronic health record system eliminates medical errors, 67% of the patients agree that EHR protect patient privacy and 66% of them think it is secured. The interviewed IT expert approved this idea also and claimed that EHR main objective is to protect patent privacy. He gave an example that student of college of Medicine and Health Sciences in Sultan Qaboos University who now in fifth year have access to some parts of the system only. Additionally, 68% of the respondents agree that EHR minimizes the communication between the doctors and patients. Further, 65 % of them agree that EHR minimize the communication between doctors and other medical staff members. One doctor was interviewed and asked about this, she mentioned that sometimes her attention is distracted between what is needed to be done through EHR and the required level of communication with patients. Moreover, 80% of the surveyed patients and all interviewees recommended the need for proper training to be offered to doctors as well as other medical staff.

Interview

7- CONCLUSION

5- METHODOLOGY This study used a qualitative and quantitative descriptive design through interviews and questionnaire. The case study was Hospital of Sultan Qaboos University (HSQU) which has adopted electronic health record (EHR) systems since 1991. Interviews and questionnaires served to elicit new information about the non-technical issues to the adoption of HER in HSQU, barriers and benefits of EHR from doctor perspectives in Oman.

Questionnaire:

Three interviews in this research were conducted to collect data for the research. All of them are semi-structured interviews. The first one was conducted with fresh graduate doctor, the second with student from college of medicine about to graduate and the last interview was done with an expert in information systems looking after HSQU HER. The aim of these interviews was to seek different opinions from different stakeholders in the adoption of electronic health record.

Several issues have been found in the adoption and diffusion of EHR in Oman. Technical barriers could easily be managed if proper funding is attained. This study focused on the major dilemma with non-technical issues that not only affects the adoption of EHR but may also compromise patients care. Technology must been seen as a facilitator for better care and services. Doctors must be trained to balance their attention between patients and EHR. Higher priority must be given to patients, and EHR must be developed and designed with this in mind. This study found that non-technical issues in the adoption of electronic health records by doctors in Oman are privacy, security and quality of care, communication between medical staff, relationships with patients, resistance to change, integration and training. Moreover, it is found that the adoption of electronic health records system by doctors in Oman faces human-related barriers such as resistance to change. Also, lack of training and lack of IT skilled doctors and the digital divide

6- RESULTS AND DISCUSSION Questionnaires participants fall into 4 main categories of age. Half (50%) of them are between 15 to 25 years, 18% are between 26 to 35 and the same percentage for the ages from 36 to 45 and 14% are above 46 years old. In terms of income, 43% of them are having less than R.O. 200, 12% are between R.O. 201 to R.O. 500, 16% of the patent income is between R.O. 501 to R.O. 1000 and 18% of them have more than R.O. 1001.

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among patients and doctors also are considered as main barriers in the adoption of EHR.

8- REFERENCES:

EU Compared available: http://works.bepress.com/wade_chumney/1/

13- Patrick A Beiter MD, Jonathan Sorscher , Carol J Henderson and Mary Talen PhD , 2009 , Do electronic medical record (EMR)demonstrations change attitudes, knowledge, skills or needs? Available : http://www.ncbi.nlm.nih.gov/pubmed/19094409

1- Abby Swanson Kazley & Yasar A. Ozcan , 2010, Organizational and Environmental Determinants of Hospital EMRAdoption: A National Study available: :http://www.springerlink.com/content/0148-5598/

14- Stephanie O. Zandieh, MD, MS1, Kahyun Yoon-Flannery, MPH2, Gilad J. Kuperman, MD, Daniel J. Langsam, BA1, Daniel Hyman, MD, MMM2,5,6, and Rainu Kaushal, 2008 , Challenges to EHR Implementation in Electronic- Versus Paper-based Office Practices available : http://www.ncbi.nlm.nih.gov/pubmed/18369679

2- Anuradha

Ganesh, Abdullah Al-Mujaini, 2009, Electronic Medical Record System: Have we Bitten off More Than we Can Chew? Available :http://www.omjournal.org/Editorial/FullText/200901/Electroni cMedicalRecordSystem1-3.html

3- Barbara Cherry , Donna Owen, 2008, Determining Factors of Organizational Readiness for Technology Adoption in LongTerm Care Facilities

15- The annual session of the council of Oman, November,2008, Council of Ministers and the Council

16- The two Councils held a meeting on 31st May 2009. Available http://www.omanet.om/english/oman2009-2010/sec4_c.pdf

4- ERIC W. FORD, PHD, MPH, NIR MENACHEMI, PHD, MPH, LORI T. PETERSON and TIMOTHY R. HUERTA, PHD, MPA , 2008 , Resistance Is Futile: But It Is Slowing the Pace of EHR Adoption Nonetheless available: http://www.ncbi.nlm.nih.gov/pubmed/19261931

17- Texas Department of Aging and Disability Services , October 1, 2009 , Long Term Care Facilities Adoption of Electronic Health Record Technology: A Qualitative Assessment of Early Adopters’ Experiences available: http://web.ascp.com/advocacy/briefing/upload/DADS%20Final %20Report%2010.2009.pdf

5- Helma van der Linden, Dipak Kalra, Arie Hasman, Jan Talmon, 2009 , Inter-organizational future proof EHR systems A review of the security and privacy related issue.

18- http://www.sciencedirect.com/science?_ob=ArticleURL&_udi= B6T7S-4T9TC9S2&_user=912155&_coverDate=03%2F31%2F2009&_rdoc=1 &_fmt=high&_orig=search&_origin=search&_sort=d&_doca nchor=&view=c&_searchStrId=1539281983&_rerunOrigin=s cholar.google&_acct=C000047883&_version=1&_urlVersion= 0&_userid=912155&md5=f7428962ea808c1cf4cda1e684f6743 9&searchtype=a

6- Janine Hiller , Matthew S. McMulle, Wade M. Chumney and David L. Baumer , 2010 , Privacy and Security in the Implementation of Health Information Technology (Electronic Health Records):U.S .and EU Compare available: http://works.bepress.com/wade_chumney/1/

7- Jennifer Fisher Wilson , 1998 , How benefits can outweigh costs of electronic records available : http://www.providersedge.com/ehdocs/ehr_articles/How_Benefit s_Can_Outweigh_Costs_of_Electronic_Records.pdf

19- UNPAN, 2010. Online Document.[online] Available at: [Accessed, 10 October 2010 20- http://www.omanet.om> [Accessed 23 October 2010 ]

8- Jeffrey A. Linder, MD, MPH; Jun Ma, MD, RD, PhD; David W. Bates, MD, MSc; Blackford Middleton, MD, MPH, MSc ; Randall S. Stafford, MD, PhD , 2007 , Electronic Health Record Use and the Quality of Ambulatory Care in the United States available : http://www.ncbi.nlm.nih.gov/pubmed/17620534

21- http://www.nasbhc.org/atf/cf/%7BCD9949F2-2761-42FBBC7ACEE165C701D9%7D/TA_HIT_history%20of%20EMR.pdf

9- National Institutes Of Health National Center for Research Resources, April2006. Electronic Health Records Overview. P:1. Retrieved from:

10- National Center for Research Resources, 2006, electronic health records available: http://www.ncrr.nih.gov/publications/informatics/ehr.pdf

11- Mohammed Al Farsi · Daniel J.West Jr.,2005, Use of Electronic Medical Records in Oman and Physician Satisfaction available: http://www.springerlink.com/content/n5547n1wm4741l40/

12- Privacy and Security in the Implementation of Health Information Technology (Electronic Health Records):U.S .and

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The Uptake of Voting Participations in Oman through E-voting Muneera Al Siyabi Sultan Qaboos University Al-Khod Sultanate of Oman [email protected]

Noora Al Jabri Sultan Qaboos University Al-Khod Sultanate of Oman [email protected]

Hafedh Al-Shihi Sultan Qaboos University Al-Khod Sultanate of Oman [email protected]

This research paper comes at same time with implementing an e-voting in Oman which was launched on March, 2011(Oman, 2011). Our study aims basically to investigate the feasibility of e-voting system in Oman. It identifies how the e-voting will increase the percentage of participation. Moreover, it investigates some non-technical barriers of adopting e-voting. In addition, it explores the factors that stimulate Oman to decide using e-voting.

ABSTRACT Oman is embarking into a new digital era where e-government is a vital subset. The government continuously encourages ministries to adopt best IT practices to facilitate their internal and external operations. The newest initiative was announced by Ministry of Interior and was named electronic voting despite its dissimilarities with standard international e-voting systems. Latest statistics from Ministry of Interior in Oman showed modest participations from citizens in the elections of Shura Council. Several public figures attribute this to the cumbersome and hectic process of elections which is done through governors’ offices. A true e-voting system is therefore seen crucial to the uptake of citizens’ participations in Shura Council elections. This paper explores the factors that hinder citizens in Oman from participating in the elections. It also surveys the feasibility and limitations of e-voting systems in encouraging more citizens’ participations. For this, several interviews were carried out with key staff in related organizations in Oman, and questionnaires were distributed to many citizens. It has been concluded that a robust e-voting system in Oman is vital to the uptake of elections participations. In addition, it will also aid in combating dishonesty and promoting fair voting process.

2- E-VOTING: OVERVIEW Several resources in the literature present detailed definition of e-voting. Bumgale and Sridhar (2003) defined electronic elections as “the use of computers or computerized voting equipment to cast ballots in an election". This definition is used specifically to refer to the voting process that takes place over the Internet. Johnson (2006) on the other hand describes evoting channels as "the use of the Internet as a medium for democratically selecting political leaders". Another definition of e-voting stresses on "the use of software and hardware to facilitate voting by individuals from either remote or poll-specific locations through a computer information system for casting votes" (Lippert and Ojumu, 2008). In brief, evoting is about utilizing information technology (IT) to capture, store and process citizens votes.

Key words: e-voting, trust , transparency, privacy

Electronic voting has raised a lot of arguments today. To start with, security is believed to be a significant issue to e-voting adoption. According to (Lee, 2008), e-voting systems should be protected not only from outsiders but even some insiders such as system administrators might impose some potential threats. The voting system should be more accurate and secure to increase the integrity of electoral processes, by keeping all the votes secure from any fraud or counterfeit (Everett, 2007). Trust is ana critical issue to the uptake of e-voting systems. E-voting is an egovernment application that require considerable amount of citizens trust. Besides, several studies have indicated there is a relationship between citizens' trust with their governments and the level of participation in e-voting. Higher levels of trust in governments will be affected positively to the citizens' interest of using e-voting system (Carter and Schaupp, 2005).

1- INTRODUCTION Although e-voting might thought to be a recent trend, some scholars attribute its root to 1960s when the United States started implementing electronic recording (Kim, 2008). Since then, Democracies around the world always struggle to facilitate and secure the voting process to enhance participations and avoid breaches. Several e-voting systems have been offered as a means to serve this purpose. Oman has implemented the Shura Council back in 1991 which is considered "the parliament council in Oman and its members are elected directly by the citizens from different regions according to the specific rules"(Ministry of Information, 2009). Citizens participation in the voting process were seen low compared to the total number of population and several redundant votes were observed. This stresses the need for a revamped voting channel to enhance adoption and security.

E-voting: Examples Advanced nations and developing countries have adopted evoting to speed up the electoral processes. This section describes some authorities that have implemented electronic elections around the world.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission from iiSC.

United States of America (USA) According to Blanc (2007), the use of e-voting systems has expanded in United State since 2000 elections from 12 percent

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to 29 percent in 2004. Since then, the government in the United State conducted the elections in several ways one of which is through electronic channels. Despite, several complications were found. For example, in election 2000 the e-voting system was damaged and as a result all the information about votes and voters were lost. In addition and according to Al-Asfar (2004), during election 2000 the e-voting devices that were used were connected to the companies that have developed the system. Accordingly, the system was seen exposed to officials in those companies which raised concerns about possible manipulation of the votes.

3- METHODOLOGY Surveys and interviews are the main data collection methods used in this study. Questionnaires were developed with the main question in mind “will e-voting increases Omanis participation in the election process?” The questionnaires were distributed randomly to 70 Omani citizens who are allowed by law to vote from two town areas in Oman; Barka and Bidied. The questionnaire was structured in several sections. The first section was for the profile of the respondents. It contains questions about their age, gender, work aspects, income and education levels. The second section was about their computer usability skills. It contains questions that measures participants’ ability to use the e-voting system. The third section was about the reasons that prevent/encourage Omani citizens to vote and the last section surveyed participants opinion on major barriers of the e-voting system found in the literature.

Australia Australian voters were first introduced e-voting system in October 2001 election and then it was used again for parliamentary process in October 2004 (Lippert and ojumu, 2008). According to the same source, e-voting in Australia uses personal computers that are connected to the voting centers. These computers are connected to secure servers in each polling location. Besides that, the citizens are not allowed to vote over public networks for security reasons.

Semi-structured interviewed were conducted with the following government officials to survey government plans and get comments on surveys results:

Bahrain Bahrain is another country that has taken some steps to change the elections process from manual to electronic way. According to Kostopoulos (2003), "the Kingdom of Bahrain has been the first to introduce e-voting system. During February 14-15, 2001, the 200,000 Bahraini voters participated in referendum where they had the opportunity to express their position in a variety of national issues". The kingdom has implemented e-voting system hoping to achieve better security, saving costs and time, enhancing accuracy and encouraging the citizens’ participation.

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E-voting in Oman: Overview Oman is one of the countries that have taken a big step in egovernment field. As e-voting is one of the e-government aspects, Oman have decided to implement similar system by 2011 (Ministry of Information, 2009). According to the same source, Shura Council was established to engage Omani citizens in the democratic process and at same time to study the requirements of the society in order to enhance the social and economic development. Currently, "the Shura Council is composed of 84 members selected as representatives of the States (Ministry of Interior, 2009). According Al-Abaidi (2007), in Shura Council elections 2007 there were 631 candidates including 21 women and the number of registered voters was 388,684 voters (out of more than 2 million population), while the total number of polling stations was 102 which were distributed in 61 election centers. It is clear that the total number of voters compared with the total number of population at the same year is very low. The tribal conflicts are believed to be one of the biggest reasons behind the declining voting proportion as voters only vote for candidates from their own. This makes citizens with no candidates running for election from their own tribe reluctant to participate. In addition, AlAbaidi (2007) stresses that lack of awareness about the importance of election is another reason that contributes to the declining voting percentage.

The analysis of the questionnaire showed some interesting findings. Seventy people took part in this survey and the response rate was 100%. To begin with, of the 70 survey participants, 41 were men and 29 were female; 38.5% of the male respondents had a college degree, and 20% indicated that they had a high school diploma. In comparison to the female respondents 10% reported that they had a high school degree and 31.4% of them having a college degree. The average age of all the participants was in a range from 31-40 years. Tables (1) and (2) summarize the age and income profile data of the respondents.

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The Director of electoral register in the Ministry of Interior. Administrative clerk in Walli of Bidbid Office. Official in the Ministry of Interior.

Several other government officials with similar exposure on the voting process in Oman were approached but access was refused.

4- FINDINGS

Age

Total

Percentage

21-30

34

48.6%

31-40

22

31.4%

41-50 0ver 50

8 6

Total 70 Table1: Age Profile data of the sample

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11.4% 8.6% 100%

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iiSC2011 Proceedings respondents indicated the tribal conflicts are considered the main reason of retreat the voting proportion. Fifty-three percent of them gave this reply.

Income

Total

Percentage

Less than 200 OMR

4

5.8%

200-500 OMR

22

31.4%

More than 600

36

51.4%

8 No job Total 70 Table1: Income Profile data of the sample

Issues of e-voting were the last section of the questionnaire. Most of the respondents confirmed that the e-voting system will enhance the citizen’s trust in their government since this was considered one of the issues in some countries. This was the opinion of fifty- seven respondents (81%). In addition, the participants in this survey were asked if the electronic election will provide results without any manipulation or counterfeit; a little over half (51%) responded yes while 49% said no and it is clear the difference between the two is slight. Privacy is another issue of e-voting system. The vast majority of respondents (93%) indicated that e-voting is a technology that will maintain the privacy either for voters or candidates and just 5 out of 70 respondents (7%) disagreed with this point. Finally, many respondents which represent (70% of the total sample) confirmed that the e-voting should complement the current manual process not to substitute it.

11.4% 100%

The next section of the questionnaire was about the usage of the computer. The main reason of including this section in the questionnaire is to measure the respondents' readiness to use computer applications as an indication of their eligibility to participate in e-voting or not. Moreover, the study respondents were asked if they have used computer before: 91.4% responded yes and only 8.6% said no. The average number of hours that the respondents spent on using computer was more than three hour per day which represents 40% of the sample. Table (2) shows the time spent in using computer in more details. Hour Frequency Percentage Less than 1 hour

17

24.3%

1-2 hour

14

20%

3 hour

5

7.1%

More than 3 hour

28

40%

Not use

6

8.6%

5-

DISCUSSION

Many people in Oman thought that Omani women will not be willing to participate in e-voting because of some cultural concerns as some segments of the society believe that women should work only at home and others reject the idea that women go out to polling places to participate, but the survey results shows the opposite. The study indicated there was a slight difference between male and female and their intention of using e-voting technology. The study found a strong association between age and the willingness to use e-voting which illustrate a good opportunity for any future e-voting system in Oman. Old respondents (more than 50 years old) have been found not willing in general to participate in e-voting comparing to the younger respondents. This might be attributed to their technology illiteracy which goes in agreement with Lippert and Ojumu (2008) findings that the degree of individual acceptance technology will affect positively or negatively to participate in e-voting.

Total 70 100% Table2: Hours spent per day of using computer The following section of the questionnaire was about e-voting system and the respondents of the study were asked if they have participated in Omani elections previously, their answers differed slightly: 48.6% responded yes while 51.4% said no. The respondents also, indicated that they knew about e-voting system (18 of the respondents said Yes when asked about evoting system which represents 25.7% of total sample). On the other hand, 74.3% (52 respondents) stated that they never heard about this system. Clearly, the difference between the percentages is high. Another significant finding of this survey was that most of respondents agreed that e-voting will increase the Omanis’ participation rate in elections. This was the opinion of (77%) of them. Interestingly, most of the respondents (80%) said they have willingness to use electronic elections when it begins to apply; 47% of males said yes, whereas just one third (33%) of females gave same response. Regarding the reasons of preventing people from participating in Shura Council elections, approximately half of the respondents (48.5%) reported that the crowded polling location was a reason for not participating in elections. Furthermore, many respondents stated that incompetent running candidates were a reason that makes the participants reluctant from participation. Sixty-four percent of the respondents said this. Finally, just over half of the

The study revealed that most of the respondents did not hear about e-voting before and this will become as one of the issue that might prevent people from participating in this system. This finding is in line with what an official of ministry said “the lack of media campaign to educate people about the importance of Shura Council and e-voting system is one of the issues that reduce the participation proportion in voting.” In addition, the results of the study found that the citizens’ trust in their government does not significantly affect citizen’s participation in electronic elections. An interesting fact compared to similar studies in the literature which showed otherwise. Perhaps this is due to citizens reluctance in Oman to express their level of trust in the government publicly. Security in the other hand was found not a big issue of e-voting in Oman. Lack of participants knowledge about e-voting systems in general and Oman’s plans to implement an e-voting process make it hard for participants to decide. In addition, the announced e-voting system in Oman is planned to utilize ID cards with smart chips to enhance security and privacy. This

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must have assured some segments of the Omani society about the security procedure.

8. 9.

Other key findings were that participants thought in general that e-voting will achieve the transparency and credibility of the voting results. This finding reflects what the director of electoral register in the Ministry of Interior said “through the fingerprint and identity card we can make sure that the same person cannot vote twice”. In addition, the majority of respondents agreed that e-voting will maintain the privacy of both voters and candidates since in previous elections, there was incidents where voters profile were breached. This is also in agreement to what the official in Ministry of Interior indicated that the “system will prevent diversion of information”. Finally, the study revealed also that respondents see the e-voting should be as complementary to the current system.

10.

11. 12. 13.

6- CONCLUSION

14.

It is clear that a true e-voting system in Oman is needed where voters can freely cast their votes online. It is also recommended that candidates should start utilizing online channels to reach possible voters regarding their plans and programs. Currently the voting process is cumbersome and hectic and only few segment of the Omani population is willing to vote. In general, there is an indication that good percentage of voters is extrinsically encouraged to vote by some financial/tribal influence. Hence, awareness and educational campaigns about the true purpose of Shura Council and its future implications on the success and development of the country must be introduced.

15. 16.

17.

18. 19.

7- REFERENCES 1.

2.

3.

4.

5.

6.

7.

Al-Abaidi, M.(2007)." Al-Shwra Elections In Oman Sultanate October 27,2007"[Online] Avialiable at : http://www.regionalstudiescenter.net/site/arabic_home.htm [Accesed 6 Novenber 2010]. Al-marzooq, K.(2009). "E-voting non beneficial to the electoral process and political experience". Available at: [Accessed 07 November 2010] Al Amer, M. (2009). " Electronic Democracy Strategy For Bahrain". A Thesis presented to DE MONTFORT UNIVERSITY. No. ,pp.207. Al-arabia.net, 2010. Sultanate of Oman will apply the electronic voting in the upcoming elections.Alayam [online] 23 October 2010. Available at: http://www.alayam.com/Articles.aspx?aid=18073 [Accessed 23 October 2010]. Al-Asfar, A. (2004). Electronic Elections risks [online] 23 March 2004. Available at: < http://www.aawsat.com/sections.asp?section> [Accessed 07 November 2010] Al-Rashed, A.(2006). "Bahrain against the electronic elections".[Online] 3 October 2007 Avaliablea athttp://www.aawsat.com/sections.asp?section [Accessed 07 November 2010]. Oman newspaper, 2011."To run and vote in the election Shura unconditional install the system in the e-ID card”. [Online] 04 January, 2011. Available at: [accessed 05 Januray, 2011].

Blanc, J, 2007. Challenging the norms and standard of election administration: Electronic voting. pp.11-19. Brweez,S,2001.Electronic voting,[online] 15 February 2001. Available at: http://aceproject.org/ace-ar/topics/et/ [Accessed 20 October 2010]. Buchsbaum. T.(2004). E-Voting: International Developments and Lessons Learnt: Gesellschaft fur Informatik, Bonn: http://subs.emis.de/LNI/Proceedings/Proceedings47.html Bungale, P. & Sridhar, S.(2003). "Electronic Voting - A Survey".pp.1. Dennis,A., Wixom, B., Roth, R. (2006), “System Analysis & Design”, John Wiley & Sons . Department of Economic and Social Affairs.( 2010)."United Nations E-Government Survey 2010 Leveraging e-government at a time of financial and economic crisis", pp.77. Everett, S.(2007)." The Usability of Electronic Voting Machines and How Votes Can Be Changed Without Detection".pp.27. Gritzalis, D.(2002)." Principles and requirements for a secure e-voting system".No.6,pp. 539-556. Hernon, P., Romena, C. and Relyaa, H.(2006)." Comparative perspectives on e-government. Serving Today and Building for Tomorrow". Lanham, Mayland.Toronto, Oxford. Kim, H. (2007). " Development and application of a framework for evaluating multi-mode voting risks".pp.121135. Kostopoulos, G. (2003). " E-Government in the Arabian Gulf: A vision towards reality ". pp. 622-631. Lai, J. Lin, C., Yang, C.(2008). " Design and Implementation of an Electronic Voting System with Contactless IC Cards".pp. 1-2.

20. Lippert,S . and Ojumu,E, 2008. Thinking outside of Ballot Box: Examining Public Trust in E-Voting Technology. Journal of Organizational and End User Computing, No:20, pp.85. 21. Ministry of Information, 2009. The Omani shura.[online] Available at: [Accessed 23 October 2010 ] 22. Mamia .T“ QuantitativeResearch Methods”: General studies / ISSS 23. Milne.J. “QUESTIONNAIRES: SOME ADVANTAGES AND DISADVANTAGES”: Evaluation Cookbook, pp:52. 24. Ministry of Interior, 2009. A'shura Councel [online] Available at: [Accessed 07 November 2010] . 25. Owens.L (2002). “INTRODUCTION TO SURVEY RESEARCH DESIGN”: Seminar Series pp: 1-18. 26. Ulin, P, Robinson, E. and Tolley, E. (2004) Qualitative Methods in Public Health: A Field Guide for Applied Research, 2004. 27. Neuman, G. (1999) First-Hand Report: The New Kuwaiti Parliament Gets Down To Business, Middle East review of International Affairs, [Internet] available at: http://meria.idc.ac.il/news/1999/99news10.html#FIRSTHAND [Accessed 28Decesemer2010]

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Differentiated eLearning: the possible approaches Virendra Gawande Sur College of Applied Sciences, Ministry of Higher Education, PB – 484, PC – 411, Oman. Tel: +968 9224 1948

[email protected]

Differentiation usually includes one or more of the following areas:

ABSTRACT In differentiated instruction (aka differentiated learning), the curriculum adjusts to fit individual learners or groups of learners, whether in the classroom or online. It is an approach to teaching that acknowledges people having multiple paths for learning and for making sense of ideas. Differentiated instruction has been popular in the schools in the last decade, and picked up many dedicated advocates, and eLearning fits right in because technology can make curriculum adjustments easy to do. This paper outlines some possible strategies or approaches for differentiation in eLearning, may also be referred to as e-diff.

A. Content

Keywords e-diff, differentiated learning, differentiated instruction, content, process, product.

B. Process

1. INTRODUCTION Differentiated instruction (or differentiated learning) involves providing students with different avenues to acquiring content; to processing, constructing, or making sense of ideas; and to developing teaching materials so that all students within a classroom can learn effectively, regardless of differences in ability. Research indicates that many of the emotional or social difficulties gifted students experience disappear when their educational climates are adapted to their level and pace of learning." Differentiation in education can also include how a student shows that they have mastery of a concept. This could be through a research paper, role play, podcast, diagram, poster, etc. The key is finding how your students learn and displays their learning that meets their specific needs. By using differentiated instruction, educators can meet all individual student needs and help every student meet and exceed established standards (Levy, 2008). According to Tomlinson (as cited by Rebora, 2008), the perceived need for differentiated instruction lies in the fact that students vary in so many ways and student populations are becoming more academically diverse.

Is “what” students learn Includes curriculum topics or concepts Reflects state or national standards Presents essential facts and skills Differentiates by pre-assessing student skills and understandings, then matching learners with appropriate activities Provides students with choices in order to add depth to learning Provides students with additional resources that match their levels of understanding

Is “how” students learn Refers to how students make sense or understand the information, ideas, and skills being studied Reflects student learning styles and preferences Varies the learning process depending upon how students learn

C. Product

Is the end result of student learning Tends to be tangible: reports, tests, brochures, speeches, skits Reflects student understanding Differentiates by providing challenge, variety, and choice

1.1 What is Differentiation Instruction? In this context when differentiation is discussed, it is not about product differentiation by learning delivery location, as in hybrid eLearning content compared to fully online courses and/or cyberschools (National Leadership Institute, 2005). Nor is it about differentiation in time, as in synchronous and asynchronous learning. Rather, in e-diff, one of three types of adjustment is usually involved (Hall, 2002; Reis et al., 1988; Sizer, 2001; Tomlinson, 2001; Tomlinson & Allan, 2000; Tomlinson & McTighe, 2006; Willis & Mann, 2000):

A. Differentiation of content Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission from iiSC. iiSC’11, October 11–12, 2011, Muscat, Sultanate of Oman. Copyright 2011 iiSC ISBN: 978-9948-16-253-7

Offering students the chance to start at different places in the curriculum and/or proceed at different paces.

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iiSC2011 Proceedings learning activities or modules, or can allow much more range of choice. The courseware design determines where choice points are. Self differentiation is also very common in online content.

B. Differentiation of learning style approach Emphasizing many modalities of learning style or learning preference, such as visual and auditory learners.

C. Differentiation of product Giving different assignments to different students, and turn in different work products.

c) Naive differentiation Comes about almost inadvertently in many eLearning products. It involves changing portions of content in a more random way, not based on the specific needs of individual students, but simply rotating content and graphics so that screens have different images, representations and so forth each time viewed. This might involve a randomizing factor or a shuffle function. Though diffuse and self-directed strategies can be quite consistent with improved learning objectives of differentiated instruction, it can be harder to make the case for naïve differentiation. Gains in motivation and engagement as learning displays change, for instance, are hard to argue for if the same student only sees one of the displays.

2. DIFFERENTIATION IN ELEARNING Technology to make content change on the fly is quite simple online. It can be as straightforward as html coding and back-end databases. The challenge is not in the delivery technology itself, but in establishing good logic for differentiation — if we are going to differentiate, how do we decide who gets what? Here we organize the most common e-diff strategies, based on what type of decisionmaking process and evidence is used to establish the adjustment choices. Approaches can also be combined, or blended, in eLearning products. Some of the possible general approaches are: “Diffuse” approaches to differentiation, in which students receive the same content but have multiple opportunities for learning and are provided with different approaches for making sense of ideas planfully “diffused” throughout the content. Self-directed approaches, in which students receive different content by a mechanism of self-selection built in the content. This introduces differentiation through student choice. Naive differentiation, in which the computer is determining the course of differentiation, not the user, no specific plan or overall strategy is in place in the eLearning content for why differentiation is happening, or what it is intended to mean in the learning context. Boolean differentiation, in which software uses types of Boolean logic, such as rule-based frameworks or decision trees, to determine how to adjust content for different students. Model-based differentiation, in which expert opinion is combined with a variety of data mining techniques to generate ideas for how content might be appropriately differentiated. Language based differentiation, in which the students from different cultural backgrounds and different language skills can be benefitted. This is based on the differentiation in the contents of materials to be delivered by language.

d) Boolean differentiation Uses assessment evidence to change the flow of content for different students. Boolean here simply describes logic that computers use to determine if a statement is true of false. Main boolean operators include “and,” “not” and “or.” Operators get used with a series of rules to describe what happens with the content as students make their responses. There are many distinctions among different rule-based methods, including various planning agents, bug bases and chaining algorithms. But the idea is that a set of rules have been devised, often by very carefully studying many students. These rule-based boolean methods make up some of the oldest forms of e-diff. The simplest types look like a checklist of learning objectives. Students go down the list and complete the objectives. If they successfully complete 1 AND 2, they go onto 3, for instance. But 1 and NOT 2 and maybe the student is redirected to 2A, or given some additional feedback or other learning intervention that passing students don’t get. Rule based methods can take much more elaborate forms, and have been in very fine-grained ways to describe the multitude of conceptions and misconceptions students hold in certain subject matter areas, and what to do about them.

e) Model-based differentiation Is actually a large family of approaches that will be grouped together here for the sake of discussion. Some of the approaches are among the newer e-diff forms and others have been around for some time. Most use some form of expert opinion, including from teachers and other subject matter experts, combined with data mining to generate ideas about how content might be differentiated. Common data mining techniques include a variety of regression and Gaussian statistical models, Bayesian networks, neural networks, item response models, and mixed method approaches that combine quantitative and qualitative data to make interpretive or generative predictions.

2.1 Differences in the Approaches a) In diffuse differentiation There is no direct intention to assess or match the needs of individual users, or to customize content or feedback, as all students receive the same content. But enough variety and different sources of stimulation are provided to interest and engage diverse audiences. This is a very common approach to differentiated instruction in a traditional classroom teaching setting. The hope is that with enough variety provided, everyone’s needs can be addressed.

f) Language-based differentiation

b) Self differentiation Allows students to select their personal choices as they work their way through online content. This can consist of simply selecting the order of completion among a fixed menu of

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In which the same contents are provided to the students in different possible languages of understanding. This strategy is more related to the content repositories where we need to have

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the contents in different languages, or use some technology which may assist to convert from one language to another. On the plus side, data mining approaches can be faster and easier than deriving complex rule-based forms. However, the question often is which model to use, and why. Also crucial in the case of eLearning is whether the model really is doing an appropriate job of telling you something about students.

3. CONCLUSION Developers are building more differentiation into eLearning products, acknowledging that people have multiple paths for learning and for making sense of ideas. But differentiation via technology is complex. There are numerous approaches that have quite different implementations and results, as can be seen by the general strategies described here. As the field matures and developers explore more ways to differentiate online, it is important that non-disclosure agreements and other intellectual property issues don’t shut down the conversation about what these products are doing, and how they are doing it. So, sure, let’s all be different — but let’s find some common ground to talk about these important approaches to differentiation online.

4. REFERENCES [I] Hall, T. (2002). Differentiated instruction. Retrieved November, 2006, from http://www.cast.org/publications/ncac/ncac_diffinstruc.html [II] Parshall, C. G., Stewart, R., Ritter, J. (1996, April). Innovations: Sound, Graphics, and Alternative Response Modes. Paper presented at the National Council on Measurement in Education, New York. [III] Reis, S. M., Kaplan, S. N., Tomlinson, C. A., Westbert, K. L., Callahan, C. M., & Cooper, C. R. (1988). How the brain learns, A response: Equal does not mean identical. Educational Leadership, 56(3). [IV] Tomlinson, C. A. (2001). How to differentiate instruction in mixed-ability classrooms (2nd ed.). Alexandria, VA: ASCD. [V] Tomlinson, C. A., & Allan, S. D. (2000). Leadership for differentiating schools and classrooms. Alexandria, VA: ASCD. [VI] Tomlinson, C. A., & McTighe, J. (2006). Integrating Differentiated Instruction +Understanding by Design: Connecting Content and Kids. Alexandria, VA: Association for Supervision and Curriculum Development. [VII] Turker, A., Görgün, I., & Conlan, O. (2006). The Challenge of Content Creation to Facilitate Personalized E-Learning Experiences. International Journal on ELearning, 5(1), 11-17.

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iiSC 2011 Proceedings

Predicting Consumer Buying Behavior Pattern using Classification Technique Boumedyen Shannaq

Kaneez Fatima Sadriwala

College of Economics Management and Information Systems University of Nizwa, Sultanate of Oman, 99125782

College of Economics Management and Information Systems University of Nizwa, Sultanate of Oman

[email protected]

[email protected] at least some departments. By delivering a better customer experience retailer can improve the conversion significantly. For some retailers, however, it is hard to fix what is not seen or understood. Figure 1.1 below shows the conversion rate for various types of retailers [2].

ABSTRACT Psychology plays a crucial role in marketing; the mind of the customer must be properly attuned or brought into proper agreement to affect the sale. The sale thus, really takes place in the mind of the customer. If the buying pattern is known it can be associated with product positioning and assortment, which may result in satisfying more customers and high conversion rate. This work studies the buying behavior of the customers and highlights the combination of products and patterns of purchasing. The major objective of this paper is to generate list of product combinations which are associated with buying pattern. The ‘classifier’ software technology helps in building association rules regarding the consumers’ mind set. For this purpose instances and attributes pertaining to a particular market have been studied. By applying J48 classifier some rules have been generated. This research paper shall be useful for retailers and marketers in planning their marketing strategy. They can plan better product assortment, product positioning and placement so as to better serve the customer resulting in high purchase conversion rate. It will also assist the customers in better recollection of needs and wants and ease in buying.

Keywords

Figure 1.1: Conversion rate for various types of retailers [2]

Classification, marketing, buying behavior, association rules, product positioning

2. LITERATURE REVIEW The authors argue that consumer behavior is often strongly influenced by subtle environmental cues [3]. They argue that the traditional perspective on consumer choice based on conscious information processing leaves much variance to be explained and propose that many choices are made unconsciously and are strongly affected by the environment. Potential psychological predictors of stated willingness to pay (WTP) for different sustainable food attributes was examined [4]. Specifically, consumer attitudes and level of PCE (perceived consumer effectiveness) are measured to identify and define potential factors that aid in predicting consumer willingness to pay for products labeled locally grown, organically grown or fair trade. Choices are often identity-based but the linkage to identity is not necessarily explicit or obvious for a number of reasons [5]. Once an identity is formed, action and procedural-readiness can be cued without conscious awareness or systematic processing, resulting in beneficial or iatrogenic outcomes. The main problem currently faced by market-oriented firms is not the availability of information (data), but the possession of appropriate levels of knowledge to take the right decisions [6]. The authors deal with uncertain data by using a multi-objective genetic algorithm to derive fuzzy rules and propose a complete methodology that considers the different stages of knowledge discovery: data collection, data mining, and knowledge interpretation. Statistical

1. INTRODUCTION Retailers are always in search for various ways and methods to increase their sales, yet every day they lose opportunities to convert a significant part of their buyer traffic into satisfied purchasers [1]. These lost sales when added together represent a substantial amount of missed revenues. If opportunities are lost very day some customers will shift to other stores. In long run there will be permanent loss to the retailer’s consumer base. The biggest challenge is to address the customer’s needs and convert them into satisfied purchasers. But it is difficult to benchmark conversion because it varies across different countries, culture, social influences, demographic influences, retail strategies, channels, and formats. Usually businesses like consumer good i.e. tooth paste, soap, fruits, vegetables etc having lower margins and costs and thus they tend to convert at higher rates. In effect, the economics of the retail business model impact conversion, a web site might convert at a rate as low as 2%. In contrast, a grocery store may convert nearly 100% of its customers into purchasers in Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission from iiSC. iiSC’11, October 11–12, 2011, Muscat, Sultanate of Oman. Copyright 2011 iiSC ISBN: 978-9948-16-253-7

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association models and, specifically, log linear and graphical models can be usefully employed to study consumer behaviors [7]. With use of data mining technique marketing managers can develop long-term and pleasant relationships with customers if they can detect and predict changes in customer behavior [8]. They integrate customer behavioral variables, demographic variables, and transaction database to establish a method of mining changes in customer behavior. Improvements can be brought through the use of consumer behavior research as a supplement to point-of-purchase scanner information [9]. An empirical demonstration of one such opportunity is presented showing how two consumer behavior concepts - context effects and categorization theory - reveal insights relevant to item placement decisions within category management that would not be revealed by scanner data. A dual-system model of consumer behavior has been presented in article [10]. The relative contribution of impulsive and reflective processes depends on personal and contextual circumstances. The operation and interaction of the two systems at different stages of information processing is described and applied to the dynamics of consumer behavior, with a special emphasis on impulse buying. The authors develop a methodology to detect the existence of repeat-buying behavior and discover the potential period of the repeat-buying behavior [11].

learning to prefer a particular product brand. The marketing manager can only do his task successfully if he knows the answers as to what do the consumers buy? How do they buy? When do they buy? Where do they buy? Why do they buy? Not only this, Product assortment plays a very effective role in customer conversion [13, 14]. The first step in the buying process is Desire awareness; a want, desire or a consumption problem without whose satisfaction the consumer normally builds up tension. Attention or Product Awareness is the second stage of buying. The sale is affected only if the customer is convinced in his own mind that it will be beneficial for him to make the purchase. The first step in the buying process is awareness about a want, desire or a consumption problem without whose satisfaction the consumer normally builds up tension. Attention or Product Awareness is the second stage of buying. A mother feels the need for health drink for her child [15]. This recognition of the need for drink might divert her attention to search for a flavored milk or laban or fresh juice. Nevertheless, it is possible that she might be already aware of a few brands of milk or juice before she recognizes the need. If she always purchases pasteurized milk, placing fresh juice or flavored milk near pasteurized milk will increase the chances of being in sight and in mind. There is a possibility that in her next purchases she will select any item from juices or laban. In the product awareness stage, the ‘consumer is exposed to the existence of a product that may satisfy a need. This awareness may be on account of the search carried out by the consumer himself or because of the selling companies’ sales promotion efforts through advertising or personal selling or through other environmental channels [16, 17, and 18]. Figure 3.1 shows the perceptual constructs which lead to conversion.

3. CONSUMER BUYING BEHAVIOR Consumer behavior is the process whereby individuals decide whether, what, when, where, how and from whom to purchase goods and services [12]. Consumer behavior consists of both physical and mental activities. The physical activities involve visiting a shop, examining and selecting the product. Mental activities on the other hand, involve deliberations within and forming of attitudes, perceiving communication material and Inputs Stimulus display Significative a. Quality b. Price c. Distinctiveness d. Service e. Availability Symbolic a. Quality b. Price c. Distinctiveness d. Service e. Availability Social a. Family b. Reference groups c. Social Class

Perceptual constructs

Intention Over search

Confidence

Attitude

Stimulus ambiguity

Motives

Attention

Choice criteria

Brand Comprehension

Perceptual bias

Satisfaction

Figure 3.1: The Howard- Sheth Consumer Behaviour Model [16]

4. EXPERIMENT

on 36424 instances and 20 Attributes. Figure 4.1 shows sample of the data set.

The data set was collected from Jordan city Irbid, Raddida Super market. The researchers have selected attributes from one particular domain, i.e. groceries. The experiment was conducted

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Figure 4.1: Sample of the data set

4.1 Preparing the Data:

appears in the box above the histogram, and the same for any other attribute. In Figure 4.2 Rice is selected as the class attribute; it is used to color the histogram, and any filters that require a class value use it too. The histogram shows that 17937 customers have purchased Rice with Milk and 18487 customers did not buy Rice with Milk. All attributes are Nominal (Yes, No).The Red color denominates the ‘No’, and Blue color denominates ‘Yes’.

It has 36424 instances and 20 Attribute (center left); the attributes are pertaining to the class “groceries” for example Milk, Butter, etc (lower left). The first attribute , Milk , is selected , it has neither any missing value nor unique value; two distinct values{freq(Yes) =17937 ,freq(No)=18487} , the actual values are Yes , No and they occur 17037 , 18487 times , respectively (center right). A histogram at the lower right shows how often each of the two values of the class ’Rice’ occurs for each value of the ‘Milk’ attribute. The attribute ‘Milk’ is used because it

Figure 4.2: Attributes and Histogram showing Relationship between milk and rice

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iiSC 2011 Proceedings year period beginning in the late 1970s. A complete description, appears in book (Quinlan 1993), along with the full source code. The more recent version, C5.0 , is available commercially. The J4.8 algorithm , implements a later improved version called C4.5 revision 8 , which was the last public version of this family of algorithms before the commercial implementation C5.0 was released .

In the sample data set, ‘Yes’= Purchases; ‘No’= No purchases. Each record in the database represents the consumer transaction.

4.2 Building a Decision Tree C4.5 Decision Tree Learner: The Decision Tree Program C4.5 and its successor C5.0. were devised by J.Ross Quinlan over a 20-

4.3 Examining the Output

Figure 4.3: The lower half of the output

Figure 4.4: Summary of the dataset and tenfold cross validation

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iiSC 2011 Proceedings each time. The procedure is repeated ten times so that, in the end, every instance has been used exactly once for testing. Thus 100% testing of the data has been performed. As per the standard way of predicting the error rate of a learning technique; given a single, fixed sample of data is to use 10-fold crossvalidation; the folds have been fixed to ten. Standard procedure to repeat the cross validation process is 10 times, i.e. 10 times 10-fold and averaging the results. This involves invoking the learning algorithm 100 times on datasets that are all nine-tenths the size of the original .Obtaining a good measure of performance is a commutation intensive undertaking.

4.4 Selection of Validation First train the system on the test data. Secondly test it on the training data. Thereafter average the two results, this will reduce the effect of irregular representation in training and test sets. The cross validation is a statistical technique which helps to decide on a fixed number of folds, or partitions of the data, for the purpose the data has been fixed to 10 folds. Thus the data is split into ten approximately equal partitions. Each in turn is used for testing and the remainder is used for training. Nine-tenth of the data is used for training and one-tenth of the data for testing

Figure 4.5: The experiment output, a pruned decision tree J48 in textual form Figure 4.5 Shows part of the experiment output, a pruned decision tree J48 in textual form. The first split is on the frozen meat number because of the way the algorithm user fractional instances product attribute, and then, at the second level, the splits are on to handle missing values . For example the freeze vegetables: Yes; Biscuit, Butter etc. In the tree structure, a colon introduces the No (42.0/4.0) means that 42 instances reached that leaf, of which class label that has been assigned to a particular leaf , followed by four is classified incorrectly. Under the tree structure the number the number of instances that reach that leaf, expressed as decimal of leaves is printed; then the total number of nods (size of the tree)

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Figure 4.6: Sample of the tree graphically The next part of the output gives estimates of the tree predictive performance. In this case using 10 folds from figure 4.3, we can see, more than 21% of the instances (20 Attributes and 36424 instances) have been misclassified in the cross-validation. This indicates that the results obtained from the training data are optimistic compared with what might be obtained from an independent test set from the same source.

incorrectly predicted as ‘yes’ (or positive) when it is actually ‘no’ (negative). A false negative (FN) occurs when the outcome is incorrectly predicted as negative when it is actually positive. The true positive rate is TP divided by the total number of positives, which is TP + FN; the false positive rate is FP divided by the total number of negatives, FP + TN. The overall success rate is the number of correct classification divided by total number of classification:

From the confusion matrix, as shown in figure 4.3 we observe that 3064 instances of class ‘Yes’ have been assigned to class ‘no’ and 4586 of class ‘No’ are assigned to class ‘Yes’.

TP + TN (TP+TN+FP+FN)

In other words different outcomes of two –class prediction shall be as follows.

Finally the error rate is one minus this

Table 1: Class Prediction Predicated class No

Yes

False negative

True positive

Yes

True negative

False positive

No

A single prediction has four different possible outcomes shown in table 1.The true positive (TP) and true negative (TN) are correct classifications. A false positive (FP) occurs when the outcome is

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iiSC 2011 Proceedings enough footfalls and less conversion rate. If the above experiment is conducted for the particular store the results will be generated to be used for formulating strategies for that particular store. It will thus be useful for the store manager, retailer, management and ultimate benefit will go to the consumers due to the ease of selecting and buying. The desire awareness and product awareness will be stimulated with proper product assortment and placement thus leading to win-win situation for both the parties.

6. REFERENCES: [1] Figure 4.7: Plot Threshold Curve (Class value No)

http://www.wpp.com/NR/rdonlyres/B3A9A259-13A2-4112AFA6-0B796289ED6A/

[2] Pat Conroy, Deloitte & Touche USA LLP, Scott Bearse, Deloitte Consulting LLP, the Store_newsletter_003_Deloitte

This allows seeing the effect of varying the probability threshold above which an instance is assigned to that class , X : False positive rate; Y : True positive

[3] Ap. Dijksterhuis, Pamela K. Smith, Rick B. van Baaren and Daniël H.J. Wigboldus, “The Unconscious Consumer: Effects of Environment on Consumer Behavior”, Journal of Consumer Psychology Volume 15, Issue 3, 2005, Pages 193202 [4] Gretchen Nurse, Yuko Onozaka, and Dawn Thilmany McFadden, Colorado State University, “Understanding the Connections between Consumer Motivations and Buying Behavior: The Case of the Local Food System Movemen”, Selected Paper prepared for presentation at the Southern Agricultural Economics Association Annual Meeting, Orlando, FL, February 6-9, 2010 [5] “Identity-based motivation: Implications for actionreadiness, procedural-readiness, and consumer behavior”, Original Research Article, Journal of Consumer Psychology, Volume 19, Issue 3, July 2009, Pages 250-260 [6] Jorge Casillas and Francisco J. Martínez-López "Mining uncertain data with multiobjective genetic fuzzy systems to be applied in consumer behaviour modelling", Expert Systems with Applications, volume 36, number 2, Part- 1, pages 1645 – 1659

Figure 4.8: Plot Threshold Curve (Class value Yes)

5. CONCLUSION

[7]

By knowing the consumer behavior pattern, marketing professionals can better plan their strategies. They can satisfy the customer's conscious and unconscious needs and wants on the basis of the buying pattern thus satisfying the consumers and developing long term relationship. From the experiment in the above paper we can predict the behavior of the customer that with ‘frozen meat they are sure to buy rice, butter and laban but they will not buy milk, biscuit, soda and cake’, ‘with frozen vegetables they will buy spices and juice’. ‘With frozen vegetables if spices are not purchased, coffee is not purchased, cake (bread) is positively related’. ‘When sadrins (fish, meat etc) are purchased cold drinks and ice-creams are not purchased’. Thus by following the generated decision tree for the given data of particular geographic location, mall, city centre, family purchasing , consumable goods store etc the consumer behavior can be predicted. The products usually purchased by the customers can be assorted and placed in such an order that there is convenience in buying and which may also generate stimuli and impulse of buying other products. This will not only help in conversion of customers but also increase the basket value. Thus the behavior of the customers depends on the context. It will differ from country to country, market to market and also from store to store. This research may be particularly useful for the stores which have

Paolo Giudici and Gianluca Passerone, “Data mining of association structures to model consumer behaviour”, Computational Statistics & Data Analysis, volume 38, number4, pages 533 - 541

[8] Mu-Chen Chen and Ai-Lun Chiu and Hsu-Hwa Chang, “Mining changes in customer behavior in retail marketing”, Expert Systems with Applications, volume 28, number 4, pages 773 - 781 [9] Debra M. Desrochers and Paul Nelson, “Adding consumer behavior insights to category management: Improving item placement decisions”, Journal of Retailing, volume 82, number 4, pages 357 - 365 [10] Fritz Strack and Lioba Werth' and Roland Deutsch, “Reflective and Impulsive Determinants of Consumer Behavior”, Journal of Consumer Psychology, volume 16, number 3, pages 205 - 216 [11] Ding-An Chiang and Yi-Hsin Wang and Shao-Ping Chen, “Analysis on repeat-buying patterns, Knowledge-Based Systems”, volume 23, number 8, pages 757 - 768 [12] Walters, C. Glenn and Gordon W. Paul. Consumer Behavior: An Integrated Framework. Homewood: Richard D. Irwin, 1970.

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iiSC 2011 Proceedings [17] J.A. Howard and J. Sheth: The Theory of Buyer Behaviour, New York, John Wiley & Sons, Inc., 1969.

[13] P.K. Srivastava, Kaneez Fatima, Arif Sheikh; Marketing Management, Himalaya Publishing House, Mumbai (under publication)

[18] F. Nicosia: Consumer Decision Processes, Englewood, Cliffs N.J. Prentice Hall, 1966.

[14] Consumer Self-Concept, Symbolism and Market Behavior: A Theoretical Approach

[19] Arif Sheikh, Kaneez Fatima Sadriwala, Retail Management, Himalaya Publishing House, Mumbai, India, 2009.

[15] Edward L. Grubb and Harrison L. Grathwohl, The Journal of Marketing, Vol. 31, No. 4, Part 1 (Oct., 1967), pp. 22-27

[20] Arif Sheikh, Kaneez Fatima Sadriwala, Mall Management, Himalaya Publishing House, Mumbai, India, 2009.

[16] J.F. Engle, D.T. Kollat and R.D. Blackwell: Consumer Behaviours, New York, Holt, Rinehart & Co., 1973, 2nd Edn.

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AUTHOR INDEX

Authors


Page number

Abeer Al-Suleima Abid Abdelouahab Afaq Ahmad Ahmed A. Mohammad Ahmed A.A. Radwan Al Ajmi, M Ali H. Al-Badi Al-Khanjari, Z. A. Al-Kindi, K. Al-Zeidi, A. Arthur Tatnall Arthur Tatnall Awny Sayed Awny Sayed Bechir Gattoufi Boumedyen Shannaq Boumedyen Shannaq Brian Guillemin Charles Robert Chia-Sheng Lin Elfadil A/Alla Mohamed Ernest Johnson Eva Dakich Fatma Mirza Hafedh Al-Shihi Ian Michael John D Haynes Jyoti Kumar Chandel Kaneez Fatima Sadriwala Khalid Al-Mabrouk Komal Dave Maitham H. Al Lawati Mauth Al Hashli Mithun Shrivastava Mostaq M. Hussain Mphamed M. Abdallah Muna Al mahrouqi Muneera Al Siyabi

204 195 200 18 67 191 195 173, 191 173 173 40, 126 126 25, 67 67 182, 195 60, 215 215 152 179 32 105 152 126 46 204, 208 126 60 159 215 131 73 167 191 73, 110 87 67 204 208 223

AUTHOR INDEX


Naeem-ul Hassan Janjua Nasser Taleb Niels Bjørn-Andersen Noora Al Jabri Raja Waseem Anwar Rajan Yadav S. Manasa S.Arockiasamy Sadiq Al-Baghdady Said Gattoufi Salem Ben Dhaou Dakhli Salim Al-Hajri Salim Fadhil Sana Guetat Saqib Ali Sujeet Sharma Syed J. Naqvi Syed Rashid Ali Tahera Paperwala Theo Thiadens Toon Abcouwer Virendra Gawande Wesley Shu Youcef Baghdadi Yu-Hao Chuang

54 105 3 208 188 159 110 60 185 159 10 40 191 10 46, 167 159 167 54 73 96 96 212 32 80 32

224

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