Antecedents of Cloud Computing Usage Influencing Malaysian Users’ Work Outcomes – A Conceptual Paper HP Fung ITIL v3 Expert, ITIL v2 Mgr, CISSP, PMP
[email protected] Presented during Asia e University’s PhD Colloquium (www.aeu.edu.my)
24-Apr-2011
Overview 1. 2. 3. 4. 5. 6. 7. 8. 9. 4/4/2015
Introduction Research Problem Research Objectives & Questions Literature Review Conceptual Framework Hypotheses Research Methodology Contribution to Knowledge Q&A HP Fung
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1. Introduction – Operational Definitions 1. Cloud Computing System Quality – concern with whether or not there are “bugs” in the cloud computing system, the consistency of the user interface, ease of use, response rates within the cloud computing system, quality of documentation, quality and maintainability of the cloud computing system (adapted fr Seddon & Kiew, 2007) 2. Cloud Computing Information Quality – concern with issues like timeliness, accuracy, relevance and format of information generated by cloud computing system (adapted fr Seddon & Kiew, 2007) 3. Cloud Computing Service Quality – degree & direction of discrepancy btw user’s expectation of cloud computing services & perception of actual service received (adapted fr Grover et al., 1996; Parasuraman et al., 1988) 4. Cloud Computing Facilitating Conditions – degree a user believes his organization & technical infrastructure exists to support his usage of cloud computing system (adapted fr Venkatesh et al., 2003) 5. Cloud Computing Social Influence – degree a user perceives the importance others believe him should or should not use cloud computing system (adapted fr Venkatesh et al., 2003) 6. Cloud Computing Performance Expectancy – degree in which a user believes that using cloud computing system which had adopted by his organization will help him obtain gains in his work outcomes (adapted fr Venkatesh et al., 2003) 4/4/2015
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1. Introduction – Operational Definitions 7. Cloud Computing Effort Expectancy – degree of ease related to the use of cloud computing system by a user (adapted fr Venkatesh et al., 2003) 8. Cloud Computing Usage Attitude – user’s positive or negative feelings about the usage of cloud computing system that the organization had adopted (adapted fr Venkatesh et al., 2003) 9. Cloud Computing Usage Intention – measure a user’s intention to use the cloud computing system adopted by his organization (adapted fr Venkatesh et al, 2003) 10.Cloud Computing Usage – user’s behavior of or effort put into using the cloud computing system (adapted fr Sabherwal et al., 2006) 11.Work Effectiveness – degree to which work task is completed effectively using cloud computing system (adapted fr Pentland, 1989) 12.User Satisfaction – function of user’s perception of cloud computing work outcome i.e. satisfaction with work completed using cloud computing system (adapted fr Dailey, 1993) 4/4/2015
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1. Introduction – Conceptual Framework
Proposed Framework to Measure Users’ Work Outcomes as a result of using Cloud Computing
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2. Research Problem Cloud Computing is a model that can provide anywhere on demand network access to a pool of computing resources e.g. servers, storages, networks, applications & services in which these resources can be quickly provisioned with minimum human interaction effort (Mell & Grance, 2009)
General Components of Cloud Computing (Kossmann & Kraska, 2010)
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2. Research Problem
NIST Cloud Definition Framework (www.nist.gov/itl/cloud/)
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2. Research Problem
Cloud Deployment Models (Badger & Grance, 2010)
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Cloud Service Models (Badger & Grance, 2010)
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2. Research Problem Cloud Usage Areas (IT & Biz Users): 1. Server Cloud – eg. Amazon EC2 2. Storage Cloud – eg. Amazon S3 3. Development & Test Cloud – eg. Amazon
Web Services, Google App Engine, IBM Smart Biz Cloud Enterprise, IBM CloudBurst, Microsoft Azure, Manjrasoft Aneka etc 4. Unified Communication Cloud – eg. Cisco WebEx 5. Security Cloud – eg. HP Cloud Assure 6. 7.
Disaster Recovery Cloud Expense Reporting Cloud – eg. Telecom,
network, mobile expenses claims etc. 8. Applications & DB Cloud – eg. Salesforce.com, SAP, IBM Smart Biz Cloud Enterprise+, Tivoli Live, Amazon SimpleDB etc. 9. Business Process Cloud – eg. HR, Finance, Payroll, Biz Process Mgmt etc. 10. Business
Analytics Cloud 11. Email & Collaboration Cloud – eg. Google Mail, Lotus Live, etc.
12. Office
Automation Application Cloud –
eg. Google Docs & Spreadsheets, Windows Live Office etc. 13. Virtual Desktop – eg. VMware Hypervisor, VMware View, XenServer, XenApp, XenClient etc. Cloud Reference Model (CSA, 2009)
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14. Virtual
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Service Desk / Call Center
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2. Research Problem According to a survey done by Frost & Sullivan (2011) in Feb-2011, 30% of Malaysian enterprises use some forms of Cloud Computing & more than 64% of survey respondents believe Cloud Computing technology in any delivery form can help businesses reduce their infrastructure cost & lower CAPEX investment compared to traditional IT management As more & more Malaysian organizations are using Cloud Computing to provide them more business values like quality of service, business innovation, lower TCO etc, there is lack of research to evaluate how the usage of Cloud Computing will impact its user work outcomes like work effectiveness & user satisfaction To date there is lack of research to evaluate how Cloud Computing Usage impacting user’s work outcomes using IS Success Model (Delone & McLean, 2003) and Unified Theory of Acceptance & Use of Technology / UTAUT (Venkatesh et al., 2003) Unclear whether adapted combined Delone & McLean’s IS Success Model & UTAUT can apply onto work effectiveness & Cloud Computing context as Cloud Computing is relatively new concept in social science research Problem statement is lack of research how Cloud Computing usage will impact its Malaysian user work effectiveness & user satisfaction based on adapted combined Delone & McLean’s IS Success Model & UTAUT 10 4/4/2015 HP Fung
2. Research Problem Proposed Scope of Research
Cloud Computing Work Outcomes •Work Effectiveness •User Satisfaction
Organizational Benefits
(commercial feedback)
1. Improve Service Delivery - self-service oriented - reduce provision time - increase productivity
Cloud Computing Usage
Other IT Factors
Research Gap •IT Competency •Job Performance •Job Satisfaction
2. Enable Business Innovation - ubiquitous access - cater workload fluctuation - speed to market
3. Reduce Cost - improve IT utilization - opex instead of capex - on demand pay per use
Individual Benefits 4/4/2015
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3. Research Objectives & Questions 1.
Explore what are the Cloud Computing Usage antecedents that can impact its user’s work outcomes a.
What are the antecedents that can influence Cloud Computing Performance Expectancy?
b.
What are the antecedents that can influence Cloud Computing Effort Expectancy?
c.
What are the antecedents that can influence Cloud Computing Usage Attitude?
d.
What are the antecedents that can influence Cloud Computing Usage Intention?
e.
What are the antecedents that can influence Cloud Computing Usage?
f.
Which is the most significant predictor for Cloud Computing Usage?
g.
Can Cloud Computing Usage & other constructs influencing Cloud Computing User Work Outcomes?
h.
Which is the most significant predictor for Cloud Computing User Work Outcomes?
2.
Evaluate whether the use of adapted combined Delone & McLean IS Success Model & UTAUT which are predominantly IS/T tools centric can explain Cloud Computing usage that leads to its user’s work outcomes a.
With the combined Delone & McLean IS Success Model & UTAUT being adapted, can the new model still produce the same outcome for Cloud Computing as they
did separately for other IS/IT tools? 4/4/2015
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4. Literature Review Distributed Computing, On Demand Computing, Utility Computing, Elastic Computing, Grid Computing, Cloud Computing Nurmi etc (2008), Abadi (2009), Kim (2009), Rimal etc (2010), Weinhardt etc (2009), Foster etc (2008) There are claims that Cloud Computing is similar to other of its predecessors. There are also claims that they are different especially Grid vs Cloud Computing – differences & each computing characteristics had been reviewed & hi-lighted
Cloud Computing Characteristics, Deployment Models (Private, Community, Public, Hybrid), Service Models (IaaS, PaaS, SaaS), Cloud Computing Benefits & Concerns, Differences btw Cloud Computing vs Traditional IT Computing System vs Outsourcing Mell & Grance (2009), Kossmann & Kraska (2010), Abadi (2009), Vaquero etc (2009), Kim (2009), Wang etc (20100, Rimal etc (2010), Badger & Grance (2010), CSA (2009), Aboulnaga etc (2009), Grossman & Gu (2009), Kim (2009) Literature of Cloud Computing Characteristics, Deployment & Service Models, Benefits & Concerns had been reviewed. Differences btw Cloud Computing vs Traditional IT Computing System vs Outsourcing also had been reviewed in which Cloud Computing has its unique attributes 4/4/2015
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4. Literature Review Delone & McLean IS Success Model, Technology Adoption or Usage Theories & Models (Theory of Reasoned Action / TRA, Theory of Planned Behavior / TPB, Technology Acceptance Model / TAM, Unified Theory of Acceptance & Use of Technology / UTAUT) Delone & McLean (1992, 2003), Fishbein & Ajzen (1975), Ajzen (1991), Davis (1989), Davis & Venkatesh (1996), Venkatesh & Davis (2000), Venkatesh etc (2003) Delone & McLean IS success model & technology adoption/usage theories/models evolved from TRA to UTAUT mainly on ICT technology e.g. computer, PDA, mobile devices, VOIP, network, wireless LAN, Internet & Web App, Airline Internet Reservation & CRM System, ELearning System, MIS, EIS & ERP systems but to date lack of research apply any above theory/model on Cloud Computing
Cloud Computing Usage Antecedents & User Work Outcomes (System Quality, Information Quality, Service Quality, Facilitating Conditions, Social Influence, Performance Expectancy, Effort Expectancy, Usage Attitude, Usage Intention, Work Effectiveness, User Satisfaction) Delone & McLean (1992, 2003), Venkatesh etc (2003), Davis (1989), Seddon & Kiew (2007), Grover etc (1996), Parasuraman etc (1988), Sabherwal etc (2006) Delone & McLean (D&M) IS Success Model & UTAUT are the latest & most complete theories & their constructs had been reviewed for appropriateness to be included in new proposed framework Constructs extracted from D&M include: System, Info & Service Quality, Usage, User Satisfaction. Constructs extracted from UTAUT include: Performance & Effort Expectancy, Facilitating Conditions, Social Influence, Usage Intention. Usage Attitude from TAM also extracted. Work Effectiveness as a new construct equivalent to D&M’s Net Benefits had been reviewed & added into the new framework Construct operational definitions had been defined. Survey questionnaire items for each construct had been reviewed, adapted or developed 14 4/4/2015 HP Fung
4. Literature Review IS Success Model (Delone & McLean, 1992)
Unified Theory of Acceptance & Use of Technology / UTAUT (Venkatesh et al., 2003)
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Updated IS Success Model (Delone & McLean, 2003)
Technology Acceptance Model / TAM (Davis, 1989)
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4. Literature Review – Operational Definitions 1. Cloud Computing System Quality – concern with whether or not there are “bugs” in the cloud computing system, the consistency of the user interface, ease of use, response rates within the cloud computing system, quality of documentation, quality and maintainability of the cloud computing system (adapted fr Seddon & Kiew, 2007) 2. Cloud Computing Information Quality – concern with issues like timeliness, accuracy, relevance and format of information generated by cloud computing system (adapted fr Seddon & Kiew, 2007) 3. Cloud Computing Service Quality – degree & direction of discrepancy btw user’s expectation of cloud computing services & perception of actual service received (adapted fr Grover et al., 1996; Parasuraman et al., 1988) 4. Cloud Computing Facilitating Conditions – degree a user believes his organization & technical infrastructure exists to support his usage of cloud computing system (adapted fr Venkatesh et al., 2003) 5. Cloud Computing Social Influence – degree a user perceives the importance others believe him should or should not use cloud computing system (adapted fr Venkatesh et al., 2003) 6. Cloud Computing Performance Expectancy – degree in which a user believes that using cloud computing system which had adopted by his organization will help him obtain gains in his work outcomes (adapted fr Venkatesh et al., 2003) 4/4/2015
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4. Literature Review – Operational Definitions 7. Cloud Computing Effort Expectancy – degree of ease related to the use of cloud computing system by a user (adapted fr Venkatesh et al., 2003) 8. Cloud Computing Usage Attitude – user’s positive or negative feelings about the usage of cloud computing system that the organization had adopted (adapted fr Venkatesh et al., 2003) 9. Cloud Computing Usage Intention – measure a user’s intention to use the cloud computing system adopted by his organization (adapted fr Venkatesh et al, 2003) 10.Cloud Computing Usage – user’s behavior of or effort put into using the cloud computing system (adapted fr Sabherwal et al., 2006) 11.Work Effectiveness – degree to which work task is completed effectively using cloud computing system (adapted fr Pentland, 1989) 12.User Satisfaction – function of user’s perception of cloud computing work outcome i.e. satisfaction with work completed using cloud computing system (adapted fr Dailey, 1993) 4/4/2015
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5. Conceptual Framework CC System Quality
Cloud Computing User’s Work Outcomes
H1 + H3 + H2 +
CC Information Quality
CC Performance Expectancy
H12 +
CC Usage Attitude
H11 +
CC Service Quality
H6 +
H21 +
H16 + H14 +
H5 +
H20 +
CC Effort Expectancy
H15 +
H18 +
CC Usage
CC Usage Intention
H23 + H22 +
CC Social Influence 4/4/2015
User Satisfaction
H24 +
H7 +
CC Facilitating Conditions
Work Effectiveness
H17 +
H13 + H4 +
H19 +
H8 + H9 +
H10 +
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Note: CC = Cloud Computing
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5. Conceptual Framework
Proposed Framework to Measure Users’ Work Outcomes as a result of using Cloud Computing
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5. Conceptual Framework - Epistemology Delone & McLean IS Success Model
Proposed Framework Conceptual framework underpinned on both Delone & McLean (2003) IS Success Model & Venkatesth etc (2003) UTAUT Extracted System, Information & Service Quality, Usage & User Satisfaction from IS Success Model Extracted Facilitating Conditions, Social Influence, Performance & Effort Expectancy & Usage Intention from UTAUT Extracted Usage Attitude from Technology Acceptance Model / TAM (Davis, 1989) Replace IS Success Model’s Net Benefits with Cloud Computing User’s Work Effectiveness Then combined above constructs to form new conceptual framework Excluded loop back from Work Effectiveness & User Satisfaction to Usage Attitude and Usage Intention which is not part of this research objective Excluded the UTAUT moderating effects in proposed framework which is not part of this research objective Excluded TAM’s Perceived Usefulness & Perceived Ease of Use as they have been replaced by UTAUT’s Performance Expectancy & Effort Expectancy
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5. Conceptual Framework - Epistemology IS Success Model (Delone & McLean, 2003)
Technology Acceptance Model (Davis, 1989)
UTAUT (Venkatesh etc, 2003)
Epistemological Proposed Framework
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6. Hypotheses H1 – Cloud Computing System Quality will positively influences Cloud Computing Performance Expectancy H2 – Cloud Computing System Quality will positively influences Cloud Computing Effort Expectancy H3 – Cloud Computing Information Quality will positively influences Cloud Computing Performance Expectancy H4 – Cloud Computing Information Quality will positively influences Cloud Computing Effort Expectancy H5 – Cloud Computing Service Quality will positively influences Cloud Computing Performance Expectancy H6 – Cloud Computing Service Quality will positively influences Cloud Computing Effort Expectancy H7 – Cloud Computing Facilitating Conditions will positively influence Cloud Computing Performance Expectancy H8 – Cloud Computing Facilitating Conditions will positively influence Cloud Computing Effort Expectancy H9 – Cloud Computing Facilitating Conditions will positively influence Cloud Computing Usage H10 – Cloud Computing Social Influence will positively influences Cloud Computing Usage Intention 4/4/2015
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6. Hypotheses H11 – Cloud Computing Performance Expectancy will positively influences Cloud Computing Effort Expectancy H12 – Cloud Computing Performance Expectancy will positively influences Cloud Computing Usage Attitude H13 – Cloud Computing Performance Expectancy will positively influences Cloud Computing Usage Intention H14 – Cloud Computing Effort Expectancy will positively influences Cloud Computing Usage Attitude H15 – Cloud Computing Effort Expectancy will positively influences Cloud Computing Usage Intention H16 – Cloud Computing Usage Attitude will positively influences Cloud Computing Usage Intention H17 – Cloud Computing Usage Attitude will positively influences Cloud Computing Usage H18 – Cloud Computing Usage Intention will positively influences Cloud Computing Usage H19 – Cloud Computing Usage Attitude will positively influences Work Effectiveness H20 – Cloud Computing Usage Attitude will positively influences User Satisfaction 4/4/2015
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6. Hypotheses H21 – Cloud Computing Usage will positively influences Work Effectiveness H22 – Cloud Computing Usage will positively influences User Satisfaction H23 – Cloud Computing Usage Intention will positively influences Work Effectiveness H24 – Cloud Computing Usage Intention will positively influences User Satisfaction
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7. Research Methodology
Approach – Cross Sectional Quantitative Research with Online Survey Method based on deductive research questions
Sampling & Data Collection: Randomly select 2,000 user target respondents from PIKOM for those Malaysian companies that have implemented Cloud Computing via SPSS (respondents that have used the system > 6 months will be solicited to minimize initial usage dissatisfaction) Total 2,000 emails will send out with structured questionnaire hyperlink within each mail 3-waves mailing is used & survey complete in 4 weeks Expecting 200-300 samples
Questionnaire: Total 101 questions (87 research + 14 Demographic) all with 7-point Likert scale Cloud Computing System Quality (10 questions) – adapted fr Seddon & Kiew (2007), Hellsten & Markova (2006) Cloud Computing Information Quality (10 questions) – adapted fr Seddon & Kiew (2007) Cloud Computing Service Quality (12 questions) – adapted fr Ali & Khan (2010), Chien & Tsaur (2007) Cloud Computing Facilitating Conditions (6 questions) – adapted fr Venkatesh et al. (2003) Cloud Computing Social Influence (4 questions) – adapted fr Venkatesh et al. (2003) Cloud Computing Performance Expectancy (4 questions) – adapted fr Venkatesh et al. (2003) 25 4/4/2015 HP Fung
7. Research Methodology Questionnaire (cont’d): Cloud Computing Effort Expectancy (4 questions) – adapted fr Venkatesh et al. (2003) Cloud Computing Usage Attitude (11 questions) – adapted fr Venkatesh et al. (2003) Cloud Computing Usage Intention (6 questions) – adapted fr Venkatesh et al. (2003) Cloud Computing Usage (2 questions) - adapted fr Ali & Khan (2010) Work Effectiveness (14 questions) – self developed (will pilot test for reliability, validity & enhancement before adopt as final instrument for data collection) User Satisfaction (4 questions) – adapted fr Seddon & Kiew (2007) Data Analysis: SPSS v17 Normality Test, Descriptive statistics, Reliability Test, Validity Test, Factor Analysis, Multiple Regression Analysis, AMOS v18 Structural Equation Modeling & Path Analysis, Hypotheses Test & Cross tabulations of research outcomes with demographic factors 4/4/2015
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8. Contribution to Knowledge 1.
Theoretical Contribution: a.
Develop a framework to explain what are the antecedents in influencing cloud computing usage and work outcomes among Malaysian users
b.
Discover whether combined IS Success Model & UTAUT which are very much IS / technology / tools centric can be adapted & applied to cloud computing
2.
Practical Contribution: a.
Help organizations & IT departments in planning how best & how soon to rollout their new Cloud Computing System in view of its impact on their users’ work effectiveness & satisfaction
b.
If Cloud Computing Usage Attitude, Intention & Usage are significantly influencing user work outcomes like Work Effectiveness & User Satisfaction, this can prompt IT management to pay more attention or more effort in adjusting users’ positive attitude, intention & behavior towards the usage of Cloud Computing System
c.
If Cloud Computing Usage Attitude & Intention are significantly influencing Cloud Computing Usage, this can prompt IT management to focus more on users’ Cloud Computing Performance Expectancy, Effort Expectancy & Social Influence i.e. to improve how useful is the Cloud Computing System is, its ease of use & exert the individual influence surrounding the user e.g. coworkers, superiors, subordinates etc to motivate the user to use the system
d.
If Cloud Computing System, Information & Service Quality and Facilitating Conditions are significantly influencing Performance & Effort Expectancy and Usage, IT management should ensure the new Cloud Computing System is implemented successfully i.e. meeting its system, information & service performance and facilitating conditions like earlier user involvement, superior design, project management, training, documentation, support etc are delivered accordingly
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9. Questions & Answers?
References will be provided upon request has been approved Email:
[email protected]
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