A Foresight Framework for Understanding the

A Foresight Framework for Understanding the Future of Mobile Commerce

Shengnan Han* − Ville Harkke* − Pär Landor** − Ruggero Rossi de Mio*

** Institute for Advanced Management Systems Research/ Abo Akademi University. *Turku Centre for Computer Science, Lemminkainengatan 14B, FIN-20520 ABO, FINLAND [email protected]; [email protected]; [email protected]; [email protected]. ABSTRACT:

The emerging markets of mobile commerce are calling for potential successful products and services. This process is challenging all actors of the mobile commerce industry (MCI). Learning from the future and discovering a route to a desired future are keys to successful mobile commerce business. In this paper we argue that it is very important that all actors in the MCI use an industry foresight approach in order to discover a successful route to future markets. We present a framework for creating industry foresights and for understanding the future of mobile commerce. We focus on the mobile commerce industry as a whole and introduce two broad variables; (1) adoption and diffusion of mobile commerce products and services; and (2) the macro economic development trend. Based on these variables we build four foresight scenarios: Rapid-up, Rapid-down, Slowdown and Slow-up. Based on product feature characteristics in each of these four different scenarios we suggest some features of promising mobile commerce products and services. As our research moves further on, we will use informationgathering agents for collecting information for our analysis. KEYWORDS:

mobile commerce, industry foresight, scenarios, promising mobile products and services.

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1. Introduction The development, i.e. the coming, of the 3G world of mobile commerce has suffered from the wait-and-see mode of the last couple of years. The actual development trend of the 3G mobile world and the calling for potential successful mobile commerce products and services (Carlsson and Walden, 2001) are however challenging all actors of the mobile commerce industry to achieve more knowledge about the future. Learning from the future and building competitive industry foresights are a rather new framework for understanding the future of the mobile commerce industry (MCI). (Fahey and Randall, 1998) This paper describes an approach for modelling the future of the MCI. Mobile commerce is a descendant of electronic commerce that uses the possibilities of new technologies for mobile communication. As a definition of mobile commerce we use the following: The use of mobile technologies and devices to provide, sell and buy convenient, personalised, and location-based services. The consumers of mobile commerce are understood to be any customers, employees and/or business partners, thus, B2B, B2C, B2E, and P2P are becoming the contexts of mobile commerce. With MCI we understand the numerous companies needed to produce mobile services, ranging from technology providers and network operators to content providers. A mobile commerce product can be practically anything, ranging from an SMS message delivered from a user to another, to remote use of very complex systems, such as bank account management or electronic retailers and mobile ehealth. The difference between a product and a service is very vague in a mobile commerce setting. We understand that even in purchasing physical products through mobile networks and devices there is an important service component. We refrain from ruling out any possible commercial uses of the mobile technologies. 2. Industry Foresight Approach Industry foresight building is a process of discovering a route to a desirable future and about being ready for the future of an organisation (Walden et al., 2000). This foresight, however, is not intended to be used by any specific organisation, but to outline the future of the MCI as a whole. This objective makes our foresight somewhat more challenging than any specific company’s foresight, and this inevitably causes us to focus away from the details and try to recognise the macro level trends and their implications for the industry. This work could even be seen as a specified technology foresight, if one wishes to follow the definition of Martin (1995): “Technology foresight is the systematic attempt to look into the longer-term future of science, technology, the economy and society, with the aim of identifying the areas of strategic research and the emerging of generic technologies likely to yield the greatest economic and social benefits”. Our objective is however to forecast the future of an industry and not just the technological aspects of mobile commerce development.

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Long range forecasting requires two kinds of tasks: discovering established patterns or relationships and determining how these may change in the future. Both of these tasks are mostly judgmental (Makridakis and Wheelwright, 1989). In order to systematise our judgements we have used a framework with four initial scenarios based on two crucial variables: (1) the rate of innovation adoption concerning mobile commerce products and services, and (2) the overall economic development in the world that forms the society and the environment of the mobile commerce actors. Developing industry foresights requires more than good scenario planning or technology forecasting, although scenarios and forecasts are often useful building blocks (Hamel and Prahalad, 1994). Due to the emerging nature of mobile commerce the trend projection methods of forecasting would be highly inaccurate in absence of long-term data. Even precursor analysis and comparisons with previous technology-enabled changes would probably fail, as the social phenomena surrounding mobile services are not clearly preceded anywhere. Thus, a major part of our foresight approach is building scenarios about the possible futures. A scenario in this sense is not intended to be an accurate forecast but merely a plausible future, which may emerge from the trends visible today (Mante-Meijer et al., 1998). Data used for creating the initial scenarios are information in various forms and sources, mainly published forecasts and surveys, ranging from one-point forecasts of mobile phone usage to sociological scenarios of the development of the society, and even editorials and Internet discussion group listings. As Hamel and Prahalad (1994) stated: “The cues, weak signals and trend lines that suggest how the future might be different are there for everyone to observe”. We chose not to include any formal information-gathering method such as Delphi due to the method’s tendency to suppress the subtle judgements, (Coates, 1996). After building the initial scenarios, the economic development is monitored weekly with the help of an information-gathering software agent, developed by Agentum Technologies Inc. (Finland). The agent gathers articles containing significant weak signals, according to pre-defined profiles, from the vast masses of information published on the Reuters Business Briefing, covering nearly 8,000 publications worldwide. The main benefit of using an agent is that it automates information searches that would be very time-consuming if done manually, given the complex search patterns and the amounts of information. The expertise from key industry players is connected to the work by distributing the foresight suggestion to a number of corporate decision makers, who individually comment and revise the initial scenarios. The economic updates written based on the information gathered by the agent are distributed weekly to the same decision makers. After the feedback from the corporate experts, our research team rewrites the foresight including the characteristics of the scenarios, twice a year, and a new round of corporate cooperation begins. This process is planned to be ongoing, with the present foresight horizon being set to 2005.

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The foresight framework provides its users with a set of possible successful mobile commerce products and services for each scenario, complete with the logic behind their adoption by the users. Since single, outstanding equivocal applications may be rare and far between, we focus on various types of combinations or “killer bouquets” (Carlsson and Walden 2001). The scope of the foresight is wide, concerning not only the consumer sector of future mobile commerce, but also the industrial implications and the roles of the key actors.

Initial Foresight

Corporate opinions

Biannual revised foresight

Weekly economic update Figure 1. Our research process of mobile commerce industry foresight

3. Two Variables in Focus As we indicated earlier, two variables are intensively focused on in developing our foresight framework. One is adoption and diffusion, the other is economic trends. A detailed discussion follows. 3.1 The Adoption and Diffusion Processes − Slow and Rapid It is of great importance to study the adoption and diffusion of mobile commerce products and services. Generally, studies on information and communication technology (ICT) adoption suggest that the adoption process takes one of three possible approaches, a diffusion approach, an adoption approach or a domestication approach (Pedersen, 2002). Three models are widely applied in the adoption approach, the technology acceptance model (Davis, 1989), the theory of reasoned action (Fishbein and Ajzen, 1975) and the theory of planned behaviour (Ajzen, 1985). Domestication research focuses on the adoption and use of technology in everyday life. The two approaches above only describe the micro-level behaviour of adoption in particular, and ignore the macro adoption and diffusion phenomena. The adoption and diffusion requirements of mobile commerce products and services have to be considered from the perspective of the business organisations’, on the supply and demand sides, as well as from the individual consumer’s perspective. (Methlie and Pedersen, 2001; Pedersen, 2001). In order to explore the comprehensive view of adoption and diffusion of mobile commerce products and services, we have to exploit approaches that include macro and micro studies of adoption and diffusion at the same time. The aggregative diffusion of innovation theory and models has been richly used when studying business organization and individual consumer adoption and diffusion of technology or new products and services (e.g., Bass, 1969; Norton & Bass 1987, 1992; Wind ed. 1981; Mahajan et

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al., 1990; Cooper & Zmud, 1990; Roger, 1995;Roberson & Gatignon 1986; Hannan & McDowell 1987; Frambach, 1993; Yamada et al., 2001; Black et al., 2001; Crawford 1996, Gopalakrishnan and Damanpour, 1997). Therefore, we will use this rich and widely tested theory in our research on the mobile commerce products and services adoption and diffusion process. There are two possible extremes for adoption of mobile commerce products and services in the future; rapid versus slow. If a rapid process is taking place, the MCI may be very prosperous. If the adoption process is slow, the MCI is still in its infant stage and the adoption requirements may not match in a proper way. Thus, all value chain providers of mobile commerce need more time and effort to make fast adoption happen. Obviously, two future extremes of adoption and diffusion will have different impact on organisational strategy making. There is no one-fit-all strategy for all actors in the MCI. Any specific organisation needs to start from its business idea and combine the knowledge of the future in order to build particular industry scenarios (Van der Heijden, 1996). 3.2 Economic Variable − Upturn and Downturn Mobile commerce is a new market ready to explode. Despite the hype surrounding it, concerns regarding the necessary big investments and the user acceptance arise. The economic environment influences investment and consumer behaviour (Engle et al., 1990, Hopenhayn, 1992, Jovanovic 1982, Cooper 2000). It is commonly accepted that in an economic upturn, from the investor’s point of view, investment rates, acceptance of risk taking, investments in future growth, business travels, investments in R&D or employment rates are usually high. Whereas wages, purchasing power, travels, and the general demand for non-basic goods (Engel’s law) increase from the consumer’s point of view. The economic variable is monitored in order to study the behaviour from the supply-demand point of view. Indeed, considering both consumer and industrial behaviour, a wide range of possible mobile commerce product and service features can be identified, and the cross-section-study of the economic and the innovation adoption processes create an even more accurate foresight framework for this market. Huge amounts of capital have already been invested in the mobile market and even more in the development of the new network generation. Businesses involved in the mobile commerce market are certainly willing to take advantage of their investments, but the economic situation will determine when this is going to happen. The growth of mobile commerce will depend upon consumer adoption (Kalakota et al., 2001). Thus, studying the economic development allows keeping track of the potential consumers’ purchasing behaviours. According to recent experiences, in for example, Japan, when the Japanese economy was experiencing a strong recession, the mobile market was still growing and was very popular. A down-turning economy would lead towards reluctance to spend money, but with a high adoption rate of mobile commerce the expenses may be more focused and targeted on some

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kinds of products rather than others. We therefore suggest that the economy influences consumer behaviour not when analysed by itself, but when crossedanalysed with the adoption of mobile commerce 4. The Foresight Scenarios Our MCI foresight is built on four scenarios, a matrix where the x-axes describes the adoption rate of mobile commerce, and the y-axes describes the general state of the economy. By intersecting the dimensions described above, we create four foresight scenarios for MCI by the year 2005 (See figure 2). Economic Upturn Slow-Up

RapidRapid-Up

The economy is growing stably.Business organizations and customers are willing to make new investments. The relative advantages provided by the m-commerce products and services are not perceived to justify the expenditure in them. The users in both the business and consumer sector choose to invest in something else and the overall rate of adoption for mobile commerce is slow Suitable technological platforms

The economic situation is well ordered and growing stably. M-commerce has showed its relative advantage and compatibility with earlier models of ebusiness and e-commerce. There is an early majority of customers and firms adopting new m-commerce products and services. The rate of adoption is fast. Suitable technological platforms Bluetooth, WLAN and mobile Internet connectivity, UMTS

WLAN, GSM, GPRS, (UMTS, Bluetooth)

Slow Adoption

Rapid Adoption The economic situation is gloomy. Since mcommerce does not show much relative advantage compared to the prevailing products and services, firms and customers are very unwilling to use mobile services. Suitable technological platforms GSM, GPRS, WLAN, (Bluetooth, UMTS)

The economic situation is sluggish and poor. Business organizations and customers do not have financial support to purchase the available m-commerce products and services. They adopt new mcommerce products and services according to their immediate needs and desires. Suitable technological platforms Bluetooth, WLAN, GSM, GPRS, (UMTS)

Slow-Down

R apid-Down Economic Downturn

Figure 2. M-commerce Industry foresight scenarios Rapid-up: The economic situation is well ordered and growing stably. Mcommerce has shown its relative advantage and compatibility with earlier models of e-business and e-commerce. There is an early majority of customers and firms adopting new m-commerce products and services. The rate of adoption is fast.

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In this scenario, both businesses and individual customers have more money to spend and will adopt new m-commerce products and services. 3G or even more advanced generations of mobile technologies are adopted very quickly and more mcommerce products and services are launched on to the market at great speed. The innovative and distinguishing features of mobile technology, promising products and services may have features like: aggressive, fancy and efficient. The “killer bouquet” will reflect such features in the concrete products and services both in B2B, B2C, B2E, P2P areas, i.e. complex universal mobile payment, real time mobile customer relationship management applications both for sales persons and customers, mobile video conferencing, and real time mobile supply chain management, etc. By Bluetooth, wireless LAN and mobile Internet connectivity, wireless handheld devices, personal computers and laptops can work together and highlight the Multichannel principle of m-commerce. Rapid-down: The economic situation is sluggish and poor. Business organizations and customers do not have financial support to purchase the available m-commerce products and services. They adopt new m-commerce products and services according to their immediate needs and desires. In the Rapid-down scenario one can find product features like cost cutting, money saving, and time saving. Therefore, the products and services may be teleworking, supply chain management, customer relationship management and entertainment. Critical issues in this scenario are cost cutting, money saving and cheap operations. Mobile commerce allows developing such kinds of implementations, for example, introducing teleworking, mobile supply chain management solutions or mobile customer relationship management solutions for B2B and B2E purposes, and mobile entertainment for B2C or C2C purposes. These are all mobile applications with great potential cost cutting features. The ideal technologies allowing building such services are Bluetooth and WLAN for business applications; whereas for the consumer applications the GSM standard and the GPRS always-on connection are seen as the most suitable in this scenario. Bluetooth and WLAN do not require big investments in order to be implemented as intra- or extra-nets and the GSM together with the GPRS technologies are already a reality. The third generation networks, such as UMTS, may be instead located only in the metropolitan areas because of the lack of disposable investment capital. Slow-down: The economic situation is gloomy. Since m-commerce does not show much relative advantage compared to the prevailing products and services, firms and customers are very unwilling to use mobile services The average customer, like the average business, is quite unwilling to invest money in the new mobile devices, which are needed to get access to fancier mobile commerce applications. The producers, and some consumers, still regard mobile commerce as a promising future concept. The whole economic climate is frightened and cautious, and therefore people and companies spend their money on proven, safe solutions. The mobile commerce solutions have to clearly prove their workability to be accepted. The GPRS technology is bringing faster access to the Internet. Since the Internet is a well-known channel for banking, brokerage, shopping etc. the

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demand for mobile services of these kinds is very low. MMS (Multi Messaging Service) supporting GIF and JPEG, MPEG4, MP3 and MIDI will be implemented if UMTS and 3G solutions are carried out successfully. The SMS text message is still an unequivocal application. Some advanced SMS based applications may be used, for example, machine-to-machine applications Slow-up: The economy is growing stably. Business organizations and customers are willing to make new investments. However, the relative advantages provided by the m-commerce products and services are not perceived to justify the expenditure in them. The users in both the business and consumer sectors choose to invest in something else and the overall rate of adoption for mobile commerce is slow. In this scenario, despite the overall economic activity, the new generation mobile technologies are not adopted rapidly. The early hype of mobility is replaced by disinterest as truly beneficial services have failed to emerge. The “killer bouquet” of services is very down-to-earth, containing very fast, time-critical and non-intrusive services like ticketing and information-on-demand. In the business sector there are a number of applications using different technologies like Wireless LANs in order to automate processes. One of the most profitable parts of mobile commerce is Machine-to-Machine communication, continuing the trend of interconnected information systems to locations previously unreachable. 5. Conclusion In this paper we introduce an industry foresight tool in order to discover a useful route for the future of mobile commerce. We have developed a new framework for creating industry foresight. We focus on the MCI as a whole and provide two important axes of variables in order to build our initial foresight scenarios; adoption and diffusion of mobile commerce products and services and the macro economy development trend. From these variables we have derived four possible scenarios, or worlds, of mobile commerce; (1) rapid-up, (2) rapid-down, (3) slow-down, and (4) slow-up. We strongly believe that the foresight scenarios described above are useful to all actors in the MCI in order to find a competitive route for the future. We believe that our four scenarios described in this paper will enhance the capabilities for being ready for the future. Right now the mobile commerce actors who want to be first out on the 3G mobile commerce market will have to make competitive strategies and be prepared to launch the right products and services at the right moment. In a situation like this, where the MCI is on the starting line waiting for the call, the winning actors have to know exactly what the customers and the organisations out there want and need. We suggest that the adoption of new innovations and the economic situation are the two most important variables for finding out what products and services will be hits on the new markets. We have carried out some initial tests using economic reports and innovation adoption surveys, and we found that the results were encouraging. It also seems to be possible to plot different products and services on the matrix in further studies.

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Based on the feature characteristics of our four scenarios, we highlight some suggestions for the features of promising mobile commerce products and services. As the research moves further on, we will use information-gathering agents to search for information and refine our previous work continuously. Besides these, we may also have more systematic feedback from some industry actors who are connected to this MCI foresight. Thus, we are able to adjust our foresight framework, for instance, to refocus our variables or factors in the different scenarios, or even develop a new matrix of foresight scenarios, which may present the plausible futures in greater detail for a specific mobile commerce company. 6. References AJZEN, I.: From intentions to actions: a theory of planned behaviour. In KURL, J. and BECHMANN, J (eds). Action control: From cognition to behaviour. 1985, Springer Verlag, New York. BLACK, N. and LOCKETT, A. and WINKLHOFER, H. and ENNEW, C. (). The Adoption Of Internet Financial Services: A Qualitative Study. International Journal of Retail & Distribution Management. Vol.29, No.8, 2001,pp390-398. CARLSSON, C. and WALDEN, P. . The Mobile Commerce Quest For Value-Added Products And Services. In SSGRR 2001, L’Aquila, Italy,August 6-12,2001. COATES, JOSEPH F.: An Overview of Futures Methods, in: The Knowledge Base of Futures Studies, volume 2 – Organisations Practices Products, Richard A Slaughter(ed), DDM Media Group, Victoria, Australia 1996,pp 56-75. COOPRT LEE G.: Strategic marketing planning for radically new products, Journal of Marketing, Vol 64, January 2000,pp1-16. COOPER R.B. and ZMUD R.W.: Information technology implementation research: a technological diffusion approach. Management Science, Vol. 36, No. 2, Feb 1990. COOPER JUETT, R.: A Multidimensional Approach To The Adoption Of Innovation. Management Decision, 36/8, 1998, pp495-502. CRAWFORD, C.M.: New Products Management. 5th edition. 1996, Richard D. Irwin Inc. DAVIS, F.D : Perceived Usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13, 1989, pp319-340. ENGL JAMES F and BLACKWELL ROGER D. and MINIARD PAUL W: Consumer behavior, sixth edition, The Dryden Press,1990. FAHEY, L. and RANDALL, R.M. (ed.): Learning From The Future: Competitive Foresight Scenarios. 1998, John Wiley & Sons, Inc. FISHBEIN M. and AJZEN, I: Belief, attitude, intention and behaviour: an introduction to theory and research. 1975, Addison-Wesley, Reading MA. FRAMBACH, R.T.: An Integrated Model Of Organizational Adoption And Diffusion Of Innovations. European Journal of Marketing. Vol. 27 No.5, 1998, pp22-41. GOLD, B.:. Technological Diffusion In Industry: Research Needs And Shortcomings. Journal of industrial economics. Vol. 29,Issuew 3, 1981, pp247-269. GOPALAKRISHNA S and DAMANPOUR F: A review of innovation Research in Economics, sociology and technology management. Omega, Int.J. Mgmt Sci.Vol 25, No. 1, 1997, pp15-28. HANNAN, T.H. and MCDOWELL, J.M.: Rival Precedence And The Dynamics Of Technology Adoption: An Empirical Analysis. Economica. New Series, Vol. 54, Issue 214, 1987, 155-171. HAMEL, G. and PRAHALAD, C.K.: Competing for the Future. 1994, Harvard Business School Press, Boston

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