Proceedings of the 39th Hawaii International Conference on System Sciences

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1 Use of Internet Technologies and e-business Solutions: a Structural Model of Sources of Business Value among Canadian Micro-enterprises Charles H. Davis, Ryerson University, Toronto, Canada Florin Vladica, University of New Brunswick - Saint John, Canada Abstract This paper presents a structural model of sources of use value of Internet technologies and e-business solutions among micro-enterprises. The model postulates direct effects of connectivity, website functionality, transaction capability, and e-business use on perceived business value, and indirect effects of these capabilities on value creation via internal and external factors. The model is estimated with PLS with data from 181 micro-enterprises in Eastern Canada. It shows that perceived business value is predictable among micro-enterprises that use specific Internet technologies and e-business solutions to sell goods or services online and that seek to expand their market reach. This finding helps to explain the relatively slower uptake of e-business among micro-enterprises, many of which operate in face-to-face service industries and are embedded in local markets. 1. Introduction Micro-enterprises make up the majority of firms in most countries. 1 Canada has more than a half million employer micro-enterprises, representing 77% of all firms [15]; if owner-operated firms with no employees are included, the number of microenterprises is much larger. The development potential of micro-enterprises may seem to be huge, but these firms face numerous obstacles to growth. Furthermore, although information and communication technologies (ICTs) may appear to provide major advantages to micro-enterprises, the smallest firms lag larger SMEs in the adoption of most Internet technologies and e-business solutions [6, 7]. Most research on e-commerce adoption among SMEs has focused on SMEs in general. Very little has been published specifically about the technological behavior of micro-enterprises. Moreover, much of the research on SMEs use of e-commerce focuses on adoption patterns and barriers to adoption, rather than on business outcomes. In the present article we 1 In Canada, micro-enterprises are defined as firms with fewer than five employees. build on these lines of research to identify perceived sources of business value resulting from adoption and use of Internet technologies and e-business solutions by micro-enterprises. Based on data obtained from a survey of SME e-commerce users in eastern Canada, we present a structural model using PLS that identifies effects in micro-enterprises of e-commerce use on production of various kinds of business value. In our model, effects may be direct or moderated by internal or external facilitating or constraining factors. We investigate the direct and indirect effects of connectivity, website functionality, use of e-business solutions, and online transaction capability, and we identify the kinds of business value that micro-enterprises claim to derive from use of these technologies and solutions. Our research has implications for understanding processes of e-business enablement among the smallest enterprises, and for developing e- business products and services for the micro-enterprise sector. 2. Characteristics and growth challenges of micro-enterprises Few comprehensive empirically-based typologies of micro-enterprises have been published, but several types of micro-enterprise have been described in the literature. Among the micro-enterprises described by [15, 19], around one-third are growth oriented. Among these are high-growth ventures, micro-enterprises established by entrepreneurs with growth as a primary objective. High-growth micro-enterprise ventures are distinguishable by entrepreneurial intent (i.e. growth objectives) as well by characteristics of the entrepreneurs and their business plans [13]. Non growth-oriented micro-enterprises are lifestyle firms, firms with low capabilities, unregistered owner-operator firms, or firms established in distressed environments as vehicles to escape from poverty. Surveys of Canadian employer micro-enterprises show that more than three-quarters are owned by males, and over 80% of micro-enterprise owners are 40 years of age or older [15, 19]. However, surveys /06/$20.00 (C) 2006 IEEE 1

2 that include owner-operated firms show a much higher degree of participation by females and younger persons [23]. In the aggregate, Canadian employer micro-enterprises are not noticeably entrepreneurial or risk-oriented. Two-thirds have no expansion plans. Rate of graduation to the next size category of SMEs is about one percent over ten years [15]. However, firm longevity is impressive 83% of micro-enterprises are over seven years old (Ibid.). The owner-manager performs most of the business operations. Canadian micro-enterprises provide important sources of personal income and employment. In about three-quarters of cases, the micro-enterprise is the sole or most important source of income for its owner. Nearly half of micro-enterprises are located in homes [19]. The following characteristics of Canadian microenterprises or their owners are related positively to firm growth: higher education, entrepreneurial intensity, informal networking with customers and suppliers, business partnering, product innovation, adoption of e-business technologies, managerial delegation, focus on local market, age, and size (younger, smaller firms grow faster) [19; 20]. 3. E-commerce adoption and use: models of sources of business value Only a limited amount of research has been published on IT or e-commerce adoption and use by micro-enterprises in wealthy Northern countries (see especially [8, 11, 22]). The approach is primarily qualitative and the recurring emphasis is on the social embeddedness of the firm that is believed to influence or even determine the firm s business behavior. [9] propose a conceptual framework regarding e-commerce adoption by smaller firms. They emphasize the competencies and orientation of the micro-enterprise owner-manager, the perception of opportunity and value, and the implications of risk aversion. How should the use of IT to create business value be conceptualized? The literature contains an impressive array of models of IT adoption and value creation by firms. Stage or ladder models, which are popular in policy and some scholarly literature on e- commerce adoption by SMEs, refer to steps of engagement in increasing technological complexity or process integration (e.g. [5]). Because they introduce concepts of evolution, technological trajectories, and technology packages (bundles of interconnected technologies), stage models provide a potentially valuable framework for understanding the dynamics of technological change. Unfortunately, while the stage model makes conceptual sense, it seems not to accurately describe SMEs behavior ([17, 26]. Empirical research suggests instead patterns of adoption in specific functional areas of the firm, often in response to perceived opportunities or threats represented by customers, suppliers, or competitors [17]. Furthermore, because of their size, micro-enterprises are unlikely candidates for intensive internal process integration. Finally, the vast majority of Canadian micro-enterprises are oriented toward the local market. Therefore, the potential of Internet technologies and e-business solutions to facilitate internationalization is not likely to be of great interest to them. However, some micro-enterprises that do seek to develop export activities, such as the small craft firms described in [12] are natural candidates for adoption of e-commerce solutions. In summary, stage models referring to stages of technological complexity do not appear promising at present as conceptual frameworks for understanding the technological behavior of micro-enterprises. Much e-commerce and IT adoption research conceptualizes adoption and its outcomes in terms of technological, organizational, and environmental variables (for a review of this literature see [25]). Although these models go by a variety of names, we will call them TOE (Technology-Organization-Environment) models after [27]. In TOE models, the dependent variable can be adoption, business performance, or business value, and many combinations of independent variables have been used [24]. Our structural model, described below, is based on TOE models of technology adoption, and our measurement model uses an index of perceived business outcomes as the dependent variable. Value creation from IT assets is an unsettled area in IS/IT research and is characterized by considerable conceptual and methodological diversity [3, 16, 21]. We assembled a composite list of possible outcomes of use of Internet technologies and e-business solutions from the scholarly literature and from statistical agency survey questionnaires, and we used a streamlined version of this list of variables to construct the composite dependent variable. Our survey of use of Internet technologies and e- business solutions among SMEs in New Brunswick, Canada was conducted in March and April, 2004 (for complete results see [7]). Responses were solicited regarding technology use, the economic and social characteristics of the firm, perceived constraints to and facilitators of adoption of Internet technologies and e-business solutions, desired support services, and perceived impacts or benefits of adoption of these technologies. Participation was solicited via local economic development agencies. Response rate was about 12%, much higher than reported average response rates for web-based surveys. 2

3 The main drawback of online surveys is that they exclude possible respondents who do not have online capabilities [9]. Since our research focuses only on current e-business users, exclusion of non users is not an issue. In other words, our research refers only to current users of Internet technologies and e-business solutions. It does not refer to non-users or potential users. Of the 280 respondents, 181 were micro-enterprises. Micro-enterprises represent about two-thirds of the population of respondent firms, but only 11% of employees and 14% of sales of the respondent population. This is comparable to the distribution and economic and employment size of micro-enterprises in the New Brunswick economy. Around half the firms were in tourism, arts and crafts, consulting and professional services, IT services, and other services. Are processes of technology adoption and value creation in micro-enterprises similar to processes in larger firms, except on a smaller scale? Except for the most widely diffused Internet technologies and e- business solutions, which are used by practically all SMEs ( , PCs, access to the Internet), microenterprises lag behind larger SMEs in the adoption of nearly all other technologies (see Figure 1). Other important differences are found between micro-enterprises and larger SMEs regarding exposure to competition, facilitators of e-business adoption, perceived barriers, declared needs and desired capabilities, and strategic behavior [7]. However, although they adopt Internet technologies and e-business solutions more slowly than larger SMEs, online micro-enterprises are quicker than larger SMEs to identify and exploit opportunities for Internet-based export: micro-enterprises have the highest rate of Internet-based export sales of SME size classes (on average 26% of microenterprises Internet sales are to international customers). 4. Measurement and structural models In this paper we employ a version of the TOE class of explanatory frameworks, testing a range of internal and external enabling and constraining factors as exogenous variables that respondents rated in importance on a five-point Likert scale. The other set of exogenous variables in our model has to do with use of various Internet technologies and e-business solutions. Since the purpose of this research is to identify sources of business value, Internet technologies and e- business solutions are exogenous variables in our model (we do not seek to explain the conditions that led to their adoption). Most of the business value variables measure the respondent s perception of impact of IT on business on a five-point Likert scale. (It would obviously be of interest to compare the microenteprise owner-manager s perception of IT impacts with objective measures of impacts. The accuracy of micro-enterprise owner-managers attributions of changes in business performance to use of technology is a topic requiring research). We have also included several objective measures among the business value variables having to do with rate of growth and geographical composition of revenue. The model contains seven composite variables (described in Table 3). Indicators measuring the use of Internet technologies and e-business solutions are grouped into four composite variables: connectivity, website functionality, e-business use, and transactions. Indicators measuring internal and external enabling and constraining factors are grouped into two composite variables: internal and external factors. (The distinction between internal and external factors that constrain or enable firm performance is commonly accepted in competitiveness research; see for example [18]). Significant indicators for each composite variable are shown in Table 1. The composite dependent variable, business value, is comprised of a number of outcome indicators as described in Table 3. We modeled the data using the technique of Partial Least Squares (PLS). 2 All of the measurement relationships between indicators and constructs in our model are specified as formative. In other words, the latent constructs are conceived as being formed by the indicators that measure them, rather than the reverse. Constructs created with formative indicators are linear composites of the indicators, and are conventionally called composite variables or indices. Reflective indicators must be unidimensional and correlated, while formative indicators need not be [2, 14]. The literature does not contain tested constructs or validated scales that are suitable for use as reflective indicators for measuring adoption of Internet technologies and e- business solutions. Therefore, although the use of formative indicators is less elegant than a model based on reflective indicators, the current state of theory obliges us to use formative indicators and so we make do with composite variables. The structural model is shown in Figure 2. The composite variables External Factors and Internal Factors are hypothesized to moderate the effects of the Internet technologies and e-business solutions on firm performance. We also hypothesized that these e- commerce technologies have direct effects on firm performance. The significance levels of variables were measured using PLS s bootstrap re-sampling procedures. Ex- 2 We used PLS Graph build

4 ogenous variables with significant negative weights were eliminated from the model in several iterations, but variables with non significant weights were not removed from the model. 5. Results and discussion Significant exogenous variables in the model are shown in Table 1, along with their path weights and level of significance. Table 2 shows levels of significance of hypothesized pathways and Figure 2 shows path coefficients. As seen in Figure 2, the model has modest predictive power for two of the dependent variables (external factors and internal factors), and good predictive power for the composite variable for business value (R 2 =.524). All dependent variable R 2 s are significant at p<.001. The meaning of the model can be summarized as follows: Micro-enterprises report greatest business value from market development, information sharing with customers, and undertaking online transactions. Market development and recruitment of distant customers are significant external moderating factors, while ICT implementation capabilities and strategic choice of products and services that lend themselves to Internet commerce are significant internal moderating factors. Website functionality has a strong indirect effect on business value via external factors (defined by exogenous variables measuring market development) if the firm has an external website. E-business use (defined by the exogenous variables measuring use of shared file folders and remote data storage) has a strong direct effect on business value. Transactions (defined by exogenous variables measuring online presence and intensity of online commercial activity) have strong direct effects on business value as well as strong indirect effects via internal and external factors. Connectivity (speed, mode, or combination of connections to the Internet) has no measurable direct or indirect effects on business value. Moreover, connectivity, website functionality, or interactivity per se are not important sources of business value for microenterprises. In micro-enterprises, the production of value from e-business appears to be lumpy. Increased profitability, increased productivity, increased adaptability, increased market share improvements in one area seem to bring improvements in other areas. This suggests that for micro-enterprises, the business value construct might be developed as a scale rather than as a composite index. 6. Conclusions The model that we have described portrays microenterprises that grow by adopting web-based commerce and developing new markets for products and services, especially products and services that lend themselves to Internet commerce. The firms create business value that includes top line and bottom line benefits. This business model does not characterize the average member of the community of New Brunswick micro-enterprises. It seems, instead, to characterize micro-enterprises that are actively exploiting Internet technologies and e-business solutions for purposes of business development and export growth. The fact that this business model emerges clearly from the survey data suggests that evolutionary pressures and learning processes are at work on some members of the micro-enterprise community, inducing them to use Internet technologies and e-business solutions to undertake business activities that produce value in new ways. However, many of the micro-enterprises in our survey are in segments of the service industry, and with the exception of tourism the market for these services is primarily local. Enablement of global reach is of little interest to these firms, but affordable and reliable Internet technologies and e-business solutions that provide local visibility, security, interactivity, data sharing, and mobility should be of interest. 7. Acknowledgements Research reported here was supported by a contract to the Electronic Commerce Centre of the University of New Brunswick from the Atlantic Canada Opportunities Agency (ACOA) to develop e-commerce training and awareness services for SMEs in New Brunswick. This support is gratefully acknowledged. Data analysis was supported through a project funded by the Social Sciences and Humanities Research Council (SSHRC) for research in Atlantic Canada on Innovation Systems and Economic Development: the Role of Local and RegionalClusters in Canada. This support is gratefully acknowledged also. Finally, thanks to Dr. Barbara Marcolin for her assistance with PLS, and to anonymous reviewers. Errors are our own. 8. References 4

5 [1] Amit, R., and Zott, C, Value Creation in e-business, Strategic Management Journal 22, (2001), [2] Chin, W., "The Partial Least Squares Approach to Structural Equation Modeling," In G.A. Marcoulides (ed.), Modern Business Research Methods, Mahwah, New Jersey: LEA, [3] Cronk, M.C., and Fitzgerald, E.P., Constructing a Theory of IS Business Value from the Literature, Electronic Journal of Business Research Methods 1(1), 2002, [4] Daniel, E., An Exploration of the Inside-Out Model : e-commerce Integration in UK SMEs, Journal of Small Business and Enterprise Development 10(3), 2003, [5] Daniel, E., and Grimshaw, D.J., An Exploratory Comparison of Electronic Commerce Adoption in Large and Small Enterprises, Journal of Information Technology 17, 2002, [6] Davis, C.H., and Vladica, F., Adoption and Use of Internet Technologies and e-business Solutions by Canadian Micro-enterprises, Proceedings of the Annual Conference of the International Association for Management of Technology, Vienna, May [7] Davis, C.H., and Vladica, F., Adoption of Internet Technologies and e-business Solutions by Small and Medium Enterprises (SMEs) in New Brunswick. Report prepared for the Atlantic Canada Opportunities Agency, August [8] De Berranger, P. Tucker, D., and Jones, L., Internet Diffusion in Creative Micro-businesses. Identifying Change Agent Characteristics as Critical Success Factors, Journal of Organizational Computing and Electronic Commerce 11(3), 2001, [9] Evans, J.R., and Mathur, A., The Value of Online Surveys, Internet Research 15(2), 2005, [10] Fillis, I., The Internationalization Process of the Craft Microenterprise, Journal of Developmental Entrepreneurship 7(1), 2002, [11] Fillis, I., Johansson, U., and Wagner, B., A Qualitative Investigation of Smaller Firm e-business Development, Journal of Small Business and Enterprise Development 11(3), 2004, [12] Fillis, I., Johansson, U., and Wagner, B., Factors Impacting on e-business Adoption and Development in the Smaller Firm, International Journal of Entrepreneurial Behaviour and Research 10(3), 2004, [13] Friar, J.H., and Meyer, M.H., Entrepreneurship and Start-ups in the Boston Region: Factors Differentiating High-Growth Ventures from Micro-Ventures, Small Business Economics 21, 2003, [14] Gefen, D., Straub, D.W., and Boudreau, M.-C., Structural Equation Modeling and Regression: Guidelines for Research Practice, Communications of the Association for Information Systems 4(7), 2000, October. [15] Industry Canada, Micro-Enterprises Survey 2000: a Progress Report. Small Business Policy Branch, Ottawa, [16] Kwon, D., Watts-Sussman, S., and Collopy, F., Value Frame, Paradox and Change: the Constructive Nature of Information Technology Business Value. Cleveland: Sprouts Working Papers on Information Environments, Systems and Organizations, [17] Levy, M., and Powell, P., Exploring SME Internet Adoption: Towards a Contingent Model, Electronic Markets 13(2), 2003, [18] Man, T.W.Y., Lau, T., and Chan, K.F., The Competitiveness of Small and Medium Enterprises. A Conceptualization with a Focus on Entrepreneurial Competencies, Journal of Business Venturing 17, 2002, [19] Papadaki, E., and Chami, B., Growth Determinants of Micro-Businesses in Canada. Industry Canada: Small Business Policy Branch, Ottawa, [20] Perren, L., Factors in the Growth of Microenterprises. Part 1: Developing a Framework, Journal of Small Business and Enterprise Development 64), 1999, [21] Pflughoeft, K., Ramamurthy, A.K., Soofi, E.S., Yasai-Ardekani, M., and Zahedi, F., Multiple Conceptualizations of Small Business Web Use and Benefit, Decision Sciences 34(3), 2003, [22] Pierson, J., There s No Business Like Small Business: the Use and Meaning of ICT for Micro-Enterprises, paper presented at the conference The 5

6 Good, the Bad and the Irrelevant, Helsinki, September [23] Robichaud, Y., and McGraw, E., Les objectifs entrepreneuriaux comme facteur explicatif de la taille des entreprises, paper presented at the 7ème Congrès International Francophone en Entrepreneuriat et PME, Montpellier, October [24] Van der Deen, M., Measuring e-business Adoption in SME, chap. 3 in W. During, R. Oakey, & S. Kauser, eds., New Technology-Based Firms in the New Millenium, v. 3. Amsterdam: Elsevier, MERIT-Infonomics Research Memorandum Series [26] Zheng, J., Caldwell, N., Harland, C., Powell, P., Woerndl, M., Xu, S., Small Firms and e-business: Cautiousness, Contingency, and Cost-Benefit, Journal of Purchasing and Supply Chain Management 10, 2004, [27] Zhu, K., Xu, S., and Dedrick, J., Assessing Drivers of e-business Value. Results of a Cross- Country Study, Proceedings of the 24 th International Conference on Information Systems, , [25] Windrum, P., and de Berranger, P., The Adoption of e-business Technology by SMEs. Maastricht: 6

7 Figure 1: SME adoption of various Internet technologies and e-business solutions by size category of firm, New Brunswick, Canada, A B C D E F G H I J K L M N O P micro (<5) very small (5-19) small (20-49) medium (50-499) Total Scale: percent of firms in each size category using technology or solution. N = 280 firms. Legend: A: . B: Internet. C: Personal computer. D: Functional (application) software. E: External website. F: Wireless. G: Shared file folders. H: Secure transactions with consumers. I: Secure transactions with business or government. J: Remote data storage. K: Intranet. L: Hosted solutions. M: Extranet. N: Remote help desk. O: Networking/information security technology (firewall, anti-virus software, access control). P: Net meetings. Source: [7]. 7

8 Figure 2: structural model of sources of business value among micro-enterprise users of Internet technologies and e-business solutions. **** p<.001; *** p<.01; ** p<.05; * p<.1. Non significant pathways are in dotted lines. Non significant variables are not shown. 8

9 Table 1: significant indicators in the model construct code explanation Metric weight sig. connectivity Q35_4 T1 line or greater don t use/plan to use/use now ** e-business Q40 shared file folders Q47 remote data storage website Q42 external website don t use/plan to use/use now *** don t use/plan to use/use now 0.46 ** don t use/plan to use/use now 0.67 *** don t use/plan to transaction Q56 goods or services sold via Internet use/use now **** Q57i percent of gross sales conducted on the Internet Continuous *** external factors Q26r find customers abroad 5 point scale ** Q76r possibility to access new markets 5 point scale *** internal factors Q32r implementing new ICTs 5 point scale * Q75r nature of goods or services sold 5 point scale *** business value Q59r increased productivity 5 point scale **** Q60r increased profitability 5 point scale **** Q61r increased speed of delivery 5 point scale **** Q62r increased adaptability 5 point scale **** Q63r increased domestic market share 5 point scale 0.09 **** Q64r increased international market share 5 point scale **** Q65r increased customer service 5 point scale **** Q66r improved relationships with existing customers 5 point scale **** Q67r kept up with competitors 5 point scale **** Q68r decreased cost of production 5 point scale **** Q69r increased quality of goods and services 5 point scale **** Q70r improved coordination with partners or suppliers 5 point scale **** Q71r improved rate of new product development 5 point scale **** Q72r developed unique expertise or market 5 point scale **** Q73r improved brand image 5 point scale 0.1 **** growth average annual rate of growth, past three years continuous **** **** p<.001; *** p<.01; ** p<.05; * p<.1. Non significant variables are not shown. 9

10 Table 2: significance of pathways in the model external factors internal factors connectivity transactions e-business use website functionality external factors n.s. ***** n.s. **** internal factors n.s. ***** * n.s. business value *** ***** n.s. ***** **** n.s. **** p<.001; *** p<.01; ** p<.05; * p<.1 Table 3: variables originally in the model Business value: increased productivity, increased profitability, decreased cost of production, increased quality of goods and services, improved rate of new product development, developed unique expertise or market, increased speed of delivery, increased adaptability, increased domestic market share, increased international market share, increased customer service, improved relationships with existing customers, kept up with competitors, improved coordination with partners or suppliers, improved brand or image. Internal factors: nature of goods or services sold, skillful employees, business processes that support learning, capability of managing technological change, management effectiveness, management commitment, leadership quality, strategic objectives, internal business culture, attitude toward risk, entrepreneurship, focus, keeping overhead costs down, improving the quality of groducts and services, improving staff productivity, attracting and retaining staff, managing customer information, managing and communicating with mobile staff, managing office information technology, implementing new information and communication technologies, managing and reporting financial and tax information. External factors: purchasing supplies and raw materials, costs of equipment, developing niche or specialized markets, delivery of product and services to customers, attracting new domestic customers, find customers abroad, getting marketing message out, geographical distance from customers and suppliers, possibility to access new markets, competitive threats, demanding customers or suppliers, access to specialized suppliers, access to financial resources, favorable regulatory environment, intenwity of competition. Index of connectivity: use of dialup, cable modem, high speed, T1 or greater, wireless. Index of e-business use: items in Figure 1. Index of transactions: use of Internet to buy, to sell; percent of gross sales conducted over the Internet. Index of website functionality: organization has a website, online payment, asynchronous two-way communcation, synchronous two-way communication, digital products or services delivered via the website, secure website, privacy poliy statement, wireless access, information about products, information about the business. 10