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Economic Implications of e-Business for Organizations

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Handbook of Strategic e-Business Management

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Abstract

We review the macroeconomic and microeconomic impacts of e-business on organizations. E-business improves the economic efficiency of national economies through greater capital formation and long-run efficiency gains. E-business affects many aspects of the economy, from international trade to monetary and fiscal policies. At the microeconomic level, we use Porter’s Five Forces to organize our discussion of how e-business changes the creation of value and its division among market players. ICT affects industry through many channels and at many levels, from how inputs are purchased to how final goods and services are sold and delivered. The corporate strategist must consider how e-business may change the nature of rivalry among the competitors. Changes in upstream and downstream interactions in the market and expanded opportunities for substitutes and potential entrants also influence strategy. Thus, e-business can alter strategy by changing the nature of entry threats, suppliers’ power, buyers’ power, threats from substitutes, and rivalry among existing firms. We discuss empirical results from the literature wherever possible to illustrate the importance of e-business for a firm’s strategy. We close with a brief look at e-business and non-profit organizations.

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Notes

  1. 1.

    We use the term e-business to refer to any use of ICT by organizations. We reserve the term e-commerce to refer specifically to ICT use in commercial transactions among organizations and consumers.

  2. 2.

    We note some exceptions in Sect. 3.

  3. 3.

    We mainly focus on the US and European economies, but include estimates for developing nations when available.

  4. 4.

    In growth accounting, TFP is a measurement of changes in output that are not directly attributed to changes in the supply of labor, capital, or other factors of production (Jorgenson et al. 2006).

  5. 5.

    The US consumer price index (CPI) overstated inflation by as much as 1.1 % annually during the 1990s (Boskin et al. 1996), and (despite improved methodology) probably still overstates inflation by as much as 0.8 % points per year (Gordon 2006). Likewise, European price indices largely neglected quality improvements (Timmer and van Ark 2005).

  6. 6.

    See also the survey on online price dispersion research by Baye et al. (2007).

  7. 7.

    Originally, the definition of e-money only included payment methods that stored monetary value on a device in the possession of the consumer. New types of e-money have instead largely been server-based, where funds are stored on the issuer’s servers or a distributed network and consumers access their funds remotely (Hartmann 2006).

  8. 8.

    Refer to ECB (1998) and Prieger and Heil (2010a) for more complete discussions.

  9. 9.

    One reason for the slow acceptance of e-money are its strong network effects: demand is contingent on merchants’ willingness to exchange goods and services for the e-money, but merchants have little incentive to accept new sources of money that are not popular among consumers (Hartmann 2006).

  10. 10.

    Online retailer Amazon.com responded to the California law by ending its relationship with its California affiliates. California lawmakers have subsequently repealed the law in exchange for Amazon’s cooperation with future efforts to streamline the nation’s sales tax system.

  11. 11.

    Unsurprisingly, Bruce et al. (2009) find that states with larger than average percentage losses include states like California and New York who have been particularly aggressive in redefining what counts as a “physical presence” within a state.

  12. 12.

    It is important to note that the strategic approach taken here differs from a normative economic approach. While the Five Forces are organized to help a corporate strategist assess competition and profitability from the industry participant’s point of view, a typical normative economic approach instead emphasizes social efficiency and welfare. See Prieger and Heil (2010a, b) for the economic view of the impact of e-business.

  13. 13.

    We also set aside another factor affecting the threat of entry, government policy that raises entry barriers, because policy regarding e-business is an extensive field of academic study that is largely separate from the strategy literature. See Kraemer et al. (2006) for an overview of policy toward e-business across countries.

  14. 14.

    See also the many other studies cited in Sect. 3.3 of Forman and Goldfarb (2006).

  15. 15.

    Mitra and Singhal (2008) define B2B hubs as “virtual marketplaces that enable any-to-any transactions between buyers and sellers, aggregate demand and supply, and enable price determination through a variety of mechanisms such as catalogs, real-time negotiation, auctions, and reverse auctions. These hubs [provide an infrastructure for commerce by] matching buyers and sellers, facilitating product comparisons”.

  16. 16.

    However, sellers may obfuscate their offerings precisely to avoid such transparency, as we explain below in Sect. 3.4.2.

  17. 17.

    As examples of hubs in which sellers hold the upper hand, Ravichanran et al. (2007) point to “forward aggregation sites typically associated with either supplier aligned or neutral hubs with the primary role of enabling suppliers to reach a larger set of buyers.” See those authors for specific examples of such B2B hubs.

  18. 18.

    For a contrary view, see Cordella (2006), who argues that in some situations ICT increases transaction costs due to information overload and other market, organizational, or managerial imperfections.

  19. 19.

    See Sect. 4.2 of Katz (1989).

  20. 20.

    Susarla et al. (2011) measure trust with the extent of collaboration between suppliers and buyers, attitudinal willingness to transact with the exchange partner, and the comfort-level reported by exchange partners in their survey data. Performance of the supply chain was measured with the incidence of stock-outs.

  21. 21.

    See Prieger and Heil (2010b) for a review of other empirical studies of the benefits of VSCI.

  22. 22.

    See Lucking-Reiley and Spulber (2001) and Parker and Anderson (2002) for general discussion; see Görg et al. (2008) for empirical evidence on outsourcing and improved productivity.

  23. 23.

    To illustrate mass customization, consider just one line of residential garage doors out of the several offered through HomeDepot.com: Clopay’s Coachman line. With the various options for style, color, materials, and hardware, there are 844,800 combinations for a doublewide door from which to choose (authors’ calculations, as of March 2012).

  24. 24.

    Rensmann and Smits (2008) describe CareAuction, a reverse auction platform in The Netherlands supporting the allocation of requests from individual maternity care patients (via their insurance companies) to care providers.

  25. 25.

    If the substitute good is more profitable to the large bundler than to a stand-alone rival, then the fundamental idea of gains from trade imply that, absent other considerations, the two parties will be able to agree upon a transaction that transfers sale of the product to the bundler, gives a payment to the rival, and makes both sides better off.

  26. 26.

    With a demand elasticity of -20, the theory of pricing with market power suggests that the relative markup (or Lerner Index, defined as the ratio of price less marginal cost to price) a firm could set is just 5 %.

  27. 27.

    In particular, Augereau et al. (2006) show that ISPs were less likely to adopt a particular modem standard the more that competitors adopted it.

  28. 28.

    See also Bonera (2011) and Cao et al. (2005) on the importance of perceived security and trust to customers in e-commerce.

  29. 29.

    Given the high degree of comfort with and the prevalence of search engine usage today in most developed nations, this result may have current relevance only to emerging markets where e-commerce is in a nascent stage.

  30. 30.

    Given that Porter’s (2008) Five Forces model is rooted in the older “Structure-Conduct-Performance” view of an industry, his work pays less attention to the ways that rivalry itself shapes market structure, as the “New Industrial Organization” focuses on (see, for example, Jacquemin (1987) and Tirole (1988)).

  31. 31.

    See Pepall et al. (2005, p.364).

  32. 32.

    A firm’s hazard rate is its probability of exiting in the current period, conditional on surviving up to that period. See also evidence from Goldfarb et al. (2007), who show that even though the “Get Big Fast” strategy pursued during the dot.com boom may not have been optimal, it may not have led to increased chances of a firm’s failure due to counteracting effects.

  33. 33.

    See also Zorn et al.’s (2011) survey of the literature on ICT adoption and use among nonprofits.

References

  • Alesina, A., & Summers, L. H. (1993). Central bank independence and macroeconomic performance: Some comparative evidence. Journal of Money, Credit, and Banking, 25(2), 151–162.

    Google Scholar 

  • Anderson, C. (2006). The long tail: Why the future of business is selling less of more. New York: Hyperion Press.

    Google Scholar 

  • Animesh, A., Ramachandran, V., & Viswanathan, S. (2010). Research note—Quality uncertainty and the performance of online sponsored search markets: An empirical investigation. Information Systems Research, 21(1), 190–201.

    Google Scholar 

  • Augereau, A., Greenstein, S., & Rysman, M. (2006). Coordination versus differentiation in a standards war: 56 K modems. The Rand Journal of Economics, 37(4), 887–909.

    Google Scholar 

  • Bachis, E., & Piga, C. A. (2011). Low-cost airlines and online price dispersion. International Journal of Industrial Organization, 29(6), 655–667.

    Google Scholar 

  • Bailey, J.P. (1998). Electronic commerce: prices and consumer issues for three products: Books, compact discs, and software, Organisation for Economic Co-operation and Development (OECD), DSTI/ICCP/IE(98)4, available online at www.oecd.org/dataoecd/13/31/35497325.pdf

  • Bakos, J. Y. (1997). Reducing buyer search costs: Implications for electronic marketplaces. Management Science, 43(12), 1676–1692.

    Google Scholar 

  • Bakos, Y., & Brynjolfsson, E. (2007). Bundling and competition on the internet. In E. Brousseau & N. Curien (Eds.), Internet and digital economics: Principles, methods and applications (pp. 313–344). Cambridge: Cambridge University Press.

    Google Scholar 

  • Bakos, Y., Lucas, H. C, Jr, Oh, W., Simon, G., Viswanathan, S., & Weber, B. W. (2005). The impact of e-commerce on competition in the retail Brokerage Industry. Information Systems Research, 16(4), 352–371.

    Google Scholar 

  • Banerjee, S., & Golhar, D. Y. (1994). Electronic data interchange: Characteristics of users and nonusers. Information & Management, 26(2), 65–74.

    Google Scholar 

  • Bank for International Settlements (BIS). (1996). Implications for central banks of the development of electronic money. Basel: Bank for International Settlements.

    Google Scholar 

  • Basu, A. & Siems, T.F. (2004). The impact of e-business technologies on supply chain operations: A macroeconomic perspective. Research Department Working Paper 0404. Dallas: Federal Reserve Bank of Dallas.

    Google Scholar 

  • Baye, M.R., Morgan, J., Scholten, P., (2007). Information, search, and price dispersion. In T. Hendershott (ed.), Handbook of economics and systems. Amsterdam: North-Holland.

    Google Scholar 

  • Berthon, P., Ewing, M., Pitt, L., & Naudé, P. (2003). Understanding B2B and the web: The acceleration of coordination and motivation. Industrial Marketing Management, 32(7), 553–561.

    Google Scholar 

  • Blum, B., & Goldfarb, A. (2006). Does the internet defy the law of gravity? Journal of International Economics, 70, 384–405.

    Google Scholar 

  • Bock, G.-W., Lee, S.-Y., & Li, H. (2007). Price comparison and price dispersion: products and retailers at different internet maturity stages. International Journal of Electronic Commerce, 11(4), 101–124.

    Google Scholar 

  • Bonera, M. (2011). The propensity of e-commerce usage: The influencing variables. Management Research Review, 34(7), 821–837.

    Google Scholar 

  • Boskin, M.J., Dulberger, E.R., Gordon, R.J., Griliches, Z. & Jorgenson, D. (1996). Toward a more accurate measure of the cost of living. Final Report to the Senate Finance Committee, December 4.

    Google Scholar 

  • Brookes, M., & Wahhaj, Z. (2001). The economic effects of business to business internet activity. National Institute Economic Review, 175(1), 95–108.

    Google Scholar 

  • Brown, J. R., & Goolsbee, A. (2002). Does the internet make markets more competitive? Evidence from the life insurance industry. Journal of Political Economy, 110(3), 481–507.

    Google Scholar 

  • Bruce, D., Fox, W. F., & Luna, L. (2009). State and local sales tax revenue losses from e-commerce. State Tax Notes, 52(7), 537–558.

    Google Scholar 

  • Brynjolfsson, E. (1993). The productivity paradox of information technology. Communications of the ACM, 36(12), 67–77.

    Google Scholar 

  • Brynjolfsson, E., & Hitt, L. M. (2002). Computing productivity: Firm-level evidence. Review of Economics and Statistics, 85(4), 793–808.

    Google Scholar 

  • Brynjolfsson, E., & Smith, M. D. (2000). Frictionless commerce? A comparison of internet and conventional retailers. Management Science, 46(4), 563–585.

    Google Scholar 

  • Brynjolfsson, E., Hu, Y., & Smith, M. D. (2003). Consumer surplus in the digital economy: Estimating the value of increased product variety at online booksellers. Management Science, 49(11), 1580–1596.

    Google Scholar 

  • Buhalis, D., & Zoge, M. (2007). The strategic impact of the internet on the tourism industry. In M. Sigala, et al. (Eds.), Information and communication technologies in tourism (pp. 481–492). Vienna: Springer Vienna.

    Google Scholar 

  • Cao, M., Zhang, Q., & Seydel, J. (2005). B2C e-commerce web site quality: An empirical examination. Industrial Management & Data Systems, 105(5), 645–661.

    Google Scholar 

  • Carr, N. G. (2003). IT doesn’t matter. Harvard Business Review, 81, 5–12.

    Google Scholar 

  • Chakrabarti, R., & Scholnick, B. (2007). The mechanics of price adjustment: New evidence of the (un)importance of menu costs. Managerial and Decision Economics, 28(7), 657–668.

    Google Scholar 

  • Chellappa, R. K., Sin, R. G., & Siddarth, S. (2010). Price formats as a source of price dispersion: A study of online and offline prices in the domestic US airline markets. Information Systems Research, 22(1), 83.

    Google Scholar 

  • Choudhury, V. (1997). Strategic choices in the development of interorganizational information systems. Information Systems Research, 8(1), 1–24.

    Google Scholar 

  • Clarke, G. R. G. (2008). Has the internet increased exports for firms from low and middle-income countries? Information Economics and Policy, 20(1), 16–37.

    Google Scholar 

  • Clay, K., Krishnan, R., & Wolff, E. (2001). Prices and price dispersion on the web: evidence from the online book industry. Journal of Industrial Economics, 49(4), 521–539.

    Google Scholar 

  • Clemons, E. K. (2008). How information changes consumer behavior and how consumer behavior determines corporate strategy. Journal of Management Information Systems, 25(2), 13–40.

    Google Scholar 

  • Clemons, E. K., Hann, I., & Hitt, L. (2002). Price dispersion and differentiation in online travel: An empirical investigation. Management Science, 48(4), 534–550.

    Google Scholar 

  • Clemons, E. K., Spitler, R., Gu, B., & Markopoulos, P. (2005). Information, hyperdifferentiation, and delight: The value of being different. In S. Bradley & R. Austin (Eds.), The broadband explosion: Leading thinkers on the promise of a truly interactive world (pp. 116–137). Boston: Harvard Business School Press.

    Google Scholar 

  • Committee on Payment and Settlement Systems (CPSS). (2008). Statistics on Payment and Settlement Systems in Selected Countries. Basel, Switzerland: Bank for International Settlements.

    Google Scholar 

  • Cordella, A. (2006). Transaction costs and information systems: Does it add up? Journal of Information Technology, 21, 195–202.

    Google Scholar 

  • Cummins, J. G., & Violante, G. L. (2002). Investment-specific technical change in the United States (1947–2000), Measurement and macroeconomic consequences. Review of Economic Dynamics, 5(2), 243–284.

    Google Scholar 

  • Davila, A., Gupta, M., & Palmer, R. (2003). Moving procurement systems to the internet: Adoption and use of e-procurement technology. European Management Journal, 21, 11–23.

    Google Scholar 

  • Day, G. S., Fein, A. J., & Ruppersberger, G. (2003). Shakeouts in digital markets: Lessons from B2B exchanges. California Management Revue, 45(2), 131–150.

    Google Scholar 

  • Dewan, S., & Hsu, Vernon. (2004). Adverse selection in electronic markets: Evidence from online stamp auctions. Journal of Industrial Economics, 52(4), 497–516.

    Google Scholar 

  • Economides, N. (1996). Network externalities, complementarities, and invitations to enter. European Journal of Political Economy, 12(2), 211–233.

    Google Scholar 

  • Economides, N. (2007). The internet and network economics. In E. Brousseau & C. Nicolas (Eds.), Internet and digital economics: Principles, methods and applications (pp. 239–267). Cambridge: Cambridge University Press.

    Google Scholar 

  • Efendi, J., Kinney, M.R. & Smith L.M. (2007). Technology and profitability: Did B2B buy-side e-commerce systems improve financial performance? Unpublished manuscript, Texas A&M University.

    Google Scholar 

  • Ellison, G., & Ellison, S. F. (2009). Search, obfuscation, and price elasticities on the internet. Econometrica, 77(2), 427–452.

    Google Scholar 

  • Eppright, D. R., & Hawkins, R. R. (2009). Determinants of emerging e-commerce markets: A developmental perspective. Journal of Internet Commerce, 8(1–2), 113–134.

    Google Scholar 

  • Ernst & Young. (1999). The second annual ernst and young internet shopping study: The digital channel continues to gather steam. New York: Ernst and Young.

    Google Scholar 

  • Etro, F. (2009). The economic impact of cloud computing on business creation, employment and output in Europe. Review of Business and Economics, 54(2), 179–208.

    Google Scholar 

  • European Central Bank (ECB). (1998). Report on electronic money. Frankfurt am Main: ECB.

    Google Scholar 

  • European Commission, DG Enterprise and Industry (EC DGEI) (2010). ICT and e-business for an innovative and sustainable economy: 7th Synthesis Report of the Sectoral e-Business Watch. Luxembourg: Office for Official Publications of the European Communities.

    Google Scholar 

  • Finn, S., Maher, J. K., & Forster, J. (2006). Indicators of information and communication technology adoption in the nonprofit sector: Changes between 2000 and 2004. Nonprofit Management and Leadership, 16(3), 277–295.

    Google Scholar 

  • Forman, C. (2005). The corporate digital divide: Determinants of internet adoption. Management Science, 51(4), 641–654.

    Google Scholar 

  • Forman, C., & Goldfarb, A. (2006). Diffusion of information and communication technologies to businesses. In T. Hendershott (Ed.), Economics and information systems (pp. 1–52). Amsterdam: Elsevier BV.

    Google Scholar 

  • Friberg, R., Ganslandt, M. & Sandström, M. (2000). E-commerce and prices: Theory and evidence. SSE/EFI Working Paper series in economics and finance no. 389, Stockholm School of Economics.

    Google Scholar 

  • Gensollen, M. (2007). Information goods and online communities. In E. Brousseau & C. Nicolas (Eds.), Internet and digital economics: Principles, methods and applications (pp. 173–200). Cambridge: Cambridge University Press.

    Google Scholar 

  • Goldfarb, B., Kirsch, D., & Miller, D. A. (2007). Was there too little entry during the dot com era? Journal of Financial Economics, 86(1), 100–144.

    Google Scholar 

  • Goldmanis, M., Hortaçsu, A., Syverson, C., & Emre, Ö. (2010). E-commerce and the market structure of retail industries. The Economic Journal, 120, 651–682.

    Google Scholar 

  • Goolsbee, A. (2009). Implications of electronic commerce for fiscal policy. In W. Lehr & L. M. Pupillo (Eds.), Internet policy and economics: Challenges and perspectives (2nd ed., pp. 141–150). Heidelberg: Springer.

    Google Scholar 

  • Gordon, R. J. (2006). The boskin commission report: a retrospective one decade later. International Productivity Monitor, Centre for the Study of Living Standards, 12, 7–22.

    Google Scholar 

  • Görg, H., Hanley, A., & Strobl, E. (2008). Productivity effects of international outsourcing: Evidence from plant-level data. Canadian Journal of Economics, 41(2), 670–688.

    Google Scholar 

  • Graham, I., Spinardi, G., Williams, R., & Webster, J. (1995). The dynamics of EDI standards development. Technology Analysis & Strategic Management, 7(1), 3–20.

    Google Scholar 

  • Hartmann, M. E. (2006). E-payments evolution. In T. Lammer (Ed.), Handbuch E-Money, E-Payment & M-Payment (pp. 10–18). Heidelberg: Springer.

    Google Scholar 

  • Humphrey, D. B., Kim, M., & Vale, B. (2001). Realizing the gains from electronic payments: Costs, pricing, and payment choice. Journal of Money, Credit and Banking, 33(2), 216–234.

    Google Scholar 

  • International Data Corporation (IDC) (2011). IDC: More Mobile internet users than wireline users in the U.S. by 2015, press release dated 12 September.

    Google Scholar 

  • Ivenson, J. (2003). Why the EU VAT and e-commerce directive does not work. International Tax Review, 27, 27–29.

    Google Scholar 

  • Jacquemin, A. (1987). The new industrial organization: Market forces and strategic behavior. Oxford: Clarendon Press.

    Google Scholar 

  • Janssen, M. C. W., Moraga-González, J. L., & Wildenbeest, M. R. (2007). Consumer search and pricing behavior in internet markets. In E. Brousseau & C. Nicolas (Eds.), Internet and digital economics: Principles, methods and applications (pp. 460–483). Cambridge: Cambridge University Press.

    Google Scholar 

  • Jin, G. Z., & Kato, A. (2006). Price, quality and reputation: Evidence from an online field experiment. RAND Journal of Economics, 37(4), 983–1005.

    Google Scholar 

  • Jorgenson, D. W., & Vu, K. (2005). Information technology and the world economy. Scandinavian Journal of Economics, 107(4), 631–650.

    Google Scholar 

  • Jorgenson, D. W., Ho, M. S., & Stiroh, K. J. (2006). Potential growth of the U.S. Economy: Will the productivity resurgence continue? Business Economics, 41(1), 7–16.

    Google Scholar 

  • Kaplan, S., & Sawhney, M. (2000). E-hubs: The New B2B marketplaces. Harvard Business Review, 78(3), 97–104.

    Google Scholar 

  • Karagiannopoulos, G. D., Georgopoulos, N., & Nikolopoulos, K. (2005). Fathoming porter’s five forces model in the internet era. Info, 7(6), 66–76.

    Google Scholar 

  • Katz, M. L. (1989). Vertical contractual relations. In R. Schmalensee & R. Willig (Eds.), Handbook of industrial organization (Vol. 1, pp. 655–721). Amsterdam: Elsevier Science.

    Google Scholar 

  • Kauffman, R. J., & Lee, D. (2010). A multi-level theory approach to understanding price rigidity in internet retailing. Journal of the Association for Information Systems, 11(6), 303–338.

    Google Scholar 

  • Kraemer, K. L., Dedrick, J., Melville, N. P., & Zhu, K. (2006). Global e-commerce: Impacts of national environment and policy. Cambridge: Cambridge University Press.

    Google Scholar 

  • Laye, J., & Tanguy, H. (2007). Are neighbors welcome? E-buyer search, price competition and coalition strategy in internet retailing. In E. Brousseau & C. Nicolas (Eds.), Internet and digital economics: Principles, methods and applications (pp. 484–509). Cambridge: Cambridge University Press.

    Google Scholar 

  • Layne, K., & Lee, J. (2001). Developing fully functional E-government: A four stage model. Developing fully functional E-government: A four stage model, 18(2), 122–136.

    Google Scholar 

  • Lazonick, W. (2007). Evolution of the new economy business model. In E. Brousseau & C. Nicolas (Eds.), Internet and digital economics: Principles, methods and applications (pp. 59–113). Cambridge: Cambridge University Press.

    Google Scholar 

  • Lee, H.-G. (1998). Do electronic marketplaces lower the price of goods? Communications of the ACM, 41(1), 73–80.

    Google Scholar 

  • Lee, H. G., Westland, J. C., & Hong, S. (1999). The impact of electronic marketplaces on product prices: An empirical study of AUCNET. International Journal of Electronic Commerce, 4(2), 45–60.

    Google Scholar 

  • Lee, S.-Y. T., Gholami, R., & Tong, T. Y. (2005). Time series analysis in the assessment of ICT impact at the aggregate level-lessons and implications for the new economy. Information and Management, 42(7), 1009–1022.

    Google Scholar 

  • Lee, T. E., Chen, J. Q., & Zhang, R. (2001). Utilizing the internet as a competitive tool for nonprofit organizations. Journal of Computer Information Systems, 41(3), 26–31.

    Google Scholar 

  • Lucking-Reiley, D., & Spulber, D. F. (2001). Business-to-business electronic commerce. The Journal of Economic Perspectives, 15(1), 55–68.

    Google Scholar 

  • Lunnemann, P., & Wintr, L. (2011). Price stickiness in the US and Europe revisited: evidence from internet prices. Oxford Bulletin of Economics and Statistics, 73(5), 593–621.

    Google Scholar 

  • Maryanchyk, I. (2008). Are ratings informative signals? Analysis of netflix data. NET Institute Working Paper No. 08-22.

    Google Scholar 

  • McLure, C. E. (2002). Sales and use taxes on electronic commerce: Legal, economic, administrative, and political issues. Urban Lawyer, 34, 487–520.

    Google Scholar 

  • McLure, C. E. (2003). The value added tax on electronic commerce in the European Union. International Tax and Public Finance, 10, 753–762.

    Google Scholar 

  • Mitra, S., & Singhal, V. (2008). Supply chain integration and shareholder value: Evidence from consortium based industry exchanges. Journal of Operations Management, 2, 96–114.

    Google Scholar 

  • Morton, F. S., Zettelmeyer, F., & Silva-Risso, J. (2001). Internet car retailing. Journal of Industrial Economics, 49(4), 501–519.

    Google Scholar 

  • Nikolaeva, R. (2007). The dynamic nature of survival determinants in e-commerce. Journal of the Academy of Marketing Science, 35, 560–571.

    Google Scholar 

  • Oliner, S. D., & Sichel, D. E. (2000). The resurgence of growth in the late 1990s: Is information technology the story? Journal of Economic Perspectives, 14(4), 3–22.

    Google Scholar 

  • Organization for Economic Co-Operation and Development (OECD). (2011). The future of the internet economy: A statistical profile. Available online at http://www.oecd.org/dataoecd/24/5/48255770.pdf

  • Pan, X., Shankar, V., & Ratchford, B. T. (2002). Price competition between pure play versus bricks-and-clicks e-tailers: Analytical model and empirical analysis. In M. Baye (Ed.), The economics of the internet and e-commerce (pp. 29–61). Amsterdam: JAI.

    Google Scholar 

  • Parker, G. G., & Anderson, E. G. (2002). from buyer to integrator: The transformation of the supply chain manager in the vertically disintegrating firm. Production and Operations Management, 11(1), 75–91.

    Google Scholar 

  • Pepall, L., Richards, D. J., & Norman, G. (2005). Industrial organization: contemporary theory & practice (3rd ed.). Mason: Thomson South-Western.

    Google Scholar 

  • Peristeras, V., Mentzas, G., Tarabanis, K. A., & Abecker, A. (2009). Transforming e-government and e-participation through IT. IEEE Intelligent Systems, 25(4), 14–19.

    Google Scholar 

  • Phillips, C. & Meeker, M. (2000). The B2B Internet report: Collaborative commerce. New York: Morgan Stanley Dean Witter Equity Research. Available online at http://www.morganstanley.com/institutional/techresearch/pdfs/b2bp1a.pdf

  • Porter, M. E. (2001). Strategy and the internet. Harvard Business Review, 79(3), 62–78.

    Google Scholar 

  • Porter, M. E. (2008). The five competitive forces that shape strategy. In M. Porter (Ed.), On competition (pp. 3–36). Boston: Harvard Business School Publishing.

    Google Scholar 

  • Prieger, J. E., & Heil, D. (2010a). The macroeconomic impact of e-business. In I. Lee (Ed.), Encyclopedia of e-business development and management in the global economy (pp. 1–11). Hershey: IGI Global.

    Google Scholar 

  • Prieger, J. E., & Heil, D. (2010b). The microeconomic impact of e-business. In I. Lee (Ed.), Encyclopedia of e-business development and management in the global economy (pp. 12–22). Hershey: IGI Global.

    Google Scholar 

  • Prieger, J. E., & Hu, W.-H. (2010). Applications barrier to entry and exclusive vertical contracts in platform markets. Economic Inquiry,. doi:10.1111/j.1465-7295.2010.00355.x

    Google Scholar 

  • Qu, W. G., Pinsonneault, A., & Oh, W. (2011). Influence of industry characteristics on information technology outsourcing. Journal of Management Information Systems, 27(4), 99–127.

    Google Scholar 

  • Ravichandran, T., Pant, S., & Chatterjee, D. (2007). Impact of industry structure and product characteristics on the structure of B2B vertical hubs. IEEE Transactions on Engineering Management, 54(3), 506–521.

    Google Scholar 

  • Rensmann, B. & Smits, M. (2008). Analyzing the added value of electronic intermediaries in the dutch health care sector. In BLED 2008 Proceedings, Paper 29. Available online at http://aisel.aisnet.org/bled2008/29

  • Rochet, J., & Tirole, J. (2003). Platform competition in two-sided markets. Journal of the European Economic Association, 1(4), 990–1029.

    Google Scholar 

  • Rosen, K., & Howard, A. (2000). E-retail: Gold rush or fool’s gold? California Management Review, 42(3), 72–100.

    Google Scholar 

  • Sakellaris, P., & Vijselaar, F. (2005). Capital quality improvement and euroland growth: Sources of growth. Economic Policy, 20(42), 267–306.

    Google Scholar 

  • Schneider, J. A. (2003). Small, minority-based nonprofits in the information age. Nonprofit Management and Leadership, 13(4), 383–399.

    Google Scholar 

  • Scholten, P., & Smith, S. A. (2002). Price dispersion then and now: Evidence from retail and e-tail markets. In M. Baye (Ed.), The economics of the internet and e-commerce (pp. 63–88). Amsterdam: JAI.

    Google Scholar 

  • Siaw, I., & Yu, A. (2004). An analysis of the impact of the internet on competition in the banking industry, using Porter’s five forces model. International Journal of Management, 21(4), 514–523.

    Google Scholar 

  • Sinha, I. (2000). Cost transparency: The net’s real threat to prices and brands. Harvard Business Review, 78(2), 43–50.

    Google Scholar 

  • Susarla, A., Barua, A., Konana, P. & Whinston, A.B. (2011). An empirical investigation of complementarity in IT-enabled supply chain initiatives. Unpublished manuscript, available online at http://ssrn.com/abstract=1975388

  • Terzi, N. (2011). The impact of e-commerce on international trade and employment. Procedia Social and Behavioral Sciences, 24, 745–753.

    Google Scholar 

  • Timmer, M. P., & van Ark, B. (2005). Does information and communication technology drive EU–US productivity growth differentials? Oxford Economic Papers, 57, 693–716.

    Google Scholar 

  • Tirole, J. (1988). The theory of industrial organization. Cambridge: MIT Press.

    Google Scholar 

  • United Nations Conference on Trade and Development (UNCTAD). (2007). Information economy report 2007–2008: Science and technology for development: The new paradigm of ICT. New York, Geneva: United Nations.

    Google Scholar 

  • United Nations Conference on Trade and Development (UNCTAD). (2011a). Information economy report 2011: ICTS as an enabler for private sector development. Geneva: United Nations.

    Google Scholar 

  • United Nations Conference on Trade and Development (UNCTAD). (2011b). Implications of applying the new definition of “ICT goods”. Technical Note no. 1. Available online at http://new.unctad.org/Documents/ICT%20sector/ICTA_TN_1_unedited.PDF

  • US Census Bureau, US Department of Commerce. (2011a). E-commerce 2009. E-stats, May 26. Available online at http://www.census.gov/econ/estats/2009/2009reportfinal.pdf, last visited January 24, 2011.

  • US Census Bureau, US Department of Commerce (2011b). Quarterly retail e-commerce sales: 3 Quarter 2011. Retail e-commerce sales report CB11-186, November 17. Available online at http://www.census.gov/retail/mrts/www/data/pdf/ec_current.pdf, last visited January 24, 2011.

  • Van Winden, W., de Carvalho, L., van Tuijl, E., van Haaren, J., & van den Berg, L. (2012). Creating knowledge locations in cities: Innovation and integration challenges. Abingdon, UK and New York: Routledge.

    Google Scholar 

  • Varian, H., Litan, R.E., Elder, A. & Shutter J. (2002). The net impact study: The projected economic benefits of the internet in the United States, United Kingdom, France and Germany. Retrieved September 20, 2011, from http://www.itu.int/wsis/stocktaking/docs/activities/1288617396/NetImpact_Study_Report_Brookings.pdf

  • Venturini, F. (2009). The long-run impact of ICT. Empirical Economics, 37(1), 497–515.

    Google Scholar 

  • Vickery, S. K., Jayaram, J., Droge, C., & Calantone, R. (2003). The effects of an integrative supply chain strategy on customer service and financial performance: An analysis of direct versus indirect relationships. Journal of Operations Management, 21, 523–539.

    Google Scholar 

  • Walter, Z., Gupta, A., & Su, B.-C. (2006). the sources of on-line price dispersion across product types: An integrative view of on-line search costs and price premiums. International Journal of Electronic Commerce, 11(1), 37–62.

    Google Scholar 

  • Waters, R. D. (2007). Nonprofit organizations’ use of the internet: A content analysis of communication trends on the internet sites of the philanthropy 400. Nonprofit Management & Leadership, 18(1), 59–76.

    Google Scholar 

  • Wen, M. (2004). E-commerce, productivity, and fluctuation. Journal of Economic Behavior & Organization, 55(2), 187–206.

    Google Scholar 

  • Willis, J. L. (2004). What impact will e-commerce have on the U.S. economy? Federal Reserve Bank of Kansas City Economic Review, 89(2), 53–71.

    Google Scholar 

  • Yen, Y.-S. (2010). Can perceived risks affect the relationship of switching costs and customer loyalty in e-commerce? Internet Research, 20(2), 210–224.

    Google Scholar 

  • Yeo, J., & Huang, W. (2003). Mobile e-commerce outlook. International Journal of Information Technology & Decision Making, 2(2), 313–332.

    Google Scholar 

  • Zorn, T. E., Flanagin, A. J., & Shoham, M. D. (2011). Institutional and noninstitutional influences on information and communication technology adoption and use among nonprofit organizations. Human Communication Research, 37, 1–33.

    Google Scholar 

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Appendix: Summary Table of e-Business Factors and Implications for Strategy

Appendix: Summary Table of e-Business Factors and Implications for Strategy

Subject and place in chapter outline

Summary

Implication for strategy

2. Macroeconomics

  

2.1. Size of e-commerce

E-commerce has increased considerably in the developed world in the last 20 years. B2B e-commerce, the predominant form of e-commerce, accounts for nearly a third of all B2B transactions. B2C e-commerce accounts for only 2.8 % of B2C e-commerce. Developing nations have yet to witness considerable gains from e-commerce

E-business is increasing in importance and cannot be ignored by strategists. First-mover advantages may be available in developing countries

2.2. Productivity and economic growth

E-business affects economies by increasing productivity (through additional capital formation) and may spur innovations in processes that will further increase productivity over the long term. Investments in ICT have clearly increased economic growth in many developed countries. The evidence is mixed in developing nations

While adopting ICT by itself may not confer lasting competitive advantage, failure to do so will surely put an organization at a disadvantage

2.3. International trade

E-business improves opportunities for increased specialization which increase the gains from international trade. Little research, however, exists on the impacts of e-business on trade. A lack of infrastructure, poorly trained workforces, and regulatory obstacles may reduce any potential gains from trade for developing nations

Firms could find international trade more profitable with e-business. Trading opportunities in developing nations may not prove profitable in the short-run

2.4. Monetary policy

  

2.4.1. E-business and prices

Overall, e-commerce is expected to increase competition and reduce search and transaction cost. The net effect will be lower prices. In the long run, these lower prices will represent a onetime change in the price level

In the aggregate, firms will face increased pressure to lower prices, but individual industries may avoid price reductions through product differentiation and increased customization

2.4.1. E-business and menu costs

The costs associated with inflation, namely menu costs (the cost of physically changing prices) could be dramatically reduced with e-commerce. Nevertheless, price rigidities will likely remain a fact of business even with greater adoption of e-commerce

Firms can more readily change prices in the wake of inflation and other price shocks. However, e-business does not eliminate all costs associated with price changes

2.4.2. E-business and the money supply

E-payments and e-money present futures challenges for policymakers who may find normal monetary policy tools less effective with the proliferation of e-payments and e-money. Practically speaking, e-commerce has had little effect on monetary policy to date

Sellers must consider whether to adopt e-payment systems for online and offline sales to avoid falling behind rivals

2.5 Fiscal policy and taxation

E-commerce reduces geographical constraints and increases interstate and international transactions. Governments fear these transactions will reduce sales tax revenue. Revenue losses are small to date, but policymakers are increasingly exploring options to tax these transactions

Firms conducting interstate or international transactions will likely face increased pressure to collect sales tax revenue on behalf of their buyer’s governments

3. Microeconomics

  

3.1. Threat of entry

  

3.1.1. Economies of scale and scope

E-business may increase economies of scale in industries where fixed costs are unchanged, but variable costs are reduced

Minimum efficient scale increases and the threat of entry falls

E-business may decrease economies of scale in industries where e-business reduces fixed costs

Minimum efficient scale decreases and the threat of entry rises

E-business may increase economies of scope and aggregation, particularly in information goods

The threat of entry decreases because rivals must enter with a bundle of goods

3.1.2. Network effects

E-business may increase the importance of network externalities enjoyed by incumbents

The threat from entrants on competing networks is reduced

E-business may encourage subsidization of one side of a platform market

Entry barriers in the subsidized side of the platform fall

E-business encourages the proliferation of two-sided (platform) markets, which may be subject to “lock in” of complementary goods

Application barriers to entry may arise from such vertical restraints

3.1.3. Capital requirements and sunk costs

E-business enables ICT outsourcing, converting fixed, sunk cost into variable cost

The threat from entrants increases as the importance of sunk costs declines

3.1.4. Unequal access to distribution channels

E-business decreases the importance of physical location in prime real estate

Entry barriers fall

E-business B2B vertical hubs may be owned and controlled by large incumbents

B2B vertical hubs may be able to dominate supply and distribution channels, effectively limiting opportunities for new rivals

3.1.5. Other advantages of incumbency

E-business decreases the importance of face-to-face trained sales force

Entry barriers fall

E-business and outsourcing decrease the importance of physical nearness to skilled labor

Entry barriers fall

Early entry into e-commerce confers initial but not necessarily lasting advantages to incumbents

Entry barriers decrease over time

3.2. Power of Suppliers

  

3.2.1. Concentration of the supplier group

E-commerce may increase the number of sellers and facilitate greater transparency of product prices and cost structures

Suppliers could see reduced power over industry

 

Suppliers (incumbents) may maintain control over B2B vertical hubs

Suppliers could see increased power over industry

3.2.2. Dependence of the supplier group on the industry

E-business reduces transaction costs between supplier and industry

Suppliers lose ability to extract rents from industry, as firms can more easily contract with competing suppliers

E-business and vertical supply chain integration tightens bonds between supplier and buyer

Supplier loses bargaining power due to the hold-up problem

3.2.3. Switching costs

E-business reduces switching costs through the brokerage effect.

Lower switching costs of buyers reduce supplier power.

Buyers may make significant investments in vertical supply chain integration

Higher switching costs of buyers increase supplier power

3.2.4 Downstream integration by the supplier group

E-business can increase vertical disintegration through outsourcing

Reduced incentives for suppliers to enter downstream markets lowers supplier power

3.3. Power of buyers

  

3.3.1. Intermediaries and B2B hubs

E-business spurs disintermediation in industries such as travel agency service and brokerages

Intermediaries’ power (and even existence) is threatened

E-business spurs reintermediation through B2B vertical hubs

Intermediaries’ power is strengthened

3.3.2. B2C e-commerce and product differentiation

Information and search costs are reduced with e-commerce, and branding may become less important

Product differentiation through branding decreases, and buyer power increases

E-business allows new forms of product differentiation, such as online ratings supplied by past customers

Product differentiation increases, and buyer power decreases

E-business allows firms to offer greater customization of products and services, such as computers sold to order

Product differentiation increases, and buyer power decreases

Informational problems such as adverse selection E-business allows firms to offer greater customization of products and services, such as computers sold to order

Product differentiation increases, and buyer power decreases

3.3.3. B2C e-commerce and other factors

E-business enables gathering information about customers and resonance marketing

Sellers can ability to extract value from buyers

Consumers might be able to aggregate demand (Groupon, LivingSocial, etc.)

Buyer power increases, resulting in lower prices and higher quality

3.4. Threat of substitutes

  

3.4.1. Good substitutes versus poor substitutes

E-commerce enables consumers to more quickly identify and purchase substitutes for a firm’s products

The power of any one seller decreases

Increasingly informed customers can easily find firms offering unique products filling gaps in the marketplace

Firms selling unique products can market share

3.4.2. Buyer switching costs

E-commerce reduces search costs and therefore decreases switching costs for consumers in markets where they are willing to search for alternatives

Seller power declines, and price levels and dispersion fall

E-commerce allows firms to reduce the efficacy of search engines (through sponsored search) and to obfuscate prices and products

The consumer’s ability to compare prices and products falls, allowing firms to raise profits

3.5. Rivalry among existing competitors

  

3.5.1. General factors affecting the intensity of rivalry

ICT, electronic market exchanges, and e-business vertical hubs may enhance the market share of the largest incumbents

Where significant differences exist between firms, the impact of e-commerce on market share will likely be greater

E-business-enabled outsourcing and reduced capital requirements for entry may make market structure more competitive

Incumbent suppliers lose power and market share

In the wake of e-commerce innovations, firms may attempt to capture a significant portion of the market share through aggressive pricing strategies, particularly for goods with very low marginal costs (e.g., information goods)

Competitive rivalry among sellers in the industry heats up, and seller power in general decreases

3.5.2. Factors specifically affecting price competition

Firms may join a coalition of competing firms selling less close substitutes in a B2C exchange

The coalition can attract more customers to its site than any one company could, and seller power increases

E-business lowers variable cost relative to fixed cost, making overcapacity problems relatively greater

Overcapacity in industry leads to cutthroat pricing; competition among sellers increases and prices fall

4. Nonprofit organizations

Nonprofits attempt to adopt e-commerce practices from the for-profit sector, such as using terms like “checkout” when soliciting donations online

The commercialization of the donation process leads philanthropists to decline to contribute to the nonprofit

Nonprofits adopt ICT as a symbolic resource

The nonprofit establishes legitimacy and improves its reputation among donors and accountability organizations

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Prieger, J.E., Heil, D. (2014). Economic Implications of e-Business for Organizations. In: Martínez-López, F. (eds) Handbook of Strategic e-Business Management. Progress in IS. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39747-9_2

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