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2014 | OriginalPaper | Chapter

Economic Implications of e-Business for Organizations

Authors : James E. Prieger, Daniel Heil

Published in: Handbook of Strategic e-Business Management

Publisher: Springer Berlin Heidelberg

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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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Appendix
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Footnotes
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
We note some exceptions in Sect. 3.
 
3
We mainly focus on the US and European economies, but include estimates for developing nations when available.
 
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
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
See also the survey on online price dispersion research by Baye et al. (2007).
 
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
Refer to ECB (1998) and Prieger and Heil (2010a) for more complete discussions.
 
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
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
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
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
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
See also the many other studies cited in Sect. 3.3 of Forman and Goldfarb (2006).
 
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
However, sellers may obfuscate their offerings precisely to avoid such transparency, as we explain below in Sect. 3.4.2.
 
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
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
See Sect. 4.2 of Katz (1989).
 
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
See Prieger and Heil (2010b) for a review of other empirical studies of the benefits of VSCI.
 
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
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
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
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
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
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
See also Bonera (2011) and Cao et al. (2005) on the importance of perceived security and trust to customers in e-commerce.
 
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
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
See Pepall et al. (2005, p.364).
 
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
See also Zorn et al.’s (2011) survey of the literature on ICT adoption and use among nonprofits.
 
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Metadata
Title
Economic Implications of e-Business for Organizations
Authors
James E. Prieger
Daniel Heil
Copyright Year
2014
Publisher
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-642-39747-9_2