Using examples from information technology adoption, we emphasize the role of costs, benefits, communications channels and dynamic considerations in the decision to adopt new technology. We discuss differences between adoption by consumers and adoption by firms. We emphasize the adoption of business process innovations, which alter organizational practices and often involve the post-adoption invention of complementary business processes and adaptations. Within the context of business adoption, we discuss the inherent challenges in identifying the decision maker and the role of competition in influencing the benefits to adoption.
KeywordsBusiness Process Technology Adoption Electronic Commerce Adoption Decision Dynamic Consideration
Technology adoption occurs when an individual, firm or other agent first makes use of a new technology. In this setting, technology can refer to a new product, service or management innovation.
There is a vast economics literature studying the use of newly available technologies. When an individual, firm or other agent (e.g., government or non-profit) first makes use of the new service or product, this act is often labelled ‘adoption’. An important facet of this literature analyses the economic determinants of heterogeneity in adoption behaviour, principally the timing of adoption and the willingness to pay more for new products and services. In this entry we discuss several key issues for understanding the economics of the adoption of new technologies, using information technology as an example.
A General Discussion of Costs and Benefits of Adopting a New Technology
In weighing the decision to adopt a new technology, the basic economic model compares the costs of adoption with the benefits. The costs include the physical set-up costs, the costs of learning to use the new technology and the costs of purchasing any services that are complementary to the technology being adopted. The benefits include the initial increase in utility or productivity through the use of the new technology as well as the longer-term benefits.
The most common method for comparing costs and benefits is the ‘Probit model of adoption’, developed by David (1969). In this model, agents adopt the new technology when the benefits exceed the costs. Empirical studies of adoption regress the adoption decision on factors that might affect costs and benefits. For example, Forman et al. (2005) examine internet adoption by businesses. They use a comprehensive cross-section of US business establishments and regress the establishments’ adoption decision on features of the establishments and features of their locations.
The probit model implicitly measures the adoption decision as the reduced form of a dynamic process in which agents weigh the present value of all future costs and benefits of adopting a new technology. Agents might wait to adopt in order to take advantage of lower future prices, better future complementary technologies or better future quality; or they might adopt early in order to benefit from the technology over a longer period. This suggests that past investments in technology can reduce the marginal benefit of adopting the next generation (Forman 2005).
The probit model of adoption is missing one important aspect of the economics of technology diffusion: that diffusion happens slowly as agents learn about the existence of, and benefits of, the new technology. Thus, learning and communication channels matter to the diffusion of new technology. Goolsbee and Klenow (2002) emphasize the importance of learning by seeing what other people are doing as a key aspect of the diffusion of personal computers. Their work highlights the econometric challenges of identifying the effects of learning and communication from other factors that might drive correlation in user behaviour, such as network externalities or other types of user spillovers.
Below, we provide examples of the costs and benefits of adoption, the dynamic considerations and the communication channels through which people learn about new technology. Because the technology adoption process differs depending on whether the adopters are households or firms, we discuss households and firms separately.
Technology Adoption by Households
Prince’s (2008) study of personal computer (PC) ownership illustrates the tenor of many studies of household adoption of new technology. Three main factors help explain both the timing of adoption and the willingness to pay: (1) differences across consumers in their valuation of the product (benefits), (2) the barriers to the initial purchase (costs) and (3) dynamic aspects of the decision. His results indicate that the marginal utility of PC quality is strongly increasing in income and education, and strongly decreasing in age. Further, as prices fall and quality rises over time, the decision about whether to buy a new PC is complicated by the dynamic decision of when to buy a new PC. Furthermore, the households that become first-time purchasers are more price sensitive than repeat purchasers, and perceive large costs in the initial adoption.
Goldfarb and Prince (2008) examine a probit model of adoption and emphasize the current period trade-off between costs and benefits. While the relative costs of adoption vary according to consumer budget constraints, the benefits depend in large part on the opportunity cost of time. Specifically, they find that people with high levels of income and education are more likely to adopt, but spend less time online when they do adopt. Their results suggest that this is driven by the large array of other leisure activities available to people with high levels of income and education.
Household adoption decisions can often be shaped by the behaviour of other users or through institutions. For example, Goolsbee and Klenow (2002) add spillovers to the standard probit, studying how users’ adoption decisions are interrelated either through learning effects or through network externalities. Goldfarb (2006) documents the role of universities as a communications channel that aided the diffusion of internet technology. Internet technology diffused from university researchers to undergraduate students in the mid-1990s. Those students then brought the technology home with them and it diffused to other household members.
Overall, technology adoption by households involves a (potentially dynamic) trade-off between costs and benefits, and a communication process through which individuals learn about the existence of, and benefits to, the new technology.
Technology Adoption by Firms
The study of adoption in business tends to raise additional questions beyond those faced by households. Unlike household adoption studies, in a business setting it can be difficult to identify the decision maker or ‘adopter’. This confusion arises for many reasons, but principally because there may be sharing of non-capital investments across a wide array of processes. Though the unit costs of sharing are lower for large organizations, the sharing usually does not occur instantaneously or without high coordination costs across many parts of an organization (Astebro 2002, 2004). Many decision makers and considerations can shape the coordination of adoptions decisions. As a result, organizations may adopt new technologies that take time to diffuse across users.
Competitive pressure is another key factor in technology adoption by businesses. That is, there first may be a minimal level of investment necessary just to be in business. Second, adoption of some technologies may confer competitive advantage vis-à-vis rivals. As an illustration, computing frequently enables the invention of entirely new services and products that may or may not provide permanent or temporary competitive advantage. When new services are reasonably permanent, a private firm may see returns to the investment in the form of increases in final revenue or other strategic advantages. If a new product or service is quickly imitated by all firms, it rapidly becomes a standard feature of doing business in a downstream market. The benefits from the new technology are quickly passed on to consumers in the form of lower prices and better products. In this case, the benefits to a firm do not appear as an increase in revenues but they exist, nonetheless, in the form of losses avoided by the businesses in question.
McElheran (2012) uses such reasoning to investigate the order in which existing manufacturing firms adopted electronic commerce during its first wave of diffusion in the late 1990s. She shows that many of the most productive firms adopted electronic commerce in their procurement processes – to secure inputs – which led to a reinforcement of cost leadership. On the other hand, many of the most productive firms were followers in adopting customer-facing electronic commerce, which had much riskier payoffs and did not integrate as well with existing business processes. That led many leading firms to be more cautious, while a second tier of firms took the lead in experimenting.
One particularly important type of technology adoption by businesses is the adoption of business process innovations. Such innovations alter organizational practices, generally with the intent of improving services, reducing operational costs and taking advantage of new opportunities to match new services to new operational practices. Typically, this type of innovation involves changes in the discretion given to employees, changes to the knowledge and information that employees are expected to retain and employ, and changes to the patterns of communications between employees and administrators within an organization. Such innovations involve the retraining of employees and the redesign of organizational architecture, such as its hierarchy, lines of control, compensation patterns and oversight norms.
Prior studies stress the importance of co-invention, the post-adoption invention of complementary business processes and adaptations aimed at making adoption useful (Bresnahan and Greenstein 1996). For example, an initial investment in information technology (IT) is not sufficient for ensuring that productivity gains arise. Those gains depend on whether the employees of the adopting organization find new uses or services to take advantage of the new capabilities, and/or invent new processes for unanticipated problems.
The adoption costs of business process innovations may depend on the availability of third-party services, such as third-party consulting, which may not be present at early moments in a new technology’s diffusion (Bresnahan et al. 2002). In the absence of market solutions, adopters may have to divert internal resources to solve idiosyncratic issues. The incentives around utilization and investment can also change considerably over time, owing to changes in the restructuring of the organization’s hierarchy and operational practices (Bloom et al. 2011).
Co-invention costs are an important factor in explaining business adoption of the Internet. By the late 1990s, implementation of first-generation internet applications such as email was straightforward. It involved a PC, a modem, a contract with an ISP and some appropriate software. In contrast, investment in the use of the Internet for an application module in a suite of Enterprise Resource Planning software was anything but routine. Such an implementation included technical challenges beyond the Internet’s core technologies, such as security, privacy and dynamic communication between browsers and servers. Usually organizational procedures also changed. In particular, Forman et al. (2003a, b, 2005, 2008, 2012) examine the causes and consequences of business adoption of internet technology, and emphasize the importance of coinvention as a driver of technology adoption by firms. For example, Forman et al. (2008) showed that firms with easy access to skilled IT workers (whether locally or within the firm) were much more likely to adopt advanced internet applications.
Directly connecting adoption of business process innovation with performance is challenging. Building on their work on internet adoption, Forman et al. (2012) show that the aggregate benefits (in terms of wages) of such adoption are much higher in locations with a ready supply of IT expertise. Hubbard (2000, 2003) and Baker and Hubbard (2003, 2004) examine the productivity benefits of a business process innovation at a more micro level. In particular, they examine the use of computing technologies to monitor the performance of trucks. They document the fact that such technologies improve the ability of trucking firms and private fleets to coordinate assets and better match trucks to tasks, and monitoring of trucker actions. Both lead to improved output.
Overall, the study of business adoption raises additional issues owing to the inherent challenges in identifying the decision maker, the role of competition and, especially, the role of co-invention in the adoption of business process innovations.
Using examples from information technology adoption, we have emphasized the role of costs, benefits, communications channels and dynamic considerations in the decision to adopt new technology. We have also discussed differences between adoption by consumers and adoption by firms. Of course, such a short article cannot comprehensively cover all issues related to technology adoption and diffusion. Literature reviews, with various perspectives, include Rogers’ (1995) review of the communications literature, Stoneman’s (2002) review of the economics literature, and Forman and Goldfarb’s (2006) review of the drivers of information technology adoption by businesses.
- Bloom N, Garicano L, Sadun R, Van Reenen J. 2011. The distinct effects of information technology and communication technology on firm organization. Working paper, Stanford University.Google Scholar
- Bresnahan, T. and Greenstein, S. 1996. Technical progress and co-invention in computing and in the use of computers. Brookings Papers on Economic Activity: Microeconomics 1–78.Google Scholar
- David, P. A. 1969. A contribution to the theory of diffusion. Memorandum No. 71, Stanford Center for Research in Economic Growth, Stanford University.Google Scholar
- Forman, C., and A. Goldfarb. 2006. Diffusion of information and communications technology to business. In Handbooks in information systems, Economics and Information Systems, vol. 1, ed. T. Hendershott. Amsterdam: Elsevier.Google Scholar
- Forman, C., A. Goldfarb, and S. Greenstein. 2003a. Which industries use the internet? In Organizing the new industrial economy, ed. M. Baye. Amsterdam: Elsevier.Google Scholar
- Forman, C., A. Goldfarb, and S. Greenstein. 2003b. The geographic dispersion of commercial internet use. In Rethinking rights and regulations: Institutional responses to new communications technologies, ed. L. Cranor and S. Wildman. Cambridge, MA: The MIT Press.Google Scholar
- McElheran, K. 2012. Do market leaders lead in business process adoption? Customers and co-invention in e-business adoption. Working paper, Harvard Business School.Google Scholar
- Rogers, E. 1995. The diffusion of innovations, 4th ed. New York: Free Press.Google Scholar
- Stoneman, P. 2002. The economics of technological diffusion. Oxford: Blackwell.Google Scholar