PAYOFF EXTERNALITIES, INFORMATIONAL CASCADES AND MANAGERIAL INCENTIVES A THEORETICAL FRAMEWORK FOR IT ADOPTION HERDING

PAYOFF EXTERNALITIES, INFORMATIONAL CASCADES AND MANAGERIAL INCENTIVES: A THEORETICAL FRAMEWORK FOR IT ADOPTION HERDING Robert J Kauffman Professor and Chair, Information and Decision Sciences Co-Director, MIS Research Center Carlson School of Management University of Minnesota Minneapolis, MN 55455 Email: rkauffman@csom.umn.edu Xiaotong Li Assistant Professor of Management Information Systems Department of Accounting and MIS University of Alabama, Huntsville Huntsville, AL 35899 Email: lixi@uah.edu Last revised: May 11, 2003 _ _ ABSTRACT We have recently observed herd behavior in many instances of information technology (IT) adoption This study examines the basis for IT adoption herding generated by corporate decisionmakers’ investment decisions We propose rational herding theory as a new perspective from which some of the dynamics of IT adoption can be systematically analyzed and understood We also investigate the roles of payoff externalities, asymmetric information, conversational learning and managerial incentives in IT adoption herding By constructing a synthesis of the critical drivers influencing managers’ IT investment decisions, this study will help business researchers and practitioners to critically address the issues of information asymmetries and incentive incompatibility in firm- and market-level IT adoption Keywords: Agency problem, asymmetric information, herd behavior, incentives, informational cascades, IT adoption, network externalities, reputations, signaling games _ _ Acknowledgements: The authors wish to acknowledge Yoris Au for helpful discussions on related work _ _ INTRODUCTION In the recent years, there have been many instances of information technology (IT) adoption in which we have observed “herd behavior,” as many investment decisionmakers lost touch with their own cautious value-maximizing approaches to investment decisionmaking, and decided to follow the advice of the many “smart cookies” in the Digital Economy “Herd behavior,” such as we saw during the height of the DotCom days arises in the presence of differences in the information endowments of decisionmakers in different organizations Bikchandani and Sharma (2001, pp 280-281) define herd behavior in terms of three related aspects: (1) the actions and assessments of investors who decide early will be critical to the way the majority will decide; (2) investors may herd on the wrong decision; and, (3) if they make the wrong decision, then experience or new information may cause them to reverse their decisions, and a herd will be created in the opposite direction Examples that we have observed The above cartoon was originally published by the New Yorker Magazine in 1972 and is reproduced from Bikhchandani, S., Hirshleifer, D., and Welch, I (1996), “Informational Cascades and Rational Herding: An Annotated Bibliography,” Working Paper, Anderson Graduate School of Management, University of California, Los Angeles; Fisher College of Management, Ohio State University; and School of Management, Yale University Available on the Internet at welch.som.yale.edu/cascades/ include the adoption of price-discriminating electronic auctions, wireless telecommunications technologies, business-to-business electronic market solutions, and enterprise systems software, among others In other instances, however, considerable inertia seems to have stalled market adoption, as senior managers ask: “Should we wait?” (Au and Kauffman, 2001) Examples include the slow growth of electronic bill payment and presentment technologies and only modest adoption of powerful Internet-based corporate travel reservation systems Herd behavior has long been studied in other fields, including Finance, Biology, Sociology and Psychology, and especially Economics, where the literature has reached an exceptional depth of coverage of the issues (Bikhchandani, Hirshleifer and Welch, 1996) In some cases, such as stock market bubbles or the Internet and DotCom mania, herding is driven—in the words of Federal Reserve Bank Chairman, Alan Greenspan—by people’s “irrational exuberance.” Unfortunately, this can be exploited by other rational people in the economy, as Liebowitz (2002) and Schiller (2000) point out However, recent theoretical and empirical studies suggest that in many other cases herd behavior is rather counterintuitively caused by the decisions of perfectly rational people Unfortunately, such rational decisions at the individual level sometimes result in significant problems with information transmission, due to people’s unwillingness to pass on information that does not match other information which they have decided to herd on, and the associated welfare losses that arise for others in the marketplace and the economy In the context of IT adoption, rational herding has the potential to generate several problems First, valuable information about new technologies is most often lost (or at least poorly aggregated) when IT managers blindly follow the adoption decisions of others Second, payoff externalities-driven herding makes early adopters’ decisions disproportionately important It gives other adopters little chance to compare and experience different technologies Third, managers sometimes intentionally imitate others’ adoption decisions because of their career concerns, and those reputation-motivated decisions usually fail to maximize expected IT investment payoffs The widespread mimicry in IT adoption and the resultant inefficiencies motivate us to investigate the basis for technology adoption herding generated by corporate managers’ decisions A common and well-studied justification for IT adoption herding is positive payoff externalities like network externalities Recent studies have indicated that many technology markets are subject to positive network feedback that makes the leading technology grow more dominant (Brynjolfsson and Kemerer, 1996; Gallaugher and Wang, 2002; Kauffman, McAndrews and Wang, 2000) Because positive network feedback makes a company’s IT adoption return rise as more companies adopt the same technology, it usually gives managers strong incentives to adopt the technology with the larger installed base of users In addition to the studies of positive payoff externalities, recent research in the area of information economics demonstrates how rational herd behavior may arise because of “informational cascades” (Banerjee 1992; Bikhchandani, Hirshleifer and Welch, 1992 and 1998) or managers’ career concerns (Scharfstein and Stein, 1990; Zwiebel, 1995) Informational cascades occur when individuals ignore their own private information and instead mimic the actions of previous decisionmakers Those mimetic strategies are rational when private information is swamped by publicly observable information accumulated over time This is why informational cascading is sometimes referred to as “statistical herding” (Banerjee, 1992; Ottaviani and Sorensen, 2000) Like informational cascade models, career concerns models have information economics and Bayesian games as their theoretical foundations, but they distinguish themselves by examining rational investment herding through the lens of agency theory (Holmström, 1999) The primary implication of those models is that managers concerned about their reputations may imitate others’ investment decisions to positively influence others’ inferences of their professional capabilities Although reputational herding decisions are rational for individual managers, they are usually not in the best interests of those companies who hire their managers to maximize investment payoffs Empirical evidence of herd behavior and imitative strategies has been recently documented in financial investment decisionmaking, stock analysts’ equity recommendations, emerging technology adoption and television programming selection (Hong, Kubik and Solomon, 2000; Hong, Kubik and Stein, 2003; Kennedy, 2002; Walden and Browne, 2002; Welch, 2000) There is also extensive experimental evidence of rational herding and informational cascades in the economics literature (Anderson and Holt, 1996 and 1997; Hung and Plott, 2001) Another recent experimental study of behavioral conformity is by Tingling and Parent (2002), who employ senior IT and business decisionmakers instead of college students are used as subjects Despite the fast-growing rational herding literature and the pervasiveness of imitative behavior in IT adoption, systematic studies of IT adoption herding are still rare in the IS literature By synthesizing previous rational herding models, this paper proposes an integrated research framework based on economic theory, and within which the dynamics of IT adoption herding can be better analyzed and understood The next three sections discuss the underlying theories in greater detail We investigate the relationship between payoff externalities and IT adoption herding in Section We next demonstrate in Section how the vagaries of information transmission and observational learning can lead to information cascades in technology investment The problem of managerial incentives in IT investment and adoption decisionmaking is the focus of Section We discuss why agency problems predispose the market to reputational herding in IT adoption Managerial compensation schemes designed to address those incentive issues are also discussed Section provides a synthesis of critical theoretical drivers of IT adoption herding and brings the ideas together into a single integrative framework We provide preliminary thoughts about why stakeholders to IT adoption at different levels (e.g., business process or firm-level investor/decisionmaker, senior executive or member of the board of directors, industry sector promoters or regulators of the economy) may have distinctly different perspectives about , and briefly discusses its potential application Section concludes the paper with the contributions of this work to ongoing research in IS, and ideas for further research PAYOFF EXTERNALITIES: DOES ADOPTION HERDING PAY OR HURT? One of a number of different types of payoff externalities that is commonly observed in the IT market is “network externalities” (Economides, 1996; Katz and Shapiro, 1994; Shapiro and Varian, 1999) Network externalities are sometimes referred to as demand-side economies of scale ( For additional constructs related this area of theory, see Table 1.) Table Key Constructs in the Payoff Externalities Theory Relative to IT Adoption CONSTRUCT Rational IT adoption herding Network externalities Intrinsic and extrinsic network externalities Installed base Path dependencies Tipping equilibrium DEFINITION xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx COMMENTS xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx They stem from the presence of significant technology switching costs and the benefits associated with a large installed base of users of compatible technologies These and other relevant findings that characterize the Economics literature on network effects and technology switching costs was recently surveyed by Farrell and Klemperer (2001) In the context of IT adoption, network externalities tend to reward herding decisions by increasing the payoffs to IT adopters who associate themselves with the majority They also decrease the risks that an IT adopter will be stranded in its adoption of an IT that has too small an installed base of users In technology markets subject to network externalities, IT diffusion processes are often characterized by path dependencies They represent the situational specifics of irreversible managerial decisions and their impacts on the decisions of others Many managers believe that network externalities and technology switching costs work in tandem to justify imitative technology adoption In some cases, strong network effects create a “tippy” technology market in which one technology very quickly emerges as the dominant product because of massive adoption imitation Under such a winner-take-all tipping equilibrium scenario, the question most managers face is when to jump on the bandwagon, and whether to join the herd Although herd behavior driven by positive network feedback can be easily justified by individual rationality, it usually leads to obvious information and welfare loss Companies make their IT adoption decisions mainly based on the installed user bases of competing technologies Consequently, managers not concentrate on the intrinsic merits and suitableness of competing technologies, and under many circumstances they not even have enough time to compare all available technology choices because the technology competition could end very quickly in favor of a technology So does network externality-driven IT adoption herding pay off? Or does it hurt those firms that adopt this way? At the individual level, each decisionmaker gains by joining the herd and taking advantage of the positive network feedback However, most decisionmakers lose a chance to deliberate the associated opportunities Very often, as some have claimed for the VHS video format winning out over the Sony Beta format (Shapiro and Varian, 1999), the market may end up adopting an inferior technology, which will hurt all adopters in the long run Payoff externalities, as a stand-alone justification for rational IT adoption herding, has its limitations Strong network externalities may not be so pervasive in the technology market as many IT and business strategists expected (e.g., see Liebowitz, 2002) As a result, imitative technology adoption strategies driven by those illusive network effects are not even individually rational Moreover, technology managers sometimes choose to adopt emerging technologies with superior performance instead of imitating others by using the dominant technology Clearly, there is a tradeoff between the future potentials of superior new technologies and the network benefits of current technologies Adoption herding may not persist or even exist if some firms find that the benefits of exploring new technologies outweigh those of exploiting the dominant technology with network benefits (Lee, Lee and Lee, 2003) It is also worth noting that payoff externalities can be either positive or negative Unsurprisingly, negative payoff externalities play an important role in mitigating a technology market’s propensity to adoption herding They are commonly seen in most competitive business environments where downward-sloping demand curves make a company’s IT adoption payoffs decrease as more companies adopt the same technology Therefore, companies imitate others’ IT investment decisions may be punished by intense ex post competition in the downstream market Both the fiber cable network glut and the e-commerce gold rush exemplify how severely IT adoption herding may have been penalized by negative payoff externalities Interestingly, adoption herding sometimes still happens in those situations where negative payoff externalities are evidently present (Kennedy, 2002; Khanna, 1998) Because of these limitations for payoff externalities as a justification for rational adoption herding, we need to investigate other theoretical explanations of firm-level herd behavior in IT adoption INFORMATIONAL CASCADES: TOO MUCH OR TOO LITTLE INFORMATION? The theory of payoff externalities-driven adoption herding does not sufficiently emphasize two important features that are present in IT diffusion The first feature is that information asymmetries and information incompleteness are pervasive in emerging technology markets 10 Different decisionmakers have their own judgments about the business value of a new technology based upon their own private information, and generally no one possesses perfect information in making an individual IT adoption decision These information structure problems lead to the second feature: to improve the quality of their decisions, decisionmakers keep trying to learn valuable information by observing others’ IT adoption decisions For those who make their adoption decisions earlier, their actions may reveal their private information to others, which generates information spillovers These are often referred to as information externalities (Zhang, 1997) (See Table for constructs related to information cascades-driven herding.) Table Key Constructs in the Informational Cascades Theory Relative to IT Adoption CONSTRUCT Information asymmetry DEFINITION xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx Information xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx completeness xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx Information xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx spillover xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx Informational xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx cascade xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx Observational xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx learning xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx Word-of-mouth xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx learning xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx COMMENTS xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx 19 xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxx An Evaluative Framework for Assessing Herding Theories of IT Adoption □ paragraphs for this section o 1st paragraph: introduce the framework with a brief couple sentences and then give the table o 2nd paragraph: explain the contrasts that the framework depicts, answer question about why this framework provides a basis for figuring out which of the herding behavior theories is the most appropriate to use in the interpretation of the observed adoption phenomena in real world settings o 3rd paragraph: explain the structure of a mini-case analysis in general terms using the framework; provides an opportunity to tell reader how to think about our “results”— how we will sell the quality of the framework dimensions in terms of the insights it offers Xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 20 xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 21 Table An Evaluative Framework for the Alternative IT Adoption Herding Theories THEORETICAL PERSPECTIVE BUSINESS PROCESS LEVEL/ IT ADOPTER, INVESTOR Payoff externalities Xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx Xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx Xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx Informational Cascades Managerial incentives FIRM LEVEL / BOARD OF DIRECTORS, SENIOR MGMT xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx INDUSTRY SECTOR / STANDARDS GROUP ECONOMY LEVEL / REGULATOR xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxx 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xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxx (1) Payoff Externalities-Focused IT Adoption: The Case of Wi-Fi Hotspot Adoption xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 23 xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 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Adoption: ICQ and Microsoft Messenger xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 24 xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 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xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxx (4) A Mixed Theoretical Interpretation: Micropayment Solutions on the Internet xxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 26 xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 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xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx CONCLUSION This study provides a new theoretical framework for rational IT adoption herding as basis for understanding some observed forms of IT adoption and the related fundamentals of managerial decisionmaking for IT investments Herding, as a type of human imitative behavior, tends to result rather naturally from an individual’s imperfect reasoning and cognitive capabilities with respect to the costs, benefits and risks associated with an IT investment Au and Kauffman (2003) have argued that many inefficient IT adoption decisions can be attributed to the adopters’ bounded rationality Thus, it will be helpful to explore some of the potential behavioral justifications of observed investment decision herding under certain circumstances (Schiller, 28 1995) We also believe that the rational herding theory synthesized in our framework is likely to be very useful in many settings where bounded rationality plays a significant role In fact, many problems associated with bounded rationality can be studied in fully rational models with imperfect information and vice versa (Conlisk, 1996) By formally analyzing IT adoption herding in a somewhat simplified rational world, we are able to pay attention to the relevant information and incentive problems, without sacrificing the real world applicability of most of the managerial insights that will be generated The reader should not interpret our exposition in this article as a basis for rationalizing the herd behaviors that are commonly observed in IT investment decisionmaking Nevertheless, our rational herding framework suggests payoff externalities, informational cascades and managers’ career concerns as three interrelated explanations for the kinds of imitative decisionmaking behaviors that are observed in IT adoption We investigated network externalities, observational learning and managerial incentives as critical drivers influencing managers’ IT investment decisions By doing so, we demonstrated the relevance and the importance of our proposed framework to academic researchers, business strategists and IT investment managers Instead of introducing various rational herding models as standalone theories, instead we emphasized their inherent relationships in an attempt to acquire more distinctive insights for IT adoption herding For example, we showed why an adoption herd is much more likely to form in a market for an emerging technology market, where information asymmetries and network effects come into play We also demonstrated why reputational herding is more common in IT adoption processes where agency problems are compounded by severe information problems This paper presents a research framework within which IT adoption herding can be systematically studied We believe that future studies within this framework will not only 29 enhance our understanding of herd behavior in IT investment, but also offer insights and contributions to the rational herding literature in Economics Most informational cascade models downplay the importance of conversation and information sharing across firms because of the credibility issue However, word-of-mouth communications are usually very useful in IT diffusion and social learning in general (Ellison and Fudenberg, 1995; Rogers 1995), and the growing literature on “cheap talk” in Economics also sheds light on the effectiveness of conversational learning in strategic interactions (Crawford and Sobel, 1982; Farrell and Rabin, 1996) So future studies that explore the role of conversation in IT adoption herding have the potential to inform the herding literature by generalizing the prior informational cascade models Future studies of IT adoption herding can also provide additional insights related to the theory of reputational herding In most reputational herding models that we have seen to date, the outcomes of managers’ investment decisions are observable ex post in a mechanistic manner So the labor market and firm owners can infer managers’ capabilities through Bayesian updating However, as we pointed out earlier, many IT projects are strategically instrumental to the firms that invest in them, and yet their payoffs are hard to measure in the short run This complicates the inference process that leads to managerial decisions about IT investments, and thus requires the extension of reputational herding models so that they will yield more useful insights in this managerial context Finally, we believe that the framework proposed in our study can also make contributions to the IS literature in some contexts other than IT adoption For example, we frequently observe herd behavior in IS curriculum design, research topic selection, consumer online shopping patterns, IT firms’ advertising campaigns, R&D spending in developing certain kinds of information systems, and so on The applications are varied and interesting it turns out Our 30 study suggests that IS researchers ought to pay close attention to a number of related issues when they study a decisionmaker’s behavior in those contexts The first issue is payoff interdependence It is important to try to figure out whether a decisionmaker’s decision will hurt or benefit others who make the same decision The second issue is information gathering through learning In this case, it is useful to understand whether a decisionmaker can learn information from the similar decisions of others, and whether the information gathered is credible The third 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maximize investment returns, Managers imitate others’ decisions to build their reputations and to maximize their own human capital returns Information incompleteness and information asymmetries in the IT market make observational learning important for decision-makers, and thus increase the possibility of an informational cascade The financial returns of most IT investments are hard to measure in the short run, which creates more implicit incentives for managers to engage in investment herding when situations warrant Table A Comparison of Three Explanations for IT Adoption Herding Network-effect-driven Herding Models Informational Cascade Models Reputational Herding Models Theoretical Foundation Payoff interdependency and strategic complementarities Information economics and Bayesian learning Aspects of IT Adoption emphasized Model Strength IT switching costs, network externalities and technology compatibilities Many IT markets are subject to network feedback These herding models are generally more intuitive and robust Model Weakness Hard to explain herding in situations where network externalities are weak or negative payoff externalities are strong Information externality and social learning in IT adoption These models rigorously demonstrate how herding arise because of Information asymmetries and the associated learning problems Simplified assumptions of market information structure and learning processes make these models unrealistic in some settings Information economics, contracting and agency theory Managers’ implicit incentives and career concerns in IT adoption These models show that herding may be caused by incentive problems, which builds a bridge between the agency theory and the rational herding theory The conditions that lead to herding are more complex and less obvious Most models only deal with very simple investment settings ... provides a new theoretical framework for rational IT adoption herding as basis for understanding some observed forms of IT adoption and the related fundamentals of managerial decisionmaking for IT. .. that are rather unfortunately based upon limited information As two possible mechanisms that cause rational IT adoption herding, informational cascades and network externalities are not mutually... positive payoff externalities, recent research in the area of information economics demonstrates how rational herd behavior may arise because of ? ?informational cascades? ?? (Banerjee 1992; Bikhchandani,