مدهای منطقی در واکنش های سرمایه گذار به اطلاعیه های تجارت الکترونیک: توضیح حباب اینترنت

This work proposes that information cascade theory can help to explain the formation of the Internet bubble. We propose that the bubble existed because a lack of good information about the potential value of electronic commerce led investors to rely on other investors’ private valuations of electronic commerce. We use the event study methodology to estimate returns to company announcements of electronic commerce initiatives in 1999 and 2000. We find that after controlling for network externalities and time trends, investors’ valuations of the returns to electronic commerce initiatives were significantly influenced by the market return from prior periods. Moreover, the relative weight placed on prior periods’ returns decreased as the variance of the prior periods’ returns increased. Both of the results are consistent with the behavior predicted by information cascade theory.

Technology is subject to fads – situations in which many agents adopt a technology with exaggerated zeal [1], [2] and [3]. Recently, we witnessed an impressive technology fad – the Internet bubble. From 1998 to 2000 the popular press hailed the beginning of a new economy, and investments in electronic commerce activities were believed to be the best use of one’s money. Then, by 2002, we returned to the old economy and electronic commerce investment was no longer seen as being particularly better or worse than any other kind of business investment. Businesses certainly needed the electronic channel, but they also needed many other things. During this time the chosen vehicle for investing in electronic commerce was the stock market. For example, in the 24 months from January 1998 to January 2000, the AMEX Internet stock index increased nearly 600%. However, by January 2002 it had returned almost to its 1998 level. Even today, in 2006, it is only about 50% higher than its 1998 level. Why did investors believe that the returns on electronic commerce initiatives should be so large? Mills [4] cites four key reasons given to explain the Internet bubble: It was an accident, it was engineered by the incentive structures of financial services firms, it was due to inexperienced investors entering the market, and it was an example of “the madness of crowds”. To this list we add another reason. This work proposes that investors’ estimates of electronic commerce returns were the best guess of rationally-motivated individuals making decisions with great uncertainty. Specifically, we argue that each individual was very uncertain about how large returns on e-commerce investments should have been, and therefore supplemented his or her own information by relying on information contained in the investment behavior of others. Although there were clearly other causes of the bubble, our data suggest that as much as 25% of the value investors placed in an electronic commerce investment was based on the value others placed on prior electronic commerce investments. In this paper, we investigate empirically the idea that technology fads are a consequence of agents inferring information about the benefits of a technology from the observable actions of other agents. We use stock return data from the “DotCom” era to investigate this question. In particular, we investigate agents’ willingness to pay for technology based on other agents’ willingness to pay for similar technologies. The paper proceeds as follows. In the next section we review literature explaining technology fads. We then develop a theoretical explanation of fads as information processes. We then describe the data and conduct our analyses. We conclude with implications of our findings for research and practice.

6.1. Contribution We have proposed a theoretical explanation of the DotCom fad of 1999–2000. Specifically, we posited that the willingness of investors to commit capital to successive electronic commerce initiatives stemmed from the lack of information in the environment. To supplement their own limited information investors used the pooled information present in the market’s previous reactions to e-commerce initiatives. Each successive positive market reaction modified investor perceptions of electronic commerce in a positive manner, and each successive negative reaction modified investor perceptions in a negative manner, thus creating reinforcing effects that caused a rapid rise, then fall, in perceptions of electronic commerce value. The primary implication of this research is that IT will continue to be characterized by fads. IT is complex and requires complementary organizational changes to realize value. This means that the real benefits of IT are not known when firms have to make decisions about them. One mechanism rational individuals can use to help them value novel IT is to observe how others value the same IT. While this helps each decision maker individually, it leads to fads. These fads can move in both directions, with adopters overvaluing IT or undervaluing IT. Therefore, both researchers and organizations must be careful in evaluating new IT. This means that decision makers should collect as much private information about the value of IT as possible before incorporating the behaviors of others. However, the behavior of others should be incorporated because it does lead to better decisions, but it should be discounted appropriately. An important implication for practitioners is that theory should be used when valuing IT. Theory that bases its arguments on well-tested logic can facilitate realistic valuations of IT. For example, while a common perception at the time of the DotCom bubble in the popular press was that the Internet was a new economy with new rules, and that firms like eToys and Pets.com would replace firms like Toys R Us and Petsmart, researchers used the resource-based view of the firm to argue, “…the initial disadvantages of non-net firms from being on the learning curve with respect to Internet technologies and the novel e-commerce context are likely to be largely offset by the considerable advantages derived from the migration of existing firm competencies to e-commerce operations” [33, p. 195]. Use of theory provides a foundation for decision making, which can lead to the avoidance of irrational fads. This is particularly important in domains such as IT, in which the artifacts being evaluated change frequently. 6.2. Limitations As with any research effort, there are certain limitations to the work performed in this paper. A central limitation of the study is the period examined. Undoubtedly, the time period under consideration was not a typical period in stock market history. We chose it specifically to examine behavior in fad-like conditions. Therefore, it is not clear that we can generalize the results to other periods. On the other hand, information cascade theory suggests that some fads are rational specifically because relying on the behavior of others improves one’s chance of making a good decision. In fact, information cascade theory shows that people will, on average, do better by relying on the signals of others. The theory mainly focuses on what happens when things go awry because that is more interesting, but following the model we suggest does in fact result in better estimates over time than relying on personal information alone. Thus, the results may be generalizable, with this period simply representing an extreme outcome. There are also several statistical limitations that are worth noting. First, on many days there were multiple announcements, and we used the average abnormal return to all announcements on a day. However, this is only one way to deal with the problem that many firms may pursue a particular course of action on a given day. We chose to look at day-to-day changes rather than event-to-event changes. Also, we do not allow for information decay. That is, we only count periods as days that electronic commerce initiatives were announced. Several days may actually elapse between periods, particularly on weekends. It is not clear whether it makes sense to discount the effects of a Friday event on a Monday return more than the effects of a Tuesday event on a Wednesday return. Finally, it is important to note that not all events are created equal. Some electronic commerce announcements may be profound while others may be trivial. We do not classify events into different types. In general, this would tend to increase the error of measure, and thus reduce the power of the tests, so the fact that the tests are significant is even more surprising. However, it is possible that our theory holds for some subsets of electronic commerce initiatives and not others. In particular, it seems reasonable to argue that those for which there is a great deal of information would be less susceptible to the behavior of others, while those that are particularly novel would be more susceptible to the processes we describe. 6.3. Future research An area for future research is a consideration of the scope of e-commerce initiatives that lead to fads. Our unit of analysis is e-commerce initiatives generally, but other researchers have delineated different categories of e-commerce initiatives [9], [31] and [32]. Future research could examine which categories of electronic commerce activities are most subject to fads and what sorts of spillovers one category has on another. For example, consumer portal investors may react more strongly to market information than online travel services investors. Similarly, content provider investors may react more strongly to the information contained in the market’s reaction to initiatives by online retailers than to the information contained in market reactions to business-to-business exchanges. Elucidating theory about who receives information from whom about the value of IT initiatives has great potential value. Another area for future research is the decision processes of the electronic commerce firms themselves. In this case, our unit of analysis was investors, but firm behavior is likely to be dependent upon investor perceptions and upon other firms’ behavior. However, the dependencies are likely to be different, largely because firms have a great deal of time and resources to devote to their decisions, whereas individual investors in modern markets must often react very quickly to information without access to such resources. Moreover, firm decisions are much more complicated than simply deciding on a price. Of course, firms exercise direct control over the execution of the decision and can choose to modify their decisions in complicated ways over time. Taken together, the firm decision is likely to be different than the decisions of investors. In sum, this research offers a promising new direction for research on technological fads. Our results indicate that investors put significant weight on prior market sentiment about the value of technology when they make their own decisions about the value of similar technology. We propose that this occurs because the market is a means of aggregating the scarce information available about the potential benefits of new technologies. Thus, we follow Surowiecki in suggesting that people make use of the wisdom of crowds [22]. Moreover, people should make use of such wisdom, as it often leads to better individual decisions. However, it can also lead to pathological outcomes, such as electronic commerce bubbles and busts, for the system as a whole. Thus, further investigations into the behavior of individuals in valuing technological innovations in contexts involving potential information cascades are warranted.