Consumer informedness plays a critical role in determining consumer choice in the presence of information technology deployed by competing firms in the marketplace. This paper develops a new <i>theory of consumer informedness</i>. Using data collected through a series of stated choice experiments in two different research contexts, we examine how consumer characteristics and observed behaviors moderate the influence of price and product informedness on consumer choice. The results indicate that different types of consumer informedness amplify different consumer behaviors in specific consumer segments. In particular, we found that price informedness is more influential among consumers in the <i>commodity segment</i>. They exhibit greater <i>trading down</i> behavior, which represents stronger preferences for choosing the products that provide the best price. In contrast, product informedness is more influential among consumers in the <i>differentiated segment</i>. This group exhibits greater <i>trading out</i> behavior, involving stronger preferences for choosing products that best suit their specific needs. These results suggest that firm information strategy should take into account consumers' characteristics, their past observed behaviors, and the impact of consumer informedness. We also discuss the theoretical contributions of this research and its broader implications for firm-level information strategy.
The application of fundamental option pricing models (OPMs), such as the binomial and the Black-Scholes models, to problems in information technology (IT) investment decision making have been the subject of some debate in the last few years. Prior research, for example, has made the case that pricing "real options" in real world operational and strategic settings offers the potential for useful insights in the evaluation of irreversible investments under uncertainty. However, most authors in the IS literature have made their cases using illustrative, rather than actual real world examples, and have always concluded with caveats and questions for future research about the applicability of such methods in practice. This paper makes three important contributions in this context: (1) it provides a formal theoretical grounding for the validity of the Black-Scholes option pricing model in the context of the spectrum of capital budgeting methods that might be employed to assess IT investments; (2) it shows why the assumptions of both the Black-Scholes and the binomial option pricing models place constraints on the range of IT investment situations that one can evaluate that are similar to those implied by traditional capital budgeting methods such as discounted cash flow analysis; and (3) it presents the first application of the Black-Scholes model that uses a real world business situation involving IT as its test bed. Our application focuses on an analysis of the timing of the deployment of point-of-sale (POS) debit services by the Yankee 24 shared electronic banking network of New England. This application enables us to make the case for the generalizability of the approach we discuss to four IT investment settings.