Cognitive Geometry: An Analysis of Structure Underlying Representations of Similarity

This paper discusses the formal analysis of the underlying distance-based representations of consumer similarity judgments. Four models common in the marketing and psychological literature are examined—Euclidean and city-block spaces and ultrametric and additive trees. The analysis uses the distinction between “algebraic” and “geometric” structures as the basis for a unifying framework within which the four representations are compared and contrasted. The framework is then used to understand (1) the conditions under which model structure is theoretically revealing of the cognitive structure behind consumer behavior and (2) the degree to which similarity judgments and the resultant distance patterns are diagnostic of the appropriateness of a particular model. An important implication of the analysis is that there is a basic measurement indeterminacy associated with distance patterns, so that similarity data may not always reveal which is the “true” model in a given application. The consequences arising from this indeterminacy for the problem of model selection in marketing are illustrated with an empirical experiment designed to test the implications of the formal analysis in practical settings.product positioning, multidimensional scaling

The Formation of Key Marketing Variable Expectations and Their Impact on Firm Performance: Some Experimental Evidence

The expectation formation process has been extensively studied by economists, particularly for macroeconomic variables. However, no prior research has examined how expectations are formed and used in the context of marketing forecasting. In this paper, we use data from a simulated competitive environment (1) to examine the expectation formation process for important marketing variables such as market size, number of competing products, and average industry price, and (2) determine how inter-firm variation in the formation process affects performance. Using the Rational Expectations Hypothesis as a framework, we find that decision-makers' forecasts tend to be efficient, i.e., utilize all relevant available information, but are biased. Other key findings suggest that degree of firm rationality in the forecasting process as well as the level of forecasting accuracy are positively related to performance.

Locally Rational Decision Making: The Distracting Effect of Information on Managerial Performance

This paper describes a phenomenon called "locally rational" decision-making, in which the mere presence of information may have dysfunctional consequences even if decision makers do not process the information incorrectly. Using the results from an experiment conducted with a strategic market simulation game, we find that the accessibility of information results in a disposition to focus on those components of decision-making most clearly addressed by the information. If these are not the components most closely tied to success, overall performance may in fact suffer. The decision-making process is thus "locally rational" since it may be optimal with respect to specific components of a larger plan, but globally suboptimal with regard to ultimate outcomes and for the organization as a whole. We describe the implications of the phenomenon for the use of market-related data in managerial decision-making.decision making, rationality, strategy, information, performance, marketing simulation