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How do consumers choose among complementary products (e.g., a cell phone and a service plan) when some of the offerings may be incompatible? In many industries (e.g., the fast-growing technology industry, the entertainment industry), products from complementary categories are often not compatible with one another. For example, different cell phones (e.g., iPhone versus Motorola RAZR V3t) are compatible with different wireless service plans (e.g., Cingular versus T-Mobile). To what extent do consumers screen by category or evaluate products simultaneously from multiple categories to simplify such complex decisions? If consumers engage in category-based screening, can some context-related factors (e.g., intracategory differentiation—that is, the degree of differentiation among competing products within a category) and individual factors (e.g., the decision goal—that is, the primary benefit the consumer seeks) influence them to choose a certain category to screen first?

The authors conceptualize and demonstrate that when choosing a pair of such complementary products, a consumer is likely to use a two-stage decision strategy: screening by one category first to narrow down the number of pairs for further evaluation in the second stage. In the presence of incompatibility, screening by one category rather than the other may lead to different choice outcomes. The authors develop a behavioral theory–driven choice model that accounts for both preference heterogeneity and structural heterogeneity of decision strategies to examine the extent to which consumers engage in category-based screening. Analysis of data from a 2 (intracategory differentiation conditions) × 2 (decision goals) conjoint choice experiment reveals that people tend to screen a category that has higher intracategory differentiation and that is congruent with their decision goals. The authors suggest possible marketing actions that a firm can take to promote the use of a specific decision strategy that leads consumers to choose its product. In particular, they demonstrate that a firm with a superior (inferior) product might benefit from product strategies that increase differentiation within its own (complementary) category and from promoting its own (compatible complementary) product. These results are particularly noteworthy because they suggest that firms offering superior versus inferior products should take different courses of actions to compete more effectively.

Overall, this research is of both theoretical and managerial interest. It broadens the multicategory choice literature to many other contexts in which incompatibility exists between categories. It further broadens the examination of decision heuristics from the attribute to the category level. Its investigation of the possible use, and the factors that influence such use, of category-based screening strategies provides guidelines for firm decision making in response to consumers’ propensity to engage in category-based screening. Finally, this study exemplifies the value of fusing behavior theories, experimental design, and econometric modeling in marketing research.

Biography
Anocha Aribarg received her PhD from the University of Wisconsin and is Assistant Professor of Marketing in the Ross School of Business at the University of Michigan. Her primary research interests involve integrating econometric modeling, Bayesian statistical inference, and consumer behavior theories to (1) examine consumer complex choice decision making, such as group decision making and the use of compensatory and noncompensatory decision processes, and (2) address challenging issues related to product portfolio management.

Natasha Zhang Foutz received her PhD from Cornell University and is Assistant Professor of Commerce in the McIntire School of Commerce at the University of Virginia. Previously, she was on the faculty at the University of Maryland. Her research focuses on using Bayesian and dynamic modeling approaches to study (1) the design of innovative products while accounting for the influence of choice contexts and consumer psychological factors and (2) firms’ release timing strategy and media promotional strategy when managing the diffusion of short-life-cycle technology products and entertainment services.

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