Knowledge that Transforms

Marketing Science greatly benefited from the admirable and fastidious efforts of more than 200 different individuals who provided manuscript reviews last year. Beyond those individuals already recognized on the editorial board, the editor-in-chief and senior/guest editors of Marketing Science are indebted to the many guest editors-in-chief, guest associate editors, and ad hoc reviewers who provided expert counsel and guidance on a voluntary basis. The following list acknowledges the contribution of guest editors-in-chief, guest associate editors, and ad hoc reviewers who served from January 1, 2015 to December 31, 2015. Finally, let us not forget to thank the authors. Marketing Science requires and receives outstanding submissions from many leading researchers and prestigious organizations. K. Sudhir Yale University

Features involving the taste, smell, touch, and sight of products, as well as attributes such as safety and confidence, are not easily measured in product research without respondents actually experiencing them. Moreover, product researchers often evaluate a large number of these attributes (e.g., >50) in applied studies, making standard valuation techniques such as conjoint analysis difficult to implement. Product researchers instead rely on ratings data to assess features for which the respondent has had actual experience. In this paper we develop a method of monetizing rating data to standardize product evaluations among respondents. The adjusted data are shown to increase the accuracy of purchase predictions by about 20% relative to existing methods of scale adjustment, leading to better inference in models using ratings data. We demonstrate our method using data from a large scale product use study by a packaged goods manufacturer. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mksc.2016.0980 .

Experimental methods are critical tools in marketing, psychology, and economics to isolate the effects of key variables from vagaries intrinsic to field data. As such, they are often considered exempt from the sort of sample selectivity artifacts widely documented in empirical research, in part because participants are randomly assigned to experimental conditions. To conserve time and resources, experiments often focus on items participants have chosen or are familiar with, for example, postchoice satisfaction ratings, certain free recall tasks, or specifying consideration sets preceding brand choice. When consumer input even partially influences the items about which researchers request subsequent data, the potential for item selectivity arises. In such situations, analyses are contingent on both the choice context(s) of the experiment and the alternatives participants elect to evaluate, potentially leading to substantial item selectivity overall and to differing degrees across conditions. We examine situations in which a nonignorable “choose one of many” (polytomous) selection process limits which items offer up subsequent information, and develop methods to allow substantive results to pertain to the full set of items, not only those selected. The framework is illustrated via two experiments in which participants choose and then evaluate a frequently purchased consumer good as well as data first examined by Ratner et al. [Ratner RK, Kahn BE, Kahneman D (1999) Choosing less-preferred experiences for the sake of variety. J. Consumer Res. 26(1):1–15]. Results indicate substantial item selectivity that, when corrected for, can lead to markedly different interpretations of focal variable effects, such as large effect size changes and even sign reversal. Moreover, failing to flexibly account for item selectivity across experimental conditions, even in well-designed experimental settings, can lead to inaccurate substantive inferences about consumers’ evaluative criteria. We further demonstrate robustness to theoretically driven (but not overtly misspecified) selection rules and provide researchers with a simple, “two-step” exploratory procedure akin to a “control function” approach—involving just one additional variable added to standard models—to determine whether and to what degree item selectivity may be affecting their substantive results. Data, as supplemental material, are available at https://doi.org/10.1287/mksc.2016.0991 .

We randomize advertising content motivated by the psychology literature on sympathy generation and framing effects in mailings to about 185,000 prospective new donors in India. We find a significant impact on the number of donors and amounts donated consistent with sympathy biases such as the “identifiable victim,” “in-group,” and “reference dependence.” A monthly reframing of the ask amount increases donors and the amount donated relative to daily reframing. A second field experiment targeted to past donors, finds that the effect of sympathy bias on giving is smaller in percentage terms but statistically and economically highly significant in terms of the magnitude of additional dollars raised. Methodologically, the paper complements the work of behavioral scholars by adopting an empirical researchers’ lens of measuring relative effect sizes and economic relevance of multiple behavioral theoretical constructs in the sympathy bias and charity domain within one field setting. Beyond the benefit of conceptual replications, the effect sizes provide guidance to managers on which behavioral theories are most managerially and economically relevant when developing advertising content. Data, as supplemental material, are available at https://doi.org/10.1287/mksc.2016.0989 .