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Abstract
Political ideology plays a pivotal role in shaping individuals' attitudes, opinions, and behaviors. However, apart from a handful of studies, little is known about how consumers' political ideology affects their marketplace behavior. The authors used three large consumer complaint databases from the Consumer Financial Protection Bureau, National Highway Traffic Safety Administration, and Federal Communications Commission in conjunction with a county-level indicator of political ideology (the 2012 US presidential election results) to demonstrate that conservative consumers are not only less likely than liberal consumers to report complaints but also less likely to dispute complaint resolutions. A survey also sheds light on the relationship between political ideology and complaint/dispute behavior. Due to stronger motivations to engage in "system justification," conservative (as opposed to liberal) consumers are less likely to complain or dispute. The present research offers a useful means of identifying those consumers most and least likely to complain and dispute, given that political ideology is more observable than most psychological factors and more stable than most situational factors. Furthermore, this research and its theoretical framework open opportunities for future research examining the influence of political ideology on other marketplace behaviors.

Abstract
A typical behavioral research paper features multiple studies of a common phenomenon that are analyzed solely in isolation. Because the studies are of a common phenomenon, this practice is inefficient and forgoes important benefits that can be obtained only by analyzing them jointly in a single-paper meta-analysis (SPM). To facilitate SPM, we introduce meta-analytic methodology that is user-friendly, widely applicable, and specially tailored to the SPM of the set of studies that appear in a typical behavioral research paper. Our SPM methodology provides important benefits for study summary, theory testing, and replicability that we illustrate via three case studies that include papers recently published in the Journal of Consumer Research and the Journal of Marketing Research. We advocate that authors of typical behavioral research papers use it to supplement the single-study analyses that independently examine the multiple studies in the body of their papers as well as the "qualitative meta-analysis" that verbally synthesizes the studies in the general discussion of their papers. When used as such, this requires only a minor modification of current practice. We provide an easy-to-use website that implements our SPM methodology.

Abstract
How, and to what extent, consumer choices are influenced by the context in which the product is consumed remain important marketing questions. In this article, the authors develop a parsimonious context-dependent multidimensional unfolding model that can accommodate consumers' context-specific behaviors via ideal points in multiattribute space along with brand locations in that space while accounting for unobserved heterogeneity in consumer behavior. The authors provide an empirical illustration using panel data on beer brand choices in different contexts from U.S. beer consumers. They find more heterogeneity in behavior across social versus nonsocial contexts than across in-home and out-of-home consumption. The authors then show how the model can be used to derive a firm's optimal direction of brand repositioning given its competitive landscape in the various consumption contexts. Since consumer preferences can be correlated across contexts, they show that a movement toward the ideal point in one context does not necessarily improve the firm's market competitiveness in other contexts; thereby hurting the brand's overall performance.

Abstract
Deciphering consumers' sentiment expressions from big data (e.g., online reviews) has become a managerial priority to monitor product and service evaluations. However, sentiment analysis, the process of automatically distilling sentiment from text, provides little insight regarding the language granularities beyond the use of positive and negative words. Drawing on speech act theory, this study provides a fine-grained analysis of the implicit and explicit language used by consumers to express sentiment in text. An empirical text-mining study using more than 45,000 consumer reviews demonstrates the differential impacts of activation levels (e.g., tentative language), implicit sentiment expressions (e.g., commissive language), and discourse patterns (e.g., incoherence) on overall consumer sentiment (i.e., star ratings). In two follow-up studies, we demonstrate that these speech act features also influence the readers' behavior and are generalizable to other social media contexts, such as Twitter and Facebook. We contribute to research on consumer sentiment analysis by offering a more nuanced understanding of consumer sentiments and their implications.