International Journal of Research in Marketing最新文献

Product listing platforms commonly use generalized second-price auctions to select competing advertisers for limited ad positions. However, when advertisers are asymmetric, position auctions may confound the post-auction competition structure and thus endogenize the bidders’ values of the ad positions. We build an analytical model to examine the impact of position auctions on an asymmetric market structure, which consists of a mass marketer and two specialized advertisers of heterogeneous quality efficiencies. The advertisers bid for two ad slots and then compete for the market in price and quality. We find that the asymmetric market structure may increase the uncertainty of the auction outcomes, which then may induce the advertisers to underbid using a conservative strategy profile in the locally-envy free equilibrium. Consequently, the auction outcome may adversely include the less-efficient specialized advertiser. This result is stronger than the position paradox in the classic auction literature, as the advertiser with a competitive advantage may be driven out and obtain zero profit.

In the past few decades, the modern marketplace has offered consumers a proliferation of models for consumption based on sharing and access. Extant literature provides systematic examinations of motives for consuming products through the sharing economy on the demand side, but factors that affect consumers' asset-providing decisions on the supply side remain understudied. The current paper explores whether the socioeconomic environment one grew up in might produce a long-lasting impact on willingness to sharing one’s unused assets. Results from the analysis of a national-level field dataset and six preregistered studies (combined N = 45,289) reveal that lower childhood socioeconomic status can hinder consumers’ asset-providing behavior, an effect that holds beyond the influence of other factors such as current SES and asset availability. We identify greater territorial feelings towards one’s assets as a central mechanism driving the decreased asset-providing behavior of consumers with a lower childhood socioeconomic background, and we show that asset providers’ closeness to potential borrowers attenuates the negative impact of lower childhood SES.

This research examines the interdependencies in users’ sequential app adoptions within and across diverse app categories. We employ a Zero-inflated Negative Binomial (ZINB) model to analyze a unique, granular, and individual-level mobile app adoption dataset, revealing three main findings. First, users’ app adoption decisions are highly history-dependent and category-specific in a nonlinear fashion. Early adoption can enhance subsequent downloads within the same category for app categories with high needs evolvement and horizontal differentiation (e.g., Game and Education apps). However, it may crowd out subsequent downloads in other categories with low needs evolvement and horizontal differentiation (e.g., Communication and Social media apps). Second, these effects are further moderated by users’ individual characteristics such as app usage tenure and phone price. Third, there exist nontrivial app adoption spillovers across app categories. For example, users’ adoptions of apps with relatively high hedonic values (e.g., Game and Music apps) can suppress their subsequent need for apps with relatively high utilitarian values (e.g., Education and Online banking apps), and vice versa. Together, these results offer novel managerial implications for app developers and platforms to promote apps in different categories based on users’ adoption histories.

The advent of digitization has allowed firms to collect high-frequency data - subjective and objective - to monitor their service performance. This paper proposes a methodological framework to help firms understand the value of collecting these data. We apply the framework to novel high-frequency, individual-level, cross-sectional and time-series measures of subjective post-purchase perceptions (via surveys) and objective operational performance from a quick service restaurant and an auto rental company. Our approach allows for the quantification of the statistical and economic significance of collecting high-frequency subjective measures in the presence of their objective counterpart. In both settings, our results show that not collecting subjective service measures can lead to economically significant biases in resource allocation. We also find the presence of both within- and across-individual selection in survey responses, with the latter having a much bigger impact on the results. Our findings advance the literature on the measurement and management of service performance and provide insights to managers for forecasting and resource allocation in service settings.

Does the local presence of premium branded stores with strong associations to a product group help promote the relevant category as a whole? Based on the Starbucks example, this paper documents such a demand spillover effect for coffee across channels and firms: The firm’s stores stimulate coffee demand in mass-market grocery channels, benefiting rival firms that target consumption at home. I show the spillover at the household level, as well as with retail scanner data, employing a demand model to account for supply-side responses. To establish causality, I use a strict fixed effects specification with trend controls, and also validate the findings using instrumental variables based on the supply-side advantage to operating chain stores in proximate markets. In a representative market, the presence of a Starbucks stores boosts rival packaged coffee sales by 1.2%. The increase appears consistent a consumption stimulation effect of Starbucks stores acting as environmental cues for coffee, their main product. Evidence from other chains confirms the spillover, mainly from more premium brands with high demand-stimulating potential to lower-end mass products. The effect builds over time, and as cue theories predict, interacts positively with past consumption, suggesting a reinforcing effect on consumption habits.

Although donors may prefer contributing to causes that help those who are socially closer to them, we propose that donating to socially distant beneficiaries makes donors feel happier. This occurs because donating to distant (vs. close) others results in an experience of greater benevolence. We further identify regulatory focus as a boundary condition of these effects. In one choice study and four experiments featuring close to 2,500 respondents, we demonstrate this phenomenon across diverse samples and varying forms of beneficiaries. Our research extends prior work examining the impact of recognition from others on charitable behavior to examine donors’ self-evaluations, and how they impact happiness.

An online experiment and a large-scale correlational study show that the effects of a humor appeal in product advertising go beyond consumers’ general attitudes toward the ad and the advertised product. A humor appeal influences consumers’ perceptions of the advertised firms’ competence and warmth. Importantly, the competence and warmth signaling values of humor in advertising vary with the nature of the humor appeal. We specifically find that an incongruity resolution humor appeal enhances consumers’ impressions of the firms’ competence but only when consumers can resolve the incongruity. A tension relief humor appeal enhances consumers’ impressions of the firms’ warmth. Humorous self-disparagement reduces impressions of the firms’ competence, while other-disparagement reduces both warmth and competence firm impressions. We discuss how firms can use humor appeals in their marketing communication to signal their different qualities.

Part of marketing academia’s mandate is to generate findings that improve management practice. Managerial relevance plays a key role in this mandate as it describes a research project’s potential to influence managerial decision-making and thinking. Therefore, it is crucial to understand what makes research managerially relevant and to uncover success factors in the genesis of such research. This study addresses these issues through a qualitative analysis of 65 depth interviews with senior editors of business transfer journals, marketing managers, and academic researchers. The authors carve out distinct, multidimensional properties that determine managerial relevance. From specific configurations of these properties, four archetypical relevance types emerge: (1) problem-solving, (2) explicating, (3) consolidating, and (4) forward-thinking relevance. Finally, the authors develop a unifying framework and identify success factors for generating highly relevant research. Based on these insights, they suggest concrete courses of action for academics who seek to increase the managerial relevance of their research.

Designers of artificial agents often give them humanlike features, reflecting assumptions that humanlike agents evoke more positive evaluations than machinelike agents do. However, through four studies, the current article reveals a detrimental effect of anthropomorphizing embodied artificial agents. This effect occurs because these agents appear physically less safe in dangerous situations, which leads to consumers’ diminished self-safety perceptions and less favorable downstream consequences, both attitudinal (e.g., quality and trust perceptions, consumer evaluations, willingness to pay) and behavioral (e.g., information search, donation behavior). However, this detrimental effect is mitigated in non-dangerous situations or for artificial agents that usually do not operate in dangerous situations. The findings also reveal some theoretically important and practically relevant moderators. Specifically, when consumers receive marketing messages that direct their attention to artificial agents’ humanlike minds (e.g., cognitive and socio-emotional capabilities) rather than their humanlike bodies, the negative effect of anthropomorphizing artificial agents disappears. In addition to advancing emerging research on embodied artificial agents, this study provides practical guidance for marketers who plan to integrate artificial agents with humanlike features into their operations.

Concerns over the authenticity of reviews hinder their usefulness. Consumers discount the information they get from reviews, and this particularly harms brands with high ratings. The authors argue that perceived brand strength, brand advertising effort, price, and sales each act as signals that help positive reviews of a brand seem more reliable. They investigate this by studying Amazon.com reviews of branded products from 16 product categories that have the resources and potential desire to advertise. They examine consumer perceptions of review authenticity as perceived by machine learning algorithms trained on human subjects, as well as by direct perceptions of human subjects during validation. The results indicate that having a strong brand and investment in brand advertising, along with price and sales rank, are valuable to managers since they form a certain protection from suspiciousness.