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Prior literature has reported a tendency for consumers to rate peer-to-peer (P2P) services more positively than the same services provided by traditional businesses (e.g. Airbnb vs. hotel). We first show that consumers experience greater empathy toward a P2P service provider (a person) than a traditional service provider (a business). We then show that P2P services enjoy higher evaluations because empathy for the provider leads consumers to tolerate minor negative elements in those settings as compared to traditional business settings. Further, we show that this effect is moderated by the perceived size of the business. The implications of this type of rating bias on traditional businesses and consumer welfare, and the limitations of this research, are discussed. © 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
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Requests for charitable cash gifts during rite-of-passage occasions (e.g., weddings) are becoming increasingly common. This research examines whether recipients’ appreciation differs depending on whether a requested cash gift is charitable (e.g., donating to support people in need) or recipient-benefiting (e.g., renovating the recipient’s kitchen). Across five studies, we find that the effect of the gift type on appreciation is moderated by the gift amount. For low amounts, recipients appreciate charitable gifts more than recipient-benefiting gifts. However, for moderate and high amounts, appreciation is similar across gift types. This effect is mediated by the recipients’ perception of whether the gift amount meets their expectations and their subsequent perception of thoughtfulness. Consistent with our mechanism, in distant giver-recipient relationships, the effect of the gift type on appreciation for low amounts is attenuated. When gifts are not requested, recipients appreciate charitable gifts less than recipient-benefiting gifts.
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Academic dishonesty of students is a problem that threatens the integrity of educational institutions. Understanding the sources of academic dishonesty has become an urgent need, which compels higher educational institutions to evaluate and redesign approaches to address this problem. To develop new and important insights about this this form of student misconduct, this paper takes an integrative social cognitive perspective. It explores students’ attitudes toward various forms of academic dishonesty. The central research question concerns the impact of individual differences in moral disengagement and Machiavellianism on academic dishonesty tendencies. The study is based on a sample of 195 students at a public university in northeastern United States. Analysis was conducted by partial least squares equation modeling (SmartPLS-SEM). The analysis disclosed that, in sum, moral disengagement was strongly associated with academic dishonesty attitudes of fabricating information and both moral disengagement and Machiavellianism were associated with obtaining unfair academic dishonesty advantages. Data supported nearly all aspects of a structural model of academic dishonesty tendencies, with the exception of an association between Machiavellianism and receiving or abetting academic dishonesty, as well as an association between moral disengagement and ignoring prevalent practices that were in the predicted direction but were not significant. These findings provide a general understanding of the process by which academic dishonesty is determined. Study implications for ameliorating the impact of academic dishonesty are as follows: students should be engaged in an atmosphere full of communal morality, dissuasive of justificatory rationalizations and social arrangements that negate students’ use of moral disengagement.
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The exponential growth of big data, driven by AI and machine learning technologies, underscores the need for an ethical and sustainable approach to data utilization. Using problematization methodology, we consider the assumptions underpinning Big Data and AI and reconsider them from a sensemaking perspective. Big data represents an enactment rather than an objective reality, and organizations play an active role in its adoption and use. Strategizing is driven by plausibility rather than accuracy, and big data generates a retrospection of the past rather than a prediction of the future. A sensemaking perspective serves as reality check for managers, emphasizing the necessity of long-term sustainability and societal well-being. By cultivating experiments for learning communities and incubating innovation, organizations can effectively leverage big data in marketing, fostering transparent, collaborative, ethical, and sustainable data practices. © 2025 IEEE Computer Society. All rights reserved.
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Conditional promotions are designed to entice consumers to increase their basket sizes to meet a preset promotional threshold. In this research, we examine consumers' basket sizes, promotional thresholds, incentive framing and seemingly irrelevant cues in shopping environment as the factors that may jointly influence the effectiveness of a conditional promotion in inducing shoppers to increase their basket sizes. Our findings from five studies demonstrate that (i) the difference between basket sizes and promotional thresholds or seemingly irrelevant cues in shopping environment may induce an experience of psychological distance, (ii) the experience of psychological distance may interact with incentive framing to influence consumers' search likelihood in response to a conditional promotion such that psychological proximity (remoteness) leads to higher search likelihood in response to negatively (positively) framed incentives. We found that this effect is consistent across studies with different values of basket sizes and promotional thresholds and across behavioral and self‐reported measures representing search likelihood. (PsycInfo Database Record (c) 2025 APA, all rights reserved)
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