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A growing literature shows that (integral) emotions arising in response to firm transgressions may influence consumer punishment. However, incidental emotions (which are unrelated to the decision at hand) can also be powerful drivers of consumer decision-making and could influence responses to firm transgressions. This paper aims to examine the role of incidental gratitude, as compared to incidental pride and a control condition, in shaping the acceptance of questionable consumer behavior toward a transgressing firm and the mediating role of self-righteousness in this regard.

Four experimental studies are conducted to examine the effect of gratitude, as compared to pride and a control condition, on the acceptance of questionable consumer behavior against a transgressing firm. Further, this research tests the underlying mechanism and a boundary condition of the predicted effect.

The results show that consumers experiencing gratitude, as compared to pride and a control condition, judge a questionable consumer behavior directed against a transgressing firm as less acceptable. These different emotion effects are found to be explained by self-righteousness. The findings also demonstrate that an apology by the firm attenuates the effect of emotions on consumer response toward the transgressing firm.

The present research contributes to the literature on consumer punishment by identifying the role of incidental emotions in determining self-righteousness and ethical judgments. The research focuses on and contrasts the effects of two specific positive emotions – gratitude and pride.

This paper offers managerial implications for firms involved in a transgression by highlighting the potential of gratitude. Notably, the findings of this research suggest that gratitude activation via marketing communications may help firms mitigate the negative effects of transgression events.

The present research provides a novel perspective on when and how positive emotions, such as gratitude and pride, can differentially and systematically influence ethical judgment toward a transgressing firm.

Choice deferral (making no choice at all) is a common phenomenon, especially when individuals face a difficult decision. This is further exacerbated in the presence of negative incidental emotions which can have a wide-ranging influence on various aspects of decision-making. Previous research suggests that process (vs outcome) accountability might be more effective at mitigating the effect of irrelevant factors. This paper aims to examine whether accountability attenuates emotion effects on choice and examines the differences in the efficacy of the two accountability types.

The paper uses the appraisal tendency framework to propose differences between same valenced emotions on choice deferral and predicts the moderating role of process versus outcome accountability. Two experiments are conducted to test the predictions and the results analyzed using logistic regression.

The authors find that outcome and process accountability have different moderating effects on emotion and choice deferral relationship: under outcome accountability, angry individuals are more likely to defer choice while under process accountability, differences in choice across emotion conditions are attenuated. As predicted, differences between anger and fear on the certainty appraisal and thereby information processing, mediate the effects of emotion on choice deferral in the outcome (but not process) condition.

This research studies the intersection of two developing research streams, affect and accountability, by focusing on specific affective states (anger and fear) and specific accountability types (outcome and process) in the important context of decision avoidance in consumer behavior. Thus, theoretical understanding in both domains is advanced and the benefits of specific accountability types clarified. Key implications for consumers and future research directions are also discussed.

This study aims to examine the role of hope and hate in political leaders’ messages in influencing liberals versus conservatives’ social-distancing behavior during the COVID-19 pandemic. Given the increasing political partisanship across the world today, using the appropriate message framing has important implications for social and public policy.

The authors use two Natural Language Processing (NLP) methods – a pretrained package (HateSonar) and a classifier built to implement our supervised neural network-based model architecture using RoBERTa – to analyze 61,466 tweets by each US state’s governor and two senators with the goal of examining the association between message factors invoking hate and hope and increased or decreased social distancing from March to May 2020. The authors examine individuals’ social-distancing behaviors (the amount of nonessential driving undertaken) using data from 3,047 US counties between March 13 and May 31, 2020, as reported by Google COVID-19 Community Mobility Reports and the New York Times repository of COVID-19 data.

The results show that for conservative state leaders, the use of hate increases nonessential driving of state residents. However, when these leaders use hope in their speech, nonessential driving of state residents decreases. For liberal state leaders, the use of hate displays a directionally different result as compared to their conservative counterparts.

Amid the emergence of new analytic techniques and novel data sources, the findings demonstrate that the use of global positioning systems data and social media analysis can provide valuable and precise insights into individual behavior. They also contribute to the literature on political ideology and emotion by demonstrating the use of specific emotion appeals in targeting specific consumer segments based on their political ideology.

The findings have significant implications for policymakers and public health officials regarding the importance of considering partisanship when developing and implementing public health policies. As partisanship continues to increase, applying the appropriate emotion appeal in messages will become increasingly crucial. The findings can help marketers and policymakers develop more effective social marketing campaigns by tailoring specific appeals given the political identity of the consumer.

Using Neural NLP methods, this study identifies the specific factors linking social media messaging from political leaders and increased compliance with health directives in a partisan population.

This study aims to investigate how gratitude, as compared to pride, can leverage the effectiveness of cause-related marketing, particularly a donation-based promotion. Drawing upon the appraisal tendency framework, this study establishes the underlying process driving these emotion effects. It also examines the moderating role of product type (hedonic vs utilitarian).

Five studies are conducted to test the predictions. Importantly, this study examines the predicted emotion effects across different sources of affect (dispositional, incidental and integral), different subject populations (students and Amazon Mechanical Turk panel) and different product categories (water bottle, chocolate and printer), leading to robust and generalizable findings.

Results show that gratitude (vs pride) increases the likelihood of purchasing a product with a donation-based promotion. This effect is mediated by gratitude’s other-responsibility appraisal and, in turn, increased reciprocity concerns (a serial mediation). Further, this study finds that how the gratitude (vs pride) effect is attenuated when the product is hedonic (but not utilitarian) in nature.

Past study on emotion and cause-related marketing has emphasized the role of negative emotions such as guilt. This study provides empirical evidence on the potential benefit of using positive emotions such as gratitude in cause-related marketing.

The implications of this study can benefit marketers by highlighting the use of gratitude appeals in their cause-related marketing campaigns.

The findings of the present research are significant because they highlight the potential role of a discrete positive emotion – gratitude – in leveraging the effectiveness of cause-related marketing and establish the underlying process driving this effect.

An employee’s satisfaction with the work context may affect her/his perception of the organization and may hence be a predictor of her/his intention to leave. The purpose of this paper is to explore the possible mediating role of context satisfaction between employees’ perception of job characteristics and their turnover intention and rests on the Job Characteristics Model (JCM).

Hierarchical regression analysis was used to test the moderation hypothesis on sample data of 214 employees of 19 public sector banks in India. The population comprised both junior and middle management grade employees as these are expected to succeed retiring middle and senior management employees.

Findings suggest that in addition to enriched jobs, context satisfaction is critical to establish a positive environment to lessen turnover intention of employees. This highlights the need for a positive and supportive work context to maximize the benefits of jobs with positive characteristics.

The study is important for academicians and practitioners alike as it is evidence to the underlying process of how perception towards job characteristics together with work context as a less researched construct of JCM may influence intention to quit. The findings find relevance in the Indian banking sector, where retaining talent is a major challenge.