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Purpose – This chapter discusses the role of emotion expression in decision-making. To understand connections between emotion and decision it is helpful first to differentiate between emotion experience and emotion expression. Understanding how emotion expression influences decision-making is important as a practical matter. However, in contrast to emotion experience, economic research has paid little attention to the significance of emotion expression in decision-making.

Approach – I review recent studies on emotion expression, paying specific attention to possible connections between emotion expression, punishment, fair economic exchange, and well-being.

Practical implications – In contrast to emotions, which are typically difficult to control, I suggest that opportunities for emotion expression can feasibly be manipulated through appropriately designed policies. I further suggest that this approach may have the ability to positively affect well-being and economic outcomes.

Value of the chapter – The chapter provides new perspectives on how policy-makers can benefit by understanding the effect of emotion expression in decision-making. The chapter also suggests future research to improve our understanding of emotion expression.

Purpose – We aim to elucidate the influence of leaders' emotion expressions on the social distance between leaders and followers in face-to-face and digital communication.

Design/methodology/approach – Literature review

Findings – Following functional theories on emotions, leaders' expressions of socially engaging emotions (e.g., guilt, happiness, gratitude, and compassion) lower social distance. Leaders' expressions of socially disengaging emotions (e.g., anger, contempt, disgust, and pride) increase social distance. In digital communication, we propose that the effect of socially engaging and disengaging emotions depends on the social presence that is provided by the different digital communication media.

Practical implication – Based on our theoretical model, we derive implications for (1) leaders' use of face-to-face communication, (2) the importance of digital communication with high social presence, (3) leaders' use of digital communication as a tool for emotion regulation, and (4) coping strategies when communicating via digital means with low social presence.

Research in industrial and organizational psychology demonstrates that the regulation of negative emotions in response to both organizational stressors and interpersonal workplace interactions can result in functional and dysfunctional outcomes (Côté, 2005; Diefendorff, Richard, & Yang, 2008). Research on the regulation of negative emotions has additionally been conducted in social psychology, developmental psychology, neuropsychology, health psychology, and clinical psychology. A close reading of this broader literature, however, reveals that the conceptualization and use of the term “emotion regulation” varies within each research field as well as across these fields. The main focus of our chapter is to make sense of the term “emotion regulation” in the workplace by considering its use across a broad range of psychology disciplines. We then develop an overarching theoretical framework using disambiguating terminology to highlight what we argue are the important constructs involved in the process of intrapersonal emotion generation, emotional experience regulation, and emotional expression regulation in the workplace (e.g., emotional intelligence, emotion regulation strategies, emotion expression displays). We anticipate this chapter will enable researchers and industrial and organizational psychologists to identify the conditions under which functional regulation outcomes are more likely to occur and then build interventions around these findings.

The use of artificial intelligence (AI) in management research is still nascent and has primarily focused on content analyses of text data. Some method scholars have begun to discuss the potential benefits of far broader applications; however, these discussions have not led yet to a wave of corresponding AI applications by management researchers. This chapter explores the feasibility and the potential value of using AI for a very specific methodological task: the reliable and efficient capturing of higher-level psychological constructs in management research. It introduces the capturing of basic emotions and emotional authenticity of entrepreneurs based on their macro- and microfacial expressions during pitch presentations as an illustrative example of related AI opportunities and challenges. Thus, this chapter provides both motivation and guidance to management scholars for future applications of AI to advance management research.

This chapter focuses on whether perceived emotional intensity and help need is possible to discriminate in expressions of fear and neutrality in brief authentic emergency calls. Extraction of acoustic parameters of fear and neutrality was done prior to letting participants listen to a low-pass-filtered stimuli set. Participants discriminated fear and neutrality in both the intensity and help need condition. In turn, judged intensity and judged help need correlated strongly, with partial correlations indicating that participants use acoustically measured intensity (mean dB) as information to infer the intensity/help need relationship. We also discuss the implications of emotional expression in the call centre domain.

Past research exploring the influence of affect on group outcomes has primarily considered how the experience of single emotions and mood vary and converge across group members, but does not address the fact that a single group member may express multiple, conflicting emotions simultaneously (e.g., emotional ambivalence). Such complex expressions may drastically alter the way other group members perceive and respond to one another, and in turn, drastically alter the group-level dynamics. We address this gap in the literature by modeling the social consequences of expressing emotional ambivalence, thereby expanding our understanding of emotional ambivalence in group contexts. Implications for research on emotional ambivalence and research on emotions in groups are discussed.

Extant research shows mixed results on the impact of expressed negative emotions on donations in online charitable crowdfunding. This study solves the puzzle by examining how different types of negative emotions (i.e. sadness, anxiety and fear) expressed in crowdfunding project descriptions affect donations.

Data on 15,653 projects across four categories (medical assistance, education assistance, disaster assistance and poverty assistance) from September 2013 to May 2019 come from a leading online crowdfunding platform in China. Text analysis and regression models serve to test the hypotheses.

In the medical assistance category, the expression of sadness has an inverted U-shaped effect on donations, while the expression of anxiety has a negative effect. An appropriate number of sadness words is helpful but should not exceed five times. In the education assistance and disaster assistance categories, the expression of sadness has a positive effect on donations, but disclosure of anxiety and fear has no influence on donations. Expressions of sadness, anxiety and fear have no impact on donations in the poverty assistance category.

This work has important implications for fundraisers on how to regulate the fundraisers' expressions of negative emotions in a project's description to attract donations. These insights are also relevant for online crowdfunding platforms.

Online crowdfunding research often studies negative emotions as a whole and does not differentiate project types. The current work contributes by empirically testing the impact of three types of negative emotions on donations across four major online crowdfunding categories.

Current research suggests a positive link between followers’ perceptions of their leaders’ expression of positive emotions and followers’ trust in their leaders. Based on the theories about the social function of emotions, the authors aim to qualify this generalized assumption. The purpose of this paper is to demonstrate that followers’ perceptions of leaders’ expressions of specific positive emotions – namely, pride and gratitude – differentially influence follower ratings of leaders’ trustworthiness (benevolence, integrity, and ability), and, ultimately, trust in the leader.

The hypotheses were tested using a multimethod approach combining experimental evidence (n=271) with longitudinal field data (n=120).

Both when experimentally manipulating leaders’ emotion expressions and when measuring followers’ perceptions of leaders’ emotion expressions, this research found leaders’ expressions of pride to be consistently associated with lower perceived benevolence, while leaders’ expressions of gratitude were associated with higher perceptions of benevolence and integrity.

This paper theoretically and empirically establishes that leaders’ expressions of discrete positive emotions differentially influence followers’ trust in the leader via trustworthiness perceptions.

Theorists, such as Darwin and Aristotle, have long argued that facial expressions communicate information about a person's emotional state. Recently, validated coding strategies for facial expressions have been developed, which enable researchers to reliably assess a person's affect. Although social, health, and clinical psychologists have regularly employed these objective measures of facial expressions (OMFE), occupational stress and well-being researchers are yet to benefit from this method. The subsequent chapter integrates the facial expression and occupational well-being literature. Specifically, we discuss the advantages of OMFE over self-reports and implications of OMFE for future research on occupational well-being.

This chapter presents a compassionate response model of workplace anger. The model incorporates an interpersonal feedback loop to show how compassionate responses to workplace anger have the potential for generating gratitude within the angry individual. Both reactions should ultimately result in more favorable organizational outcomes from anger episodes. In addition, the model identifies message, individual, relational, and organizational factors moderating the likelihood that an anger expression, compassion, and gratitude progression take place. The model proposes that anger expression is not inherently negative for individuals and organizations, but may initiate a series of potentially positive exchanges of emotion and caring.