Should Reviewers Stand in the Shoes of Review Readers? The Role of Perspective Taking in Online Reviews

Reviewers can describe their experience with a product or service from their own perspective or from the perspective of review readers (or prospective consumers). The present paper investigates how and why reviewers’ perspective taking may influence review readers’ perception of review helpfulness. Drawing on the perspective taking literature, we posit that reviews that take (vs. do not take) the perspective of prospective consumers are more likely to be perceived helpful, and that this effect can be explained through greater reviewer attractiveness perceived by consumers. In Study 1, real app reviews from Apple’s App Store were collected to examine the relationship between perspective taking and review helpfulness. In Study 2, experimental methodology was utilized to identify and explain the effect of perspective taking in terms of perceived reviewer attractiveness. The findings provide converging evidence for the important role of perspective taking in online reviews

Dreading and Ranting: The Distinct Effects of Anxiety and Anger in Online Seller Reviews

This paper explores effects of the emotions embedded in a seller review on its perceived helpfulness. Drawing on frameworks from the emotion and cognitive processing literatures, the authors propose that although emotional review content is subject to a well-known negativity bias, the effects of discrete emotions will vary, and that one source of this variance is perceptions of reviewers’ cognitive effort. We focused on the roles of two distinct, negative emotions common to seller reviews: anxiety and anger. In Study 1, actual seller reviews from Yahoo Shopping websites were collected to determine the effects of anxiety and anger on review helpfulness. In Study 2, an experiment was utilized to identify and explain the differential impact of anxiety and anger in terms of perceived reviewer effort. Our findings demonstrate the importance of examining discrete emotions in online word-of-mouth, and they also carry important practical implications for consumers and online retailers

Mechanisms of Negativity Bias: An Empirical Exploration of App Reviews In Apple’s App Store

Researchers in many diverse areas have consistently found that we are unduly influenced by negative information. In electronic commerce, this negativity bias is evident in the effect of product reviews on consumer behavior in the information systems literature. While the negativity bias is well documented, there has been little systematic and empirical research on its underlying causes. Utilizing a novel data set collected from Apple’s App Store, we examine three probable causes of the negativity bias: that negative reviews are more specific, that they have higher surprise value, and that they increase our ability to avoid losses. The empirical analysis revealed that while all three mechanisms contribute to the negativity bias, the ‘surprise’ factor and the ability to avoid losses play a more prominent role when consumers process and integrate positive and negative review information. Our findings also carry important practical implications for review platforms and online companies

Emotional Arousal and News Readership in Social Media

Expressions of emotions are common in news posts on social media. News providers embed emotional expressions to grab users’ attention and entice them to read the full article. However, there is a lack of empirical evidence to support this practice. We develop a theoretical model using emotions as social information theory to explain how, when and why the arousal of emotions expressed in headlines influences news article reading in social media. Through three experiments, we provide converging evidence that the use of expressed arousal backfires and reduces news reading. We also reveal a context-dependent boundary condition (i.e., information gap) and explore underlying mechanisms. Our findings speak to the growing literature on emotional expressions in social media and challenge the assumption that expressed arousal is beneficial in increasing news readership in social media

Chatbot Empathy in Customer Service: When It Works and When It Backfires

The advance of artificial intelligence technologies has enabled chatbots to be emotionally responsive. While expressing empathy constitutes a critical component of emotional responsiveness often required for human service employees, the impact of empathy expressions by service chatbots is underexamined. In this research, we investigate the effect of service chatbots’ empathy expressions towards two possible sources for customers’ negative emotions: negative consumption experience and chatbot failure. Drawing on the social perception literature, we propose that chatbot-expressed empathy towards negative consumption experience enhances service evaluations by increasing perceived warmth of a chatbot, but not competence. We further propose that chatbot-expressed empathy towards chatbot failure hurts service evaluations by decreasing perceived competence of a chatbot, but not warmth. Results from laboratory experiments provide suggestive evidence for our arguments. Our theoretical framework and findings illuminate the role of empathy expressed by service chatbots and offer guidance on when to deploy empathic chatbots in practice

Positive Shift, Social Projection, and Honesty on Social Networking Sites

Positive emotions are prevalent on Social Networking Sites (SNS) because of positive shift—users’ tendency to shift the expression of their emotions in the more positive direction. Emotion expressers aim to gain a more positive impression and elevate their social standing through positive shift, but little is known about the unintended consequences of positive shift for the expressors. Drawing on social projection theory and emotional journey theory, we argue that positive shift can lead to social projection and reduce the expressor’s perceived honesty of other SNS users—an important antecedent of trust and satisfaction with SNS, and this is more likely to occur when the user shifts emotions with higher emotional dissonance (i.e., difference between expressed and experienced emotions). We further propose a diversity reminder as a likely remedy that suppresses the social projection process. Using two experiments, we found evidence supporting these predictions. Our findings provide important implications

Implementing Choices in Chatbot-initiated Service Interactions: Helpful or Harmful?

Chatbots are increasingly equipped to provide choices for customers to click and choose from when communicating with the chatbots. This research investigates when and why implementing choices enhances or impairs customers’ service experience. Based on the concept of fluency, we posit that the implementation of choices is beneficial only after a conversational breakdown occurs because the value of choice provision for facilitating fluency may not be recognizable or realized in the absence of service breakdowns. We further propose that the implementation of choices is counterproductive when the choice set is perceived as incomprehensive because it decreases the perception of fluency. We conducted several experiments to test these hypotheses. By illuminating when and why choice implementation may help or harm customers during a chatbot-initiated service interaction, we augment the current understanding of a chatbot’s role in customers’ service experience and provide insights for the deployment of choice-equipped chatbots in customer service

The Journey to Self: An Intra-personal Perspective of Emotion Regulation on Social Networking Sites

Although social networking sites (SNS) users often share positive emotions in the content posted online, their satisfaction with SNS and intention to continue using it vary greatly across users. We argue that a key to addressing this puzzle is how content creators up-regulate their emotions on SNS. Building on emotion regulation theory and belongingness theory, we characterize digital emotion regulation in two ways (i.e., positive shift and emotional labor) and propose a dual-pathway model that involves two self-views. By constructing three complementary studies, we find that it is emotional labor, rather than positive shift, that drives a user’s sense of belonging through anticipated self-enhancement (i.e., communal self-view) and felt authenticity (i.e., authentic self-view) and explains the varying outcomes. Our findings reveal the benefits of deep acting and countervailing effects of surface acting. The present research provides important theoretical and practical implications