Listening

Listen to this: Why consumer behavior researchers should care about listening

Abstract

Consumers’ decisions are intricately interwoven with their conversations. Whether it is an animated discussion with a trusted friend extolling the virtues of a newly acquired car (i.e., Word-of-Mouth), an engaging dialogue with a salesperson, or a clarifying call to a help center seeking guidance on a just-purchased smartwatch, every exchange hinges on a pivotal factor: the quality of listening. Listening quality shapes perceptions, affects social influence, drives behavioral intentions, and, ultimately, determines purchase and post-purchase outcomes. Yet, despite its importance to these consumer behavior outcomes, listening has received scant attention in consumer psychology. In this paper, we review the effects of listening on consumer behavior-relevant outcomes and unpack the components of quality listening to reveal their independent mechanisms. We also point to new frontiers in listening research beyond the in-person, dyadic interactions that have been the primary focus of listening research to date. By doing this, we elucidate how listening and consumer behavior are connected and encourage more research on listening in consumer psychology.
Netta Weinstein, Guy Itzchakov, Michael R. Maniaci
|
Attitudes
Conversational artificial intelligence (AI) can be harnessed to provide supportive parasocial interactions that rival or even exceed social support from human interactions. High-quality listening in human conversations fosters social connection that heals interpersonal wounds and lessens loneliness. While AI can furnish advice, listening involves the speakers’ perceptions of positive intention, a quality that AI can only simulate. Can such deep-seated support be provided by AI? This research examined two previously siloed areas of knowledge: the healing capabilities of human interpersonal listening, and the potential for AI to produce parasocial experiences of connection. Three experiments (N = 668) addressed this question through manipulating conversational AI listening to test effects on perceived listening, psychological needs, and state loneliness. We show that when prompted, AI could provide high-quality listening, characterized by careful attention and a positive environment for self-expression. More so, AI’s high-quality listening was perceived as better than participants’ average human interaction (Studies 1–3). Receiving high-quality listening predicted greater relatedness (Study 3) and autonomy (Studies 2 and 3) need satisfaction after participants discussed rejection (Study 2–3), loneliness (Study 3), and isolating attitudes (Study 3). Despite this, we did not observe downstream lessening of loneliness typically observed in human interactions, even for those who were high in trait loneliness (Study 3). These findings clearly contrast with research on human interactions and hint at the potential power, but also the limits, of AI in replicating supportive human interactions.
Keep reading
Guy Itzchakov, Avraham N. (Avi) Kluger
|
Listening
Giving performance feedback is one of the most common ways managers help their subordinates learn and improve. Yet, research revealed that feedback could actually hurt performance: More than 20 years ago, one of us (Kluger) analyzed 607 experiments on feedback effectiveness and found that feedback caused performance to decline in 38% of cases. This happened with both positive and negative feedback, mostly when the feedback threatened how people saw themselves.
Keep reading