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• Article | Organizational Behavior and Human Decision Processes

  Conversational Receptiveness: Expressing Engagement with Opposing Views

  M. Yeomans, J. Minson, H. Collins, H. Chen, F. Gino, M. Yeomans, J. Minson, H. Collins, H. Chen and F. Gino

  We examine “conversational receptiveness”—the use of language to communicate one’s willingness to thoughtfully engage with opposing views. We develop an interpretable machine-learning algorithm to identify the linguistic profile of receptiveness (Studies 1A-B). We then show that in contentious policy discussions, government executives who were rated as more receptive—according to our algorithm and their partners but not their own self-evaluations—were considered better teammates, advisors, and workplace representatives (Study 2). Furthermore, using field data from a setting where conflict management is endemic to productivity, we show that conversational receptiveness at the beginning of a conversation forestalls conflict escalation at the end. Specifically, Wikipedia editors who write more receptive posts are less prone to receiving personal attacks from disagreeing editors (Study 3). We develop a “receptiveness recipe” intervention based on our algorithm. We find that writers who follow the recipe are seen as more desirable partners for future collaboration and their messages are seen as more persuasive (Study 4). Overall, we find that conversational receptiveness is reliably measurable, has meaningful relational consequences, and can be substantially improved using our intervention.

  Keywords: receptiveness; natural language processing; disagreement; Interpersonal Communication; Relationships; Conflict Management;

  Citation:

  Yeomans, M., J. Minson, H. Collins, H. Chen, and F. Gino. "Conversational Receptiveness: Expressing Engagement with Opposing Views." Organizational Behavior and Human Decision Processes 160 (September 2020): 131–148.  View Details

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• Article | Organizational Behavior and Human Decision Processes

  Conversational Receptiveness: Expressing Engagement with Opposing Views

  M. Yeomans, J. Minson, H. Collins, H. Chen, F. Gino, M. Yeomans, J. Minson, H. Collins, H. Chen and F. Gino

  We examine “conversational receptiveness”—the use of language to communicate one’s willingness to thoughtfully engage with opposing views. We develop an interpretable machine-learning algorithm to identify the linguistic profile of receptiveness (Studies 1A-B). We then show that in contentious policy discussions, government executives who were rated as more receptive—according to our algorithm and their partners but not their own self-evaluations—were considered better teammates, advisors, and workplace representatives (Study 2). Furthermore, using field data from a setting where conflict management is endemic to productivity, we show that conversational receptiveness at the beginning of a conversation forestalls conflict escalation at the end. Specifically, Wikipedia editors who write more receptive posts are less prone to receiving personal attacks from disagreeing editors (Study 3). We develop a “receptiveness recipe” intervention based on our algorithm. We find that writers who follow the recipe are seen as more desirable partners for future collaboration and their messages are seen as more persuasive (Study 4). Overall, we find that conversational receptiveness is reliably measurable, has meaningful relational consequences, and can be substantially improved using our intervention.

  Keywords: receptiveness; natural language processing; disagreement; Interpersonal Communication; Relationships; Conflict Management;

  Citation:

  Yeomans, M., J. Minson, H. Collins, H. Chen, and F. Gino. "Conversational Receptiveness: Expressing Engagement with Opposing Views." Organizational Behavior and Human Decision Processes 160 (September 2020): 131–148.  View Details

  CiteView Details Read Now Read Now

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• Article | Organizational Behavior and Human Decision Processes

  Feeling Authentic Serves as a Buffer Against Rejections

  F. Gino and M. Kouchaki

  Social exclusion is a painful yet common experience in many people’s personal and professional lives. This research demonstrates that feeling authentic serves as a buffer against social rejection, leading people to experience less social pain. Across five studies, using different manipulations of authenticity, different paradigms to create social exclusion, and different measures of feeling rejected, we found that experiencing authenticity led participants to appraise situations as less threatening and to experience lower feelings of rejection from the social exclusion. We also found that perceived threat explains these effects. Our findings suggest that authenticity may be an underused resource for people who perceive themselves to be, or actually are, socially excluded or ostracized. This research has diverse and important implications: Interventions that increase authenticity could be used to reduce perceptions of threatening situations and the pain of impending exclusion episodes in situations ranging from adjustment to college to organizational orientation programs.

  Keywords: Authenticity; social exclusion; Threat; Decision Making; Perception; Relationships;

  Citation:

  Gino, F., and M. Kouchaki. "Feeling Authentic Serves as a Buffer Against Rejections." Organizational Behavior and Human Decision Processes 160 (September 2020): 36–50.  View Details

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