The effect of flaming on computer-mediated negotiations

Abstract

There is an increasing use of computer media for negotiations. However, the use of computer-mediated channels increases the hostile expressions of emotion, termed flaming. Although researchers agree that flaming has important effects on negotiation, predictions concerning these effects are inconsistent, suggesting a need for further investigation. We address this need by extending current flaming and negotiation research in two ways. First, we identify two different types of flaming: that which is motivated by perceptions concerning the negotiating opponent (e.g., he/she is unfair) and that which is motivated by perceptions concerning the negotiating context (e.g., the communication channel is too slow). Second, we differentiate between the effects of flaming on the concession behaviors of the flame sender and the flame recipient, and the effects of these behaviors on negotiated agreement. Via a laboratory study, we demonstrate that flames directed at the negotiation opponent slightly decrease the likelihood of reaching an agreement, and when an agreement is reached, it result in outcomes significantly favoring the flame recipient rather than the flame sender. In contrast, flames directed at the negotiation context significantly increase the likelihood of agreement, although outcomes still favor the flame recipient over the flame sender. These results suggest that flame senders are generally worse off than flame recipients, which provides an important basis for the strategic use of flaming in negotiations.

Keywords:

• flaming
• computer mediation
• negotiation
• concession
• emotion
• affect

Acknowledgements

We thank Blake Ives as well as the anonymous reviewers for their comments on earlier versions of this paper. We also thank Richard Holowczak and Bruce Weber for their contributions to the development of the negotiation task that was used in our study. We are grateful to Rebecca Biel and Brian Woods, along with Leah Duque, Vlad Krotov, Elham Mousavidin, Hesam Panhi, and Doug Steel for their efforts in coding our data.

Additional information

Notes on contributors

Norman A Johnson

About the authors

Norman A. Johson is an assistant professor in the Decision and Information Sciences Department in the Bauer College of Business at the University of Houston. He earned his masters and doctorate degrees from Baruch College, City University of New York. His current research interests include construct development, computer-mediated negotiation, communication and decision-making under uncertainty, affect and trust.

Randolph B Cooper

Randolph B. Cooper is a Professor in the Decision and Information Sciences Department in the Bauer College of Business at the University of Houston. He received his bachelors, masters, and doctorate degrees from the University of California at Los Angeles. He has published in a variety of academic journals, including DataBase, Journal of Management Information Systems, Management Science, MIS Quarterly, and Omega. His current research interests include the diffusion of information technology innovations, management of systems design creativity, and the impact of information systems on negotiation.

Wynne W Chin

Wynne W. Chin is a Professor in the Decision and Information Sciences Department in the Bauer College of Business at the University of Houston. He received his doctorate from the University of Michigan in Computers and Information Systems, M.S. in Chemical Engineering (biomedical option) from Northwestern University, MBA from the University of Michigan, and a Bachelors in Biophysics from U.C. Berkeley. He has published in journals such as MIS Quarterly, Information Systems Research, and Decision Sciences. Dr. Chin's substantive interests include modeling the individual IT adoption process, end-user satisfaction, and developing group process measures such as cohesion, satisfaction, and consensus to understand the impact of electronic meeting systems. More recently, he has begun working on cross-cultural analysis. His research is largely empirical and quantitative relying on lab and Monte Carlo experiments as well as surveys. Methodologically Dr. Chin focuses on construct development through the use of structural equation modeling (both covariance-based and partial least squares) as well as developing new causal modeling techniques for topics such as assessing interaction effects.