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      The Role of Digital Channels in Predicting Objective and Subjective Negotiation Outcomes

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          Abstract

          Today’s hiring and workplace communications are increasingly occurring in the digital space, a trend accelerated by the coronavirus disease (COVID-19) pandemic. In two preregistered experiments and an internal meta-analysis, we test the subjective and objective impact of two digital channels—video and synchronous text—that are popularly used in today’s workplace contexts. In doing so, we isolate the role that richness of digital channels plays in influencing negotiation outcomes while holding synchrony constant. Specifically, we predicted that negotiating via video (vs. synchronous text) will foster better integrative outcomes and improve negotiators’ subjective outcomes. Results indicated that negotiating via video, compared to synchronous text, improved subjective outcomes such as satisfaction with the negotiation process, satisfaction with negotiation outcomes, favorable impressions about one’s negotiation partner, and willingness to negotiate with the same partner again in the future. Contrary to our predictions, we did not observe significant improvements in objective negotiation outcomes (i.e., integrative outcomes) as a result of negotiating via video (vs. synchronous text), suggesting the possibility that the influence of digital channels on negotiations is primarily perceptual. We discuss implications of our findings for research on negotiations, the psychology of technology, and the future of work.

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            Bayesian inference for psychology. Part I: Theoretical advantages and practical ramifications

            Bayesian parameter estimation and Bayesian hypothesis testing present attractive alternatives to classical inference using confidence intervals and p values. In part I of this series we outline ten prominent advantages of the Bayesian approach. Many of these advantages translate to concrete opportunities for pragmatic researchers. For instance, Bayesian hypothesis testing allows researchers to quantify evidence and monitor its progression as data come in, without needing to know the intention with which the data were collected. We end by countering several objections to Bayesian hypothesis testing. Part II of this series discusses JASP, a free and open source software program that makes it easy to conduct Bayesian estimation and testing for a range of popular statistical scenarios (Wagenmakers et al. this issue).
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              Mini Meta-Analysis of Your Own Studies: Some Arguments on Why and a Primer on How

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                Author and article information

                Journal
                Technology, Mind, and Behavior
                American Psychological Association
                2689-0208
                2022
                : 3
                : 1
                Affiliations
                [1]Darden School of Business, University of Virginia
                [2]Department of Management and Entrepreneurship, Kelley School of Business, Indiana University
                Author notes
                Special Collection Editors: C. Shawn Green, Nicholas David Bowman, and Tobias Greitemeyer.
                Acknowledgments: We thank our editor, Tobias Greitemeyer, for his valuable guidance in this process. We thank the Batten Institute for Entrepreneurship and Innovation for supporting this research. We also thank Rhys Aglio, Jennie Kim, and Caitlin Boyer for their research assistance.
                Action Editor: Tobias Greitemeyer was the action editor for this article.
                Disclosures: We have no known conflicts of interest to disclose.
                Open Science Disclosures:

                The data are available at https://tinyurl.com/OSF-3gbtw.

                The experimental materials are available at https://tinyurl.com/OSF-3gbtw.

                The preregistered design is available at https://tinyurl.com/OSF-3gbtw.

                [*] Roshni Raveendhran, Darden School of Business, University of Virginia, 100 Darden Blvd, Charlottesville, VA 22903, United States raveendhranr@darden.virginia.edu
                Author information
                https://orcid.org/0000-0002-0288-057X
                https://orcid.org/0000-0001-7300-8976
                Article
                2022-30880-001
                10.1037/tmb0000060
                3f165312-cb7c-48e1-aa59-e4b1c3ad3de0
                © 2022 The Author(s)

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC-BY-NC-ND). This license permits copying and redistributing the work in any medium or format for noncommercial use provided the original authors and source are credited and a link to the license is included in attribution. No derivative works are permitted under this license.

                History
                Categories
                Technology in a Time of Social Distancing

                Education,Psychology,Vocational technology,Engineering,Clinical Psychology & Psychiatry
                technology-mediated interactions,digital medium,negotiations,COVID-19

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