IDEAS home Printed from https://ideas.repec.org/a/inm/ororsc/v11y2000i6p648-664.html
   My bibliography  Save this article

Dyadic Communication Relationships in Organizations: An Attribution/Expectancy Approach

Author

Listed:
  • Bruce Barry

    (Owen Graduate School of Management, Vanderbilt University, 401 21st Avenue South, Nashville, Tennessee 37203)

  • J. Michael Crant

    (Mendoza College of Business, University of Notre Dame, Notre Dame, Indiana 46556)

Abstract

Research in organizational communication has examined the structure and content of interaction, but has paid little attention to research traditions outside the organizational sciences that explore the social-psychological interconnections between relationship development and interaction. In this paper we draw upon and extend those traditions to develop a model of how communication relationships develop within organizational dyads. The proposed model examines organization-based communication relationships through a synthesis of theoretical perspectives on communication richness, relational communication, interpersonal attribution, and social expectancy. We also call upon precepts of structuration theory to embed these microlevel processes in an organizational context.The relational outcome in the model is “interactional richness,” a dyad-level construct that assesses the extent to which communication within the dyad is high in shared meaning. Model antecedents are aspects of interaction through which communicators reciprocally define their relationships, including relational message properties, message patterns that emerge over time, and relational perceptions. We propose that these communication properties and behaviors give rise to relationship attributions. We then incorporate processes of expectancy confirmation and violation to explain how specific communication encounters lead individuals to reformulate attributions regarding the status of a given relationship. Research propositions articulate how attribution/expectancy processes mediate between relational communication behavior and relationship development outcomes. We also develop propositions addressing how relational communication behavior is influenced by macrolevel factors, including hierarchy, structure, and culture.In a concluding section we discuss the model's potential contribution to research and practice, address its limitations, and offer recommendations for future research aimed at testing its embedded hypotheses.

Suggested Citation

  • Bruce Barry & J. Michael Crant, 2000. "Dyadic Communication Relationships in Organizations: An Attribution/Expectancy Approach," Organization Science, INFORMS, vol. 11(6), pages 648-664, December.
    • Handle: RePEc:inm:ororsc:v:11:y:2000:i:6:p:648-664
    DOI: 10.1287/orsc.11.6.648.12537
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/orsc.11.6.648.12537
    Download Restriction: no
    File URL: https://libkey.io/10.1287/orsc.11.6.648.12537?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Gerardine DeSanctis & Marshall Scott Poole, 1994. "Capturing the Complexity in Advanced Technology Use: Adaptive Structuration Theory," Organization Science, INFORMS, vol. 5(2), pages 121-147, May.
    2. Ronald E. Rice & Douglas E. Shook, 1990. "Relationships Of Job Categories And Organizational Levels To Use Of Communication Channels, Including Electronic Mail: A Meta‐Analysis And Extension," Journal of Management Studies, Wiley Blackwell, vol. 27(2), pages 195-229, March.
    3. Richard L. Daft & Robert H. Lengel, 1986. "Organizational Information Requirements, Media Richness and Structural Design," Management Science, INFORMS, vol. 32(5), pages 554-571, May.
    4. Ronald E. Rice, 1992. "Task Analyzability, Use of New Media, and Effectiveness: A Multi-Site Exploration of Media Richness," Organization Science, INFORMS, vol. 3(4), pages 475-500, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xingguang Chen & Zhentao Zhu, 2019. "Interactional Effects Between Individual Heterogeneity and Collective Behavior in Complex Organizational Systems," Computational Economics, Springer;Society for Computational Economics, vol. 53(1), pages 289-313, January.
    2. Brown, Zachariah C. & Anicich, Eric M. & Galinsky, Adam D., 2020. "Compensatory conspicuous communication: Low status increases jargon use," Organizational Behavior and Human Decision Processes, Elsevier, vol. 161(C), pages 274-290.
    3. Junichi Yamanoi & Hiroki Sayama, 2013. "Post-merger cultural integration from a social network perspective: a computational modeling approach," Computational and Mathematical Organization Theory, Springer, vol. 19(4), pages 516-537, December.
    4. Chung, Minjee & Ko, Eunju & Joung, Heerim & Kim, Sang Jin, 2020. "Chatbot e-service and customer satisfaction regarding luxury brands," Journal of Business Research, Elsevier, vol. 117(C), pages 587-595.
    5. Narda R. Quigley & Paul E. Tesluk & Edwin A. Locke & Kathryn M. Bartol, 2007. "A Multilevel Investigation of the Motivational Mechanisms Underlying Knowledge Sharing and Performance," Organization Science, INFORMS, vol. 18(1), pages 71-88, February.
    6. Lalin Anik & Lara B Aknin & Michael I Norton & Elizabeth W Dunn & Jordi Quoidbach, 2013. "Prosocial Bonuses Increase Employee Satisfaction and Team Performance," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-8, September.
    7. Cam Caldwell & Brian Davis & James Devine, 2009. "Trust, Faith, and Betrayal: Insights from Management for the Wise Believer," Journal of Business Ethics, Springer, vol. 84(1), pages 103-114, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Meissner, Jens O., 2005. "Relationship Quality in the Context of Computer-Mediated Communication - A social constructionist approach," Working papers 2005/15, Faculty of Business and Economics - University of Basel.
    2. Rebentisch, Eric., 1997. "The link between technology complexity and communication complexity in international technology transfer," Working papers 158-97. Working paper (Sl, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    3. Jonathan W. Palmer, 2002. "Web Site Usability, Design, and Performance Metrics," Information Systems Research, INFORMS, vol. 13(2), pages 151-167, June.
    4. Koo, Chulmo & Wati, Yulia & Jung, Jason J., 2011. "Examination of how social aspects moderate the relationship between task characteristics and usage of social communication technologies (SCTs) in organizations," International Journal of Information Management, Elsevier, vol. 31(5), pages 445-459.
    5. Brian E. Mennecke & Joseph S. Valacich & Bradley C. Wheeler, 2000. "The Effects of Media and Task on User Performance: A Test of the Task-Media Fit Hypothesis," Group Decision and Negotiation, Springer, vol. 9(6), pages 507-529, November.
    6. Kurtzberg, Terri R. & Naquin, Charles E. & Belkin, Liuba Y., 2005. "Electronic performance appraisals: The effects of e-mail communication on peer ratings in actual and simulated environments," Organizational Behavior and Human Decision Processes, Elsevier, vol. 98(2), pages 216-226, November.
    7. Linda Klebe Treviño & Jane Webster & Eric W. Stein, 2000. "Making Connections: Complementary Influences on Communication Media Choices, Attitudes, and Use," Organization Science, INFORMS, vol. 11(2), pages 163-182, April.
    8. Ofir Turel & Catherine E. Connelly, 2012. "Team Spirit: The Influence of Psychological Collectivism on the Usage of E-Collaboration Tools," Group Decision and Negotiation, Springer, vol. 21(5), pages 703-725, September.
    9. Alan R. Dennis & Susan T. Kinney, 1998. "Testing Media Richness Theory in the New Media: The Effects of Cues, Feedback, and Task Equivocality," Information Systems Research, INFORMS, vol. 9(3), pages 256-274, September.
    10. Spivack, April J. & Woodside, Arch G., 2019. "Applying complexity theory for modeling human resource outcomes: Antecedent configurations indicating perceived location autonomy and work environment choice," Journal of Business Research, Elsevier, vol. 102(C), pages 109-119.
    11. Gary E Bolton & Claudia Loebbecke & Axel Ockenfels, 2007. "How Social Reputation Networks Interact with Competition in Anonymous Online Trading: An Experimental Study," Working Paper Series in Economics 32, University of Cologne, Department of Economics.
    12. Yinan Wang & Yingchong Wang, 2022. "Developing Creative Leadership in the Use of Digital Communication Tools: A Psychological Perspective," Sustainability, MDPI, vol. 14(19), pages 1-20, September.
    13. Sumita Raghuram & Philipp Tuertscher & Raghu Garud, 2010. "Research Note ---Mapping the Field of Virtual Work: A Cocitation Analysis," Information Systems Research, INFORMS, vol. 21(4), pages 983-999, December.
    14. Kelly Burke & Laku Chidambaram & Kregg Aytes, 2002. "Do Some Things Change Faster than Others? The Dynamics of Behavioral Change in Computer-Supported Groups," Group Decision and Negotiation, Springer, vol. 11(4), pages 293-309, July.
    15. Martha L. Maznevski & Katherine M. Chudoba, 2000. "Bridging Space Over Time: Global Virtual Team Dynamics and Effectiveness," Organization Science, INFORMS, vol. 11(5), pages 473-492, October.
    16. Li, Shenxue & Easterby-Smith, Mark & Lyles, Marjorie A. & Clark, Timothy, 2016. "Tapping the power of local knowledge: A local-global interactive perspective," Journal of World Business, Elsevier, vol. 51(4), pages 641-653.
    17. Terri L. Griffith & John E. Sawyer, 2006. "Supporting Technologies and Organizational Practices for the Transfer of Knowledge in Virtual Environments," Group Decision and Negotiation, Springer, vol. 15(4), pages 407-423, July.
    18. Bernard C. Y. Tan & Kwok-Kee Wei & Richard T. Watson & Danial L. Clapper & Ephraim R. McLean, 1998. "Computer-Mediated Communication and Majority Influence: Assessing the Impact in an Individualistic and a Collectivistic Culture," Management Science, INFORMS, vol. 44(9), pages 1263-1278, September.
    19. Jeanine Warisse Turner & N. Lamar Reinsch, 2010. "Successful and unsuccessful multicommunication episodes: Engaging in dialogue or juggling messages?," Information Systems Frontiers, Springer, vol. 12(3), pages 277-285, July.
    20. Eun-Ho Kim & Dongho Yoo & Sun-Jae Doh, 2021. "Self-construal on brand fan pages: the mediating effect of para-social interaction and consumer engagement on brand loyalty," Journal of Brand Management, Palgrave Macmillan, vol. 28(3), pages 254-271, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ororsc:v:11:y:2000:i:6:p:648-664. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.