Self-other Agreement on Influence Attempts in Virtual Organizations - Do Agents and Peers See Eye to Eye?

The aim of the study was to determine the convergent and discriminant validity of self-peer reports from three different sources on the use of influence tactics in virtual organizations. Therefore, directly related triads of network members were analyzed. First, members (agents) should describe how they try to influence a certain person (target) in the joint collaboration. Second, the defined target and another network member (non-target) described how they perceive the agent’s influence attempts. All sources rated nine types of influence tactics. The resulting multitrait-multimethod design was analyzed with 243 sets of triads using structural equation modeling (SEM). Results supported evidence for convergence of agents’ and peers’ reports on influence attempts and confirmed the multidimensionality of micro-political behavior in virtual organizations.

[1]  Alexander Artikis,et al.  Formalization of a voting protocol for virtual organizations , 2005, AAMAS '05.

[2]  E. Vance Wilson,et al.  Perceived effectiveness of interpersonal persuasion strategies in computer-mediated communication , 2003, Comput. Hum. Behav..

[3]  Gerald R. Ferris,et al.  Research in Personnel and Human Resources Management , 2018, Research in Personnel and Human Resources Management.

[4]  E. Salas,et al.  Virtual Teams: Effects of Technological Mediation on Team Performance , 2003 .

[5]  G. Blickle.  Convergence of Agents' and Targets' Reports on Intraorganizational Influence Attempts1 , 2003 .

[6]  Efrat Elron,et al.  Influence and Political Processes in Cyberspace , 2006 .

[7]  Rosanna E. Guadagno,et al.  Social Influence and Computer Mediated Communication , 2008, Handbook of Research on Computer Mediated Communication.

[8]  D. Campbell,et al.  Convergent and discriminant validation by the multitrait-multimethod matrix. , 1959, Psychological bulletin.

[9]  Rosanna E. Guadagno,et al.  Getting to know you: Face-to-face versus online interactions , 2011, Comput. Hum. Behav..

[10]  P. Bentler,et al.  Cutoff criteria for fit indexes in covariance structure analysis : Conventional criteria versus new alternatives , 1999 .

[11]  Bob Travica,et al.  Virtual organization and electronic commerce , 2005, DATB.

[12]  Rex B. Kline,et al.  Principles and Practice of Structural Equation Modeling , 1998 .

[13]  L. E. Raho,et al.  Organizational Politics:Tactics, Channels, andHierarchical Roles , 2002 .

[14]  Barbara M. Byrne,et al.  Structural equation modeling with EQS : basic concepts, applications, and programming , 2000 .

[15]  Henning Staar,et al.  Playing Virtual Power Games: Micro-Political Processes in Inter-Organizational Networks , 2011, Int. J. Soc. Organ. Dyn. IT.

[16]  B. Barry,et al.  The Medium and the Message: The Adaptive Use of Communication Media in Dyadic Influence , 2004 .

[17]  James H. Liu,et al.  Distance Matters: Physical Space and Social Impact , 1995 .

[18]  Cecilia M. Falbe,et al.  Influence tactics and objectives in upward, downward, and lateral influence attempts. , 1990 .

[19]  L. Tidwell,et al.  Computer-Mediated Communication Effects on Disclosure, Impressions, and Interpersonal Evaluations: Getting to Know One Another a Bit at a Time , 2002 .

[20]  J. Barbuto,et al.  Dispositional Effects in Intra-Organizational Influence Tactics: A Meta-Analytic Review , 2006 .

[21]  R. P. McDonald,et al.  Goodness-of-fit indexes in confirmatory factor analysis : The effect of sample size , 1988 .

[22]  Karen A. Jehn,et al.  Follow me: strategies used by emergent leaders in virtual organizations , 2009 .