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236 research is that we were not able to explore in depth differences among high and low self-monitors concerning the reasons for the differential pattern of results concern- ing trust brokerage. An issue for future research is to investigate whether high self- monitors are better able to exploit brokerage positions in the trust network because they perceive their network positions more accurately (Flynn et al., 2006) or whether network brokers who happen to be high self-monitors have different motivations than their low self-monitoring colleagues. Conclusion Self-monitoring theory shows itself to be valuable in understanding the patterns of leadership emergence in an actual organization in which colleagues provide each other advice and establish patterns of trust and lack of trust. The current research may help to explain why it is that high self-monitors tend to get ahead in the race for promotion and advancement in organizations (Kilduff & Day, 1994). As individuals pursue their careers, they establish reputations in the eyes of others in terms of lead- ership behaviors. If self-monitoring theory as employed in this study has an overall message, it is that to understand the structures of social behavior that emerge in organizations we must first understand the psychology of the interacting individuals. References Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Thousand Oaks: Sage. Arvey, R. D., & Murphy, K. R. (1998). Performance evaluation in work settings. Annual Review of Psychology, 49, 141–168. doi:10.1146/annurev.psych.49.1.141 Bavelas, A. (1950). Communication patterns in task-oriented groups. Journal of the Acoustical Society of America, 22, 725–730. doi:10.1121/1.1906679 Bedeian, A. G., & Day, D. V. (2004). Can chameleons lead? Leadership Quarterly, 15, 687–718. doi:10.1016/j.leaqua.2004.07.005 Berscheid, E., Graziano, W., Monson, T C., & Dermer, M. (1976). Outcome dependency: Attention, attribution, and attraction. Journal of Personality and Social Psychology, 34, 978–989. doi:10.1037//0022-3514.34.5.978 Bono, J. E., & Anderson, M. H. (2005). The advice and influence networks of transformational leaders. Journal of Applied Psychology, 90, 1306–1314. doi:10.1037/0021-9010.90.6.1306 Borgatti, S. P., Everett, M. G., & Freeman, L. C. (2002). UCINET 6 for Windows: Software for social network analysis. Harvard: Analytic Technologies. Borgatti, S. P., Jones, C., & Everett, M. G. (1998). Network measures of social capital. Connections, 21(2), 27–36. Bretz, R. D. Jr., Milkovich, G. T., & Read, W. (1992). The current state of performance appraisal research and practice: Concerns, directions, and implications. Journal of Management, 18, 321–352. doi:10.1177/014920639201800206 M. Kilduff et al.
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Knowledge and Networks
Titel
Knowledge and Networks
Autoren
Johannes Glückler
Emmanuel Lazega
Ingmar Hammer
Verlag
Springer Open
Ort
Cham
Datum
2017
Sprache
deutsch
Lizenz
CC BY 4.0
ISBN
978-3-319-45023-0
Abmessungen
15.5 x 24.1 cm
Seiten
390
Schlagwörter
Human Geography, Innovation/Technology Management, Economic Geography, Knowledge, Discourse
Kategorie
Technik
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