thesis_Daniela Noethen_print final - Jacobs University

Intergenerational Knowledge Transfer in Work Teams: A Multilevel Social Network Perspective
at different levels (e.g., individual level and team level). The integration of these two
approaches, the social network approach and multilevel analysis, has been first proposed by
Snijders, Spreen, and Zwaagstra (1995) and then been further developed by van Duijn and
colleagues (1999). According to the latter group of authors, the application of multilevel
analysis to social networks is rather simple: when the relations between actors constitute the
dependent variable, then these relations between actors are located at the first, dyadic level,
and the individual actors within which the relations are nested are located at the second,
individual level. In the case of the present research model, the teams that the individual
employees are nested in constitute a third level, i.e., the team level. Thus, by combining the
social network approach with a multilevel analysis, we have an ideal framework to test our
model, we furthermore enrich the present literature by taking a third, i.e., the team level into
account, and moreover answer the call for multilevel approaches, which include the micro
level of analysis, in knowledge transfer research (Foss et al., 2010).
3.4. Method
3.4.1. Sample and data collection
The study was conducted at three branches of a German public administration. This setting
was chosen as it presents a stable environment for employees in which experience and
knowledge can accumulate with age, other than in some rapidly changing contexts. N=349
online-questionnaires were filled out by employees and supervisors stemming from 72 teams.
Two teams which formed subunits of another, larger team in the data sample had to be
excluded to avoid the double inclusion of the same dyads. Eleven teams had to be eliminated
from the data set as only one team member each had filled out the questionnaire, and no
dyadic information could be computed. Thus, the sample resulted in N=1940 dyads,
stemming from 331 participants (283 employees, 48 supervisors) belonging to 59 teams.
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