Simulating the impacts of mutual trust on tacit knowledge transfer using agent-based modelling approach
Authored by Hong Li, Changhong Li, Zhan Wang, Xinlan Li
Date Published: 2019
DOI: 10.1080/14778238.2019.1601506
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Model Documentation:
Other Narrative
Mathematical description
Model Code URLs:
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Abstract
Effective transfer of tacit knowledge within an organization is the key
issue to ensure its sustainable competitive advantage. However due to
the asymmetric nature of information when transferring the tacit
knowledge, there is a tendency for the moral hazard of information
hiding to emerge, which hinders the effective transfer of tacit
knowledge. According to the norm of reciprocity, we assume that the
primary motivation of suppliers to transfer tacit knowledge is that the
individuals who share their tacit knowledge trust the recipients can
reciprocate in the future. In this paper, we build a simulation model
based on trust and mutual benefit through the agent-based modeling and
simulation. From the perspective of theoretical quantification, our
simulation result shows that, the endowment effect, the initial trust
between members and the minimum honesty are very important, which
provides relevant practical guidance for organization managers in the
context of tacit knowledge transfer.
Tags
Cooperation
Performance
Reciprocity
Agent-based modelling and simulation
preferences
transmission
stability
Empirical-evidence
Population biology
Intention
Tacit knowledge
Trust and
honesty
Norm of reciprocity
Management approach