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Identifying Factors Influencing Knowledge Collaboration Effects in Knowledge Alliances in Cambodia: A Structural Equation Model

Tapas R. Dash and Lim Siphat
CamEd Business School

ACBSP Region 10 Annual Conference
2023, pp. 7 – 16

DOI: https://doi.org/10.62458/CamEd/OAR/ACBSP/7-16

 

Abstract

Knowledge sharing between organizations helps increase the competency of employees in performing their work, but the level of knowledge collaboration might be affected by willingness to cooperate, learning abilities, knowledge attributes, and knowledge activity. To unwind this suspicion, our study used a Structural Equation Model initially composed of twenty-seven manifest or observed variables in predicting five latent or unobserved variables. The first latent variable, Willingness to Cooperate, was measured by five manifest variables. The second latent variable, Learning Ability, was measured by seven observed variables. Knowledge Attributes, Knowledge Activities, and Knowledge Collaboration Effects were measured by six, six, and three variables respectively. Based on the Confirmatory Factor Analysis, seven measurements were eliminated since their loading was less than the threshold. Maximum Likelihood Estimation Method was combined with bootstrapping technique to estimate sample parameters and establish standard errors for hypothesis testing. The empirical results of the study reveal that Learning Abilities and Knowledge Attributes have a highly significant positive impact on Knowledge Collaboration Effects. As such the empirical findings of this study have implications for both private and public sector organizations that should take initiatives to encourage members to learn better understand, and use the acquired knowledge that meets their needs, and to establish knowledge alliances with external partners.

Keywords: Knowledge collaboration effects, latent variables, manifest variables, confirmatory factor analysis, structural equation model

 

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