Psychological contract, organizational commitment, and knowledge innovation: A perspective of open innovation

  • Received May 14, 2021;
    Accepted June 23, 2021;
    Published June 30, 2021
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/ppm.19(2).2021.33
  • Article Info
    Volume 19 2021, Issue #2, pp. 418-432
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This work is licensed under a Creative Commons Attribution 4.0 International License

This paper explores the influence of employee perception of psychological contracts on knowledge innovation from the perspective of open innovation. The purpose is to explore internal factors affecting knowledge innovation through the construction of the SEM model and provide enterprise managers with scientific and effective management methods. The survey sample includes 312 technical and scientific research employees from 16 high-tech enterprises in China. This study adopts a quantitative research method and conducts a questionnaire survey through the subjective sampling method of improbability sampling. Through empirical analysis, the results show that a psychological contract has a significant positive effect on knowledge innovation. Among them, the relational psychological contract is more influential than the transactional one. The influence of the relational psychological contract on organizational commitment is extremely significant; the influence is more than 50%. It reflects the importance that employees attach to the employment relationship. However, the transactional psychological contract has no significant effect on organizational commitment, and organizational commitment plays a partial mediating role. Therefore, enterprises should focus on building mutual trust and friendly employment relationships and implement targeted management strategies and incentives for employees to enhance their ability of knowledge innovation.

Acknowledgment
This study is a part of the research project: Youth Foundation of Ministry of Education of China (19YJC630141).

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    • Figure 1. The conceptual framework
    • Figure 2. Confirmatory factor analysis model
    • Figure 3. Structural model of the study
    • Table 1. Demographics
    • Table 2. Descriptive statistical analysis
    • Table 3. Reliability analysis
    • Table 4. Validity analysis
    • Table 5. Confirmatory factor analysis
    • Table 6. Discriminant validity analysis
    • Table 7. Model fit index
    • Table 8. Path coefficient analysis of the structural equation
    • Table 9. Mediating effect analysis
    • Conceptualization
      Ling Peng, Zhongwu Li
    • Formal Analysis
      Ling Peng, Zhongwu Li
    • Methodology
      Ling Peng, Zhongwu Li
    • Software
      Ling Peng, Zhongwu Li
    • Resources
      Ling Peng
    • Writing – original draft
      Ling Peng
    • Writing – review & editing
      Ling Peng, Zhongwu Li
    • Supervision
      Zhongwu Li