Causes of intra-organization conflict: Telecommuting triggered by the epidemic

  • Received January 4, 2022;
    Accepted April 13, 2022;
    Published May 3, 2022
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/ppm.20(2).2022.14
  • Article Info
    Volume 20 2022, Issue #2, pp. 161-174
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This work is licensed under a Creative Commons Attribution 4.0 International License

The COVID-19 pandemic has made many companies in China adopting telecommuting to continue their operations. Like traditional office work, telecommuting requires communication and cooperation to complete the work, and getting along with others means the possibility of conflict. Therefore, conflict can also occur in telecommuting. The purpose of this paper is to analyze telecommuting based on conflict process theory and build a model to test the hypothesis. Quota sampling and convenience sampling are used to conduct online questionnaires, and quantitative research methods are used to analyze the collected data and provide solutions. To this end, 282 Chinese respondents from different service industries completed online questionnaires. Through empirical analysis, the results show that telecommuting has a significant negative relationship with inter-role conflict and interpersonal conflict but has a significant positive effect on stress. In addition, interpersonal conflict, stress, and inter-role conflict have significant positive impacts on affective conflict. Similarly, interpersonal conflict and stress have significant positive effects on cognitive conflict. However, the relationship between inter-role conflict and cognitive conflict, cognitive conflict, and affective conflict is not significant. Thus, the results provide suggestions for managers on how to manage telecommuters and key factors that need to be considered. It also provides a new way for other scholars to study telecommuting.

Acknowledgments
We thank LetPub (www.letpub.com) for its linguistic assistance during the preparation of this manuscript.

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    • Figure 1. Conceptual framework
    • Figure 2. Confirmatory factor analysis model
    • Figure 3. Structural model of the study
    • Table 1. Respondents’ statistics
    • Table 2. Analysis of reliability
    • Table 2 (cont.). Analysis of reliability
    • Table 3. KMO and Bartlett’s test
    • Table 4. Rotated component matrix
    • Table 5. Results of the confirmatory factor analysis
    • Table 6. Correlation analysis
    • Table 7. Fitting index
    • Table 8. Test results
    • Table 9. Mediating effect analysis
    • Data curation
      Junjun Li
    • Formal Analysis
      Junjun Li
    • Investigation
      Junjun Li
    • Conceptualization
      Junjun Li
    • Software
      Junjun Li
    • Writing – original draft
      Junjun Li
    • Writing – review & editing
      Junjun Li
    • Methodology
      Zhongwu Li
    • Resources
      Zhongwu Li
    • Supervision
      Zhongwu Li