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Research on the Impact of Temporary Workers’ Psychological Contract Fulfillment on Task Performance in the Sharing Economy

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Business Intelligence and Information Technology (BIIT 2021)

Abstract

In the sharing economy, temporary workers have a sense of isolation, which leads to the weak cognition of the organization and the unpredictability of job performance. Based on Social Exchange Theory, taking temporary workers in the sharing economy as the research object, this paper examines the influence of psychological contract fulfillment perceived by employees on task performance. It explores the mediating effect of organizational identification and the moderating effect of length of service. The structural equation model is used to analyze 572 shared temporary workers’ questionnaires. The results indicate that employees perceived psychological contract fulfillment positively influences task performance, and transactional psychological contract fulfillment directly influences task performance. Organizational identification plays a mediating part in the path of psychological contract fulfillment’s influence on task performance, and relational contract fulfillment has a mediating effect on task performance in the mediating mechanism. The fulfillment of transactional psychological contracts perceived by employees with shorter service has a greater influence on organizational identity. The fulfillment of relational psychological contracts perceived by employees with longer service greatly influences task performance.

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Acknowledgment

This research was supported by the grants of Shaanxi collaborative innovation support project No. 2019KRM149 and Shaanxi Provincial Department of Education project No. 20JK0230.

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Appendix

Appendix

The Questionnaire used in this study (Fig. 4).

Fig. 4.
figure 4

Research on the scale.

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Zhang, G., Tian, L., Xie, J. (2022). Research on the Impact of Temporary Workers’ Psychological Contract Fulfillment on Task Performance in the Sharing Economy. In: Hassanien, A.E., Xu, Y., Zhao, Z., Mohammed, S., Fan, Z. (eds) Business Intelligence and Information Technology. BIIT 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 107. Springer, Cham. https://doi.org/10.1007/978-3-030-92632-8_65

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