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Drawing from the resource-based view (RBV), this study aims to develop a parsimonious model in the context of digital platforms that links strategic network resources (SNR) and firm performance through considering dynamic capabilities (DC) as important mediating mechanisms. In addition, we also investigate how platform monitoring shapes the relationship between SNR and DC.

This study uses the survey data from 162 firms in eastern China.

The findings indicate that both two DC dimensions (i.e., sensing and reconfiguring) significantly mediate the relationship of SNR-performance. Moreover, platform monitoring positively moderates the relationship of SNR and sensing as well as SNR and reconfiguring.

With these findings, this study advances SNR and digital platform research and provides insights into how to transform SNR into superior performance through DC.

This paper aims to investigate how perpetrators who engage in unethical pro-organizational behavior (UPB) feel and respond in the aftermath of such behavior.

This paper used a two-wave time-lagged design and collected data from 260 full-time employees working in different industries in China.

The results indicated that UPB was negatively and indirectly associated with internal whistle-blowing through shame. Perceived moral leadership weakened the effect of shame on internal whistle-blowing.

Based on affective events theory, this paper explored an integrated behavior-emotion-behavior sequence. This paper proposed that the negative emotion, shame, evoked by UPB subsequently influences the extent to which UPB perpetrators engage in internal whistle-blowing.

This study aims to solve the problem of job scheduling and multi automated guided vehicle (AGV) cooperation in intelligent manufacturing workshops.

In this study, an algorithm for job scheduling and cooperative work of multiple AGVs is designed. In the first part, with the goal of minimizing the total processing time and the total power consumption, the niche multi-objective evolutionary algorithm is used to determine the processing task arrangement on different machines. In the second part, AGV is called to transport workpieces, and an improved ant colony algorithm is used to generate the initial path of AGV. In the third part, to avoid path conflicts between running AGVs, the authors propose a simple priority-based waiting strategy to avoid collisions.

The experiment shows that the solution can effectively deal with job scheduling and multiple AGV operation problems in the workshop.

In this paper, a collaborative work algorithm is proposed, which combines the job scheduling and AGV running problem to make the research results adapt to the real job environment in the workshop.