ABSTRACT By integrating theories of social learning and moral judgment, we developed a theoretical model on whether and when peers imitate employees’ unethical pro-organizational behavior in the workplace. The study, which involved 256 employees in a large manufacturing company in China, revealed that employees’ UPB positively predicted peers’ vicarious learning of UPB, with the effect strengthened by employees’ organizational tenure but weakened by peers’ deontic injustice. Moreover, the positive effect of employees’ UPB on their peers’ vicarious learning was mitigated, and (...) even turned negative when employees’ organizational tenure was low, but peers’ deontic injustice was high. (shrink)

While prior literature has widely acknowledged that the entrepreneurial environment significantly fertilizes entrepreneurship, the impact of workplace receives limited attention, and the vital role of organizations in linking social entrepreneurial environment and employee entrepreneurship has been largely ignored. Therefore, this study aims to unfold how multiple entrepreneurial environments shape employee entrepreneurship and then further reveal how such relationships vary with employees’ risk propensity. Drawn on the theoretical lens of mindsponge process, which offers an explanation of why and how organizations and (...) individuals adopt new values through the cost-benefit analysis, we proposed a research model to explain the influence mechanisms of the social entrepreneurial environment on the cost-benefit analysis of both organizations and individual employees. Specifically, given that organizations deeply embedded in the society need to balance the costs and benefits under the pressure of the social entrepreneurial environment, the social entrepreneurial environment affects the organizational entrepreneurial environment. Similarly, employees’ cost-benefit analysis under the pressure of organizational hostility will influence their entrepreneurial intentions. Through analyzing the data collected from a two-wave survey with 220 employees, we showed that organizational hostility toward employee entrepreneurship plays a mediating role between social entrepreneurial environment and employees’ entrepreneurial intentions. In addition, such mediation relationship is moderated by coworkers’ unethical behaviors during their entrepreneurship and employees’ risk propensity, which are expected to influence organizations’ and employees’ cost-benefit analysis, respectively. (shrink)

This study proposes a moderated mediation model based on deontic justice theory to investigate the impact of unethical peer behavior on employee performance. Data were collected in China through two survey studies, with two measurement points in each study. The data in study 1 were obtained from 271 employees of 17 firms, and the data in study 2 were collected from 225 employees of 9 firms. Confirmatory factor analysis was conducted to confirm the factorial validity of the measures employed in (...) the studies. The hypothesized moderated mediation model was tested using hierarchical multiple regression analysis. The results show that employee deontic justice mediates the negative relationship between unethical peer behavior and employee performance, and a stronger ethical climate tends to strengthen this indirect relationship. This study extends previous research by introducing deontic justice theory to explore the unconscious process that relates unethical peer behavior to employee performance. The theoretical and practical implications of this paper are discussed. (shrink)

This study explores how the variability of the work environment shapes the impact of educational level diversity on team creativity. By adopting an integrative framework—“status characteristics–information elaboration” model as a theoretical lens, we propose and examine the moderating roles of task and personnel variability in educational level diversity–team creativity relationship. Utilizing multiple survey data collected from 90 knowledge work teams, the empirical results indicate that educational level diversity is more conducive to team creativity when teams are confronted with more variable (...) tasks and when teams experience less frequent personnel changes. The findings of this study provide valuable insight on the conditions under which team diversity’s information potential is more likely to realize and contribute to a more context-based understanding of the relationship between diversity and creativity. (shrink)

College student entrepreneurship is a complex and dynamic process, in which the potential risks faced by entrepreneurial enterprises are interactive and diverse. The changes in risk assessment for college student entrepreneurship are also dynamic and nonlinear and are affected by many factors, which make the risk assessment process for college student entrepreneurship quite complicated. Big data analysis technology is a new product formed under the background of cloud computing and Internet technology, which has the characteristics of large data scale, multiple (...) data types, and strong data value and provides more technical support for the researches on the risk assessment algorithm for college student entrepreneurship. On the basis of summarizing and analyzing previous research results, this article expounded the research status and significance of the risk assessment algorithm for college student entrepreneurship, elaborated the development background, current status, and future challenges of big data analysis technology, introduced the basic principles of support vector machine and hierarchical analytic process, constructed a risk assessment model for college student entrepreneurship based on big data analysis, analyzed the risk factors and assessment indicators of the entrepreneurial model, proposed a risk assessment algorithm for college student entrepreneurship based on big data analysis, performed the discrimination coefficient calculation and comprehensive correlation optimization, and finally conducted a case experiment and its result analysis. The study results show that the risk assessment algorithm for college student entrepreneurship based on big data analysis can effectively realize the comprehensive management of risk factors, make full use of the value of assessment parameter data, and significantly improve the accuracy and efficiency of the risk assessment for college student entrepreneurship, providing more technical support for the researches on the risk assessment algorithm for college student entrepreneurship. The study results of this article provide a reference for further researches on the risk assessment algorithm of college student entrepreneurship based on big data analysis. (shrink)