Increasing concerns for sustainable development have motivated the study of closed-loop supply chain network design from a multidimensional perspective. To cope with such issues, this paper presents a general closed-loop supply chain network comprising various recovery options and further formulates a multi-objective mixed-integer linear programming model considering enterprise profit and service level simultaneously. Within this model, market segmentation is also considered to meet real-world operating conditions. Moreover, an ε -constraint method and two interactive fuzzy approaches are applied to find a global optimum for this model together with the decisions on the numbers, locations, and capacities of the facilities, as well as the material flow through the network. Ultimately, numerical experiments are conducted to demonstrate the viability and effectiveness of both the proposed model and solution approaches.

Departing from past research on managers’ influence on employees’ informal leadership emergence, we explore the mechanism of how distributed leadership enhances individual leadership emergence from a cognitive perspective. Drawing upon the leadership identity construction theory and role identity theory, we theoretically developed and empirically tested a serial mediation model. It examines how distributed leadership promotes employees’ leadership emergence via individual empowerment role identity and enacted leader identity. Using a three-wave field survey from 496 subordinate–supervisor dyads (82 supervisors and 496 employees) in China, we found that empowerment role identity and enacted leader identity serially mediate the association between distributed leadership and employees’ leadership emergence. The results demonstrate the leadership identity construction process of employees’ leadership emergence under distributed leadership. The theoretical and practical implications of our findings are then discussed.

Usually, the quasi-normal fluctuations in practical applications are described via symmetric uncertainty variables, which is a common phenomenon in the manufacturing industry. However, it is relatively scarce in the literature to discuss two-fold uncertainty due to the its complexity. To deal with roughness and ambiguity to accommodate inherent uncertainties, fuzzy rough programming approaches are put forward. In this paper, we pay attention to exploring two kinds of programming problems, namely fuzzy rough single-objective programming and fuzzy rough multi-objective programming, in which objective functions and/or constraints involve fuzzy rough variables (FRV). In accordance with the related existing research of FRVs, such as the chance measure and the expected value (EV) operator, this paper further discusses the EV model, convexity theory, and the crisp equivalent model of fuzzy rough programming. After that, combined with the latest published NIA-S fuzzy simulation technique, a new fuzzy rough simulation algorithm is developed to calculate the EVs of complicated functions for handling the presented fuzzy rough programming problems. In the end, the two types of numerical examples are provided for demonstration.