This study aims to evaluate the effects of leader-member exchange (LMX) on job and life satisfaction among nurses in China and to examine the mediating effect of individual and collaborative job crafting between LMX and job and life satisfaction. The study recruited 263 nurses who worked in hospitals in Zhejiang province, China. A set of self-administered questionnaires were used to measure the variables of LMX, job crafting, job and life satisfaction. The data was analyzed using the partial least square structural equation modelling (PLS-SEM). The results reveal that LMX has a significant positive influence on job crafting and job satisfaction. Collaborative job crafting has a significant positive influence on the job satisfaction of nurses, whereas individual job crafting does not. Moreover, LMX will affect job satisfaction and life satisfaction through a partial mediating effect of both individual and collaborative job crafting. Finally, the article discusses the academically and practical implications, and also provide some suggestions and directions for the future research.

Carbon cap-and-trade and carbon offsets are common and important carbon emission reduction policies in many countries. In addition, carbon emissions from business activities can be effectively reduced through specific capital investments in green technologies. Nevertheless, such capital investments are costly and not all enterprises can afford these investments. Therefore, if all members of a supply chain agree to share the investments in the facilities, the supply chain can reduce carbon emissions and generate more profit. Under carbon cap-and-trade and carbon tax policies, this study proposes a production–inventory model in which the buyer and vendor in the integrated supply chain agree to co-invest funds to reduce carbon emissions. We planned to integrate production, delivery, replenishment, and technology to reduce carbon emissions so as to maximize the total profit of the supply chain system. Several examples are simulated and the sensitivity analysis of the main parameters is carried out. The optimal solutions and joint total profit under various carbon emission policies are also compared. The future carbon emission control trend is expected to enable companies to share risks by co-investing and developing sustainable supply chains.

Due to the effect COVID-19 epidemic, promoting green consumption is now a key marketing strategy in the hospitality and tourism industry. As it is vital green hotels predict their customers’ visit intention, this study attempts to discover the factors affecting Taiwan’s Z-generation tourists’ green hotel visit intention using an extended theory of planned behavior [including personal moral norms (PMN) and environmental concern (EC)]. Data were gathered from 296 Z-generation tourists via an online survey, which was subsequently analyzed using partial least squares structural equation modeling. The results evidence that Z-generation tourists’ attitude, subjective norms, (SN) and perceived behavioral control positively and significantly influence their green hotel visit intention, with attitude being the most significant factor. Moreover, the mediation model analysis indicates Z-generation tourists’ attitude toward green hotels mediates the relationships between PMN, SN, EC, and visit intention. This study provides new insights into tourists’ green hotel visit intention and emphasizes the importance of attitude in the formation of intention.

In this paper, the study of a sustainable production–inventory model with price and advertisement dependent on demand considering carbon emission reduction technology is investigated. The aim of this paper is to determine the optimal appropriate pricing, advertising, production, inventory, and capital investment decisions under various carbon emission policies to maximize the joint total profit of a multi-stage supply chain system. Various theoretical results and an algorithm are provided to verify and obtain the optimal solution of the problem. Further, the model is verified by numerical examples, and the robustness check of parameter variation is also analyzed. Finally, some management implications for decision makers are drawn from numerical examples. In summary, this study puts forward more realistic modeling hypothesis, which is beneficial to the academic research, and the research results can provide relevant decision makers with a model for managing a sustainable supply chain.