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The hospitality and tourism industry strives to enhance its corporate image to speed up recovery from the effects of the COVID-19 pandemic. Since employees are service providers and practitioners of a company’s philosophy, it is vital to determine whether their work performance is conducive to corporate sustainability. This study investigated employees’ green behaviors in the hospitality and tourism industries using the behavioral reasoning theory (BRT).

This study performed fuzzy-set qualitative comparative analysis (fsQCA) and necessary condition analysis (NCA) to evaluate the formation of employees’ approach intentions for green behaviors at work.

The fsQCA and NCA results revealed complex causal recipes for the formation of high-level and low-level employees’ approach intentions for green behaviors at work and predicted that there is no single necessary condition.

The research findings have significant managerial implications for enhancing employees’ approaches to green practices in the workplace and promoting the green performance of existing tourism and hotel products.

The research findings established a theoretical basis for industry managers to activate employees’ green behaviors, providing significant references for scholars to investigate green work performance in the hospitality and tourism industry.

This paper studies the location-inventory problem (LIP) in pallet pooling systems to improve resource utilization and save logistics costs, which is a new extension of the classical LIP and also an application of the LIP in pallet pooling systems.

A mixed-integer linear programming is established, considering the location problem of pallet pooling centers (PPCs) with multi-level capacity, multi-period inventory management and bi-directional logistics. Owing to the computational complexity of the problem, a hybrid genetic algorithm (GA) is then proposed, where three local searching strategies are designed to improve the problem-solving efficiency. Lastly, numerical experiments are carried out to validate the feasibility of the established model and the efficiency of the proposed algorithm.

The results of numerical experiments show that (1) the proposed model can obtain the integrated optimal solution of the location problem and inventory management, which is better than the two-stage model and the model with single-level capacity; (2) the total cost and network structure are sensitive to the number of PPCs, the unit inventory cost, the proportion of repairable pallets and the fixed transportation cost and (3) the proposed hybrid GA shows good performance in terms of solution quality and computational time.

The established model extends the classical LIP by considering more practical factors, and the proposed algorithm provides support for solving large-scale problems. In addition, this study can also offer valuable decision support for managers in pallet pooling systems.