Drawing upon positive psychology and a social relational perspective, this article examines the relationship between well‐being‐oriented human resource management (HRM) practices and employee performance. Our multilevel model examines relationships among collectively experienced well‐being‐oriented HRM practices, social climate (characterized by trust, cooperation, and shared codes and language that exist among individuals within the organization), employee resilience, and employee (in‐role) performance. Based on the two‐wave data obtained from 561 employees and their managers within 62 bank branches in 16 Chinese banks, our multilevel analyses provide support for our four hypotheses. First, we found a positive relationship between well‐being‐oriented HRM practices and social climate. Second, social climate mediated the relationship between well‐being‐oriented HRM practices and employee resilience. Third, we found a positive relationship between resilience and employee performance. Finally, employee resilience mediated the relationship between social climate and employee performance. This study is one of the first to unpack the social mechanisms through which well‐being‐oriented HRM practices increase development of resilience and subsequent employee performance at the workplace, namely through influencing group feelings of social climate.

Abstract The current increasing volatility in international politics makes it more important to understand how multinational enterprises respond to political tension between host and home countries. This paper explains the impact of macro-level bilateral political tension on micro-level strategy of multinationals in the host country. We developed the idea that patenting may be used to signal a firm’s commitment and contribution to the host country’s economy and development. Data on 437 large multinationals and interviews with senior managers of 20 foreign subsidiaries in China show that patenting local innovation does indeed help an investing firm signal its usefulness to the host country government. It can thus serve as a response to bilateral political tension. The relationship between political tension and local patenting also depends on the relative trade dependence of the home and host countries and on the investing firm’s technology level and its stake in China. The greater the dependence of an MNE and its home country government on the host country, the more likely patenting of local innovations would increase in times of bilateral political tension.

Abstract Online marketplaces such as Amazon.com represent a new channel through which multinational enterprises (MNEs) can sell their products in foreign markets, either as third-party sellers or as suppliers to the platform owner. An MNE can have better control of the marketing mix when selling directly on Amazon.com as a third-party seller, but this task entails two challenges. First is the liability of foreignness, and second is the disadvantage of competing with other products that are directly sold by the platform owner. The platform owner sets the rules of the platform and has data and algorithmic advantages, putting competitive pressure on MNEs with tighter control. Data obtained from Amazon are analyzed and reveal that maintaining control as a third-party seller predicts lower sales than being a supplier to the platform owner. However, the penalty associated with retaining control is smaller for MNEs with more host-country experience and country-of-origin advantage. These findings provide new insights into how MNEs leverage platforms such as Amazon.com to expand their global reach.

Amid an unprecedented loss of biodiversity, a pressing issue is how to improve the efficiency of conservation with limited resources and information. Collecting data on species with a small population is costly and time consuming, and many high-stakes decisions need to be made based on limited data. We develop a partially observable Markov decision processes model with unknown parameters to jointly optimize the information collection and protection efforts for threatened species. The model takes into account uncertainties about the state, detectability, and dynamics of the species, and it adaptively adjusts the efforts of surveying and protection in real time. Although the standard formulation is intractable, we exploit the structure of ecological problems to identify a hybrid belief state in low dimensions, and we reformulate the stochastic dynamic program as a piecewise deterministic optimal control problem. This enables us to obtain structural insights into the optimal policy (some are in closed form) and find a near-optimal approximate policy with performance guarantee. In certain situations, areas where the species has never been found may be more likely to contain the species than areas where it has been previously found. We also conduct a case study on the conservation of the Hainan gibbon, the rarest primate species, in which we extend the model to optimize the spatiotemporal allocation of limited resources. This paper was accepted by Chung Piaw Teo, optimization. Funding: This work was supported by the Natural Sciences and Engineering Research Council of Canada [Grant RGPIN-2019-05671]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.01753 .