Managerial and Decision Economics最新文献

Effective near-miss reporting is important for achieving high reliability in safety management. To enhance the effectiveness of near-miss reporting, this paper examines the dynamic evolution of stakeholders' decision-making behaviors using coal mines as a case study. A tripartite evolutionary game model is developed, involving enterprises, management, and employees, based on prospect theory and mental accounting theory (PT-MA theory). Stability analysis and simulations under varying parameters yield the following insights: (i) A higher initial probability of active decision-making promotes positive strategy evolution, with sensitivity ranked as enterprise $�>$ management $�>$ employee. (ii) Near-miss reporting is mainly driven by cost considerations, with stakeholders' sensitivity to cost changes ranked as employee $�>$ management $�>$ enterprise. Lowering the perceived cost of active strategies and raising that of passive strategies encourages active decisions. (iii) A combined reward–punishment strategy is more effective than either alone in motivating employees and management. (iv) The psychological stress experienced by management when the enterprise adopts passive strategies is greater than that employees feel in response to management's passive strategies. Reducing such stress facilitates active strategy evolution. (v) Modifying reference points for perceived benefits and costs, reducing risk preference, and increasing sensitivity to loss aversion can facilitate active strategy evolution. This research offers practical implications for improving near-miss reporting management in the coal mine industry, including optimizing incentive mechanisms, implementing role-specific psychological interventions, and adjusting cost–benefit perceptions. These insights may also be applicable to other high-risk industries facing similar challenges, contributing to more effective and sustainable safety management practices.

The open-source platform emerges as a complex and dynamic system, shaped by the intricate interplay and interdependence of a diverse array of stakeholders. Existing studies mostly focus on micro-level aspects such as individual open-source entities, projects, or platforms, and rarely rise to the ecosystem level to conduct dynamic evolutionary analysis on the governance mechanisms of highly heterogeneous stakeholders within open-source platforms. This paper, therefore, constructs an evolutionary game model based on innovation ecosystem theory, with platform governors and complementors as the primary players. By quantifying the strategic choices of both parties under different profit scenarios, the study explores the system's stability characteristics. Additionally, MATLAB simulation analysis is used to examine the impact of parameter changes on the evolution of strategies and paths, elucidating the evolutionary stability of stakeholder strategies within the open-source platform ecosystem (OSPE). The study finds that: First, incentives for complementors can effectively drive their active contributions, but continuous strong stimuli will instead cause governors to strategically reduce their intervention inputs. Second, the exposure of potential risks from governance inaction has a corrective effect on the behaviors of both parties: It not only forces governors to turn to active performance of duties to safeguard the long-term value of the OSPE, but also prompts complementors to accelerate behavioral standardization based on direct constraint rules. Third, a high level of open knowledge sharing can create the dual dividends of a systematic reduction in contribution costs and a multiplier effect on the value of the governance ecosystem. This paper unpacks the governance mechanism from the stakeholders' perspective, providing a clearer understanding of the evolutionary dynamics of OSPE and practical insights for formulating its governance mechanisms.

This study investigates how digital transformation affects enterprise innovation from a peer effect perspective, considering customer concentration, managerial ability, and operational risk as mediating variables. This study utilizes A-share listed enterprises as research samples. An unbalanced panel dataset spanning from 2011 to 2023 was constructed to explore the impact of the peer effect of digital transformation on enterprise innovation. The results suggest that the peer effect of digital transformation significantly promotes enterprise innovation. The study emphasizes the significance of decreasing customer concentration and operational risk as key pathways through which digital transformation influences enterprise innovation. Furthermore, it was discovered that industry competitive intensity positively moderates the connection between peer digital transformation and enterprise innovation. The heterogeneity test reveals that peer digital transformation has a more significant impact on enhancing the innovation of SOEs and enterprises in central regions. These empirical findings offer valuable insights for policymakers seeking to foster the coordinated development of digital transformation and enterprise innovation. This study expands the research scope of digital transformation and enterprise innovation by adopting a peer effect perspective. The findings elucidate how peer digital transformation drives enterprise innovation, offering empirical evidence for enterprises seeking to enhance innovation from a digital transformation standpoint.

Against the backdrop of profound economic restructuring, the establishment of patent-intensive industrial cluster networks is of great significance for enhancing China's overall innovation capacity and propelling industrial transformation and upgrading. This study takes the biopharmaceutical industry as an example, utilizing patent data spanning from 2012 to 2023 to construct an innovation network. It delves into the spatial distribution characteristics of patent-intensive industrial clusters at the urban scale. Furthermore, a temporal exponential random graph model (TERGM) is employed to uncover the multidimensional dynamics driving network evolution. The findings reveal that cities ranking high in various centrality measures within the biopharmaceutical industrial cluster network exhibit stability, with a notable concentration in the eastern coastal regions. Spatial correlations within the cluster network are primarily driven by spillover effects across sectors. The biopharmaceutical industrial cluster network demonstrates positive mediation and transitive effects, accompanied by negative agglomeration effects. Factors such as economic development, the level of openness, heterogeneity in administrative hierarchies, government support levels, and multidimensional proximity among cities all contribute to driving the formation and evolution of the network. The conclusions broaden the application of innovation network theory within the specific context of China and provide a scientific basis for decision-making in fostering patent-intensive industrial clusters.

Motivated by the global sustainability imperative, this paper reveals that ESG committees boost corporate sustainable performance in Chinese A + H firms by balancing conforming legitimacy (norm adherence) and strategic legitimacy (stakeholder engagement). Ownership structure moderates outcomes, and effectiveness rises in firms prioritizing core stakeholders or having gender-diverse boards but diminishes with strong internal controls. The findings advance legitimacy theory by integrating institutional and strategic perspectives. Practical guidance urges firms to establish ESG committees, tailor strategies to ownership contexts, and leverage board diversity. Policymakers should refine guidelines for emerging markets balancing state and market forces.

Firms frequently participate in alliances to develop new products cooperatively. Knowledge sharing in a cooperative development alliance positively affects product innovation. However, sharing knowledge also creates technology leakage and misappropriation risks that constrain partners' willingness to use their technology for the alliance's goals. How to alleviate partners' concerns about these hazards arouses wide concern among academics and managers. We develop a two-stage model to explore the operations of two strategies: a commitment that restricts knowledge sharing and an exclusive codevelopment commitment. These alleviate partners' concerns about these knowledge-sharing risks. We show that if the focal firm chooses to restrict the knowledge-sharing level of the alliance, the alliance's firms will increase their use of their proprietary technology to improve the new product performance. The focal firm can mitigate the hazards of knowledge sharing by committing not to cooperate with rivals of the follower firm, but doing so does not always benefit the focal firm. Our results show that the focal firm may prefer to change its partner in the second stage if its development desire and capability are small. We also show that firms prefer to cooperate with partners whose development capacities and desires are similar to their own.

This paper investigates the impact of typhoon disasters on the operational performance of regional commercial banks in China. To better quantify disaster severity, we construct a novel, ex ante typhoon damage index by combining detailed typhoon trajectory data with a parametric wind-field model and a potential damage function. Applying this measure to a panel of 477 banks from 2014 to 2023, we find that typhoon strikes cause large and persistent declines in the deposit and loan ratios of coastal banks, whereas inland banks primarily experience deposit declines. In response to the resulting liquidity pressures, affected banks increase their reliance on wholesale funding. A heterogeneity analysis further reveals that rural, small-sized, and low-capital banks are disproportionately vulnerable. We trace these impacts to the real economy, finding that they are transmitted through significant disruptions to the sales, productivity, and supply chain resilience of firm borrowers. These findings underline the critical need for targeted climate risk management to strengthen the financial system's resilience against climate shocks.

The recycling of used products and the reuse of resources have emerged as prominent themes in current sustainability discussions. Although the influence of policy incentives and the behaviors of responsible entities are frequently cited, their effectiveness in enhancing recycling practices among various stakeholders remains ambiguous. Therefore, this study examines a closed-loop supply chain system consisting of a manufacturer, a retailer, and/or a third-party recycler. By incorporating a reward-penalty mechanism, we aim to assess the impact of the manufacturer's recycling altruistic behavior on recycling efficiency, considering scenarios involving retailer recycling and third-party recycling. Moreover, this research explores how the reward-penalty mechanism and the manufacturer's recycling altruistic behavior influence the choice of recycling channels. Through theoretical analysis of four game models and subsequent numerical experiments, our findings reveal that (1) incorporating a reward-penalty mechanism, coupled with the manufacturer's recycling altruistic behavior, not only enhances the recycling rate but also lowers retail prices and boosts consumer surplus. (2) The effectiveness of various recycling channels in achieving substantial recycling outcomes is significantly influenced by both the government's reward-penalty mechanism and the manufacturer's recycling altruistic behavior, which, in turn, affect the manufacturer's decisions regarding recycling outsourcing. (3) At lower levels of reward-penalty intensity or recycling altruistic coefficient, retailer recycling can improve the recycling rate, enhance profits for all involved parties, and advance social welfare, albeit at the expense of higher environmental impact. Conversely, at higher levels of these factors, third-party recycling becomes more advantageous for both corporate and social development.

In this paper, we extend the differentiated product duopoly model of Singh and Vives (1984) to a setting where the firms are asymmetric in terms of their marginal costs, and the more efficient firm has the option to license its technology to its rival before they engage in price competition, quantity competition, or mixed competition. Our numerical computations reveal that the unique subgame perfect Nash equilibrium of the duopolistic competition game with licensing involves price competition when the products are complements. However, when the products are substitutes, either price or quantity competition can emerge in an equilibrium, depending on the level of cost asymmetry and the degree of substitution. Furthermore, when the products are complements, consumers and the firms benefit from licensing. In contrast, when the products are substitutes, licensing can benefit both consumers and the firms only if the degree of substitution and cost asymmetry are sufficiently low. Our results complement the earlier findings in Niu (2008), where the timing of licensing and contract decisions differs from ours.