Managerial and Decision Economics最新文献

Numerous e-commerce marketplaces are establishing their own resale platforms. Some e-commerce marketplaces gain profits from resale transactions, while others use the resale platform as a traffic pool for their new products. For example, Taobao.com places many advertisements for new products on its self-built resale platform, Idle Fish, which is called a promotion strategy. Considering the interaction between the two sources of profit, this study develops an analytical model to investigate how the e-commerce marketplace with a self-built resale platform strategically sets resale transaction commission and promotion strategy to maximize profit. The main conclusions are as follows. Firstly, the marketplace may set a low resale transaction commission when the sales price of new products is high when adopting no-promotion strategy, but it is completely reversed when the promotion strategy is used. Secondly, when the promotion strategy is adopted, the resale transactions will always decrease, but the market clearing price may increase. Lastly, the marketplace should adopt the promotion strategy when the sales price of new products is high, or the durability of products is low. Finally, we examine the impact of repurchase behaviour and the intrinsic impact of promotion on consumer valuation, the main conclusions derived from the baseline model remain valid under both extensions. This conclusion may explain why JD.com does not place any new product advertisements on its resale platform, Paipai.com, which focuses on the resale transactions of pricey products such as laptops and smart phones.

Forest ecological benefit compensation mechanisms are critical for aligning private landowner incentives with forest ecosystem service objectives. However, traditional area-based schemes in China neglect the additionality of the ecosystem services and fail to capture dynamic strategic interactions between policymakers and forest managers. To address this gap, this study develops a two-player evolutionary game model, in which the government chooses between equalization and compensation incentive compensation, whereas forest farmers decide whether to conserve. The model then analyzes the evolutionary stability of the strategy selection of the game players and explores the impacts of different parameter changes on the evolutionary stable strategy. The results show that the evolutionary stable states of the strategy selection of both parties in the game exhibit complexity due to different initial states. Increases in compensation fees, forest farmers' production revenue, and silvicultural capacity, as well as reductions in forest farmers' risk aversion coefficient, fairness preference coefficient, government free-riding coefficient, and information asymmetry coefficient, will promote the evolution of the system to the optimal stable equilibrium point. Notably, the forest farmers' conservation effort level under incentive compensation on system evolution presents a significant “inverted U-shaped” feature. This research provides a new analytical perspective and scientific basis for the optimal design of the forest ecological benefit compensation mechanism.

While the United States has imposed trade restriction policies on Xinjiang cotton from China, few studies have examined their economic impacts. This research theoretically clarifies the mechanism through which these restrictions affect the economic system and utilizes a global multiregional, multisector dynamic computable general equilibrium model to quantitatively assess their international economic impacts. Results show that the restrictions adversely impact both the Chinese and US economic growth and welfare. Initially, China's real GDP decreased by 0.0232%–0.0629%, with social welfare deteriorating by $2433–6678 million, while the US real GDP declined by 0.0202%–0.0217%, with welfare losses of $3886–4347 million. Over time, as Chinese products are substituted in the US and European markets, China's economic losses and welfare deterioration tend to intensify, while the US situation gradually improves. The Southeast Asian countries may benefit from this trade conflict, showing some economic growth and welfare improvements. The impacts vary across Chinese industries, with the textile and apparel sectors most severely affected. This paper offers a quantitative assessment of the international macroeconomic impacts of the Xinjiang cotton trade restrictions, revealing the gains and losses across countries and providing valuable empirical evidence for understanding the economic impacts of such trade restrictions.

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.