Abstract:Artificial Intelligence is profoundly affecting Management Sciences research. From a broader perspective of Management Sciences, this paper develops a “paradigm elements-research process-emerging issues” framework, explains the shifts in light of research scopes, research objects, research assumptions, and research methods, and examines AI-enabled pathways across observation, theory building, hypothesis generation, simulation experiments, and hypothesis testing, along with related mechanisms and boundary conditions. Finally, it discusses key research subjects including human-computer interaction biases and large model-based decision simulation, as well as other directions of future exploration.This paper argues that AI empowering Management Sciences research represents a human-AI collaborative paradigm evolution constrained by data conditions, task structures, theoretical boundaries, interpretability, and external validity.

Abstract:This paper focuses on the key frontier research achievements of the Management Science and Engineering discipline in China from 2021 to 2025. Based on 9 864 papers published in 46 international frontier journals, and including 197 related papers from 7 world-leading comprehensive journals, this study systematically examines the current research progress and hot trends in the Management Science and Engineering discipline in China by using bibliometric and text mining methods. The research results show that: First, the research level and scientific research competitiveness of the Management Science and Engineering discipline in China have steadily improved, and the research results are closely related to the local context; Second, The National Natural Science Foundation of China has become the core funding agency for the research results of the Management Science and Engineering discipline in China; Third, the research hotspots in the Management Science and Engineering discipline in China focus on system risks, and the methodology shows a trend of integration with artificial intelligence.

Abstract:In the past two decades, the environmental, social, and governance (ESG) framework has evolved from a peripheral aspect of corporate social responsibility into a core organizational paradigm, attracting growing attention from investors, policymakers, managers, and scholars. This study reviews the origins of ESG both in practice and academic discourse, and explores the institutional logic that have driven its global diffusion. Building on this foundation, the study identifies key drivers behind ESG development and examines its associated risks and challenges, including inconsistent measurement standards, rent-seeking, politicization, and greenwashing. It provides a comprehensive analysis of the effectiveness and limitations of ESG in advancing corporate sustainability at the micro level. Additionally, drawing on macroeconomic and industry-level cases, the study evaluates the potential contributions and practical constraints of ESG in promoting economic growth and social welfare at the macro level. Finally, based on recent advancements in management, finance, and public policy research, this study outlines prospective trajectories for the evolution of ESG research and practice: moving from responsibility-based narratives toward institutional logic, ESG is no longer merely about “doing the right thing.”

Abstract:Although mega-infrastructure projects play a pivotal role in reshaping regional economic landscapes, its underlying mechanisms in influencing firms’ micro-level technology transaction behaviors remain unclear. Leveraging the construction of China’s high-speed rail (HSR) network as a quasi-natural experiment, this study investigates how HSR accessibility differentially shapes firms’ technology transfer patterns. Using patent transaction data from Chinese listed firms between 2000 and 2023, this paper finds that HSR connectivity significantly promotes patent licensing: A relational form of technology transfer; While exhibiting no significant effect on patent assignment. This pattern suggests that HSR’s influence is most salient in contexts requiring sustained collaboration. The results indicate that the core mechanisms driving this result stem from HSR-induced spatial-temporal convergence: it mitigates ex ante information asymmetry regarding technological quality and reduces ex post coordination and monitoring costs during technology commercialization. Further analysis reveals that the effect of HSR is stronger among firms with low innovation reputation, limited market attention, and those in less competitive industries, indicating a substitutive relationship between HSR connectivity and formal market signals. Moreover, the promoting effect is more pronounced for firms characterized by low technological complexity, private ownership, and locations outside major innovation clusters, underscoring HSR’s distinctive role in facilitating tacit knowledge exchange and informal collaboration. By integrating transaction type heterogeneity and transaction cost perspectives, this study uncovers a novel pathway through which mega-infrastructure projects shape innovation diffusion, offering new theoretical and practical insights into how transportation revolutions enable technology markets.

Abstract:As China’s platform antitrust regulation transitions toward normalized governance, coercive exclusivity practices have been effectively curbed. However, platforms may continue to compete for exclusive listing agreements with superstar sellers through voluntary bidding mechanisms, a form of competition inadequately studied by scholars and regulators. To analyze platform competition over non-coercive exclusive listing agreements and its implications, this paper develops a four-stage game-theoretic model in which two asymmetric two-sided platforms compete for exclusive listing agreements with a superstar seller. Competition occurs through voluntary bidding rather than coercive measures, with target sellers retaining autonomy over multi-homing or single-homing decisions. The paper finds that: 1) Exclusive agreement competition disrupts the “winner-takes-all” equilibrium, enabling vertically disadvantaged platforms to prevail through superior horizontal compatibility with superstar sellers; 2) Exclusive listing agreements with superstar sellers possessing sufficient influence over consumers can simultaneously enhance consumer surplus and ordinary seller welfare; 3) When platforms exhibit comparable competitive capabilities, exclusive agreement competition generates a Pareto-inefficient “prisoner’s dilemma”. These findings provide theoretical insights into platform competition for exclusive listing agreements and platform regulatory policy-making.

Abstract:As mobile payment becomes increasingly widespread, promotional activities play a crucial role in driving its adoption. In a two-sided market involving both merchants and customers, mobile payment providers offering promotional discounts to users also significantly impact merchants. This study analyzes five months of sales data from 40 chain convenience stores to examine the effect of user-targeted promotions by mobile payment providers on store sales performance. During this period, Tencent launched a WeChat Pay promotion offering random discounts to users who made payments on Tuesdays. Based on this, the study applies the Difference-in-Differences (DID) method to analyze the impact of WeChat Pay’s random discount promotion on merchants’ sales performance. The results indicate that random discount promotions have a significant positive impact on merchants’ sales performance on the day of the promotion. Further analysis rules out the possibility that this sales growth is due to consumers delaying or advancing their purchases. Additionally, the study examines the dynamic effects of the promotion, investigating how the impact of the promotion evolves over time to address the question of the optimal promotional duration for merchants. Finally, the study finds that the proportion of payments made using WeChat Pay moderates the effect of the promotion on sales performance.

Abstract:Online reviews have a profound impact on firms’ pricing and quality strategies. However, consumer self-selection bias may distort review information and mislead firm’s decisions. This paper incorporates consumer self-selection into the review-generation process and develops a two-period dynamic model to study firms’ optimal product line design and pricing decisions. It compares three informational environments: No reviews, objective (unbiased) reviews, and reviews subject to positive or negative self-selection bias. The analysis yields several insights. First, objective reviews do not affect initial product introduction decisions, whereas biased reviews systematically distort firms’ subsequent choices: Negative bias induces higher quality and lower prices, while positive bias leads to the opposite response. Second, optimal product line strategies depend jointly on the direction and magnitude of review bias, product experience quality, and production costs. Third, the welfare effects of online reviews are non-monotonic. Depending on cost and bias conditions, reviews may either improve both firm profits and consumer surplus or exacerbate conflicts between them. A win-win outcome arises only when negative bias is sufficiently weak or when bias is positive and production costs are relatively high. Overall, this study clarifies how biased online reviews reshape firms’ dynamic product decisions and offers insights into pricing, quality iteration, and review management.

Abstract:Carbon neutrality requires joint efforts of society. Consumer subsidies are an important way to spread the concept of green consumption. Point-based green consumption reward programs, which are being piloted in many cities, represent a greenness subsidy scheme. Under this new subsidy scheme, the amount of subsidy is calculated based on the greenness of the product consumed—The greener the product is, the higher the subsidy. This is different from the traditional lump-sum subsidy scheme where the government determines the amount of subsidy that is not related to the greenness of the product. This paper constructs a game-theoretic model with endogenized green product development and pricing decisions. It proposes optimal subsidy strategies under lump-sum and greenness subsidy schemes and compares their economic and environmental consequences. The results show that both schemes can encourage firms to exert more efforts in green product development, and greenness subsidy is effective in a wider range of contexts. When optimizing a subsidy scheme, it is important to note that consumer subsidies can increase carbon emissions by stimulating overconsumption; however, a large market size and strong consumer preference for green products can mitigate this adverse effect. From the perspective of scheme selection, when the government budget is extremely low or high, the greenness-based subsidy performs better in terms of carbon reduction. When the budget is moderate, the lump-sum subsidy scheme with a proper subsidy standard can achieve higher emission reduction. These findings provide theoretical support for governments in designing green consumption subsidy schemes.

Abstract:To promote positive values and foster a good social atmosphere, all walks of life launch some benchmark selection activities, such as “the most beautiful doctor” and “the most beautiful teacher”. These role models (or benchmarks) tend to be a minority among numerous candidates. However, traditional methods have difficulty evaluating tens of thousands of candidates and do not consider the learning relationships and specific advantages among candidates. Thus, it is difficult to realize benchmark identification by traditional methods. To reduce the workload of benchmark identification, this study proposes a social network data envelopment analysis method for identifying benchmarks from a large-scale sample, by combining the data envelopment analysis (DEA) with social network analysis (SNA). First, a pairwise evaluation process is constructed using the DEA method to explore the efficiency state of each decision-making unit (DMU) relative to another DMU, and a pairwise evaluation matrix that reflects the reference relationship between any two DMUs is obtained. Then, a social network is built based on this matrix, and role-model DMUs in a large sample are identified by comparing the in-degree centrality values of all DMUs. Next, the specific advantages of the selected benchmarks are analyzed based on the interpretation of weights in the DEA model. Finally, an experiment is carried out using online diagnosis data from 10 418 doctors across 55 departments on The Chunyu Doctor Platform to verify the social network data envelopment analysis method.

Abstract:This study investigates the impact of extreme temperature exposure on corporate bond financing costs in China. Using raster temperature data matched with the geographical locations of subsidiaries of listed firms over the period 2007-2022, this paper first estimates industry-level temperature sensitivities of corporate profitability by season and derives industry-quarter-specific extreme temperature thresholds. Based on these thresholds, it constructs a measure of firm-level extreme temperature exposure, defined as the annual number of days on which local temperatures exceed the corresponding threshold, and examines its effect on bond issuance yields. The results show that: 1) Extreme temperatures exert widespread and significant effects on corporate profitability, with 59.7% of industries exhibiting statistically significant temperature sensitivity; 2) Greater extreme temperature exposure is associated with higher bond financing costs, an effect driven primarily by heat and negative temperature deviations, whereas cold and positive deviations show no significant impact; And 3) The adverse effect is more pronounced for non-state-owned enterprises, non-tradable goods enterprises, and labor-intensive firms. Mechanism analyses indicate that extreme temperature exposure impairs firm performance and elevates default risk, thereby raising financing costs. It further finds that strong environmental performance mitigates this adverse effect, while firms with higher reliance on external financing are more vulnerable to temperature shocks. These findings highlight climate physical risk as a financially material factor in corporate debt markets.

Abstract:Information disclosure is at the core of the registration-based IPO reform. Using the pilot implementation of the registration-based IPO reform on China’s Growth Enterprise Market (GEM) as the research setting, this paper constructs a multi-dimensional measure of information disclosure quality based on accuracy, readability, and completeness, and employs a difference-in-differences (DID) approach to examine the impact of the registration-based system on the quality of information disclosure. The results show that, overall, the registration-based IPO reform improves the quality of IPO firms’information disclosure. A more detailed analysis reveals that the reform enhances readability and completeness but has no significant effect on the accuracy of information disclosure. The positive impacts of the reform on readability and completeness is more pronounced when underwriters have higher reputations and executives receive stronger incentives. Mechanism tests indicate that the reform influences information disclosure quality by strengthening regulatory constraints and enhancing pricing incentives. Further analysis demonstrates that, by improving information disclosure quality, the reform effectively enhances market pricing efficiency and increases IPO firms’long-term post-listing returns. This study contributes to the literature on the effects of implementing the registration-based system implementation and provides empirical evidence and policy insights for further optimizing the reform.

Abstract:Entrepreneurs on crowdfunding platforms increasingly rely on third-party certification. While prior studies on reward-based crowdfunding generally find that certification enhances performance, little is known about its role in prosocial crowdfunding, where backers are motivated by both financial returns and altruistic rewards. As a result, third-party certification may exert heterogeneous effects on these motivations, thereby influencing crowdfunding performance. This study integrates a theoretical model with empirical analysis to examine the mechanisms through which third-party certification affects prosocial crowdfunding performance. First, a theoretical model that incorporates backers’ financial and altruistic motivations is developed to analyze creators’ certification decisions and derive testable hypotheses. Then, these hypotheses are tested using data from Kiva, a lending-based prosocial crowdfunding platform. The results show that creators who adopt third-party certification generally achieve higher crowdfunding performance. Specifically, certification strengthens backers’ financial motivations while weakening their altruistic motivations. Financial motivations positively affect crowdfunding performance, whereas altruistic motivations have a negative effect. Moreover, creators are more likely to choose certification when their projects exhibit stronger financial (quality) signals and weaker altruistic signals.

Abstract:It has always been a thorny dilemma for family entrepreneurs that they cannot strike a proper balance between family and business, yet existing studies have failed to provide convincing evidence to address it. Drawing on the dual-goal perspective of family firms, this paper investigates the interactive effects of business-oriented and family-oriented strategic behaviors on firm performance. Using data from the China Private Enterprise Survey Database, this paper finds that: First, the time invested by family entrepreneurs in work and in family significantly enhance firm performance, yet the two exhibit heterogeneous interaction effects in different contexts. Specifically, in family firms controlled by female owners, start-up family firms, and those operating in highly competitive market environments, prioritizing business and prioritizing family demonstrate a substitution effect. In contrast, in family firms controlled by male owners, mature family firms, and those operating in low-competition market environments, the two show a complementary effect. Second, there exists an optimal work-family time allocation ratio that maximizes the net profit of the enterprise. Furthermore, in comparison with family firms controlled by male owners, mature family firms, and those in low-competition market environments, the optimal work-family time allocation ratio is relatively higher in family firms controlled by female owners, start-up family firms, and those in highly competitive market environments. This study expands the analytical framework of work-family relationship research and provides practical implications for family entrepreneurs on how to balance work and family responsibilities.

Abstract:In a double-hazard scenario consisting of a public health event and a natural disaster, the public spreads a particular category of compound rumor involving both of these public safety events, referred to as compound rumors involving pandemics and natural disasters. To prevent the spread of compound rumors involving pandemics and natural disasters, it is important to release and spread debunking information specifically targeting such compound rumors. Recently, the coupling effects of different disasters in terms of information dissemination have been confirmed. This study speculates that the spread of debunking information targeting compound rumors involving pandemics and natural disasters may similarly be influenced by such coupling effects, resulting in an amplification phenomenon to reach a broader audience, thereby aiding in alleviating the negative impacts of rumors. This study establishes a debunking information spread model applicable to double-hazard scenarios consisting of public health events and natural disasters, aiming to describe the spread process of debunking information in such contexts. Furthermore, this study conducts empirical research using a real double-hazard case consisting of the earthquake and the public health event that occurred in Sichuan, China, in 2022. It demonstrates the amplification phenomenon in the spread of debunking information targeting compound rumors involving pandemics and natural disasters. In addition, it validates the effectiveness of the new proposed model. This study provides guidance for rumor management, facilitating the more effective dissemination of debunking information to mitigate the harm caused by rumors.

Abstract:Commodity futures prices exhibit high nonlinearity, non-stationarity, and volatility. The sentiment polarity extracted from news texts has significantly improved the timeliness and accuracy of forecasting. However, massive news texts contain a significant amount of noise information, which severely impacts the stability of forecasting. Therefore, sentiment analysis is conducted on news texts related to futures prices, and a weighted double-well potential surface support vector regression (WDWPS-SVR) model is proposed to improve prediction robustness for commodity futures prices. The model generates a quartic double well potential surface to conduct regression on the data in the original feature space, capturing the complex data characteristics in high-frequency data. Besides, the weight of each training sample are calculated using a weight function to assess their importance in the fitting process, reducing the interference of news texts noise in parameter estimation. The model is applied to predict soybean futures closing prices on the Dalian Commodity Exchange from 2019 to 2022. The experimental results show that: 1) Sentiment variables extracted from news texts effectively explain high-frequency price volatility, improving prediction timeliness; 2) The WDWPS-SVR model’s strong nonlinear learning ability enhances prediction accuracy by fitting fine-grained price fluctuations; 3) A weighting approach reduces noise from news texts, boosting model robustness and prediction stability.