2025-2026学年第二学期，安徽师范大学经济管理学院（科技商学院）师生学术研究成果丰硕，在国内外知名学术期刊发表论文49篇，其中，SSCI/SCI/CSSCI收录期刊发表论文39篇，A4类论文1篇，A5类论文2篇，B2类及以上论文19篇。学院教师在经济学、会计与金融学、工商管理学等多个学科领域取得重要进展，研究成果发表于 《International Journal of Production Economics》《ABACUS-A Journal of Accounting, Finance and Business Studies》《The British Accounting Review》《Journal of Industrial Information Integration》《Economic Modelling》《APPLIED ECONOMICS》等国际权威期刊，以及《国际金融研究》《自然资源学报》等国内权威期刊，充分展现了我院在学术研究与人才培养方面的显著成效。
汪伟忠副教授合作论文"Analyzing Barriers to AI-HI Integration for Food Loss and Waste Reduction: A Multi-Actor Study of Food Supply Chains"在运营管理领域国际权威期刊《International Journal of Production Economics》发表。该期刊为SCIE期刊，JCR分区为Q1区，中科院一区TOP期刊，学校A4类期刊，影响因子10.6。
International Journal of Production Economics
Volume 278, December 2026
Abstract：
The integration of artificial intelligence (AI) and human intelligence (HI) has significant potential to reduce food loss and waste in food supply chains (FSCs), yet its implementation is hindered by socio-technical barriers whose interdependencies and actor-specific implications remain insufficiently understood. This study analyses barriers to AI-HI integration for food loss and waste reduction from a multi-actor FSC perspective. Drawing on socio-technical systems theory, a multidimensional barrier system is developed from the literature and refined through fuzzy Delphi expert elicitation. To account for uncertainty and hesitation in expert judgments, an interval-valued T-spherical fuzzy weighted Heronian mean aggregation procedure is used to derive collective assessments. The interdependent relationships among barriers are examined using the interval-valued T-spherical fuzzy-WINGS method, and a WISP-Borda decision framework is applied to assess the performance of four representative FSC actor groups in addressing these barriers. Sensitivity and comparative analyses indicate stable and consistent results. The findings identify “privacy and cybersecurity-related concerns” as the most salient barrier to AI-HI integration and reveal heterogeneous coping capabilities across FSC actors. These results suggest that AI-HI integration for food loss and waste reduction requires differentiated strategies tailored to actor-specific constraints, digital readiness, and coordination roles. By linking socio-technical barrier interdependencies with actor-level assessment, this study offers a structured decision-aiding framework and context-bounded insights for policymakers and practitioners seeking to promote AI-HI integration in FSCs.
徐飞教授合作论文"贸易摩擦与脱虚向实：风险感知与自主创新视角"在金融学领域权威期刊《国际金融研究》正式发表。该期刊为CSSCI来源期刊、北京大学中文核心期刊、AMI核心期刊，学校A5类期刊，复合影响因子8.905。
国际金融研究
2026年第6期
摘要:
基于2011—2023年沪深A股非金融企业样本，本文深入探讨贸易摩擦对外向型企业金融化程度的影响及作用机制。研究发现：贸易摩擦冲击显著降低外向型企业金融化程度，即贸易摩擦有助于推动外向型企业“脱虚向实”。异质性分析表明，在非国有企业、高科技行业企业，以及客户分散型企业，贸易摩擦冲击对企业金融化程度的影响更显著。机制检验表明，贸易摩擦冲击通过增强管理层供应链中断风险感知、推动企业增加研发投入影响企业金融化程度。经济后果检验表明，贸易摩擦冲击通过降低外向型企业金融化程度提高企业全要素生产率，显著降低外向型企业信用销售比例，进而增加企业净商业信用占用程度，提高外向型企业实体投资规模。本文为深刻理解贸易摩擦微观效应提供新视角，为促进企业“脱虚向实”提供经验借鉴。
任以胜副教授合作论文"丽水市河权到户改革对农民收入的影响机制及其政策启示"在资源科学领域权威期刊《自然资源学报》正式发表。该期刊为CSSCI来源期刊、CSCD来源期刊、北京大学中文核心期刊，学校A5类期刊，复合影响因子10.773，位列我国资源科学类期刊第一。
自然资源学报
2026年第6期
摘要:
水资源资产产权制度是优化水资源配置、实现水生态产品价值的关键制度保障。以2014年丽水市“河权到户”改革作为水资源资产产权制度改革的一项准自然实验，基于2010—2022年的浙江省县域面板数据，利用双重差分模型、中介效应模型探究“河权到户”改革对农民收入的影响机制。研究发现：（1）基准回归结果表明，“河权到户”改革对农民收入具有显著的促进作用，且这种影响在经过安慰剂检验、排除其他政策干扰等一系列稳健性检验后仍然成立。（2）机制分析表明，“河权到户”改革通过发展优势产业、壮大农村集体经济、吸引企业进入三大路径发挥作用。（3）异质性分析表明，“河权到户”改革在地形起伏低、坡度平缓、公路里程长和旅游公共服务条件更好的地区，对农民收入的促进作用更明显。研究结果不仅为水资源资产产权制度改革提供了经验证据，也为生态优势地区通过生态资源价值转化实现共同富裕提供了政策启示。
罗昆教授合作论文"Smart accountability: leveraging AI to align ESG disclosure with practice"在会计信息系统领域国际权威期刊《International Journal of Accounting Information Systems》正式发表。该期刊为SSCI收录期刊，JCR分区为Q2区，中科院三区期刊，学校B1类期刊，影响因子4.5。
International Journal of Accounting Information Systems
Volume 56, March 2026
Abstract：
This study examines whether artificial intelligence (AI) functions as a governance mechanism that reduces the misalignment between firms’ environmental, social, and governance (ESG) disclosures and their underlying ESG performance. Using a sample of Chinese listed firms from 2011 to 2023, we find that AI adoption is associated with lower levels of ESG disclosure-performance misalignment, encompassing both the overstatement and understatement of ESG performance. Cross-sectional analyses further indicate that the association is more pronounced among large firms, non-state-owned enterprises, and firms operating in capital-intensive and technology-driven industries. Additional analysis shows that AI adoption is linked to improved access to green credit, with this relationship mediated by reductions in ESG disclosure-performance misalignment. Overall, this study contributes to the literature on AI and ESG by highlighting AI, particularly learning-based AI, can function as a governance-enabling technology that enhances the alignment between ESG disclosures and actual practices. Our study offers new insights into how different forms of AI (learning-based versus logic-based AI) influence ESG disclosure-performance alignment and capital market responses.
罗昆教授合作论文"Green is the new gold: The role of professional managers in enhancing ESG performance in Chinese state-owned enterprises"在会计学领域国际权威期刊《The British Accounting Review》正式发表。该期刊为SSCI期刊，JCR分区为Q2区，中科院二区期刊，学校B1类期刊，影响因子4.2。
The British Accounting Review
Volume 58, Issue 3, 2026
Abstract：
Recent reforms in Chinese state-owned enterprises (SOEs) have transformed executive recruitment, shifting top management appointments from direct government selection to board-driven, market-oriented processes. This study examines how the presence of professional managers influences the environmental, social, and governance (ESG) performance of Chinese SOEs between 2011 and 2020. Our results show that SOEs led by professional managers exhibit significantly higher ESG performance, primarily due to reduced managerial shirking and increased appeal to green investors. These positive effects are particularly pronounced in SOEs operating in heavily polluting industries, in firms that offer equity incentives, and when professional managers hold key executive positions or face less pressure from poor financial performance. We also find a positive association between the presence of professional managers and firm value. These findings have important implications for the design of executive systems and governance reforms aimed at better aligning SOE performance with sustainable development goals.
汪伟忠副教授合作论文"Promoting circular supply chain in food sector: A decision framework for analysing the role of artificial intelligence-driven open innovation"在人工智能工程应用领域国际权威期刊《ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE》正式发表。该期刊为SCIE收录期刊，JCR分区为Q1区，中科院二区期刊，学校B1类期刊，影响因子7.5。
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
Volume 145, July 2026
Abstract：
The circular economy, open innovation, and artificial intelligence (AI) have become prominent topics in academic, managerial, and policy discussions. Integrating the food supply chain has emerged as a crucial approach to attaining sustainable development within the food industry. Previous research has mainly concentrated on examining the relationships between any two of these three elements within supply chain management. In contrast to these studies, this research systematically analyzes the transformative power of AI-driven open innovation in advancing the circular supply chain in the food sector. To achieve this, we propose a novel interval-valued spherical fuzzy hierarchical structure model to identify the driving factors, construct the cause-and-effect relationships and driving paths, and ascertain the nature of each driving factor. First, an established Technology-Organization-Environment-Data (TOE-D) framework is introduced for the first time to identify the enablers from AI-driven open innovation. Within this framework, we propose the interval-valued spherical fuzzy the Decision-Making Trial and Evaluation Laboratory to express the cause-effect relationships. Then, the Interpretive Structural Modeling with Cross-Impact Matrix Multiplication Applied to Classification is utilized to construct the hierarchical structure with driving paths and classify the enablers. The findings indicate that the enablers can be divided into three layers and four types of influence effects. Our theoretical contribution consists of giving a quantitative framework for systematically understanding the driving force of AI-driven open innovation in adopting the practices of the circular supply chain in the food sector. The findings of this work are expected to be advantageous for relevant stakeholders in implementing effective AI-driven open innovation, thereby enhancing the promotion of the circular supply chain within the food sector.
孔敏副教授合作论文"Human-Robot Collaborative Supply Chain Scheduling via Reinforcement Learning, Large Neighborhood Search, and Large Language Models"在工业信息融合领域国际权威期刊《Journal of Industrial Information Integration》正式发表。该期刊为SCIE期刊，JCR分区为Q1区，中科院一区期刊，学校B1类期刊，影响因子11.2。
Journal of Industrial Information Integration
Volume 52, July 2026
Abstract：
Compressors are critical components in automobile manufacturing, and delays in their production may directly affect downstream vehicle assembly. Motivated by this practical challenge, this study investigates a supply chain-oriented distributed hybrid flow shop scheduling problem (SCDHFSSP), in which multiple factories jointly perform production and testing tasks under coordinated supply chain requirements. To formulate this problem, a mixed-integer linear programming model is developed. Since the problem is highly complex optimization model, a reinforcement learning-enhanced adaptive large neighborhood search algorithm, termed R-ALNS, is proposed. In the proposed framework, reinforcement learning is used to adaptively select destruction and repair operators, thereby improving the search efficiency and robustness of ALNS. Extensive computational experiments and statistical analyses show that R-ALNS consistently outperforms classical meta-heuristic algorithms, achieving performance improvements of more than 10% across diverse benchmark instances. Comparisons with the Gurobi solver and several state-of-the-art hybrid meta-heuristics further confirm the effectiveness and superiority of the proposed method. In addition, the proposed algorithm is embedded into an LLM-based scheduling agent to support natural language interaction and real-time decision-making, demonstrating its potential for human-machine collaborative scheduling in smart manufacturing.
孔敏副教授合作论文"Digital twin-enabled dynamic energy-efficient rescheduling: balancing service responsiveness, energy consumption, and system flexibility"在工业信息融合领域国际权威期刊《Journal of Industrial Information Integration》正式发表。该期刊为SCIE期刊，JCR分区为Q1区，中科院一区期刊，学校B1类期刊，影响因子11.2。
Journal of Industrial Information Integration
Volume 51, May 2026
Abstract：
This study presents a digital twin (DT)-driven dynamic energy-efficient rescheduling framework to make trade-offs among service responsiveness, energy consumption, and system flexibility in mobile phone manufacturing. To this end, this paper formulates a hybrid flow shop static scheduling model for mobile phone manufacturing (HFSS-MPM) and a hybrid flow shop rescheduling model for mobile phone manufacturing (HFSR-MPM). These models are solved using a genetic algorithm (GA), while real-time detection of defective orders through the DT system triggers the rescheduling process. In comparison with the non-DT framework (NDTF), the proposed DT framework (DTF) achieves its most significant advantages in high energy-sensitivity, low time-sensitivity, and high-flexibility production enterprises, with an average performance improvement of 10.73%. This study confirms that DT technology enhances the adaptive capability of multi-stage production systems to dynamic events, particularly the rework of defective products, through real-time physical-virtual workshop interaction, thereby providing a novel paradigm for efficient and low-carbon operations in Industry 5.0 manufacturing systems.
谭卫民老师合作论文"High speed rail opening and enterprise survival: Empirical analysis using panel data from Chinese industrial enterprises"在经济政策领域国际权威期刊《Economic Analysis and Policy》正式发表。该期刊为SSCI期刊，JCR分区为Q2区，中科院二区期刊，学校B1类期刊，影响因子4.8。
Economic Analysis and Policy
Volume 86, June 2026
Abstract：
High-speed rail (HSR) can compress spatiotemporal distances and alleviate information asymmetry, thereby positively affecting enterprise performance. Although studies have examined HSR’s influence on enterprise performance, its role in shaping enterprise survival has received limited attention. To fill this research gap, this study examines relationship between HSR opening and enterprise survival using the Cox proportional hazards model and data for Chinese industrial enterprises (1998–2009). The findings are as follows: (1) HSR opening reduces enterprises’ survival risk by optimizing their lifecycle: it accelerates the transition from the start-up to the growth-maturity stages and delays the shift from the growth-maturity to the decline. (2) Mechanistically, HSR opening lowers survival risk by improving total-factor productivity and enhancing environmental adaptability. (3) Heterogeneity and boundary analyses show that HSR has a more pronounced risk-reduction effect on labor-intensive enterprises (vs. technology-/capital-intensive ones), with an optimal influence radius of about 40 km. This study provides theoretical and empirical evidence for HSR’s role in reducing enterprise survival risk and offers insights for policies to enhance enterprise resilience.
杨盈盈老师合作论文"Regional Integrity, Financing Constraints, and Corporate Innovation"在金融学领域国际权威期刊《Finance Research Letters》正式发表。该期刊为SSCI期刊，JCR分区为Q1区，中科院二区期刊，学校B1类期刊，影响因子9.4。
Finance Research Letters
Volume 73, May 2026
Abstract：
Regional integrity level is an important part of the local business climate and has a direct bearing on firms’ incentives and ability to innovate. Drawing on the Supreme People’s Court records of delinquent enterprises, together with patent application data and the Chinese Industrial Enterprise Database, this study investigates how variations in regional integrity influence firms’ innovation activities. The results show that weaker regional integrity significantly dampens both innovation output and productivity among normally operating firms. Further examination points to financing constraints as the pivotal channel: a decline in integrity narrows firms’ internal financial space by eroding operating performance, and at the same time tightens external funding conditions through distortions in credit allocation. These findings suggest that strengthening regional integrity level can ease financing pressures, improve the allocation of financial resources, and foster a healthier environment for innovation-driven development.
马振宇老师合作论文"External risk shocks and China's macroeconomic Fluctuations: Which transmission channel matters?"在宏观经济学领域国际权威期刊《Economic Modelling》正式发表。该期刊为SSCI期刊，JCR分区为Q1区，中科院二区期刊，学校B1类期刊，影响因子4.7。
Economic Modelling
Volume 162, September 2026
Abstract：
This paper examines how external risk shocks transmit to China’s macroeconomy and identifies the dominant transmission channel. We develop a two-country dynamic stochastic general equilibrium model with cross-border risk contagion, estimated via Bayesian methods using China–U.S. data. Simulations show that external risk shocks raise China’s domestic market risk, increase corporate risk premia, reduce cross-border capital inflows, and weaken trade, investment, and output. We then estimate a structural vector autoregression model and find consistent evidence that risk contagion, credit, cross-border capital flows, and trade serve as key transmission channels. Variance decomposition indicates that risk contagion is the most important channel, accounting for about 17% of output fluctuations. Counterfactual analysis further shows that weakening this channel substantially reduces the macroeconomic effects of external shocks. These findings suggest that macroprudential tools and financial market reforms that insulate the domestic economy from external risk can effectively safeguard macroeconomic stability.
李展副教授合作论文"Industry Origins of Resource Reallocation in China: Lessons from International Comparisons with the United States and Japan"在生产率分析领域国际权威期刊《Journal of Productivity Analysis》正式发表。该期刊为SSCI期刊，JCR分区为Q3区，中科院三区期刊，学校B2类期刊，影响因子2.2。
Journal of Productivity Analysis
Volume 63, April 2026
Abstract：
This paper adopts KLEMS method to measure TFP and decomposes the economy-wide resource reallocations into the growth rate of factor inputs and service prices at industry level to explore the contribution of individual industries to the overall resource reallocation and its causes, and takes the United States and Japan as references to explore the lessons for the development of China’s TFP. The combined reallocation of resources dominated by significant positive labor reallocation contributes 36% of China’s TFP growth rate through 1978 to 2018, which is larger than 12% in the United States and − 14% in Japan. Due to a large number of capital flows into some service sectors with low return to capital, the combined capital reallocation is negative in China while it is positive in the United States. The outflow of a large amount of labors from the agricultural sector where the return to labor is low makes the positive reallocation of labor input brought about by the agricultural sector to be evident in China and Japan. The reallocations of capital and labor inputs brought about by industrial sectors in three countries are relatively insignificant. The high-developed market mechanism in the United States may promote the efficient allocation of resources.
李展副教授合作论文"Understanding the slowdown of China's total factor productivity since 2008 from a supply-side perspective"在生产率分析领域国际权威期刊《Journal of Productivity Analysis》正式发表。该期刊为SSCI期刊，JCR分区为Q3区，中科院三区期刊，学校B2类期刊，影响因子2.2。
Journal of Productivity Analysis
Volume 64, August 2026
Abstract：
This study employs the KLEMS framework to analyze the sources of China’s economic growth from a supply-side perspective, measuring TFP and decomposing it into industries to identify sectoral contributions. By integrating resource reallocation effects into the analytical framework, the paper examines their impacts on TFP dynamics so as to investigate the causes behind China’s TFP slowdown since 2008. The findings reveal that compared to the 1978–2007 period, China’s GDP growth rate declined by 2.6% points during 2008–2018, with TFP growth accounting for a 2.0% points reduction. Notably, declining TFP growth in downstream manufacturing sectors and the service industry emerged as primary industrial sources of this TFP slowdown. Concurrently, diminishing resource reallocation efficiency explained one-third of the overall TFP growth deceleration.
孔敏副教授合作论文"Reinforcement learning-enhanced metaheuristic algorithm for a battery recycling closed-loop supply chain network design problem"在交通运输管理领域国际权威期刊《Research in Transportation Business & Management》正式发表。该期刊为SSCI期刊，JCR分区为Q1区，中科院二区期刊，学校B2类期刊，影响因子4.8。
Research in Transportation Business & Management
Volume 54, June 2026
Abstract：
With the rapid growth of the electric vehicle and energy storage industries, a large number of power batteries are reaching the end of their service life, leading to increasing concerns regarding resource waste, environmental pollution, and the supply pressure of critical metals. Consequently, designing an efficient and sustainable closed-loop supply chain network (CLSCN) for battery recycling has become a critical issue for both industry and policymakers. To address this challenge, this study develops a multi-stage mixed-integer linear programming (MILP) model that integrates the key processes of collection, distribution, and remanufacturing while simultaneously considering vehicle routing and scheduling decisions. The objective of the model is to minimize the total system cost, including transportation, processing, facility operation, and other related expenses. To solve this computationally complex model, a hybrid optimization algorithm, RL-SA-TS, which combines reinforcement learning (RL), simulated annealing (SA), and tabu search (TS), is proposed. In this framework, RL adaptively selects neighborhood structures according to the current solution state, effectively balancing global exploration and local exploitation. To verify the effectiveness of the RL framework, the proposed algorithm is compared with the SA-TS method, the Gurobi solver, and several classical metaheuristic algorithms. Furthermore, a case study based on the real spatial distribution of nodes in Wuhu City is conducted to evaluate the practical applicability of the proposed approach. Experimental results demonstrate that RL-SA-TS achieves superior facility layout and routing decisions, significantly reduces the overall system cost, and improves the operational efficiency of battery recycling and remanufacturing. Compared with classical metaheuristic algorithms, RL-SA-TS obtains more than 10% cost advantages in most test instances. From a managerial perspective, the findings provide decision-makers with practical guidance for strategically locating recycling and remanufacturing facilities, optimizing transportation routes, improving demand-responsive network configuration, and strengthening cross-stage coordination in battery recycling systems. Overall, this study provides a scalable optimization model and an intelligent solution framework for CLSCN design, supporting more cost-effective, resource-efficient, and sustainable battery recycling operations.
孔敏副教授合作论文"Smart outbound scheduling for textile warehousing: an integrated ALNS optimisation algorithm and LLM-based fuzzy decision-making framework"在工程设计领域国际权威期刊《JOURNAL OF ENGINEERING DESIGN》正式发表。该期刊为SCIE期刊，JCR分区为Q2区，中科院三区期刊，学校B2类期刊，影响因子2.5。
JOURNAL OF ENGINEERING DESIGN
Volume 37, Issue 5, 2026
Abstract：
Order heterogeneity, multi-stage operations, and multi-production line coordination introduce considerable complexity to multi-Stock-Keeping Unit (SKU) outbound scheduling in smart textile warehouses. To address these challenges, we propose an integrated intelligent scheduling framework that combines advanced optimisation with human-centric decision support. The core of the framework is a Mixed-Integer Linear Programming (MILP) model that captures key practical constraints, such as workload balancing across production lines and penalties for order tardiness. To efficiently solve this model, we develop a tailored Adaptive Large Neighborhood Search (ALNS) algorithm featuring customised destroy-repair operators, an adaptive operator selection mechanism, and a simulated annealing-based acceptance criterion to enhance solution quality and convergence speed. Beyond algorithmic optimisation, the framework incorporates an interactive decision-making module that integrates T-Spherical Fuzzy Sets (T-SFS) with Large Language Models (LLMs). This module facilitates human-AI collaboration by capturing and processing decision-makers’ subjective preferences, allowing for flexible, preference-aware scheduling outcomes. Extensive computational experiments on benchmark instances demonstrate the superiority of our approach over traditional heuristics and metaheuristics in both performance and adaptability. The proposed framework offers a comprehensive solution for intelligent, responsive outbound scheduling in the textile warehousing domain.
马振宇老师合作论文"We are all in the same boat: the welfare and carbon abatement effects of the EU carbon border adjustment mechanism"在经济系统领域国际权威期刊《Economic Systems Research》正式发表。该期刊为SSCI期刊，JCR分区为Q2区，中科院三区期刊，学校B2类期刊，影响因子2.0。
Economic Systems Research
Volume 36, Issue 2, 2026
Abstract：
Amid the intensifying global climate crisis, the European Union (EU) has introduced the Carbon Border Adjustment Mechanism (CBAM) to strengthen climate action and mitigate carbon leakage. This paper quantitatively evaluates the welfare and carbon abatement effects of CBAM using a multi-country, multi-sector general equilibrium model that integrates global production networks and carbon emissions. Employing a structural approach with ventilation coefficients as instrumental variables, we address endogeneity in pollution elasticities. Our findings indicate that CBAM improves the welfare of the EU and several developed economies such as Japan and the USA through terms-of-trade improvements. Conversely, most other economies suffer significant welfare losses. While CBAM effectively reduces global emissions, its contribution to the EU's domestic reduction is limited due to internal scale effects. Counterfactual analyses further indicate that a globally harmonized carbon pricing scheme achieves larger emission reductions with lower aggregate welfare costs, highlighting the importance of international policy coordination.
陈超老师合作论文"Effect of financial integration on total factor productivity: innovation with spillover"在应用经济学领域国际知名期刊《APPLIED ECONOMICS》正式发表。该期刊为SSCI期刊，JCR分区为Q2区，中科院三区期刊，学校B2类期刊，影响因子2.6。
Applied Economics
Volume 58, Issue 14, March 2026
Abstract：
The spillover effects of financial integration have remained an unresolved issue for decades. Empirical tests employing micro datasets tend to obtain robust and significant evidence, whereas tests with macro datasets cannot obtain significant regressors. This study suggests that the advantage of backwardness is a necessary condition for the spillover effect and addresses the core empirical issue of the applicability of macro datasets. By developing a theoretical framework and embedding it into a simulated generalized method of moments estimation, robust evidence is obtained using a macro cross-country panel dataset. The results indicate that financial integration, together with the advantage of backwardness, can foster significant innovation and identify the spillover effects of financial integration.
汪伟忠副教授合作论文"An integrated fuzzy decision model for potential digital transformation overcoming circular food consumption and production promotion"在软计算领域国际权威期刊《Applied Soft Computing》正式发表。该期刊为SCIE期刊，JCR分区为Q1区，中科院二区期刊，学校B2类期刊，影响因子7.2。
Applied Soft Computing
Volume 148, November 2026
Abstract：
Digital transformation is being increasingly acknowledged as a pivotal strategy for fostering the circular economy in the realm of food consumption and production. Previous studies focus on revealing the effect of digital transformation on implementing circular economy within food supply chain sector, however, a gap remains in understanding the comprehensive potential of digital transformation overcoming circular consumption and production (CFCP) promotion. This concerns the scalability of the digital transformation and the expansion of CFCP. Thus, this work introduces a comprehensive evaluation framework that integrates various advantages of digital transformation along with barriers derived from the Technology-Organization-Environment (TOE) theory. To measure the significance of these barriers, an extended picture q-rung orthopair fuzzy sets (PqROFSs) based-Cronbach’s coefficient, combined with weighted Heronian mean aggregation operator, is utilized to determine the barrier weights, considering the uncertain conditions and interdependent relationships. After that, through the integration of PqROFSs, the Cronbach’s coefficient, and CoCoSo’B, this framework offers a quantifiable utility index for assessing the potential of digital transformation advantages. Upon applying this framework to an illustrative example, the findings suggest that the advantage, namely “Predicting food demand accurately”, with a utility index of 1.7618, exhibits the greatest potential for overcoming the identified barriers. A validation test, comprising sensitivity and comparison studies, is conducted to assess the reliability of the evaluation framework. The findings of this research are expected to be advantageous for relevant stakeholders in implementing effective digital advantage construction strategies and resource orchestration methods, thereby facilitating the promotion of CFCP models. From a theoretical perspective, employing this framework can enhance our comprehension of digitalization as a driving force for adopting CFCP practices.
叶雷副教授合作论文"Impact of big data technology application on corporate financing constraints: evidence from Chinese listed companies"在应用经济学领域国际知名期刊《Applied Economics》正式发表。该期刊为SSCI期刊，JCR分区为Q2区，中科院三区期刊，学校B2类期刊，影响因子2.6。
Applied Economics
Volume 58, Issue 20, 2026
Abstract：
Big data technologies (BDTs) are widely used in the financial industry due to their ability to quickly integrate and analyse large datasets. However, the effect of BDTs on corporate financing constraints (FCs) remains underexplored. Using data on Chinese listed companies from 2016 to 2022, this study explores the influence of BDT applications on corporate FCs. Results indicate that BDT applications alleviate corporate FCs. Heterogeneity tests show that BDTs more effectively reduce FCs for non-state-owned firms than those for state-owned firms, and for firms in central and western China compared with those for firms in the eastern region. Mechanism tests indicate that BDTs reduce FCs by improving information control, attracting analyst coverage, and increasing institutional investment. These findings contribute to the existing literature on corporate FCs and offer novel insights into avenues for narrowing the financing gap in China.