Assessed ESG increasingly enters capital allocation and stewardship, yet it remains unclear when observed persistence reflects durable information rather than benchmarking, discretization and updating rules embedded in provider architectures. This study examines when temporal dependence in Wind-assessed ESG for Chinese A-share firms is empirically defensible under timerespecting evaluation. Using annual Wind ESG scores and ratings for a balanced panel of 3,092 firms from 2018 to 2025, we implement rolling-origin forecasts with time-ordered training and out-ofsample tests for 2022-2025, restricting predictors to information dated t-1 or earlier. Past ESG is represented as continuous score histories or rating histories encoded consistently with Wind's measurement architecture, and we compare an additive linear benchmark with tree-and neighbourbased learners. Additional diagnostics separate rating transitions from within-category score drift, remove within-industry common components, and extend forecasts to t+2 and t+3. Lag histories contain recoverable information about next-year Wind-assessed ESG, with the additive linear benchmark performing best overall; the same broad ordering remains after industry adjustment. Predictive reliability is uneven across years, weaker at distributional extremes, and materially lower at longer horizons. Rating histories retain substantial predictive content when encoded coherently, whereas one-hot lag blocks can destabilize linear estimation. Stable labels can also coexist with within-category score movement, and most recoverable signal is concentrated in management and practice histories rather than more episodic controversy measures. The findings clarify when persistence in Wind-assessed ESG is empirically defensible and where interpretation is most sensitive to horizon, encoding and distributional position.

In digital ecosystems, consumers have evolved from passive end-users to essential participants in production and value co-creation. Collaboration between consumers, small and medium-sized enterprises (SMEs), and leading industry enterprises is a crucial factor in the digital transformation of industries. However, SMEs have undermined the effectiveness of industrial chain collaboration in their digital transformation because they lack resources and expertise, as well as a lack of strategic vision. The purpose of this research is to investigate how players in consumer-driven digital ecosystems are implementing digital transformation techniques and how government subsidies affect behavioral choice tactics. This study constructs a differential game model to solve for the optimal pricing levels, co-innovation effort levels, digital transformation levels, and industrial chain profits under various cooperation intensities and behavioral choice patterns, as well as to analyze the impact of key parameters on optimal decisions, digital transformation, and member behavior choices. The main research findings indicate that cooperative decision-making significantly improves the level of industrial digitalization and the total profit of the system, unleashing the multiplier effect of collaborative innovation; myopic behavior has a significant inhibitory effect on supply chain development, with the myopia of leading enterprises having a more obvious negative impact; consumer demand and policy incentives are key driving factors for digital transformation, The findings offer theoretical insights into digital transformation and consumer behavior within digital ecosystems.

This study examines the relationships between social accountability, environmental commitment, and the adoption of eco-friendly practices in supply chains within Bangladesh. Targeting stakeholders from diverse industrial sectors, the research uses standardized questionnaires and Structural Equation Modeling (SEM) via Smart PLS software to develop a framework that highlights the impact of green supply chain strategies on social responsibility. It also explores how environmental commitment influences these relationships and supports sustainable practices. The analysis reveals key insights into the dynamics between environmental dedication and sustainable supply chain management, offering guidance for improving eco-friendly practices in developing economies. The findings emphasize the necessity of aligning sustainability goals with social and environmental responsibilities, contributing to broader sustainable management strategies and policy development for emerging markets.

The rapid growth of e-commerce demands innovative solutions for resilient and sustainable supply chains. This study explores the role of AI-driven demand forecasting (AIDF) and AI-driven waste reduction (AIDWR) in enhancing supply chain efficiency, minimizing operational waste, and fostering sustainability. Analyzing data from 539 samples via PLS-SEM, the findings highlight how AIDF optimizes demand accuracy, reduces overproduction, and minimizes stockouts, while AIDWR lowers resource consumption and mitigates environmental impacts. Operational Waste Reduction mediates AI's effectiveness, aligning efficiency with sustainability goals and promoting adaptable, environmentally conscious supply chains. These insights guide e-commerce managers in leveraging AI for resilience and sustainable growth. The study underscores the transformative potential of AI to meet dual objectives of operational excellence and sustainability.

In conjunction with the rapid development of big data technology, many big data service providers (BDSPs) have been widely integrated into closed-loop supply chains (CLSCs). This study examines the role of BDSPs in a dynamic CLSC that employs a manufacturer for recycling and remanufacturing, a retailer for retailing, and a BDSP for providing big data services such as site selection for recycling. In the presence of stochastic disturbances, the Itô process is used to describe the dynamic evolution of recycling ratios. Differential game models are presented that decentralize independently without a BDSP (scenario D) and with a BDSP (scenario B) and introduce a coordinating contract that combines wholesale price discount and cost-sharing (scenario C). Furthermore, we explore the decisional differences between the three scenarios, the contract’s effects, and sensitivity to parameters by using comparative and numerical analysis. The findings indicate that BDSPs participation in CLSCs could positively affect recycling ratios and supply chain profits, and an increase in the volatility of recycling ratios could be beneficial to manufacturers and retailers. In addition, the designed contract is likely to reduce retail prices, enhance recycling ratios, and contribute to Pareto improvements. Sustainability can be attained in a way that maximizes profits and minimizes environmental impact by properly using the proposed model. Enterprises are recommended to work with BDSPs to enhance their goodwill because BDSPs facilitate the use of big data marketing for increasing sales and recycling ratios, thereby promoting sustainable economic development and environmental protection.

文章以再制造供应链为研究背景,在考虑消费者后悔预期的情况下,构建了新产品和再制品的需求函数,研究了分散决策无领导(N)、制造商领导(M)和零售商领导(R)3种权力结构下再制造供应链的最优定价问题,并比较了3种权力结构下再制造供应链的最优价格和利润.最后通过数值仿真方法分析了新产品和再制品的批发价格、销售价格、需求量与消费者对再制品偏好程度差异和消费者后悔预期敏感系数的关系.通过研究,我们得到如下结论:消费者偏好程度差异和消费者后悔预期敏感系数较高时,供应链各成员应采用较低的定价策略以扩大需求;在3种权力结构中,制造商领导和零售商领导模式下产品的零售价格相等,且高于无领导模式下产品的零售价格;制造商和零售商的利润分别在各自领导模式下达到最高,再制造供应链总利润在无领导模式下最高,从消费者和供应链整体角度出发,采取无领导模式最有利.

为研究政府补贴和制造商的互惠偏好行为对碳减排供应链运营产生的长期影响,在考虑产品碳减排水平动态影响消费者需求的基础上,文章构建了无政府补贴制造商无互惠偏好模式、有政府补贴制造商无互惠偏好模式、无政府补贴制造商具互惠偏好模式、有政府补贴制造商具互惠偏好模式以及集中模式5种微分博弈模型,将碳减排量作为状态变量,求解供应链减排量最优轨迹,比较不同模式下制造商和供应商的碳减排水平以及政府的补贴系数,以集中决策为基准,探究政府补贴和制造商互惠偏好行为对供应链碳减排水平和利润产生的影响.研究表明:制造商的互惠偏好行为不仅会提高制造商自身的利润和碳减排努力水平,也会提高供应商的利润.政府补贴行为可以提高供应链碳减排水平和利润,但是政府补贴会削弱制造商的互惠偏好行为.

This study investigates the influence of consumer cooperation, eco-design, and green marketing on the adoption of green supply chain management in developing countries. The mediating role of innovation in this relationship is also examined. A survey method was employed, using a questionnaire adapted from previous studies. The sample comprised 250 respondents who were employees of small and medium size and multinational manufacturing industries in Bangladesh. Smart partial least squares (PLS) are currently being used for data analysis, while PLS-structural equation modeling is being employed to assess measurement and structural models. The findings reveal that consumer cooperation, eco-design, and green marketing significantly affect innovation. Furthermore, innovation acts as a mediator between these variables and the adoption of green supply chain management. This study identifies green supply chain management practices that have the potential to enhance organizational performance and motivate companies to implement strategic and operational changes, leading to significant economic, social, and environmental impacts. The research holds significant importance for emerging economies and green supply chain adoption considering the constraints at both organizational and government levels. It provides a framework for a synergistic combination of asset-based elements, innovation, and green supply chain management, benefiting small and medium size organization, multinational corporations, and the supply chain sector in achieving sustainable development goals. The implications of this study extend to supervisors and managers in the corporate world, assisting them in making informed decisions. By expanding the existing literature on the consumer cooperation, eco-design, and green marketing model to include green supply chain management, this study contributes to the field. However, it should be noted that the findings and recommendations may be influenced by contextual factors, and therefore, future research should explore other countries to identify regional and specific sectors, enabling a broader perspective and comparisons as well as green related aspects and performances.

Purpose Although previous studies have studied the impact of spiritual leadership (SL) on employees’ innovation, the research on mechanisms and the boundary conditions for stimulating this relationship is scant. This paper aims to follow the idea of social capital theory (SCT), which contends that social relationships are resources that lead toward the development of intellectual capital, important for innovative work behavior (IWB) of employees; the mediating role of knowledge sharing self-efficacy (KSSE) and moderating role of innovation climate (IC) are considered. Design/methodology/approach The authors collected the data from the foreign and local employees working in multinational companies in China. The quantitative analysis was performed using Smart-PLS 3.0. Findings The results indicated that employee high-ranking of SL is positively related to KSSE. Moreover, SL is significant to enhance IWB, whereas KSSE explained this relationship. The authors also suggest that an employee’s KSSE is significant to form important behavior at work (IWB). However, IC did not play its moderating role in the SL – IWB link. Originality/value This study explores the influence of the leadership style (SL) on employees’ KSSE and the effect of KSSE on IWB, which have not been studied previously. The current study confirms the relationship between SL and IWB in the multicultural workplace and reveals the deeper influence of an individual’s belief (KSSE) mechanism between them. SCT was applied to explain the proposed relationships.

Although there have been studies in the past that have highlighted the important role of leadership in motivating employees to speak up, relational leadership has been scarcely investigated in this context. Therefore, the current research investigates the relationship between inclusive leadership, as a form of relational leadership, and employees' voice behavior directly and indirectly via psychological empowerment. Using the data collected from 252 employees and their respective supervisors working in cargo companies across the United Kingdom, this study finds a positive relationship between inclusive leadership and voice behavior. The results further confirm the mediating role of psychological empowerment in the relationship between inclusive leadership and voice behavior. We use causal attribution theory to support the findings and discuss implications for research and practice.

In the aviation sector, supply chain management is critical for reducing operating costs. The performance of a corporation is determined by how successfully it implements the supply chain strategy. This research aims to propose the improvement in the field of business process improvement (BPI) and supply chain management (SCM) processes in the international airline industry. Improvisation of efficient SCM has dramatically changed the way organizations conduct business by implementing procedures that can improve process efficiency, reduce costs, and improve the organization's performance. This paper leads to formulating the concept of an effective model of the SCM process for Pakistan Int. Airlines (PIA) taken as an example and obtained results can be implemented on any international airline as well. BPI provides competent strategies for the target organization keeping in view the implementation of the proposed SCM model. Simulation analysis is executed using the ARENA software tool to analyze the performance of the proposed model. T-test has been taken into account to demonstrate the competency of the proposed SCM model. It is observed that the implementation of effective business techniques in the SCM process can lead to enhancing the efficiency of a target organization.

中小企业往往面临产出不确定的风险,区块链背景下,本文利用定量模型刻画应用区块链技术对产出不确定的预测作用;分析区块链技术应用程度对中小企业生产决策、银行贷款决策以及贷款企业和银行期望利润的影响;利用下侧风险控制模型研究银行考虑风险规避时的授信限额决策.研究表明:贷款企业的计划生产量随着区块链技术应用程度的提高而增加;银行追求利润最大化时制定的贷款额度在一定条件下也随着区块链技术应用程度的提高而增加;银行授信限额决策随着区块链技术应用程度的变化情况与风险容忍度和产出波动的均值有关.贷款企业的期望利润随着区块链技术应用程度的提高先减后增,当供应商产出波动的均值较大时,银行期望利润随着区块链技术应用程度的提高而增加.

考虑市场上存在一定比例的消费者对应用区块链技术信息披露敏感,利用CVaR风险度量方法构建融资模型,求解均衡状态下供应链最优批发价、订货量和区块链技术应用程度决策,对区块链供应链融资和传统供应链融资模式进行比较分析.研究表明:对于供应商而言,区块链供应链融资模式下获得的收益恒大于传统供应链融资模式.若市场中消费者敏感比例较高,则在区块链技术应用成本系数较低时,零售商选择区块链供应链融资模式获得的最优风险收益值更高.若消费者对应用区块链技术敏感比例较低且产品生产成本满足一定条件,此时若供应商还具有较高的风险规避程度,则传统融资模式对零售商更有利.

在闭环供应链中考虑了大数据服务商参与和受企业声誉、时间等多种因素影响的回收率,研究了无大数据服务商参与、大数据服务商协助回收和营销三种情形下供应链成员的均衡策略,并进行了对比分析.通过伊藤过程对动态变化的回收率进行了刻画,分析了大数据服务费分担比例和回收率对企业声誉敏感参数对供应链成员的影响.研究表明:废旧产品的回收率、制造商的回收努力水平、零售商的零售价格和两者的利润能够在较短时间内达到期望值,受随机因素干扰在期望值附近波动;零售商对市场变化以及自身利润的感知速度更快;大数据服务商的参与能够提高废旧产品的回收率、制造商的回收努力水平和闭环供应链成员的利润.相同的大数据服务水平下,外部环境对废旧产品回收的限制约束大于激励时,协助营销相较于协助回收对回收努力水平以及制造商和零售商利润的提升更有利.

This research aims to explore the positive effects of the COVID outbreak on labor and corporate social responsibility (CSR) environmental issues, using both shareholders and cognitional theories. The study emphasizes the importance of sustainability and CSR in addressing work environmental issues and investigates the correlation between CSR and labor environment issues in Bangladeshi “small and medium enterprises (SMEs),” based on the ISO 26,000 standard set by the “International Organization for Standardization.” The research analyzed data from 399 executives in Bangladeshi SMEs, using partial least squares structural equation modeling for hypothesis testing and data analysis. The results revealed that the implementation of CSR practices had a positive impact on various aspects of work practices, such as employment relationships, human development and training, social exchange, conditions of work and social protection, and health and safety at work. The study contributes to a better knowledge of the impact of the pandemic on labor and environmental issues in Bangladeshi SMEs and demonstrates how CSR practices can effectively address these issues. This research delves into the influence of individuals’ emotions on CSR practices amid the pandemic. It emphasizes the positive resurgence of sustainability and green initiatives. Furthermore, our study uncovers how negative sentiments toward the pandemic prompt a reevaluation of social practices, providing opportunities to strengthen CSR efforts. The findings from our study indicate that the COVID-19 pandemic has influenced companies to prioritize corporate social responsibility (CSR) initiatives in response to the economic, social, and ecological challenges confronting various stakeholders, with a particular emphasis on employees. Thus, the primary objective of this study is to establish a comprehensive connection among the diverse elements encompassing CSR practices, the COVID-19 pandemic, and the challenges faced in the work environment. The research also discusses the theoretical and practical implications of the findings, as well as potential areas for future research in this field. However, the study acknowledges its limitations and highlights the need for further investigation in this area.

The closed-loop supply chain has been receiving increasing attention in recent years. Supply chain coordination and remanufactured products quality control are two fundamental factors for the closed-loop supply chain to obtain a competitive advantage. Besides, fierce competition brings more uncertainty to the market demand. Supply chain members tend to show the characteristics of loss aversion, which could affect them in making quality decisions. Therefore, this paper attempts to coordinate the closed-loop supply chain under remanufactured products quality control with a loss-averse manufacturer and a loss-averse retailer. Under remanufactured product quality control, expected utility function of manufacturers and retailers are established under centralized decision and decentralized decision respectively. According to the principle of utility maximization, the optimal choices of manufacturers and retailers are obtained. Further, by analyzing and comparing the optimal decisions in decentralized and centralized cases, it is found that the closed-loop supply chain cannot achieve coordination. Therefore, the wholesale price and the quality cost-sharing contract are introduced which is proved to be able to harmonize the supply chain. Finally, the impacts of the parameters change on the optimal quality level and remanufactured product price under two typical decision structures are presented through the sensitivity analysis.

Taking into consideration fairness concerns and altruistic preferences of manufacturers, this paper aims to propose a green dual-channel supply chain that incorporates consumers' environmental awareness (CEA) and channel preference. The purpose of this work is to explore and further compare the optimal outcomes in a green dual-channel supply chain in three scenarios, which are the fairness-neutrality scenario (Model N), the manufacturer is concerned with fairness scenario (Model F), and the manufacturer has altruistic preference (Model A), respectively. The game-theoretical models with different fairness preferences, comparative, and numerical analyses are used to put forward the impacts of consumers' channel preference and CEA on pricing, profits, and utilities, and to identify the differences in decisional outcomes between the three models. The results indicate that CEA always contributes to developing the green market while adversely affecting common products. Moreover, consumers' channel preferences might enable the manufacturer and retailer to enhance profitability under certain conditions. The findings also reveal that manufacturer's fairness concerns can possibly increase the demand for green products but impair the overall performance of the supply chain in general. Moreover, while the manufacturer's altruistic preference benefits the retailer's profits, it has a detrimental effect on the performance of the green supply chain. The practical implications of this research come to promote green consumption and increasing consumer awareness of environmental protection are effective ways to develop a green supply chain. It is also important to note that in order to maintain the durability and stability of the sup-ply chain, the manufacturer must maintain a moderate level of fairness preference behaviors so that downstream retailers will remain enthusiastic about establishing long-term relationships.