Search Results (90)

Driven by China’s “dual carbon” strategy, concerns about channel fairness and green investment have become key frontier issues in supply chain management. This study focuses on a two-tier supply chain under a low-carbon background and innovatively incorporates both fairness concerns and green investment perspectives. It systematically explores the impact mechanisms of fairness concern coefficients and green investment levels on channel pricing and profit distribution across four scenarios: information symmetry vs. asymmetry and the presence vs. absence of channel encroachment. The simulation results reveal the following: (1) Under information symmetry and without channel encroachment, an increase in the retailer’s fairness concern significantly enhances its bargaining power and profit margin, while the supplier actively adjusts the wholesale price to maintain cooperation stability. (2) Channel encroachment and changes in information structure intensify the nonlinearity and complexity of profit distribution. The marginal benefit of green investment for supply chain members shows a diminishing return, indicating the existence of an optimal investment range. (3) The green premium is predominantly captured by the supplier, while the retailer’s profit margin tends to be compressed, and order quantity exhibits rigidity in response to green investment. (4) The synergy between fairness concerns and green investment drives dynamic adjustments in channel strategies and the overall profit structure of the supply chain. This study not only reveals new equilibrium patterns under the interaction of multidimensional behavioral factors but also provides theoretical support for achieving both economic efficiency and sustainable development goals in supply chains. Based on these findings, it is recommended that managers optimize fairness incentives and green benefit-sharing mechanisms, improve information-sharing platforms, and promote collaborative upgrading of green supply chains to better integrate social responsibility with business performance. Full article

The transition to a circular economy has increased the significance of reusable plastic container (RPC) pooling systems in green logistics. These systems are third-party reliant; selecting an appropriate service provider becomes crucial, particularly when measured against Environmental, Social, and Governance (ESG) principles. This study proposes a novel decision-making paradigm that incorporates ESG considerations into the evaluation process of RPC pooling service providers through an SF-RANCOM-ARLON (Spherical Fuzzy Sets-Ranking Comparison-Alternative Ranking Using Two-Step Logarithmic Normalization) hybrid method. A real-world case study involving multiple RPC service providers is presented to ensure that the proposed framework is appropriate. It determined 13 sub-criteria under 4 essential headings in the direction of assessing. Not only does this approach provide decision-makers with a methodical and unbiased approach for selecting the leading RPC pooling service provider within an uncertain environment, but it also helps in determining the necessary criteria for RPC pooling service provider selection. Based on rankings, the most critical criteria for service provider selection are delivery reliability, service flexibility, and customer relationship management, while less emphasis is placed on information disclosure. This research contributes to the emerging discourse on ESG-integrated supplier selection and offers a decision-support tool adaptable for sustainability-oriented supply chain networks. Full article

The rapid growth of e-commerce has created substantial environmental impacts, driving the need for advanced optimization models to enhance supply chain sustainability. As consumer preferences shift toward environmental responsibility, organizations must adopt robust quantitative methods to reduce ecological footprints while ensuring operational efficiency. This study develops a novel hybrid multi-criteria decision-making (MCDM) model to evaluate and prioritize green suppliers under uncertainty, integrating the rough-Dombi best–worst method (BWM) and an improved Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The proposed model addresses two key challenges: (1) inconsistency in expert judgments through rough set theory and Dombi aggregation operators and (2) ranking instability via an enhanced TOPSIS formulation that mitigates rank reversal. Mathematically, the rough-Dombi BWM leverages interval-valued rough numbers to model subjective expert preferences, while the Dombi operator ensures flexible and precise weight aggregation. The modified TOPSIS incorporates a dynamic distance metric to strengthen ranking robustness. A case study of five e-commerce suppliers validates the model’s effectiveness, with results identifying cost, green competitiveness, and external environmental management as the dominant evaluation dimensions. Key indicators—such as product price, pollution control, and green design—are rigorously prioritized using the proposed framework. Theoretical contributions include (1) a new rough-Dombi fusion for criteria weighting under uncertainty and (2) a stabilized TOPSIS variant with reduced sensitivity to data perturbations. Practically, the model provides e-commerce enterprises with a computationally efficient tool for sustainable supplier selection, enhancing resource allocation and green innovation. This study advances the intersection of uncertainty modeling, operational research, and sustainability analytics, offering scalable methodologies for mathematical decision-making in supply chain contexts. Full article

Green product innovation in aluminum building material supply chains is critical for sustainability, particularly amid growing economic and environmental pressures. However, effective coordination is challenged by the presence of multiple agents with divergent interests and heterogeneous innovation capacities. This study proposes coordination mechanisms based on a biform game that integrates both non-cooperative and cooperative elements. Key findings include the following: (1) Greater innovation capability heterogeneity promotes green innovation investment by the stronger manufacturer and enhances overall welfare, but reduce the supplier’s profit. (2) Biform game-based decision making supports the triple bottom line more effectively than decentralized models and offers greater flexibility than centralized ones. (3) A multi-perspective compensation contract, incorporating three decision-making modes, is developed within the biform game. Exogenous decision making helps resolve the endogenous game dilemma, improving coordination outcomes. (4) The coordination framework allows firms to dynamically adjust compensation parameters in response to environmental changes, thereby enhancing supply chain resilience. Our main contribution lies in applying a novel biform game approach to address coordination challenges in green product innovation under innovation capability heterogeneity. In addition, a multi-perspective contract coordination paradigm is proposed to support triple bottom line sustainability. Full article

Achieving the construction sector’s dual carbon objectives necessitates scaling green energy adoption in new residential buildings. The current literature critically overlooks four unresolved problems: oversimplified penalty mechanisms, ignoring escalating regulatory costs; static subsidies misaligned with market maturity evolution; systematic exclusion of innovation feedback from energy suppliers; and underexplored behavioral evolution of building owners. This study establishes a government–suppliers–owners evolutionary game framework with dynamically calibrated policies, simulated using MATLAB multi-scenario analysis. Novel findings demonstrate: (1) A dual-threshold penalty effect where excessive fines diminish policy returns due to regulatory costs, requiring dynamic calibration distinct from fixed-penalty approaches; (2) Market-maturity-phased subsidies increasing owner adoption probability by 30% through staged progression; (3) Energy suppliers’ cost-reducing innovations as pivotal feedback drivers resolving coordination failures, overlooked in prior tripartite models; (4) Owners’ adoption motivation shifts from short-term economic incentives to environmentally driven decisions under policy guidance. The framework resolves these gaps through integrated dynamic mechanisms, providing policymakers with evidence-based regulatory thresholds, energy suppliers with cost-reduction targets, and academia with replicable modeling tools. Full article

Production involves processes such as raw material extraction, energy consumption, and waste management, which can lead to significant environmental consequences. Therefore, supplier selection based not only on technical performance but also on environmental sustainability criteria has become a fundamental component of eco-friendly manufacturing strategies. Moreover, in the selection of electric vehicle batteries, it is essential to consider customer demands alongside environmental factors. Accordingly, selected suppliers should fulfill company expectations while also reflecting the “voice” of the customer. The objective of this study is to propose an integrated approach for green supplier selection by taking into account various environmental performance requirements and criteria. The proposed approach evaluates battery suppliers with respect to both customer requirements and green criteria. To construct the relational structure, the DEMATEL method was employed to analyze the interrelationships among customer requirements (CRs). Subsequently, the Quality Function Deployment (QFD) model was used to establish a central relational matrix that captures the degree of correlation between each pair of supplier selection criteria and CRs. Finally, to evaluate and rank alternative suppliers, the Interval Type-2 Fuzzy VIKOR (IT2 F-VIKOR) method was applied. The hybrid approach proposed by us, integrating DEMATEL, QFD, and IT2 F-VIKOR, offers significant improvements over traditional methods. Unlike previous approaches that focus independently on customer preferences or supplier criteria, our model provides a unified evaluation by considering both dimensions simultaneously. Furthermore, the use of Interval Type-2 Fuzzy Logic enables the model to better manage uncertainty and ambiguity in expert judgments, yielding more reliable results compared to conventional fuzzy approaches. Additionally, the applicability of the model has been demonstrated through a real-world case study, confirming its practical relevance and robustness in the selection of green suppliers for electric vehicle battery procurement. Full article

The present study examines the impact of customer firms’ environmental, social, and governance (ESG) performance on suppliers’ green innovation efficiency, grounded in stakeholder theory and innovation diffusion theory. The DEA-SBM model is employed to measure green innovation efficiency and analyze transmission mechanisms through knowledge spillovers, financing constraints, and the moderating roles of executives’ green cognition and digitization. This analysis is based on panel data from 3134 customer–supplier pairs of China’s A-share listed firms from 2014 to 2023. The findings indicate that high ESG performance by customer firms has a substantial impact on suppliers’ green innovation efficiency, with a 1% increase in customer ESG score resulting in a 1.38% improvement in supplier efficiency. The phenomenon under scrutiny is hypothesized to be precipitated by knowledge spillovers and mitigated by reduced financing constraints. The hypothesis further posits that supplier firm executives’ green cognition and customer digitization will amplify the effect. A heterogeneity analysis reveals stronger effects in technology-intensive firms and regions with higher governmental environmental oversight. These findings underscore the pivotal function of ESG-driven supply chain collaboration in propelling sustainable industrialization. It is imperative that policymakers prioritize cross-regional ESG benchmarking and digital infrastructure to amplify green spillovers. Conversely, firms must integrate ESG metrics into supplier evaluation systems and foster executive training on sustainability. This research provides empirical evidence for the optimization of green innovation policies and the achievement of China’s dual carbon goals through the coordination of supply chain governance. Full article

As China’s marine economy and green high-quality development strategy both progress, traditional marine crab farming is reaching its capacity limits. In response, the land-based aquaculture farming model for saline–alkali crabs has emerged, offering new opportunities for the industry. Simultaneously, consumer demand for specialty aquatic products is rising, with growing preferences for products of varying quality and distinctive flavors. To remain competitive, developing quality and flavor differentiation strategies that align with market structures is essential. In this paper, a sequential game-theoretic model is constructed to capture supplier behavior under different market conditions while incorporating consumer heterogeneity and cost structures. The paper examines how flavor preference, quality preference, and market segmentation shape supplier strategies, focusing particularly on the interaction between market entry and segmentation under geographic and cultural influences. The model incorporates consumer utility functions, search costs, and quality investment costs, allowing equilibrium strategies to be derived and compared across scenarios. By incorporating information search costs and technology investment, this paper analyzes optimal pricing and quality decisions in order to inform effective market entry strategies. In addition, the paper explores how the timing of entry affects product quality improvements and price competition, highlighting the evolving acceptance of new products by consumers. In coastal markets, suppliers must prioritize consolidating their presence and leveraging brand equity in order to enhance pricing power. In contrast, emerging markets require accelerated penetration through product differentiation and improved information transparency. This paper proposes an integrated approach to optimizing pricing and product strategies, providing firms with precise market encroachment and competitive strategies that can enhance their market share and longterm competitiveness. Full article

The evaluation and selection of green suppliers is an important way for enterprises to maintain sustainable development and help them reduce costs and increase efficiency. This paper proposes a multi-criteria decision-making (MCDM) model in an interval intuitive fuzzy environment. This model uses interval-valued intuitive uncertainty language number (IVIULN) to describe expert evaluation of qualitative indices. Expert weights are determined through expert social networks, and an improved aggregation operator is proposed to aggregate the evaluation information. The proposed operator can ensure the stability of the results even in the case of extreme values. Subsequently, considering a large number of mutually related indices, a novel teaching-learning-based optimization (NTLBO) algorithm is used to identify the value of $\lambda$-fuzzy measures. This algorithm improves the teaching stage and proposes the idea of teaching students in accordance with their aptitude, introduces precision parameters, and adds a self-study stage. It has been verified by numerical examples that it is far superior to commonly used heuristic algorithms in terms of algorithm accuracy and run time. Finally, the alternatives are ranked by bi-direction Shapley–Choquet integral. The model’s effectiveness is demonstrated through a case study. This paper also examines the impact of key parameters on the results through sensitivity analysis. Full article

The increasing demand for sustainable business practices has highlighted the need for a robust and risk-aware green supplier selection framework. Traditional supplier evaluation methods primarily focus on cost, quality, and delivery performance but often fail to incorporate sustainability and risk factors effectively. This study proposes an improved AHP-FMEA method that integrates the Analytic Hierarchy Process (AHP), entropy weight method, and Failure Mode and Effects Analysis (FMEA) to enhance decision-making in green supplier selection. The AHP method determines subjective criteria weights, while the entropy method adjusts these weights objectively to reduce bias. The FMEA approach incorporates risk assessment by identifying and quantifying potential supplier failures, ensuring a more comprehensive evaluation. A case study is conducted to validate the proposed model, comparing it with classical AHP and AHP-Entropy methods. The results show that incorporating risk factors significantly influences supplier ranking, demonstrating the model’s ability to provide a more scientific, objective, and risk-conscious evaluation. The proposed approach enhances the accuracy and reliability of green supplier selection, making it a valuable tool for sustainable supply chain management. Full article

Purpose: The objective of this study is to examine the influences of green supply chain integration, digital transformation of the supply chain, and environmental uncertainty on corporate green innovation. Moreover, relevant policy suggestions are put forward to facilitate the sustainable development of corporate green innovation. Design/methodology/approach: This study adopts the literature research method to sort out variables to understand the current situation as the foundation for our study, uses the questionnaire survey method to create a questionnaire to collect data, and analyzes the data with the help of the empirical research method to verify our hypotheses to draw conclusions. Findings: Green supply chain integration positively promotes corporate green innovation and also positively affects supply chain digital transformation, which in turn positively promotes corporate green innovation. Moreover, supply chain digital transformation acts as a mediator, while environmental uncertainty plays a moderating role and affects green supply chain integration and green innovation. Originality/value: This study delves into how green supply chain integration, with green internal integration, green supplier integration, and green customer integration as its independent variables, affects the green innovation of domestic manufacturing enterprises. By doing so, it breaks new ground for empirical research in this area and offers theoretical directions for the green innovation efforts of enterprises. Meanwhile, in the digital era, from the overall supply chain perspective, we break through the limitations of previously studied intermediary variables. We construct a theoretical model by integrating supply chain digital transformation and environmental uncertainty variables and explore the variable influence paths. This can fill the research gaps, lay a solid theoretical groundwork for enhancing enterprise sustainable development, and open a new path for enterprise growth. Full article

The construction sector is a significant contributor to global greenhouse gas (GHG) emissions, necessitating urgent decarbonization efforts to align with international climate goals such as the Paris Agreement and the European Green Deal. This study explores a comprehensive framework for construction companies to map and reduce their GHG emissions through a structured four-step approach: defining emission scopes, conducting GHG inventories, setting reduction targets, and planning actionable reductions. Four key pathways are proposed: electricity decarbonization through renewable energy adoption and energy efficiency measures; direct emissions reduction via fleet electrification and infrastructure optimization; recycling and resource efficiency improvements through waste diversion and material reuse; and supply chain emissions reduction by enforcing sustainability standards and responsible sourcing practices. The analysis highlights the importance of integrating technological, organizational, and policy-driven solutions, such as rooftop photovoltaic systems, virtual power purchase agreements, waste management strategies, and supplier codes of conduct aligned with global sustainability benchmarks. The study concludes that construction companies can achieve significant emission reductions by adopting a structured, multi-pathway approach; emphasizing progress over perfection; and aligning their strategies with national and international climate targets. This research provides actionable insights for the construction sector to transition toward a net-zero future by 2050. Full article

Background: Nowadays, traditional supply chain management (SCM) processes are undergoing a profound transformation enabled by advanced technologies derived from Industry 4.0. The rapid adoption of these technologies has led to the emergence of smart SCM, which integrates modern technologies in sourcing, production, distribution, and sales. Supplier evaluation and selection (SES) in smart SCM is a strategic decision impacting the entire supply chain. Organizations must also incorporate sustainability principles into their strategic decisions alongside smart production and efficiency. Methods: The main objective of this study is to develop a multi-criteria decision-making (MCDM) approach under uncertainty to address sustainable–smart supplier evaluation and selection problems. The approach integrates polygonal fuzzy numbers (POFNs), Z-numbers, expected interval (EI), and expected value (EV) to develop methods such as the logarithmic methodology of additive weights (LMAW) and the weighted aggregated sum product assessment (WASPAS), which are used to prioritize criteria and rank suppliers. Furthermore, novel approaches are introduced for calculating membership functions, $\mathcal{a}$-cut formulations, and the crispification process in POFNs. Results: A real case study in the home appliance industry revealed that cost reduction through smart technologies, green and smart logistics and manufacturing, and smart working environments are the most critical evaluation criteria. Suppliers three and four, excelling in these areas, were identified as top suppliers. Conclusions: The proposed approaches effectively addressed hybrid uncertainty in SES problems within smart SCM. Finally, sensitivity and comparative analysis confirmed their robustness and reliability. Full article

The relationship between ports and energy markets is undergoing a transition in their functions as suppliers, consumers, and energy processors. Environmental factors increasingly force the maritime sector to reduce its carbon footprint and improve energy efficiency. Governing the maritime sector’s environmental performance requires leveling decarbonization through integration with energy supply chains and rethinking green strategies and environmental sustainability. This paper highlights that a port’s energy management system can be an example of supply–demand equalizing sustainable alternative energy sources. Such systems engage more profoundly within the energy value chain by assessing green and environmental indicators in port operations, strategies, and investments. This manuscript investigates the challenges in ports’ operations, strategies, and investments, considering their energy transition and decarbonization. Therefore, this research conducted a qualitative study on ports’ energy efficiency and greening using an in-depth interview method in three seaports in the Adriatic, Baltic, and Black Sea basins. The paper proposes a framework for analyzing green variables in the ports’ operations, strategies, and investments to improve their environmental performance. The framework examines a set of green variables, researching their cause-and-effect relationship, enabling testing and evaluation of the determined relationships, and identifying asynchrony in the balanced development of green investments and energy efficiency. Full article

In the food manufacturing industry, which is critical to national economies, there is a growing imperative to meet heightened safety, quality, and environmental standards, particularly in the face of supply chain disruptions. This study addresses the gap in literature by integrating sustainable and resilient supply chain theories with risk management and low-carbon principles into a supplier selection framework. Utilizing the Delphi method, fuzzy analytic hierarchy process (FAHP), and fuzzy multi-objective programming (FMOP), we develop a decision-making model specifically calibrated for the food sector. Initially, the study establishes a comprehensive criteria system encompassing quality, cost, delivery, low-carbon, and risk management through a literature review and expert consultation. Subsequently, FAHP is employed to determine the relative importance of each criterion in supplier selection. Furthermore, FMOP is utilized to develop a decision-making model for optimizing supplier selection and order allocation. Validated through a numerical study based on a Chinese food manufacturer, the framework presents a practical tool for food manufacturers, ensuring supply chain stability while aligning with sustainability objectives. This research refines decision making and strengthens the competitive stance of food manufacturers, significantly propelling the industry’s green transformation. Full article