Search Results (144)

The main objective of this article is to conduct a literature review on the use of open innovation (OI) for green transition to identify tools and methods that can make green transition more effective, efficient, and socially acceptable. This review is accompanied by an attempt to answer the following research questions: R1. How can open innovation be used in the economy and by individual entities to achieve the goals of the green transition? R2. How can individual stakeholders be activated and motivated to participate in the process of creating open innovation for the green transition? and R3. What are the real effects of using open innovation on a macroeconomic, social, and individual scale? The results allow concluding that OI is used by enterprises, cities, regions, and entire economies. Among the methods of activating and motivating individual stakeholders to engage in the process of creating OI for green transition, the following can be selected: (1) internal resources and competencies (knowledge management, internal programs, open leadership, trust, complementarity of resources); (2) partnership characteristics (modern business models, involvement of partnership intermediaries, strengthening relationships with suppliers and customers, involvement of prosumers, cooperation with universities and research institutions); (3) external legal and regulatory conditions (protection of intellectual property rights, pro-innovation and pro-environmental education systems, creation of a legal framework for cooperation between science and business); and (4) external technical and organizational solutions (online platforms, social media, Living Labs, external sources of knowledge). The most frequently mentioned individual effects of open innovation in the energy sector include: improved efficiency, effectiveness and competitiveness in environmental management and the implementation of sustainable development, as well as the use of modern technologies. At the economic level, OI supports investment and economic growth. It can also have a positive impact on reducing energy poverty and developing renewable energy sources, including in emerging economies. This form of innovation also promotes social integration and the creation of social values. The findings of this review can be utilized by scholars to identify current and future research directions. They may also prove valuable for practitioners as both an incentive to engage in open innovation and guidance for its design and implementation. Furthermore, the results can contribute to disseminating knowledge about open innovation and its role in the green transformation. Full article

High-quality development highlights the importance of environmental protection and green low-carbon development. The high-quality development of the manufacturing industry is not only the key content for achieving green transformation, but also an important cornerstone for building a modern national industrial system. Current research focuses on companies and governments, ignoring the important value of suppliers and consumers. As a result, existing mechanisms have failed to deliver the desired results. This paper constructs an evolutionary game model involving manufacturing enterprises, local governments, suppliers, and consumers, and systematically analyzes the strategy selection process of the four participating populations. On this basis, the impact of exogenous and endogenous factors on the evolutionarily stable strategy is studied at the microscopic level using numerical simulation methods. The results show that (1) increasing any of the endogenous factors, such as innovative capability, organization building, and industrial resources, can accelerate the evolution of manufacturing enterprises evolve to smart upgrade strategy. (2) Increasing any one of the exogenous factors, such as policy environment, industrial cooperation, and market demand, can accelerate the rate at which manufacturing enterprises choose to adopt the strategy of smart upgrade. The purpose of this paper is to provide a theoretical reference for the behavioral strategies of manufacturing enterprises, and to provide a realistic reference for local governments to build a mechanism to promote the high-quality development of the manufacturing industry. 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 specificity of the business of agro-food companies is that their products have little or no impact on the environment. However, environmental pollution of these products is caused by the use of packaging. Therefore, it is necessary to apply the principles of the circular economy in the business of companies. Applying green packaging that has little or no impact on the environment helps in preserving the environment. Companies usually purchase packaging from suppliers and therefore, it is necessary to choose the right supplier from which to purchase green packaging to support the implementation of the circular economy. The aim of this research is to select a green packaging supplier for company X in order to influence the development of a circular economy in the company’s business. Based on this, the following research question is considered in this paper: how can the selection of a green packaging supplier influence the implementation of a circular economy at company X? The research covers ten criteria used in this selection, with which eight suppliers were observed. Because every decision-making process in the economy is characterized by risk and insecurity that affects the uncertainty in decision-making, an intuitionistic fuzzy set (IFS) was used. Determining the importance of weights was performed directly based on the ratings of the decision-maker (DM) and the steps of the SiWeC (Simple Weight Calculation) method, as well as using the Entropy method. The compromise results of these methods showed that the most important criteria for assessing the life cycle of packaging are transparency and ethics in business. The ranking of suppliers was carried out using the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method and its results showed that supplier 5 is the first choice for establishing long-term cooperation in the procurement of green packaging. 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

As environmental issues become increasingly prominent, the sustainable practices of enterprises, especially measures at the product level, have garnered widespread attention from scholars. Although numerous studies have explored suppliers’ sales strategies for green products, they often overlook the scenario where suppliers simultaneously sell both green and non-green products.This study focuses on the sales mode selection strategies of suppliers when providing green and non-green products through e-commerce platforms. Utilizing a game model, we analyze the equilibrium strategies between suppliers and e-commerce platforms, and conduct sensitivity analyses to evaluate the impact of key parameters on decision-making. The results reveal that there are significant differences in the strategic preferences of suppliers and e-commerce platforms. However, when commission rates are moderate and green products incur high production costs, these preferences tend to align, leading to Pareto optimal outcomes. Additionally, our findings demonstrate that adopting differentiated sales modes for the two product types can effectively mitigate the problem of double marginalization, thereby enhancing the efficiencyof supply chains. These insights provide valuable guidance for e-commerce platform managers and suppliers in making decisions on sales models for managing multiple types of products. 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

By researching how to select green products for express packaging, this study provides a scientific decision-making basis and methodology for logistics enterprises, encouraging them to accelerate green transformation and meet consumer demands. This article proposes a method for logistics companies to evaluate green products using specific indicators. First, triangular fuzzy numbers and their α-levels are incorporated into the calculation process. Second, when determining the weights of each indicator, both the priority and its relative degree are considered, enhancing the evaluation in relevant scenarios. Finally, an improved approach for calculating positive and negative ideal solutions in the TOPSIS method is presented. Through numerical examples, we demonstrate that the value of α in the improved fuzzy TOPSIS method proposed in this study critically influences logistics enterprises’ selection of container bag suppliers. Full article

Climate change and sustainable development have become critical global issues. The foodservice industry and its supply chain are among the sectors with high carbon emissions. As such, many foodservice businesses are actively implementing carbon reduction initiatives. This study established professional competence indicators for carbon-reducing culinary practices from a sustainability perspective. Using the Modified Delphi Method, 14 food service experts were invited to participate in a three-round survey questionnaire to develop a competency framework applicable to kitchen operations. The findings identified three major dimensions of carbon-reducing culinary professional competence: knowledge competence (19 indicators), attitude competence (13 indicators), and technical competence (13 indicators), totaling 45 indicators. Attitude competence was deemed the most critical, followed by knowledge competence. Regarding the attitude dimension, the most important indicators included selecting suppliers aligning with carbon reduction and sustainability goals, commitment to sustainability initiatives, green procurement, energy management, and water conservation practices. Understanding inventory preservation management regulations and principles was the most essential indicator in the knowledge dimension. In the technical dimension, using seasonal ingredients and accurately managing inventory levels were the key factors. The findings provide a reference for government agencies, the foodservice industry, and higher education institutions in promoting sustainable culinary development. Strengthening chefs’ awareness and competencies in carbon reduction is essential in advancing sustainability within the food supply chain. 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

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

Uncertainty exists in reality decision-making problems. Therefore, fuzzy theories, fuzzy intervals, intuitionistic fuzzy, and Z-numbers have been proposed and successfully applied to multi-criteria decision-making (MCDM). However, since the information presented in the Z-numbers method is the subjective opinion of the decision-maker, the problem of overestimating or underestimating the reliability of the information may occur in both individual and group decision-making. The Extended Z-numbers (Z^E-numbers) method was proposed in 2021 to solve this problem; hence, the decision-making process no longer relies on subjective opinions only but seeks external experts related to the problem to further vote on the evaluation value given by the internal decision-maker, in order to modify the information’s reliability, and thus to obtain a more realistic result. This paper combines the Z^E-numbers method with the improved Elimination et Choix Traduisant la Realite II (ELECTRE II) proposed in 2022 and proposes a new MCDM method based on Z^E-numbers, named Z^E-ELECTRE II. The green supplier selection problem was used as an illustrative example. Meanwhile, the close analysis in this paper examines two primary dimensions of variability: (1) simulation of external expert voting situations to analyze the variations in information reliability and decision-making results and to cross-compare them with other MCDM methods; (2) investigation of the impact of internal preferences, as reflected through systematic adjustments to the weights of the evaluation criteria. The results show that uncertainty of information, reliability, and the perspectives of different decision-makers and expert groups can be considered through Z^E-numbers. The proposed Z^E-ELECTRE II is applicable to group decision-making, validates the robustness of the process, and is suitable for dynamic decision-making under varying decision-maker preferences. Furthermore, using the Z^E-numbers along with the MCDM method can obtain more flexibility and more reliable results. Full article

Although sustainability in Tanzania’s construction sector has been explored in areas such as energy efficiency and green building practices, little attention has been given to understanding the specific barriers to the selection of SBMs in residential projects. This study fills that gap by identifying and analyzing the critical barriers hindering the effective selection of SBMs in Tanzania’s residential construction sector. Through qualitative interviews with experts from regulatory bodies, public developers, and academic researchers, this research provides a comprehensive examination of these barriers. Using Atlas.ti 23 software for a qualitative data analysis, six key categories of barriers were identified: (1) Regulatory and Policy Barriers, (2) Financial Barriers, (3) Knowledge and Awareness Barriers, (4) Technical Barriers, (5) Market and Supply Chain Issues, and (6) Cultural and Social Barriers. Among these, lack of awareness and limited knowledge emerged as particularly significant, alongside regulatory and policy barriers, in hindering the effective selection of SBMs. This study’s novelty lies in its focus on the Tanzanian context, depth of the analysis of the unique challenges, and categorization of the barriers. The findings underscore the need for targeted policy interventions, particularly in raising awareness, offering financial incentives, and establishing comprehensive regulatory frameworks. Furthermore, this study presents a graphical representation to illustrate the categories and constructs of these barriers, adding a visual dimension to the understanding of the issues. Future research should expand the scope to include private developers and material suppliers, whose roles are critical in enhancing the availability and adoption of SBMs in Tanzania’s construction industry. 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