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This paper aims to introduce a joint DEMATEL and NK methodology to develop a process model for introducing and implementing relational supply chain practices for low-carbon supply chains. Using this process model as a guide, insights into specific practices and how to implement these relational practices to achieve competitive advantage across organizations are introduced.

Low-carbon cooperation practices framework based on the relational view is developed. A methodology based on DEMATEL and the NK model is used to construct a sequential process model for introducing and implementing these relational practices. Empirical data from three manufacturing organizations in China are utilized to validate the model.

Initial results provide a sequence of relational practices for guiding those organizations and their suppliers for healthy and low-carbon development. Interdependencies between relational practices are analyzed and evaluated from four aspects. Insights into the broader application of the methodology and initial results from both a research and managerial perspective are presented, especially with consideration of the China, an emerging economy, context.

The methodology remains relatively abstract in nature, yet the tool can provide very useful interpretations and information for both researchers and practitioners.

This paper stipulates that in addition to internal operational practices, the relational practices between buyer and supplier may be equally important to achieve a low-carbon outcome, especially in supply chain setting. This paper also shows that not only the relational practice itself but also the implementation sequence of the relational practices can relate to performance. According to the authors’ initial results, organizations in this study should first develop product development cooperation, then exchange carbon knowledge and implement effective governance and last build a trust relationship with its suppliers for low-carbon cooperation.

This is one of the few approaches that directly evaluates and identifies the interdependencies among relational practices and to construct a process model for introducing and implementing low-carbon supply chain cooperation. It is also the first time that the NK model has been integrated with DEMATEL. Focusing on Chinese supply chain carbon emissions concerns is also a unique perspective.

The purpose of this paper is to identify how organizations can evaluate the green product deletion decision within an environmentally sustainable consumption and production environment through a hybrid multistage multiple criteria evaluation approach.

This paper proposes a decision-making model by integrating “soft computation” using neighborhood rough set theory, fuzzy cluster means, and cumulative prospect theory. Literature is used to identify various factors for the decision environment. An illustrative problem provides insights into the methodology and application.

The results indicate that green products can be evaluated from both their relative environmental burdens and benefits. Sustainable consumption and production factors that play a role in this multifactor decision are identified. The results show that a comprehensive evaluation can capture an effective overall picture on which green product(s) to delete.

The opaqueness of the proposed methodology may cause less acceptance by management. The methodology made a number of assumptions related to the data. An actual application of the tool rather than just an illustrative example is needed.

The main contribution of this study is the novel integration of supply chain perspectives, both upstream (supply and production) and downstream (demand/usage), with green product deletion decision making. The hybrid multistage technique has advantages of being able to incorporate many factors that have a variety of quantitative and qualitative characteristics to help managers address green product deletion issues as well as its impact on greening of supply chains and organizational environmental sustainability. This paper adds value to product deletion, supply chain management, and sustainable production and consumption literatures.

There is great uncertainty and volatility in the evaluation and measurement of green supplier satisfaction. The purpose of this paper is to fill this gap based on the information entropy theory (IET) to describe the probability of green supplier satisfaction degree.

The authors introduce a formal model using analytic hierarchy process (AHP), IET and entropy technique for order preference by similarity to an ideal solution (TOPSIS) method to evaluate green supplier satisfaction and promote them for the better implementation of green supply chain management practices.

The first finding is developing an effective framework for green supplier satisfaction, incorporating various measures of environmental dimension. Second, a hybrid uncertainty decision method is introduced, by integrating AHP and IET and entropy-TOPSIS.

One of the main limitations of the research is that the authors introduced a conceptual example. Real-world applications need to investigate the accuracy and effectiveness of these measures, and the operational feasibility of this method.

This is one of the first works to provide a comprehensive appraisal model for evaluation of green supplier satisfaction. This study and research method can form general guidelines, and organizations can increasingly benefit from using green supplier satisfaction evaluation as a management tool. Green supplier satisfaction evaluation is just the beginning.

Sustainability trends have changed the modus operandi in businesses even as the market environment becomes more socially conscious. However, relatively little research has been conducted on integrating social sustainability aspects with a focus on corporate social responsibility (CSR) into the selection of suppliers in the service sector, particularly the banking industry. In this paper, this study aims to propose a CSR decision support methodology to evaluate and prioritize socially responsible suppliers.

A novel integrated decision support methodology composed of Shannon Entropy and TOmada de Decisão Interativa e Multicritério (TODIM) methods is introduced. The Shannon-Entropy approach is used to estimate CSR factor weights, and TODIM is used to rank the suppliers, with the process completed in a group decision setting.

A Nigerian bank was used as a case study to test and show the usefulness of the CSR-based decision framework in evaluating and selecting socially responsible suppliers. The results show the topmost ranked suppliers that are recommended for future negotiations by the case (bank). The study will enable banks to select socially responsible suppliers, which could accelerate the attainment of sustainability objectives, protect their reputations and improve competitiveness.

This study pioneers the application of a novel decision methodology based on Shannon Entropy and TODIM in selecting socially sustainable suppliers in the Banking sector of an African emerging economy-Nigeria.

Supply chain agility (SCA) is the primary strategy for reducing impacts and quick recovery when supply chains experience a disruption risk, such as the COVID-19 pandemic. This study will investigate how SCA can be achieved through supply chain information sharing (SCIS) under the different dependence relationships (DR) with suppliers or customers. The purpose of this paper is to investigate this issue.

Based on information process and resource dependency theories, this study constructs and empirically tests a proposed model of the relationships amongst the three dimensions of SCIS and the two areas of SCA and the contingency effects of two types of DR on those relationships. Using a dataset collected from 400 manufacturers in China, the authors tested this theoretical model using multi-group and structural path analysis.

The results of the structural path and multi-group analyses show that (1) all dimensions of SCIS are positively correlated with both areas of SCA and (2) dependence on the supplier and dependence on the customer have completely different impacts on the relationship between SCIS and SCA.

This study can improve the understanding of the multidimensional concepts of SCIS and SCA and relationships between them under two different DR conditions in the Chinese manufacturing setting. It contributes to IS and the SCA literature and provides theoretically driven and empirical explanations for the diverse dynamics between the dependence on the supplier and customer.

As green marketing is a critical function of green supply chain management, it has generated a great deal of discussion in public discourse and academic research. Interestingly, there is a gap in the research on how a company can effectively invest and manage various green marketing activities. Thus this paper aims to introduce a grey multiple criteria decision-making methodology to investigate the relationships between green marketing activities and performance outcomes (environmental and business performance). This paper seeks to make the following contributions to the green supply chain management literature. First, review the literature to identify implementation activities for green marketing from green supply chain management literature. Second, develop a methodology to evaluate relationships of green marketing activities by integrating grey number and rough set method. Third, obtain various decision rules relating the various green marketing activities to the environmental and/or business performance outcomes through an illustrative application within an incomplete information system. Knowing those rules to help in the implementation, management, and evaluation of these green marketing activities is valuable to both researchers and practitioners. Included in the discussion are insights into how these rules for individual and aggregated performance (environmental, business, and joint performance) may be evaluated. Practical and research implications of this work are detailed in the final section of this paper.

The purpose of this paper is to introduce a methodology to identify sustainable supply chain key performance indicators (KPI) that can then be used for sustainability performance evaluation for suppliers.

Initially the complexity of sustainable supply chain performance measurement is discussed. Then, a two-stage method utilizing neighborhood rough set theory to identify KPI and data envelopment analysis (DEA) to benchmark and evaluate relative performance using the KPI is completed. Additional analysis is performed to determine the sensitivity of the KPI set formation and performance results.

The results show that KPI can be determined using neighborhood rough set, and DEA performance results provide insight into relative performance of suppliers. The supply chain sustainability performance results from both the neighborhood rough set and DEA can be quite sensitive parameters selected and sustainability KPI sets that were determined.

The data utilized in this study are illustrative and simulated. Only one model for the neighborhood rough set and DEA was utilized. Additional investigations using a variation of rough set and DEA models can be completed.

This tool set is valuable for managers to help identify sustainable supply chain KPI (from among hundreds of potential measures) and evaluate sustainability performance of various units within supply chains, including supply chain partners, departments, projects and programs.

Sustainability incorporates many business, economic and social implications. The methods introduced in this paper can help organizations and their supply chains become more strategically and operationally sustainable.

Few tools and techniques exist in the sustainable supply chain literature to help develop KPIs and evaluate sustainability performance of suppliers and the supply chain. This paper is one of the first that integrates neighborhood rough set and DEA to address this important sustainable supply chain performance measurement issue.

The purpose of this paper is to threefold. The first purpose is to review and critically analyze corporate sustainability development (CSD) research in China. Second, the paper extracts a unified theoretical framework among CSD drivers, CSD practices, and corporate performance in China. Finally, it seeks to identify links between CSD and industrial management and data systems (IMDS) topics.

A comprehensive and structured review of the research literature investigating CSD in China was completed. Categorizations and classifications of the literature were summarized. A critical analysis of the literature resulted in a generic theoretical framework that can be used for evaluation of the literature and further investigation.

The literature review found over 189 papers on CSD in China published from 1997 to 2013. The framework developed focussed on relationships among drivers, practices, and performance within a CSD in China context. The framework provides useful insights into the implementation of CSD practices. The integration of the three dimensions of sustainability and decision-making methodology are still rare. Specific features of CSD are also reviewed with a linkage to IMDS research around information technology, business process modeling, and supply chain management.

This is one of the first works to provide a comprehensive focus on CSD in China. The theoretical framework was developed for CSD in China to clarify the relationships between the drivers, the corporation’s characteristics, CSD practices, and corporation performance and will prove useful for future research development and investigation. The linkage to IMDS topics is novel and will help further research related to CSD in China for this journal.

This paper aims to introduce relatively novel multi‐supply chain activity overview rough set theoretic applications to aid management decision making with an especial focus on green and sustainable supply chain management.

The methodology is a review of recent literature with extensions around rough set or neighborhood rough set methodologies for supply chain management. An overview of how the techniques can be applied to various stages of green supply chain management, selection, evaluation, development is presented in various sections.

The paper finds that rough set methodology is flexible enough to be applied as a selection tool, performance measurement evaluation tool, and a development program evaluation tool. Its application to green supply chain management topics is warranted and valuable.

Limitations of the approach provide additional avenues for further research. One major limitation of the research is that a real‐world application to validate the approaches is necessary. Extensions and integration with other tools can also provide avenues for improvement.

A three‐staged ecological green supplier management process may help to get a broader corporate social responsibility and general sustainability perspective on the supply chain. Management can use these tools for planning, decision making, and maintenance of green supply chain activities.

The application of sustainability and environmental issues for supply chain management has significant social impact.

Methodologically, this is the first time that neighborhood rough set has been comprehensively evaluated as a tool for managing green suppliers. A comprehensive overview of the green supplier management process considering the sustainability factors helps researchers to identify many opportunities for further investigation.