Optimal selection and investment-allocation decisions for sustainable supplier development practices

Organization’s sustainability performance is influenced by its suppliers’ sustainability performance. This relationship makes sustainable supplier development a strategic competitive option for a buyer or focal organization. When considering sustainable supplier development practices (SSDPs) adoption, organizations have to balance and consider their limited financial resources and operational constraints. It becomes necessary to both select the best SSDPs set and investment allocation among the selected SSDP set such that the organization can maximize overall sustainability performance level. In this paper, an integrated formal modeling methodology using DEMATEL, the NK model, and multi-objective linear programming model is used support this objective. The proposed methodology is evaluated in a practical sustainable supply chain field study of an equipment manufacturing company in China. Through case study, we found that the interdependency among SSDPs must be considered in SSDPs selection and investment allocation problem. Theoretical, managerial and methodology implications, conclusions, and directions for future research are also presented. © 2023, The Author(s)

Integrating sustainability into supplier selection: a grey-based TOPSIS analysis

Sustainable supplier selection plays an important role in sustainable supply chain management operations and implementation. In this paper a novel formal modeling approach is conceptually developed and presented to address sustainable supplier selection. Grey theory and TOPSIS, a distance based multiple criteria method, are used for the integration and evaluation of sustainable supplier performance for sustainable supplier selection. From a research perspective, TOPSIS is improved to more effectively deal with grey numbers by integrating a degree of likelihood rather than converting grey numbers into crisp numbers functions, and it provides more flexible supplier rankings. This methodology strengthens the sustainable supplier selection process, and can be applied to other multiple criteria decision making problems. Illustrative calculations are made using data on sustainable supplier selection and evaluation published by Bai and Sarkis (2010). The technique is relatively accurate, matching well with results from a published grey rough set approach. The methodology easily implementable with minimal complex calculations required. It can also provide support for sustainable supplier selection, benchmarking, and improvement decisions. This is one of the first papers to integrate a broad set of sustainability factors for grey-based TOPSIS and supplier selection

Social sustainable supplier evaluation and selection: a group decision-support approach

Organisational and managerial decisions are influenced by corporate sustainability pressures. Organisations need to consider economic, environmental and social sustainability dimensions in their decisions to become sustainable. Supply chain decisions play a distinct and critical role in organisational good and service outputs sustainability. Sustainable supplier selection influences the supply chain sustainability allowing many organisations to build competitive advantage. Within this context, the social sustainability dimension has received relatively minor investigation; with emphasis typically on economic and environmental sustainability. Neglecting social sustainability can have serious repercussions for organisational supply chains. This study proposes a social sustainability attribute decision framework to evaluate and select socially sustainable suppliers. A grey-based multi-criteria decision-support tool composed of the ‘best-worst method’ (BWM) and TODIM (TOmada de Decisão Interativa e Multicritério – in Portuguese ‘Interactive and Multicriteria Decision Making’) is introduced. A grey-BWM approach is used to determine social sustainability attribute weights, and a grey-TODIM method is utilised to rank suppliers. This process is completed in a group decision setting. A case study of an Iranian manufacturing company is used to exemplify the applicability and suitability of the proposed social sustainability decision framework. Managerial implications, limitations, and future research directions are introduced after the application of the model

An implementation path for green information technology systems in the Ghanaian mining industry

The mining and extractive industry’s operations have significant harmful environmental consequences. Mining companies have started adopting green supply chain management (GSCM) practices which include green information technology systems (GITS) to help provide economic benefits while seeking minimal environmental damage. These mining organizations face significant hurdles related to introducing and implementing various GSCM practices which can address some of the environmental burdens. This study addresses this issue by adopting a GSCM practices framework and applying a novel decision support method that integrates grey numbers with DEMATEL and the NK model for evaluating and developing an implementation path model. Using a multiple case field study with input from managers of the Ghanaian gold mining industry, the adopted GSCM practices framework and methodology is applied. The results provide an evaluation and development path model to guide these organizations and managers for GSCM planning and investment decisions. The path results show that these organizations should first develop SSP (Strategic Supplier Partnership) with their suppliers for implementing GITS (Green Information Technology and Systems) and other GSCM practices. These results provide some exploratory insight and guidelines for managers and policy-makers who seek to integrate green initiatives. This study also sets the stage for further investigation of organizational greening in developing countries and the mining industry

Green supply chain practices evaluation in the mining industry using a joint rough sets and fuzzy TOPSIS methodology

Environmental issues from the extractive industries and especially mining are prevalent and maleficent. An effective way to manage these pernicious environmental problems is through organizational practices that include the broader supply chain. Green supply chain practices and their role in mining industry strategy and operations have not been comprehensively addressed. To address this gap in the literature, and building upon the literature in general green supply chain management and environmental decision tools, we introduce a comprehensive framework for green supply chain practices in the mining industry. The framework is categorized into six areas of practice, with detailed practices described and summarized. The green supply chain practices framework is useful for practical managerial decision making purposes such as programmatic evaluation. The framework may also be useful as a theoretical construct for empirical research on green supply chain practices in the mining industry. To exemplify the practical utility of the framework we introduce a multiple criteria evaluation of green supply programs using a novel multiple criteria approach that integrates rough set theory elements and fuzzy TOPSIS. Using illustrative data we provide an example of how the methodology can be used with the green supply chain practices framework for the mining industry. This paper sets the foundation for significant future research in green supply chain practices in the mining industry

Collection and Evaluation of Genetic Diversity and Population Structure of Potato Landraces and Varieties in China

China is the world’s leading country for potato production but potato is not native to China. To gain insights into the genetic diversity of potato germplasm various studies have been performed but no study has been reported for potato landraces in China. To improve the available genepool for future potato breeding programs, a diverse population containing 292 genotypes (including foreign elite lines, local landraces and cultivars) was developed and genotyped using 30 SSR markers covering the entire potato genome. A total of 174 alleles were detected with an average of 5.5 alleles per locus. The model-based structure analysis discriminated the population into two main sub-groups, which can be further subdivided into seven groups based on collection sites. One sub-group (P1) revealed less genetic diversity than other (P2) and contained a higher number of commercial cultivars possibly indicating a slight reduction in diversity due to selection in breeding programs. The P2 sub-group showed a wider range of genetic diversity with more new and unique alleles attained from wild relatives. The potato landraces, clustered in sub-population P1 may be derived from historical population imported from ancient European and International Potato Center genotypes while sub-population P2 may be derived from modern populations from International Potato Center and European genotypes. It is proposed that in the first step, the potato genotypes were introduced from Europe to China, domesticated as landraces, and then hybridized for modern cultivars

The Water, Energy, Food, and Sustainability Nexus Decision Environment: A Multistakeholder Transdisciplinary Approach

The water, energy, and food (WEF) nexus has gained particular attention in the sustainable development community. Making effective decisions in this environment is difficult. Entwinement from multiple sustainability dimensions and various stakeholder perspectives contribute to this difficulty. Stakeholders have differing goals, interests, and preferences for potential technological and developmental solutions that address WEF nexus concerns. A holistic sustainable management approach with supporting decision support can address these concerns. This article introduces such a holistic framework to address WEF-sustainability (WEFS) concerns. Using a joint neighborhood rough set, interval-valued hesitant fuzzy set, and regret theory technique, this article introduces a multistakeholder transdisciplinary method to support WEFS nexus decisions. An illustrative example integrates the multiple stakeholder and WEFS nexus factors. The illustrative example provides insights into the modeling effort and data requirements. Research, practical implications, along with limitations of the study—which are all discussed—provide a foundation for future research directions in this socio-environmentally important field.peerReviewe

Evaluating complex decision and predictive environments: the case of green supply chain flexibility

Supply chain flexibility is an important operations strategy dimension for organizations to achieve and maintain competitive advantage. With rising greener customer expectations and increasingly stringent environmental regulations, green supply chains are now viewed as another competitive weapon. Green supply chains are characterized by higher complexity and turbulence. Green supply chain flexibility can aid organizations function in this complex and uncertain environment, yet investigation into this area is very limited. This paper aims contribute to this field by investigating green supply chain flexibility achievement through information systems. This paper introduces a green supply chain flexibility matrix framework. Given the large data needs, as described in the matrix, a novel probability evaluation methodology that can help predict rankings of projects and programs is introduced. The methodology extends a TOPSIS based three-parameter interval grey number (TpGN) approach by incorporating neighborhood rough set theory (RST) to evaluate IS programs’ green flexibility support capability. The results of this methodology are more objective and effective for two reasons. (1) The results are predictive rankings based on probability degree instead of the fixed deterministic ranks. (2) Neighborhood rough set theory used in this study can limit loss of information when compared to rough set theory, yet still simplify extensive data sets. This paper also identifies study limitations and future research directions for green supply chain flexibility

Integrating sustainability into supplier selection with grey system and rough set methodologies

Supplier selection plays an important role in the management of a supply chain. Recent emphasis on sustainability has made this selection more complex. Decision support tools and methodologies can help organizations and supply chain managers make more effective decisions. Many tools have been developed with a variety of formal modeling techniques. These techniques may be limited for a variety of reasons. To help advance this area of research and to help further integrate sustainability discussion into the supplier selection modeling area, we expand on a novel approach first introduced by (Li et al., 2008). This approach utilizes grey system and rough set theory. Our expansion and contribution includes introduction of additional levels of analysis and application of this methodology, the explicit consideration of sustainability attributes, and insights into the technique with some sensitivity analysis. Implications of the methodology and future research directions, further expanding the methodology and its applications, conclude the paper.Environment Sustainability Supply chain Rough set Grey system