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

Exploring the mutual influence among the social innovation factors amid the COVID-19 pandemic

From the triple bottom line, the social aspect has received relatively limited attention during the Corona Virus Disease (COVID-19) pandemic, particularly in the emerging economies. Social innovation factors help improve the sustainability performance of the companies. This study develops a social innovation decision framework and analyses the interrelationships among social innovation factors considering the COVID-19 situation. For this purpose, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) is extended by integrating the Z numbers and rough fuzzy set theory into its computational procedure. Z-numbers address the uncertainty of the decision and experts’ confidence in the evaluation and rough numbers are used for aggregating the experts’ opinions. On this basis, the mutual influence of social innovation factors and the influence weights of these factors are investigated. The results suggest that a quick response to market demand for sustainable products is the most influential factor in attaining social sustainability innovation during the pandemic. This article is concluded by providing insights for industrial experts and decision-makers to understand the underpinnings of social sustainability innovation during unforeseen situations

Delving Into the Interdependencies in the Network of Economic Sustainability Innovations

Legislative pressures and public awareness are urging companies to foster sustainability innovations that improve business operations. Limited studies explored the underpinnings of the economic dimension of sustainability innovations; studying economic innovation criteria in the manufacturing sector of emerging economies can inform other industries while recession fears loom the financial prospects. This article develops a decision analysis and evaluation framework for investigating the interdependencies in the network of economic sustainability innovation criteria using fuzzy Total Interpretive Structural Modeling (TISM). It is found that the ‘‘availability of financial resources for promoting innovation’’ is the criterion with the most network relations; this is what the managers should focus on to better pursue sustainability innovations in the supply chains and facilitate the shift towards sustainable industrial development. The study is concluded by providing practical insights into the economic dimension of sustainability innovations for industrial managers and academics

A best-worst-method-based performance evaluation framework for manufacturing industry

Purpose: The purpose of paper is to develop a performance evaluation framework for manufacturing industry to evaluate overall manufacturing performance. Design/methodology/approach: The Best Worst Method (BWM) is used to aid in developing a performance evaluation framework for manufacturing industry to evaluate their overall performance. Findings: The proposed BWM-based manufacturing performance evaluation framework is implemented in an Indian steel manufacturing company to evaluate their overall manufacturing performance. Operational performance of the organization is very consistent and range between 60% to 70% throughout the year. Management performance can be seen high in percentage in the first two quarter of the financial year ranging from 70% to 80% whereas a slight decrease in the management performance is observed in the 3rd and 4th quarter ranging from 60% to 70%. The social stakeholder performance has a peak in first quarter ranging from 80% to 100% as at start of financial year. Originality/value: This paper utilized BWM, a MCDM method in developing a performance evaluation index that integrates several categories of manufacturing and evaluates overall manufacturing performance. This is a novel contribution to BWM decision-making application.Output Status: Forthcoming/Available Onlin

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Assessing the social sustainability of supply chains using Best Worst Method

A truly sustainable organization needs to take the economic, environmental and social dimensions of sustainability into account. Although the economic and environmental dimensions of sustainability have been examined by many scholars and practitioners, thus far, the social dimension has been received less attention in literature and in practice, in particular in developing countries. Social sustainability enables other sustainability initiatives and overlooking this dimension can have a serious adverse impact across supply chains. To address this issue, this study proposes a framework for investigating the social sustainability of supply chains in manufacturing companies. To show the applicability and efficiency of the proposed framework, a sample of 38 experts was used to evaluate and prioritize social sustainability criteria, using a multi-criteria decision-making method called the ‘best worst method’ (BWM). The criteria are ranked according to their average weight obtained through BWM. The respondents view ‘contractual stakeholders influence’ as the most important social sustainability criterion. The results of this study help industry managers, decision-makers and practitioners decide where to focus their attention during the implementation stage, to increase social sustainability in their organizational supply chain and move towards sustainable development

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 Integrated Approach for Assessing Suppliers Considering Economic Sustainability Innovation

Innovation plays a key role in improving the sustainability performance of corporations. Limited studies have investigated the economic aspect of sustainable innovation. This article puts forward a decision framework for evaluating economic sustainable innovative suppliers. A new methodology based on fuzzy Full Consistency Method (FFUCOM) and Improved Combinative Distance-based Assessment (ICODAS) is developed and extended using interval rough Dombi-Bonferroni operators. In the developed approach, the FFUCOM is employed to determine the criteria weights, and the ICODAS is responsible for assessing and ranking the suppliers. A case study from the manufacturing sector of an emerging economy is considered for validating the developed framework and decision model. The findings introduce the “financial resumption of products” as the most critical economic innovation criterion for evaluating suppliers. Furthermore, the applicability and validity of the proposed model was confirmed through sensitivity analysis

Analyzing interrelationships among environmental sustainability innovation factors

Due to growing public awareness, governmental regulations and concerns, environmental sustainability initiatives have received increasing attention among industrial decision-makers and practitioners. Employing environmental management programs can significantly minimize the waste and preserve the environment. However, papers have not much focused on exploring the interactions and interdependencies among environmental sustainability innovation factors, particularly in the context of manufacturing sector of emerging economies. To address this issue, this paper proposes a criteria decision framework, with the target of investigating the interactions among environmental sustainability innovation criteria within an emerging economy nation manufacturing sector context using Z-based DEMATEL technique. According to the findings, “designing products for being reusable and energy efficient” is the most critical criterion and requires a considerable attention for successfully implementing environmental sustainability innovation. This paper significantly helps industrial managers and experts in emerging economies to better understand environmental sustainability innovation, employ environmental sustainability innovation practices in their supply chains and shift their industry towards sustainable development

Analyzing the Interactions Among the Challenges to Circular Economy Practices

The concept of circular economy (CE) significantly lessen the waste and environment pollution. A growing number of articles support the need to consider implementing CE within supply chains. Unfortunately, most corporations have not been successful in pursuing this goal, greatly due to existence of several challenges. Up to now, limited articles have analyzed the challenges to CE practices in the leather sector context. To address this issue, this paper introduces a decision support framework for investigating the interdependencies among challenges to CE practices in the leather industry context using Rough-based Decision-Making Trail and Evaluation Laboratory (Rough DEMATEL) technique. According to the results of the study “lack of financial support from authorities” is the most pressing challenge that impede CE implementation. Findings can assist industrial decision-makers to focus on the challenges to CE practices and employ effective strategies and solutions for moving the leather industry towards sustainable development