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Organizational and managerial decisions are influenced by corporate sustainability pressures. Organizations 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 organizational good and service outputs sustainability. Sustainable supplier selection influences the supply chain sustainability allowing many organizations 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 organizational 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 DecisionMaking") is introduced. A grey-BWM approach is used to determine social sustainability attribute weights, and a grey-TODIM method is utilized 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 application of the model.

The coronavirus (COVID-19) pandemic has undeniably influenced the global economy and environment. Major victims of the COVID-19 outbreak are Micro and Small Enterprises (MSEs), especially in developing countries, mainly because of limited use of digital technologies. This paper employs a literature review and personal insights to provide COVID-19 pandemic digitization lessons for sustainable development of MSEs from a technology for social good perspective. We develop a framework to support post COVID-19 digital transformation for sustainable development of MSEs. We find that digital payments, especially mobile money, should be a critical digital transformation priority for MSEs. Also, institutions must support MSE resources and capabilities to adopt digital transformation for business continuity, and sustainable production and consumption. Our study suggests that MSE managers and other stakeholders rethink their business strategies, incorporating crisis scenarios and business continuity plans to sustain customers virtually to enhance sustainable development. We also propose further research areas to improve the successful digital transformation of MSEs post COVID-19.

Purpose -The purpose of this paper is to introduce a methodology to help evaluate, select, and monitor sustainable supply chain performance measurement that can be integrated into a performance management system (PMS). Design/methodology/approach -Grey-based neighborhood rough set theory is used to help arrive at a core set of important business and environmental performance measures for sustainable supply chains. The supply chain operations reference (SCOR) model is used to develop both business and environmental measures for supply chain sourcing. Findings -A case illustration shows the applicability of the methodology. A sensitivity analysis shows that variations in outcome considerations may greatly influence the set of key performance measures for a sustainable supply chain PMS.Research limitations/implications -The methodology and presentation is conceptual, yet the tool can provide very useful interpretations for both researchers and practitioners. Practical implications -The tool can be valuable for companies that are trying to identify key environmental and business performance measures for their supply chains. It helps save resources by not requiring the management of a burdensome and complex set of performance measures. Originality/value -This is one of the few approaches that helps to clearly identify and narrow the set of performance measures for sustainable supply chains. It attempts to do so with minimal information loss. It is also the first time that grey techniques have been integrated with neighborhood rough set methodology.