Supply chain network design considering carbon footprint, water footprint, supplier’s social risk, solid waste, and service level under the uncertain condition

Das, Rakhi; Shaw, Krishnendu; Irfan, Mohd

doi:10.1007/s10098-019-01785-y

Cited by 25 publications

(21 citation statements)

References 94 publications

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“…A green supply chain management (GSCM) integrates environmental concerns such as waste, pollution, and emissions into supply chain management practices (Sarkis, 2012). Mishra et al (2020) investigated carbon emissions and solid waste from end-of-life goods, while Das et al (2020) considered water footprint and supplier's social risk, and developed a holistic sustainable supply chain. In literature, many quantitative and qualitative management tools can be used in modelling and developing a green supply chain (Tundys, 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

Three-Echelon Green Supply Chain Inventory Decision for Imperfect Quality Deteriorating Items

Daryanto

Wee

2020

OSCM: An Int. Journal

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Section: Literature Reviewmentioning

confidence: 99%

Three-Echelon Green Supply Chain Inventory Decision for Imperfect Quality Deteriorating Items

Daryanto

Wee

2020

OSCM: An Int. Journal

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“…Examples of sustainability initiatives delivering a significant amount of cost savings to businesses are working on energy efficiency, consuming resources more efficiently, adopting the right design and packaging, transport planning, etc. Businesses across the world are actively managing their carbon footprint and water footprint to not only gain on financial returns but also enhancing their reputation as a socially responsible organization (Das et al , 2020; Forin et al , 2020; Yang et al , 2020; Zheng and Suh, 2019; He et al , 2019). CSR engagement by many large size corporations has resulted in huge cost savings for them (Babiak and Trendafilova, 2011).…”

Section: Literature Reviewmentioning

confidence: 99%

Corporate social responsibility motives of Indian firms

Dixit¹,

Verma

Priya³

2021

JM2

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Purpose The purpose of this paper is to explore the motives of Indian firms for engaging with corporate social responsibility (CSR) practices and their interplay by using interpretive structural modelling methodology (ISM) and Matrice d’impacts croisés multiplication appliquée á un classment (MICMAC) analysis. Design/methodology/approach The research uses ISM and Matrice d’impacts croisés multiplication appliquée á un classment (MICMAC) analysis to find the structural relationship among the CSR motives of the Indian firms identified from the past literature and agreed upon by the experts. Findings The ISM model indicates that firms primarily engage in CSR either because of top management commitment to certain values, to meet the legal mandate or of the pressure from the NGOs. The top management commitment gives a strategic orientation to CSR, which results in community engagement by the firm as one of the important components of the strategy. The community engagement helps in engaging with its employees and investors along with finding sources of innovations, which, in turn, help the firm in engaging its customers, managing corporate reputation and getting a cost advantage. Collectively, these help them in improving their financial performance. However, the model highlights two autonomous sources, meeting legal mandate and pressure from NGOs also motivate firms to engage in CSR without having any strategic thought or engagement with its strategic system. Originality/value The study provides a comprehensive listing of CSR motives of Indian firms along with the structural relationships among the identified CSR motives. The model developed provides CSR professionals and policymakers an understanding of the primary CSR motives along with their driving power and dependence. This insight will help them in manipulating these motives for better CSR engagement by the Indian firms.

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“…Although social sustainability is an integral part of a business, as of now, it is being handled at the lowest priority for ordering policy (Staniškienė 2018). The importance of social sustainability for the supply chain has been illustrated in studies of Das and Shaw (2017) and Das et al (2020). Suppliers can be viewed as the backbone of the original equipment manufacturer (OEM).…”

Section: Importance Of Social Sustainability For Lot-sizingmentioning

confidence: 99%

Joint Multi-item Multi-supplier Sustainable Lot-sizing Model Applying Combined BWM, TOPSIS, Possibilistic Programming, and ε-constraint Method

Shaw

Lahri

Shankar

2021

Preprint

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Procurement decisions play a vital part in the sustainable transformation of the supply chain. Till now, a variety of supplier selection and lot-sizing models have been suggested, in particular, focusing on carbon emissions in a deterministic environment. It is noted that stressing only on carbon emissions cannot fully transform a sustainable supply chain. The present study argues that with carbon footprint, other dimensions, such as social sustainability, water footprint, recycled material use, solid and liquid waste, need to be considered in sustainable procurement decisions. To fill the gaps, this study proposed a three-stage multi-objective multi-supplier, multi-period joint supplier selection, and a lot-sizing model, taking into account carbon footprint, water footprint, solid and liquid waste, and use of recycled materials in a stochastic environment. The model optimizes three objectives (cost, carbon emission, and social sustainability). The model considers different model parameters as uncertain, such as costs, emission, solid waste, liquid waste, recycled material, quality rejection, and capacity. The present study suggests how to quantify social sustainability and further use it in the lot-sizing model. The proposed study has been carried out in three stages. In the first stage, BWM (Best-Worst method) and TOPSIS are applied to evaluate suppliers' social scores. In the second stage, the suppliers' social scores are used in the proposed possibilistic lot-sizing model. In the third stage, various trade-off curves are generated by applying the ε-constraint method. The model produces distinct optimal solutions for different uncertainty levels, which are used to create trade-off curves among the cost, emission, and social dimensions. The results facilitate decision-makers to decide the lot-size in an ambiguous environment.

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Supply chain network design considering carbon footprint, water footprint, supplier’s social risk, solid waste, and service level under the uncertain condition

Cited by 25 publications

References 94 publications

Three-Echelon Green Supply Chain Inventory Decision for Imperfect Quality Deteriorating Items

Three-Echelon Green Supply Chain Inventory Decision for Imperfect Quality Deteriorating Items

Corporate social responsibility motives of Indian firms

Joint Multi-item Multi-supplier Sustainable Lot-sizing Model Applying Combined BWM, TOPSIS, Possibilistic Programming, and ε-constraint Method

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