Reflecting on theory development in sustainable supply chain management

Seuring, Stefan; Aman, Sadaf; Hettiarachchi, Biman Darshana; Lima, Felipe Alexandre de; Schilling, Lara; Sudusinghe, Jayani Ishara

doi:10.1016/j.clscn.2021.100016

Cited by 70 publications

(48 citation statements)

References 113 publications

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“…We also corroborate research that found out that coordinating related capabilities under ROT remains key to achieve sustainable and competitive advantages and that sustainability has been understudied in these contexts ( Feizabadi et al, 2019 ). Our study's contributions answer calls made from other researchers for further theorizing in SSCM in order to elucidate and explain SCM phenomena toward economic, environmental, and social sustainability ( Seuring et al, 2022 ).…”

Section: Discussionmentioning

confidence: 71%

“…The country's economic growth and infrastructure development has also led to several undesirable social impacts ( Waroux et al, 2019 ), which raises concerns with sustainability in this sector and the necessity to go beyond environmental performance and assess social and financial performance as well. This study answers calls for more research on the environmental, financial, and social impacts of agricultural supply chains, especially in emerging economies, in an integrated manner ( Dung et al, 2020 ; Matzembacher and Meira, 2019 ; Seuring et al, 2022 ). Since sustainable SCM initiatives are context-specific, this study contributes to identifying pathways to achieve sustainability ( Jia et al, 2018 ).…”

Section: Discussionmentioning

confidence: 87%

“…Moreover, Chowdhury et al (2021) identified a lack of empirically designed and theoretically grounded studies in the field. Finally, previous studies on SSCM have not performed a thorough analysis of supply chain areas, sometimes excluding areas like transport, logistics or reverse logistics ( Seuring et al, 2022 ; Seuring and Müller, 2008 ).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Transition to a sustainable food supply chain during disruptions: A study on the Brazilian food companies in the Covid-19 era

Ardekani

Sobhani²,

Barbosa

et al. 2023

International Journal of Production Economics

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Section: Discussionmentioning

confidence: 71%

Section: Discussionmentioning

confidence: 87%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Transition to a sustainable food supply chain during disruptions: A study on the Brazilian food companies in the Covid-19 era

Ardekani

Sobhani²,

Barbosa

et al. 2023

International Journal of Production Economics

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“…From the SC concept and sustainability, this study has looked into Sustainable Supply Chain Management (SSCM), which is a concept of management of material, information, capital flow and collaboration among companies in the SC aiming to achieve sustainability by considering the economic, environmental and social aspects [28]. For example, Beske [20] proposed three more variables to complement the SC capabilities-knowledge assessing and collaborationproposed by Defee and Fugate [21].…”

Section: Introductionmentioning

confidence: 99%

Supply Chain Capabilities to Improve Sustainability Performance of Product-Service Systems

Dewi¹,

Hermanto²

2022

IJSDP

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This study aims to investigate the supply chain (SC) capabilities required for manufacturers, intermediaries and service partners to improve the Sustainability Performance of Product–Service Systems (SPOPSS). A considerable challenge faced by the SC is how manufacturers collaborate with intermediaries and service partners to develop SC capabilities in order to improve SPOPSS. This paper presents a conceptual framework using dynamic capabilities theory for investigating the relationship between SC capabilities and SPOPSS. By qualitative approach through semi-structured interviews with six senior managers from four motorcycle companies–manufacturers and intermediaries, the conceptual framework was validated using thematic analysis. This study identified six SC capabilities: collaboration, partner development and knowledge transfer, innovative service delivery, reflexive control, re-conceptualisation and sustainable product–service capability to improve SPOPSS, also identified microfoundation of dynamic capabilities for each six SC capabilities. The findings proposed two significant contributions to the body of knowledge; first, by developing six identified SC capabilities to improve SPOPSS; and second, by presenting qualitative empirical evidence on how these SC capabilities’ development is inseparable from the SC and could be interactively transferred from manufacturers through intermediaries to a network of service partners.

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“…It creates unprecedented wealth and highspeed economic growth in human history. With the deterioration of the ecological environment and the further aggravation of the natural resource shortage, enterprises begin to think about how to realize the sustainable development of energy [1]. The increasingly serious environmental problems have forced enterprises to reexamine their production mode and increase the capital investment in green production to reduce the damage to the environment [2].…”

Section: Introductionmentioning

confidence: 99%

Inventory Management Optimization of Green Supply Chain Using IPSO-BPNN Algorithm under the Artificial Intelligence

Guan

Yingli

Qin

2022

Wireless Communications and Mobile Computing

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This exploration is aimed at reducing the waste of resources in the supply chain inventory management and provide better services for green supply chain management. It mainly proposes a backpropagation neural network (BPNN) model based on improved particle swarm optimization (IPSO) (IPSO-BPNN) and applies it to inventory management prediction. First, the important technologies of green supply chain and intelligent supply chain are analyzed from the perspective of the ecological environment. Next, the particle swarm optimization (PSO) algorithm is optimized based on the adaptive improvement of the learning factor and the addition of the speed mutation operator. Then, it is applied to the learning and training of BPNN. Finally, the simulation experiment of the combination model is conducted. The application fields of the combination model are analyzed. The results show that a single BPNN model will produce large errors in the training process. The final error of BPNN using the traditional PSO algorithm is 0.0259, while the error of BPNN optimized by IPSO is 0.0163. The optimized combination model has higher accuracy, better performance, and the lowest error rate. The classification error rate of its training set and test set is 1.51 and 2.16, respectively. The mean square error of the training set is 0.0163 and that of the test set is 0.0229. Under 6 ~ 12 different hidden nodes, the daily measurement model error and monthly measurement model error are both low when the number of nodes is 11. Moreover, the training set is always better than the test set. Finally, the network structure of the combination model is determined as the structure of 6-11-1. This prediction module will provide purchase volume suggestions and inventory volume suggestions to provide a feasible direction for the green development of inventory management.

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Reflecting on theory development in sustainable supply chain management

Cited by 70 publications

References 113 publications

Transition to a sustainable food supply chain during disruptions: A study on the Brazilian food companies in the Covid-19 era

Transition to a sustainable food supply chain during disruptions: A study on the Brazilian food companies in the Covid-19 era

Supply Chain Capabilities to Improve Sustainability Performance of Product-Service Systems

Inventory Management Optimization of Green Supply Chain Using IPSO-BPNN Algorithm under the Artificial Intelligence

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