TY - JOUR
T1 - Unearthing the interplay between organisational resources, knowledge and industry 4.0 analytical decision support tools to achieve sustainability and supply chain wellbeing
AU - Vann Yaroson, Emilia
AU - Chowdhury, Soumyadeb
AU - Mangla, Sachin Kumar
AU - Dey, Prasanta
N1 - Funding Information:
The research reported in this manuscript is funded by \u201CBritish Council Environmental Links Grant\u2014528201836\u201D for the project, \u2018Circular Economy Knowledge Hub: Promoting Multi-Disciplinary Research, Capacity Building and Leadership\u2019.
Funding Information:
Emilia Vann Yaroson declares no conflicts of interest. Soumyadeb Chowdhury has received the funding from the British Council Environmental Links Grant\u2014528201836. Sachin Kumar Mangla declares no conflicts of interest. Prasanta Dey has received the funding from the British Council Environmental Links Grant\u2014528201836.
Publisher Copyright:
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
PY - 2024/11/1
Y1 - 2024/11/1
N2 - Due to increasing supply chain disruptions and stakeholder demands for more environmentally friendly business models, managers are searching for ways to ensure sustainability and supply chain performance. We propose supply chain well-being (SCWB) as a new concept that offers a more comprehensive way of managing supply networks. Similarly, the opportunities for SCWB and sustainable business performance (SBP) are facilitated through the application of Industry 4.0 (I4.0) data-driven analytical decision support systems (ADSS). In this context, our study examined the role of ADSS in fostering SBP and SCWB by integrating the theoretical perspectives stemming from organisational information processing theory (OIPT), resource-based view and the knowledge-based view. Our conceptual model was tested on 350 Vietnamese manufacturing SME managers using covariance-based structural equation modelling. The findings highlight the importance of understanding how tacit resources are generated, stored, and analysed for effectively leveraging I4.0 decision support tools. This paper contributes to the existing literature in several ways. First, we extend the supply performance literature by proposing SCWB as a more comprehensive approach to managing supply chain networks. We also show how ADSS can be absorbed by SMEs and extend the OIPT literature by elucidating the role of knowledge sharing, generation, and analysis for information processing capabilities. The findings offer policymakers, technology providers and practitioners to focus on information processing fit for achieving SBP and SCWB.
AB - Due to increasing supply chain disruptions and stakeholder demands for more environmentally friendly business models, managers are searching for ways to ensure sustainability and supply chain performance. We propose supply chain well-being (SCWB) as a new concept that offers a more comprehensive way of managing supply networks. Similarly, the opportunities for SCWB and sustainable business performance (SBP) are facilitated through the application of Industry 4.0 (I4.0) data-driven analytical decision support systems (ADSS). In this context, our study examined the role of ADSS in fostering SBP and SCWB by integrating the theoretical perspectives stemming from organisational information processing theory (OIPT), resource-based view and the knowledge-based view. Our conceptual model was tested on 350 Vietnamese manufacturing SME managers using covariance-based structural equation modelling. The findings highlight the importance of understanding how tacit resources are generated, stored, and analysed for effectively leveraging I4.0 decision support tools. This paper contributes to the existing literature in several ways. First, we extend the supply performance literature by proposing SCWB as a more comprehensive approach to managing supply chain networks. We also show how ADSS can be absorbed by SMEs and extend the OIPT literature by elucidating the role of knowledge sharing, generation, and analysis for information processing capabilities. The findings offer policymakers, technology providers and practitioners to focus on information processing fit for achieving SBP and SCWB.
KW - Industry 4.0
KW - Analytical Decision Support Systems
KW - Circular Economy
KW - Sustainability
KW - Supply Chain Wellbeing
KW - Knowledge Based View
KW - Organisational Information Processing
KW - Green Operations
UR - http://www.scopus.com/inward/record.url?scp=85186947838&partnerID=8YFLogxK
U2 - 10.1007/s10479-024-05845-5
DO - 10.1007/s10479-024-05845-5
M3 - Article
VL - 342
SP - 1321
EP - 1368
JO - Annals of Operations Research
JF - Annals of Operations Research
SN - 0254-5330
IS - 2
ER -