Sustainable performance in SMEs using big data analytics for closed-loop supply chains and reverse omnichannel

The study aims to examine the advantages of utilizing big data analytics (BDA) on circular economy (CE) dual systems, which are closed-loop supply chain (CLSC) and the reverse omnichannel (ROC), aiming to enhance sustainable firm performance (SFP) of the small and medium based enterprises (SMEs). The product return knowledge (PRK) can reinforce the proposed network of relationships and facilitate the approach of active returns in CE. Using the structural equation model (SEM) in AMOS v24, the researchers examined the hypotheses using data from a simple random sample of 232 SMEs in Pakistan. Though ROC solutions provide rare performance-related benefits, however, BDA makes the CE system more efficient. CLSC gets strengthened when the PRK is developed. The improved PRK facilitates the CLSC network and enhances its performance. This study adopts a novel approach to studying CE by considering the dual system of CE in the forms of CLSC and ROC. The research investigates whether the BDA facilitates improved product return processes by improving CLSC operations and achieving service capabilities using ROC. Finally, the proposed framework is the first to investigate the benefits evolving from the PRK, which enhance the capability to sense, seize, and reconfigure the process and facilitate the approach of active return in CE. The findings suggest that firms must decide carefully between CLSC and ROC. Choosing CLSC requires higher operational capabilities, whereas deciding on ROC requires higher service capabilities. Lastly, PRK is necessary for achieving the firm's performance objectives.

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Publication Details

Journal
Heliyon
Published
2024-08-01
DOI
https://doi.org/10.1016/j.heliyon.2024.e36237
Citations
29
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
15.33

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article

Sustainable performance in SMEs using big data analytics for closed-loop supply chains and reverse omnichannel

Adnan Ahmed Sheikh, Muhammad Tahir, Syed Abdul Rehman Khan
29 citations
Heliyon
Big Data and Business Intelligence
15.33
article

Sustainable performance in SMEs using big data analytics for closed-loop supply chains and reverse omnichannel

Adnan Ahmed Sheikh, Muhammad Tahir, Syed Abdul Rehman Khan
article en
29 citations

Abstract

The study aims to examine the advantages of utilizing big data analytics (BDA) on circular economy (CE) dual systems, which are closed-loop supply chain (CLSC) and the reverse omnichannel (ROC), aiming to enhance sustainable firm performance (SFP) of the small and medium based enterprises (SMEs). The product return knowledge (PRK) can reinforce the proposed network of relationships and facilitate the approach of active returns in CE. Using the structural equation model (SEM) in AMOS v24, the researchers examined the hypotheses using data from a simple random sample of 232 SMEs in Pakistan. Though ROC solutions provide rare performance-related benefits, however, BDA makes the CE system more efficient. CLSC gets strengthened when the PRK is developed. The improved PRK facilitates the CLSC network and enhances its performance. This study adopts a novel approach to studying CE by considering the dual system of CE in the forms of CLSC and ROC. The research investigates whether the BDA facilitates improved product return processes by improving CLSC operations and achieving service capabilities using ROC. Finally, the proposed framework is the first to investigate the benefits evolving from the PRK, which enhance the capability to sense, seize, and reconfigure the process and facilitate the approach of active return in CE. The findings suggest that firms must decide carefully between CLSC and ROC. Choosing CLSC requires higher operational capabilities, whereas deciding on ROC requires higher service capabilities. Lastly, PRK is necessary for achieving the firm's performance objectives.

HeliyonVol. 10(16)
Xuzhou University of Technology (CN), COMSATS University Islamabad (PK), University of Buraimi (OM), Air University (PK)
National Natural Science Foundation of China
Openalex Percentile: Top 1%
Big Data and Business Intelligence
15.33
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