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Performance analysis with structural equation modelling among food cold chain operators in Ibadan

Adeyinka Peter Ajayi

International Journal of Logistics Systems and Management2026https://doi.org/10.1504/ijlsm.2026.152610article
AJG 1
Weight
0.50

What the paper says

This research provides insight into how the utilisation of supply chain management concepts and nascent technologies aided the achievement of cold supply chain performance (CSCP) among retailers of protein (fish and meat) in Ibadan, a Sub-Saharan Africa metropolis. Research hypotheses investigating the possibility of the causal effects between identified SCM concepts [achievement of standardisation in quality (AOS), financial system practices (FSP), internet of things (IoT), internal supply chain practices (ISP), just-in-time (JIT), ownership structure (OS), quality control system (QCS)], and CSCP are formulated and tested using a structural equation modelling approach. A systematic random sampling technique was used to choose four categories of retailers of protein in the study area (hypermarkets, supermarkets, franchisees, and cold room operators). The results showed that there were statistically significant impacts of AOS, FSP, JIT, and, OS on CSCP. The research emphasised the role of corporate governance in the achievement of CSCP among FCC retailers.

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https://doi.org/https://doi.org/10.1504/ijlsm.2026.152610

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@article{adeyinka2026,
  title        = {{Performance analysis with structural equation modelling among food cold chain operators in Ibadan}},
  author       = {Adeyinka Peter Ajayi},
  journal      = {International Journal of Logistics Systems and Management},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1504/ijlsm.2026.152610},
}

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Performance analysis with structural equation modelling among food cold chain operators in Ibadan

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.