Economic Analysis of Agro-product: a Supply Chain Management in Rural communities

Green supply chain management (GSCM) has been identified as a strategy for addressing food security. Hence, this research aimed to implement a multi-criteria decision-making (MCDM) framework for the Agro-products subset of GSCM. This research objective addresses the issue of evaluating economic criteria parameters for green supply chain management for an Agro-business, through a developed multi-criteria decision framework. This research considered five Agro-products (poultry products, meat, fruits, fish, and vegetables) in the three major selected markets (Mowe-Ibafo, Arigbajo-Ifo, and Agbara-Lusada) in Ogun state, Nigeria. The economic parameters that affect Agro-products management was evaluated using a fuzzy entropy method (FEM). VIKOR model was introduced to assess the criteria's importance. VIKOR outputs indicated that meat and vegetable products are most important based on the fact that experts' opinions are the same in cases I, II, and III. Poultry products and meat are the second most important as the expert's views are the same in cases II, III, and I, II respectively. However, fish product was the least important as there was no agreement between the expert's opinions in the three cases. The information from this study is important for stakeholders in MCDM for Agro-products.

Authors

Institutions

Publication Details

Published
2024-11-26
DOI
https://doi.org/10.1109/nigercon62786.2024.10926953
Primary Topic
SMEs Development and Digital Marketing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Economic Analysis of Agro-product: a Supply Chain Management in Rural communities

Jeremiah Oludele Ojediran, Oludolapo Akanni Olanrewaju, Desmond Eseoghene Ighravwe, Sunday Thomas Ajayi et al.
SMEs Development and Digital Marketing
article

Economic Analysis of Agro-product: a Supply Chain Management in Rural communities

Jeremiah Oludele Ojediran, Oludolapo Akanni Olanrewaju, Desmond Eseoghene Ighravwe, Sunday Thomas Ajayi, Asukwu Enediabasi Etangetuk, Eloho Omijie
article en

Abstract

Green supply chain management (GSCM) has been identified as a strategy for addressing food security. Hence, this research aimed to implement a multi-criteria decision-making (MCDM) framework for the Agro-products subset of GSCM. This research objective addresses the issue of evaluating economic criteria parameters for green supply chain management for an Agro-business, through a developed multi-criteria decision framework. This research considered five Agro-products (poultry products, meat, fruits, fish, and vegetables) in the three major selected markets (Mowe-Ibafo, Arigbajo-Ifo, and Agbara-Lusada) in Ogun state, Nigeria. The economic parameters that affect Agro-products management was evaluated using a fuzzy entropy method (FEM). VIKOR model was introduced to assess the criteria's importance. VIKOR outputs indicated that meat and vegetable products are most important based on the fact that experts' opinions are the same in cases I, II, and III. Poultry products and meat are the second most important as the expert's views are the same in cases II, III, and I, II respectively. However, fish product was the least important as there was no agreement between the expert's opinions in the three cases. The information from this study is important for stakeholders in MCDM for Agro-products.

Bells University of Technology (NG), Durban University of Technology (ZA), Nigerian Meteorological Agency (NG)
Zero hunger
Openalex Percentile: Top 45%
SMEs Development and Digital Marketing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.