Modelling The Cost of Transportation and Distribution of Food Commodities in the South-West, Nigeria

Abstract

Food security remains a critical global challenge, particularly in developing nations where agricultural productivity, transportation, road infrastructure, and distribution systems are often inadequate or impeded by social, environmental, and infrastructural challenges. This study focused on modeling the costs of transportation and distribution of agricultural produce in South-West Nigeria. The South-West region of Nigeria comprises six (6) states: Lagos, Ogun, Oyo, Osun, Ekiti, and Ondo. Three of the six (6) states that constitute the South-West region were purposively selected for the study based on rurality, vegetation type, presence of rural markets, and prevalence of farming activities. The selected states for the study include Oyo, Osun, and Ekiti. Primary data were obtained through the administration of a structured questionnaire using the purposive-random sampling technique. One Thousand Two Hundred (1,200) copies of the structured questionnaire were administered using the Dillman (2014) formula. One Thousand One Hundred and Twelve (1,112) representing 92.6% of the returned questionnaires were adjudged suitable for the study. The data obtained were analyzed using both descriptive and Inferential Statistics. The findings show that youths constitute (30.8%) of the respondents, and are between the ages of 35and 45 who are actively involved in the transportation of food commodities.Among transport service providers, 33.50% had 6-10 years of experience in transport service operations. Bad rural roads accounted for 13.80% of the challenges in transporting agricultural produce in the region, followed by high energy prices (13.360%), seasonal road disruption (12.60%), and traffic congestion (11.46%). All these challenges have hindered the efficient flow of the agricultural distribution chain. The result of Multiple Linear Regression (MLR)indicates that the combined effect of all predictors on transportation and distribution cost was statistically robust and not attributable to random variation.