Locating Consolidation Centres For Aggregation of Subsistence Agricultural Products From The Southwestern Region of Nigeria

Yıl 2022, , 405 - 430, 16.01.2023

Sulaimon Adebiyi Jonathan Ekpudu Olamide Awe

https://doi.org/10.26650/JTL.2022.1067686

Öz

The purpose of this study is to improve agriculture product supply capacity in a way that is beneficial for subsistence farmers and consolidators in the southwestern region of Nigeria. Data gathered includes the distance travelled between various locations, units demanded, and fixed and variable costs. The data were presented on Google maps and evaluated using Weber, Centre of Gravity (CoG), and Mixed Integer Linear Program (MILP) methods. Software deployed for analysis were Microsoft 2013-Excel Solver, and Statistical Analysis System (SAS). The Weber and CoG methods yielded similar results that the consolidation centre should be located at the Oshodi area of Lagos State to minimise distance travelled. However, the MILP model suggested that opening consolidation centres at the Mushin area of the Southwest region generated the optimal outcome in terms of cost and distance travelled to market and customers. The novelty of the developed model is that it provides alternative location candidates that can be critically explored in practical location decisions. Hence, the model is a support tool applicable by managers of agricultural businesses in their decision to establish consolidation centres in such a manner that minimises cost and distance travelled to meet customer and market demand.

Anahtar Kelimeler

Location, Consolidation Center, Agricultural Products, Transportation, Facility

Kaynakça

• Adebayo, A. (2020). Migration and sustainable development in southwestern Nigeria, International Journal of Social Sciences and Humanities Reviews, 10 (2), 224 – 240,
• Adeniran, A.O., & Oladun, E.A. (2020). The implication of transport development models on agricultural development in Nigeria: An empirical review. Open Journal of Economics and Commerce, 3(2), 28-41.
• Adeniyi, O.R. (2013). Socio-economic analysis of subsistence farming practices in south-western Nigeria, Sustainable Agriculture Research, 2(1), 104-111.
• Adsida, I, R., Nkomoki, W., Bavorova, M., & Madaki, M.Y. (2021). Effects of agricultural programmes and land ownership on the adoption of sustainable agricultural practices in Nigeria, Sustainability, 13 (1), 1-16.
• African Economic Outlook, (2020). Developing Africa’s Workforce for the Future, African Economic Outlook, 11-206.
• Agbonlahor, M.U., & Philip, D.O. (2015). Deciding to settle: rural-rural migration and agricultural labour supply in southwest Nigeria, The Journal of Developing Areas, 49(1), 267-284.
• Anzaku, E.D., & Charles, A. (2022). Agricultural transformation and economic growth in Nigeria economy, Lafia Journal of Economics and Management Sciences, 3 (1), 1-19.
• Apata, T.G., Folayan, A., Apata, O.M., & Akinlua, J. (2011). The economic role of nigeria’s subsistence agriculture in the transition process: implications for rural development, 85th Annual Conference of the Agricultural Economics Society Warwick University, 1-10.
• Caizza, R. Volpe, T., & Stanton, J.L. (2015). Global supply chain: The consolidators’ role, Operations Research Perspectives 3, 1–4.
• Disney, S. (2008). Supply chain aperiodicity, bullwhip and stability analysis with Jury’s inners. IMA Journal of Management Mathematics. 19(2), 101–116.
• Ellet, S (2012). Using freight market intelligence to focus your ocean freight strategy. Chain Analytics, 1-28.
• Emidio, J., Lima, R., & Madrona, G.L, (2021). How can mixed integer linear programming assist dairy manufacturers by integrating supply decisions and production planning? Journal of Agribusiness in Developing and Emerging Economies, 11(2), 178-193.
• Fan, S., Brzeska, J., Keyer, M & Halsema, A. (2013). From subsistence to profit: transforming smallholder farms, food policy report: International Food Policy Research Institute., 1-30.
• Fearon, D. (2002). Alfred Weber: Theory of the location of industries, center for spatially Integrated Social Science, 1, 1-5.
• Food and Agriculture Organization of the United Nations (2018). Sustainable agriculture for biodiversity: Biodiversity for sustainable agriculture. Food and Agriculture Organization of the United Nations, 1-48.
• Forrester, Jay Wright (1961). Industrial Dynamics. MIT Press
• Gaal, O.H, & Afrah, A. (2017). Lack of infrastructure: the impact on economic development as a case of Benadir region and Hir-shabelle, Somalia, Developing Country Studies, 7(1), 49-55.
• Gbatsoron, A., & Raymond, A. (2017). An economic analysis of Dutch disease in Nigeria. CARD International Journal of Management Studies, Business & Entrepreneurship Research. 2(1) 75-90.
• Hanifha, N.H., Ridwan, A.Y, & Suksessanno, P.M. (2020). Site selection of new facility using gravity model and mixed integer linear programming in delivery and logistic company, Asia Pacific Conference on Research in Industrial and Systems Engineering (APCoRISE), 43-47. DOI: 10.1145/3400934.3400944,
• Hoberg, K.; Thonemann, U. (2014). Modeling and analyzing information delays in supply chains using transfer functions, International Journal of Production Economics. 156, 132–145.
• Islam, M.K., Uddin, M.F., Alam, M.M., & Faruque, M.O (2019). A mixed integer linear programming approach for two stage supply chain network coordination of agricultural products considering uncertainty, International Journal in Mathematical and Statistical Sciences, 6 (6), 36-45.
• Kano, I.S., Lengyel, B. Elekes, Z., & Lengel, I. (2019). Agglomeration, foreign firms and firm exit in regions under transition: the increasing importance of related variety in Hungary, European Planning Studies, 27(11), 2099-2122.
• Kim, B. (2018). Agricultural value creation through effective supply chain management, Current Investigations in Agriculture and Current Research, 2(2), 180-183.
• Lee, H.; Padmanabhan, V. Whang, S. (1997). Information distortion in a supply chain: The bullwhip effect. Management Science. 43 (4), 546–558.
• Ntihinyurwa, P.D., & de Vries, W.T. (2021). Farmland fragmentation, farmland consolidation and food security: relationships, research lapses and future perspectives, Land Journal, 10, 2-39.
• Nurdin, N, Zarlis, M., Tulus. S., & Efendi, S. (2020). Mixed integer linear programming model for integrated fish supply chain planning, Journal of Theoretical and Applied Information Technology, 98(12), 1-12.
• Nwangwu, G. (2019). Improving agriculture in Nigeria through public-private partnerships, African Journal of Business Management, 13(8), 256-263
• Olayemi, S.S., Oko, A.A., & Oduntan, F.T. (2020). Adoption of appropriate good agricultural practices (GAPs) technologies among smallholder farmers in Nigeria, International Journal of Agricultural Research, Sustainability, and Food Sufficiency, 7, (2) 447- 458.
• Onakuse, S. (2012). The future of subsistence agriculture in the rural community of Uzanu, Edo state, Nigeria, Journal of Agriculture, Food Systems, and Community Development, 3(1), 61-71.
• PricewaterhouseCoopers, PWC, (2017). Transforming Nigeria’s agricultural value chain: A case study of the Cocoa and Dairy industries, Retrieved from: www.pwc.com/ng
• Simiyu, A.J. (2020). Strategic Positioning and Competitive Advantage at G4S Kenya, International Journal of Innovative Social Sciences & Humanities Research 8(4), 1-19.
• Wang, X & Disney, S.M. (2016). The bull whip effect: progress, trends and directions. European Journal of Operational Research, 1(2), 691-701
• Weber, A. (1909). Theory of the location of industries. Chicago: University of Chicago Press.
• Zarini, F.G., & Javadian, N.J., (2020). A multi objective mixed integer programming model for design of a sustainable meat supply chain network, Journal of Industrial and Systems Engineering, 13(16), 78-92.