DEMAND MANAGEMENT AND PERFORMANCE OF FOOD AND BEVERAGE MANUFACTURING FIRMS IN KENYA
Main Article Content
Abstract
The food and beverage supply chain is a complex network influenced by perishability, fluctuating demand, and distribution challenges. Effective demand management plays a critical role in ensuring timely delivery, reducing customer complaints, and improving operational efficiency. Despite the significant impact of demand management on supply chain performance, Kenya’s food and beverage manufacturing sector continues to experience stagnated growth. The Kenya Association of Manufacturers (KAM) has highlighted concerns over declining performance, which threatens economic development and the realization of Vision 2030. This study investigates the relationship between demand management and the performance of food and beverage manufacturing firms in Kenya. The research evaluates demand planning strategies, forecasting techniques, and their impact on production efficiency, inventory levels, and overall supply chain responsiveness. The study is grounded in Institutional Theory. Using a descriptive research design, the study collected both qualitative and quantitative data from 217 food and beverage firms, targeting logistics and procurement managers. A sample size of 208 respondents was determined using Yamane’s Formula and selected through simple random sampling. Data was gathered using structured and unstructured questionnaires, with qualitative responses analyzed using content analysis and quantitative data processed through descriptive statistics techniques. Pearson R correlation and regression models were applied to assess the strength and direction of relationships between demand management strategies and firm performance. The findings indicate that demand management significantly influences the performance of food and beverage firms, with effective forecasting and inventory control leading to cost reductions, improved service levels, and minimized supply chain disruptions. The study also concludes that customer response plays a moderating role in the relationship between demand management and supply chain performance. The research provides critical insights into the necessity of robust demand planning to enhance efficiency, reduce wastage, and boost competitiveness in Kenya’s food and beverage industry.
Key Words: Demand Management, Bullwhip Effect, Supply Chain Performance, Food and Beverage Industry
Article Details
How to Cite
References
Agrawal, S., Sengupta, R. N., & Shanker, K. (2019). Impact of price fluctuations and lead time on bullwhip effect and on-hand inventory. European Journal of Operational Research, 192(2), 576-593.
Atieno, R., & Karuti, S. (2019). The complexities of food and beverage supply chains: Challenges and inefficiencies. African Journal of Business and Economics, 14(1), 45-61.
Alhawari, O. I., Gürsel, A., Süer, G. A., Khurrum, M., & Bhutta, S. (2021). Operations performance considering demand coverage scenarios for individual products and product families in supply chains. International Journal of Production Economics, 233, 108012. https://doi.org/10.1016/j.ijpe.2020.108012
Baganha, M., & Cohen, M. (2011). The stabilizing effect of inventory in supply chains. Operations Research, 2(4), 72–83.
Barratt, M. (2020). Understanding the meaning of collaboration in the supply chain. Supply Chain Management: An International Journal, 9(1), 30-43.
Bray, R. L., & Mendelson, H. (2016). Information transmission and the bullwhip effect: An empirical investigation. Management Science, 58(5), 860–875.
Buchmeister, B., Pavlinjek, J., & Palcic, I. (2021). Bullwhip effect problem in supply chains in Slovenia. Advances in Production Engineering & Management Journal, 16(2), 102-116.
Caplin, S. (2019). The variability of aggregate demand with (S, s) inventory policies. Econometrica, 3rd edition, 5(9), 1396-1409.
Caroll, V., & Rao, A. G. (2018). Implications of Salesforce productivity, heterogeneity, and demotivation: A Navy recruiter case study. Management Science, 32(11), 1371 - 1388.
Chen, L., & Lee, H. L. (2016). Bullwhip effect measurement and its implications. Operations Research, 60(4), 771–784.
Chen, J. (2019). Inventory management in food and beverage manufacturing firms: A review of best practices. Journal of Supply Chain Management, 14(3), 115-132.
Chent, F., Drezner, Z., Jennifer, K., & Simchi-Levi, D. (2016). The bullwhip effect: Managerial insights on the impact of forecasting and information on variability in a supply chain. Department of Decision Sciences, National University of Singapore.
Chopra, S., & Meindl, P. (2017). Supply chain management: Strategy, planning, and operations (3rd ed.). Pearson.
Disney, S. M. (2018). Supply chain aperiodicity, bullwhip, and stability analysis with jury’s inners. IMA Journal of Management Mathematics, 19(2), 101–116.
Erkan, B., Lenny, K. C., & Ekrem, T. (2018). The role of forecasting on bullwhip effect for ESCM application. International Journal of Economics, 113(1), 3-12.
Fransoo, J., & Wouters, M. (2019). Measuring the bullwhip effect in the supply chain. Supply Chain Management, 2(8), 78–89.
Furusten, S. (2013). Institutional theory and organizational change. Edward Elgar Publishing.
Goga, K. R. (2023). Effect of organizational structure on the performance of state corporations in Kenya. Economit Journal: Scientific Journal of Accountancy, Management and Finance, 3(1), 1-15. https://doi.org/10.33258/economit.v3i1.845
Hunt, T., & Kern, M. (2016). Dysrhythmia: The end of the old US dairy price cycle. Rabobank Industry Note 335.
Jack, G., Carlos, A., & Jacques, H. (2018). Agro-industrial supply chain management: Concepts and applications. Food and Agriculture Organization of the United Nations.
Jennings, D. (2019). Research methods in business studies: A practical guide (6th ed.). Pearson.
Kelly, K. (2019). Burned by busy signals: Why Motorola ramped up production way past demand. Business Week, 6(3), 36.
Kiplagat, N. K. (2024). Influence of demand forecasting system on performance of manufacturing firms in Kenya. Journal of Procurement & Supply Chain, 8(2), 36-47. https://doi.org/10.53819/81018102t4251
Kothari, C. R. (2019). Research methodology: Methods and techniques (4th ed.). New Age International.
Mugenda, O. O., & Mugenda, A. G. (2020). Research methods: Qualitative and quantitative approaches. African Center for Technology Studies, ACTS Press.
Neuman, W. L. (2016). Social research methods: Qualitative and quantitative approaches (7th ed.). Pearson.
Rajani, R. L., Heggde, G. S., Kumar, R., & Bangwal, D. (2022). Demand management approaches in the services sector and influence on company performance. International Journal of Productivity and Performance Management, 1(3), 14-27. https://doi.org/10.1108/IJPPM-02-2022-0080
RoK (Republic of Kenya). (2015). Kenya Vision 2030: A blueprint for industrialization and economic growth. Government Press.
Saremi, H., & Zadeh, M. (2019). Management of distribution channels in perishable supply chains. Indian Journal of Science Resources, 5(3), 452-456.
Silver, E. A., Pyke, D. F., & Peterson, R. (2021). Inventory management and production planning and scheduling (3rd ed.). John Wiley & Sons.
Songet, J. (2020). Inventory control in food manufacturing firms: Balancing demand and supply. Journal of Operations and Supply Chain Management, 8(2), 103-121.
Sterman, J. D. (2019). Modeling managerial behavior: Misperceptions of feedback in a dynamic decision-making experiment. Management Science, 4(3), 321-339.
Trapero, J. R., Kourentzes, N., & Fildes, R. (2016). Impact of information on supplier forecasting performance. Omega.
Vollmann, T. E., Berry, W. L., Whybark, D. C., & Jacobs, F. R. (2019). Manufacturing planning and control for supply chain management. McGraw-Hill.
Whang, S., Lee, H., & Padmanabhan, V. (2016). The bullwhip effect in supply chains: Procter & Gamble case study. Sloan Management Review, 38(3), 93-102.
World Bank. (2021). Kenya Economic Update: Assessing the impact of manufacturing sector stagnation on economic growth.
Yang, H. C., & Sheu, C. (2011). Institutional pressures and performance in the global supply chain: The moderating effect of network ties. International Journal of Production Economics, 133(1), 16-26.
Yamane, T. (1997). Statistics: An introductory analysis (2nd ed.). Harper & Row.
Yigitbasioglu, O. (2019). Price fluctuations and demand management in food supply chains. International Journal of Physical Distribution and Logistics Management, 40(7), 550-578.
Zipkin, P. H. (2019). Foundations of inventory management. McGraw-Hill.