Supplier Collaboration and Performance of Food and Beverage Manufacturing Firms in Kenya

Authors

  • David Chogo Mulweye Jomo Kenyatta University of Agriculture and Technology
  • Dr. Noor Ismail Shale Jomo Kenyatta University of Agriculture and Technology
  • Dr. Eric Namusonge Namusonge Jomo Kenyatta University of Agriculture and Technology
  • Dr. Elizabeth Wangu Wachiuri Jomo Kenyatta University of Agriculture and Technology

DOI:

https://doi.org/10.47604/ijscm.2326
Abstract views: 68
PDF downloads: 41

Keywords:

Supplier Collaboration, Supply Chain Technology, Supply Chain Performance

Abstract

Purpose: This study sought to evaluate explored the influence of supplier collaboration on the performance of food and beverage manufacturing firms in Kenya and to find out the moderating effect of supply chain technology on the performance of food and beverage manufacturing firms in Kenya.

Methodology: The study used exploratory research design and utilized both qualitative and quantitative data in carrying out the study. This study adopted a census survey sampling which was conducted on 270 food and beverage manufacturing firms in Kenya registered by Kenya Association of Manufacturers (KAM, 2022). The target population for the research was all 270 respondents each from the food and beverage manufacturing firms. Both primary and secondary data was used, the primary data was collected using semi structured questionnaire that was administered by the researcher and research assistants. Samples of the questionnaire were pilot tested to test the reliability and validity before full scale data collection. The data was analyzed using the Statistical Package for Social Sciences (SPSS) version 26 software. Quantitative data was analyzed using descriptive statistics and presented in tables and figures. The inferential analysis was further carried out using structural equation modelling, ANOVA and regression coefficients. The results were then presented using tables, figures, graphs and charts.

Findings: Supplier collaboration significantly influenced performance of food and beverage manufacturing firms in Kenya at both without a moderator and also using the moderating variable, supply chain technology. In the first model without moderator, it recorded a standardized estimate of 0.637 (p<0.001), indicating that as supplier collaboration increases performance of food and beverage manufacturing firms also increases. Fit indices on structural equation modelling revealed a marginal fit with a chi-square test of 216.155 with 86 degrees (P-value 0.0561). The structural path for structural equation modelling from supplier collaboration to supply chain performance remains positive and significant standardized estimate of 0.855 and p-value was 0.001<0.05. Which indicates that the variability of supplier collaboration on the performance of food and beverage manufacturing firms could be explained by 63.7% when no moderator is included and increase to 85.5% when supply chain technology is incorporated thereby indicating a stronger relationship. The other fit indices that gave a satisfactory model fit are RMR=.9019, GFI= .9774, NFI= .9164, RMSEA=.0191 and CFI=.9176 this implies that the model was fit to determine the relationship between supplier collaboration and performance of food and beverage manufacturing firms in Kenya and therein make conclusions and recommendations. ANOVA, regression coefficient ant model summary (R2) were also used and indicated significance of there use all recording p-value of 0.000<0.05. 

Unique Contribution to Theory, Practice and Policy: While transaction cost theory used in this study was validated by offering cost reduction strategies like outsourcing, accurate order forecasting as increasing the organization bottom line. The study recommends that when creating a supplier collaboration portfolio, companies should pool suppliers with the same activities in one pool but to use technology to mop up suppliers with high asset specificity for components delivering competitive advantage. Meanwhile, suppliers with low asset specificity for suppliers with components which result to less competitive advantage needs to be managed as a separate line of engagement.

Downloads

Download data is not yet available.

References

Alghababsheh, Mohammad, and David Gallear. "Socially sustainable supply chain management and suppliers’ social performance: The role of social capital." Journal of Business Ethics 173 (2021): 855-875.

Alkhafaji, A., & Nelson, R. A. (2013). Strategic management: formulation, implementation, and control in a dynamic environment. Routledge.

Akbar, Y. H., & Tracogna, A. (2018). The sharing economy and the future of the hotel industry: Transaction cost theory and platform economics. International Journal of Hospitality Management, 71, 91-101.

Akintokunbo, O. P., & Akpotu, C. P. (2020) Value chain management and organizational competitiveness in the Nigerian hospitality sector.

Akter, S., & Wamba, S. F. (2016). Big data analytics in E-commerce: a systematic review and agenda for future research. Electronic Markets, 26(2), 173-194.

Anastasiadis, F., Apostolidou, I., & Michailidis, A. (2020). Mapping sustainable tomato supply chain in Greece: A framework for research. Foods, 9(5), 539.

Bag, S., Wood, L. C., Xu, L., Dhamija, P., & Kayikci, Y. (2020). Big data analytics as an operational excellence approach to enhance sustainable supply chain performance. Resources, Conservation and Recycling, 153, 104559.

Borges Lopes, R., Freitas, F., & Sousa, I. (2015). Application of lean manufacturing tools in the food and beverage industries. Journal of technology management & innovation, 10(3), 120-130.

Brandon‐Jones, E., Squire, B., Autry, C. W., & Petersen, K. J. (2014). A contingent resource‐based perspective of supply chain resilience and robustness. Journal of Supply Chain Management, 50(3), 55-73.

Brusset, X., & Teller, C. (2017). Supply chain capabilities, risks, and resilience. International Journal of Production Economics, 184, 59-68.

Büyüközkan, G., & Göçer, F. (2018). Digital Supply Chain: Literature review and a proposed framework for future research. Computers in Industry, 97, 157-177.

Cagno, E., Neri, A., Howard, M., Brenna, G., & Trianni, A. (2019). Industrial sustainability performance measurement systems: A novel framework. Journal of Cleaner Production, 230, 1354-1375.

Chopra, S., & Sodhi, M. (2014). Reducing the risk of supply chain disruptions. MIT Sloan management review, 55(3), 72-80.

Chowdhury, M., Sarkar, A., Paul, S. K., & Moktadir, M. (2020). A case study on strategies to deal with the impacts of COVID-19 pandemic in the food and beverage industry. Operations Management Research, 1-13.

Christopher, M. (2016). Logistics & supply chain management. Pearson UK.

Cuypers, I. R., Hennart, J. F., Silverman, B. S., & Ertug, G. (2021). Transaction cost theory: Past progress, current challenges, and suggestions for the future. Academy of Management Annals, 15(1), 111-150.

Dagdeviren, H., & Robertson, S. A. (2016). A critical assessment of transaction cost theory and governance of public services with special reference to water and sanitation. Cambridge Journal of Economics, 40(6), 1707-1724.

Fawcett, S. E., Ellram, L. M., & Ogden, J. A. (2007). Supply chain management: from vision to implementation. Upper Saddle River, NJ: Pearson Prentice Hall.

Forkmann, S., Henneberg, S. C., Naude, P., & Mitrega, M. (2016). Supplier relationship management capability: a qualification and extension. Industrial Marketing Management, 57, 185-200.

Free, C., & Hecimovic, A. (2021). Global supply chains after COVID-19: the end of the road for neoliberal globalisation?. Accounting, Auditing & Accountability Journal.

Goksoy, A., Vayvay, O., & Ergeneli, N. (2013). Gaining competitive advantage through innovation strategies: an application in warehouse management processes. American Journal of Business and Management, 2(4), 304-321.

Govindan, K. (2018). Sustainable consumption and production in the food supply chain: A conceptual framework. International Journal of Production Economics, 195, 419-431.

Grekova, K., Calantone, R. J., Bremmers, H. J., Trienekens, J. H., & Omta, S. W. F. (2016). How environmental collaboration with suppliers and customers influences firm performance: evidence from Dutch food and beverage processors. Journal of cleaner production, 112, 1861-1871.

Grover, V., & Malhotra, M. K. (2003). Transaction cost framework in operations and supply chain management research: theory and measurement. Journal of Operations management, 21(4), 457-473.

Hailu, G. (2020). Economic thoughts on COVID-19 for Canadian food processors. Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie.

Islam, Z., Zunder, T. H., & Jorna, R. (2013). Performance evaluation of an online benchmarking tool for European freight transport chains. Benchmarking: An International Journal.

Ivanov, D., & Dolgui, A. (2019). Low-Certainty-Need (LCN) supply chains: a new perspective in managing disruption risks and resilience. International Journal of Production Research, 57(15-16), 5119-5136.

Kache, F., & Seuring, S. (2017). Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management. International journal of operations & production management.

Kashmanian, R. M., & Moore, J. R. (2014). Building greater sustainability in supply chains. Environ Qual Manage, 23(4), 13-37.

Knoll, S., Marques, C. S. S., Liu, J., Zhong, F., Padula, A. D., & Barcellos, J. O. J. (2017). The Sino-Brazilian beef supply chain: mapping and risk detection. British Food Journal.

Kumar, A., & Kushwaha, G. S. (2018). Supply chain management practices and operational performance of fair price shops in India: An empirical study. LogForum, 14(1).

Lancaster, G. A., Dodd, S., & Williamson, P. R. (2004). Design and analysis of pilot studies: recommendations for good practice. Journal of evaluation in clinical practice, 10(2), 307-312.

Mubarik, M. S., Naghavi, N., Mubarik, M., Kusi-Sarpong, S., Khan, S. A., Zaman, S. I., & Kazmi, S. H. A. (2021). Resilience and cleaner production in industry 4.0: Role of supply chain mapping and visibility. Journal of Cleaner Production, 292, 126058.

Muthoni, J. P., & Mose, T. (2020). Influence of supply chain management practices on performance of food and beverage manufacturing firms in Kenya. International Academic Journal of Procurement and Supply Chain Management, 3(2), 45-62.

Nagib, A. N. M., Adnan, A. N., Ismail, A., Halim, N. H. A., & Khusaini, N. S. (2016, November). The Role of Hybrid Make-to-Stock (MTS)-Make-to-Order (MTO) and Economic Order Quantity (EOQ) Inventory Control Models in Food and Beverage Processing Industry. In IOP Conference Series: Materials Science and Engineering (Vol. 160, No. 1, p. 012003). IOP Publishing.

Oláh, J., Kitukutha, N., Haddad, H., Pakurár, M., Máté, D., & Popp, J. (2019). Achieving sustainable e-commerce in environmental, social and economic dimensions by taking possible trade-offs. Sustainability, 11(1), 89.

Patsavellas, J., Kaur, R., & Salonitis, K. (2021). Supply chain control towers: Technology push or market pull—An assessment tool. IET Collaborative Intelligent Manufacturing, 3(3), 290-302.

Reeves III, L. A. (2019). Supply Chain Managers' Reverse Logistics Strategies to Control Cost Through Risk Mitigation (Doctoral dissertation, Walden University).

Rockart, J. F. (1979). Chief executives define their own data needs. Harvard business review, 57(2), 81-93.

Sarpong, S. (2014). Traceability and supply chain complexity: confronting the issues and concerns. European Business Review.

Saunders, M., Lewis, P., & Thornhill, A. (2009). Research methods for business students. Pearson education.

Scholten, K., & Schilder, S. (2015). The role of collaboration in supply chain resilience. Supply Chain Management: An International Journal.

Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill building approach. john wiley & sons.

Septiani, W., Marimin, M., Herdiyeni, Y., & Haditjaroko, L. (2016). Method and approach mapping for agri-food supply chain risk management: A literature review. International Journal of Supply Chain Management, 5(2), 51-64.

Singh, S., Kumar, R., Panchal, R., & Tiwari, M. K. (2021). Impact of COVID-19 on logistics systems and disruptions in food supply chain. International Journal of Production Research, 59(7), 1993-2008.

Subramaniyan, M. (2015). Production data analytics-to identify productivity potentials (Master's thesis).

Swift, C., Guide Jr, V. D. R., & Muthulingam, S. (2019). Does supply chain visibility affect operating performance? Evidence from conflict minerals disclosures. Journal of Operations Management, 65(5), 406-429.

Wang, S. C., Tsai, Y. T., & Ciou, Y. S. (2020). A hybrid big data analytical approach for analyzing customer patterns through an integrated supply chain network. Journal of Industrial Information Integration, 20, 100177.

Downloads

Published

2024-02-21

How to Cite

Mulweye, D., Shale, N., Namusonge, E., & Wachiuri, E. (2024). Supplier Collaboration and Performance of Food and Beverage Manufacturing Firms in Kenya. International Journal of Supply Chain Management, 9(2), 1–19. https://doi.org/10.47604/ijscm.2326

Issue

Section

Articles