Supply Chain Visibility and Performance of Food and Beverage Manufacturing Firms in Kenya
Authors: Mulweye David , Shale Noor , Namusonge Eric , Wachiuri Elizabeth 
Published: February 2024

Purpose: The purpose of the study was to evaluate the effect of supply chain visibility 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 exploratory research design was used in the study which utilized both qualitative and quantitative data. All 270 food and beverage manufacturing firms in Kenya registered by Kenya Association of Manufacturers (2022) were considered using the census approach. Target population for the research was one participant from logistics, supply chain or operations department at each of the registered food and beverage manufacturing firms. 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 while the inferential analysis was further carried out using structural equation modelling, ANOVA and regression coefficients to give effect of the explanatory variable.
Findings: The study found out that supply chain visibility significantly influenced the performance of food and beverage manufacturing firms in Kenya at both when there was a moderator and without a moderating variable, supply chain technology. In the first model without moderator, it recorded a standardized estimate of 0.538 (p<0.000), indicating that as supply chain visibility 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 211.322 with 86 degrees of freedom (P-value =0.0492). The structural path for structural equation modelling from supply chain visibility to supply chain performance remains positive and significant. Standardized estimate of 1.347 and p-value was 0.001<0.05. Which indicates that the variability of supply chain visibility on the performance of food and beverage manufacturing firms could be explained by 53.8% when no moderator is included and increased to 134.7% when ,moderator, supply chain technology is incorporated thereby indicating a stronger relationship. The other fit indices that gave a satisfactory model fit when the moderator supply chain technology was used are RMR=.9196, GFI=.9263, NFI= .9473, RMSEA=.0184 and CFI=.9369 which implies that the model was fit to determine the relationship between supply chain visibility and performance of food and beverage manufacturing firms in Kenya and therein make conclusions and recommendations. ANOVA, regression coefficient and model summary (R2) were also used and indicated significance for there use with all recording p-value of 0.000<0.05.
Unique Contribution to Theory, Practice and Policy: System theory of management was adopted and validated. By incorporating supply chain enabling technologies in the management and planning of production in a manufacturing firm, it has the potential of revolutionizing the business environment hence increasing flow of raw materials and other items into the company’s production plant, warehouses or retail locations in an effort to create visibility and enhanced performance. The theory can assist Kenya and the manufacturing firms in developing policies and strategies to assist manufacturing sector while creating competitive advantages through supply chain visibility. The study found out that some of the important supply chain mapping strategies to enhance performance of food and beverage manufacturing firms is supply chain visibility and supply chain technology.