<b>The Effect of Inventory practices on Beef Supply Chain Performance among Lusaka-Based Meat Companies</b>

Abstract

The beef supply chain in Lusaka District faces operational challenges associated with the perishability of beef, infrastructure limitations, and inadequate inventory management practices. Although large meat companies have started integrating semi-automated inventory management practices, many medium and small-scale beef firms continue to depend on traditional and manual inventory control practices, leading to stockouts, spoilage, inefficiencies in distribution, and increased operational costs. Therefore, this study was conducted to assess the inventory management practices used by Lusaka-based meat companies and examine their effect on beef supply chain performance. A descriptive survey design was employed under a positivist paradigm using a quantitative research approach. The study targeted 128 registered meat companies in Lusaka District. Out of these, 120 companies participated in the study, representing a 93.8% response rate. Data were collected using structured questionnaires and analysed using descriptive and inferential statistics through SPSS version 20. The findings revealed that basic inventory management practices such as First-In-First-Out (FIFO), cold storage, and Just-In-Time (JIT) are widely employed by beef companies, while advanced practices such as Vendor Managed Inventory (VMI), automated forecasting tools, and batch ordering systems remain underutilised. Hypothesis testing using the chi-square test indicated no statistically significant relationship between FIFO adoption and spoilage reduction among Lusaka meat companies (χ² (1, N = 120) = 2.069, p = 0.150). Fisher’s Exact Test also confirmed non-significance (p = 0.300); the null hypothesis was not rejected. The study recommends that beef companies should enhance inventory management practices through staff training, FIFO adherence, and digital tools to minimise stockouts. Medium-term strategies include investing in forecasting systems, semi-automated technologies, and cold chain infrastructure.