THE EFFECT OF DESCRIPTIVE DATA ANALYTICS ON FRESH FOOD SUPPLY CHAIN PERFORMANCE FOR AGRITECH COMPANIES IN KENYA

Abstract

This study evaluated the impact of descriptive data analytics on the supply chain performance of agritech companies in Kenya. The study was anchored on the Resource Dependence Theory and adopted a descriptive research design. The target population comprised 315 supply chain and information technology officers, from whom a sample of 172 respondents was selected using Yamane's (1967) formula. Primary data were collected using structured questionnaires and analyzed using correlation and linear regression techniques. The findings revealed that descriptive data analytics had a positive and statistically significant effect on fresh food supply chain performance. The study concludes that descriptive data analytics enhances supply chain performance by improving visibility, monitoring, and evidence-based decision-making within agritech firms. The study recommends that agritech companies invest in integrated data management systems, strengthen data quality practices, and build employees' analytical capabilities to maximize the benefits of descriptive analytics and improve overall supply chain performance. JEL: M11, L23, L14, R41