Artificial Intelligence Demand Forecasting and Supply Chain Performance of Large Supermarkets in Nairobi City County, Kenya

Charles Katua Kithandi and Reuben Musyoka Mwove
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Charles Katua Kithandi: Department of Economics, Daystar University
Reuben Musyoka Mwove: Daystar University

African Journal of Commercial Studies, 2026, vol. 7, issue 1

Abstract: Artificial Intelligence (AI) has become a transformative force in contemporary supply chain management, offering capabilities that optimize operational efficiency, reduce costs, and facilitate data-driven decision-making. This study examined the effect of artificial intelligence demand forecasting on supply chain performance among large supermarkets in Nairobi City County, Kenya. The study was anchored on the Hybrid Intelligence Model and the Technology Acceptance Theory. A descriptive research design was adopted. The population comprised employees working in the supply chain departments of ten large supermarkets operating in Nairobi City County, Kenya. A sample size of 70 employees was selected, and questionnaires were pretested using seven respondents drawn from two Naivas supermarkets in Kiambu County, Kenya. Primary data were collected through structured questionnaires and analyzed using descriptive statistics including percentages, means, and standard deviations, as well as inferential statistics such as correlation and regression analysis using SPSS version 30. The regression results revealed that AI-demand forecasting had a statistically significant positive effect on supply chain performance (β1 = 0.714, p-value = 0.000

Keywords: AI-Demand Forecasting; Artificial Intelligence; Supply Chain; Supply Chain Performance (search for similar items in EconPapers)
JEL-codes: C88 L81 M11 O33 (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:cwk:ajocsk:2026-19

DOI: 10.59413/ajocs/v7.i1.19

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