OPTIMIZING PRODUCTIVITY AND CONTROL OF MARKET SHARES IN THE NIGERIAN REAL SECTOR THROUGH THE INTERNET ECONOMY

Abstract

This study investigates strategies for optimizing productivity control and enhancing market share performance within the Nigerian real sector through the internet retail economy. Transactional data of Jumia and Konga were used in the study to develop an integrated analytical framework that combines inventory management, product association analysis using the Apriori algorithm, and market transition dynamics modeled through a Markov chain process. To account for market uncertainties, system performance was evaluated under stochastic conditions involving demand fluctuations, inventory turnover variability, logistics efficiency constraints, and price competition pressures, using the Monte Carlo simulation approach. The simulation results reveal a mean productivity index of 0.642, indicating a 64.2 percent improvement in productivity over the baseline system. The standard deviation of 0.108 indicates moderate variability, while the observed productivity index, which ranges from 0.38 to 0.91, reflects the sensitivity to operational and market dynamics. Further statistical characterization shows a positive skewness of 0.27, suggesting a tendency toward higher productivity outcomes, and a kurtosis of 2.74, approximating a normal distribution with limited extreme deviations. These findings imply that the integrated model maintains stable performance even under varying economic and operational conditions. The study contributes to the growing body of literature on digital transformation in emerging economies by demonstrating that the synergistic application of data analytics, inventory intelligence, and probabilistic modeling can significantly enhance productivity control and competitive positioning. It further provides actionable insights for policymakers and industry stakeholders seeking to strengthen the Nigerian real sector through the internet retail economy