Internet of Things and Supply Chain Performance of Large Manufacturing Firms in Nairobi

Abstract

This research investigates the adoption and impact of Internet of Things (IoT) technology on supply chain performance within Nairobi, Kenya's manufacturing sector. The study explores the integration of real-time data, automation, and connectivity to create a "smart" supply chain enabled by IoT. Two theoretical frameworks, the Technology Acceptance Model (TAM) and Resource-Based View (RBV), were employed to assess the extent of IoT adoption and its potential for enhancing competitive advantage in supply chain management. The primary goal is to offer insights into how IoT can enhance efficiency, agility, and cost-effectiveness, thereby driving overall performance and competitiveness among manufacturing firms in Nairobi. Furthermore, the study seeks to evaluate the degree of IoT implementation, analyze the connection between IoT adoption and supply chain performance, and identify obstacles encountered by manufacturers during IoT technology adoption. This investigation contributes to the scholarly understanding of IoT's influence on supply chain performance and provides valuable guidance for manufacturers and policymakers aiming to augment operational efficiency and competitiveness. The research design relied on a cross-sectional approach, focusing on prominent manufacturing companies situated in Nairobi, Kenya. The study's target population consisted of 455 significant manufacturers operating within the region. A representative sample was adopted using a stratified random sampling technique. Data was collected through questionnaires, and subsequent descriptive and regression analyses are conducted to examine the association between IoT adoption and supply chain performance. The study's results demonstrate notable correlations between predictor and supply chain performance. Statistical significance was confirmed through an ANOVA table that supports the regression model's validity. The coefficients table reveals the strength and direction of variable relationships, with RFID and wireless sensor networks emerging as particularly significant. The findings indicate that the implementation of IoT technologies leads to enhanced supply chain reliability, agility, and cost-effectiveness. The study recommends that large manufacturers invest in IoT to bolster supply chain efficiency and fully harness the potential of these technologies. However, challenges surrounding data security, privacy, and behavior must be systematically addressed through appropriate policies and best practices. The study acknowledges certain limitations, including limited data availability and challenges in sourcing experienced respondents. Consequently, the study suggests future research focusing on IoT adoption within small and medium-sized manufacturing enterprises.