Supply Chain Visibility Strategies and Performance of Manufacturing Firms in Nairobi City County, Kenya

Abstract

Purpose: The objective of the study was to examine the effect of real-time tracking strategies and data integration strategies on the performance of manufacturing firms in Nairobi City County, Kenya. This study was anchored on two theories, Information Processing Theory and Resource-Based View. Methodology: The target population consisted of 189 registered manufacturing firms in Nairobi City County, as documented by the Kenya Association of Manufacturers.  The study applied the Yamane (1967) sample size formula, yielding a sample size of 128 manufacturing firms, meaning data was collected from 128 knowledgeable managerial respondents, one per firm. A descriptive research design was used, supported by simple random sampling to select respondents. A structured questionnaire served as the primary data collection instrument. A pilot study involving 13 respondents (10% of the sample) was conducted to assess the validity and reliability of the research instrument. For the main study, data was analyzed using SPSS version 29, employing descriptive statistics (means, frequencies, standard deviations) and inferential techniques including Pearson correlation and multiple regression analysis to determine the effect of the four visibility strategies on firm performance. Findings: The study concludes that real-time tracking strategies significantly enhance the performance of manufacturing firms in Nairobi City County. In addition, the study concludes that data integration strategies are the most influential supply chain visibility strategy affecting the performance of manufacturing firms. Unique Contributions to Theory, Policy, and Practice: Manufacturing firms should increase investment in advanced real-time tracking technologies such as GPS systems, RFID technologies, IoT-enabled monitoring devices, and digital tracking platforms to improve visibility throughout supply chain operations.