SIX SIGMA AND PERFORMANCE OF SMALL SCALE MANUFACTURING FIRMS IN ABUJA - OZOEMENA, CHUKWUEMEKA C.; OYEKU, OYEDELE M.; OKONKWO, THOMAS M. (JOURNAL OF ECONOMICS AND ALLIED RESEARCH, 2025)
This study examined the effect of application of Six Sigma principles on performance of small-scale manufacturing firms in Abuja. Using a cross-sectional survey research design, data were collected from 205 respondents in selected small scale manufacturing firms through structured questionnaire administered to 370 participants using Goggle form. The measures of Six sigma are the dimensions of six sigma namely: process definition, process measurement, process diagnostics, process improvement, and process control while performance was measured by customer patronage indicators. Data were analyzed using regression analysis via SPSS Version 26. The findings revealed that application of the principles of: process definition, process measurement, process diagnostic, process improvement and process control have positive and significant effects on performance. On combining the five dimensions of six sigma, the result showed that all the five dimensions jointly predict performance with application of Six sigma principles having a positive and significant effect on performance with application of six sigma principles explaining 35% (Adj. R2= .350) variation in performance. Individual contribution to performance in the combined model showed that process measurement, process improvement and process control have positive and significant effects on performance whereas process definition shows a statistically significant but negative effect on performance while process diagnostics was not statistically significant, indicating it does not contribute meaningfully to explaining performance outcomes in the combined process. Based on the findings, it is recommended that small scale manufacturing firm operating in Abuja should implement the five tools of six sigma most especially process measurement, process improvement and process control tools to enhance performance of their manufacturing activities.