Analysis Of Hax Delta Strategic Positioning Model On Performance Of Mobile Telecommunication Companies In Kenya

The performance of any organization is intricately tied to its ability to design, master and withstand a strategic positioning, which can be collaborated with and thereby directed. Knowing what strategic position a firm has available and the implications of choosing between them is a dilemma facing businesses from all industries. Although each industry may have its own set of unique conditions and particularities, a number of fundamental business strategies can be generalized to assist managers with strategic positioning. The aim of this study was to analyze the influences between Strategic Positioning and subsequent Performance in the mobile telecommunication industry in Kenya. Specifically, the study sought to determine the influences of Best Product Strategies, Total Customer Solution Strategies, System Lock-In Strategies on performance and examine the moderating effect of the competition regulation in the mobile telecommunication industry in Kenya. The study was premised on Hax Delta Model as it was appropriate for studying firms’ competitive behavior in complex and uncertain market environment. The study applied a combination of explanatory design, descriptive survey research design and cross sectional design. The research adopted proportionate stratified random sampling technique and convergent parallel mixed methods design. The target population consisted of 4 mobile telecommunication firms and the respondents for this study were 343 managers and a sample size of 142 top, middle and lower level managers from Safaricom, Airtel, Telkom Kenya and Equitel. Secondary data was collected from consolidated financial annual performance reports for a three years period between 2014 and 2017. The overall reliability obtained using Cronbach’s alpha reliability coefficient was 0.746, hence the instrument was reliable. Descriptive statistics were used to summarize data while inferential statistics, Pearson correlation coefficient and multiple linear regression were used to test the relationship between the independent and dependent variable. The data were analysed by use of Stata software and Statistical Package for Social Science (SPSS) 21. Looking at the overall industry, the multiple linear regressions explained 26% of the independent variables on the variability of the dependent variable. The interaction of the moderating effect accounted for significantly less variance than just regulation and performance by R2 change .003, p = .455, indicating there was no significant moderation effect between independent and dependent variable. Correlation findings further suggested there was a positive and significant relationship between Best Product Strategy (β= .477, p