Effect Of The Value Network On The Performance Of Commercial Banks In Kenya

Abstract

Globalisation and advances in information technology have created a complex, dynamic economic landscape with a shift from a focus on tangibles to intangibles thus creating the intangible - service and information - economy: A networked economy characterized by partnerships amongst firms. As a result, the Commercial Banking sector in Kenya has progressed from a regulatory and strategic perspective as banks have built Value Networks in order to counter increasing competition thus constantly innovating products and services; and increasing market segments towards growth. The main purpose of this study was to investigate the effect of the Value Network on the performance of Commercial Banks in Kenya. Independent variables examined included scale, growth in alliances, R&D expenditure and training. A sample of 15 Commercial Banks was drawn from the target population of 43 Commercial Bank headquarters located in Nairobi and studied over five years from 2010 to 2014. Data was collected from audited financial statements. Data analysis included descriptive and inferential statistics. The former employed frequency distributions, measures of central tendency and exploratory data analysis using growth pattern graphs and overlain growth plots. The results indicated an upward trend in all variables across the period and the presence of random effects. Panel descriptive analysis was also conducted which revealed the between and within differences. The Jarque Bera test for Normality indicated that data was not normal. Consequently Logarithm transformation of all variables, excluding R&D intensity, was employed to achieve Normality. R&D intensity was not transformed because it is a ratio. Inferential statistics entailed the use of correlation and panel regression analysis. No multicollinearity was present because all independent variables registered a correlation coefficient of less than 0.8. Prior to regression panel data diagnostic tests were run. They confirmed: The appropriateness of random effects regression for analysis (Breusch-Pagan LM test), absence of heteroskedasticity (modified Wald test), presence of time effects (time fixed effects test) and serial correlation (Wooldridge-Drukker test). Therefore, the FGLS two way random effects regression model was employed in the study (random effects model was also clarified by the Hausman test). The findings indicated that scale, growth in alliances and training had a positive significant relationship whilst R&D expenditure had a negative significant relationship with Commercial Bank performance. The study suggested various recommendations: On scale: Bank managers are advised to increase adoption of NPS and TCF metrics. Secondly, on growth in strategic alliances: As banks establish more strategic alliances management should apply Epstein’s five measures of success to ensure well structured management. Thirdly, on R&D expenditure: Policy makers should shift the approach to R&D financial reporting: Capitalize R&D’s Development component and seek sectoral reforms on this through regulators such as the Central Bank of Kenya and Kenya Banker’s Association. Finally, on training: Managers are encouraged to incorporate more of the Value Network’s systems thinking as they invest further in training. Suggested areas for further study include comparative analysis amongst different industry sectors and countries, investigation on other firm level factors such as customer loyalty and macroeconomic factors as the determinants of Commercial Banks’ performance in Kenya, study on the effect of R&D on firm performance in the longer term and the threshold effect of R&D investment on optimal performance.