Influence of Innovation on performance of Insurance companies in Kenya
Date
2016
Authors
Kiragu, Rachael Wangu
Journal Title
Journal ISSN
Volume Title
Publisher
Strathmore University
Abstract
The need for improved performance by insurance companies in Kenya in both life and non-life segments has been underscored and innovation has been identified as a means to boost performance. The main objective of this study was to determine the influence of innovation on performance of insurance companies in Kenya. The study adopted the use of a descriptive cross-sectional design. A census survey was used with the study population comprising all 49 insurance companies operational in Kenya as at 31st December 2014. Primary data was collected using structured questionnaires. Data was analyzed using SPSS statistical package program version 22 for descriptive and inferential statistics. The results of the study revealed that product innovation positively and significantly influences organizational performance (β=57271.822, t=2.423, p<0.05) and process innovation positively and significantly influences organizational performance (β=91651.229, t=2.485, p<0.05). No evidence was found for a significant relationship between market innovation and performance (β=20108.084, t=0.196, p>0.05). The results also showed that process innovation was the most predominant type of innovation in the insurance industry in Kenya. Additionally, the survey found that among the three types of innovation studied, process innovation registered the strongest correlation to organizational performance (coefficient value 0.584, 0.01 level of significance, and p value 0.001). The study recommends that management of insurance companies in Kenya should place greater emphasis on process innovation in order to improve performance. Further research should adopt a longitudinal research design, multiple informant approach, wider scope of study and the use of both objective and subjective measures to assess performance. These will give useful insight into the relationship between the variables under study.