Networking And Firm Peformance Among Small And Medium Enterprises In Kenya

ABSTRACT

SMEs are the backbone of global economies and they serve as medium of job creation and poverty eradication. They are unique compared to large organizations in terms of size, resources and flexibility. Since most of the SMEs are constrained resource wise, they are unable to compete and hence their survival and longevity is a major concern. In addition, they are known to operate in isolation which is considered as a major obstacle to their competitiveness and hence performance. It is assumed that networking among SMEs can enhance their performance. This study evaluates networking outcomes and how they influence performance of manufacturing SMEs in Kenya. A critical literature review identified three network outcomes that were likely to influence form performance. These include: network relationships, dimensions and networking capability. These variables have been previously studied separately and hence there are inconsistent findings regarding their influence on performance. This study integrated these three dimensions together because firms are likely to use them in a combination as they compete with their rivals. The three network outcomes were the basis of three objectives that guided the study and eight hypotheses that were tested. Extant literature reveals scanty details on networking and performance in the developing and least developed countries. It is unclear whether those studies can be replicated in both developing and least developing countries. In particular, there are no comprehensive studies related to networking and firm performance in Kenya. Consequently, there exists a gap regarding whether being in a business network influences SMEs performance in Kenya and how firms can leverage on their position in the network to enhance their competitiveness. The study targeted manufacturing sector which has huge potential yet it has stagnated in growth for years. The study targeted manufacturing SMEs registered under Kenya Association of Manufacturers (KAM) with a population of 660 and drew a sample of 132 firms using systematic random stratified sampling. A survey was conducted targeting CEOs of the firms using questionnaires. Data was analyzed by use of statistical package for social sciences (SPSS) version 20. Descriptive and inferential statistics were used to present data. Quantitative methods that were used in this study include multiple regression analysis, Factor analysis, ANOVA and Pearson correlation coefficient.