INFLUENCE OF SUPPLY CHAIN PERFORMANCE ON THE CHOICE OF FLORICULTURAL DISTRIBUTION CHANNELS IN KENYA
Gerald Musyoki Nyumu
Master of Science in Procurement & Logistics, Jomo Kenyatta University of Agriculture and Technology, Kenya
ABSTRACT
The floriculture industry is amongst the fastest growing sectors of the Kenyan economy and this is evident through its growth within the last two decades. The industry has however lately experienced challenges due to continued depressed returns despite year on year increase in export volumes. This state of affairs threatens the livelihoods of millions of Kenyans who depend on floriculture. In that respect, an examination of the floriculture supply chain performance between the various distribution networks becomes a crucial subject as this forms a key determinant of the returns that accrue from the industry. The main objective of the research was to empirically investigate the influence of supply chain performance on the choice floricultural distribution channels. The research targeted Kenyan flower farms using a sample size of thirty farms which was arrived at after employing two sampling techniques namely purposeful sampling and simple random sampling and by use of a quantitative survey research design the study applied a self designed questionnaire to collect data from the sample population. The data collected was analyzed using both the descriptive and inferential analysis tools of weighted means, t - tests, chi square and correlation analysis supported by an SPSS programme. The study established that at the farm level not all supply chain performance indicators have a significant influence on the choice of distribution channels chosen by farms and of the four independent performance variables investigated only quality standards and lead time had a major and significant influence on the choice of distribution channel at the farm level. The researcher recommends that the study be extended to the downstream linkages within the supply chain as this is where the other performance variables could be having major impact.
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