Tea Production Automation Influence on Selected Multinational Tea Companies Field Costs in Kericho and Bomet Counties, Kenya
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Date
2020
Authors
Tare, Julius
Journal Title
Journal ISSN
Volume Title
Publisher
Kenyatta University
Abstract
The independent variables of the study were; automation, information technology and
human capital information systems while the dependent variable was field cost. The
purpose of this study was to determine Tea Production Automation Influence on
Selected Multinational Tea Companies Field Costs in Kericho and Bomet Counties,
Kenya. The specific objectives which guided the study were to; examine the effect of
automation, Information Technology and Human Capital information systems on
Field Costs in multinational tea companies in Kericho and Bomet Counties. Research
hypotheses for the study were tested at 95% confidence level where (p<0.05)
hypotheses was accepted else were rejected. The study used the theories of induced
innovation, basic human capital, and profit maximization theory of a firm.
Correlational and descriptive research design was used. Census sampling method was
used to sample unit managers and field managers from the target population of 91
employee of the three multi-national tea companies in Kericho and Bomet Counties
which were; Unilever Tea Kenya Limited, James Finlays Kenya Limited and
Williamsons Tea Kenya Limited. Responses were received from 83 respondents
translating to 91.2% response rate. The study used open ended structured
questionnaire as the primary tool for data collection. Reliability of the research
instrument was tested against Cronbach’s alpha coefficient where a value of 0.876
was obtained and it showed that the instrument was reliable while validity was gauged
through research experts’ opinions. Data was analyzed using both the descriptive and
inferential statistics. The findings from the study will be of great importance to the
management of both the tea estates and smallholders since it addresses the most
critical factors pertaining Production field costs. The findings from the study will also
be significant to investors who wish to invest directly or indirectly in the tea subsector in Kenya. The findings reveal that automation has significantly reduced the
cost of land preparation, tea pruning cost; fertilizer application cost and cost of
pruning. Information Technology has enabled effective tracking of tea production;
electronic weighing system has enabled efficiency and accountability in transmission
of accurate green leaf field weights information; adoption of innovation has led to
increased efficiency and quality of work done. Human capital information system
ensured that there are skilled personnel who have expert in tea production and who
can innovate on ways of reducing field production cost. The study concludes that
automation significantly reduced the cost of land preparation; application of fertilizers
cost; reduces harvesting costs; it reduces tea production field labour costs and
reduction in number of errors thus increasing tonnage of tea weighed and collected,
the reduction in the number of trainings does not lead to improved work output led to
increase in efficiency and quality of work done and that skilled man power has an
impact on human resources costs leading to reduction on tea Production field Costs.
There is need for multinational tea companies to fully embrace tea harvesting
technology. It leads to faster work flow and that a bigger area is covered by few
people working using machines. Information technology is key since it enables
automation to be deployed effectively in the field. It creates a platform which
automation operates on leading to lower cost of operation and lower down time thus
reduction of labour per hectares and also it leads to faster work output.
Description
A Research Project Submitted to the School of Business in
Partial Fulfillment of the Requirements for the Degree
of Master of Business Administration (Strategic
Management Option) of Kenyatta University
Keywords
Tea Production Automation, Multinational Tea Companies, Kericho County, Bomet County, Human capital information systems