International Journal of Modern Science and Technology

INDEXED IN 

ISSN 2456-0235

​International Journal of Modern Science and Technology, 1(7), 2016, Pages 236-241. 


Cost Drivers Analysis for Sugar Processing in Kenya using Optimization Models with Adoption of Goal Programming 

John Obiero Abuto1, Adrian Mukhebi2, N. B. Okelo3
1 School of business and Economics, 2 School of Agriculture and Food Security,
3 School of Mathematics and Actuarial Science, Jaramogi Oginga Odinga University of Science and Technology,

P. O. Box 210-40601, Bondo-Kenya.

Abstract
The cost of production in Kenya has been high when compared to other regional producers and world market prices, which for political and economic reasons are lower than the production costs in most factories in Kenya. For these reasons, production cost drivers analysis for sugar processing in Kenya is in inevitable so that good production mix can be put in place by the various companies. The objective was to analyse cost variables using optimization models with goal programming. Use of questionnaire, observation and interview schedules were used to collect data. The findings from goal programming application on cost analysis on resource allocation reveals that, with current level of operation strategies it is still a challenge for the Kenyan sugar manufacturer to produce sugar at 300 USD or less. The result gives an under achievement of 86 USD. Meaning with the current state of our factories and built in strategies, the operating resources projected at optimal level (current constraint still in place), for example Sony sugar company producing at a cost of 841 USD can only minimise production cost to 755 USD and Mumias with relatively improved technology, which does its production at a cost 465 USD can manage 379 USD with optimal production mix. It is also important to recognise that with sugar cost which is sighted as optimal ( X1 = 0), the cost of 35 USD is still revealed as relatively high and needed to be reduced further, this can be done by introducing high sugar variety that can yield so much from an hector to compensate for primary farm inputs.

​​Keywords: Cost drivers analysis, optimization, sugar processing and goal programming. 

​References

  1. Abuto JO, Mukhebi A, Okelo NB. Influence of modern technology on cost optimization of sugar processing in Kenya, International Journal of modern science and Technology 1 (2016) 218-223.
  2. Fraenkel JR, Wallen NE. How to Design and Evaluate Research in Education (5th Ed.), McGraw-Hill Publishing Company, New York, 2015
  3. Fargonyinbo IS, Akinbo RY, Ajibode IA. Maximization of profit in manufacturing industries using linear programming. Mediterenean Journal of Social Sciences, 2 (2011) 134-149.
  4. Hira D. Operations Research. Ram Nagar, New Delhi, 2014.
  5. Kate  S,  Kamau N.  Kenya annual sugar report. Global Agricultural Network, 2013.
  6. Kegode P, Otieno O,  Ochola S. Challenges and way forward for the sugar subsector in Kenya. Friedrich Erbert Stiftung (FES), Nairobi, 2003.
  7. Kothari CR. Quantitative techniques. New Delhi, UBS publishers Pvt Limited, 2010.
  8. Meyer L,  Scrima T. Process Optimization through Sigma six. Global congress on proceeses and project management. Seattle- Washingtone, 2006.
  9. Mulwa MR, Emrouznejad A, Murithi FM. Impact of liberalization on efficiency and productivity of sugar industry in Kenya. Journal of Economic Studies 36  (2009) 250-264.
  10. Mugenda MO, Mugenda AG. Research Methods: Quantitative and Qualitative Approaches. Nairobi: Acts Press Network, 2003.
  11. TIFAC. Sugar technology mission. New Delhi: Department of science & Technology Govt. of India, 2015.
  12. Tangani M. Kenana Works production mission and Vision 2013 and beyond. Kenana Sugar Works, 2013.
  13. Zalalem G. Projecting technology change in Sugar supply. Adisababa: Ethopian herald, 2016.