Development of a Weighted Productivity Model for a Food Processing Industry
DOI:
https://doi.org/10.38032/jea.2023.04.003Keywords:
Productivity Attributes, Food Processing Industry, Weighted Model, CompetitivenessAbstract
In this paper, the data collected from a food processing industry was used to calculate the total productivity. It presents a comprehensive model and methodology for defining and measuring productivity attributes in the food processing industry. The proposed productivity model encompasses seven key factor groups, namely labor, capital, material, energy, machines, facility maintenance, and worker stress levels. Each group is further disaggregated into individual factors, which are assigned specific weights. The mathematical expression of the productivity index model involves summing the weighted individual factors and dividing the result by the total number of group factors. In the case study conducted at a Nigerian food processing company, the developed model was applied to measure the productivity levels. The findings revealed that the current productivity of the company stands at approximately 90%. By utilizing the model, the parameters of productivity were measured, and the results were set as baseline values for future assessments. The study outcomes shed light on the perceived importance and weight values of factors within each group, highlighting their significance in influencing productivity within a technologically advanced food processing corporation. This research contributes valuable insights into the measurement and enhancement of productivity in the food processing industry, offering a structured framework for evaluating process outcomes and optimizing operations to enhance competitiveness. Incorporating the current productivity level of 90% and setting it as the baseline value provides a reference point by allowing comparisons and analysis of productivity improvements over time.
References
Gershwin, S. B. (2005). MIT. [Online] Available at: http://web.mit.edu/manuf-sys/www/ [Accessed 8 February 2023].
Teng, H.S.S., 2014. Qualitative productivity analysis: does a non-financial measurement model exist?. International Journal of Productivity and performance management, 63(2), pp.250-256. DOI: https://doi.org/10.1108/IJPPM-03-2013-0034
Phusavat, K. and Photaranon, W., 2006. Productivity/performance measurement: case application at the government pharmaceutical organization. Industrial Management & Data Systems, 106(9), pp.1272-1287. DOI: https://doi.org/10.1108/02635570610712573
Tangen, S., 2004. Evaluation and revision of performance measurement systems (Doctoral dissertation, Industriell produktion).
Oyeranti, A, (2006). CiteSeerx. [Online] Available at: http://citeseerx.ist.psu.edu/viewdoc/download? doi=10.1.1.511.9388&rep=rep1&type=pdf [Accessed 21 February 2023].
Krugman, P., 1991. Increasing returns and economic geography. Journal of political economy, 99(3), pp.483-499. DOI: https://doi.org/10.1086/261763
Wazed, M.A. and Ahmed, S., 2008. Multifactor productivity measurements model (MFPMM) as effectual performance measures in manufacturing. Australian Journal of Basic and Applied Sciences, 2(4), pp.987-996.
Sink, D. and Tuttle, T. (1989). Planning and measurement of productivity in your organisation of the future. Norcross, USA: Industrial Engineering and Management Press.
Hannula, M., 2002. Total productivity measurement based on partial productivity ratios. International Journal of production economics, 78(1), pp.57-67. DOI: https://doi.org/10.1016/S0925-5273(00)00186-9
Craig, R. L., and Harris, H. P. (1973). Management for productivity: The Wiley series in management. John Wiley & Sons.
Taylor, F. W., and Davis, L. J. (1955). Principles of scientific management. Harper & Brothers.
Grünberg, T., 2004. Performance improvement: Towards a method for finding and prioritizing potential performance improvement areas in manufacturing operations. International journal of productivity and performance management, 53(1), pp.52-71. DOI: https://doi.org/10.1108/17410400410509969
Heap, J., 2007. Stormy productivity weather ahead?. International Journal of Productivity and Performance Management, 56(2), pp.170-177. DOI: https://doi.org/10.1108/17410400710722662
Koss, E. and Lewis, D.A., 1993. Productivity or efficiency—Measuring what we really want. National productivity review, 12(2), pp.273-284. DOI: https://doi.org/10.1002/npr.4040120212
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Copyright (c) 2023 B Kareem, A S Ilori, A S Lawal

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