Analysis of the efficiency levels of the manufacturing sector in Zimbabwe
Date
2018-08
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Abstract
Identifying the best level of efficiency within firms and determining efficiency drivers and barriers is the main issues in efficiency theory, as the use of efficiency scores is believed to have an important influence when crafting efficiency models in the manufacturing sector of an economy. Using input-output data from developed economies and blend it with financial ratios will salvage decimation in any sectors of the economy. This study analysed the efficiency levels of the manufacturing sector in Zimbabwe. The manufacturing sector is one of the most significant pillars of the economy due to its contribution to the Gross Domestic Product (GDP), export earnings, employment levels and investment opportunities. The two efficiency orientations namely Output-Orientation and Input-Orientation were considered to determine the barriers and the drivers of efficiency in Zimbabwe’s manufacturing sector. The underpinnings of the efficiency measurement was guided by Duality theory and approaches to efficiency measurement, namely the production function approach and the cost function approach. Applying both descriptive and non-parametric Data Enveloping Analysis (DEA) statistics, and a hybrid of cross sectional and longitudinal quantitative surveys, primary data from questionnaires, and secondary data from the Zimbabwe Stock Exchange financial statements, were utilized. The sample size used was 21 firms from each of the 10 manufacturing sub-sectors. Using the primary and secondary data, the study, in addition, the study calculated the efficiency scores for each firm in the 10 manufacturing sub-sectors, average efficiency score for each sub-sector and the overall efficiency score for the Zimbabwe’s manufacturing sector. This allowed for firm efficiency comparison and sectorial efficiency. The sectors were analysed under the assumptions of constant returns to scale (CRS) and variable returns to scale (VRS) in line with the study objectives. Using Output- Orientation and Input-Orientation there was certainty that inefficiencies in Zimbabwe’s manufacturing sector is a result of both input excesses and output shortfalls, the slacks-based measure was be used. This slacks-based measure was able to identify and assign the magnitudes of barriers and drivers of efficiency in each sub-sector and the whole manufacturing sector in Zimbabwe. The input variable which is a major driver of efficiency in the manufacturing sector is costs of material, both under CRS and VRS. The output variable which is a major driver of efficiency in the manufacturing sector is the sales, both under CRS and VRS. The input variable which is a major barrier to efficiency in the manufacturing sector is cost of services, both under CRS and VRS. The output variable which is a major barrier to efficiency in the manufacturing sector is the level of value-
addition in manufactured products, both under CRS and VRS. The study found that average efficiency score for Zimbabwe’s manufacturing sector is 67.1% under CRS and 80.2% under VRS. It can be deduced that 34.9% of DMU in the whole manufacturing sector are efficient under CRS and assuming VRS, 52.5% are efficient. Combining the DEA results will better inform the government on sectorial and national policies to effect and prepare the best efficient model which will favour Gross Domestic Product (GDP), export earnings, employment levels and investment opportunities. These efficiency results can be used by management and government as an assessment tool to rank firms’ efficiency performance based on sector-by-sector, input-by-input and output-by-output. Given that efficiency ratios obtained differs from the financial ratios from financial statements, this study offered hybrid disclosure of efficiency ratio and conventional financial ratio as a solution to decimation of the Zimbabwe’s manufacturing sector tracking.
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Submitted in fulfillment of the requirements for the Doctorate degree in Philosophy, Durban University of Technology, Durban, South Africa, 2018.
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DOI
https://doi.org/10.51415/10321/3326