Kembo Bwana, Omary J Ally


The aim of this paper is to measure the efficiency of listed manufacturing companies in Tanzania, the study covers the year 2010 to 2014. The study employed a non-parametric approach, known as Data Envelopment Analysis (DEA) to measure efficiency under input oriented with constant returns to scale (CRS) and variable returns to scale assumptions (VRS). The study also employs Pearson correlation to test positive correlation between inputs and outputs variables. Data was extracted from respective annual financial reports of the manufacturing firms listed at Dar es Salaam stock exchange (DSE) before   the year 2010. Three critical inputs variables (raw materials, staff expenses as well as plant and machinery) and two output variables (net sales and earnings after tax) were employed to measure relative efficiency of 6 listed manufacturing.  Findings revealed that Tanzania Cigarette Company (TCC) was performing relatively better in terms of pure technical efficiency (PTE) and scale efficiency (SE) with an average efficiency score of 98% and 99 % respectively. While, Tanzania Oxygen Limited (TOL) experienced difficulties in terms of PTE and SE with an average efficiency score of 72% and 45% respectively. Results of average annual performance in the years 2010, 2011 and 2012 were better compared to the remaining years. Result for returns to scale indicates that there was no firm which consistently experienced increasing return to scale (IRS) throughout the period under review, which implies that none of the firms has the room to enjoy economies of scale throughout the period under review. Findings have significant bearing on policy issues relating to size of manufacturing firms   in the country. Firms indicating decreasing returns to scale (DRS) should revisit their size versus production scale so as to improve the scale efficiency. The findings from this study can also enrich the ongoing agenda of promoting industrialization in Tanzania particularly, on issues relating to size and production scale (optimality).



Efficiency, Manufacturing Firms, Data Envelopment Analysis (DEA), Tanzania

Full Text:

PDF Untitled


Abokaresh, M. S. M. and Kamaruddin, B. H. (2011).Performance Rating of Privatized and Non-Privatized Firms Using Data Envelopment Analysis Technique. Journal of Information Engineering and Applications, 1 (4), pp. 1-12.

Africa Development Group(2014) Eastern Africa Manufacturing Sector: Promoting Technology , innovation, productivity and Linkages, Tanzania Country Report

Chang, H. J. (2007). State-owned enterprise reform. UN DESA Policy Note.

Ar, D. M. and Baki, B. (2007). Measuring and Evaluating Efficiency of a Glass Company through Data Envelopment Analysis. Problems and Perspectives in Management, 5 (1), pp. 72-81.

Banker R. D., Charnes A. and Cooper W. W. (1984). Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis. Management Science, 30 (9), pp. 1078–1092

Banker, R., Emrouznejad, A., Lopes, A. L. M., & Almeida, M. R. de. (2012). Data Envelopment Analysis: Theory and Applications. 10th International Conference on DEA, 1, 1–305

Charnes A., Cooper, W. W. and Rhodes. E. (1978). Measuring the Efficiency of Decision Making Units. European Journal of Operational Research, 2 (6), pp. 429-444

Eslami, G. R., Mehralizadeh, M., and Jahanshahloo, G. R. (2009), Efficiency Measurement of Multi-Component Decision Making Units Using Data Envelopment Analysis, Applied Mathematical Sciences, Vol.3, No.52, PP. 2575-2594

Hajiha, Z. and Ghilavi, M. (2012). Presenting a Model for Determination of the Efficiency of the Production Companies Listed in Tehran Stock Exchange Based on Financial Variables. International Journal of Business and Behavioral Sciences, 2 (1), pp. 1-11.

Haro, M and Chellakumar, A(2012) Efficiency Performance of Manufacturing Companies in Kenya: Evaluation and Policies, International journal of Manag and Business Research, 2 (3), 233- 24

Lin, W. C., Liu, C. F. and Chu C. W. (2005). Performance Efficiency Evaluation of the Taiwan’s Shipping Industry: An Application of Data Envelopment Analysis. Eastern Asia Society for Transportation Studies, 5, pp. 467-476.

Ling, O. P. and Kamil, A. A. (2010). Data Envelopment Analysis for stocks selection on Bursa Malaysia. Archives of Applied Science Research, 2 (5), pp. 11-35.

Maudos, J., Pastor, J. M., Perez, F., & Quesada, J. (2002). Cost and profit efficiency in European banks. Journal of international financial markets, institutions and money, 12(1), 33-58.

Mazumdar, M. and Rajeev, M. (2009). Comparing the Efficiency and Productivity of the Indian Pharmaceutical Firms: A Malmquist-Meta Frontier Approach: International Journal of Business and Economics, 8 (2), pp. 159-181.

Mohamad, N. H., and Said, F. (2010b). Measuring the performance of 100 largest listed companies in Malaysia. African Journal of Business Management, 4(13), 3178-3190

Ngui-Muchai. M. D and Muniu. M (2012), Firm efficiency differences and distribution in the Kenyan manufacturing sector, African Development Review, Vol. 24, No. 1, PP. 52–66.

Qian, L. and Dawei, L. (2009). Efficiency and Productivity in the Chinese Maritime Seaports. Paper presented at the International Conference on Information Management, Innovation Management and Industrial Engineering

Reddy, T (2015). Comparison and Correlation Coefficient between CRS and VRS models of OC Mines. International Journal of Ethics in Engineering & Management Education, 2(1), 2348–4748

Sharma, S. (2008). Analyzing the Technical and Scale Efficiency Performance: A Case Study of Cement Firms in India. Journal of Advances in Management Research, 5 (II), pp. 56-63.

Memon. A. M and Tahir, M.I (2011), Applying DEA in Analysing the Efficiency of Top Manufacturing Companies in Pakistan, Journal of Public Administration and Governance, Vol. 1, No. 2, PP. 225-239.

Thore, S., Kozmetsky, G., and Phillips, F. (1994), DEA of Financial Statements Data: The U.S. Computer Industry, The Journal of Productivity Analysis, Vol. 5, PP. 229-248.

UNIDO (2009): “Breaking In and Moving Up: New Industrial Challenges for the Bottom Billion and the Middle Income Countries, Industrial Development Report 2009, Vienna.

Wang, W. (2003). Ownership Structure and Company Performance: Evidence from Taiwan. Asia Pacific Management Review, 8(2), 135-160.

Wang, W. K. (2008). An Intelligent Support System for Performance Evaluation of State Owned Enterprises of Electronic Industry. Citeserx Digital Library, pp. 40-51.

Wangwe,S .Mmari, D.Haikaeli, J. Rutatin,N. Mboghoina, T. Kinyondo, A (2014) The Performance of the Manufacturing Sector in Tanzania; Challenges and Way forward, WIDER Working paper 2014/85 - UNU WIDER

Wei, C. K., Chen, L. C., Li, R. K., Tsai, C. H. and Huang, H. L., (2012). A Study of Optimal Weights of Data Envelopment Analysis – Development of a Context-Dependent DEA-R Model. Expert Systems with Applications, 39 (4), pp. 4599-4608.

Wu, H. L. (2005). A DEA Approach to Understanding the Performance of Taiwan’s Steel Industries 19701996. Asia Pacific Management Review, 10 (6), pp. 349-356


  • There are currently no refbacks.

Copyright (c) 2019 Business Education Journal