Please use this identifier to cite or link to this item: http://localhost:8081/xmlui/handle/123456789/225
Title: PERFORMANCE ASSESSMENT OF INDIAN TEXTILE MILL INDUSTRY THROUGH DATA ENVELOPMENT ANALYSIS
Authors: Gynoba, Solankar Pradeep Kumar
Keywords: PERFORMANCE ASSESSMENT;INDIAN TEXTILE;MILL INDUSTRY;TECHNICAL-EFFICIENCY
Issue Date: 2002
Abstract: The present study has been undertaken to measure the performance of the Indian Textile Mills and Textile Mill Industry for the period 1973-74 to 1997-98. The study covers the following objectives: (i) to measure relative efficiency of composite textile mills, (ii) to identify excess input-use and deficient output for inefficient firms, (iii) to set targets for monitoring the performance of inefficient mills, (iv) to analyse growth rates, single factor productivity trends, efficiency trends in the textile mill industry and to measure total factor productivity changes, technical efficiency and technological changes in the composite mills, (v) to identify issues, strategies and policies that can improve the performance of the mills under reference and the textile mill industry as a whole, and vi) to offer suggestions which could have important policy implications. RESEARCH METHODOLOGY Out of the total 164 working mills in the year 1998-99, 82 mills have been selected for the study. Time series data have been obtained from the Annual Survey of Industries- Factory Sector and Centre for Monitoring Indian Economy for the period 1973-74 to 1997-98. Suitable variables have been selected to measure relative efficiency and productivity changes in composite textile mills and textile mill industry. Annual compound growth rates, single factor productivity and Data Envelopment Analysis (DEA) have been applied to analyse the time series data on textile mill industry. Malmquist Productivity Index (MPI) has been applied to the panel data on 35 private composite mills for the period 1999-92 to 1999-2000. FRAMEWORK OF THE THESIS The Introductory chapter defines important terms and deals with the aspects of performance measurement, statement of the problem, objectives, scopes and limitations of the study. Chapter Two is devoted to narration of performance measures, efficiency measurement techniques and also provides a synoptic view of the major studies on efficiency (with and without environmental effects) and productivity. Chapter Three presents brief history, growth and structure of the Indian Textile Industry. This chapter also focuses on the progress of the textile industry during pre and post Independence periods and the government textile policies implemented during various plan periods. Model formulation, choice of variables, model description, and terms related to the model, etc. are discussed in Chapter Four. This chapter also analyses firm-wise relative efficiency and economic performance of the mills. Chapter Five provides methodological details for various performance assessment studies and an xv empirical background to the estimation of productivity indices. This chapter also investigates industry growth rates, single factor productivity trends, efficiency patterns in the textile mill industry and total factor productivity changes, technical efficiency and technological changes in the composite mills. Chapter Six discusses various major issues of the industry, and strategies and economic policies that can be formulated for improving the performance of selected firms and the industry as a whole. The last chapter lists findings and conclusions emanating from the study, and recommendations for policy considerations along with directions for future research. CHAPTER-WISE SUMMARY OF THE THESIS Chapter I: Inter-firm comparison provides a basis for identifying factors or causes creating adverse effects or variations in the performance of a firm. Ratio analysis and regression based production function methods are popularly used to assess the performance of firms. In ratio analysis, at atime, only two factors can be considered. Multiple ratios have to be estimated to know the performance of afirm or industry. Ratio analysis requires industry averages for comparison. In case of regression-based methods, an algebraic form for the production function is assumed. It cannot describe the changes that must take place for a relatively inefficient firm to become efficient. In this respect, DEA scores over both the methods and can be used as apowerful inter-firm comparison and total factor productivity measurement tool. Chapter II: By a critical examination of the available literature on Indian Textile Industry, it has been found that most of the studies concentrated either on the industrial unrest, production problems, managing agency system, location of the units or on the size and integration of the units. However, the number of non-parametric production function based studies, that deal specially with relative efficiency of individual mills and productivity changes in textile industry, are extremely limited. Chapter III: The Textile Industry has shown phenomenal growth during the last two decades in terms of installed spindleage, production of yarn, exports, output of cloth and its per capita availability. During the last two decades, there has been manifold increase in spinning capacity, but weaving capacity of organised mill sector has witnessed a decline. The industry was not paid adequate attention during the earlier Five-Year Plan periods. Until 1978, no coherent and unified policy existed for the industry. The era ofliberalisation in the textile sector has started with the implementation of the Textile Policy of 1985. The recently announced National Textile Policy (2000) has a thrust on improving the availability, productivity and quality of cotton at reasonable price for the industry through Cotton Technology Mission. XVI Chapter IV: Among the various factors of production available for measurement of efficiency of a mill, net fixed assets, wages, energy, selling and distribution expenses are found suitable as input variables, and gross value added as output variable for estimating the relative performance of the 82 mills under reference. Among all the performance assessment techniques, DEA is an unconventional option for inter-firm comparison and productivity assessment. The study reveals that out of 82 mills, 94 % mills are found to exhibit relative technical inefficiency, about 93 % mills are found to evince scale inefficiency, and around 81 % mills are found to show pure technical inefficiency. Chapter V: Productivity changes in the Textile Mill Industry have been investigated estimating annual compound growth rates, single factor productivity trends, and DEA efficiency patterns for the period 1973-74 to 1997-98. Total factor productivity changes, technical efficiency and technological changes have been estimated in the composite mills using Malmquist Productivity Index (MPI) for the period 1991-92 to 1999-2000. Among various factors of production, net fixed assets, working capital, number of employees as input variables and net value added as output variable have been selected for industry-analysis. The input-output variables, which have been used for cross sectional analysis of the composite mills, have been selected for the MPI analysis also. Various productivity measurement approaches are discussed along with MPI. Use of growth rates and single factor productivity ratios along with DEA and MPI give more insights in performance assessment of the industry and mills. The study finds that labour productivity has increased at the rate of 5.78%, while capital productivity has declined by 3.75% perannum in the textile mill industry. Annual 6.3% productivity growth has been observed in the composite mills. Chapter VI: In this chapter, various problems affecting the textile mill industry have been discussed. Strategies and policies such as: value addition, obsolescence removal, restructuring, product diversification, people management, market demand, scrapping of excess capacity, infrastructure development, government policies, etc., have been suggested in order to overcome these problems. Yearly Assessment System (YAS) has been proposed to measure and monitor the performance of individual mill as well as that of the industry as a whole. Chapter VII: This chapter presents the findings of the study and recommendations, which are as follow: MAIN FINDINGS: Cross Sectional Analysis 1. The results of DEA analysis carried out on 82 firms representing the composite mill sector reveal that the loss of efficiency due to scale (size) effect in the mills works out to be only xvii 20 %, whereas the loss of efficiency due to pure technical inefficiency is estimated to be 32 %, thus indicating the inefficient use of inputs and improper use of input proportions (mixes). 2. The input-output slack analysis identifies the short-term deficiencies in the inefficient mills. It is found that about 31 % mills have employed excess workforce in their manufacturing activities. Excess use of energy has also been observed in 55% mills. Further, 30% mills have been found over-spending on selling, administration, storage and distribution. 3. On the basis of efficiency-output matrix, about 19% mills are found under sleeper category, about 32% under the questionable performance category, 29% under star category, and the remaining 20% under the category of dog performers. 4. The study also finds that large-size mills are more efficient than medium-size mills. These large-size mills have been indirectly benefited by economies of scale. Based on efficiency ratings, private sector mills are found more efficient than those which are in the public sector. Time Series Analysis 1. Gross output and net value added of the industry have increased at a moderate rate of3.63 %and 1.13% per annum respectively. 2. Industry's net fixed assets have grown by 7.66 %per annum, which reveals that there has been a huge expansion in production capacity ofthe industry. 3. The net income, working capital, and the number of persons engaged in the industry have declined at the annual compound rate of 1.6%, 3.17%, and 2.02% respectively. 4. Labour productivity has increased at the rate of 5.78% per annum, while capital productivity has declined by 3.75% per annum. This increase in labour productivity seems to be due to retrenchment of workers, closure of mills, and increase in capital intensity. The average number ofemployees per factory has come down from 535 in 1973-74 to 227 in 1997-98. Capital productivity has declined due to under utilization of the installed capacity of spindles and looms. 5. DEA time series analysis shows that average technical efficiency of the textile mill industry has been found 86% for the period under review. Loss of efficiency due to inefficient use of input resources and input-mix is about 10%. The inefficiency due to size differences between mills is worked out to 4%. 6. The results of the MPI model applied on the panel data of 35 private mills reveal that on an average, mills' technical efficiency has increased by 3.3 percent per annum, while technological progress has occurred at the rate of 2.9% per annum. XVlll CONCLUSIONS 1. Widespread inefficiency remains in the composite mills simply because of wasting of input resources and improper use of their proportions. There is a wide variation in the performance of mills due to differences in size, ownership, and locational factors. 2. Private mills have performed better than public sector mills, as all star category mills belong to private sector, and dog and questionable categories to public sector. 3. Large-size mills have attained higher efficiency ratings than medium-size mills. Hence, it is concluded that these mills are favoured by economies of scale. 4. Results of logistic regression show that the mill inefficiency is inversely associated with capital productivity. Results of OLS regression show that utilisation of fixed capital is inversely related to capital intensity. 5. From the value of coefficient of variation in the total factor productivity scores across the mills and the years, it can be concluded that there is a considerable deviation in the operational practices that are being followed by different mills. Workers' training in best practices could reduce this variation in technical efficiency among mills. 6. Based on single factor productivity analysis, it can be inferred that labour productivity has increased on account of capital intensity, retrenchment of workers and closure of mills, and not because of increase in efficiency and skill of labour. 7. Technical inefficiency is observed higher than scale inefficiency in the textile mill industry. Working capital and labour have not been sensibly utilised in the industry. 8. During pre-reform period (1973-1985), the textile mill industry has exhibited mixed performance. Economic reforms have made notable impact on the performance of the industry. However, during the late reform period (1996 onwards), the industry has witnessed a deterioration in its performance. RECOMMENDATIONS Micro / Mill Level 1 The firms for which the value of DEA-efficiency score has been less than one, improved performance could result from diffusion of new technical knowledge, improved managerial practices, learning by doing and efficientuse of inputs. 2 Measures to shift the frontier upward through introduction of sophisticated technology have been recommended for improving the performance of star category firms. The sleepers are better performers, they should be prime candidates for an efficiency improvement effort leading to greater outputs. 3 The reasons for the lower outputs in the dog category mills have to be carefully studied to see where improvement in the performance is possible. The questionable performance XIX 11 111 IV, mills have to be evaluated, taking into account the back history, management structure, labour relations, and location, to identify those with the potential for improvement. 4 Considering the global competition, it is recommended that the textile mills should make their yearly assessment by developing amechanism to evaluate their own performance. Meso / Industry Level 1. The mills, having value of technical change score less than one, require renovation, modernisation, and maintenance of the existing processes. There is a need to modernise management systems also hand-in-hand with technology upgradation. 2. In order to arrest decline in productivity growth of the composite mill sector, it is suggested to exploit intrinsic strengths of the mills, such as capability to supply superior quality goods, economies of scale, higher productivity, superior technology, integrated working, etc. Government Level . In order to improve the performance ofthe public sector mills, disinvestment in these mills is suggested. In general, strategic capacity additions, mergers and collaboration between the mills are recommended to attain higher economies of scale The study indicates the failure of current policies to optimise resource usage and hence suggests that the Ministry of Textiles through Textile Research Associations (viz. BITRA, ATIRA and SITRA) should consider introducing performance benchmarks based on the best industry practice. The industry is singularly over-regulated. In view of enough availability of hank yarn, the statutory obligations should be abolished. Control cloth obligation should also be abolished. In national interest, there should be agreater thrust on maximizing exports and minimizing imports providing a better future to the industry. Production and export of ready-made garments should be stepped up to facilitate employment generation. As there is an excess of capacity in spinning sector, the government should not permit expansion in spinning capacity. Efforts should be directed towards revival of sick mills, so that there will be utilization oflocked assets and rehabilitation ofretrenched workers.
URI: http://hdl.handle.net/123456789/225
Other Identifiers: Ph.D
Research Supervisor/ Guide: Singh, S.P
metadata.dc.type: Doctoral Thesis
Appears in Collections:DOCTORAL THESES (HSS)

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