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  Many students struggle to conduct an effective Ph.D. literature review. To write an effective PhD literature review writing, it is an essential factor to synthesize and evaluate it according to the guiding concept of your dissertation or research question. We can assist with your topic, title, proposal, introduction, methodology, background, evidence, conclusion, recommendations, referencing and appendices. We can even write you a full Ph.D. thesis to your exact specification or we can revise your work and edit it to improve it. Our experts will review your dissertation proposal, plans, ideas, introduction - or whatever chapter you completed so far- and create a concise, valuable literature review for you. Contact Us India : +91 8754446690 UK : +44-1143520021 Email: info@phdassistance.com
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  • 1. © 2017-2018 All Rights Reserved, No part of this document should be modified/used without prior consent PhD Assistance ™ - Your trusted mentor since 2001 www.phdassistance.com India: Nungambakkam,Chennai-600034 # +91 8754446690 Info@phdassistance.com 1 Globalization and Productivity Analysis of Indian Small Scale Industrial Sector
  • 2. © 2017-2018 All Rights Reserved, No part of this document should be modified/used without prior consent PhD Assistance ™ - Your trusted mentor since 2001 www.phdassistance.com India: Nungambakkam,Chennai-600034 # +91 8754446690 Info@phdassistance.com 2 Table of Contents CHAPTER II: REVIEW OF LITERATURE Section I 3 Section II 8 Section III 14 Section IV 15 References 25
  • 3. © 2017-2018 All Rights Reserved, No part of this document should be modified/used without prior consent PhD Assistance ™ - Your trusted mentor since 2001 www.phdassistance.com India: Nungambakkam,Chennai-600034 # +91 8754446690 Info@phdassistance.com 3 CHAPTER II: REVIEW OF LITERATURE The present chapter is the review of literature pertaining to the study with the purpose of conveying the knowledge and ideas that have been established on the topic previously. The intention of this chapter is to formulate the problem statement precisely and develop the basis for undertaking the research. The review of previous literature is to identify and state the objective in a clear manner and postulate the premise of the study. The present chapter will be a review of the number of studies which elucidate the efficiency and productivity levels in the Indian industrial sector, and in specific the small scale industrial sector of the country. This aids on the formulation of the suitable methodology for the present study. Global economic integration, open market policies, rapid growth of technology, the intense competition between traders and productive companies and the revolution in media created a positive stir in the Indian economy which led to the emergence of a vast number of small scale industrial and productive units in India. In this context, the present study will analyse various empirical studies that have been conducted which are based on the examination of different growth and performance aspects of the Indian industrial sector, especially small scale units. The chapters are categorised into three sections. Section I deals with the review of previous studies pertaining to the measurement of technical efficiency in the Indian manufacturing sector. Section II analyses the empirical studies relating to the performance and productivity of the Indian industrial sector. Section III examines economic reformation in India and sustainability of Indian Small scale industries. Lastly, section IV will focus on reviewing studies that are relating to the challenges and problems faced by the Indian small scale industries. Section I Parameswaran (2002) analysed the performance of the Indian manufacturing sector in the selected industries in terms of assessing the technical efficiency against the industrial and trade liberalisation introduced in the year 1991. Time varying firm specific technical efficiency is measured using the stochastic frontier production function. The results of the study revealed that the selected industries showed high rate of technical progress during the post reforms period which is accompanied with the decline in the level of technical efficiency. However, the effect of economic liberalisation on the technical efficiency of the selected firms varied from one another. In addition, the study discerned that international trade involvement with respect to import and export of industrial raw materials had a positive effect on the technical efficiency. Kumar (2004) evaluated the growth and development of the Indian industrial sector by measuring the Total factor productivity (TFP) for 15 major states in India for the period 1982-83 to 2000-01. Non- parametric linear programming methods were used to calculate the TFP growth
  • 4. © 2017-2018 All Rights Reserved, No part of this document should be modified/used without prior consent PhD Assistance ™ - Your trusted mentor since 2001 www.phdassistance.com India: Nungambakkam,Chennai-600034 # +91 8754446690 Info@phdassistance.com 4 in Indian states. The growth measured through TFP is disintegrated into efficiency and technological changes and the bias in the technical change is also measured. The results obtained from the use of non- parametric linear programming methods are used to examine whether economic liberalisation had positive impacts on the efficiency and productivity in the Indian economy. Post and pre reforms period analysis was conducted. The findings of the study revealed significant growth in the Indian economy after liberalisation. The growth is attributed to the changes in TFP which is governed by the progress in technical aspects. The progress in technological aspects in the productive sector of the state exhibited a capital bias during the period of study. The differences in the region wise TFP is evident; however, the difference in the variation significantly declined in the post –reforms period. In addition, it is also found that the rate of TFP growth is converging among the different states of the country during the post- reforms period and those states which were efficient technically during the post-reforms period had significant growth. Sivakumar and Patnaik (n.d.) estimated and analysed the efficiencies of the Indian industrial sector in terms of technical productivity within the period 1973-74 to 1997-98. The study covered 144 three-digit industries and calculated their efficiency within the specified time period. The study is aimed to capture the technical efficiency behaviour during the pre and post economic reforms period. Time-varying stochastic frontier production function in the transcendental logarithmic form is employed in the study wherein the analysis using the selected methodology revealed that the efficiency of the selected industries in the period of 1973-74 to 1997-98. The findings of the study revealed that the effects of industry specific inefficiency hinder the growth of production in the selected industries in achieving the maximised output. Other factors such as weather, strikes and luck are neglected in the study. The study further identifies that the technical efficiency of the selected industries is low in post –reforms period when compared with that of the pre-reforms period. Madheswara et al. (2007) applied the Stochastic Production Frontier analysis to examine the Total Factor Productivity (TFP) growth during the period between 1979-80 and 1997-98. Sector level data within the Indian industrial sector was used for the analysis. The study is concentrated on the trends of technical efficiency change (TEC) and technical progress (TP). Stochastic Production Frontier analysis is employed in the study to segregate the two principal components, technical efficiency change (TEC) and technical progress (TP). This process of segregation is also used to recognise the growth in productivity which could be either due to improvement in efficiency or progress in technology. The significance of utilising the frontier approach as an alternative to the traditional index number approach to measure the growth of productivity lies within the identification of unobservable and idealized production possibility frontier with production-unit specific one-sided deviation from the frontier. If a unit of production functions below the production frontier, then the maximal distance is the measure of
  • 5. © 2017-2018 All Rights Reserved, No part of this document should be modified/used without prior consent PhD Assistance ™ - Your trusted mentor since 2001 www.phdassistance.com India: Nungambakkam,Chennai-600034 # +91 8754446690 Info@phdassistance.com 5 its technical efficiency. Henceforth, the Stochastic Production Frontier analysis method captures the change in efficiency and the change in technologies as the constituting parts of the change in productivity which is an additional dimension for analysis of policy perspectives. The results of the study suggest that during the period 1997-98, the total factor productivity growth in a majority of companies improved when compared with the same during the pre-reforms period, and in specific 1980-81. In addition, the study findings also revealed that the TFP growth is steered by progress in technology and technological change adaptation in the companies rather than change in technical efficiency. Bhaumik and Kumbhakar (2008) employed the use of plant-level data for the years between 1989-90 and 2000-2001 in order to assess if the growth that occurred after 1991 resulted in the use of resources more efficiently. This is inclusive of the assessment for factor inputs inclusive of capital. The findings of this study are indicative of the fact that the increase in productivity during the 1990’s was largely attributed to the increase in factor inputs. Other findings of the study included the alteration of the technical efficiency. This was evidenced with the decline in the median technical efficiency across all industries except one in the set timeline as above, however, this change in the technical efficiency offers a partial explanation as to the change in the added gross value. The analysis of the research points to the aspects of the increase in return for the factor inputs in these two years which explains the change in gross value increase across these industries more adequately. Another study by Mazumdar et al. (2009) evaluated the technical efficiency in order to measure the competitiveness of pharmaceutical firms in India from 1991-2005. The study employs a non-parametric approached of Data Envelopment Analysis (DEA). The analysis reveals that even though the efficiency outputs were found to be declining, the evidence also depicted that resources were being made use of adequately in this period. An aspect of the study that attempted to identify the factors contributory to technical efficiency revealed that the export expenditure, research and development (R&D) or the use of imported and expensive equipment did not improve the technical efficiency of the firm. Mitra et al. (2011) in this regard explores the role of factors such as infrastructure, information technology, communicative technology and R&D as predictors for technical efficiency and total factor productivity growth. The study was carried out from 1994-2008 in the Indian manufacturing industry. In this study advanced estimation techniques are used in order to counteract the existing limitations such as non-stationary omitted variables, reverse causality and endogeneity. This was carried out by the application of a fully modified OLS, panel co- integration and also system GMM. The findings of the study reveal that infrastructure and the IT with communicative technology are strongly associated with the technical efficiency. Another interesting finding is that the companies that are more globally acquainted were more likely to
  • 6. © 2017-2018 All Rights Reserved, No part of this document should be modified/used without prior consent PhD Assistance ™ - Your trusted mentor since 2001 www.phdassistance.com India: Nungambakkam,Chennai-600034 # +91 8754446690 Info@phdassistance.com 6 have deficiencies in the infrastructure (like transport or chemical companies). The implications of the findings are that the improvement in the infrastructure and the IT components of the firm can aid to the enhancement of these sectors further improving the competitive edge for India. The findings also shed light on the current scenario of infrastructure in India. Lastly, as with the study above this study too finds for R&D being a weak predictor for technical efficiency, to the extent that it does not impact the manufacturing industry, but however that it may play a more vital role in industries that depend on research. Bhandari et al. (2010) too explored the economic realms of the manufacturing sector in India and employed the DEA in order to study the economic reforms. This was done to measure the technical and scale efficiency changes that occurred before and after 1991 as per the reform initiatives. It was found that the efficiency of the industries declined in the post reform period as compared to the pre reform period. These implied that the findings are rather significant for the manufacturing industries but also implies that the changes are varied across different industries. Another study conducted by Kathuria et al. (2013) in the manufacturing industry in India post the economic reforms in 1991. This study too employed the use of advanced estimation techniques such as non-parametric accounting, semi-parametric product function accounting for endogeneity and parametric stochastic production frontier to measure the total factor productivity (TFP). The study assessed the same for the periods of 1994-95 and 2005-06. The study findings reveal that the TFP for both the formal and informal sectors differed vastly over the timeframe. There was a decline in the TFP in the formal sector between 1994 and 2001. In the case of the informal sector, all the three methods showed a decline in TFP for 2001-2006. This evidences that the inconsistencies in the measure for TFP exist, especially between the formal and informal sectors of the manufacturing industry. Baliyan et al. (2015) analysed the changes in efficiency and productivity in the 17 major Indian states known for its considerable growth in the manufacturing sector during the period 1971-82 to 2009-10. State-wise productivity change and efficiency are measured using the Data Envelopment Analysis (DEA) approach which is calculated over the period of 1973-1974 to 2009-2010. The period is divided into pre-liberalisation (1980-1981 to 1989-1990), first phase of post-liberalisation (1990-1991 to 1999- 2000) and second phase of post-liberalisation (2000- 2001 to 2009-2010). Total Factor Productivity (TFP) change is calculated using the non- parametric Data Envelopment Analysis (DEA) approach. In addition, the paper evaluates the performance metrics of the major inputs used in the Indian industrial sector and reveals the reasons for inefficiency across the different segments. The findings of the study revealed that the productivity growth and efficiency vary across the different states in the country.
  • 7. © 2017-2018 All Rights Reserved, No part of this document should be modified/used without prior consent PhD Assistance ™ - Your trusted mentor since 2001 www.phdassistance.com India: Nungambakkam,Chennai-600034 # +91 8754446690 Info@phdassistance.com 7 Chaudhuri (2016) examined the impacts of economic reformation (liberalisation) on the technical efficiency and technical progress of the electronics and hardware manufacturing units in India. Translog stochastic frontier production function is used in the present study to assess the technical progress and technical efficiency of the industries in the era of economic reformation. The findings of the study revealed that the electronic manufacturing units in India experience improvements in the technical progress during the period of 2001-2002 to 2009-2010. However, the mean level of technical efficiency of the firms had a declining rate during the same period. The study thereby discerns that a majority of companies failed in spite of the Information Technology Agreement (ITA) of World Trade Organization (WTO) implementation and such implementation does not impact the technical efficiency of the electronic manufacturing firms. Section II Unel (2003) analysed the trends of productivity in the manufacturing sector of India during the period of 1980-81 to 1998-1999. The findings of the study revealed that the labour and total factor productivity (TFP) growth in the Indian industrial sector were significantly higher till the 1980s; however, the accelerated growth of the TFP is attributed to factor elasticities and the production function structure. The productivity growth of the manufacturing as well as the subsectors improved after the liberalisation. In the same context, Banga and Goldar (2004) assessed the contribution of services to the productivity and output growth of the Indian industrial sector during the pre and post reforms period. The KLEMS (capital-labor-energy-materials-services) production function framework is used to analyse the contribution of the services to the productivity and growth of the Indian manufacturing sector. The utilised production framework considers services as inputs to the process of production. The study used panel data of 148 three-digit level industries during the time frame of 1980-81 to 1997-98 (18 years) and the data is used to estimate the production function. The results of the analysis revealed that the increasing use of services brought favourable effects on the productivity and output growth of the Indian manufacturing sector in the 1990s. It is also to be noted that such favourable could even be due to the economic liberalisation that was carried out. It is revealed in the study that the percentage of contribution of services that are input to the growth of the manufacturing sector is just one per cent in the 1980s; however, the rate increased to 25 per cent in the 1990s. A multilateral total factor productivity index is used to study the effect of services on the productivity of the manufacturing units. The index is constructed for a majority of 41 industry groups for the period of 1980-81 to 1999-00 and the index is constructed for both with and without services. It is revealed that the estimate for productivity growth during the period of post-reforms is found to be over-stated when the services are not considered. The findings of the study indicated that the economic reforms are responsible for the growth of manufacturing units in the country post liberalisation.
  • 8. © 2017-2018 All Rights Reserved, No part of this document should be modified/used without prior consent PhD Assistance ™ - Your trusted mentor since 2001 www.phdassistance.com India: Nungambakkam,Chennai-600034 # +91 8754446690 Info@phdassistance.com 8 Kaur and Kiran (2008) the trends in the partial productivity and the total productivity factor in the all Indian manufacturing units for 22 industrial groups at the aggregative and disaggregative levels. Other trends in the output and inputs are also analysed in the study. The period selected for the study is 1980-81 to 2002- 03 wherein for the purpose of evaluating the growth of the indian industrial sector, the period for study is divided into two: 1980-81 to 1990- 91 as the pre-reforms period and 1991-92 to 2002-03 as the post reforms period. The study assesses the changes in the growth of inputs and output and productivity during the pre and post reforms period. The comparison of results based on the pre and post reforms growth in productivity in the Indian industrial sector revealed that the post reform era had a slower growth rate than the pre-reforms period for both aggregative and disaggregative levels. In the same context, Das and Kalita (2009) computes the productivity growth of the industrial sector in aggregate levels. The Domar aggregation technique is used to compute the productivity growth in the Indian manufacturing sector which is the steering factor for the overall growth of the industrial sector. However, the study states the measurement of the productivity growth is still an issue due to two reasons. Firstly, a firm’s productivity should be reflected in the productivity of the lower levels which form the aggregate. Secondly, the aggregate productivity should highlight the importance of the inter-industry transactions in the analysis of the productivity growth. Domar weights were used to compute the total factor p
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