Efficiency and Ranking of Indian Pharmaceutical Industry: Does Type of Ownership Matter?

Mahajan, Varun; Nauriyal, D. K.; Singh, Sanjay Kumar

doi:10.17015/ejbe.2014.014.02

Cited by 17 publications

(8 citation statements)

References 28 publications

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“…This industry would be useful to increase the growth of the manufacturing sector in India. 6) Pharmaceuticals: The Indian pharmaceutical industry has a dominant position among the developing economies (Mahajan, Nauriyal & Singh, 2014). This industry needs knowledge and indigenous technology to increase the growth of this sector in India.…”

Section: ) Industrial Equipment and Machinery (Electrical Machinery)mentioning

confidence: 99%

“…Thus, India should use science & technology and IPRs regime to boost the growth of the manufacturing sector. In India, earlier studies have estimated the impact of various socio-economic, science & technological development and IPRs related factors on various aspects of firms in manufacturing sector (Rajesh, 2007;Bhayani, 2010;Pattnayak & Chadha, 2013;Kathuria, Raj & Sen, 2013;Debnath & Sabastian, 2014;Mahajan, Nauriyal & Singh, 2014;Sahu & Narayanan, 2015;Abri & Mahmoudzadeh, 2015;Sen & Das, 2016;Kapoor, 2016;Chaudhuri, 2016;Singh et al, 2017;Mehta & Johan, 2017;Singh, Narayanan & Sharma, 2019;Jyoti & Singh, 2020;. Also, several studies have assessed the impact of socio-economic and policy factors on growth, profit, and other characteristics of the manufacturing sector in India (Tripathy et al, 2016;Tyagi & Nauryal, 2016).…”

Section: Introductionmentioning

confidence: 99%

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Factors Affecting Firm’s Annual Turnover in Selected Manufacturing Industries of India

Singh

Jyoti²

2020

business-perspective-review

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Purpose: This study makes a comparison of the manufacturing sector and its determinants for India and selected Asian countries. It examines the factors affecting the annual turnover of randomly selected 154 firms in seven different industries of the Indian manufacturing sector. Methods: In this study, the firm’s annual turnover is used as a dependent variable. Labor productivity, age, investment on plant & machinery, annual expenditure on marketing, total employees, production technology up-gradation, shortage of skilled workers, skills to improve the process, use of hi-tech tool and technique in production activities, technology transfer abilities, in-house R&D expertise, quality certification, foreign collaboration, waste management capabilities and building capacity of firms are used as independent variables. Regression coefficients of explanatory variables are assessed using linear, log-linear, and non-linear regression models. Results: The study concluded that the firm's annual turnover has a significant association with technological development related variables, labor productivity, age, technology transfer abilities, in-house R&D expertise, quality certification, and waste management practices of firms. Implications: It suggests that Indian policymakers need to adopt a strong IPRs, education, and S&T policy in research institutions. India needs to increase R&D expenditure and researchers in research institutions. Research institutions should collaborate with the existing industries to discover more technologies and innovations for the manufacturing sector. All research organizations must set up technology transfer offices to increase technology transfer and commercialization. Furthermore, India needs to set up hi-tech firms to face global challenges. Originality: It uses primary data of 154 firms which are collected from seven different industries across Indian states. Thus, the study substantially contributes to the existing literature. Limitations: This study considers seven different industries that have high diversity in socio-economic, science & technological and IPRs related activities, technology transfer, commercialization of technology, and association with research institutions. Therefore, this study cannot provide policy suggestions for a specific industry.

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Section: ) Industrial Equipment and Machinery (Electrical Machinery)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Factors Affecting Firm’s Annual Turnover in Selected Manufacturing Industries of India

Singh

Jyoti²

2020

business-perspective-review

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“…Stochastic frontier production function approach (SFPFA) and data envelopment analysis (DEA) are the two main techniques which can be used to estimate the technical efficiency (TE) of firms/industries and other sectors of the economy (Aigner, Lovell & Schmidt, 1977;Meeusen & Van den Broeck, 1977;Chavas & Aliber, 1993;Kumbhakar & Lovell, 2003;Rajesh, 2007;Faruq & Yi, 2010;Akpan et al, 2012;Pattnayak & Chadha, 2013;Kumar & Arora, 2012;Hamjah, 2014;Zhou, 2014;Mahajan, Nauriyal & Singh, 2014;Debnath & Sabastian, 2014;Bhatia & Mahendru, 2015;Munisamy, Fon & Khin, 2015;Sahu, 2015;Ng'ombe & Kalinda, 2015;Narwal & Pathneja, 2015;Ikram, Su & Sadiq, 2016); Okoye et al, 2016;Kea, Li & Pich, 2016;Vu, 2016;Fahmy-Abdullah et al, 2017;Gebresilassie, & Nyatanga, 2017;Singh, Narayanan & Sharma, 2018;Singh, Narayanan & Sharma, 2019). Efficiency is defined as the best allocation of resources to achieve the highest level of output (Bhatia & Mahendru, 2015).…”

Section: Theoretical Framework Of Stochastic Frontier Production Funcmentioning

confidence: 99%

“…However, patenting firms have more TE as compared to non-patenting firms. Mahajan, Nauriyal, and Singh (2014) have assessed the TE of pharmaceutical firms in India using the Data Envelopment Analysis (DEA) technique. It observes that productivity and efficiency of firms improve as an increase in inputs cost on advertisement and marketing, and applications of skill labors in the manufacturing sector.…”

Section: Review Of Existing Literaturementioning

confidence: 99%

Estimating Factors Affecting Technical Efficiency in Indian Manufacturing Sector

Singh

Ashraf

Arya

2019

EJBE

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Existing studies could not estimate the technical efficiency (TE) of firms and it's affecting factors in the Indian manufacturing sector. So, the present study examines the TE of firms using a stochastic frontier production function approach. Thereupon, it examines the impact of S&T and IPRs related factors on estimated TE of firms using a linear regression model. Estimated values of TE of firms show that most firms have a TE of 94%; thus, firms are efficient in producing surplus production in the manufacturing sector. It is acclaimed that firms can improve production scale using more technological upgradation and advancement. Furthermore, empirical results indicate that process innovations of firms, quality certification of firm, firm acquired process/product patents, in-house R&D expertise of firms, public-technology support institutions of firms, proficiency to improve processes of firms, new or improved products of firms, waste management capabilities of firms, and skilled workforce of firms are appeared effective activities to increase the TE of firms. It is proposed that there is a requirement to increase R&D expenditure, a collaboration of industries with research academia, incentive to researchers and scientists to do extensive research in emerging sectors of technologies and appropriate financial support to firms to boost the growth of Indian manufacturing sector.

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“…All the inputs and output data collected from the CMIE PROWESS database are reported in rupees millions. The selection of the salaries and wages as one of the input variables is based on some previous studies (Das 2017;Das et al 2017;Mahajan et al 2014). Since the firm-level data on number of employees is not frequently reported in the CMIE PROWESS database, salaries and wages data is considered as a measure of labour input of the firm.…”

Section: Variables For First Stage Tfpg (Mi) Estimationmentioning

confidence: 99%

An Evaluation of the Determinants of Total Factor Productivity Growth in Indian Information Technology Industry: An Application of DEA-based Malmquist Index

Das

2017

CEREM

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Aim: India has emerged as one of the most favoured destinations in the global Information Technology (IT) outsourcing market. On the other hand, the IT industry has been playing an instrumental role in transforming India’s image from a low income-backward nation to a knowledge-based economy. Furthermore, the role of IT industry has been pivotal in putting India on a higher growth path. In addition, India’s IT industry has been showing robust performance in revenue earning, particularly in export revenue. However, the performance of this industry is likely affected by some recent global phenomena, such as 2008’s subprime crisis originated in the US, uncertainties in changes in H1-B visa rules, Britain’s exit from the EU, automation etc. There are other factors, like exchange rate volatility, emerging competition from other low-cost outsourcing destination countries, are also posing threat to India’s IT-outsourcing business. Against this backdrop, it is crucial to analyse the sustainability of performance of Indian IT industry. Thus, the present study aims at assessing the performance of Indian IT industry and evaluating the determinants of performance thereafter.Design / Research methods: To realize the objectives of the study, firm level data has been collected from the Centre for Monitoring Indian Economy (CMIE) Prowess database. For empirical analysis, we have applied a two-stage method. In the first-stage, we have used Data Envelopment Analysis (DEA) based Malmquist Productivity Index (MPI) to evaluate the Total Factor Productivity Growth (TFPG) of Indian IT industry during the period from 2004-05 to 2014-15. For this purpose, a balanced panel consists of 70 IT firms has been considered. Further, the TFPG has been decomposed into three components, viz. Catch-up, frontier-shift, and scale efficiency change (SEC). Consequently, in the second-stage, three random-effects panel regression models are considered to investigate the determinants of TFPG, catch-up, and frontier-shift separately. Conclusions / findings: During the study period, the average TFP and frontier-shift has been improved. On the other hand, catch up effect is found to have declined. The variables, such as export intensity, salaries and wages intensity have positive and statistically significant impact on the catch-up and frontier-shift. Export intensity has positive impact on TFPG. Age of the firms has positive impact on catch-up and TFPG. Salaries and wages intensity has positive impact on TFPG. On an average, the firms which spent on research and Development (R&D) have experienced improvement in TFPG and frontier-shift. The public limited firms performed better than their private counterparts in terms of catch-up, frontier-shift, and TFPG. The non-group firms have performed better than the group firms in case of catch-up. On the other hand, on an average, the firms exhibiting decreasing Returns to Scale (DRS) are found to have registered deterioration in catch-up and TFPG with respect to the benchmark firms which are exhibiting Constant Returns to Scale (CRS). The firms exhibiting Increasing Returns to Scale (IRS) have shown improvement in catch-up and TFPG over the benchmark CRS firms. The impact of the US subprime crisis has been negative on catch-up, frontier-shift, and TFPG. The firms, which have spent on royalty, have experienced improvement in catch-up and TFPG. Originality / value of the article: So far in our knowledge, not so many studies of this kind have been done in the arena of empirical research pertains to the IT industry, especially in a developing country like India. Moreover, we have not found any study that covers the span of the dataset considered in the present study. In addition to this, the present study has employed a random-effects panel model to accommodate a number of time-invariant dummy variables which would not be possible in case of a fixed-effects panel model incorporated by some previous studies of this genre.Implications of the research: The identification of the determinants of TFPG and its components would help the stakeholders and policy makers of the IT industry to formulate appropriate policies which could mitigate the risks faced by the industry on one hand, and stimulate the forces that would enhance the growth of this industry on the other. For instance, to mitigate future risks, Indian IT industry should reduce its dependence on the US and UK markets. Besides, it should explore new markets in the EU, and other emerging economies where opportunities are plenty. To maintain India’s robust global position in the long run, Government of India should play the key role in providing world class infrastructure and telecommunication facilities to its IT industry. In addition to this, Government needs to rationalise and simplify the existing Indian labour law to facilitate the business of IT industry. Various stakeholders along with the Government should put necessary efforts to develop the domestic IT market as there exists ample of opportunities in future. Keywords: information technology industry, data envelopment analysis, Malmquist productivity index, random-effects model, total factor productivity, catch-up, frontier-shift, India. JEL: C23, C61, L86, O47

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Efficiency and Ranking of Indian Pharmaceutical Industry: Does Type of Ownership Matter?

Cited by 17 publications

References 28 publications

Factors Affecting Firm’s Annual Turnover in Selected Manufacturing Industries of India

Factors Affecting Firm’s Annual Turnover in Selected Manufacturing Industries of India

Estimating Factors Affecting Technical Efficiency in Indian Manufacturing Sector

An Evaluation of the Determinants of Total Factor Productivity Growth in Indian Information Technology Industry: An Application of DEA-based Malmquist Index

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