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The purpose of this study is to comprehend the efficiency levels of the Indian textile industry and also its sub-sectors in the light of changing global and national business environment. It is imperative to study the efficiency levels of textile industry for an emerging economy like India, where the industry contributes up to 13 per cent in export earnings, 10 per cent in total industrial production and 2 per cent in gross domestic product (GDP). The study holds an important place in the wake of phasing out of the quota regime existing under the Multi Fibre Agreement (MFA) and the rising competition being faced from countries such as Bangladesh, Vietnam and Cambodia.

The present study attempts to have an in-depth analysis of the efficiency levels in the Indian textile industry using meta-frontier data envelopment analysis, which is a non-parametric linear programming based frontier technique.

The findings highlight that the Indian textile industry is inefficient and has a huge scope of improvement in terms of efficiency. It also confirms the existence of different production functions among the sub-sectors of the industry. Among the different sub-sectors, the proximity of production frontier of readymade garments is the closest to meta-frontier followed by cotton and blended yarn, man-made fibre, cloth and others.

The findings bear strong implications for the policymakers in their attempt to regain the lost competitive position of the Indian textile industry and to enhance its contribution in the economy. As per the findings, policymakers should target the relatively inefficient sub-sectors of textile industry (cloth, man-made fibre, cotton and blended yarn) to infuse more efficiency in these sectors to enhance the market share of the Indian textile industry in the global textiles market.

The current study is a unique addition to the sparse literature on managing efficiencies in the textile industry, particularly of emerging economy like India. Looking at the methodological and geographical coverage of the previous work, it was found that no study has explored and analysed the efficiencies of the sub-sectors in the Indian textile industry using meta-frontier analysis. Therefore, this study will be the first of its kind which seeks to fill such gaps and intends to enrich the available literature.

This research study explores the adoption of integrated sustainable SCM practices in the textile industry in India and its impact on the firm's business performance.

The analysis was carried out using the partial least squares structural equation modeling using SmartPLS 3.3.2.

It was found that the demand-side sustainability initiatives of the large firms and the internal sustainability practices of the small firms directly impacted their business performance. It was also found that the suppliers' sustainability initiatives had a direct and positive impact on the internal sustainability of the firm, which in turn had a direct and positive impact on the demand-side sustainability in the Indian textile industry.

The findings emphasize the distinctive role of each dimension of the integrated sustainable SCM on the firm performance in the Indian textile industry.

The purpose of this study was to explore relationships between textile and apparel manufacturers in India and the United States. Results of the survey indicated that respondents differed significantly on perceptions of industry opportunities and problems in their respective countries. Significant differences were also found between industry leaders in the two countries when various aspects of their business practices and opinions were examined. Findings are analysed and discussed in relation to their implications for improving global marketing strategies, industrial competitiveness, and international trade.

This study aims to examine whether export competitiveness (EC) in the two groups of the Indian textile industry i.e. “textiles” and “textile products” group differ.

The study examines how exchange rate (ER), real effective exchange rate (REER) and EC of both the groups are related in the long run over the period 1991-1992 to 2018-2019 using Granger causality test and Johansen and Juselius co-integration test.

The study confirms that EC is a challenge that needs to be addressed to sustain in the international market, as the volatile trend can be found for EC in both groups. The econometric framework shedding light on both groups of the textile industry suggest that select determinants have different relationships with the EC for two groups. The findings of the Granger causality test reveal that the presence of unidirectional causality running from ER to EC in the case of both the groups. Also, the select variables are found to be co-integrated in the long run. However, in the case of REER, no causality is found running from REER to EC.

ER is a vital determinant of EC and exporters can sustain competitiveness in global markets by reducing their profit mark-up in the face of an appreciating currency.

This paper aims to examine technical efficiency and its determinants in Indian textile garments industry in post-agreement on textiles and clothing regime and evaluate the technical efficiency among micro, small and medium enterprises (MSMEs) firms.

This study uses unbalanced panel data for the period 2005–2010 to 2015–2016. The stochastic frontier function is used to estimate technical efficiency and its determinants.

The results show that the overall ecosystem of textile garments’ value chains could be improved to enhance the technical efficiency thereof. The result also reveals that small-scale firms have the highest technical efficiency scores, and medium-scale firms have the least technical efficiency score among all the categories of MSMEs.

The textile garments industry needs to define its innovation strategies, as these strategies lead to different results that can be achieved only through the management of resources dedicated to the generation and implementation of innovations.

This study has shown that to offset India’s cost disadvantage in the international markets, there is a need to develop an ecosystem of textile manufacturing and value chains, eliminate the inverted duty structure (where inputs are taxed at a higher rate than the final product) and switch over from shuttle looms toward shuttle-less looms. This would unleash the potential of textile and garments industry and make it globally competitive and technically efficient. Further, there will be an alignment with the ease of doing business with an appropriate mix of policy, technology, institution, infrastructure, information and services.

Using frontier production function takes stochastic context into account for the dynamic character of technical efficiency and its components. Most of the past studies have assessed technical efficiency at the aggregate level using three-digit National Industrial Classification (NIC) or four-digit NIC code. An analysis at higher levels of aggregation masks the variation in technical efficiency. This study used five-digit NIC data to measure the firm-specific technical efficiency of the textile industry. According to the authors’ knowledge, this study is the first of its kind in the Indian textile industry using stochastic frontier approach and panel data. Further, it also looks at the contribution of different determinants in technical efficiency to the firms.

The Indian retailing industry has undergone dramatic changes because of the government's recent liberalization in retail sectors along with the country's rapid economic development and emerging consumer groups with market power. Despite the increasing importance of India in the global market, little is known about apparel retail sectors in India and the information available is fragmented and under‐developed. The purpose of this paper is to assess the competitiveness of the Indian apparel retail industry and the changing market conditions since the 2006 retail trade liberalization to identify the opportunities and challenges of operating in the Indian market.

This study employs Porter's diamond model as the theoretical framework. This study conducts an extensive review of published documents including academic journals, trade publications, and government and industry web sites and discusses them within the framework of the diamond model.

By analyzing the multi‐determinants of the diamond model (factor conditions, demand conditions, related and supporting industries, firm strategy and rivalry and the role of government), the authors identified key opportunities and challenges of entering the Indian apparel retail industry.

This study provides a comprehensive view of the rapidly evolving Indian apparel retailing industry by evaluating multi‐dimensions of competitive conditions in Porter's model.

This paper aims to study whether exporting enterprises are more productive in export-intensive industries. It also aims to identify the action area and policy direction for enhancing productivity in Indian textile manufacturing. Global integration has increased the volume of international trade. It is crucial for countries to have competitive enterprises to capture a larger share of the global economy. Improvement in productivity performance not only enhances competitiveness but also promotes growth in an economy.

A productivity analysis for the Indian textile manufacturing industry using firm-level panel data is conducted. The data are collected for 160 firms relevant to the period from 2007-2008 to 2012-2013 from Ace Equity database. Using the technique of data envelopment analysis, the output oriented Malmquist productivity index is computed and the sources of productivity change are identified. Also, a comparison between the productivity performance of the exporting and non-exporting firms has been made.

The results suggest that exporting firms are exhibiting better productivity performance and resource utilisation during the study period. Technology change and scale efficiency seem to be the major sources of productivity gain for exporting firms.

The research is limited to a single industry, reference database and methodology. There is scope for further in-depth, micro-level research to analyze the differences in drivers of productivity for exporting and non-exporting firms.

This paper provides validation to export promotional policies in the Indian textile industry by establishing better productivity performance of exporting firms. It also provides direction for managerial action by identifying efficiency component as the factor pulling down productivity.

Productivity gain in the manufacturing sector draws immense significance for all developing countries, particularly due to its contribution in enhancing competitiveness and promoting economic growth in the long run. The purpose of this paper is to study the sources of productivity gain for large and small-scale manufacturing firms.

This paper studies productivity performance of Indian textile manufacturing industry using firm-level panel data of 160 companies for the period 2007-2008 to 2012-2013. The output-oriented Malmquist productivity index has been computed through data envelopment analysis. Further, the sources of productivity gain are identified for the entire textile industry as well as for the small and large-scale sector companies separately.

Regarding the sources of productivity gain, technology change and scale efficiency seem to be the major drivers. Pure efficiency change is a concern for all firms irrespective of scale. The results suggest that moderately large companies are exhibiting better productivity performance during the study period.

The research is limited to a single industry, reference database and methodology. There is scope for further research at the micro-level to analyse the drivers of productivity for enterprises operating at different scales.

The paper contributes to existing literature by identifying the core action area for improving productivity performance in Indian textile manufacturing as the pure efficiency component. It also adds to research on the most productive scale of operation in manufacturing.

The Indian garment industry has witnessed a significant change since the inception of the New Textile Policy 2000 that suggests removing the industry from the list of small‐scale industries with a view to improving its competitiveness in the global market. As productivity is the driving factor in enhancing the competitiveness of any decision‐making entity (firm), a study of total factor productivity (TFP) and its sources can provide vital inputs to a firm for improving its competitiveness. Keeping this as a backdrop, the paper attempts to measure the TFP in the Indian garment‐manufacturing firms; identify sources of the TFP; and suggest measures for the firms to enhance their productivity.

The study is based on the firm‐level panel data collected from the Centre for Monitoring Indian Economy for the years 2002‐2007. One output variable, namely, gross sale and four input variables, namely, net fixed assets, wages & salaries, raw material, and energy & fuel, have been selected. The DEA‐based Malmquist Productivity Index (MPI) approach has been applied to measure the TFP.

The Indian garment industry has achieved a moderate average TFP growth rate of 1.7 per cent per annum during the study period. The small‐scale firms are found to be more productive than the medium‐ and large‐scale firms. The decomposition of TFP growth into technical efficiency change (catch‐up effect) and technological change (frontier shift) reveals that the productivity growth is contributed largely by technical efficiency change rather than by technological change.

Earlier studies on the Indian garment industry have applied the partial factor productivity approach, which has several limitations. This paper measures the TFP and identifies its sources through applying a non‐parametric DEA‐based MPI approach. Through this approach, the productivity growth is decomposed into technical efficiency change and technological change. Further, an attempt has also been made to study the variation in the productivity growth rates across location, scale‐size and type of garments.

Considering the role of the textile industry in the generation of employment and export in the Indian economy, it is important to comprehend the efficiency level in the operations of the textile units located in different states in India. In this light, the purpose of this paper is to examine the operational efficiency of textile manufacturing units in Haryana, a northern state of India.

The study applies data envelopment analysis (DEA) approach consisting of input-oriented CCR and BCC techniques along with the return to scale technique for the analysis of five years of data from 2015–2016 to 2019–2020.

The results reveal that Haryana’s textile units have significantly underperformed operationally, with an average technical efficiency score of just 0.25 for five years, from 2015–2016 to 2019–2020. The yearly ratings of the overall technical efficiency of the selected textile companies include 0.20, 0.18, 0.18, 0.40 and 0.28; PTE scores are 0.43, 0.43, 0.55, 0.60, 0.62 and scale efficiency scores 0.54, 0.44, 0.29, 0.71, 0.38, respectively, from 2015–2016 to 2019–2020. On the other hand, average of 5.8 units are functioning at the constant return to scale, 10.2 units are at increasing return to scale and average of 45 units are functioning at decreasing return to scale (DRS). It is found that most of the companies are functioning at a DRS; to boost efficiency, these companies must reduce their input size since they are running at a DRS.

The results of the current paper provide key insight into the inefficiency level of the textile manufacturing industry in the context of northern India. Industry professionals can take corrective measures based on these findings. Moreover, for investors and portfolio managers, knowing which companies are efficient and which are not will help them make better decisions. The study helps policymakers to frame appropriate policy guidelines to make the textile units in the state more efficient and competitive.

To the best of the authors’ knowledge, no study has been done so far on the operational performance of the textile industry in Haryana based on the DEA technique. So, it will contribute to the extant literature on the performance of the textile industry.