Indian Manufacturing Industries Research Articles

Analyzing green entrepreneurial orientation drivers: Insights from the Indian manufacturing industry

ABSTRACT Business activities often lead to various environmental issues, like deforestation, waste, and pollution. Hence, integrating environmental concerns into manufacturing operations is essential for ensuring long-term sustainability. In this direction, green entrepreneurial orientation (GEO) represents an internal strategy that integrates environmental concerns into business operations. While much of the discussion around GEO has centered on the manufacturing sector in general, the unique dynamics of the textile industry have often been overlooked. This highlights the need for a more targeted exploration of GEO drivers specific to the textile sector. An exploratory approach has been used in the study, where in the first stage drivers are identified through a literature review strategy, while the second stage involves analysis of the company sustainability reports to validate the drivers. The results indicate that managerial environment concerns, technical orientation, big data analytical capabilities, environmental collaboration, and institutional pressure are the primary drivers that must be operationalized by firms to implement GEO. Furthermore, textile firms are concentrating on five core areas that align with GEO principles: energy efficiency, renewable energy, water and effluents management, waste management, and awareness programs. The study provides implications for managers and policy makers to prioritize the integration of environmental concerns into strategic decision making, foster collaborations, invest in data-driven technologies, and strengthen regulatory frameworks to encourage the adoption of green entrepreneurial practices.

Investigating the Measures of Sustainable Business Performance in Implementation of Industry 4.0 in Indian Manufacturing Industries: A PLS-SEM Approach

Investigating the Measures of Sustainable Business Performance in Implementation of Industry 4.0 in Indian Manufacturing Industries: A PLS-SEM Approach

Assessing Drivers Influencing Net-Zero Emission Adoption in Manufacturing Supply Chain: A Hybrid ANN-Fuzzy ISM Approach

Nowadays, there is a constant focus on implementing the net-zero emission (NZE) concept in the manufacturing supply chain (MSC). To reduce emissions and improve organisational efficiency, adopting the net-zero concept is a prevalent trend in today’s highly competitive global business environment. Governments and stakeholders are pressuring the manufacturing sector to use natural resources efficiently and reduce environmental impacts. As a result, the manufacturing industry is focusing on cleaner production using net-zero practices. This study aims to identify and analyse the interaction among the drivers of net-zero adoption in the MSC. Through a systematic literature review (SLR), a list of drivers was recognised. To validate these drivers, we conducted an empirical study with 173 respondents from the Indian manufacturing industry. Further, we employed an artificial neural network (ANN) to weigh the nonlinear effect of drivers. Fuzzy interpretive structural modelling (F-ISM) was used to identify the interaction relationships among the drivers and construct a hierarchical structure among these identified drivers. The fuzzy matrix of cross-impact multiplications applied to the classification (F-MICMAC) method was used to categorise these drivers into driving and dependent categories. The outcomes of ANN show that Environmental predictors (100%) emerged as the most significant drivers, followed by Economic drivers (60.38%) and Technological drivers (59.05%). This study is a valuable resource for academia and industry professionals, providing essential insights into how adopting net zero facilitates the manufacturing industry’s ability to achieve net zero across the supply chain.

Sustainability index development by integrating lean green and Six Sigma tools: a case study of the Indian manufacturing industry

PurposeIndia’s manufacturing sector employs about 12% of the labour force and contributes to about 17% of the nation’s GDP. The Indian government intends to implement several initiatives under the “Make in India” and Atma Nirbhar Bharat banners to increase the manufacturing sector’s share of the nation’s GDP to 25% by 2025. Applying lean manufacturing, green manufacturing and Six Sigma is crucial to ensure that India’s manufacturing sectors grow sustainably in international markets. This study aims to identify sustainability indicators and ascertain their respective weights to evaluate the sustainability performance of the Indian manufacturing industry.Design/methodology/approachThis research identifies 25 sustainability indicators and classifies them into the triple bottom line of sustainability based on an evaluative literature review and expert opinion. The Best Worst Method was utilised to determine the weights of the sustainability indicators. The sustainability index was developed to evaluate economic, social and environmental sustainability.FindingsThe sustainability performance of a foundry in a significant Western Indian State city was assessed by applying the developed sustainability index. After the adoption of integrated lean, green and Six Sigma (LG&SS) strategies and related practices in the foundry, there has been a notable improvement of 68.03% in the economic index, 61.62% in the social index and 13.24% in the environmental index.Research limitations/implicationsThe proposed sustainability index is applied and evaluated specifically for assessing the sustainability performance of Indian manufacturing SMEs. It can be used to substantiate firm’s sustainability performance and also to assess the improvement in firm’s performance in economic, environmental and social dimensions after implementing various operational excellence practices. However, it cannot serve as a benchmark tool across similar companies or organisations.Practical implicationsThe developed sustainable index can be used to analyse the company or organisation’s sustainability performance and see how various strategies have improved things. Practitioners can use this index to assess social, economic and environmental performance and focus on areas that need improvement.Social implicationsThe proposed sustainability index serves as a vital tool for monitoring a firm’s progress in triple bottom line (TBL) dimensions of sustainability, tracking a diverse range of indicators and encouraging sustainable organisational practices.Originality/valueThis study attempts to assess the economic, social and environmental performance of Indian Manufacturing SMEs by proposing a sustainability index.

Lean Practices in Tractor Manufacturing Industries in India

Lean is one of the most popular concepts of an Industry and being utilized to improve efficiency by reducing or eliminating waste. This study investigates the impact of implementing lean practices in Indian Tractor Industry, specifically the 5S System, Kanban Framework, Worth Stream Planning (VSM), and Kaizen (Nonstop Improvement), based on hierarchical execution in conditions of conveyance and adaptability improvement, business result upgrade, and efficiency improvement. The examination philosophy includes relapse investigation of information gathered from businesses that have embraced lean practices. This research paper will focus on the existing research gap on impact of Lean Practices in the manufacturing operations in Tractor Manufacturing Industry in India. Keywords: Lean Manufacturing, Shop Floor Management, Qualitative Research, Tractor Industry

Impact of Digital Transformation on Indian Manufacturing Industry

Impact of Digital Transformation on Indian Manufacturing Industry

Enablers Impacting the Circular Economy in Indian Manufacturing Industries: Modeling through a SmartPLS4-SEM Approach

Enablers Impacting the Circular Economy in Indian Manufacturing Industries: Modeling through a SmartPLS4-SEM Approach

Achieving energy efficiency and sustainability in galvanization process: A case study on Indian tower manufacturing industry

Abstract There is a significant gap between India’s energy production and its demand. Dependency on energy imports to meet the energy requirement affects the economic growth & overall development. The manufacturing sector consumes a substantial portion of the country’s energy but also holds considerable potential for reducing consumption. This paper presents a case study on an Indian tower manufacturing industry, aiming to achieve energy efficiency and sustainability in the galvanization process through the application of the statistical tool Design of Experiments (DOE). By systematic implementation of 22 factorial model of DOE, the study identified that the excessive zinc coating thickness is the major cause of energy consumption in hot-dip batch galvanization process (HDBGP). It was found that average LPG consumption is minimized at moderate coating thickness. Applying DOE resulted in a 38.67% reduction in LPG consumption when the zinc coating thickness was maintained at a moderate level in HDBGP. DOE provides a systematic mechanism based on experimental data to identify potential causes of problems and offers statistical validation of results. This research focuses on creating an energy-efficient production system and demonstrates the practical application of statistical tools and techniques to achieve sustainable competitive advantages. Highlights Experimental work using the Design of Experiments tool identified excessive zinc coating thickness as the primary cause of high energy consumption in the hot-dip batch galvanization process. Validation of optimized parameters showed that average energy consumption is minimized at moderate coating thickness, resulting in a 38.67% reduction in energy usage. Design of experiments tool provides a systematic mechanism based on experimental data to identify potential causes of problems and offers successful validation of results. Discussion While the significant reduction in LPG consumption enhances energy efficiency and sustainability, excess reduction in coating thickness may compromise the quality and durability of galvanized products, potentially leading to higher long-term costs for maintenance and replacements. Additionally, the focus on statistical tools like DOE alone could divert attention from exploring alternative potential energy-saving technologies and methods that might offer greater benefits. Therefore, it is also essential to consider the broader implications and potential limitations of various approaches in the quest for sustainability and competitive advantage suitable for the existing manufacturing setups. Graphical abstract

Do firms’ performance act as a catalyst of innovation: empirical evidence from innovative Indian manufacturing firms

PurposeThis paper aims to explore whether firms’ performance determines innovation using a sample of Indian manufacturing firms. The impact of innovation on firms’ performance across specific countries has been discussed in the literature. However, the effect of firms’ performance on innovation output, especially for a developing country like India, remains an open question. Against this backdrop, this paper investigates whether firms’ performance determines innovation in Indian manufacturing firms.Design/methodology/approachThe authors use patent filing information to instrument innovation and total factor productivity to instrument firms’ performance. The patent data are collected from the Patent Search and Analysis Software database and firm-level data from the Centre for Monitoring Indian Economy’s Prowess database. The study uses a sample of 309 Indian manufacturing firms from 2005 to 2021. Given the count nature of the data set used in this study coupled with over-dispersion issues, the authors have used the negative binomial regression to estimate the empirical specification of the models. There could be a possible problem of endogeneity due to the contemporary nature of innovation and firms’ performance. Therefore, to address the possible issues of endogeneity in the model, the authors have used the Generalized Method of Moments (GMM) estimators for more robustness checks of the empirical results.FindingsThe empirical results exhibit a positive and significant impact of firms’ performance on the innovation output, validating that firms’ performance determines innovation in Indian manufacturing firms. The posterior estimation results using GMM estimation also corroborate that firms’ productivity is a determining factor for the innovation output of Indian manufacturing firms. Furthermore, empirical results exhibit that the ex ante innovativeness of the firms substantially affects the current innovation. This validates that the firms’ prior experience, learning by doing and past innovative efforts are more likely to precipitate more innovation in the current period.Originality/valueThis paper’s main contribution is empirically estimating whether firms’ performance determines innovation, which is hardly discussed in the existing innovation literature, specifically using Indian manufacturing industries. Further, it adds to the existing literature in two other prominent ways. First, this paper investigates whether firms require ex ante expertise to innovate or if a firm starting from scratch can innovate significantly without any hindrances. Second, it enriches the literature by instrumenting innovation in output terms with the patent application against input measures of innovation, such as research and development expenditures, acquisition of machinery and equipment, while discussing the relationship between firms’ performance and innovation, specifically in the context of a developing economy like India.

Does carbon intensity affect technical efficiency? An empirical assessment of manufacturing industries in Maharashtra, Odisha, and India

Technical progress has a tremendous potential to reduce carbon dioxide emissions by reducing energy consumption, a major concern across production units. However, the existing empirical literature concerning technical efficiency and carbon intensity is scanty. Thus, this paper examines the relationship between technical efficiency and carbon intensity for the organized manufacturing sector of two states, Maharashtra and Odisha, and the all-India level from 2001 to 2018. The paper uses data envelopment analysis to estimate technical efficiency scores. It applies the 2006 Intergovernmental Panel on Climate Change Tier 1 methodology for estimating carbon intensity for each 3-digit manufacturing industry in all three sample cases. The study has used static panel regression and fractional logit regression techniques to examine the deterministic relationship between technical efficiency and carbon intensity. The result shows that technical efficiency is highly sensitive to carbon intensity in the Indian manufacturing industries. The findings also addressed that the size of the industries also reduces the technical performance of manufacturing units. This paper also confirmed that increased profit could boost the Indian manufacturing industries’ technical efficiency. Thus, this study addresses that carbon intensity as a proxy for the manufacturing sector’s potential to affect climate change plays a crucial role in explaining the technical efficiency variations across industries. Thus, it calls for better policies aimed at reducing the emissions of industries specifically to achieve sustainable growth for the Indian manufacturing sector.

Investigating smart manufacturing process implementation in the Indian manufacturing industries using tecnomatix and response surface methodology

Investigating smart manufacturing process implementation in the Indian manufacturing industries using tecnomatix and response surface methodology

From intentions to action: how behavioural intentions shape employee performance through digital learning?

PurposeThis study aims to explore the impact of “Performance Expectancy” (PE) on the performance of Indian automotive manufacturing employees through their “Behavioural Intention” (BI) in the context of digital learning within the volatile, uncertain, complex and ambiguous (VUCA) world.Design/methodology/approachA descriptive research design was adopted to gather data from 211 employees of Indian automotive manufacturing companies. Structural equation modelling was applied for data analysis and obtaining results.FindingsLargely, the findings indicate that BI does mediate the relationship between PE and employee performance (EP) in the context of the Indian automotive manufacturing sector. The findings would help in boosting digital learning initiatives, improving EP and fostering organizational success in the VUCA world.Research limitations/implicationsThe current study focused on the Indian manufacturing industry. Extending the research beyond the manufacturing sector to other industries in India could possibly help in generalizing the findings, and thereby enhance knowledge of the broader consequences of digital learning on EP.Practical implicationsDigital learning platforms can enhance sustainable industrialization in the manufacturing sector by providing employees with access to digital learning opportunities. Managers must provide employees with access to digital learning opportunities for making them more creative and innovative, so that they can become real change agents, and can handle real-world problems more efficiently, leading the organization to deal with the complexities and unpredictability in this VUCA world.Originality/valueWithin the ambits of Indian automotive manufacturing organizations, there have been limited research studies that have used two constructs of the UTAUT2 framework to see their impact on EP in terms of digital learning. Thus, based on the limited information available, this research stands as a pioneering effort in the realm of digital learning within the Indian automotive manufacturing industry, where the relationship between PE and EP is examined through the mediational role of BI of employees. Moreover, this research possibly would pave the way for further research studies on exploring the role of potential factors influencing the strength and direction of the relationships between these variables (PE and EP).

Mediating factors and spillover effects of foreign direct investment : Evidence from Indian manufacturing firms

The present study examines the extent and direction of horizontal, backward and forward spillover effects of FDIs on firms' productivity. It also shows how the mediating factors (firm's age, export and import intensity, R&D and advertisement intensity) contribute to the firms' productivity. Further, the study also uncovers the importance of the ownership patterns of the firms that affect the spillovers. It uses a balanced firm-level panel data set from the Indian manufacturing industries over the available period 2003 to 2016 to examine the inter- and intra-industry spillovers of the FDIs. The estimation methods used in this study are the fixed effects approach and the generalised method of moments. The study also applies the Levinsohn-Petrin method to compute firm-level productivity. It finds a significant positive spillover backward effect and confirms the supportive role of the mediating factors in augmenting the spillover channels. However, the results do not support the existence of horizontal and forward FDI spillover effects for the overall manufacturing industries. They suggest that a comprehensive policy package approach be used, thereby underlining the importance of all channels of the FDI spillover effects and their relations to the downstream sector, particularly by keeping the performance of the firms and their external links in perspective.

What explains exit in Indian manufacturing industries?

PurposeThe purpose of this paper is to investigate the likelihood of firm exit, focusing on firm- and sector-specific factors and other potential constraints that may lead to exit.Design/methodology/approachThe authors address the main research question by using hazard-cox and probit models on plant level data for the period 1998–1999 to 2012–2013, drawn from the Annual Survey of Industries collected by the Central Statistical Organisation.FindingsThe authors find that probability of exit reduces with improved firm performance. Urban firms, proprietary firms and smaller firms are more likely to exit as compared with their respective counterparts. The findings are robust to alternate measures of performance, alternate specifications and different methods.Originality/valueStudies of entry and exit rates at a point in time are useful in examining the turnover of establishments. But to understand the establishment survival, the authors must also examine the probability of firm exit and the possible determinants that aid exit. There are institutional factors that prevent easy exit of firms from an industry. It would be worthwhile to see how the exit rate will be impacted if these barriers ceased to exist. In this study, the authors construct a model of exit, which would help us to predict firm exit.

Validation of Lean–Green–Six Sigma practice model for improving performance and competitiveness in an Indian manufacturing industry

Validation of Lean–Green–Six Sigma practice model for improving performance and competitiveness in an Indian manufacturing industry

Stage-wise green supply chain management and environmental performance: Impact of blockchain technology

In the era of globalisation, the use of technology and concerns for sustainability is eminent in the supply chain management practices. The current study focuses on sustainable and green supply practices in different stages of supply chain management and how they can be facilitated by blockchain technology (BT). The study has addressed the existing gaps in the area namely, the lack of research assessing stage-wise green supply chain for environmental performance focusing on BT. The current study aims to assess the impact of BT on different stages of the green supply chain and a firm's environmental performance. The study also focuses on analyzing the impact of green supply chain stages on environmental performance. The study uses PLS-based structural equation modelling approach to investigate the hypothesised relationships between BT adoption and stage-wise green supply chain practices. The data was collected from individuals from medium-sized enterprises from the manufacturing industry in India. The findings reveal a positive association between blockchain adoption and green supply chain management practices leading to enhancement in environmental performance. Furthermore, the study indicates a positive relationship between blockchain integration and different stages of the green supply chain, underscoring its multi-faceted impact on environmental performance. The findings imply that the BT adoption can facilitate the realization of sustainable supply chain practices and performance improvement.

Examining the impact of Industry 4.0 technologies on industrial performance of manufacturing organisations in India: an empirical study

ABSTRACT Industry 4.0 (I 4.0) technologies can significantly enhance the competitiveness, agility, and sustainability of the Indian manufacturing industry in the global market landscape. However, a lack of awareness about the potential benefits of I 4.0 inhibits its adoption within the sector. This lack of understanding, coupled with the complexities and implementation challenges associated with these technologies, disguises the relationship between benefits and adoption. This study aims to investigate the relationship between the adoption of I 4.0 technologies and the benefits expected from these technologies. A survey of 174 manufacturing organisations operating in India is conducted. The results of the survey suggest that the adoption of I 4.0 technologies has a positive relationship with operational performance benefits. The secondary benefits such as product flexibility, work-life balance and sustainability could only be considered after achieving operational performance. This paper contributes to the growing body of literature on the impact of I 4.0 on the manufacturing industry in India. Further it provides a base for future research on real benefits of I 4.0 technologies for manufacturing organisations from emerging economies.

An assessment framework to evaluate the critical success factors to Quality 4.0 transition in developing countries: a case experience of sustainable performance of Indian manufacturers

PurposeThe research aims to develop an assessment framework that evaluates critical success factors (CSFs) for the Quality 4.0 (Q 4.0) transition among Indian firms.Design/methodology/approachThe authors use the fuzzy-Delphi method to validate the results of a systematic literature review (SLR) that explores critical aspects. Further, the fuzzy decision-making trial and laboratory (DEMATEL) method determines the cause-and-effect link. The findings indicate that developing a Q 4.0 framework is essential for the long-term success of manufacturing companies. Utilizing the power of digital technology, data analytics and automation, manufacturing companies can benefit from the Q 4.0 framework. Product quality, operational effectiveness and overall business performance may all be enhanced by implementing the Q 4.0 transition framework.FindingsThe study highlights significant awareness of Q 4.0 in the Indian manufacturing sector that is acquired through various means such as training, experience, learning and research. However, most manufacturing industries in India still follow older quality paradigms. On the other hand, Indian manufacturing industries seem well-equipped to adopt Q 4.0, given practitioners' firm grasp of its concepts and anticipated benefits, including improved customer satisfaction, product refinement, continuous process enhancement, waste reduction and informed decision-making. Adoption hurdles involve challenges including reliable electricity access, high-speed Internet, infrastructure, a skilled workforce and financial support. The study also introduces a transition framework facilitating the shift from conventional methods to Q 4.0, aligned with the principles of the Fourth Industrial Revolution (IR).Research limitations/implicationsThis research exclusively examines the manufacturing sector, neglecting other fields such as medical, service, mining and construction. Additionally, there needs to be more emphasis on the Q 4.0 implementation frameworks within the scope of the study.Originality/valueThis may be the inaugural framework for transitioning to Q 4.0 in India's manufacturing sectors and, conceivably, other developing nations.

WITHDRAWN: Sustainable circular supplier selection for textile manufacturing industries in India: An integrated WINGS-MABAC approach

The significant quantity of waste produced by the textile industry has recently sparked an increase in the adoption of Circular Economy (CE). To aim towards CE, companies should focus on selecting suppliers who share certain key characteristics, such as being compliant with the CE standards, recycling used resources to reduce waste, minimal use of water & energy. Till date, very few studies have managed to cover the in-depth analysis of suppliers on the basis of circularity and sustainability aspects. The criteria addressed in this study have been identified through thorough literature review and discussions with the experts. This paper addresses this problem with the aid of multi-criteria decision-making (MCDM) framework for sustainable circular supplier selection (SCSS) in the Indian textile industry. This study applies Weighted Influence Non-linear Gauge System (WINGS) - Multi-Attributive Border Approximation Area Comparison (MABAC) approach to estimate the importance of different criteria to select the best performing supplier of recycled cotton yarn for an Indian textile industry. WINGS is used to analyse the different criteria for evaluating suppliers in textile industry, while MABAC is used to select the most suitable sustainable circular supplier. Our results suggest that sustainable circular suppliers should be evaluated mainly on the basis of factors like whether or not the supplier is willing to collaborate, robustness, green certifications and the recycling capability of the suppliers. The proposed approach and decision-making model can help the managers of the textile industry to choose more sustainable suppliers, respond to fast fashion and maintain the competitive standard in the market. An illustrative application of the proposed framework is undertaken in an Indian textile micro, small and medium enterprise (MSME).

Investments in Innovations and Market Structure: A Semi-parametric Approach

The economic literature suggests that there is an inverted-U type of relationship between innovation and product market competition. Existing empirical studies assume a quadratic functional form while estimating the relationship between the two variables. Using data on the Indian manufacturing industry, this article contributes by using a semi-parametric approach to test the ‘Inverted-U’ hypothesis without assuming a priori functional form. The estimation results suggest that the functional form of the relationship is contingent upon the choice of product market competition indicator in the model. When product market competition is defined as overall price competition, the empirical evidence confirms the inverted-U hypothesis. This implies that both escape competition and the Schumpeterian effect are observed as price competition increases. However, when product market competition is defined as domestic competition, only the escape competition effect is observed. JEL Codes: L10, L60, O30, O33, F10