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While firms in developing countries are increasingly adopting lean practices of inventory management, there is limited evidence showing the impact of lean practices on firm performance in countries such as India. Lean practices improve the financial performance of the firms through superior cost-reduction measures and operational efficiencies. This paper examines the impact of inventory leanness in Indian manufacturing firms on their financial performance.

The authors measure inventory leanness based on stochastic frontier analysis (SLA), apart from using conventional measures available in the literature. The authors analyze the impact of inventory leanness on the financial performance of firms by examining data for 12,334 unique Indian manufacturing firms for the period 2009–2018. The authors present a comparative analysis using different methods of inventory leanness and study the effects on firm performance.

First, the authors find that only 68 industries out of 411 industries follow lean practices, i.e. most industries do not follow lean practices. Second, the estimation results show that there exists a positive relationship between inventory leanness and firm performance. The results suggest that an inverted U-shaped relationship exists between inventory leanness and firm performance for the entire sample. In particular, 17% of the industries in the sample exhibit such a relationship, and it is sufficiently strong to show up in the average regression results for the entire sample.

The authors introduce a novel measure of inventory leanness named stochastic frontier leanness based on the SFA method used in production economics. It measures leanness by benchmarking the inventory levels against the industry “frontier”. Furthermore, the authors conduct an empirical study of the lean-financial performance relationship with a large panel dataset of Indian firms instead of the survey-based methods that were previously used in the literature.

The paper explores the managerial perceptions in Indian apparel manufacturing firms related to production performance, challenges faced, causes of low efficiency and the government support needed.

A structured survey of Indian apparel manufacturing firms was undertaken in person and through the online mode; the questionnaire was designed to collect data on demographic profile of a firm using categorical questions and perceptions of its top managers using a five-point Likert scale.

The survey findings reveal that most apparel manufacturing firms believe that exporting promotes efficiency and adopt output orientation to production, which may not be suitable in a competitive and uncertain environment. Machines are not used much for value-addition and labour related issues are most pressing challenges. Government support is expected for several aspects such as power supply and skill development.

The paper is limited by the nature of the sampling method and sample size; perceptions should be explored without bias and with good judgement.

The survey findings suggest that government policy should have a firm-specific approach to support improved production performance along with generic policies to build infrastructure and logistical facilities.

To the best of authors’ knowledge, there has been no such exercise to study managerial perceptions related to production performance in Indian apparel manufacturing in the past decade.

Sustainability performances (SPs) are the most crucial performances for an organisation in today's world, and they can be measured by economic, social, and environmental metrics. Previous research has not been clear on the role of total productive maintenance (TPM) in the context of sustainability, which motivates the authors to investigate the relationship between TPM and various SPs of the manufacturing firm. Therefore, current research investigates the relationship between TPM and the overall sustainability of the manufacturing firm from the perspective of resource-based view (RBV) theory.

The current study proposed, tested and validated a conceptual framework using partial least squares structural equation modelling (PLS-SEM). A total of 326 responses were received to validate the conceptual framework in smartsPLS 3.0 software.

The research outcomes indicate that TPM considerably impacts a manufacturing firm's economic, environmental and social performance.

This research demonstrates that outstanding shop floor behaviour, such as TPM, can become an important asset to offer competitive advantages in a manufacturing firm. Similarly, TPM might serve as a roadmap for leveraging overall sustainability for manufacturing companies. The study indicates the establishment of a sustainability-oriented training protocol while practising TPM.

No past investigation indicates that a shop floor activity like TPM could be used as an input to offer sustainability in a single index for a manufacturing firm from the perception of RBV theory.

This study investigates the relationship between working capital investment (WCI) and firm value for Indian manufacturing firms using excess net working capital (NWC) and Tobin's Q as a measure of WCI and firm value, respectively. The study also examines whether firms use the cash released from excess investment in working capital to make long-term investments.

The sample comprises 834 Bombay Stock Exchange (BSE) listed Indian manufacturing firms whose data from April 2010 to March 2020 are analyzed using a fixed-effect panel regression analysis approach.

The empirical results show that excess NWC influences firm value negatively and significantly. However, the nature of the relationship becomes nonlinear upon dividing the sample into positive excess NWC and negative excess NWC. The findings from the study also reveal that firms redistribute cash freed from positive excess NWC for long-term investments to improve their value without impacting the corresponding risk.

Overall, the results suggest that firms with positive excess NWC can enhance their valuations by building adequate long-term investments from surplus WCI funds.

To the authors’ best knowledge, studies on this issue have primarily focused on developed economies. No study seems to have been done on this subject in the emerging South Asian economies. The present study is the first to bridge the research gap by investigating the relationship between excess WCI and firm value for manufacturing firms in India. Moreover, it examines whether a positive excess NWC reduction translates into corporate investments (CI).

This paper analyses the effect of circular economy practices on sustainable supply chain performance. The study explores the impact of mediating variables such as supply chain flexibility and capabilities and the moderating role of supply chain integration in the relationship between circular economy practices and sustainable supply chain performance in Indian manufacturing firms. The study builds on the stimulus-organism-response (S-O-R) model to conceptualise circular economy practices that influence supply chain capabilities, integration and flexibility, impacting sustainable supply chain performance.

This study adopted an online survey questionnaire distributed to managers of Indian manufacturing firms adopting circular economy practices. The data were analysed using SPSS Amos 25 and PROCESS macros.

The results suggest a positive impact of circular economy practices on sustainable supply chain performance in manufacturing firms. In addition, a supply chain manager's relationship with retailers is improved in the presence of supply chain capabilities and flexibility. Supply chain integration further strengthens this relationship as a moderating variable.

By examining the literature on circular economy practices and sustainable supply chain management, this study contributes to bridging the gap between supply chain capabilities, integration and flexibility using the S-O-R model. This study is possibly among the first to explore and provide empirical evidence on how circular economy practices in manufacturing firms can impact supply chain managers' experiences and thus help to improve environmental well-being. Both academics and business professionals might find these contributions interesting.

This study aims to assess the efficiency of managing working capital in 1,388 Indian manufacturing firms from 2008 to 2019 and investigate the effects of firm-specific and macro-level determinants on working capital management (WCM) efficiency.

The current study accommodates a slack-based measure (SBM) in data envelopment analysis (DEA) for computing WCM efficiency. Further, we implement a panel data fixed-effects model that controls for heterogeneity across firms in determining the relationships of selected variables with WCM efficiency.

The results highlight that manufacturing firms operate at around 50 percent efficiency, which is constant throughout the study period. Furthermore, among the selected variables, yield, earnings, age, size, ability to create internal resources, interest rate and gross domestic product (GDP) significantly affect WCM efficiency.

Instead of the traditional models used for assessing efficiency, the SBM-DEA model is unit-invariant and monotone for slacks, implying that it can handle zero and negative data, which overcomes the incapability of prior DEA models. Hence, this provides accurate efficiency scores for robust analysis. Additionally, this paper provides a holistic working capital model recognizing firm-specific and macro-level determinants for a more explicit estimation of the relationship between WCM efficiency and the selected determinants.

Given the lack of focus on a standardized measurement framework (e.g. benchmarking tool) to assess and quantify complexity within the supply chain, this study has developed a unified supply chain complexity (SCC) index and validated its utility by examining the relationship with firm performance. More importantly, it examines the role of firm owners' business knowledge, sales strategy and board management on the relationship between SCC and firm performance.

In this study, the unit of analysis is Indian manufacturing companies listed on the Bombay Stock Exchange (BSE). This research has merged panel data from two secondary data sources: Bloomberg and Prowess and empirically operationalized five key SCC drivers, namely, number of suppliers, the number of supplier countries, the number of products, the number of plants and the number of customers. The study employs panel data regression analyses to examine the proposed conceptual model and associated hypotheses. Moreover, the present study employs models that incorporate robust standard errors to account for heteroscedasticity.

The results show that complexity has a negative and significant effect on firm performance. Further, the study reveals that an owner's business knowledge and the firm's effective sales strategy and board management can significantly lessen the negative effect of SCC.

This study develops an SCC index and validates its utility. Also, it presents a novel idea to operationalize the measure for SCC characteristics using secondary databases like Prowess and Bloomberg.

The 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.

The 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.

The 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).

This 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.

This may be the inaugural framework for transitioning to Q 4.0 in India's manufacturing sectors and, conceivably, other developing nations.

The focus of this paper is to provide an assessment of the impact of imports from China on Indian manufacturing and capture the multifarious dimensions of India–China bilateral trade flows. By examining the comparative disadvantage imports (RCA<1), the paper critically examines their significance on India's industry output and performance and underlines factors beyond trade competitiveness.

For examining the impact of India's manufacturing imports from China on industry performance, four stages of analysis is adopted. First, the imports with RCA <1 have been identified. For these, BRCA was also computed. Second, trends in industry performance associated with high imports from China. Third, for estimating the impact of imports on industry output, augmented production function was specified and estimated with imports from China as a potential determinant. And fourth, comparison of industry performance between India and China.

The impact of imports from China on industry output is positive and significant. A 1% increase/decrease in the share of China in world imports will result in output increasing by 0.31%. The rise in imports from China seems to be on account of non-availability of necessary intermediate and capital goods domestically, thereby making these imports critical and complementary for production. This negates the threat perception of imports from China.

The paper recognizes the need for understanding the firm heterogeneity in import decisions and R&D intensity of imports. Across industries, the drivers for firms' decisions to import are “learning by importing’ and “self-selection” (Camino-Magro et al., 2020). Also, another important dimension at the firm-level analysis is the elasticity of substitution between foreign and domestic inputs. If the elasticity of substitution is low then high import barriers will lead to reduction of domestic output. These firm-level issues are important for effective policy interventions.

One, the inward looking focus of the industry which is exhibited in low export intensity will not provide the necessary impetus to propel the manufacturing sector to a higher technology frontier and translate the productivity gains to export competitiveness. Two, unless the domestic manufacturing is propelled from the current low/medium technology to high technology products, the current policy thrust on “self-reliance” cannot be realized.

Analysis is based on manufacturing imports with RCA<1 from China thereby underlining factors beyond trade competitiveness not covered by RCA methodology. Complementing the quantitative analysis with economic policy developments in China and India and contrasting the same has provided insights into the real factors determining India–China bilateral trade.

This study aims to add to the growing literature on the trade–finance nexus by exploring the interplay between a country's level of financial development, the external finance dependence of firms and their exporting decisions.

The study first develops a theoretical model to motivate the idea that a firm's liquidity (financial) position and its home country's level of financial development act as substitute factors in its export market entry decisions. It then empirically tests whether an improvement in a country's financial development level enhances the number of entrants in the foreign markets and boosts the exports of incumbent exporters using firm-level data of manufacturing firms in India for the period 1993–2020.

Empirical results suggest that a higher level of financial development helps increase the exporting probability of firms that rely more on external finance for their operations. Further, the study finds that the sunk costs-induced hysteresis effect plays a major role in firms' exporting decisions and financial factors don't play a significant role in the exporting activities of incumbent exporters.

The findings suggest that a well-developed financial market is necessary to help more and more firms initiate their foreign market operations. The results underscore that trade-liberalisation measures alone may not increase India's exports and the government must complement them with financial sector reforms.

Studies highlighting the role of financial sector development in helping financially-constrained Indian firms overcome the entry barriers associated with exporting are extremely limited. This study contributes to this nascent literature by conducting an empirical investigation on an extensive database of Indian manufacturing firms. Moreover, in contrast to the previous firm-level studies in this area, this empirical analysis uses the actual values of external finance raised by the firms as a critical factor in determining their extensive and intensive margin of exports instead of the usual balance sheet variables such as liquidity and leverage.