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This paper evaluates the working capital management (WCM) efficiency of the Indian manufacturing industries through data envelopment analysis (DEA) and empirically investigates the influence of several exogenous variables on the WCM efficiency.

WCM efficiency was calculated using BCC input-oriented DEA model. Further, the panel data fixed effect model was used on a sample of 1391 Indian manufacturing firms spread across nine industries, covering the period from 2008 to 2019.

Firstly, the WCM efficiency of Indian manufacturing industries has been stable over the analysis period. Secondly, the capacity to generate internal resources, size, age, productivity, gross domestic product and interest rate significantly influence WCM efficiency.

First, the selected study period has observed various economic uncertainties including demonetization and recession, so the scenario might differ in normal conditions or country-wise. Second, the findings might not be generalizable to the developed economies, since the current study sample belongs to a developing economy, which further provides scope for comparative study.

An efficient model for managing the working capital comprising most vital determinants could enhance the firms' valuation and goodwill. Also, this study would be helpful for financial executives, manufacturers, policymakers, investors, researchers and other stakeholders.

This study estimates the industry-wise WCM efficiency of the Indian manufacturing sector and suggests measures to the concerned parties on areas to focus on and provide evidence on the estimated relationships of firm-level and macroeconomic determinants with WCM efficiency.

The purpose of this paper is to examine the extent to which lean management practices are adopted by small- and medium-sized manufacturing organizations in India and their impact on firm’s operational performance (OP). Also, the paper makes an attempt to identify the barriers and challenges faced by Indian SMEs that are striving to succeed with improvement efforts based on lean manufacturing.

In this paper, acceptability and implementation of lean manufacturing in Indian Manufacturing SMEs were analyzed using three constructs, namely, process improvement (PI), flow management (FM) and waste minimization (WM). The responding firms were categorized into “lean-Beginners,” “In-transition lean” and “lean” group based on their phases of lean implementation. Using a survey questionnaire, data were collected from 121 manufacturing SMEs in India. Lean tools and barriers, identified from the literature review, were also included in the survey. The reliability and validity of the practice and performance measures were evaluated. Correlation analysis was employed to investigate the effects of three constructs on OP.

The results indicate that all the three lean constructs are significantly related to OP. In the context of Indian manufacturing SMEs, “PI” and “WM” practices have shown a higher level of significance on OP, compared to “FM” practices. “5S -workplace organization” was found to be the most practiced lean tool. “Attitude of workmen” was highlighted as the main obstacle in successfully implementing lean. The findings suggest overall positive effects as a result of applying lean tools and philosophy in Indian SMEs.

The research results may lack qualitative justification because of the chosen research approach. Therefore, the researchers are encouraged to explore the inter-relationship among various lean tools/practices and performance criteria by conducting a qualitative study in the form of a case study or action research.

This paper is a beneficial source of information that highlights the contribution of lean implementation in enhancing manufacturing productivity. The major tools and techniques used by Indian SMEs have been highlighted and discussed; it could be a genuine source of motivation to lean practitioner and entrepreneurs of SMEs to go in for lean implementation. The findings are also expected to benefit the lean practitioners and entrepreneurs of SMEs to focus on vital issues to facilitate successful lean implementation in an organization.

The paper demonstrates that practical implication of lean implementation can bring real breakthroughs in productivity to small- and medium-scale manufacturing firms.

This study examines the innovation-efficiency linkage for Indian and Chinese manufacturing and service firms.

We applied the stochastic production and cost frontier approach to determine the output and cost efficiency of the firms surveyed in World Bank enterprise surveys. We then used both unconditional and conditional propensity score matching (PSM) estimation techniques to examine the effects of innovation as well as R&D on output and cost efficiency of the firms surveyed.

The study results suggest that innovation-efficiency linkage varies between countries and sectors. Innovations significantly raise output and cost efficiency of Indian manufacturing firms, whereas innovations in Chinese manufacturing firms are cost-oriented and negatively affect output efficiency. For the service firms of both countries, innovations are significantly positively linked with output and cost efficiency. The study also suggests that R&D acts as a crucial moderator for innovation-efficiency linkage for Chinese manufacturing firms but not for Indian firms, and the interaction effects of innovations are not substantially higher in magnitude than their individual effects. Finally, conditional PSM results suggest knowledge spillover for effective innovations of Indian firms, whereas R&D is a must for substantial innovation-efficiency linkage in Chinese firms.

This study offers quite a few crucial policy decisions concerning the relationship between innovation and efficiency as well as the moderation effect of R&D on innovation-efficiency linkage. It concludes that the effects of innovation on firms' efficiency and the role of R&D as a moderator of the innovation-efficiency relationship differ between India and China across the manufacturing and service sectors.

The purpose of this study is to examine the impact of financial and technical education of chief executive officer (CEO) on investment–cash flow sensitivity (ICFS) of Indian manufacturing firms.

The study uses the dynamic panel data model and more specifically, the system-generalized method of moments (GMM) technique to investigate the effect of CEOs' education on ICFS of Indian manufacturing firms during the period 1998–1999 to 2016–2017.

The study shows that financial (technical) education of CEOs does (not) affect ICFS. The results explain that the role of the CEO's education in ICFS is highly significant during the crisis period. The robustness test depicts that the influence of financial education on ICFS is less (more) for group-affiliated and large-sized firms (stand-alone and small-sized firms). Further, the CEO's education is significantly associated with corporate investment decisions.

Due to the unavailability of the CEO's compensation data for the selected sample, future research could explore the impact of CEO's education with respect to CEO's compensation on ICFS.

First, the authors find that financially educated CEOs affect ICFS; therefore, firms should take care of CEO's education during recruitment of CEOs. Second, lending agencies should also consider the educational background of the CEO before approval of funding to make it safe. Third, investors should keep in mind the educational background of the CEO for the growth of their investment as it may be easier for financially educated CEOs to borrow from the market at the time of requirement.

This study contributes to the existing literature by providing empirical evidence through analyzing the impact of a CEO's education on ICFS in the context of India. This study is very unique in itself as it uses the sample of manufacturing sectors of India, which are growing very fast and attracting global investors to create a global hub of manufacturing in India. This study also considers different types of education such as financial and technical education of CEOs in the context of a developing economy like India. This study made its findings robust across company characteristics and periods based on the financial crisis.

The purpose of this paper is to empirically investigate the relationship between working capital management (WCM) efficiency and exogenous variables of the Indian manufacturing sector along with its sub-industries that are involved in export activities.

Panel regression (fixed effects) was used on a sample of 563 Indian manufacturing firms involved in export activities, covering a time period from 2008 to 2018.

Industry-wise results showed a significant relation of leverage, net fixed asset ratio, profitability, asset turnover ratio, total asset growth rate and productivity with cash conversion cycle (CCC).

Firstly, having taken a sample from a developing economy, the results of our study may be generalizable only among developing contexts. Secondly, the time period taken in this study (2008–2018) has witnessed several economic fluctuations such as recession and demonetization which might differ for the firms or countries in normal conditions.

An improved working capital model could advance the firms' performance by reducing the CCC of the firm, thereby creating efficiency in WCM. In addition, the results of this study could be helpful for many stakeholders such as working capital managers, debt holders, investors, financial consultants and others for monitoring the firms.

This study contributes to the existing literature in the relation between WCM efficiency and exogenous variables of the Indian manufacturing firms engaged in the export activities. Moreover, this study is one of the few research studies to investigate this relationship among Indian export firms in different industries, thus filling the gap in similar work done in other countries.

The purpose of this paper is to study the key determinants of capital structure for Indian manufacturing firms and which theory implications, i.e. trade off vs pecking order are more applicable in current Indian manufacturing sector scenario.

A sample size of 422 listed Indian manufacturing companies on Bombay Stock Exchange has been considered to do the empirical evaluation. A ten year period from 2003-2004 to 2012-2013 and annual financial standalone data have been considered for study. Ratio analysis and panel data approach have been applied to perform the empirical evaluation. Total debt to total capital and total debt to total assets are used as the proxy for firm financial leverage.

It was empirically found that size, age, asset tangibility, growth, profitability, non-debt tax shield, business risk, uniqueness and ownership structure are significantly correlated with the firm financial leverage or key determinants of capital structure in Indian manufacturing sector. Also, other variables like dividend payout, liquidity, interest coverage ratio, cash flow coverage ratio (CFCR), India inflation and GDP growth rate are empirically found to be insignificant to determine the capital structure of Indian manufacturing sector. There is no single theory implications, i.e. trade off vs pecking order which can explain the capital structure nature of Indian manufacturing sector and rather it is a mix of both the theories.

The findings of the study would enhance the literature on capital structure and is significant for the Indian manufacturing firm’s decisions as it includes the most recent data and covers the period of both pre- and post-recession of 2008-2009.

The purpose of this study is to examine the firms’ determinants of being acquired in Indian manufacturing sector. There is evidence of relationship between likelihood of being acquired and several firm specific characteristics such as age, size, research and development (R&D), advertising intensity, productivity, leverage, profitability, intangible assets and financial constraints. However, little is known about the association between these characteristics and likelihood of acquisition in Indian manufacturing sector.

The sample is a panel of 2,189 Indian manufacturing firms spanning almost 10 years (1998-2007). Random effects logistic (REL) regression model is adopted to control the firm specific unobserved heterogeneity in the sample. This is an essential requirement for providing accurate and effective determinants of being acquired.

Empirical results reveal that the determinants of being acquired in Indian manufacturing sector are age, size, R&D intensity, advertising intensity, productivity and leverage. The findings indicate that increase in firms’ age, size, R&D intensity and advertising intensity increases the likelihood of being acquired. However, increase in productivity and leverage decreases the likelihood of being acquired.

Findings of this study may be useful for potential targets to arrive at more thoughtful assessment of their attractiveness and, accordingly, promote their acquisition as a more efficient mode of exit.

The paper contributes some empirical evidence on the determinants of being acquired in Indian manufacturing sector by using panel data and REL regression model.

This article aims to explore synergies between Lean, Green and Six Sigma practices in order to propose an integrated LGSS framework for continuous and incremental improvement in the Indian manufacturing industries. The three-dimensional LGSS framework seeks to provide various combinations and support operational, financial, environmental and social needs.

In the research method, first, the current problems faced by Indian manufacturing industries are considered and proposition of a conceptual framework that qualitatively integrates synergistic aspects of Lean, Green and Six Sigma practices, and second, the framework is checked by a survey taken from 203 Indian firms by using SPSS-AMOS.

The hypothesized result suggests that the positive impact of integrated practices on firm performance in terms of operational, financial, social and environmental outcomes. It also provides a systemic and holistic approach to problem-solving through constant and incremental enhancement in the manufacturing sector.

In this research, only Indian manufacturing industries have been studied but can be extending into different geographical areas and sectors. Future research is also possible for different behavior and characteristics of companies that can lead to recommending strategies on how companies can improve performance. Most importantly, future research can try to understand which specific practice can contribute to competitive advantage and business success.

Manufacturing firms that want to improve environmental sustainability should implement integrated LGSS practices into their supply chain. The set of combined practices improves operational, social, economical and environmental benefits.

The research presents an integrated approach of LSS for the manufacturing industry which leads their business processes to achieve economic sustainability through continuous growth and improved operational efficiency. Manufacturing industries result in outcomes like reduced cost, lead time, improved quality, sustainable market position, profitability, customer satisfaction, etc.

This research is different from previous studies because it integrates Lean, Green and Six Sigma practices into a unique framework that fulfills a specific need of the Indian manufacturing sector that guides operational, social, environmental and financial issues in Indian industries.

In order to enhance the performance of R&D in manufacturing organizations, the R&D managers need to identify the internal as well as the external factors that affect the R&D performance of manufacturing organizations in India. They need to understand the inter‐dependencies of these factors. This paper seeks to identify the critical success factors for R&D in Indian manufacturing firms.

There may be a number of factors that are critical for achieving acceptable R&D performance and these factors have been identified by a number of instruments or means, such as questionnaire surveys, brainstorming, and consolidation by Principal Component Analysis (PCA). A total of 14 factors have been identified by using principal component analysis and finally we have developed a structure of interrelationship among the identified critical success factors using an interpretive structural model.

The results show that R&D vision and direction and R&D oriented culture are the most important critical success factors (CSFs) and they have a great influence on the other CSFs. Though R&D vision and direction and R&D oriented culture are the short‐term objectives, Indian manufacturing firms should be equipped with proper R&D management strategy to achieve the long‐term objectives, such as achievement of revenue and profitability within a quick time frame.

Although R&D managers of Indian manufacturing firms are aware of various critical success factors, a systematic approach is required for identifying them, and as these factors may have complex interrelations between them for analyzing R&D performance in a manufacturing firm, it is essential that such an approach is in place. The hierarchy based ISM further defines those factors which are really critical and need more focus on the root causes of the success. In addition to that, the proposed ISM model acts as a good guideline in order to improve the performance of the manufacturing R&D organizations in India.

The paper provides an interpretive structural model to develop a map of the complex relationships and magnitude among identified critical success factors.

The purpose of this paper is to investigate the complex interrelationships among the key constructs, supply chain orientation (SCO), supply chain integration (SCI) and supply chain performance (SCP) in Indian manufacturing industries. These relationships have been studied using the relational view (RV) and the knowledge-based view (KBV) theoretical perspectives.

The conceptual model was derived from the existing body of knowledge in the supply chain domain. The study is based on a sample size of 122 data collected via face-to-face meetings with the Indian manufacturers using well-established scales. The covariance-based structural equation modeling was used to test the proposed hypotheses.

In Indian manufacturing and supply chains, SCO has a positive relationship with SCI and SCP. Moreover, the direct impact of SCO on SCP diminishes when SCI is used as a mediating variable. This study also observes positive impact of: i) SCO on SCP, ii) SCI on SCP and iii) discovery of mediating role of SCI on SCP under the theoretical lenses of RV and KBV.

Cross-sectional survey of manufacturing firms of one country (using one response per firm) calls for validation covering other parts of the world and demands a longitudinal survey. This research will trigger more scholarly, practice and policy debate among researchers studying Indian and emerging economies context.

The notion of a holistic view of the SC with a focus on improving the customer value can enhance strategic partnerships among the SC partners (i.e. SCI) and overall SCP. Firms should make efforts to include SCI in SC designs to successfully transform SCO into SCP.

The originality of the research lies in studying the complex interrelationships among key concepts of SC in a unique Indian manufacturing context. The Indian supply chains operate in a set of unique characteristics, which have been detailed out in this paper. This paper not only establishes the mediating role of SCI for overall SCP in emerging economies but also enhances the scholarly knowledge in the SC domain. Most studies report SCO as a single-order construct, measured by scales comprising of only few items. The second-order SCO measures in this study bring credibility to the findings. Additionally, it contributes to both academicians and practitioners alike in the context of an integrated SC in emerging economies.