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Working capital efficiency (WCE) is crucial for the sustainability of both large and small firms. This study aims to use the sample of micro, small and medium-sized enterprises (MSMEs) in India and tries to understand the critical determinants of WCE.

Using a fixed effect panel data model on a sample of 578 MSMEs (59 micro, 226 medium and 296 small firms), this study explores the relationship between the predictors of WCE. Additionally, the study adopted two metrics for measuring WCE among each type of firm (micro, small and medium).

Several firm-specific variables, including leverage (lever), firm age (AGE), firm size (Fsiz), profitability (Prof), extended payment terms (EPT), human capital (HCap), asset turnover ratio (ATR), reverse factoring (RF) and firm growth (FG), have a significant effect on working capital management efficiency (WCE). In contrast, tangibility (Tangib) and salary expenses (Sal) had an insignificant effect on working capital management efficiency.

The study is based on secondary data. Future studies may incorporate some primary data, which will facilitate qualitative analysis.

The studies explore the relationship between WCE and expenses in HCap, EPT, RF and Sal as the predictors for WCE, which was not studied earlier in MSMEs scenario, especially in case of developing nation.

This study aims to present an innovative predictive methodology that transitions from traditional efficiency assessment techniques to a forward-looking strategy for evaluating working capital management(WCM) and its determinants by integrating data envelopment analysis (DEA) with artificial neural networks (ANN).

A slack-based measure (SBM) within DEA was used to evaluate the WCME of 1,388 firms in the Indian manufacturing sector across nine industries over the period from April 2009 to March 2024. Subsequently, a fixed-effects model was used to determine the relationships between selected determinants and WCME. Moreover, the multi-layer perceptron method was applied to calculate the artificial neural network (ANN). Finally, sensitivity analysis was conducted to determine the relative significance of key predictors on WCME.

Manufacturing firms consistently operate at around 50% WCME throughout the study period. Furthermore, among the selected variables, ability to create internal resources, leverage, growth, total fixed assets and productivity are relatively significant vital predictors influencing WCME.

The integration of SBM-DEA and ANN represents the primary contribution of this research, introducing a novel approach to efficiency assessment. Unlike traditional models, the SBM-DEA model offers unit invariance and monotonicity for slacks, allowing it to handle zero and negative data, which overcomes the limitations of previous DEA models. This innovation leads to more accurate efficiency scores, enabling robust analysis. Furthermore, applying neural networks provides predictive insights by identifying critical predictors for WCME, equipping firms to address WCM challenges proactively.

To examine the impact of experience in terms of time period on TQM's effectiveness in improving performance of Indian manufacturing companies. To establish the impact of TPM support on TQM's effectiveness.

This is an empirical research with testing of hypotheses using t tests. The data are collected with the help of a questionnaire on six performance parameters, which are measured on a five‐point scale. The study considers three time periods (phases) of implementation and two improvement strategies, i.e. TQM alone and TQM supported by TPM (combined strategy), for the purpose of analysis. The analysis is based on valid responses from 111 manufacturing companies.

The performance improvements contributed by TQM in the transition phase have been marginal due to initial investments and efforts required as well as to country‐specific factors. The effectiveness of TQM in the stability and maturity phases is established in an Indian context. The synergetic effect of TPM support on TQM's performance is also established in an Indian context.

The paper establishes the long‐term effects of TQM on companies' performance in an Indian context. It also highlights various country‐specific factors, which led to marginal improvement during the transition phase. The paper also establishes that TQM with TPM support can be an effective strategy to improve competitiveness of Indian manufacturing companies.

This paper studies the two important factors which influence TQM's effectiveness. Although the study has been carried out in an Indian context, it is equally significant in a global scenario. This paper addresses a pertinent issue of simultaneous implementation of TQM and TPM, which is commonly found in industry but not adequately researched.

To study the strategic implications of TQM and TPM in an Indian manufacturing set‐up and to detail literature reviews to highlight gap areas. To examine the relationship between factors influencing the implementation of TQM and TPM and business performance for the following three approaches in an Indian context: TQM alone; TPM alone; both TQM and TPM together. This is done to extract significant factors for the above three approaches.

Empirical survey‐based research on a sample size of 108 manufacturing companies. Uses bivariate correlation and multiple regression analysis techniques to extract significant factors using SPSS.

The research identifies two sets of factors which are critical for the effectiveness of TQM and TPM: universally significant factors for all the three approaches like leadership, process management and strategic planning; and approach‐specific factors like equipment management and focus on customer satisfaction. The study also highlights the complexities involved in implementing TQM and TPM together.

The emphasis on extracted factors will help companies in realizing greater benefits through TQM and TPM. This study is equally important in a global context also, as companies across the globe are striving to achieve synergy of TQM and TPM.

The preparedness/status of Indian manufacturing industry for TQM and TPM implementation, as India is becoming a major sourcing base for the world and there is a paucity of such studies. The study of TQM and TPM in all the three modes simultaneously has not been investigated in the context of developing countries. Such studies are equally important in a global context.

Acceptance of remanufactured products by the consumers is highly essential for the success of closed loop supply chain and for achieving the goal of circular economy. However, the literature shows that consumers are reluctant to purchase remanufactured products. Therefore, the study of attitude and purchase intention (PI) of the consumers toward remanufactured products becomes inevitable for popularizing these products. The paper aims to discuss this issue.

This research proposes a conceptual model to examine the critical factors influencing the PI of Indian consumers toward remanufactured products. Further, this model is empirically tested, using structural equation modeling technique, based on the data obtained from 1,534 respondents.

The findings of this research suggest that PI of consumers is influenced by attitude, personal benefits, remanufactured product knowledge, risk perception, subjective norm and market strategy. However, perceived behavior control and green awareness have a non-significant impact on the PI of Indian consumers.

The proposed conceptual model is tested only against the data received from the students of Indian universities who possess electronic gadgets.

The circular economy can be realized through remanufacturing if the attitude of consumers is shaped positively toward remanufactured products through the dissemination of comprehensive product information.

This research is the first attempt to assess the PI of Indian consumers by developing and testing the conceptual model. Further, this research provides guidelines to remanufacturing firms for attracting the consumers toward the purchase of remanufactured products.

As the COVID-19 epidemic ravages the world in the fourth industrial revolution era, the manufacturing sector faces its worst situation in a century. Lean philosophy, renowned as a “warrior philosophy,” can be an able rescuer to these industries. This study aims to identify the hurdles to lean strategy implementation and conduct an analysis to provide cognizance to policymakers, practitioners and decision-makers.

This study aims to identify the obstacles that obstruct lean implementation into seven primary barriers/components, with the fuzzy DEMATEL approach being used to evaluate the critical factors as well as the cause and effect factors among them. Expert opinions are sought to obtain the relevant data for evaluation purposes.

The results reveal that a firm should focus on firm cultural conflict scenario, resources–responses incapability, improve on suppliers’ attitude and execute a proper planning and logistics equation to alleviate the hindrances of implementing lean. As these causal factors influence the effect factors, namely, top management vision, management–employee relationship and human resource building, focusing on them automatically improves the effect factors; thus, the surge to overcome resistance to lean implementation is alleviated.

This research aids in identifying and analyzing lean implementation issues in the manufacturing and industrial sectors. The observations, results and insights drawn can act as a guiding force to rupture the resistance envelope covering the domain of lean implementation and possibly reinstating industries to survive and excel in the business post-COVID era.

This research introduces barriers to lean implementation in a unique way, as it articulates all sections of an industry and group the barriers based on the classification. It further prioritizes the barriers for their importance in the Indian industrial scenario. This would help the industry professionals and managers access the barriers and generate insight on how and where to start implementing lean.

In recent times, there has been a lot of research focused on performance measurement (PM) in project-based sectors. However, there are very few studies that were reported on the significance of PM in the construction sector. Keeping track of an organization in achieving organizations goals and objectives seems an important way. One of the major challenges faced by the industry is unavailable of an appropriate PM system for assessing organizational performance. Most of the PM approaches consider the traditional project triangle assessment of project success. Based on the limitations identified in existing PM models, the purpose of this paper is to develop a comprehensive PM model, i.e. Modified Project Quarter Back Rating (MPQR) applicable for construction projects.

A detailed list of performance areas as a method for PM is analyzed in the construction industry context. Also, industry-specific professionals conducted semi-structured interviews to assess whether these performance areas are sufficient to measure and understand the PM systems.

The research finding focuses on developing the MPQR model that considers both financial and non-financial areas for performance assessment to provide a holistic assessment of project performance.

MPQR model provides an opportunity to set the benchmark for overall performance for construction organizations.

The findings of the study are expected to provide guidelines to construction professionals for implementing the performance model that will improve performance in the construction industry.

In this chapter, I explore two media texts, Imtiaz Ali's Highway and Alankrita Shrivastava's Netflix original series Bombay Begums (2021). I contend that recent filmmakers have begun to arguably reframe the narratives of rape victim-survivors and disrupting the cultural of silence described above. They offer progressive and multi-faceted representations of these experiences, such that there is an opportunity for a dialogue within both private and public spheres. What I mean when I say that they are ‘progressive representations’ is that the rape victim-survivors are not merely reduced to helpless women in distress, nor painted as vengeful, aggressive characters. Instead, their characterisation shows that they have agency and autonomy, but at the same time struggle with the repercussions of speaking out against their perpetrators in a society that does not support them wholly.

Safety in construction projects is essential and requires more attention towards minimizing the accident rate. Problems concerning awareness of safety risks, procedures and practices still exist in the industry, which indicate a shortfall in diffusion of safety-related knowledge in construction industry. Also, there is dearth of studies on knowledge management strategies to prevent reoccurrence of accidents and thereby improve safety culture in construction industry. This study attempts to unveil aspects of knowledge management that are ignored in considering safety culture and discern the differences in the perception of key stakeholders of construction industry. Therefore, the objective of this study is to identify and measure knowledge-based safety culture elements.

In this paper, the focus is on the application of a reliable, valid and sensitive knowledge-based safety culture assessment tool on key stakeholders operational in construction industry. Research method adopted is a questionnaire-based survey to seek responses from industry professionals. A total of 199 responses were obtained from 106 different companies operational in Indian construction industry. Statistical analyses including ranking analysis, t-test, correlation analysis, and ANOVA test are utilized for comparing and identifying the differences in view of stakeholder's perceptions concerning workplace safety.

This study helps to identify and rank critical knowledge-based safety culture elements from the perspective of key stakeholders of construction industry. This contributes in identifying the most critical and neglected variables among the key stakeholders regarding aspects of safety culture. Also, the study shows the importance of knowledge dimension in developing overall safety culture in construction industry.

Results of this study offer valuable insight in enabling key stakeholders of construction industry to examine and enhance their safety performance. The implications of this study contribute new knowledge in assessing conditions that will improve worker safety in the construction industry. The paper should be of interest to researchers and practitioners in the area of occupational health and safety management.

The purpose of this study is to gain insight into how citations are distributed and concentrated in the introduction, methods, discussion, results and other sections of journal articles to determine which section has received the most citations and whether the citation concentration score affects how articles rank.

The present study uses scite.ai and the Dimensions database to emphasize the significance of including multiple in-text citations in evaluating the impact and quality of journal publications. The study has two approaches: paper-based and author-based.

The study provides empirical insights into how variations in ranking are observed when citation concentration is considered in the evaluation process. It also suggests that in-text citations be used as an evaluation criterion or aspect for assessing the impact and quality of journals, publications and authors.

This study underscores the importance of considering citation concentration when evaluating journal articles. To assess highly cited articles, it suggests using the CC-index method, which is based on scite.ai.