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This research analyses the linkages between green manufacturing (GM) and manufacturing performance (MP) dimensions comprising sustainable performance (SuP) (economic [EcP], social [SP] and environmental [ENP]) and operational performance (OP) with supply chain alertness (SCAL) and supply chain preparedness (SCP) as mediators.

This deductive-quantitative approach embraces the explanatory design. It analyses 285 datasets gathered from structured questionnaires via structural equation modelling.

The study found that GM, SCAL and SCP significantly improve manufacturing firms' operational and sustainable performance. Also, SCP and SCAL partially mediate the GM-MP correlations among manufacturing firms in Ghana, a developing economy.

The paper is limited to the quantitative methodologies given its relevance in examining causal relationships among constructs. Also, it was conducted within the scope of manufacturing firms in developing economies, specifically Ghana. Despite the limitations, the study's outcomes imply that manufacturing firms can perform well in sustainable and operational aspects if they prioritise green manufacturing practices, supply chain preparedness and alertness.

This research offers new insights into the significant contributions of adopting the GM practice to MP (SuP and OP). Also, it advocates for more investments into GM, SCAL and SCP to ensure sustainability in today's highly disruptive manufacturing environment, leading to superior manufacturing performance. The study provides relevant directions for policymakers, industry players and supply chain practitioners in adopting GM throughout their production processes to attain manufacturing performance targets.

By advocating for sustainable manufacturing practices like green, the study contributes to a cleaner environment, resource conservation, and ultimately, a more sustainable future. The shift towards eco-friendly production methods can influence public attitudes towards manufacturing and promote environmentally conscious practices.

The study's originality lies in examining the mediation roles of SCAL and SCP on the GM-MP nexus of manufacturing industries in a developing economy, where environmental sustainability and disruptions along supply chains are becoming major concerns.

This study examines the impact of profitability, firm size and leverage on corporate tax avoidance in Bangladesh, an emerging South Asian economy.

A balanced panel data of 62 firms from Dhaka and Chittagong stock exchanges in Bangladesh from 2009 to 2020 were used to run the regression. This study employed the fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) to examine the hypotheses.

The findings show that large firms positively impact corporate tax avoidance. Similarly, profitability and leverage are positively associated with tax avoidance, and the results are significant. Furthermore, the study conducts robustness tests that confirm the findings.

The use of cash effective tax rate (ETR) to investigate firms’ tax avoidance practices poses some limitations, and the results should be interpreted cautiously.

The current study may help policymakers better enhance tax collection from business firms. The findings could serve as a valuable input for effectively monitoring tax collection from large profit-earning firms.

To the authors' best knowledge, this is the first historical attempt in Bangladesh to use panel data to examine the relationship between the firm’s level characteristics and corporate tax avoidance. Panel data often provides greater flexibility with large data, simplifying calculation and statistical analysis.

The current study investigates the impact of directors' attributes on the extent of compliance with International Financial Reporting Standards (IFRS) fair value disclosure requirements. The attributes investigated include directors' human capital (accounting qualification) and social capital (political association), directors' share ownership and the power distance between the chief executive officer (CEO) and the rest of the board members.

The study uses disclosure analysis to measure the extent of compliance with the fair value disclosure requirements of IFRS. Ordinary least squares (OLS) regression is used to test the relationship between the disclosure score and directors' attributes. Data were collected from the annual reports and websites of the sample companies.

Contrary to conventional belief, this study's findings suggest that directors' social capital and the power distance between the CEO and the rest of the board act as more powerful factors than directors' human capital in explaining corporate mandatory disclosure. Specifically, the results indicate that powerful actors form a dominant coalition and co-opt influential constituents from the institutional domain to neutralize the effect of legal coercion and the accounting expertise of board members and Big Four audit firms on the extent of compliance with institutional (fair value) rules.

This study utilizes Oliver's (1991) framework of strategic response to institutional processes in the Bangladeshi context. Although the study provides new insights into corporate disclosure practices, findings are not generalizable due to different institutional settings in different countries. Therefore, future studies could replicate the approach in different institutional settings.

The findings of this study will be of interest to the International Accounting Standards Board (IASB) as it focuses on a developing country that has adopted IFRS 13 and other fair value-related standards relatively recently.

The disclosure analysis contained in this study represents the first comprehensive analysis of the extent of compliance with the fair value disclosure requirements of IFRS. Furthermore, this study considers the impact of directors' social capital and finds that it is a more powerful determinant of the extent of compliance with IFRS as compared to human capital.

This study aims to investigate the factors influencing Indian banks’ choice of green loan disclosure practices. The study analyzes the effect of financial and governance variables to understand the sustainable reporting (through green lending) behavior of Indian banks.

The data on green loan disclosure has been hand-collected from the annual reports using a content analysis approach. Using the data of 26 banks for 12 years (2012–2023), the study uses the panel regression method to control for cross-sectional heterogeneity and generalized methods of the moment to address potential endogeneity issues.

The empirical results depict that larger banks with sufficient risk capital and a strong corporate governance framework demonstrate greater disclosure of green loans. However, growth opportunities and higher market value impedes the reporting of green lending.

The findings of the study will enhance the extant literature on sustainability disclosure by integrating the financial sector companies in the context of an emerging economy. However, future research may include nonbanking finance companies as well.

Banks use societal deposits to invest in productive avenues, and therefore, it is paramount to understand their social and environmental consciousness while evaluating a financing proposal. This research provides a thorough understanding of the sustainable reporting of banks through the lens of green lending.

This research provides unique evidence on the bank-specific determinants of green loan disclosure in an emerging economy context as against the extant literature which primarily focused on sustainable reporting of nonfinancial companies.

India liberalized its economy in 1991, which resulted in intense global competition, quality-conscious and demanding customers. Additionally, significant technological advancements lead to enhancements in products and processes. These forced Indian organizations to adopt innovative business strategies in the past 30 years. Meanwhile, the Lean Six Sigma methodology has significantly grown with vast applicability during the past 30 years. Thus, the purpose of this study is to develop the learning on Lean Six Sigma methodology in the Indian context through investigation of literature.

A three-stage systematic literature review approach was adopted to investigate the literature during the present study. In total, 187 articles published in 62 journals/conference proceedings from 2005 to 2022 (18 years) were shortlisted. The first part of the article summarizes the significant milestones towards the quality journey in the Indian context, along with the evolution of the Lean Six Sigma methodology. The second part examines the shortlisted papers on Lean Six Sigma frameworks, their applicability in industrial sectors, performance metrics, outcomes realized, publication trends, authorship patterns and leading researchers from the Indian perspective.

Lean Six Sigma has emerged as a highly acclaimed and structured business improvement strategy worldwide. The Indian economy has seen remarkable growth in the past decade and is one of the fastest-growing economies in the 21st century. Lean Six Sigma implementation in India has significantly increased from 2014 onward. The study revealed that researchers have proposed several different frameworks for Lean Six Sigma implementation, the majority of which are conceptual. Furthermore, the balanced applicability of Lean Six Sigma in manufacturing and service sectors was observed with the highest implementation in the health-care sector. Additionally, the widely adopted tools, techniques along with performance metrics exploring case studies were reported along with a summary of eminent and leading researchers in the Indian context.

This study is confined to reviewed papers as per the research criteria with a significant focus on the Indian context and might have missed some papers due to the adopted papers selection strategy.

The present study is one of the initial attempts to investigate the literature published on Lean Six Sigma in the Indian context, including perspective on the Indian quality movement. Therefore, the present study will provide an understanding of Lean Six Sigma methodology in the Indian context to graduating students in engineering and management and entry-level executives. The analysis and findings on Lean Six Sigma frameworks, research approach, publications details, etc., will be helpful to potential research scholars and academia. Additionally, analysis of case studies on Lean Six Sigma implementation by Indian industries will assist the managers and professionals in decision making.

The purpose of this study is to provide a review of the existing research landscape on work-life balance and women’s career motivation. It examines the relationship between work-life balance and career motivation in the context of Indian women. Specifically, it explores how the work-life balance of women influences the motivational aspects of their careers.

The research uses a systematic literature review to identify and analyze relevant literature on work-life balance and women’s career motivation among Indian women from the Scopus database.

The study uncovers critical insights into the connection between work-life balance and women’s career decisions. It gives insight on how work-life balance significantly impacts women’s career choices. The SLR reveals a notable and consistent upward trend in the domains of work-life balance and career motivation among women.

The findings of this study can inform organizations in tailoring policies that foster women’s career growth while simultaneously supporting a healthy work-life balance. In addition, the research can empower women to make informed decisions about their careers and personal lives. Ultimately, it contributes to creating a more inclusive and gender-equitable work environment, promoting both women’s career aspirations and their overall well-being.

This research stands out in its examination of the relationship between work-life balance and women’s career motivation, particularly in the unique context of Indian women. While previous studies have explored these topics individually, this research bridges the gap by investigating their interplay. Moreover, the application of a systematic literature review approach to these variables in the context of Indian women represents a novel contribution.

The primary objective of this paper is to determine the factors that affect the entrepreneurship propensity of students undergoing compulsory entrepreneurship education courses at various universities.

A research instrument was developed and implemented on a sample of 380 students who were offered compulsory entrepreneurship education courses at six major universities in the Jammu and Kashmir region of India. The study employed multiple cross-sectional designs with a simple random sampling technique to gather data. The collected data was subjected to descriptive statistics and structural equation modeling using SMART-PLS (Version 4).

The findings reveal that conceptualization, opportunity identification and implementation are the three antecedents of entrepreneurship propensity. The results indicate that the conceptualization factor is one of the most important predictors of entrepreneurship propensity, followed by opportunity identification, whereas implementation through education has the weakest influence on students' entrepreneurship propensity.

This research provides important insights to universities for designing and developing entrepreneurship courses that can foster the start-up culture. The results will be helpful for policymakers to devise various programs to boost entrepreneurship.

The study integrated the theories of planned behavior and human capital to evaluate the effectiveness of entrepreneurship courses at the university level. The three factors, namely, conceptual factors, actualization factors and implementation factors of entrepreneurship propensity are under-researched.

To augment sales revenue, B2B digital start-ups aim to create and sustain commercial relationships with industry incumbents. However, since these incumbents have traditionally struggled with implementing disruptive digital artifacts, most studies have almost exclusively concentrated on their challenges, leaving the digital start-ups' side underexplored. Therefore, this study seeks to understand how digital start-ups navigate digital implementation (DI) hardships to ultimately achieve digital entrepreneurship success.

An abductive explanatory multi-case study of four industries that pose a variety of implementation challenges for B2B digital start-ups (agriculture, insurance, real estate and construction, and healthcare) was conducted using data collected from 40 interviews with Israeli experts and relevant digital data observations.

This study articulates two main observations. (1) Throughout their journeys, digital start-ups have utilized newly created and/or refined dynamic capabilities (DC) to successfully implement their digital artifacts. Simultaneously, successful DI has enabled digital start-ups to create new DC or sustain and evolve current DC. (2) We provide empirical evidence outlining how digital start-ups using continuous learning have combined causation and effectuation logic throughout their DI journeys.

This study answers a call to explore more explicit digital-related drivers (i.e. DI) for digital entrepreneurship success by studying a highly-ranked country on the Global Entrepreneurship Index (GEI) to achieve this. Moreover, it illustrates how digital start-ups evolve throughout their commercial relationships with industry incumbents, thereby enabling an effective approach for successful DI. Such an approach can be considered very valuable for both practitioners and policymakers. Consequently, it advances digital entrepreneurship as an independent research topic.

This study aims to address the critical challenge of implementing lean manufacturing (LM) in emerging economies, where sustainability complexities on the production floor hinder production efficiency and the transition towards a circular economy (CE). Addressing a gap in existing research, the paper introduces a path analysis model to systematically identify, prioritize and overcome LM implementation barriers, aiming to enhance performance through strategic removal.

The authors used a mixed-method approach, combining empirical survey data with literature reviews to pinpoint key LM barriers. Using the grey-based Decision-Making Trial and Evaluation Laboratory (DEMATEL) along with the Network Knowledge (NK) method, they mapped causal relationships and barrier intensities. This formed the basis for developing a path simulation algorithm, integrating heuristic considerations for practical decision-making.

This analysis reveals that the primary barriers to LM adoption is the negative perception and inadequate understanding of lean tools and CE principles. The study provides a strategic framework for managers, offering new insights into barrier prioritization and overcoming strategies to facilitate successful LM adoption.

This research provides a strategic pathway for overcoming LM implementation barriers, empowering managers in emerging economies to enhance sustainability and competitive advantage through LM and CE integration. It emphasizes the significance of structured barrier management in the manufacturing sector.

This research pioneers a systematic exploration of LM implementation barriers in the CE context, making a significant contribution to the literature. It identifies, evaluates barriers and proposes a practical model for overcoming them, enriching sustainable manufacturing practices in emerging markets.