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The purpose of this research is to identify and study the contextual relationships of the significant lean enablers in the Indian coal mining industry using the application of interpretive structural modeling (ISM), matrice d' impacts croisés-multiplication appliquée á un classement (MICMAC) and structural equation modeling (SEM).

In this study, a conceptual model based on ISM was developed forming a hierarchy and contextual relationships of significant enablers for lean implementation in the Indian coal mining industry using a literature review and eliciting expert opinion, which is followed by MICMAC for grouping of enablers and questionnaire survey to validate the ISM based conceptual model using SEM.

The study modeled and analyzed ten significant enablers of lean implementation in the Indian coal mining industry. The findings suggest that the most important lean enablers in the Indian coal mining industry are employee empowerment, employee motivation and commitment, consistent financial performance measurement and management support.

Judgmental sampling was used for selecting the respondents for conducting the questionnaire survey in this research work as there are a few numbers of coal mines implementing lean principles in India. Although the study was not restricted to a particular part of India with the sample representing the heterogeneous population, the study represents more data from the coal mines in eastern India.

The model on lean enablers would help the researchers, decision-makers and practitioners to anticipate potential lean enablers in the Indian coal mines and rank the enablers for improved and efficient usage of the available resources creating value to customers with lean and to sustenance academic research on lean.

Studies on lean enablers in the mining sector are scarce in the literature, and this study is a novel contribution of exploring lean enablers in the Indian coal mining industry using an integrated approach of ISM–MICMAC and SEM.

The COVID-19 epidemic has brought attention to the variables that influence the mental health of health workers who are entrusted with nursing individuals. Despite the fact that many articles have examined the effects of social media usage on mental health, there is a lack of research synthesizing learning from this body of research. The purpose of this study is to use text mining and citation-based bibliometric analysis to conduct a detailed review of extant literature on health workers’ mental health and social networking habits.

This study conducts a full-text analysis of 36 articles selected on health workers' mental health and social media using text-mining techniques in R programming and a bibliometric citation analysis of 183 papers from the Scopus database in VOS viewer software. But the limitations of the methods used in this study are that the bibliometric analysis was limited to the Scopus database because the VOS viewer program did not support any other database and the text-mining approach caused the natural processing redundancy.

The bibliometric analysis reveals the thematic networks that exist in the literature of health workers’ mental health and social networking. The findings from text mining identified ten topic models, which helped to find the related papers classified in ten different groups and are provided alongside a summary of the published research and a list of the primary authors with posterior probability through Latent Dirichlet Allocation.

To the best of the authors’ knowledge, this is the first hybrid review, combining text mining and bibliometric review, on health workers’ mental health where social networking plays a moderating role. This paper critically provides an overview of the impact of social networking on health workers' mental health, presents the most important and frequent topics, introduces the scientific visualization of articles published in the Scopus database and suggests further research avenues. These findings are important for academics, health practitioners and medical specialists interested in learning how to better support the mental health of health workers using social media.

The banking sector in West Asia has always experienced positive growth except for Palestine. Apart from some negligible outlying outcomes in some countries that have faced political crises and war, most West Asian countries have gained bank profitability and efficiency. However, the stability in the banking sector has been rarely examined in the literature. Hence, this study sheds light on examining bank stability by considering 12 countries in West Asia.

A fixed effect panel data regression analysis is employed on strongly balanced panel data using data from 2004 to 2018.

Results reveal that the net interest margin has a positive relationship with bank stability. The bank’s stability rises as the net interest margin improves. Furthermore, the non-interest income reveals a positive significant impact on the stability of banks, depicting that the increase in non-interest income increases the stability of banks. Additionally, the non-interest expense also reveals positive significant results with the stability of banks. Nevertheless, leverage ratio and long-term debt portray a negative significant impact on banks’ stability. The finding reveals that higher long-term debt and leverage ratios may decrease the stability of the banks in West Asia.

Overall, the authors’ findings add to the literature on the stability of the banks by providing some new but significant information. Some of the recommendations may be beneficial to the long-term success of 12 Western Asian countries’ banks.

The study examines the stability of banks by incorporating both profitability and operating efficiency along with net-interest income, which extends to the current literature’s insight.

The study aims to explore the relationship between the dimensions of green intellectual capital (GIC) and employee green behavior (EGB).

A survey has been conducted among a random representative population of employees working for the energy-sector organizations in India to collect data for this study. Exploratory factor analysis (EFA) for GIC supports the inclusion of the new dimension in its construct. Confirmatory factor analysis (CFA) validates the measurement model. Hypothesized relationships have been examined by applying structural equation modeling using partial least squares method.

Results corroborate that all the four dimensions of GIC have varying degrees of significant positive impact on EGB. The study contributes to the existing literature by extending the understanding of the concept of GIC and its connection with EGB using natural-resource based theory and social cognitive theory (SCT).

The study has empirically examined the relationship between GIC and EGB in the context of a developing country like India. Moreover, unlike the existing literature that have classified GIC into green human capital (GHC), green structural capital (GSC) and green relational capital (GRC), the study identifies green spiritual capital (GSpC) as another important dimension of GIC which is an intangible asset and highly relevant in influencing altruistic activities like green behavior. The study presents significant implications for managers and policy-makers for ensuring EGB by investing in GIC resources.

The purpose of this paper is to analyze the bank efficiency in three developing countries, namely Angola, Brazil and Mozambique, aiming to infer differences given that they belong to the same cultural tradition. The underlying idea is to control for the cultural background, thus allowing the discussion on how different socio-economic and historical variables maybe impacting different levels of banking efficiency and returns to scale results within the ambit of these three countries.

Due to the presence of latent inefficiency, the authors have to modify the technique to accommodate simulation by importance sampling; therefore, in effect, the authors use a local maximum simulated likelihood approach.

The results reveal that Brazil has the highest level of output-oriented efficiency, followed by Angola and then Mozambique. The same ranking is observed in returns to scale, except that vis-à-vis technical change, Brazil and Angola rank first. Finally, inefficiency derived from technical change is highest in Mozambique, followed by Angola and then Brazil. Therefore, these results reveal that the countries with the highest degree of development are higher in efficiency.

Previous studies have identified factors such as legal tradition, accounting conventions, regulatory structures, property rights, culture and religion as possible explanations for cross-border variations in financial development and economic growth. This is the first time banking efficiency is assessed in light of a common cultural background by selecting a group of countries that share the same language and colonial past. Since results are controlled for the same background, it is possible to affirm that the findings are purely related to scale size and economic/political background issues of each country.

This study extends the current literature in the context of European countries by showing that women's participation on the board can enhance the financial performance of a company while moderated by many cultural factors.

This study examines 19 European countries throughout the period 2010–2020. The time-invariant or individual fixed-effect models are used.

The authors found that high power distance and masculinity undermine the impact of board gender diversity on firm performance. The gender-diverse board reports a statistically significant negative impact on return on asset (ROA) and return on equity (ROE) while moderated by the power distance index.

This research will be of significant value to the board directors, practitioners and the concerned authority who desire to polish up the firm performance of European countries that are governed by cultural norms.

This paper aims to examine literature on corporate governance from the gender perspective adopting the two novel approaches: bibliometric analysis and content analysis.

For citation mapping and comprehensive content analysis, total 393 Web of Science indexed journal articles were selected. Initially, this study identifies the most productive authors, journal sources, countries and affiliation within the study topic.

Findings from the intellectual structure explore four underlying research stems in the corporate governance and gender literature: participation of women on corporate boards and their characteristics, women directors and their roles in board across different countries, gender diversity in the board and corporate social responsibility and firm financial performances, risks and stock prices.

From the content analysis, it is revealed that corporate governance and gender studies have predominantly investigated the gender diversity issues as a catalyst of corporate governance, with a focus on women on corporate boards and firm financial performance, risks and stock price, while the area of board gender diversity and corporate social responsibility remains relatively under-researched.

Data envelopment analysis (DEA) calculates the efficiency of a business unit if all the inputs are creating outputs within a “black box.” Under traditional DEA, the detailed process of that business unit is ignored. However, a network DEA can explain the black box structure and provide efficiency results for sub-sections within any business process. This study aims to propose a network DEA model that explains a bank's total operation.

Earlier studies have focused only on bank efficiency ignoring this breakdown. This study departs from them by using a slack-based two-stage network DEA under a novel banking business perspective.

The results reveal that network DEA provides better benchmarking insights than the traditional DEA. As such, better benchmarking can guide both the banking industry managers and policy makers in Bangladesh.

The major contribution of this study includes dividing a bank's total operation efficiency into two sub-operations: “core operations – collecting deposits and giving loans” and “additional operations – fees, commissions and other services.”

This paper aims to present a citation-based bibliometric review of Islamic banking efficiency literature from 2000 until August 2020 for analyzing the content of the literature and mapping future research directions.

Using bibliometric citation analysis, this study reviews and examines a total of 278 documents from Web of Science (WoS) indexed sources coupled with content analysis.

The results identified that the growth of Islamic banking efficiency literature has begun to rise since 2008 with an annual growth rate of 12.5% while identifying the most influential aspects of Islamic banking efficiency literature in terms of topics, papers, authors and keywords. The outcomes of science mapping (i.e. co-citation network, bibliometric coupling and co-authorship network) reveal that there are three underlying research streams in Islamic banking efficiency literature: growth of Islamic banking efficiency literature, stability and genuineness of Islamic banking operations and the methods in Islamic banking efficiency literature.

To the best of the knowledge, this is the first bibliometric review paper on Islamic banking efficiency literature. It successfully unveils the scientific mapping of published WoS documents with a future research agenda also proposed based on the review outcomes. These findings can be used in efficiency-related initiatives by managers or regulators for managing Islamic bank operations worldwide.

Existing literature on how social learning stemming from flood experience influences management and adaptation to flood-risks, and resilience-building is scant. In this context, the purpose of this study is to map the processes and examine the application of social learning in formulating coping measures and adaptation strategies in Bangladesh's wetland communities.

To bridge this research gap, conceptually, we formulated the Social Learning from Disasters (SLD) Framework to explain the process of social learning from flood experience and the mechanism of its influence on community resilience. Applying a qualitative research approach, the empirical investigation was carried out in the Fenarbak Union of Sunamganj District, Bangladesh. Using a participatory approach and qualitative techniques, the required primary data were procured.

The results of the study yielded three key findings: (1) social learning and memory have often enabled wetland communities to adopt diverse coping and adaptive measures in response to flash floods; (2) social learning-based actions have resulted in reduced flood-risk and enhanced community resilience to flash floods, especially when these actions were supported by both local and external innovations and (3) the aforementioned social learning stemmed primarily from first-hand experience of flash floods, which was shared via various collective learning platforms.

The study followed a participatory methodology and the data were procured from two communities in the union level unit of Bangladesh. Therefore, generalization to apply to the larger context should be made with caution. Also, the study represents a cross-sectional study, and thus understanding of the long-term trend is not possible.

The findings of the study have direct and profound implications for local community-level disaster-risk planning. As there are serious deficiencies in documenting and preserving social learning for community resilience and development planning, this study offers a conceptual framework, along with empirical evidence, for transforming these lessons learned into practical actions for change.

The findings of the study highlight the importance of social learning as a collective effort and provide empirical evidence of innovative adaptations to change. These results are critical to formulating societal strategies for disaster-risk management as well as to enhance community resilience.

Limited efforts have hitherto been made to determine (1) how the actual process of social learning from disaster shocks takes place, and (2) how innovative adaptation strategies lead vulnerable communities to take up social learning-based actions. Our research attempts to fill these knowledge gaps by providing an evidence-based account of community resilience-building responses to flash flood disasters.