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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.

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.

Besides the extensive research on managerial efficiency in the financial sector worldwide, emerging economies in Europe remain untapped. This research scrutinises the impact of managerial performance and competitive structures on their financial industry growth in terms of services they offer and ability to liquefy stock in capital markets.

This study contains data from selected emerging European countries' during the period of 2010–2020. This study uses data from the Heritage Foundation's Index of Economic Freedom to control for firm-level indicators. The fixed-effects (FE) method was used to explore the nexus between financial sector growth and management performance as well as competitive firm structure.

The findings provide evidence of the existing impact of firm indicators on the financial sector's growth. Two-step system the generalized method of moments (GMM) estimations are used for the robustness check of the authors' model. Whilst on a scavenger hunt through existing literature, the authors realise that there is an overwhelming lack of enthusiasm in this field.

With the intention of better assessment, the authors use regulatory contextual variables to look for any possible impacts and surprisingly discover a pattern in the financial growth nexus.

Although there has been a significant amount of research on Smart Tourism, the articles have not yet been combined into a thorough literature review that can examine research streams and the scope of future research. The purpose of this study is to examine the literature on the impact of deploying the Internet of Things (IoT) in tourism sector development to attract more visitors using a text mining technique and citation based bibliometric analysis for the first time.

This study uses R programming to do a full-text analysis of 36 publications on IoT in tourism and visualization of similarities viewer software to conduct a bibliometric citation analysis of 469 papers from the Scopus database. Aside from that, the documents were subjected to a longitudinal study using Excel and word frequency using a trending topic using the R-tool.

Results from the bibliometric study revealed the networks that exist in the literature of Tourism Management. With the use of log-likelihood, the findings from text mining identified nine theme models on the basis of relevancy, which is presented alongside an overview of the existing papers and a list of the primary authors with posterior probability using latent Dirichlet allocation.

This study examines tourism literature in which IoT plays a significant role. To the best of the authors’ knowledge, this study is the first to combine text mining with a bibliometric review. It significantly analyzes and discusses the impact of technology in the tourism sector development on attracting tourists while presenting the most important and frequently discussed topics and research in these writings. These findings provide researchers, tourism managers and technology professionals with a complete understanding of e-tourism and to provide smart devices to attract tourists.

Aunque ha habido un número importante de estudios sobre el turismo inteligente, todavía no se dispone de una revisión bibliográfica exhaustiva que permita examinar las corrientes de investigación y las sugerencias de investigación futuras. Este estudio examina la literatura sobre el impacto del Internet de las cosas en el desarrollo del sector turístico para atraer más visitantes utilizando una técnica de minería de textos y un análisis bibliométrico basado en citas.

Este estudio utiliza la programación R para hacer un análisis de texto completo de 36 publicaciones sobre IoT en el turismo y el software de visualización de similitudes (VOS) para realizar un análisis bibliométrico de citas de 469 documentos de la base de datos Scopus. Además, los documentos fueron sometidos a un estudio longitudinal mediante Excel y a la frecuencia de palabras mediante un tema de tendencia utilizando la herramienta R.

Los resultados del estudio bibliométrico revelaron las redes existentes en la literatura de la Gestión Turística. Con el uso de la log-verosimilitud, los resultados de la minería de textos identificaron nueve modelos temáticos sobre la base de la relevancia, que se presentan junto con una visión general de los documentos existentes y una lista de los autores principales con probabilidad posterior utilizando la asignación latente de dirichlets.

Este estudio examina la literatura sobre turismo en la que la IoT desempeña un papel importante. Este estudio es el primero que combina la minería de textos con una revisión bibliométrica. Analiza y discute de forma significativa el impacto de la tecnología en el desarrollo del sector turístico para atraer a los turistas, a la vez que presenta los temas e investigaciones más importantes y más frecuentemente discutidos en estos escritos. Estos resultados proporcionan a los investigadores, gestores turísticos y profesionales de la tecnología una comprensión integral del turismo electrónico y los dispositivos inteligentes para atraer a los turistas.

虽然已经有大量关于智慧旅游的研究, 但这些文章尚未整合成一个全面的文献综述, 可以检阅目前的研究流和未来研究的范畴。本研究首次使用文本挖掘技术和基于引文的文献计量分析, 来研究有关在旅游业发展中部署物联网对吸引更多游客的影响的文献。

本研究使用R编程对36篇关于旅游业物联网的文章进行全文分析, 并使用相似性可视化（VOS）查看器软件对Scopus数据库中的469篇论文进行文献计量引文分析。除此之外, 还利用Excel对这些文献进行了纵向研究, 并使用R工具对趋势主题进行了词频分析。

文献计量研究的结果揭示了旅游管理文献中现有的网络。通过使用对数似然, 文本挖掘的结果根据相关性确定了9个主题模型, 这些模型与现有论文的概述和主要作者名单在使用潜在狄里奇分配（LDA）的后验概率一起呈现。

本研究对旅游物联网相关文献进行了分析研究, 它首次将文本挖掘与文献计量学审查相结合。这项研究着重分析和讨论了技术在旅游行业发展中对吸引游客的影响, 同时介绍了这些文章中最重要和经常讨论的主题和研究。这些发现为研究人员、旅游管理者和技术专家提供了对科技与旅游的全面了解, 并提供关于智能设备来吸引游客的建议。

The Asian banking system has been appreciated with many distinct qualities including consistent in profitability. Many studies have examined the profitability of Asian banking sector from diverse perspectives. However, studies on bank profitability in connection to the capital structure, operating efficiency and non-interest income are only a few. This study investigates the influence of capital structure as estimated by leverage ratio and long-term debt, operating efficiency and non-interest income on the profitability of the banking industry in 28 countries of Asia.

This paper utilizes fixed effect regression model by involving panel data with sample of 492 banks from 28 countries of Asia for the time span of 15 years from 2004 to 2018.

The results confirm that an increase in total debt ratio increases the profit margin of the bank as supported by the agency cost theory, suggesting that the debt financing increases the profitability of the firm. In addition, the findings reveal that lowering the operating expenses and managing of costs effectively can boost the profitability of bank. Furthermore, non-interest income plays a vital role when the interest rates are lower. Hence the study suggests that a careful investment in this sector can generate income as well as increase the profit margin of the banking arena.

The paper examines the profitability of bank by including impact of leverage ratio and long-term debt as a measure of capital structure along with the influence of operational efficiency and non-interest income which contributes to the understanding of the existing literature.

This study aims to pinpoint gaps in the literature on corporate governance and remuneration by producing a comprehensive bibliometric review for the period 1990–2020.

Bibliometric analysis is the quantitative study of the bibliographic material in a specific research field. It allows an analyst to classify that material by paper, journal, author, indexation, institution or country, among other possibilities. This study reviews a total of 298 Web of Science–indexed journal articles on corporate governance and top-management remuneration schemes.

The authors find five distinct research strands: (1) firm performance and remuneration of top management, (2) the remuneration and independence of boards of directors and the efficiency of boards of directors as a governance system, (3) outside-director remuneration and the efficiency of outside directors as a monitoring system, (4) director remuneration and the corporate governance of companies and (5) the role of ownership structure and top managers' compensation schemes as corporate-governance tools. The authors identify gaps in the literature and avenues for future research for each of these strands.

The authors’ findings have implications for board diversity (e.g. gender diversity), remuneration policy for top-level managers and governance issues (independent directors, separation of ownership with control). This study is the only one to summarize the key topics on which top research has been focused and can be broadly used for corporate governance management perspective.

This paper provides an overview of how the literature on corporate governance and remuneration has developed and a synopsis of the most influential and most productive authors, countries and journal sources. It creates an opportunity for other researchers to focus on this area. This study will also serve as a foundation for future meta-analyses.

Personal remittance and ready-made garments (RMG) export incomes have emerged as the largest source of foreign income for Bangladesh's economy. The study investigates their impact on income inequality and gross domestic product (GDP) as a control variable, using time-series yearly data from 1983 to 2018.

It employs the Autoregressive Distributed Lag (ARDL) estimation and the Toda-Yamamoto (T-Y) causality approach. The ARDL estimation outcomes confirm a long-run association among the above variables and validate the autoregressive characteristic of the model.

Personal remittances positively contribute to reducing the income gap among the people of the society and declining income inequality. In contrast, RMG export income and economic growth contribute to further income inequality. The T-Y causality analysis follows the ARDL estimation outcomes and authenticates their robustness. It reveals a feedback relationship between remittance inflow and the Gini coefficient, unidirectional causalities from RMG export income to income inequality and economic growth to income inequality.

The finding has important policy implications to limit the income gaps between low and high-income groups by channeling incremental income to the lower-income group people. The policymakers may facilitate further international migration to attract further remittances and may upgrade the minimum wage of the RMG workers.

The study is original. As far as the authors' knowledge goes, this is a maiden attempt to investigate the impact of personal remittances and RMG export income on income disparity in the case of Bangladesh.

This paper aims to study the extent of use of artificial intelligence (AI) in the modern organization; to comprehend the changing nature of future jobs in the context of application of AI; and to study the impact of AI on the economy of the country with special reference to the job market. Given the critical scenario of labor intensive Indian economy, the paper intends to show how AI shall affect rather coexist with human intelligence or labor.

The research on implementation of AI in different industries and its effect on job market are at a nascent stage. There is a dearth of literature. Hence, this study followed a qualitative approach to have a better understanding of the research questions as Bhattacherjee (2012) confirms that employing an interpretive paradigm (qualitative analysis as the analysis of data, e.g. data from interview transcripts) is the more productive way to study social order and that it is achieved through “subjective interpretation of participants involved, such as by interviewing different participants and reconciling differences among their responses using their own subjective perspectives”. Sample selection: The selection technique utilized is purposive sampling. The respondents in this research are the general managers and HRs from different companies. A total of 14 senior professionals from various sectors were approached for the interview out of which seven people gave their consent to take interview. Seven senior HR professionals, mainly general managers and HRs from various sectors viz. oil and gas sector, manufacturing, healthcare, construction, media, power and energy and retail were interviewed to understand how they are using AI in their respective fields. Inclusion Criteria: (1) Generally, the people covered under the research are from the decision-making level of their companies so they are in a position to give strategic perspective as well as day to day implication of implementation of AI. (2) Respondents have adequate knowledge of the respective industry to which they belong. (3) Respondents have reasonable industry of dealing with Human Resource Management and national economy as a whole assessment tool and its administration procedures. A narrative approach was adopted to have a better understanding of the research questions and comprehend their views regarding implementation of AI in their respective companies. A semi structured open ended interview was administered to steer the discussion around the research questions. The respondents were interviewed over the phone and each respondent shared their stories. Analysis of data: The narrations were then transcribed by online transcriber website otter.ai.com. The common keywords as prescribed by the website are as: AI, strategy, learning and implementation. The extracts of the discussions are noted in the next segment of the paper. As and when required this research also used secondary data from the journals, literature available in the websites to understand the implementation of AI globally.

A country where the government itself admits 90% of its workforce belongs to informal sector and conspicuously exits a multi-faceted stark digital divide (Huberman, 2001; DiMaggio et al., 2001; Guillen, 2006; Servon, 2002) wherein gap of digital divide is significant between the rural and urban India (Dasgupta et al., 2002; Nath, 2001; Singh, 2007; Mahajan, 2003; Dutta, 2003) talking of educating, applying and implementing AI seems to be “ a distant dream” but an “ambiguous ambition ”

Prior to implementation of AI that India has to ensure, the basic hygiene factors of informal sector labor force like social security, 2008, low wages and lack of legal protection, unpaid overtime and occupational health problems, poor bargaining power, working without leave under coercion, child care issues and health ailments(for which mere legislation or statutarization is just a formality executed than taking real action) to take the majority of Indian workforce to attain the motivational factor to acquire the knowledge and skill of AI and to implement it.

The AI and its adoption are still at their embryonic stage in Indian companies. With the adoption of such sophisticated technology, in one side, the organizations are dreaming of efficiency, higher productivity and better organizational performance whereas on the other side requirement of changing skill sets and decreasing manpower, creating fear among the mass, which results in hard resistance against the implementation process of AI. On the other hand, lack of expertise and high cost of adoption is also hindering AI to implement in the organizations. The adoption and implementation stage of AI vary from organization to organizations, as well as functions to functions. While the marketing departments of several organizations are using advanced level of AI, there, the HR departments are using AI at the very initial stage. But it is evident from the above discussions that adoption of AI in business functions is inevitable and only it is a matter of time. With the COVID-19 pandemic this has become the utmost necessity for many organizations, particularly who works across the globe. HR partners of the businesses are also adopting AI at a fast pace to do away with the mundane works and deliver efficient services to the stakeholders. It is understood from the discourse that the prerequisite for a successful implementation of AI across the industries throughout the country, needs a concerted effort from industries, academia and government.

The answer lies in Keynesian economics. The central tenet of which is government intervention rather investment to stabilize and progress the economy by way of spreading Internet connectivity, basic literacy and computer literacy, then only truly AI can be effective in a greater scale.

A study on application of artificial intelligence in the pandemic era from a wider perspective, this work is an empirical investigation into the benefits and limitations of artificial intelligence for human potential and labour -intensive pandemic ridden Indian economy.