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This study investigates the mediating role of working capital management (WCM) efficiency between board diversity (based on gender and financial knowledge) and firm performance. The study further examines which WCM approach (conservative, moderate, and aggressive) they employ to increase (decrease) firm performance.

The study employs listed energy firms of Pakistan over the period 2010 to 2019. The system generalized method of moments estimator and logit model are utilized to estimate the underlying relationships.

The results show that WCM efficiency partially mediates the relationship between board financial expertise (BFE) and firm performance. Nonetheless, the presence of female directors is merely symbolic until they reach a certain level as only the quadratic term of board gender diversity (BGD) has a significant effect on firm performance. Female directors do not influence WCM efficiency. The results also demonstrate that BGD encourages a conservative WCM approach, while BFE encourages a moderate WCM approach. Furthermore, both conservative and moderate WCM approaches are significantly associated with firm performance.

The findings hold implications for increasing the representation of women and financial experts on board to improve the capital structure decisions of the energy firms in Pakistan.

This study is the first attempt to explore the mediating role of WCM efficiency between board diversity and firm performance. To the best of the authors' knowledge, no previous study has investigated the effect of BGD and BFE on different WCM approaches distinctly.

Purpose: The primary purpose is to discuss the productivity and digitalisation interaction at the theoretical level, analyse the productivity and digitalisation differences between the European Union (EU)-14 and EU-13 countries, and evaluate the digitalisation impact on the manufacturing sector labour productivity of the EU countries.

Need for study: The average added value created per capita in new EU countries (EU-13) is one-third lower than in old EU countries (EU-14). To increase productivity, manufacturing companies must adapt to modern trends and take advantage of industrial digitisation opportunities. Digitisation can improve production efficiency, reduce costs, and improve product quality, allowing continuous monitoring and analysis of production data, enabling informed decisions and faster problem-solving.

Methodology: Analysis of scientific literature, comparing viewpoints, insights, and conclusions. The empirical study includes calculating rates of change of indicators, differences between EU-14 and EU-13, and structural analysis. The impact of digitisation on the productivity of EU countries is studied by creating a correlation matrix and using regression analysis: ordinary least square models.

Findings: EU-13 countries are behind EU-14 in labour productivity and manufacturing digitalisation. Digitalisation positively impacts productivity per employee. A faster increase in digitisation, industrial robot use, and e-commerce sales could significantly increase productivity in EU-13, reducing productivity differences between countries.

Practical implications: This study highlights the need for policy promoting digitisation innovation, particularly in EU-13 countries, to be implemented by both national and EU-based economic development and regional and cohesion institutions.

This study aims to explore the relative efficiency of the working capital management (WCM) for Emirati firms before and during the coronavirus crisis. Next, this study explores the potential impact of WCM on the likelihood of financial distress.

A data envelopment analysis (DEA) was applied to assess the relative efficiency of the WCM. This study uses the emerging market Z-score model to predict the likelihood of financial distress. The logistic regression was applied to investigate the impact of the efficiency of WCM on firms’ financial distress.

The results of this study model showed a negative and significant influence of the efficiency of WCM on firms’ financial distress likelihood.

The findings have important implications for many stakeholders, including decision makers, WC managers, financiers, investors, financial consultants, researchers and others, in increasing their awareness of firms’ WCM performance before and during the crisis. Further, the results could have implications for trading strategies as investors seek attractive economic gains from their investment in firms that care about WCM.

The implications of WCM performance on social interests would cause firms’ decision makers to operate efficiently and achieve the best practices to minimise the probability of firms' financial distress.

This study advances a novel contribution to the literature by introducing a novel model to assess WCM based on DEA technology.

The objective is to develop a more effective model that simplifies and accelerates the news classification process using advanced text mining and deep learning (DL) techniques. A distributed framework utilizing Bidirectional Encoder Representations from Transformers (BERT) was developed to classify news headlines. This approach leverages various text mining and DL techniques on a distributed infrastructure, aiming to offer an alternative to traditional news classification methods.

This study focuses on the classification of distinct types of news by analyzing tweets from various news channels. It addresses the limitations of using benchmark datasets for news classification, which often result in models that are impractical for real-world applications.

The framework’s effectiveness was evaluated on a newly proposed dataset and two additional benchmark datasets from the Kaggle repository, assessing the performance of each text mining and classification method across these datasets. The results of this study demonstrate that the proposed strategy significantly outperforms other approaches in terms of accuracy and execution time. This indicates that the distributed framework, coupled with the use of BERT for text analysis, provides a robust solution for analyzing large volumes of data efficiently. The findings also highlight the value of the newly released corpus for further research in news classification and emotion classification, suggesting its potential to facilitate advancements in these areas.

This research introduces an innovative distributed framework for news classification that addresses the shortcomings of models trained on benchmark datasets. By utilizing cutting-edge techniques and a novel dataset, the study offers significant improvements in accuracy and processing speed. The release of the corpus represents a valuable contribution to the field, enabling further exploration into news and emotion classification. This work sets a new standard for the analysis of news data, offering practical implications for the development of more effective and efficient news classification systems.

The purpose of this paper is to examine the impact of microfinance programs sponsored by Sudanese microfinance institutions (SMFIs) on monetary poverty reduction in Sudan where poverty is widely spread.

The study adopted the control group approach, where income and expenditure are taken as welfare indicators. The updated World Bank’s international poverty line of 1.90 per person per day was adopted to separate the poor from non-poor. The data were collected by the means of a questionnaire distributed to a random sample of beneficiaries in the institution under study. The study adapted the Foster, Greer and Thorbecke (FGT) model to evaluate the role of microfinance programs in poverty reduction. Furthermore, to gain more insight into the impact of the program, a preliminary analysis was conducted using the independent-samples t-test to examine the difference in the welfare indicators for the sample of the control group and treatment group as well as that of the small loan group and micro-loan group.

The findings show that the microfinance program provided by SMFIs has reduced the monetary poverty among the participants. The results also reveal that beneficiaries who had received a larger volume of loan were noted lesser poverty than those who had received very small loan size. Moreover, the results demonstrate that poverty indices based on expenditure as a welfare indicator are far lower than those based on income for both groups.

This study contributes to the available literature by filling the gaps through including income and expenditure as monetary variables, which included separately in previous studies adopted the FGT model in the area of microfinance, in addition to exploring the role of loan size in the effect of microfinance on poverty reduction.

This qualitative study aims to investigate the critical success factors (CSFs) driving the adoption of virtual reality (VR) in the hospitality industry, shedding light on key determinants for successful implementation.

Drawing on a diverse set of interviews conducted in Italy, Pakistan, the USA and Turkey, this study uses thematic analysis facilitated by NVivo 12 to comprehensively explore and identify the CSFs influencing VR adoption within the global hospitality industry.

This study identifies distinct CSFs at various phases of VR adoption in the hospitality industry. Preimplementation emphasizes budget planning and stakeholder engagement, implementation highlights safety training and feedback mechanisms and postimplementation underscores the importance of innovation, feedback utilization and maintenance for sustained success. These findings offer a strategic roadmap for VR integration in hospitality.

The study informs hospitality industry stakeholders of crucial success factors for VR adoption, thereby guiding strategic decision-making. Sustained VR integration success is ensured by emphasizing budget planning, stakeholder engagement, safety training, feedback mechanisms and postimplementation innovation.

To the best of the authors’ knowledge, this groundbreaking research is the first in-depth investigation into CSFs for the adoption of VR in the hospitality industry. This research advances our understanding of and provides fresh guidance for effective VR integration by revealing novel insights into the key variables at various deployment phases.

This study aims to explore the customers’ behaviour towards online shopping during COVID-19 in a Muslim country and proposes a co-creative service design for online businesses (webstore) in the post-COVID-19 era.

The study used a qualitative design for collecting the data where in-depth interviews from 18 customers were conducted following the qualitative design protocol. Due to the limitation of physical distancing, the interviews were conducted online using Microsoft teams.

Based on the findings, new potential services are proposed for webstores for customer engagement, the need for expansion of product lines and safety measures for customers and staff during and post-COVID-19 era. Following the findings, a co-creative service design is proposed for webstores to revamp the business during and post-COVID-19.

The study is unique because it has developed various unique strategic factors essential for revamping online businesses for better growth in post-COVID-19. The proposed new co-creative service design model for an online service provider is expected to create customers engagement and loyalty during and in post-COVID-19.

This study aims to explore the current trends in the literature about environmental, social and governance (ESG) practices within Islamic banking. It also seeks to identify research gaps and propose directions for future inquiry.

Using a bibliometric analysis, this study synthesises 753 articles from the Scopus database from 1988 to 2023. The analysis was conducted using the biblioshiny package in RStudio and VOSviewer.

It reveals an increasing trajectory in the volume of literature on ESG within Islamic banking, with Muslim-majority countries supported by robust regulatory frameworks leading the discourse. Emerging interest from Muslim-minority countries is also noted. This research delineates five principal research streams and proposes future investigative pathways, including the influence of institutional factors on Islamic banks’ ESG practices.

This study offers valuable insights for Islamic bank management and stakeholders, enhancing their comprehension of ESG practices’ current landscape. Additionally, it directs emerging scholars towards novel and pertinent research opportunities within this domain.

Amidst a growing body of work on ESG and Islamic banking, this study is, to the best of the authors’ knowledge, the first bibliometric review dedicated solely to ESG considerations in Islamic banks. It augments the extant literature by adopting a more stringent methodological approach and a rigid quality assessment.

Considering the existing evidence on the impact of female board members on the default risks of an organization, the purpose of this study is to investigate the effect of board gender diversity, alongside institutional characteristics and macroeconomic factors, on the financing costs of microfinance institutions (MFIs).

This study collected unbalanced panel data of 1,190 unique MFIs between 2010 and 2018 from the World Bank. The collected data, which covers a total of 95 developing and emerging countries, was thereafter analyzed using the pooled ordinary least squares and random effects model. To overcome endogeneity and omitted variable bias (e.g. time-invariant variables), the authors have also used the generalized method of moments and fixed effects model, respectively. Different proxies of board gender diversity and sub-sample analysis by regions were further undertaken to examine the robustness of the obtained results.

The findings of this study revealed that board gender diversity has a statistically significant negative effect on the financing costs of MFIs. This suggests that a gender-diverse board can generate cheaper funding for MFIs by minimizing their default risks through effective monitoring and strategic management. Furthermore, the negative impact of board gender diversity on financing costs appears to be more pronounced when there is a minimum of two female board members in the boardroom of MFIs. The results of this study remain consistent and valid regardless of alternate model specifications (e.g. sub-sample analysis, use of alternative proxies of board gender diversity and application of different estimators) and endogeneity issues. Ultimately, the findings in this study reiterate the importance of promoting and implementing gender diversity in the boardroom to minimize the financing costs of MFIs.

This study investigated the relationship between board gender diversity and financing costs of MFIs by using relatively recent and global data. The minimum number of female board members required to significantly reduce the financing costs of MFIs was also identified.

This study aims to provide insights into the public–private partnerships (PPP) concept and its performance measurement in the health-care sector, identifying and refining critical success factors, including the perceived quality of health care, as evidenced by patient satisfaction and policy requirements for successful PPP implementation.

This theoretical study explores the existing literature on the relationship between service quality and patient satisfaction, to propose a culture-specific conceptual model interlinking the drivers of patient satisfaction with PPP. The in-depth theoretical research focuses on the qualitative performance indicators of PPPs, as well as their corresponding peripheral factors.

The research presents theoretical evidence that the concept of patient satisfaction can only be viewed through a multifactor perspective that incorporates demographics of patients, perceived service quality factors and emotions. It is found that significant improvements in service quality and patient satisfaction do, indeed, emphasize the effective role of PPP in hospitals.

The theoretical model is based on a comprehensive set of both cognitive and affective determinants. And considering these, as well as their causes, effects and interrelations, sets the foundations for testing and for further research to develop. Moreover, the outcomes of this study can be used as a theoretical base for the development of a PPP qualitative performance measurement framework.

This study attempts to fill the gap in knowledge on service quality and patient satisfaction as qualitative indicators for hospital performance after and toward PPP, while setting explicit factors and opening clear research avenues for further studies to follow.