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The purpose of this study is to provide a comprehensive exploration of academic research on halal purchasing decisions and consumer behavior by integrating bibliometric and systematic review methodologies.

This study uses a multi-method approach, combining bibliometric and systematic review methodologies, to comprehensively analyze the domain of halal purchasing decisions and consumer behavior. A data set of 184 articles published between 2007 and 2024 was sourced from the Scopus database. The bibliometric analysis was conducted using Bibliometrix in R, facilitating performance analysis, science mapping and network analysis to explore key authors, affiliations, collaborations and thematic trends. Additionally, the systematic review examined the limitations and future research areas discussed in prior studies, providing the basis for formulating potential research questions to address identified gaps.

The study identifies significant contributions within the domain of halal purchasing decisions and consumer behavior, emphasizing the critical roles of religiosity, trust and halal certification as dominant themes. Bibliometric analysis reveals key authors, influential publications and collaborative networks, highlighting Malaysia as a central hub for research in this field. Additionally, the analysis underscores the intellectual structure and thematic evolution, identifying underexplored areas such as non-Muslim perspectives, emerging halal industries and geographic diversity. The systematic review complements these insights by addressing recurring methodological and theoretical limitations, offering targeted recommendations for future research.

This research uniquely combines bibliometric and systematic review methodologies to provide a comprehensive review of the halal consumer behavior literature, identifying limitations and gaps in prior studies and proposing actionable areas for future research.

This study aims to dissect and understand the latent themes of Islamic work ethic (IWE) and explore the driving factors of IWE research.

Structural topic modeling (STM), a sophisticated machine learning technique, was used to analyze a corpus of 205 articles sourced from the Scopus database. These articles cover the 36 years of research on IWE, from 1988 to 2024. Moreover, negative binomial regression was applied to examine the driving factors of IWE research.

The STM analysis unfolds ten topics in conjunction with IWE including individual success, workplace dynamics, organizational work ethics, knowledge management, employee citizenship behavior, financial ethics, job satisfaction, organizational commitment, performance enhancement and leadership. The further STM outputs included word clouds, prevalence proportions, correlation matrix, heatmap, relationship of topics with metadata, topic prominence in the publishing journals and, finally, illustrating trends and future prospects of research on IWE. The results of negative binomial regression reveal that number of authors, article age, journal indexing, authors from multiple countries and number of references are strong drivers of fostering research in IWE, by having significant positive impacts on total citations.

The insights from this study provide valuable guidance for businesses and organizations looking to integrate IWE principles into their operations. By promoting values such as fairness, hard work and ethical behavior, organizations can foster a more inclusive and morally grounded workplace culture. This, in turn, may lead to enhanced employee satisfaction, greater organizational commitment and improved overall performance. Additionally, the emphasis on ethical practices can contribute to broader societal benefits, such as increased trust in business practices and a stronger alignment with social responsibility initiatives.

This is a unique study that explores the latent themes and characteristics of the IWE literature through STM and provides insights on the future research directions. In addition, this study also examines the driving factors of IWE research.

This study aims to meta-synthesize the relationship between intellectual capital (IC) and the financial performance of Islamic banks. Specifically, it examines how different components of IC – human capital, structural capital, relational capital and capital employed – impact key financial performance metrics, including return on assets (ROA), return on equity (ROE) and Tobin’s Q (TQ).

A comprehensive meta-analysis was conducted, following the PRISMA guidelines, to synthesize findings from 29 peer-reviewed journal articles indexed in Scopus and Web of Science having accumulative sample size of 8,871. Effect sizes were calculated using Fisher’s r-to-z transformation, and a random-effects model was applied to estimate the overall effect sizes. Subgroup meta-analyses were performed to evaluate the relationships between specific components of IC and various financial performance measures.

The meta-analysis confirms a positive and statistically significant effect size (r = 0.227, p < 0.001) between IC and financial performance in Islamic banks. Human capital shows the strongest positive impact on ROA and ROE, highlighting the role of skilled employees in driving success. Structural and relational capital exhibit weaker and variable effects, whereas capital employed significantly enhances profitability. These findings underscore the complex nature of the IC–financial performance link, emphasizing the need for strategic management to optimize IC benefits.

This study fills a gap in the existing literature by providing a comprehensive meta-analysis focused on Islamic banks, which operate under unique principles compared to conventional banks. By highlighting the significant role of IC, particularly human capital, this research offers valuable insights for academics, practitioners and policymakers aiming to enhance the financial performance and sustainability of Islamic banks through strategic management of intellectual assets.

The purpose of this chapter is to assess the importance of individual social capital characteristics in determining wages, both directly through their valuation by employers and indirectly through their impact on individual occupational choice. We find that a person’s level of sociability and care for others works through both channels to explain wage differences between social and nonsocial occupations. Additionally, expected wages in each occupation type are found to be at least as important as a person’s level of social capital in choosing a social occupation. We make use of restricted 2000 Decennial Census and 2000 Social Capital Community Benchmark Survey.

This study attempts to come in help for Morocco by investigating rigorously the linkage between environmental degradation, measured by ecological footprint (EF), and the gross domestic product growth (EG), the human capital (HC) index and the natural resources (NR) depletion over the period of 1980:Q1 to 2021:Q1. The paper examines the validity of environmental Kuznets curve (EKC) hypothesis in the Moroccan context.

Unlike previous studies, which are based only on the autoregressif dynamic linear (ARDL) model, this paper investigates two recent models: the novel DYNARDL simulation approach and the Kernel-based regularized least squares (KRLS) technics and uses in addition the frequency domain causality (FDC) test.

Models output say a significant and negative association between HC and the EF and a significant and positive interplay between economic growth and environmental quality in the long term. In the short term, findings reveal a significant and negative association between NR and the EF. Based on the FDC test, results conclude about a unidirectional causality from NR to the EF in short-, medium-, and long-term. Moreover, results validate the EKC hypothesis for the Moroccan environment sustainability.

In this study, the researchers use the “ecological footprint” as dependent variable to obtain more accurate and comprehensive assessment of environmental deterioration. Based on time series data investigations, this study is the first paper, which validates the EKC hypothesis and develops important policy implications for Morocco context to achieve sustainable development targets.

The economics literature on gender has expanded considerably in recent years, fueled in part by new sources of data, including from experimental studies of gender differences in preferences and other traits. At the same time, economists have been developing more realistic models of psychological and social influences on individual choices and the evolution of culture and social norms. Despite these innovations, much of the economics of gender has been left behind, and still employs a reductive framing in which gender gaps in economic outcomes are either due to discrimination or to “choice.” I suggest here that the persistence of this approach is due to several distinctive economic habits of mind – strong priors driven by market bias and gender essentialism, a perspective that views the default economic agent as male, and an oft-noted tendency to avoid complex problems in favor of those that can be modeled simply. I also suggest some paths forward.

Unfortunately in India, most landfills are located along the banks of rivers flowing through the cities. The interaction of two big, diverse and delicate ecological systems – rivers and landfills – has been investigated in this paper. During 2000, the estimated quantity of waste generation was more than 9,000 tons per day. This is one of the biggest sources of environmental degradation in Delhi, India's capital. It contributes to river pollution in a significant way through landfill leachate and runoff, especially during the rainy season. Since the 1950s over 12 large landfills have been packed with all sorts of non‐biodegradable and toxic wastes from Delhi. The area covered by landfills is at least 1 percent (14.83 sq.km) of Delhi's total area. All the landfill sites except Tilak Nagar, Hastal and Chattarpur are located close (0‐6 km) to the river Yamuna. Further, these landfills are not engineered sanitary landfills and the waste is dumped at open sites without proper compaction. A high mountain of waste can be seen at all landfill sites without a cover. The leachate produced by landfills finally percolates to the porous ground surface at the landfills or finds its way to nearby drains. A large portion of landfill leachate and runoff produced by these landfill sites finally reaches the Yamuna through ground water flow or surface water flow through the drains. The results of analysis by investigations and environmental mapping during the study clearly indicate that river water quality is affected by the presence of landfill locations, i.e. landfill leachate and landfill surface runoff.

The purpose of this paper is to develop a measurement instrument toward knowledge management (KM) implementation in the Iranian oil industry.

Based on an in-depth study of the relevant literature, the critical success factors (CSFs) related to the sub-factors were identified. Then, exploratory and confirmatory factor analysis was used to validate the instrument. Finally, based on the developed instrument, the KM implementation was evaluated in the subsidiaries of the Iranian oil industry.

The obtained results reveal the 13 factors as follows: human resource management; KM processes; information technology; business strategy; intellectual capital; KM system; executive practices of KM; management information system; culture; partnership and cooperation with business partners; KM road map; leadership commitment and support; and organizational environment.

As this study was conducted in the Iranian oil industry, cautious should be taken regarding the generalizability of the results.

The proposed instrument can help policymakers and top managers of the subsidiaries of Iranian oil industry in successful implementation and measurement of their KM practices.

Identification and measurement of the CSFs of KM implementation through developing a comprehensive instrument in the context of the Iranian oil industry.

The emergence of smart cities, metropolises that integrate physical infrastructure, digital technology, and data analytics, and that focus on urban sustainability, have profoundly changed urban development. In the modern digital era, robust infrastructure has become an indispensable catalyst for urban advancement. Kuwait is dedicated to the integration of diverse renewable energy technologies in the development of smart cities that enhance energy security, promote innovation, and contribute to global climate change mitigation efforts. Focusing on smart cities within Gulf Cooperation Council (GCC) countries, a review is presented of how successfully they have effectively combined technology, infrastructure, and sustainability to serve as models for new global and regional developments. Insights into what makes a city smart are provided in different settings.

This chapter uses a college-by-graduate degree fixed effects estimator to evaluate the returns to 19 different graduate degrees for men and women. We find substantial variation across degrees, and evidence that OLS overestimates the returns to degrees with the highest average earnings and underestimates the returns to degrees with the lowest average earnings. Second, we decompose the impacts on earnings into effects on wage rates and effects on hours. For most degrees, the earnings gains come from increased wage rates, though hours play an important role in some degrees, such as medicine, especially for women. Third, we estimate the net present value and internal rate of return for each degree, which account for the time and monetary costs of degrees. Finally, we provide descriptive evidence that satisfaction gains are large for some degrees with smaller economic returns, such as education and humanities degrees, especially for men.