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Given the overlapping themes and periods in specific subjects within Islamic economics and finance bibliometric research, which may yield similar findings in bibliometric studies, it is essential to document the growth of Islamic economic and financial research using bibliometric methodologies. This study aims to understand better the critical bibliometric review trends and scientific advancements in Islamic economics and finance.

This study uses bibliometric analysis, collecting 46 Islamic economics bibliometric papers from the Web of Science Core Collection from 1975 to 2022. The authors generated top scientific scholars, keyword analysis, citation analysis, content analysis and conclusions for journal development using R Biblioshiny, VOSviewer, ATLAS.ti and Excel.

This study has established a comprehensive bibliometric framework for Islamic economics and finance bibliometric papers, encompassing all critical areas within the discipline and identifying any remaining research gaps. The major significant areas revealed were Islamic social finance and microfinance concerns, which are closely pertinent to the issues of ethics, corporate social responsibility and sustainability, respectively. The authors also identified opportunities for future bibliometric analyses in Islamic economics and finance, which include using more comprehensive databases, refining or broadening search strategies, using advanced techniques and units of analysis and suggesting themes for further exploration.

The study relies merely on the Web of Science Core Collection database, which provides the most in-depth citations by source for the world’s scientific and scholarly research. Future research may consider expanding its scope to include other databases for a broader range of sources. Furthermore, due to the rise of bibliometric studies in Islamic economics and finance, this study also comments on the saturation of bibliometric studies conducted in several similar areas. While researchers bring their unique analytical perspectives to bibliometrics, this study provides a comprehensive view of existing research in Islamic economics and finance, highlighting well-explored topics and those that remain less studied. Thus, this could assist researchers in determining their future research priorities.

Policymakers in Islamic financial and economic institutions, including banking institutions, social, financial institutions and halal institutions, should be impacted by this research when making policies or conducting research. The viability of the current Islamic economic and financial ecosystem will be indirectly maintained and managed by these implications.

This comprehensive meta-analysis in Islamic economics and finance is expected to impact the development and sustainability of the Islamic economic and financial ecosystem, promoting societal welfare through applying Islamic economics and finance.

This pioneering bibliometric analysis of Islamic economics and finance papers aims to offer insights and projections for future research in the field. This research contributes to the literature by examining various aspects, including evaluating literature on trending topics, analyzing papers related to research areas and conducting content analysis of existing bibliometric studies in Islamic economics and finance. It specifically groups these studies around fundamental topics, summarizes findings from contemporary research and identifies emerging research gaps.

This study aims to examine connections between five variables, including innovation in environment-related technology (EI), trade openness (TRADE), CO₂ emissions (CO₂) and foreign direct investment (FDI) from 1994 to 2019.

This study used an extended joint connectedness technique and the time-varying parameter vector autoregression (TVP-VAR) method. The analysis focuses on the variables of innovation in environment-related technology (EI), trade openness (TRADE), CO₂ emissions (CO₂) and foreign direct investment (FDI) using data from 1994 to 2019.

The results demonstrate that innovation in environment-related technology and an openness to the global network captured by FDI are identified as crucial net transmitters of shocks. In addition, an openness to the global trade network captured by TRADE turns from a transmitter to a receiver of shocks and vice versa. Moreover, it can be seen that the impact of EI was significant in the first five years of the observed period, and it transmitted the largest shock in 1997.

With regard to policy implications, the findings offer valuable insights for investors and policymakers. As the tradeoff between business efficiency and environmental sustainability diminishes, it is essential for Vietnam’s economy and enterprises to embrace green and sustainable growth in line with global trends. In a world characterized by uncertainties and risks, enterprises need to develop strategies to manage risks and shocks arising from geopolitical tensions, input material supply, financial–monetary instability and natural disasters.

This study contributes to the existing literature in two significant ways. First, as previously emphasized, this paper represents the first attempt to investigate the relationship between economic globalization and environmental innovation. Second, this study proposes a novel methodology that is better suited for analyzing volatility interlinkages across different market types.

The present study investigates a nexus between digital public services (DPS) and international tourism empirically.

This article analyzes the nexus of DPS and international tourism by using the international sample of 23 European countries in the span of nearly 10 years from 2011 to 2019. Various econometric techniques, including the panel-corrected standard error (PCSE) model and the feasible generalized least squares (FGLS) model, are employed to confirm the author’s findings. Furthermore, the autoregressive distributed lag (ARDL) method is applied to measure the short- and long-run effects of DPS on international tourism developments.

Tourism is positively influenced by digitalization, implying that the enhancement of digital public service usage results in the development of the tourism industry. However, when looking at the effect of DPS in the short term, a negative impact can be found on tourism, as the density reported in the previous analysis stated a negative response to the tourism density. This effect spans the course of several facets, such as international tourism arrivals, international tourism receipt, international tourism, receipts (% of total exports) and global tourism expenditure (% of total imports). Although the result is unfavorable in the short term, digitalization promises great prospects for tourism in the long term. Notably, an improvement in economic growth, financial development as well a reduction in the pervasiveness of corruption and an improvement of environmental quality are transmission channels through which DPS have favorable influences on tourism activities.

The author’s findings are vital for managers and policymakers to establish a comprehensive grasp of digitalization's role in deciding tourist adoption. This is because digitalization has been proven to play a role in determining tourism adoption.

The present study is the first to examine the relationship between DPS and international tourism empirically. The author is also the first to distinguish the effects of digitalization in the short and long run.

This study aims to investigate two issues: (1) a nexus between climate-related financial policies (CRFP) and global value chains (GVC) and (2) the government’s policies to help countries enhance the efficient use of CRFP in improving a country’s likelihood to participate in GVC.

To investigate the connection between GVC and CRFP, the authors incorporate that backward participation is measured using foreign value-added, while domestic value-added is used to measure forward participation, quantified as proportions of gross exports. The study analyses yield significant insights across a span of 20 developing countries and 26 developed countries over the period from 2010 to 2020.

Regarding the first issue, the authors affirm the presence of a linear link between GVC and CRFP, implying that involvement in CRFP is advantageous for both backward and forward participation. Furthermore, the authors identify long-term GVC and CRFP cointegration and confirm its long-term effects. Notably, the expression of a linear relationship between GVC and CRFP appears to be stronger in developing countries.

The study findings, together with previous research, highlight the importance of financial policies relating to climate change (CRFP) in the context of economic growth. Climate change’s consequences for financial stability and GVC highlight the importance of expanded policymakers and industry participation in tackling environmental concerns.

Regarding the second issue, the study findings suggest critical policy implications for authorities by highlighting the importance of financial stability and expanded policymakers in promoting countries' participation in GVC.

This paper investigates the link between GVC performance and CRFP, offering three significant advances to previous research. Moreover, as a rigorous analytical method, this study adopts a typical error model with panel correction that accounts for cross-sectional dependency and stationarity.

This paper aims to investigate the short- and long-run influence of core banking solutions (CBSs) on productive efficiency and identify the presence of potential network externalities arising from CBS adoption. This paper further examines the differential behaviour of long-term effects across the banking structure.

This study uses a panel data set of Indian commercial banks from 2005 to 2021. Economic efficiency is quantified using VRS-based DEA programming algorithms. Productivity changes are measured through an input-oriented, DEA-based Malmquist productivity index. Short- and long-run effects are examined through a finite autoregressive distributed lag model, estimated through a pooled mean-group estimator.

Findings suggest that CBS adoption negatively correlates with cost structure until the first year of adoption. Nevertheless, significant benefits are visible from the third year. Furthermore, such associations are highly susceptible to the industry structure. CBS results in higher incremental benefits for private banks vis-à-vis state-owned banks. Large banks receive significant and quicker productivity improvements from CBS vis-à-vis small banks. Bank age guides CBS–performance associations, highlighting that mature banks may face the issue of legacy infrastructure in CBS adoption. The resultant networking externalities are significant as they enhance the attractiveness of the network, which subsequently augments inter-branch and inter-bank communications.

To the best of the authors’ knowledge, this study is the first to recognise the stickiness of one of the most homogeneously adopted technological innovations in the Indian banking sector. The presence of a conjoint technological network has the potential to enhance the service delivery process and ensure superior returns for Indian banks.

House price fluctuations send vital signals to many parts of the economy, and long-term predictions of house prices are of great interest to governments and property developers. Although predictive models based on economic fundamentals are widely used, the common requirement for such studies is that underlying data are stationary. This paper aims to demonstrate the usefulness of alternative filtering methods for forecasting house prices.

We specifically focus on exponential smoothing with trend adjustment and multiplicative decomposition using median house prices for Sydney from Q3 1994 to Q1 2017. The model performance is evaluated using out-of-sample forecasting techniques and a robustness check against secondary data sources.

Multiplicative decomposition outperforms exponential smoothing at forecasting accuracy. The superior decomposition model suggests that seasonal and cyclical components provide important additional information for predicting house prices. The forecasts for 2017–2028 suggest that prices will slowly increase, going past 2016 levels by 2020 in the apartment market and by 2022/2023 in the detached housing market.

We demonstrate that filtering models are simple (univariate models that only require historical house prices), easy to implement (with no condition of stationarity) and widely used in financial trading, sports betting and other fields where producing accurate forecasts is more important than explaining the drivers of change. The paper puts forward a case for the inclusion of filtering models within the forecasting toolkit as a useful reference point for comparing forecasts from alternative models.

To the best of the authors’ knowledge, this paper undertakes the first systematic comparison of two filtering models for the Sydney housing market.

This article aims to investigate the role of socioeconomic factors and individual time preferences in the demand for fast-food in Russia. An individual discount rate shows the ability of a person to postpone utility from consumption to future periods.

An individual discount rate is measured through a hypothetical money experiment. The database is the special survey of the Levada analytical center conducted in 2017. Multivariate probit model enables the authors to consider the possible endogeneity of individual discount rate and reveal the relationship between socioeconomic factors and frequent fast-food consumption.

Results show that a higher individual discount rate is related to frequent consumption of fast-food. At the same time, there are factors that provoke both a higher individual discount rate and the refusal of frequent consumption of fast-food. Findings advise the prioritization of measures highlighting the short-term benefits of healthy eating and the short-term costs of avoiding it.

To the authors' knowledge, this article is the first one which presents comprehensive investigation of microeconomic factors of fast-food consumption in Russia including individual time preferences of consumers.

The Grey System Theory (GST) is an emerging area of research within artificial intelligence. Since its founding in 1982, it has seen a lot of multidisciplinary applications. In just a short period, it has garnered some considerable strengths. Based on the 1987–2021 data collected from the Web of Science (WoS), the current study reports the advancement of the GST.

Research papers utilizing the GST in the fields of economics and education were retrieved from the Web of Science (WoS) platform using a set of predetermined keywords. In the final stage of the process, the papers that underwent analysis were manually chosen, with selection criteria based on the information presented in the titles and abstracts.

The study identifies prominent authors, institutions, publications and journals closely associated with the subject. In terms of authors, two major clusters are identified around Liu SF and Wang ZX, while the institution with the highest number of publications is Nanjing University of Aeronautics and Astronautics. Moreover, significant keywords, trends and research directions have been extracted and analyzed. Additionally, the study highlights the regions where the theory holds substantial influence.

The study is subject to certain limitations stemming from factors such as the language employed in the chosen literature, the papers included within the Web of Science (WoS) database, the designation of works categorized as “articles” in the database, the specific selection of keywords and keyword combinations, and the meticulous manual process employed for paper selection. While the manual selection process itself is not inherently limiting, it demands a greater investment of time and meticulous attention, contributing to the overall limitations of the study.

The significance of the study extends not only to scholars and practitioners but also to readers who observe the development of emerging scientific disciplines.

The analysis of trends revealed a growing emphasis on the application of GST in diverse domains, including supply chain management, manufacturing and economic development. Notably, the emergence of COVID-19 as a new research focal point among GST scholars is evident. The heightened interest in COVID-19 can be attributed to its global impact across various academic disciplines. However, it is improbable that this interest will persist in the long term, as the pandemic is gradually brought under control.

The paper provides a detailed historical account of Douglass C. North's early intellectual contributions and analytical developments in pursuing a Grand Theory for why some countries are rich and others poor.

The author approaches the discussion using a theoretical and historical reconstruction based on published and unpublished materials.

The systematic, continuous and profound attempt to answer the Smithian social coordination problem shaped North's journey from being a young serious Marxist to becoming one of the founders of New Institutional Economics. In the process, he was converted in the early 1950s into a rigid neoclassical economist, being one of the leaders in promoting New Economic History. The success of the cliometric revolution exposed the frailties of the movement itself, namely, the limitations of neoclassical economic theory to explain economic growth and social change. Incorporating transaction costs, the institutional framework in which property rights and contracts are measured, defined and enforced assumes a prominent role in explaining economic performance.

In the early 1970s, North adopted a naive theory of institutions and property rights still grounded in neoclassical assumptions. Institutional and organizational analysis is modeled as a social maximizing efficient equilibrium outcome. However, the increasing tension between the neoclassical theoretical apparatus and its failure to account for contrasting political and institutional structures, diverging economic paths and social change propelled the modification of its assumptions and progressive conceptual innovation. In the later 1970s and early 1980s, North abandoned the efficiency view and gradually became more critical of the objective rationality postulate. In this intellectual movement, North's avant-garde research program contributed significantly to the creation of New Institutional Economics.

Differences in annual publication counts may reflect the dynamic of scientific progress. Declining annual numbers of publications may be interpreted as missing progress in field-specific knowledge.

In this paper, we present empirical results on dynamics of progress in economic fields (defined by Journal of Economic Literature (JEL), codes) based on a methodological approach introduced by Bornmann and Haunschild (2022). We focused on publications that have been published between 2012 and 2021 and identified those fields in economics with the highest dynamics (largest rates of change in paper counts).

We found that the field with the largest paper output across the years is “Economic Development”. The results reveal that the field-specific rates of changes are mostly similar. However, the two fields “Production and Organizations” and “Health” show point estimators which are clearly higher than the estimators for the other fields. We investigated the publications in “Production and Organizations” and “Health” in more detail.

Understanding how a discipline evolves over time is interesting both from a historical and a recent perspective. This study presents results on the dynamics in economic fields using a new methodological approach.