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The paper investigates if the process that led to the birth of the Euro Area had a significant impact in homogenizing the capital structure decisions of European firms since the first introduction of the common currency.

A large sample of firms was constructed, and a Tobit-censored regression model was utilized to investigate the determinants of firms' observed capital structures. The Black–Scholes–Merton model was used to infer market values of assets, as well as the volatility of those values, from the observed market values of equity and the corresponding volatility. The existing differences in national tax rules were considered for estimating firm-specific marginal tax rates.

It was found that, despite the currency union and the institutional harmonization process, certain factors still play a different role. In particular, the impact of profitability is consistent with the pecking order view in some countries, and with the trade-off theory in others. Assets risk, measured as the annualized volatility of the market enterprise value, is the best predictor of observed leverage ratios. The sector of activity is significant in determining leverage decisions even when assets' risk is taken into account. Despite the monetary union and the increased financial and institutional integration in the Euro Area, the country of origin still plays a significant role in capital structure decisions, suggesting that other country-level factors may affect firms' financing behaviour.

The paper indicates that, despite the long harmonization process of institutions, regulations and public budget required to join the Euro, firms' financing decisions are still affected by country-specific factors once the common currency is introduced. Therefore, new entrant countries in the Euro area should not expect their companies to immediately conform with those located in other countries within the common currency area.

This article investigated the impact of the currency change from national currencies to the Euro on the determinants of capital structure choices. It was shown that, despite the long harmonization process that led to the birth of the Euro Area, national factors still affect firms' financing decisions. This provides guidance for policymakers in countries that are planning to join the Euro about the impact this will have on firms' financing decisions in the entrant country.

The purpose of this research is to systematically scrutinize the influence of macroeconomic determinants on trade openness, through the lens of various trade theories, with a particular focus on the economies of the GIPSI countries – Greece, Ireland, Portugal, Spain and Italy.

This study investigates the macroeconomic factors influencing trade openness in the GIPSI economies from 1995 to 2020. Methods include stepwise regression (SR) for model selection, Pedroni panel cointegration test and panel regression results. The analysis uses advanced panel regressions, including FMOLS, Panel OLS and FEM. The long-term dynamics were tested using Pedroni cointegration, while Granger causality testing was used to examine the causal direction between the trade openness ratio and trade determinant.

The results show both long-term and short-term relationships between trade openness and (1) foreign direct investment, (2) labor force participation rate, (3) trade reserves and (4) trade balance. The researchers also detected unidirectional and bidirectional causality relationships between trade openness and these four factors. The study also revealed that trade reserves (TR) emerge as the most influential determinant of trade openness, and per capita income does not exhibit economic significance concerning the trade openness of GIPSI economies.

This research is conducted within the context of the GIPSI nations (Greece, Ireland, Portugal, Spain and Italy). As such, the outcomes may not be universally applicable to other economic systems due to the distinct institutional settings and governance structures across different economic groups. Future investigations may explore the relationship between trade openness and its determinants by incorporating different variables.

To the best of the authors' knowledge, this is the first study investigating the theory that suggested trade drivers drive the trade openness of GIPSI countries context. By focusing on GIPSI countries, the study offers a unique perspective on the dynamics of trade openness in economies that have experienced financial crises and stringent austerity measures.

Gamification is an emerging technique of applying game elements to difficult and tedious learning activities to make them fun and exciting. This study aims to review the scientific landscape of the library’s readiness to adopt gamification with context to application in teaching and learning purposes based on computational tools. The present research also aims to study the growth of literature on gamification, to identify the most contributing authors, countries, affiliations and journals and collaboration status with different geographical settings. The study will also identify the most influential paper on the area with the highest citation and Altmetric Attention Score (AAS) as well as analyzing the keywords for locating the research trend in the subject area.

The study has adopted Scientometric and Altmetric approach by considering the research outputs of a decade (2013–2022) from Scopus database. First, the required data has been searched using appropriate keywords forming the search strategy by running title–abstract–keywords considering the limitation in the system. The exported data is systematically visualized for performing science mapping like the collaboration of authors, countries, organizations and co-occurrence of keywords using VOSviewer. For finding the Altmetrics score and Mendeley readership of the influential research works, the system Dimension.ai is further used.

The study found 928 records indicating an exponential growth over the years with total 2,750 authors. Samuel Kai Wah Chu from the University of Hong Kong, China, is the most contributed author. Spain and the USA are highly productive countries, but there needs to be a strong collaboration pattern among authors. It is found that gamification is widely applied in education discipline than any other. Some of the libraries have already implemented gamification tools for learning purposes in their services. The research on gamification still lacks social media attention and needs to be promoted more through various social media platforms for greater visibility.

The study explores the global scientific literature to identify the library’s awareness of implementing gamification tools in their services for teaching and learning purposes. As per the author’s knowledge, no such study has been conducted until date with such aims and objectives through the application of both Scientometrics and Altmetrics approaches.

The aim of this study is to measure portfolio diversification benefits of the Turkey-based equity investors into top trading partner countries. Portfolio diversification benefits are analyzed from the viewpoint of two types of investors in Turkey: conventional equities investors and Islamic equity investors.

In order to evaluate the time-varying correlations of the trading partner country's stock index returns with the Turkish stock index returns, the multivariate-generalized autoregressive conditional heteroskedasticity–dynamic conditional correlation (GARCH-DCC) is applied based on daily data covering 13 years' period between January 22, 2008 and January 22, 2021.

The results revealed that the US stock indices provide the most diversified benefit for both conventional and Islamic Turkey-based equity investors. In general, Islamic indices exhibit relatively lower correlation with trading partners than conventional indices. Turkey and Russia are recorded as the most volatile indices.

The diversification potential in trading partners for Turkey-based Islamic equity investors has not been studied yet. This study is to fill in this gap in the literature and to give fruitful insights to both conventional and Islamic investors.

The purpose is to assess the usefulness of creative vouchers, a specific kind of technology and innovation vouchers (small grants usually given to SMEs to acquire external knowledge) where the knowledge suppliers are creative firms such as design agencies.

A multiple case analysis of four EU-funded pilot voucher schemes was carried out through project reports and semi-structured interviews with relevant stakeholders.

The authors show that creative vouchers are effective policy instruments despite the limited amount of money involved because they trigger new innovation trajectories often in a serendipitous way. The authors also show that the quality of projects and satisfaction of the beneficiaries increase when both proposals and suppliers are screened.

The authors’ conclusions are based on four pilot projects in a specific region of the world (Western Europe). Though two of them were extended to a much bigger scale, their generalizability may be limited. Moreover, the limited number of cases does not permit an analytical evaluation of all the voucher schemes mechanisms.

The findings of this paper can be very useful to policymakers designing voucher schemes and to the companies involved, whether they are providers or beneficiaries. In particular, the voucher allocation mechanisms may have a strong impact on the success of the program.

The innovation spurred by the collaboration with creative firms is generally neither energy-intensive nor capital intensive, but brain intensive, and this is the best way to leverage on the talent of local creative and make companies create value based on immaterial resources.

To the authors’ knowledge, this is the first study of creative vouchers after Bakhsi et al., 2015, and the only one involving several schemes in different countries. It shows the innovation potential of such a little known policy instrument for SMEs. Moreover, it provides insight on how to design a voucher scheme in order to improve its effectiveness.

The scope of this research is to investigate performing loan efficiency for fifty European banks during the period 2008–2017.

The study is structured as a two-stage analysis of performing loan efficiency and its driving factors. In the first stage of the proposed methodology “Data Envelopment Analysis” is used to estimate performing loan efficiency for each bank included in the sample. A bootstrap statistical procedure enhances the findings. In the second stage, the impact of other factors on the efficiency scores of loan performance using tobit regression is investigated.

The results are consistent with the findings of the individual banks' financial analyses. According to the findings of DEA implementation, the evaluated banks may enhance their cost efficiency by 39% on average. In addition, the results indicate that loan efficiency performance improves after 2015, coinciding with the business cycle's upward trend. The tobit regression is employed in the second stage to examine the influence of bank-related and macroeconomic factors on banks' loan management efficiency. According to the findings of the tobit regression, three factors, namely the capital adequacy ratio, GDP per capita and managerial inefficiency, have a substantial influence on performing loan efficiency.

This research investigates the effectiveness of European economic policy in protecting the European banking system from the consequences of the sovereign debt crisis in several euro area members. The results highlight the distance of the Eurozone from the level of the ‘optimal currency area’.

Recently, autonomous vehicles (AV) acceptance has been studied intensively. This paper aims to map and analyze the bibliometric characteristics of AV acceptance literature. Furthermore, this research aims to identify research gaps and propose future research opportunities.

The bibliometric analysis was performed. Scopus database was used as the source of the literature. This study selected and analyzed 297 AV acceptance papers. The performance and science mapping analysis were performed.

The developed countries tended to dominate the topic. The publication outlet tended to be in transportation or technology journals. There were four research themes in existing literature. Technology acceptance model (TAM) and UTAUT2 tended to be used for explaining AV acceptance. AV acceptance studies tended to use two types of psychological concepts for understanding AV acceptance, namely risk related concepts and functional utilitarian benefit related concepts. In the context of research design, quantitative approach tended to be used. Self-driving feature was the most exploited feature of AV in the existing literature. Three research gaps were mapped and future research opportunities were proposed.

This paper provided a comprehensive information that allowed scientists to develop future research on AV acceptance.

There is lack of paper that discussed the bibliometric characteristics of AV acceptance literature. This paper fulfilled the gap.

Investor sentiment (optimism or pessimism) may influence investors to follow others (herding) while taking their investment decisions. Herding may result in bubbles and crashes in the financial markets. The purpose of the study is to examine the presence of herding and the effects of investor sentiment on herding in China and Pakistan.

The investor sentiment is captured by five variables (trading volume, advance/decline ratio, weighted price-to-earnings ratio, relative strength index and interest rates) and a sentiment index developed through principal component analysis (PCA). The study uses daily prices of 2,184 firms from China and 568 firms from Pakistan for the period 2005 to 2018.

The study finds that herding prevails in China while reverse herding prevails in Pakistan. Interestingly, as investors become optimistic, herding in China and reverse herding in Pakistan decrease. This indicates that herding and reverse herding are greater during pessimistic periods. Further, the increase in herding in one market reduces herding in the other market. Moreover, optimistic sentiment in the Chinese market increases herding in the Pakistani market but the reverse is not true.

Considering the greater global financial liberalization, and better opportunities for emotion sharing, this study has important implications for regulators and investors. Market participants need to understand the prevalent irrational behavior before trading in the markets.

Since individual proxies may depict different picture of the relationship between sentiment and herding therefore the study also develops a sentiment index through PCA and incorporates this index in the analysis. Further, this study examines cross-country effects of herding and investor sentiment.

This paper aims to examine the dynamic impacts of the COVID-19 pandemic and government policy on real house price indices in five emerging economies, namely, Brazil, China, Thailand, Turkey and South Africa.

The authors use the local projection method with a panel data set of these countries spanning from January 2020 to July 2021.

The number of COVID-19 confirmed positive cases raised housing prices, whereas government containment measures reduced them. Both conventional and unconventional monetary policy implemented by central banks to cope with the COVID-19 helped increase housing prices. These effects were strengthened by the US monetary policy via globalized financial markets.

First, while previous researches typically concentrated on developed countries, the authors investigate emerging economies where proportionally more people were badly affected by the pandemic. Second, a panel data set of five emerging economies enabled the authors to examine the dynamic effects of the COVID-19 crisis on housing prices. Third, to the best of the authors’ knowledge, this is the first study evaluating the influences of easing monetary policy on housing prices in emerging economies during the pandemic.

The discourse on global value chains (GVC) is undergoing a transformation in terms of its conceptualisation, theorisation and pragmatic applications. Today, the production systems have become more complex as global economic order continues to witness marked geo-economic manoeuvring. Thus, the direction of discourse on GVC ought to move from mere theoretical propositions toward becoming more evidence based. There have been recent studies that have used the governance and upgrading propositions by Gary Gereffi and others to seek quantitative evidence. This study aims to decipher the quantitative discourse on GVC and to set the emerging and future research agenda.

Through a systematic literature review, the authors first analyse the quantitative studies on GVC carried out during the last two decades. The authors then outline a future research agenda and examine a few relevant modelling techniques that could potentially be used to solicit newer evidence in GVC research.

The authors categorise the quantitative discourse on GVC into three crucial themes, namely, GVC framework, GVC participation and position, environmental aspects and regionalisation in GVC. The most commonly used quantitative techniques are gravity model, panel data estimation, structural decomposition analysis and computable general equilibrium modelling.

This paper contributes to the GVC discourse in two ways. Firstly, the authors argue that the theoretical frameworks within the GVC discourse should be complemented by evidence-based quantitative studies. Secondly, the authors suggest potential modelling techniques that can be used on the emerging and future research agenda.