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Empirical evidence of the relationship between regulatory efficiency, market openness, and bank productivity in economies at different income levels: Evidence from selected Asian and MENA countries
No full textResearch background: Economic freedom plays a pivotal role in ensuring the progressive productivity of banks. It fosters a favorable economic climate and acts as a catalyst for the generation of innovative ideas. In addition, economic freedom allows new domestic and foreign entrants in the banking sector which leads to increased competition as well as wider range of product offerings and thus potentially affect bank efficiency.
Purpose of the article: This study aims to identify the effects of regulatory efficiency and market openness in terms of economic freedom on the bank’s productivity at three income levels: lower-middle, upper-middle, and high-income economies.
Methods: A sample of 15 countries are included in the study from differing income levels. The study uses the data envelopment analysis (DEA) based Malmquist productivity index (MPI) approach to measure banks’ productivity. This non-parametric approach measures the relative efficiency of banks by considering the production change while taking into account technical efficiency change and technological change in order to capture a comprehensive view over time. Then, regression analysis was performed utilizing the ordinary least squares (OLS) approach, fixed effect (FE), and random effect (RE) panel multiple regression estimation methods are utilized to measure economic freedoms and other determinants’ effect on banks’ productivity change over time.
Findings & value added: The results show that banks in high-income economies are more productive and have higher growth rates than those in upper- and lower-income economies. Furthermore, starting, obtaining permits, and closing businesses under business freedom have a detrimental effect on banks’ output, whereas the effects of labor freedom on employing, managing, and supervising staff members have a substantial favorable impact on banks’ productivity. Moreover, financial freedom and investment freedom under the market openness dimension negatively influence banks’ productivity. Government intervention is required to introduce regulations that allow foreign countries to provide labor at lower wages, introduce tax allowances, and control inflation rates. Thus, the empirical results of this study will benefit regulators and policymakers in developing a system and plan to increase banks’ productivity based on indicators of business, labor, financial, and investment freedom
Purchase intentions in a chatbot environment: An examination of the effects of customer experience
No full textResearch background: Chatbots represent valuable technological tools that allow companies to improve customer experiences, meet their expectations in real time, and provide them with personalized assistance. They have contributed to the transformation of conventional customer service models into online solutions, offering accessibility and efficiency through their integration across various digital platforms. Nevertheless, the existing literature is limited in terms of exploring the potential of chatbots in business communication and studying their impact on the customer\u27s response.
Purpose of the article: The main objective of this study is to examine how consumers perceive chatbots as customer service devices. In particular, the paper aims to analyze the influence of the dimensions of “Information”, “Entertainment”, “Media Appeal”, “Social Presence” and “Risk for Privacy” on the “Customer Experience” and the latter on the “Purchase Intention”, under the consideration of the Uses and Gratifications Theory. Moderations due to Chatbot Usage Frequency for some of the relationships proposed are also analyzed.
Methods: An empirical study was performed through a questionnaire to Spanish consumers. The statistical data analysis was conducted with R software through the lavaan package. To test the hypotheses from the conceptual model a structural equation modelling approach was adopted.
Findings & value added: The results obtained identify the main characteristics of chatbots that can support brands to effectively develop their virtual assistants in order to manage their relational communication strategies and enhance their value proposal through the online customer journey. Findings demonstrate the contribution that chatbot dimensions make to the online consumer experience and its impact on the purchase intention, with the consideration of the moderating effect exercised by the user\u27s level of experience (novice vs. experienced) with the use of chatbots. Regarding managerial implications, this research offers recommendations for e-commerce professionals to manage chatbots more effectively. The “Entertainment” and “Social Presence” dimensions can be operationalized at a visual (e.g., appearance of the avatar and text box, use of designs aligned with the website) and textual level (e.g., style and tone of voice, use of expressions typical of the target audience) to generate a feeling of proximity with the chatbot and facilitate its adoption. “Media Appeal” requires that the chatbot be easy to use, effective, and accessible, to facilitate its usability. Finally, mitigation of “Privacy Risk” concerns should be achieved by presenting an appropriate privacy policy and requesting permission for the use of customers’ private information
The effect of collateral-based monetary policy on green finance: Evidence from China
No full textResearch background: Green finance is crucial to accelerating China’s green transition, and its growth depends largely on the corresponding monetary policy. To increase financial institutions’ support for the green economy, China’s central bank has recognized green bonds as eligible collateral for monetary policy tools since June 1, 2018.
Purpose of the article: In this context, we investigate the effect of collateral-based monetary policy (CBMP) on green finance (GF) in China by utilizing a quasi-natural experiment approach.
Methods: Using the Propensity Score Matching-Difference in Difference (PSM-DID) method and daily bond trading data, we investigated the impact of CBMP on the cost and availability of green finance. In further analysis, we employed bond issuance data and listed company data to examine the spillover effects of CBMP and its influence on the real economy.
Findings & value added: Our results suggest that CBMP, in the secondary market, actively stimulated the growth of GF by reducing green bond spreads and expanding their financing scale. Furthermore, this beneficial outcome is particularly obvious for low-grade green bonds, bonds issued by state-owned enterprises (SOEs), and in regions with stringent environmental regulations and high government green attention. Particularly, we have also found that there exists a spillover effect across markets, i.e., endowing collateral eligibility to green bonds in the secondary market, can reduce bonds’ spreads and increase bonds’ financing scale in the primary market. Finally, we have found that CBMP effectively incentivizes corporate green behavior rather than “greenwashing”. Our findings suggest that China should further optimize CBMP, focus more on non-SOEs green finance difficulties, and strengthen local governments’ green attention and implementation capacity
Measuring efficiency of commercial banks and other deposit institutions: DEA-Malmquist approach
No full textResearch background: Commercial banks play a vital role in the global financial system and are critical components of it. Hence, the efficient performance of commercial banks could lead to more robust economic stability, enhanced financial resilience, and sustainable growth. The pandemic/post-pandemic period forces the expansion of digitalisation in the economy, including the banking sector. The Malmquist Index helps to assess productivity change. This research fills the gap in measuring the dynamics of efficiency and productivity change during the pandemic/post-pandemic period in a small open economy.
Purpose of the article: The current study aims to assess and compare the dynamics of banking sector efficiency and productivity change in the pandemic/post-pandemic period.
Methods: Data Envelopment Analysis (DEA) was used in the current research in order to measure the efficiency of deposit institutions operating in Lithuania. The study employed the input-oriented Constant Returns to Scale (CRS) model in order to assess how efficiently the banks utilise the inputs to achieve the outputs. The calculations of the efficiency scores were complemented using the Malmquist Index, which evaluates the productivity change over time using Total Factor Productivity Change (TFPCH), Technical Efficiency Change (TECH), and Technological Change (TCCH).
Findings & value added: To the best of the authors’ knowledge, this is the first study to explore the banks’ efficiency and productivity change using DEA and MI for the Lithuanian banking sector. The research results have revealed varying efficiency among the Lithuanian commercial banks and other deposit institutions within the four investigated models. Depending on the model, some studied deposit institutions reached the highest scores, while others showed lower efficiency. However, the results of the Malmquist Index have showed overall productivity growth across all the models, underlining positive technological advancements despite challenges like the COVID-19 pandemic, i.e. the productivity change showed a positive dynamic over the analysed period. The present research provides valuable insights and contributes to efficiency-related knowledge, highlighting trends in productivity for strategic decision-making and policy formulation based on the case of deposit institutions operating in Lithuania. The results are valuable and could be practically implied by other EU banks operating in small open economies by adopting the practices of the banks that were considered efficient and showed positive productivity change. In other words, high-performing Lithuanian banks could be treated as a benchmark and set as a model for less efficient banks operating in other EU countries
Conventional and downside CAPM with higher-order moments: Evidence from emerging markets
No full textResearch background: Conventional CAPM is a well-known and tested theory on various capital markets. It was also repeatedly rejected as a model of capital pricing. This article proposes a different approach to both CAPM testing and the use of other risk measures. In addition, research is global, including emerging countries.
Purpose of the article: This paper investigates the standard CAPM, and this model is based on higher moments of the return distribution for the global emerging market. In addition, this paper aims to compare the conventional and downside CAPM versions using the beta coefficient and co-moments.
Methods: Contrary to the classical unconditional tests for the risk premium, conditional relationships are also estimated considering the market portfolio condition. Moreover, the studies considered conventional and downside approaches to risk measures. The cross-sectional regressions are based on the Fama-MacBeth (F-M) procedure and panel models.
Findings & value added: The findings contribute to the debate on whether beta coefficient and higher order co-moments in conventional and downside approaches can explain the cross-sectional emerging indices returns. The unconditional models using all measures do not significantly describe the cross-sectional volatility of returns. The cross-sectional regressions in up and down-market based on both the classic F-M procedure and panel models show that the beta and co-kurtosis risk premium is significant and depends on market conditions. The risk premium for co-skewness is not valid, and the direction of the relationships is opposite than expected. Research also demonstrates that the test results of CAPM relationships are not robust to the presence of outliers and shocks resulting from the Covid-19 pandemic in the context of risk-return space. Research provides strong support for the importance of downside risk in the context of standard CAPM and, above all, higher co-moments
Brain gain and country\u27s resilience: A dependency analysis exemplified by OECD countries
No full textResearch background: In the light of growing demand for highly skilled workers, driven by rapid changes in the labour market and business environment, the ability to attract the talented determines not only business performance, but also macroeconomic development prospects. This stimulates national governments to create positive conditions for the development and use of the human capital of migrants. One of the most important factors of brain gain can be country stability as a sign of a comfortable environment for the realisation of intellectual potential.
Purpose of the article: The study aims to investigate the links between the factors of country’s resilience and brain gain, including its partial indicators.
Methods: For a comprehensive assessment, migration indicators were used by categories of talented migrants: highly educated workers, foreign entrepreneurs, university students and start-up founders that we integrated into an integral index of intellectual migration. The data was collected for OECD countries for 2023. The authors used the methods of statistical and correlation-regression analysis, economic-mathematical modelling in the GRETL software environment.
Findings & value added: Research has shown that the components of country’s resilience (especially Economic resilience and Supply chain) have a positive effect on brain gain. Considering the partial indicators of brain gain, it is found that resilience in the country of destination has the greatest influence on the migration decisions of highly educated workers and foreign entrepreneurs, i.e. migrants with a positive experience of economic activity and entrepreneurial capital, which, in turn, strengthens the resilience and competitiveness of countries. Such conclusions are important for the improvement of brain gain management programs in terms of the development of the environment for the attraction and retention of talents
Constructing a quantification tool of the progress towards the green economy: Aggregation perspective
No full textResearch background: The transition towards a green economy, seen as a visible alternative to climate change and the need to ensure this opportunity to future generations, is a major challenge for all of the nations of the world, regardless of their status as developed, developing or emergent. In order to highlight the current state or progress towards a green economy, the reports and research of certain institutions, as well as of the academic medium, have focused on identifying the most relevant influencing factors and choosing the quantification methods capable to generate complete and useful interpretations.
Purpose of the article: The purpose of the paper is to construct an instrument that enables to measure the progress of countries in terms of the transition to green economy, where Romania is considered as a case study. In this respect, a composite index (green economy index — GEI) is being proposed, achieved by aggregating some indicators for measuring sustainable development. The method underlying the calculation of the value of the GEI aggregate index allows not only to determine the current state of greening of the economy, but also provides information on the contribution made by each of the three dimensions of sustainable development (economic, social and environmental), as well as by each indicator individually, to this progress.
Methods: Constructing the aggregated index was based on an additive aggregation of three partial indicators: the economic indicator, comprised of 8 individual indicators, the social indicator, comprised of 8 individual indicators, and the social indicator, comprised of 10 individual indicators. The collected data covers the interval of 2010–2021.
Findings & value added: Calculating the Green Economy Index — GEI value for each of the 12 years under analysis has permitted not only the identification of progress regarding the green transition, and the underlying of each indicator’s contribution to this evolution, but has also confirmed the results obtained by similar studies carried out by the GGGI or European Union. We consider, as a result of the selection of certain indicators considered relevant in the economic, social and environmental field, that the newly-formed aggregate index represents an effective tool that can be used to measure progress in terms of achieving the 2030 Agenda for Sustainable Development goals, by easily adapting to the particularities of other states or regions
Digital Innovation Hubs and portfolio of their services across European economies
No full textResearch background: Digital ecosystems in Europe are heterogenous organizations involving different economies, industries, and contexts. Among them, Digital Innovation Hubs (DIHs) are considered a policy-driven organization fostered by the European Commission to push companies’ digital transition through a wide portfolio of supporting services.
Purpose of the article: There are DIHs existing in all European economies, but literature needs more precise indications about their status and nature. The purpose is to study a distribution of DIHs and differences in portfolios of DIHs’ services across European economies. Therefore, the paper wants to deliver more precise data on effects on national and European policies. This is required to define their final role and scope in the complex dynamics of the digital transition, depending on regional context and heterogeneity of industries.
Methods: Data on 38 economies was collected from the S3 platform (on both existing and in preparation DIHs) and further verified by native speaking researchers using manual web scrapping of websites of DIHs identified from S3. To find potential similarities of digital ecosystems in different economies as emanated by the existence of DIHs, clusterization (Ward’s method and Euclidean distances) was applied according to the services offered. Economies were clustered according to the number of DIHs and the spread of DIHs intensity in different cities. The results were further analyzed according to the scope of the provided services.
Findings & value added: The applied clustering classified European economies in four different sets, according to the types of services offered by the DIHs. These sets are expression of the different digitalization statuses and strategies of the selected economies and, as such, the services a company can benefit from in a specific economy. Potential development-related reasons behind the data-driven clustering are then conjectured and reported, to guide companies and policy makers in their digitalization strategies
Concave and convex effects of ESG performance on corporate sustainable development: Evidence from China
No full textResearch background: Corporate sustainable development (CSD) is essential to a company\u27s success and survival. Environmental, social, and governance (ESG) are regarded as major factors in measuring the impact of CSD. Companies that perform well in terms of ESG can maintain a competitive advantage and achieve sustainable development. Poor management of ESG performance and involvement in controversial activity can harm a company\u27s credibility and reputation in the market, as well as negatively impact sustainable development.
Purpose of the article: Drawing on the stakeholder and signaling theories, this paper investigates the curvilinear nexus between ESG performance and CSD.
Methods: Empirical studies were conducted on a sample of 697 Chinese listed manufacturing firms that disclosed ESG information from 2010 to 2020, with a total of 5699 firm-year observations. Quantile regression analysis and the U-test were used to examine the curvilinear ESG-CSD relationship. This technique was supplemented by conducting instrumental variables tests and propensity score matching to address concerns relating to the potential existence of endogeneity problems.
Findings & value added: The results of the quantile regression estimation confirm the concave-convex (inverted U-shaped and U-shaped) ESG-CSD relationship via the U-test. The relationships between the environmental and social components and CSD follow an inverted U-shaped or half-inverted U-shaped pattern, while the relationship between the governance component and CSD exhibits a concave-convex pattern. A concave ESG-CSD nexus is evident in environmentally sensitive industries, whereas a half concave-convex ESG-CSD nexus is confirmed in non-environmentally sensitive industries. This study improves scholars’ understanding of ESG performance and provides a comprehensive perspective on the double-edged effects (positive and negative consequences) of ESG practices. The instrumentalization of ESG practices for management to seek personal gain has a negative impact on CSD, while ESG practices that add value for stakeholders have a positive impact. These findings provide empirical evidence for Chinese publicly listed manufacturing firms to effectively conduct ESG practices
Energy communities: Insights from scientific publications
No full textResearch background: Over the last ten years, a substantial amount of scholarly research has delved into energy communities (ECs) from diverse viewpoints. These ECs are extremely important in setting the pathway to a clean energy transition.
Purpose of the article: Our objective is to glean valuable insights from publications indexed in the Web of Science (WoS) database to deepen our comprehension of ECs and their academic discourse.
Methods: Data analytics, factorial analysis, and more complex natural language processing (NLP) techniques such as latent Dirichlet allocation (LDA) are implemented to extract valuable insights from over 1000 WoS publications relevant in the EC field. The primary contribution of this study lies in furnishing details regarding the key contributors to the EC scholarly landscape, including authors, their affiliations, universities, and countries of origin. Additionally, we aim to elucidate the prevalent keywords and thematic approaches employed in their research endeavors.
Findings & value added: Considering the extracted dataset, an annual growth rate of 21.15% has been recorded, highlighting the research community’s interest in the field of ECs. Furthermore, three topics are optimally obtained. Overall, a coherence score of 0.44 suggests that the LDA model performs adequately in terms of topic interpretation. Topic 1 relates to community-based energy initiatives. Topic 2, featuring terms like “grid,” “study” and “EU” alongside “energy” and “community,” suggests a focus on energy systems. Topic 3 includes terms such as “generation,” “analysis” and “consumption,” indicating a topic that is centered around the technical or analytical aspects of energy production and usage. This study underscores how the alignment between state laws and EU directives in supporting ECs can serve as a model for other regions. The findings suggest that similar policy frameworks could be effectively adapted to different national contexts, providing valuable insights for countries looking to enhance their renewable energy strategies