Search results

This study aims to analyse the efficiency effects of institutional distance on Chinese outward foreign direct investment (FDI) in Africa.

The study utilised the true fixed-effect stochastic frontier analysis (SFA) model. Data from 2003 to 2016 (14 years) were acquired from 42 targeted African countries, which are included in the analysis.

The results reveal that FDI flow efficiency can be maximised with a high institutional distance between China and African countries. Contrariwise, comparable institutional distance, measured by the rule of law, regulatory quality and government effectiveness between the host and home countries, reflected a significant positive impact for Chinese outward foreign direct investment (OFDIs), indicating Chinese MNEs can invest directly in a country with comparable institutional characteristics.

There have been limited exceptional studies that assessed the effect of institutional distance between emerging countries. However, none of these studies investigated the effect of institutional distance between China and Africa at a national level. Using the advantage of the SFA model, this study assesses the efficiency effects of institutional distance between the host and home country.

The paper evaluates trends shaping the post-pandemic reality. The framework adopted is a case study of the V4 region (Poland, the Czech Republic, Slovakia and Hungary) that illustrates broader trends, their direction of change and their influence on the entire region. This paper aims to identify key trends and analyse how they can facilitate or hinder sustainable development.

The paper is based on a multidisciplinary literature review and an online real-time Delphi study carried out across four European countries.

The results indicate that the influence of negative trends on sustainability is much stronger than that of positive ones. Concerning the trends’ driving factors, the blockers of negative trends have a much higher influence on sustainability than the blockers of positive ones. The study shows that the most significant trends affecting sustainability are distributed throughout various fields of human activity, including geopolitics, social issues, education, the environment, technology and health.

The findings presented below can be used primarily by decision makers from the V4 region, who are responsible for crafting strategies regarding post-COVID recovery. The study illustrates trends that V4 countries and other European Union member states might be facing in the future and analyses how they relate to sustainability. The conclusions indicate that the most effective path to the desired level of sustainability is one that incorporates policies built around the blockers of negative trends.

The importance of this study lies in its focus on countries that had previously received little attention in scientific analyses. The paper shows their possible developmental pathways and sheds light on the framework of integrated foresight and its applications in sustainability-related areas.

The institutional context in which family firms operate influences their behaviour and performance, yet literature reviews seldom analyse family firms on a regional basis. To fill this gap, this review aims to present research on family entrepreneurship in the transition economies of the Visegrád countries (V4). In this particular group of European economies, the current formal institutions have largely evolved along Western European lines. However, the transformation of informal institutions appears to be still in its infancy.

In order to identify the most representative authors, the methodologies used, the main research topics and to establish a future research agenda, the authors selected, through a systematic process, 112 papers from the Web of Science up to the year 2022. The authors performed a bibliographic analysis using clustering algorithms, complemented by a traditional literature review.

The performance of family firms in transition economies has been the subject of very little research. The results allowed the authors to identify four main areas of research: governance, innovation, sustainability, competitive advantage and considering the influence of the region's characteristics on family business behaviour.

Studies from transition economies can contribute to a broader understanding of family firms in terms of the impact of the institutional environment (especially the influence of sociological changes and specific historical experiences of family members) on their long-term planning, socioemotional wealth (SEW) protection and ethics. In light of recent events, research from the region may also contribute to the understanding of how and to what extent “familiness” influences crisis management or socially responsible behaviour in family firms.

Based on the general formula, which depends on the length and difficulty of the test, the number of respondents and the number of ability levels, this study aims to provide a closed formula for the adaptive tests with medium difficulty (probability of solution is p = 1/2) to determine the accuracy of the parameters for each item and in the case of calibrated items, determine the required test length given number of respondents.

Empirical results have been obtained on computerized or multistage adaptive implementation. Simulation studies and classroom/experimental results show that adaptive tests can measure test subjects’ ability to the same quality over half the test length compared to linear versions. Due to the complexity of the problem, the authors discuss a closed mathematical formula: the relationship between the length of the tests, the difficulty of solving the items, the number of respondents and the levels of ability.

The authors present a closed formula that provides a lower bound for the minimum test length in the case of adaptive tests. The authors also present example calculations using the formula, based on the assessment framework of some student assessments to show the similarity between the theoretical calculations and the empirical results.

With this formula, we can form a connection between theoretical and simulation results.

The present study is about generating metadata to enhance thematic transparency and facilitate research on interview collections at the Research Documentation Centre, Centre for Social Sciences (TK KDK) in Budapest. It explores the use of artificial intelligence (AI) in producing, managing and processing social science data and its potential to generate useful metadata to describe the contents of such archives on a large scale.

The authors combined manual and automated/semi-automated methods of metadata development and curation. The authors developed a suitable domain-oriented taxonomy to classify a large text corpus of semi-structured interviews. To this end, the authors adapted the European Language Social Science Thesaurus (ELSST) to produce a concise, hierarchical structure of topics relevant in social sciences. The authors identified and tested the most promising natural language processing (NLP) tools supporting the Hungarian language. The results of manual and machine coding will be presented in a user interface.

The study describes how an international social scientific taxonomy can be adapted to a specific local setting and tailored to be used by automated NLP tools. The authors show the potential and limitations of existing and new NLP methods for thematic assignment. The current possibilities of multi-label classification in social scientific metadata assignment are discussed, i.e. the problem of automated selection of relevant labels from a large pool.

Interview materials have not yet been used for building manually annotated training datasets for automated indexing of scientifically relevant topics in a data repository. Comparing various automated-indexing methods, this study shows a possible implementation of a researcher tool supporting custom visualizations and the faceted search of interview collections.

Bibliotherapy, a therapeutic approach that uses books and reading materials to promote psychological well-being and personal growth, has become more prevalent in recent years. This scientometric study aims to provide a comprehensive view of the bibliotherapy research landscape by highlighting its evolution, trends, and noteworthy contributions using Biblioshiny and VOSviewer.

The academic literature on bibliotherapy is evaluated in-depth in this study utilizing scientometric techniques, including citation and co-citation analysis. A thorough search of the Scopus database revealed 1,703 papers between 1942 and 2023 that dealt with bibliotherapy. For data analysis, the renowned applications Biblioshiny and VOSViewer are employed.

The study reveals that the output of publications has fluctuated, reflecting scholarly interest in this discipline. The distribution of research across various countries, organizations and academic subjects is investigated further to highlight the diverse and global extent of bibliotherapy research. By analyzing co-citation networks and locating pertinent publications and authors, this scientometric method analyzes the intellectual structure of bibliotherapy research.

Bibliometric analysis enriches the theoretical understanding of bibliotherapy by unveiling the networks, influential works and existing gaps in the literature, thus guiding a more informed and collaborative approach to future research and practice in the domain.

Employing bibliometric analysis in bibliotherapy can refine practices and training programs, ensuring they are evidence-based and practical, enhancing the quality of therapeutic services provided to individuals.

It is a valuable resource for academics, practitioners and policymakers interested in the field since it offers a thorough and current assessment of the bibliotherapy research landscape. The findings of this study have the potential to steer future research, guide the development of bibliotherapeutic interventions supported by evidence and enhance the use of bibliotherapy as a therapeutic modality.

The current study examined Israeli researchers from various disciplines concerning their perceptions, attitudes and awareness of scientific publications in open access (OA) journals and repositories.

A survey instrument was developed and distributed to 202 Israeli researchers from universities, colleges and research institutions. The study used the united theory of acceptance and use of technology (UTAUT) model as a tool for mapping the factors known to influence researchers to publish in OA journals and repositories.

The empirical model confirmed the mediating effect of the association between researchers’ perceptions and the actual publishing in OA, through their behavioral intentions (BI). Furthermore, the BI are mediated by researchers’ self-decision to publish in OA. More specifically, a researcher's publication level in OA depended not only on the positive attitudes (Atti), performance expectancy (PE) and social influence (SI) mediated by BI, but also on conditions that support researchers who publish in OA, and disciplinary affiliation to science, technology, engineering and math (STEM) which lead the researcher to voluntarily publish in both green and gold OA.

This study contributed to the cumulative understanding of OA publishing by formulating and validating an empirical research model of acceptance and use.

The implications of the findings for scientific publication theory and practices are discussed.

The study suggests an effective framework to understand the researcher's final decision to publish in OA. This study's results are an essential step towards the cumulative understanding of OA publicity adoption and use by researchers as a global issue in general and in Israeli academic institutions in particular.

Food supply chains (FSCs) are fast becoming more and more complex. Sustainability is a necessary strategy in FSCs to meet the environmental, economic and societal requirements. Industry 4.0 (I4.0) applications for a circular economy (CE) will play a significant role in sustainable food supply chains (SFSCs). I4.0 applications can be used in for traceability, tracking, inspection and quality monitoring, environmental monitoring, precision agriculture, farm input optimization, process automation, etc. to improve circularity and sustainability of FSCs. However, the factors integrating I4.0 and CE adoption in SFSC are not yet very well understood. Furthermore, despite such high potential I4.0 adoption is also met with several barriers. The present study identifies and analyzes twelve barriers for the adoption of I4.0 in SFSC from an CE context.

A cause-effect analysis and prominence ranking of the barriers are done using Rough-DEMATEL technique. DEMATEL is a widely used technique that is applied for a structured analysis of a complex problems. The rough variant of DEMATEL helps include the uncertainty and vagueness of decision maker related to the I4.0 technologies.

“Technological immaturity,” “High investment,” “Lack of awareness and customer acceptance” and “technological limitations and lack of eco-innovation” are identified as the most prominent barriers for adoption of I4.0 in SFSC.

Successful mitigation of these barriers will improve the sustainability of FSCs through accelerated adoption of I4.0 solutions. The findings of the study will help managers, practitioners and planners to understand and successfully mitigate these barriers.

The purpose of the paper is to determine the importance of trade logistics in export intensification and competitiveness on the level of individual companies. Within the framework of logistics performance, the influences of customs efficiency and physical trade infrastructure quality were tested on export while the contribution to improving competitiveness was analyzed through logistics services and the Logistics 4.0 component. In addition, the influence of competitiveness on companies’ exports was examined.

The research was conducted based on a survey intended for the management of export-oriented companies which was distributed through the system of the Chamber of Commerce and Industry of Serbia. A total of 298 responses were collected and provided the basis for the application of structural equation modeling (SEM) approach.

The physical trade infrastructure was found to be a significant factor in stimulating exports, while the quality of logistics services has a statistically significant impact on the level of competitiveness. The results also indicate that improving the competitiveness of companies gives positive results in stimulating their exports.

Studies that analyze the impact of trade logistics using primary data from surveys are rare. In this paper, for the first time, the SEM methodology was applied in the assessment of logistics performance effects on export and competitiveness of individual companies. Also, the impact of the logistics 4.0 concept on selected companies’ performance was empirically tested for the first time.

This study aimed to evaluate the potential of artificial intelligence (AI) as a tool for knowledge synthesis, the production of written content and the delivery of coaching conversations.

The research employed the use of experts to evaluate the outputs from ChatGPT's AI tool in blind tests to review the accuracy and value of outcomes for written content and for coaching conversations.

The results from these tasks indicate that there is a significant gap between comparative search tools such as Google Scholar, specialist online discovery tools (EBSCO and PsycNet) and GPT-4's performance. GPT-4 lacks the accuracy and detail which can be found through other tools, although the material produced has strong face validity. It argues organisations, academic institutions and training providers should put in place policies regarding the use of such tools, and professional bodies should amend ethical codes of practice to reduce the risks of false claims being used in published work.

This is the first research paper to evaluate the current potential of generative AI tools for research, knowledge curation and coaching conversations.