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This study aims to contribute to the understanding of Entrepreneurship and Resource-Based View (RBV) by investigating the research landscape of Innovation Determinants (ID). Through an extensive bibliometric analysis and knowledge mapping, we explore intellectual structures, emerging trends, research hotspots, and future prospects in the field from 1990 to December 2022. Additionally, we focus on identifying top research organizations, authors, collaboration patterns, and commonly used keywords to advance knowledge and awareness in this area.

A comprehensive retrieval strategy was employed to gather 2359 articles on ID from Web of Science, covering the period from 1990 to 2022. Utilizing CiteSpace as a visualization tool, we visually represent authors, institutions, and keywords. By examining knowledge maps using various indicators, we showcase the intellectual foundation and current research frontiers within the domain of ID.

Our findings reveal significant progress in academic research on ID over the past three decades, with a substantial number of 2359 published articles in the field. This signifies considerable advancement in exploring ID. The analysis of the co-authorship network presents a network of 406 authors represented as nodes and 112 collaborative interactions as links. The network's density indicates that only a minute 0.14% of the potential connections in the ID network have been established, highlighting the need for more cohesive and extensive global collaborations in this field.

This paper's originality lies in its temporal and dynamic examination of the past thirty years, utilizing CiteSpace for co-citation and co-occurrence network analysis. Additionally, the scientometric analysis reveals key co-occurring keywords, providing insights into the conceptual characteristics within the research field.

Small and medium-sized enterprises (SMEs) are currently showing an increasingly open innovation (OI) approach. Public policies supporting the adoption of OI by SMEs are becoming a priority for policymakers. Therefore, the aim of this article is to contribute to the literature by mapping scholars' policy recommendations for implementing OI among SMEs.

The authors conducted a systematic review of the literature (SRL) on the topic to achieve this purpose. A total of 99 academic articles were selected from the Web of Science and Scopus databases to suggest the main scholars' policy recommendations to implement OI among SMEs.

Results indicated that scholars' policy recommendations for OI adoption in SMEs can be organized into: research and development (R&D), networking, collaboration, knowledge and intellectual property rights (IPR), ecosystem, managerial capabilities, funding and incentives and sustainability policies.

Only relevant articles about this topic have been included due to the reliance on the interpretations of the authors. The analysis of the literature revealed that the authors did not always distinguish policies dedicated to SMEs and those dedicated to large companies. Moreover, policies are not matched according to each OI dimensions (e.g. inbound, outbound and coupled OI).

The article uses a systematic literature review method that combines qualitative and quantitative analyses. This method contributes to theoretical development of OI policies dedicated, in particular to SMEs. This paper also provides policymakers and researchers with insights on the scope of OI policies that could support economic growth.

The aim of the study is to examine the role of crowdfunding in entrepreneurial development with the help of a systematic review of the literature and bibliometric analysis.

The present research employed bibliometric analysis to study collected data from the database. Using proper keywords, data was retrieved from Scopus. With the scaler and analytical method of bibliometric analysis, the research attempts to answer the following questions, including prominent journals, authors, keywords and cluster analysis based on keyword occurrence. The mapping/networking chart is created using the VOSviewer software.

The result of the study suggests that it is an attractive and emerging phenomenon for academicians. The most papers were published in 2021, Small Business Economics and California Management Review are the most prolific journals, while Vismara S is the most significant author with 4 publications and 488 citations. Short JC, School of Management, Royal Holland and USA collaborate most. Cluster analysis of the study will help the future researcher to broaden the existing literature utilising the distinct topics.

This research aids entrepreneurs, academia, crowdfunding practitioners and policymakers in identifying application areas for crowdfunding. In conclusion, crowdfunding will enhance the entrepreneurial ecosystem.

This study elaborates the significance of crowdfunding in the development of entrepreneurship, using SLR and bibliometric analysis. The study findings identified crowdfunding's usage, applications and potential future research areas, as well as evaluated, reviewed and assessed their significance in entrepreneurial development. The theme-based cluster was determined based on the frequency of occurrence of the keywords.

This research mirrors a 360° probe into bibliometric review of various studies aimed to examine the relationship between financial inclusion and sustainable development (FI and SD). It also offers a conspectus of apex contributors, influential articles, key journals and potential avenues for further research in this crucial area of global progress.

The study is the abstract of a total 233 papers on the subject representing a period between 2012 and 2023 in the Scopus database in the domain. This investigation probes into publication trends, the most inexhaustible contributors by national journals, publications and authors. The study conducts keyword co-occurrence analysis and examines thematic evolution using Vosviewer and Biblioshiny.

The findings reveal four prominent clusters: (a) Financial growth with FI, (b) Economic Empowerment with Sustainable Goals, (c) Environmental Sustainability and (d) Microfinance and Digital Era. Furthermore, the study paves way for the future research agenda with the help of these research themes.

To the best of the authors’ knowledge, this paper is the first of its kind in deeply probing the literature on FI and SD from a bibliometric perspective. Hence the findings of this study is a powerful weapon for researchers and practitioners coupled with future research inquiries, offering valuable insights and establishing robust quantitative foundations for advancing knowledge in the realms of FI and SD.

This study aims to synthesize extant literature on the concept of reverse knowledge transfer (RKT) built up over the past two decades with the help of bibliometric analyssis and also to suggest promising new areas for research in this field.

The study adopts a literature review methodology combined with bibliometric and network analysis based on 117 papers identified from the Scopus database. In particular, this study has tried to identify and capture themes not previously fully captured or evaluated by other reviews on this topic.

The authors have identified research themes and research gaps in the area of RKT. Overall, the review shows the main outlets that have published papers on RKT and the theoretical background this research is built on. This study exhibits core themes in this area that have persisted and grown consistently such as the subsidiary’s role in RKT. In addition, the review highlights less researched themes such as role of boundary spanning in RKT, which open exciting avenues for new research opportunities.

This study finds that RKT research has experienced remarkable growth from a complete viewpoint in recent years. There was a surge in publications in the area from 2008 onwards, and many of its influential papers seemed to have been published between 2013 and 2018. Prominent themes in this body of research have been identified and potential for future studies has been explored.

To the best of the authors’ knowledge, this is the first study to map, synthesize and discuss the literature concerning RKT.

This study explores the concept of “workplace survivor syndrome” (WSS) using bibliometric analysis and literature review, thereby identifying the avenues for future research in business management.

The study adopted a methodological combination of bibliometric analysis and literature review. The methodological order is as follows: using the Scopus database and identifying 118 articles from ABDC listed journals, performance analysis by VOS viewer (citation analysis), science mapping analysis by Biblioshiny (visualisation and graphical presentation), and finally, the content analysis of the best 40 articles with a minimum of 50 citations and without any year restriction.

The bibliometric analysis reveals the most influential authors, articles, journals, countries, publication trends, impactful articles, and impactful authors of workplace survivor syndrome research, along with popular keywords used in this area. The content analysis identified three themes: emotional, cognitive, and behavioural syndrome. The content analysis reported the central mechanism adopted in 40 articles, including theories, methodologies, variables, sample size, etc. Additionally, the study explored the positive reviews on WSS.

The study considered only the articles from the ABDC journal quality list for the review.

The article is persuasively the first research to provide the intellectual structure and comprehensive bibliometric analysis of workplace survivor syndrome.

Text classification is a widely accepted and adopted technique in organizations to mine and analyze unstructured and semi-structured data. With advancement of technological computing, deep learning has become more popular among academicians and professionals to perform mining and analytical operations. In this work, the authors study the research carried out in field of text classification using deep learning techniques to identify gaps and opportunities for doing research.

The authors adopted bibliometric-based approach in conjunction with visualization techniques to uncover new insights and findings. The authors collected data of two decades from Scopus global database to perform this study. The authors discuss business applications of deep learning techniques for text classification.

The study provides overview of various publication sources in field of text classification and deep learning together. The study also presents list of prominent authors and their countries working in this field. The authors also presented list of most cited articles based on citations and country of research. Various visualization techniques such as word cloud, network diagram and thematic map were used to identify collaboration network.

The study performed in this paper helped to understand research gaps that is original contribution to body of literature. To best of the authors' knowledge, in-depth study in the field of text classification and deep learning has not been performed in detail. The study provides high value to scholars and professionals by providing them opportunities of research in this area.

This study aims to provide an overview, the state-of-the-art “research fronts”, the emerging themes of investigation and a research agenda of crisis communication for destinations’ image.

This research is conducted with a bibliographic coupling study, complemented with an H-Classic classification and a thematic analysis of the articles included in the four clusters provided by the bibliometric methodology (papers dating from 2017 to 2021, both years included).

Based on the bibliometric analysis, four thematic clusters were identified. Two of these clusters supply the “research fronts”, the most current themes in a scientific field: Cluster 1 addresses communication related to tourists’ safety, and cluster 2 enhances the role of stakeholders’ collaboration to create destinations resilience in crisis communication. The other two clusters highlight emerging themes for future investigation: Cluster 3 focuses on recovery marketing communication strategies for a post-crisis era, and cluster 4 analyses how crisis communication strategies contribute to reduce tourists’ risk perception and boosting travel intention. Finally, a future research agenda is proposed, based on the emerging themes from this study.

To the best of the authors’ knowledge, this is the first bibliometric study to analyse crisis communication for destinations’ image (pre-crisis, crisis and post-crisis). This study, which covers the most recent academic literature in this field, provides insights of communication strategies from recent crises and disasters within the “research fronts”. Besides, a research agenda useful for future scholar investigation is proposed with its emerging themes. These rising topics and learnings from past events could be used by destination marketing organisations in crisis communication for destination image recovery in the current post-pandemic scenario or in upcoming crises or disasters.

本研究提供了目的地形象危机沟通的概述、最先进的“研究前沿”、新兴的研究主题以及研究议程。

本文进行了书目耦合研究, 辅以 H-经典分类和对文献计量方法提供的四个集群中包含的文章的主题分析 (论文日期为 2017–2021 年间)。

根据文献计量分析, 确定了四个主题集群。 其中两个集群提供“研究前沿”, 这是科学领域的最新主题：集群 一 解决与游客安全相关的沟通, 集群 二 加强利益相关者合作的作用, 以在危机沟通中创造目的地恢复力。 其他两个集群突出了未来调查的新兴主题：集群 三 侧重于后危机时代的复苏营销传播策略, 集群 四分析危机传播策略如何有助于降低游客的风险感知和提高旅行意愿。最后, 本文提出了基于新兴主题的未来研究议程。

据我们所知, 这是第一个分析了目的地形象的危机传播（危机前、危机和危机后）的, 独特的文献计量研究。该研究涵盖了该领域最新的学术文献, 通过其“研究前沿”提供了有关近期危机和灾难的沟通策略的见解。此外, 本文还提出了具有新兴主题的研究议程。这些新兴话题以及从过去事件中吸取的教训, 可以被目的地营销组织 (DMO) 用来进行灾难沟通, 以便在当前的大流行后情景或未来的危机或灾难中恢复目的地的形象。

Este estudio proporciona una perspectiva general, los “research fronts”- los temas más actuales de una disciplina científica-, los temas emergentes y una agenda de investigación sobre comunicación de crisis de la imagen de los destinos turísticos.

La investigación está basada en un análisis bibliográfico coupling, complementado con una clasificación h-Classics y un análisis temático de todos los artículos examinados con esta metodología bibliométrica (artículos fechados entre 2017 y 2021, ambos años incluidos).

Con este análisis bibliométrico, se identifican cuatro clusters temáticos. Dos de ellos, presentan los “research fronts”, los temas más vigentes de un campo científico: el cluster 1 se refiere a la comunicación realizada para transmitir el concepto de seguridad a los turistas, y el cluster 2 destaca la relevancia de la colaboración de todos los agentes turísticos para crear resiliencia en los destinos en la comunicación de crisis. Los otros dos clusters recogen los temas emergentes de investigación futura: el cluster 3 se centra en las estrategias de marketing para la época de postcrisis y el cluster 4 analiza cómo la comunicación contribuye a reducir la percepción de riesgo de los turistas y, por tanto, a potenciar su intención de viaje. Por último, el artículo propone una agenda de investigación basada en estos temas emergentes.

Hasta donde tenemos conocimiento, éste es el primer estudio bibliométrico especialmente enfocado a la comunicación de crisis para la imagen de los destinos turísticos (con sus tres etapas, precrisis, crisis y poscrisis). Esta investigación, que analiza la literatura más reciente en este campo, proporciona conocimiento sobre la comunicación de las crisis y desastres más recientes, a través de sus “research fronts”. Asimismo, propone una agenda con nuevos temas que están surgiendo en esta disciplina, útil para futuras investigaciones académicas. Dichos temas, junto con los aprendizajes de incidentes pasados, pueden ser usados por las Organizaciones de Marketing de Destinos (DMO, en sus siglas en inglés) para incorporarlos en su comunicación de crisis destinada a la recuperación de la imagen de los destinos turísticos en el actual escenario post pandemia o en futuras crisis o desastres.

This paper tries to retrospect the mounting application of machine learning (ML) and artificial intelligence (AI) in the human resource management area. The document applies bibliometric analysis and uses relational techniques to explore dimensions of documents in the field. The results highlight publication trends, most impactful authors, countries and institutes in the research area. The science mapping along with co-citation and bibliometric coupling analysis revealed major developments in the field. The thematic mapping and trend analysis highlighted the past and emerging trends towards significant and impactful research in the areas of robotics, big data, AI and data analytics. This paper sets the base for future researchers by coordinating and combining various past researches to help in understanding the evolution of ML and AI in human resource management and expansion of knowledgebase.

The purpose of this study is to examine how the implementation of edge computing can enhance the progress of the circular economy within supply chains and to address the challenges and best practices associated with this emerging technology.

This study utilized a streamlined evaluation technique that employed Latent Dirichlet Allocation modeling for thorough content analysis. Extensive searches were conducted among prominent publishers, including IEEE, Elsevier, Springer, Wiley, MDPI and Hindawi, utilizing pertinent keywords associated with edge computing, circular economy, sustainability and supply chain. The search process yielded a total of 103 articles, with the keywords being searched specifically within the titles or abstracts of these articles.

There has been a notable rise in the volume of scholarly articles dedicated to edge computing in the circular economy and supply chain management. After conducting a thorough examination of the published papers, three main research themes were identified, focused on technology, optimization and circular economy and sustainability. Edge computing adoption in supply chains results in a more responsive, efficient and agile supply chain, leading to enhanced decision-making capabilities and improved customer satisfaction. However, the adoption also poses challenges, such as data integration, security concerns, device management, connectivity and cost.

This paper offers valuable insights into the research trends of edge computing in the circular economy and supply chains, highlighting its significant role in optimizing supply chain operations and advancing the circular economy by processing and analyzing real time data generated by the internet of Things, sensors and other state-of-the-art tools and devices.