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This study aims to explore the impact of tourists’ perceptions of two rural destination attractiveness dimensions on tourists’ environmentally responsible behavioral intentions (ERBI). Further, the mediating effects of tourists’ green self-identity on the relationship between the perception of rural destination attractiveness and ERBI are investigated.

This study collected survey data from 188 tourists who had visiting experiences in rural attractions located in the Guangdong Province of China. Partial least squares structural equation modeling (PLS-SEM) was used to test the proposed hypotheses.

The results found that rural destination specialty fresh food attractiveness perceived by tourists was positively associated with their ERBI. Moreover, tourists’ green self-identity positively mediated the perception of rural destination attractiveness and ERBI.

This study explains how the tourists’ perceptions of two rural destination attractiveness dimensions influence their ERBI. By exploring the mediating role of tourists’ green self-identity, this study also emphasizes the transforming mechanism from tourists’ perceived experience to their ERBI. The study provides insights into nature-based tourism destination management and sustainability practices.

Academic coaching (AC) has gained a significant attention to support student success and achievement in higher education, management and psychology. This study aimed to conduct a comprehensive bibliometric analysis of AC literature to identify the top authors, research patterns, hotspots and research topics in the field.

The study utilized a bibliometric analysis of articles published between 1987 and 2023, using descriptive and network analysis methods with tools such as RStudio, Biblioshiny, Excel and VOSviewer. The study also conducted functional, mapping and content analysis, to identify AC literature's key themes and research areas.

The results revealed an increasing interest in AC, with increased publications. However, there are gaps in geographical diversity and authorship. Most studies were conducted in the United States of America and the UK, and were published in education, psychology and coaching journals. Common themes included coaching, professional development, higher education and mentoring. Emerging research areas include: coaching efficacy in education, AC as an online learning support and professional learning communities. More studies are needed in different contexts and with larger sample sizes.

This comprehensive bibliometric analysis adds to the existing literature by presenting a detailed analysis of the field of AC, filling a gap in the current literature. The study's unique contribution is its examination of emerging research areas and themes in AC literature, providing directions for future research. This study is particularly relevant for researchers, practitioners and policymakers interested in understanding AC's state of the art and identifying promising areas for future research.

Against the background of the I50 paradigm, this paper queries in what ways blockchain and blockchain-based applications deployed in the smart city context facilitate the integration of the I50 paradigm in smart urban contexts.

A mixed methods approach is applied. First, by means of desk research and thematic literature review, a conceptual model integrating the I50 paradigm, smart city and blockchain-based solutions is built. Second, science mapping bibliometric analysis (SciMat) based on keywords’ co-occurrence is applied to a sample of 491 research articles to identify key domains of blockchain-based applications’ use in smart city. Third, a semi-systematic literature review complements insights gained through SciMat. Fourth, the findings are interpreted through the precepts of the conceptual model devised earlier.

The key blockchain-based applications in smart cities pertain to two domains, i.e. the foundational, service facilitation-oriented domain, including security (and safety), networks, computing, resource management and the service delivery-oriented domain, including mobility, energy and healthcare. Blockchain serves as the key building block for applications developed to deliver functions specific to each of the thus identified domains. A substantial layering of blockchain-based tools and applications is necessary to advance from the less to the more complex functional domains of the smart city.

At the conceptual level, the intricacies of the (making of the) I50 paradigm are discussed and a case for I50 – smart city – blockchain nexus is made. Easton’s input–output model as well as constructivism is referenced. At the empirical level, the key major domains of blockchain-based applications are discussed; those that bear the prospect of integrating the I50 paradigm in the smart city are highlighted. At the methodological level, a strategic move is made aimed at restoring the literature review’s role as subservient to the key line of exploration, to justify and ultimately support it, rather than to showcase the literature review as the ultimate purpose for itself.

In the era of artificial intelligence (AI), algorithms have gained unprecedented importance. Scientific studies have shown that algorithms are frequently mentioned in papers, making mention frequency a classical indicator of their popularity and influence. However, contemporary methods for evaluating influence tend to focus solely on individual algorithms, disregarding the collective impact resulting from the interconnectedness of these algorithms, which can provide a new way to reveal their roles and importance within algorithm clusters. This paper aims to build the co-occurrence network of algorithms in the natural language processing field based on the full-text content of academic papers and analyze the academic influence of algorithms in the group based on the features of the network.

We use deep learning models to extract algorithm entities from articles and construct the whole, cumulative and annual co-occurrence networks. We first analyze the characteristics of algorithm networks and then use various centrality metrics to obtain the score and ranking of group influence for each algorithm in the whole domain and each year. Finally, we analyze the influence evolution of different representative algorithms.

The results indicate that algorithm networks also have the characteristics of complex networks, with tight connections between nodes developing over approximately four decades. For different algorithms, algorithms that are classic, high-performing and appear at the junctions of different eras can possess high popularity, control, central position and balanced influence in the network. As an algorithm gradually diminishes its sway within the group, it typically loses its core position first, followed by a dwindling association with other algorithms.

To the best of the authors’ knowledge, this paper is the first large-scale analysis of algorithm networks. The extensive temporal coverage, spanning over four decades of academic publications, ensures the depth and integrity of the network. Our results serve as a cornerstone for constructing multifaceted networks interlinking algorithms, scholars and tasks, facilitating future exploration of their scientific roles and semantic relations.

Business intelligence (BI) systems and tools are deemed to be a transformative source with the potential to contribute to reshaping the way different healthcare organizations’ (HCOs) services are offered and managed. However, this emerging field of research still appears underdeveloped and fragmented. Hence, this paper aims to reconciling, analyzing and synthesizing different strands of managerial-oriented literature on BI in HCOs and to enhance both theoretical and applied future contributions.

A literature-based framework was developed to establish and guide a three-stage state-of-the-art systematic literature review (SLR). The SLR was undertaken adopting a hybrid methodology that combines a bibliometric and a content analysis.

In total, 34 peer-review articles were included. Results revealed significant heterogeneity in theoretical basis and methodological strategies. Nonetheless, the knowledge structure of this research’s stream seems to be primarily composed of five clusters of interconnected topics: (1) decision-making, relevant capabilities and value creation; (2) user satisfaction and quality; (3) process management, organizational change and financial effectiveness; (4) decision-support information, dashboard and key performance indicators; and (5) performance management and organizational effectiveness.

To the authors’ knowledge, this is the first SLR providing a business and management-related state-of-the-art on the topic. Besides, the paper offers an original framework disentangling future research directions from each emerged cluster into issues pertaining to BI implementation, utilization and impact in HCOs. The paper also discusses the need of future contributions to explore possible integrations of BI with emerging data-driven technologies (e.g. artificial intelligence) in HCOs, as the role of BI in addressing sustainability challenges.