A Bibliometric Overview of Tourism Family Business

Family businesses are of particular economic relevance in the international hospitality and tourism industry. However, there are few studies that address their specific characteristics and objectives. The aim of this study is to produce a bibliometric overview that reveals the structure underpinning the analysis of the tourism family business in the business and management research field. The study also reveals the evolution of this research over time, as well as the most relevant related concepts and study gaps. Through a keyword co-occurrence analysis and a systematic review of 129 studies on tourism family businesses published between 1997 and 2020, the main contributions were organized into four thematic clusters, which include specific theoretical approaches. The clusters are Entrepreneurship, Marketing Orientation and Innovation Performance; Capabilities and Competitiveness; Sustainability; and Strategy and Economic Performance. On the basis of these results, this study introduces an integrative framework for tourism family business research, clarifying the rich diversity of research paths that seek to explain tourism business competitiveness, and identifying potential directions for future research aimed at further developing the field

Identifying collaboration dynamics of bipartite author-topic networks with the influences of interest changes

Knowing driving factors and understanding researcher behaviors from the dynamics of collaborations over time offer some insights, i.e. help funding agencies in designing research grant policies. We present longitudinal network analysis on the observed collaborations through co-authorship over 15 years. Since co-authors possibly influence researchers to have interest changes, by focusing on researchers who could become the influencer, we propose a stochastic actor-oriented model of bipartite (two-mode) author-topic networks from article metadata. Information of scientific fields or topics of article contents, which could represent the interests of researchers, are often unavailable in the metadata. Topic absence issue differentiates this work with other studies on collaboration dynamics from article metadata of title-abstract and author properties. Therefore, our works also include procedures to extract and map clustered keywords as topic substitution of research interests. Then, the next step is to generate panel-waves of co-author networks and bipartite author-topic networks for the longitudinal analysis. The proposed model is used to find the driving factors of co-authoring collaboration with the focus on researcher behaviors in interest changes. This paper investigates the dynamics in an academic social network setting using selected metadata of publicly-available crawled articles in interrelated domains of "natural language processing" and "information extraction". Based on the evidence of network evolution, researchers have a conformed tendency to co-author behaviors in publishing articles and exploring topics. Our results indicate the processes of selection and influence in forming co-author ties contribute some levels of social pressure to researchers. Our findings also discussed on how the co-author pressure accelerates the changes of interests and behaviors of the researchers