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Sharing economy
(2020)
The sharing economy has received increased attention in entrepreneurship research, resulting in a complex research landscape that is hard to overlook. Using a bibliometric analysis, we aim to further synthesise the field by: 1) summarising the most important definitions given by extant literature to capture the common understanding of the sharing economy; 2) identifying three thematic clusters based on the top 20 most cited publications; 3) conducting a citation analysis to show interdependencies between all authors; and 4) identifying the research methods used in the SE publications. Our results show: 1) many definitions with different emphases; 2) conceptualisation, collaborative consumption/ownership and the disruptive character of the sharing economy as three dominant research clusters; 3) a fairly even citation practice allowing for unbiased future research; and 4) that conceptual publications and quantitative as well as qualitative studies are fairly evenly published.
Both entrepreneurship and innovation play a key role for business growth and economic development and are conceptually highly intertwined. Both fields have received extensive attention that has resulted in a large number of publications. The aim of this work is to provide an overview on the coevolution of entrepreneurship and innovation over the last decades, with particular attention to recent research trends. To track the evolution at the intersection of both fields, we employ a bibliometric analysis, which allowed us to identify the key concepts, the backbone of research, and to provide a systematic classification of main research themes diagnosed including: 1) entrepreneurial innovation and digital transformation, 2) sustainable innovation and entrepreneurship, 3) product innovation and knowledge, 4) entrepreneurial orientation and leadership, and 5) regional entrepreneurship and innovation (innovative entrepreneurship and historical roots). The findings of this bibliometric review are reported in the form of a knowledge graph that represents the results obtained in terms of the knowledge base (key terms), knowledge domains, and knowledge evolution (themes and bursts), based on which themes for future research are suggested.
Web Tracking
(2018)
Web tracking seems to become ubiquitous in online business and leads to increased privacy concerns of users. This paper provides an overview over the current state of the art of web-tracking research, aiming to reveal the relevance and methodologies of this research area and creates a foundation for future work. In particular, this study addresses the following research questions: What methods are followed? What results have been achieved so far? What are potential future research areas? For these goals, a structured literature review based upon an established methodological framework is conducted. The identified articles are investigated with respect to the applied research methodologies and the aspects of web tracking they emphasize.