CorTexT platform

@article{Bañas2023,

title = {Stormwater Harvesting from Roof Catchments: A Review of Design, Efficiency, and Sustainability},

author = {Karen Bañas and Miguel Enrico Robles and Marla Maniquiz-Redillas},

url = {https://www.mdpi.com/2073-4441/15/9/1774

},

doi = {10.3390/w15091774},

year  = {2023},

date = {2023-05-05},

journal = {Water},

volume = {15},

pages = {1774},

publisher = {MDPI},

abstract = {Roof runoff is collected rainwater from a roof using a rainwater harvesting system (RWHS). The construction of an efficient RWHS requires a thorough analysis of the rainwater quality and the appropriate treatment process for its intended use. In line with this, a bibliometric and comprehensive review of studies related to roof rainwater harvesting was conducted. A corpus of 1123 articles was downloaded from the Scopus database and parsed through the CorText Manager to determine the relationships between keywords, journals, and topics related to rainwater harvesting. A comprehensive analysis was also conducted to determine the different designs of RWHS, the quality of harvested rainwater from roof catchments, the efficiency of the system for specific purposes, and its sustainability in terms of economic, environmental, and social aspects. Results show that the effectiveness of a RWHS heavily depends on its installation site, the physicochemical characteristics of the harvested rainwater, and the acceptability of the end users. An effective water treatment process is essential for achieving better water quality for harvested rainwater. Moreover, assessing the financial viability and return on investment of an RWHS is necessary.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Xiao2023,

title = {A Comprehensive Bibliometric Analysis of Big Data in Entrepreneurship Research},

author = {Anran Xiao and Yong Qin and Zeshui Xu and Marinko Skare},

url = {https://www.inzeko.ktu.lt/index.php/EE/article/view/30643},

doi = {https://doi.org/10.5755/j01.ee.34.2.30643 },

issn = {1392-2785},

year  = {2023},

date = {2023-04-28},

journal = {Engineering Economics},

volume = {34},

issue = {2},

pages = {175–192},

abstract = {Big data technology has been widely used in entrepreneurial research in recent years. To explore the development trend and fundamental characteristics of big data in entrepreneurship (BDIE) research, we conduct a comprehensive bibliometric analysis of BDIE based on 541 publications between 1993 and 2020 from Web of Science. On the one hand, this paper focuses on some essential characteristics of the BDIE publications, such as categories, citation, H-index, and the most cited publications. On the other hand, visual scientific maps are presented by bibliometric tools, i.e., Bibliometrix, VOS viewer, and CorTexT Manager, showing relationships between publications and knowledge structure in BDIE research. Finally, hot topics in current studies, knowledge, and limitations are discussed, guiding scholars to explore new research directions. This paper provides a relatively broad perspective for applying BDIE research, which contributes to understanding the evolution of BDIE research and inspires scholars in related fields.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Zou2023,

title = {Operations research on the sharing economy: A bibliometric analysis and literature review},

author = {Liuxin Zou and Jiang Wu and Yeming Gong and Mingyang Chen and Mengchen Xia},

url = {https://www.sciencedirect.com/science/article/pii/S1567422323000303},

doi = {https://doi.org/10.1016/j.elerap.2023.101265},

issn = {1567-4223},

year  = {2023},

date = {2023-04-26},

journal = {Electronic Commerce Research and Applications},

pages = {101265},

abstract = {Previous studies on the sharing economy have not utilized bibliometrics to classify the main stakeholders from the perspective of operations research (OR). In this study, we utilize the bibliometric method to review the supply side, demand side, the platform, and their optimization models. Based on the bibliometric network, we propose a complete multi-level framework to study the optimization decisions of stakeholders and the key factors that may influence optimal decisions in the sharing economy. The pricing, behavioral characteristics, operating strategies, and incentive methods of the three stakeholders will affect the optimal decisions and models. Multi-party interaction significantly affects the decision-making behavior of stakeholders. The sharing economy introduces a new business model to traditional industrial applications, such as transportation and trade, and has both positive and negative effects on the economy, environment, and society. We identify future research in the ecosystem of the sharing economy, hybrid methods, and breakthrough technologies, such as blockchain, AI, and data-driven optimization.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Scherngell2023,

title = {The geographical dynamics of global R&D collaboration networks in robotics: Evidence from co-patenting activities across urban areas worldwide},

author = { Thomas Scherngell and Katharina Schwegmann and Georg Zahradnik},

editor = {Celine Rozenblat from University of Lausanne SWITZERLAND},

url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0281353},

doi = {https://doi.org/10.1371/journal.pone.0281353},

year  = {2023},

date = {2023-04-13},

urldate = {2023-04-13},

journal = {PLOS ONE},

abstract = {The focus of this study is on the geography of robotics Research and Development (R&D) activities. The objectives are, first, to identify hotspots in robotics R&D worldwide, and second, to characterise structures and dynamics of global robotics R&D collaboration networks through detailed geographical lenses of global urban areas. We use patents as marker for R&D activities, and accordingly focus on technologically oriented R&D, drawing on information from patents applied for between 2002 and 2016. We employ an appropriate search strategy to identify relevant robotics patents based on detailed levels of the Cooperative Patent Classification (CPC) and assign patents to more than 900 global urban areas based on the inventor addresses. The co-patent networks are examined from a Social Network Analysis (SNA) perspective by means of robotics co-patents, contributing to a global network where urban areas are the nodes inter-linked by joint inventive activities recorded in robotics patents. Global SNA measures illustrate structures and dynamics of the network as a whole, while local measures indicate the specific positioning and roles of urban areas in the network. The results are original in characterising the global spatial emergence of this generic new industry, highlighting prominent urban hotspots in terms of specialisation in robotics R&D, pointing to a global shift reflected by the increasing role of emerging economies, in particular China. The global robotics R&D has grown significantly both in total patenting and also in terms of R&D collaboration activities between urban areas. Also, for the networks, growth is not equally distributed, but is rather characterised by significant spatial shifts, both in terms of cities declining or climbing up the specialisation ranking, but even more in terms of the spatial network structure.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}