A Bibliometric Analysis of Digital Innovation from 1998 to 2016

Zhang, Xi; Ye, Meng; Chen, Hui; Jiang, Yu; Sun, Yongqiang; Pablos, Patricia Ordóñez de; He, Joy Wei

doi:10.3724/sp.j.1383.202005

Cited by 12 publications

(8 citation statements)

References 56 publications

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“…Moreover, Zhu QH seems to have become the leader of green enterprises' research in the background of China. This research phenomenon also confirms the conclusion of some scholars that a series of research about China is becoming a hotspot (Sueyoshi et al, 2017;Zhang et al, 2017).…”

Section: Discussion and Future Research Directionssupporting

confidence: 88%

The development of green enterprises: A literature review based on VOSviewer and Pajek

Wang

Tang

Jiang

et al. 2021

Australian Journal of Management

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Being a greener enterprise is the final goal of obtaining sustainable supply chain management, achieving environmental management (EM) and ensuring environmental performance. To provide scholars with knowledge of research trends of green enterprises, we carried out this research project, took 1142 articles as research objects and three methods to review the whole picture of green enterprises research. We found that this field is mainly concentrated in three areas. While small and medium-sized enterprises’ (SMEs) greening, EM and pollution emissions have been the enduring topics, green innovation has received the most attention from researchers. Furthermore, we found that scholars pay a great amount of attention to China-related research and Italian scholars have played a leading role in the future green enterprise research. JEL classification: Q57

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Section: Discussion and Future Research Directionssupporting

confidence: 88%

The development of green enterprises: A literature review based on VOSviewer and Pajek

Wang

Tang

Jiang

et al. 2021

Australian Journal of Management

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“…The availability of funding for start-up development is a particular problem, especially in developing ecosystems. As the crowdsourcing business model has become one of the trends in digital innovation studies (Zhang et al , 2017), this area needs attention to develop studies on future funding opportunities. It may be possible to improve the BML process by adding, for example, milestones or checkpoints for more accurate monitoring (McGrath et al , 1995), so that the results are more satisfactory.…”

Section: Discussionmentioning

confidence: 99%

Determinant factors of lean start-up-based incubation metrics on post-incubation start-up viability: case-based study

Tritoasmoro

Ciptomulyono²,

Dhewanto³

et al. 2022

JSTPM

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Purpose This paper aims to investigate the effect of business incubation metrics based on an adaptation of the lean start-up (LS) framework on start-up survival after incubation. This study also analyzes the obstacles in implementing the LS framework as incubation metrics. Design/methodology/approach This study uses mixed methods. Quantitative research using multiple linear regression was applied to the data of 30 start-ups incubated at Bandung Techno Park for the 2014–2017 period and survival tracking data after the incubation. A qualitative approach to complete the explanatory work was conducted through in-depth interviews with 12 respondents, including start-up graduates from the incubation program, program managers and mentors. Findings This study confirms that several LS incubation metrics significantly affect start-up sustainability after incubation. In addition, this study also explains several problems in applying the LS discipline that needs attention to increase incubation success. Research limitations/implications Research was conducted only at one technology business incubator (TBI) model that focuses on digital start-ups in the emerging ecosystem. Research results can be biased in different situations and ecosystems. Practical implications The explanation of the relationship of LS-based incubation metrics to the survival of start-ups, as well as the challenges of their implementation, can be a reference for TBI management to consider and prioritize intervention strategies, thereby improving TBI’s business processes and increasing the success rate of incubated start-ups. Social implications The creation of university start-ups and spin-offs has become a key performance indicator mandatory for technology universities in Indonesia. The existence of TBI institutions in universities as channels of technology commercialization is essential. The incubator’s success in creating a new technology-based company will have a significant social impact on the surrounding environment. Originality/value Although the LS method is popular in start-up communities and among practitioners, it is rarely used in the incubation process at universities. These results can be considered for university TBIs to explore LS as an incubation management tool to increase the success rate of incubated start-ups.

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“…The first is the definition of the purpose and objectives of the study conducted by the authors; the second is the phase of preparation of the information field, whose structure and procedures for the selection of data have been described in detail above. The third phase is the phase of basic analysis of the obtained results, based on the use of the tools WoS -Results Analysis and Create Citation Report, as well as on the basic elements of descriptive statistics; the fourth is the phase of preparing a set of information for work in CiteSpace by uploading it in «plain text» format in the data collection mode -«Full Record and Cited References»; in the fifth phase, the basic parameters of the analysis project are set, in particular LRF (at the «unlimited» level), LIN (5), Filter Refs By Intrinsic Citations (2.0), LBY (unlimited) and percentage of nodes by Lebel (20%).…”

Section: Data Collection and Methodsmentioning

confidence: 99%

“…The analysis conducted by the authors of the scientific article has shown that the main part of the publications related to the research topic under study can be conditionally divided into se veral groups. Thus, the first group concerns aspects revealing the essence of using the CiteSpace software product for analysis in different branches of science: directly in the context of bibliometric analysis (Chen, 2016;Kim & Zhu, 2018) [1][2], chemistry and physics (Ma et al, 2020;Wang et al, 2022) [3][4], innovation theory (Xi et al, 2017) [5].…”

Section: Brief Literature Reviewmentioning

confidence: 99%

Scientometric analysis of smart tourism using CiteSpace

Mamrayeva¹,

Tashenova²

2022

EA-XXI

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This scientific article is devoted to the scientometric analysis of one of the new and relevant areas in economics – smart tourism, which has become widespread in the last 10-12 years. The research was conducted based on the using of materials from the Web of Knowledge database (Web of Science Core Collection: Science Citation Index Expanded, Social Science Citation Index, Arts and Humanities Citation Index Conference Proceedings Citation Index – Science, Conference Proceedings Citation Index – Social Science and Humanities Book Citation Index – Science, Book Citation Index – Social Science and Humanities, Emerging Sources Citation Index) for 2008-2022, which was later uploaded to CiteSpace 5.8.R3 to implement the tasks set in the research article: analysis of co-citations, including by authors; cluster analysis by keywords. It should be noted that the authors presented a capacious description of the WoS database array itself: from the perspective of the country component, institutes / universities / educational institutions and funding organizations, key sections, citation, types of documents, research area, Web of Science indexes / categories, etc. Also given a brief description of the authors whose work in the field of smart tourism is the most cited today. In general, it should be noted that the overall result of the search query «Smart Tourism» amounted to 724 documents, which were further used in the «Plain Text» format for scientometric analysis, which made it possible to determine the current and prospective areas of research in the field of smartification of tourism services, as well as build networks that visualize them visually. The author’s methodology for conducting scientometric analysis was also developed, starting from the moment the data array was received, and ending with the final visualization, which is universal, adaptive and complex, and can be used by any researcher when conducting a scientometric analysis of this kind in any of the branches of science, including in tourism.

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A Bibliometric Analysis of Digital Innovation from 1998 to 2016

Cited by 12 publications

References 56 publications

The development of green enterprises: A literature review based on VOSviewer and Pajek

The development of green enterprises: A literature review based on VOSviewer and Pajek

Determinant factors of lean start-up-based incubation metrics on post-incubation start-up viability: case-based study

Scientometric analysis of smart tourism using CiteSpace

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