This research aims to document the trend of political campaigning from 2011 onward. Further, this research will address the broader context of proposing and identifying future trends and scope in political campaigning. Using a bibliometric analysis approach using, R. Authors has examined almost 1090 documents from reputed databases like Scopus and Web of Science from 2011 onward. The findings of this study concluded that the literature on election campaigning is extremely fragmented and yet in its early stages. Henceforth, building a more coordinated effort in storing these data is necessary, which would help the scholar and researcher, regardless of their disciplines, to acquire a viewpoint on political campaign study.
本研究旨在记录2011年以后政治竞选的趋势。此外，本研究将探讨在政治竞选中提出和确定未来趋势和范围的更广泛背景。使用文献计量学分析方法，R. Authors从2011年起检查了来自Scopus和Web of Science等知名数据库的近1090篇文献。这项研究的结论是，关于竞选活动的文献非常零散，而且还处于早期阶段。因此，建立一个更加协调的努力来存储这些数据是必要的，这将有助于学者和研究人员，无论他们的学科，获得政治竞选研究的观点。
{"title":"Trends in Political Campaigning Research: A Bibliometric Literature Analysis","authors":"C. Prakash, Sunita Dwivedi","doi":"10.5530/jscires.11.2.28","DOIUrl":"https://doi.org/10.5530/jscires.11.2.28","url":null,"abstract":"This research aims to document the trend of political campaigning from 2011 onward. Further, this research will address the broader context of proposing and identifying future trends and scope in political campaigning. Using a bibliometric analysis approach using, R. Authors has examined almost 1090 documents from reputed databases like Scopus and Web of Science from 2011 onward. The findings of this study concluded that the literature on election campaigning is extremely fragmented and yet in its early stages. Henceforth, building a more coordinated effort in storing these data is necessary, which would help the scholar and researcher, regardless of their disciplines, to acquire a viewpoint on political campaign study.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"50 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86107721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Samuel-Soma M. Ajibade, N. Adhikari, Dai-Long Ngo-Hoang
Higher education students and faculty use Facebook and Twitter. Researchers have also looked at social networking platforms in higher education. Social media has facilitated student-professor communication, collaboration, and engagement. To embrace students and teachers who utilize technology to learn and teach, it must be determined what influences their readiness to do so. This report tests the adoption of social networking media for e-learning in Nigerian utilizing the Technology Acceptance Model (TAM), which emphasizes perceived ease of use, perceived usefulness, and behavioural intention to utilize new technologies. Surveys were utilized for quantitative research. This study polled teachers and students from 4 Nigerian schools. Structural Equation Modeling was used to anticipate the model’s recommended factors (SEM). The study indicated that students’ and teachers’ behavioral intentions to use social media for e-learning in Nigerian universities are influenced by perceived ease of use and perceived usefulness.
{"title":"An Analysis of Social Networking for E-learning in Institutions of Higher Learning using Perceived Ease of use and Perceived Usefulness","authors":"Samuel-Soma M. Ajibade, N. Adhikari, Dai-Long Ngo-Hoang","doi":"10.5530/jscires.11.2.26","DOIUrl":"https://doi.org/10.5530/jscires.11.2.26","url":null,"abstract":"Higher education students and faculty use Facebook and Twitter. Researchers have also looked at social networking platforms in higher education. Social media has facilitated student-professor communication, collaboration, and engagement. To embrace students and teachers who utilize technology to learn and teach, it must be determined what influences their readiness to do so. This report tests the adoption of social networking media for e-learning in Nigerian utilizing the Technology Acceptance Model (TAM), which emphasizes perceived ease of use, perceived usefulness, and behavioural intention to utilize new technologies. Surveys were utilized for quantitative research. This study polled teachers and students from 4 Nigerian schools. Structural Equation Modeling was used to anticipate the model’s recommended factors (SEM). The study indicated that students’ and teachers’ behavioral intentions to use social media for e-learning in Nigerian universities are influenced by perceived ease of use and perceived usefulness.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"29 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75496473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. C. Gouveia, Priscila Ramos-Carvalho, Marcos Gonçalves Ramos
This study aims to present exploratory and descriptive research about Latin America's online information search and Twitter activity and the repercussions of chloroquine, hydroxychloroquine, and ivermectin, which were at the time considered promising alternatives to prevent or treat COVID-19. From the perspective of Webmetrics and Altmetrics -data were collected and analysed from Twitter around indexed outputs by titles with one of these three drugs and from Google Trends (Relative Search Interest) in Latin American countries. The results demonstrated that there might be parallels between Google Search and Twitter activity. The results also showed that ivermectin was, among the three selected drugs, the most searched in Google Search and higher activity on Latin America's Twitter accounts.
{"title":"Relative Search Interest and Twitter Altmetrics of Chloroquine, Hydroxychloroquine and Ivermectin in Latin America","authors":"F. C. Gouveia, Priscila Ramos-Carvalho, Marcos Gonçalves Ramos","doi":"10.5530/jscires.11.2.19","DOIUrl":"https://doi.org/10.5530/jscires.11.2.19","url":null,"abstract":"This study aims to present exploratory and descriptive research about Latin America's online information search and Twitter activity and the repercussions of chloroquine, hydroxychloroquine, and ivermectin, which were at the time considered promising alternatives to prevent or treat COVID-19. From the perspective of Webmetrics and Altmetrics -data were collected and analysed from Twitter around indexed outputs by titles with one of these three drugs and from Google Trends (Relative Search Interest) in Latin American countries. The results demonstrated that there might be parallels between Google Search and Twitter activity. The results also showed that ivermectin was, among the three selected drugs, the most searched in Google Search and higher activity on Latin America's Twitter accounts.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"35 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76693423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Prakoso Bhairawa Putera, S. Suryanto, S. Ningrum, I. Widianingsih, Y. Rianto
The national (Indonesia) long-term development plan 2005-2025 has approached its final step. Currently, the Ministry of National Development Planning is preparing a technical text for the policy, including in the fields of science and technology. Referring to this notion, we have compiled this paper aiming at providing recommendations towards the applied indicators to measure efforts to achieve Indonesia’s 2045 target. This paper is divided into four discussions, which consist of: STI Indicator Comparison, Achievements of the STI Indicator, Notes for STI Indicators in the RPJPN, dan Author’s reflections/ insights.
{"title":"STI Performance in Indonesia: Policies, Indicators, Current Achievements, and Recommendations for 2045","authors":"Prakoso Bhairawa Putera, S. Suryanto, S. Ningrum, I. Widianingsih, Y. Rianto","doi":"10.5530/jscires.11.2.29","DOIUrl":"https://doi.org/10.5530/jscires.11.2.29","url":null,"abstract":"The national (Indonesia) long-term development plan 2005-2025 has approached its final step. Currently, the Ministry of National Development Planning is preparing a technical text for the policy, including in the fields of science and technology. Referring to this notion, we have compiled this paper aiming at providing recommendations towards the applied indicators to measure efforts to achieve Indonesia’s 2045 target. This paper is divided into four discussions, which consist of: STI Indicator Comparison, Achievements of the STI Indicator, Notes for STI Indicators in the RPJPN, dan Author’s reflections/ insights.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"28 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88933639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Numerous bibliographic databases track the number of publications, citations, and h-index to maintain the progress of an individual. However, the choice of journals varies among these databases, hence they produce different numbers of publications, citations and h-index for the same author. Various literatures are available on the comparative analysis of such bibliographic databases stating the fact that there are the differences between bibliometrics generated by different bibliographic databases but none of the literature provides any comprehensive or complete solution to overcome such differences. At present, there is no common platform that can provide a single count of number of publications, citations and h-index across multiple bibliographic databases. To overcome this limitation, we propose a new method in academic research publication to calculate weighted unified (single) informetrics for an author. With the proposed solution, one can view a single article, citation, and h-index count computed from multiple indexing databases. In this study, the data from Scopus and Web of Science is used to generate a new database named “conflate”. Further, a comparative analysis of the proposed model is performed with Scopus and Web of Science at three levels: author, organization, and journal. The proposed model can be observed as a new single indicator to determine the research influence of the author, organization, and journal. Aim: We propose a new method in academic research publication to calculate weighted unified informetrics. With the proposed solution, one can view a single article, citation, and h-index count computed from multiple indexing databases. The proposed model can be observed as a new indicator to determine the research influence of author, organization, and journal.
许多书目数据库跟踪出版物的数量、引用和h指数，以保持个人的进步。然而，这些数据库对期刊的选择各不相同，因此它们对同一作者产生不同的出版物数量、引用数和h指数。通过对这类书目数据库的比较分析，可以找到各种文献，表明不同书目数据库生成的文献计量学存在差异，但没有一种文献提供全面或完整的解决方案来克服这种差异。目前，还没有一个通用的平台可以跨多个书目数据库提供单一的出版物数、被引数和h指数统计。为了克服这一限制，我们提出了一种在学术研究出版物中计算作者加权统一(单一)信息度量的新方法。使用建议的解决方案，可以查看从多个索引数据库计算的单个文章、引文和h-index计数。在本研究中，使用Scopus和Web of Science的数据生成一个名为“conflate”的新数据库。此外，在作者、组织和期刊三个层次上对所提出的模型与Scopus和Web of Science进行了比较分析。本文提出的模型可以作为一个新的单一指标来衡量作者、机构和期刊的研究影响力。目的:提出一种计算学术研究出版物加权统一信息度量的新方法。使用建议的解决方案，可以查看从多个索引数据库计算的单个文章、引文和h-index计数。该模型可作为判断作者、机构和期刊研究影响力的新指标。
{"title":"A Comparative Analysis of Unified Informetrics with Scopus and Web of Science","authors":"P. Khurana, Geetha Ganesan, G. Kumar, K. Sharma","doi":"10.5530/jscires.11.2.16","DOIUrl":"https://doi.org/10.5530/jscires.11.2.16","url":null,"abstract":"Numerous bibliographic databases track the number of publications, citations, and h-index to maintain the progress of an individual. However, the choice of journals varies among these databases, hence they produce different numbers of publications, citations and h-index for the same author. Various literatures are available on the comparative analysis of such bibliographic databases stating the fact that there are the differences between bibliometrics generated by different bibliographic databases but none of the literature provides any comprehensive or complete solution to overcome such differences. At present, there is no common platform that can provide a single count of number of publications, citations and h-index across multiple bibliographic databases. To overcome this limitation, we propose a new method in academic research publication to calculate weighted unified (single) informetrics for an author. With the proposed solution, one can view a single article, citation, and h-index count computed from multiple indexing databases. In this study, the data from Scopus and Web of Science is used to generate a new database named “conflate”. Further, a comparative analysis of the proposed model is performed with Scopus and Web of Science at three levels: author, organization, and journal. The proposed model can be observed as a new single indicator to determine the research influence of the author, organization, and journal. Aim: We propose a new method in academic research publication to calculate weighted unified informetrics. With the proposed solution, one can view a single article, citation, and h-index count computed from multiple indexing databases. The proposed model can be observed as a new indicator to determine the research influence of author, organization, and journal.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"14 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84962318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose: It is an established conception that increased employee productivity plays an instrumental role in the sustained success of a business. Resultantly, organisations have pursued it with utmost priority. The study intended to present the academic patterns as well as structures concerning research in the field of employee productivity from the year 2002 to 2021 using bibliometric tools and applications. Design/methodology/approach: The Scopus database was used to extract the data for this study. To determine the current state of research on employee productivity, the most widely acknowledged indicators used for performing bibliometric analysis have been employed. A software application named VOS viewer is used for mapping bibliographic data. Originality/value: The term ‘productivity’ has gained popularity in the corporate quarters in recent years which has generated the interest of authors in analysing their research patterns. Moreover, no such retrospective bibliometric study on employee productivity is conducted so far.
{"title":"What do we know about Employee Productivity?: Insights from Bibliometric Analysis","authors":"Shivangi Singh, Ajay Solkhe, P. Gautam","doi":"10.5530/jscires.11.2.20","DOIUrl":"https://doi.org/10.5530/jscires.11.2.20","url":null,"abstract":"Purpose: It is an established conception that increased employee productivity plays an instrumental role in the sustained success of a business. Resultantly, organisations have pursued it with utmost priority. The study intended to present the academic patterns as well as structures concerning research in the field of employee productivity from the year 2002 to 2021 using bibliometric tools and applications. Design/methodology/approach: The Scopus database was used to extract the data for this study. To determine the current state of research on employee productivity, the most widely acknowledged indicators used for performing bibliometric analysis have been employed. A software application named VOS viewer is used for mapping bibliographic data. Originality/value: The term ‘productivity’ has gained popularity in the corporate quarters in recent years which has generated the interest of authors in analysing their research patterns. Moreover, no such retrospective bibliometric study on employee productivity is conducted so far.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"9 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75439046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The importance of scientific collaborations is mainly because of the professional learning obtained from the formation of research connections. Each researcher brings a feature and advantage to the research team, such as mastering a particular topic and its subdivisions or improving team thinking. The importance of collaboration is doubled when researchers collaborate at the international level, resulting in access to up-to-date resources and equipment, consequently increasing the quantity, quality, and impact of research activities. The primary purpose of this study is to investigate the effect of international collaboration of faculty members on the centrality of the university network collaborations, which measures how much a scientist is at the center of a local collaboration network. The data is taken from faculty members’ publications in the electrical and computer engineering departments of the selected Iranian universities (the Isfahan University of Technology, Iran University of Science and Technology, Amirkabir University of Technology, University of Tehran, Ferdowsi University of Mashhad, and the Sharif University of Technology). Using multiple linear regression, the results show a twofold effect: The significant positive effect of having international collaboration on the centrality degree of scientists’ network and the significant negative effect of the international collaborations over the total collaborations ratio on the centrality degree. This means that international collaborations of faculty members per se put them at the center of the university network. However, this positive effect turns negative if its weight is dominant compared to all publications. The finding highlights the importance of a balance between international and local collaborations
{"title":"The Impact of Faculty Members’ International Collaboration on the Centrality Measure of their Local Collaboration Network: The Case of Electrical and Computer Engineering in the Selected Iranian Universities","authors":"Seyed Reza Mirnezami, Molud Mohammadi","doi":"10.5530/jscires.11.2.21","DOIUrl":"https://doi.org/10.5530/jscires.11.2.21","url":null,"abstract":"The importance of scientific collaborations is mainly because of the professional learning obtained from the formation of research connections. Each researcher brings a feature and advantage to the research team, such as mastering a particular topic and its subdivisions or improving team thinking. The importance of collaboration is doubled when researchers collaborate at the international level, resulting in access to up-to-date resources and equipment, consequently increasing the quantity, quality, and impact of research activities. The primary purpose of this study is to investigate the effect of international collaboration of faculty members on the centrality of the university network collaborations, which measures how much a scientist is at the center of a local collaboration network. The data is taken from faculty members’ publications in the electrical and computer engineering departments of the selected Iranian universities (the Isfahan University of Technology, Iran University of Science and Technology, Amirkabir University of Technology, University of Tehran, Ferdowsi University of Mashhad, and the Sharif University of Technology). Using multiple linear regression, the results show a twofold effect: The significant positive effect of having international collaboration on the centrality degree of scientists’ network and the significant negative effect of the international collaborations over the total collaborations ratio on the centrality degree. This means that international collaborations of faculty members per se put them at the center of the university network. However, this positive effect turns negative if its weight is dominant compared to all publications. The finding highlights the importance of a balance between international and local collaborations","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"1 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88908353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Citation is a measure that quantifies the impact of the researcher, research article and journal’s quality. Investigating the citation of articles and/or researchers is one of the important tasks in the research community. So, understanding and predicting citation patterns of research articles has become popular in scientific research fields. In this work, we give a machine learning approach to predict the citations of research articles using the keywords. We study the citation impact based on keywords motioned in the articles using the data set of publications which are published in the various physical review journals from 1985-2012. In this dataset, for each publication is allocated some PACS codes (keywords) by their authors which represent a sub-field of Physics. In this work, we are investigating the impact of PACS codes of article on article’s citation. We are performing our analysis on the first (sub-field of physics), second (sub area of sub-field of physics) and third level of PACS codes. We observed that compared to the first level, every pair of citation patterns of the second level is highly correlated. We also obtained a universal approximation curve for the third level that matches with the average value of the first level. This curve looks like a shifted and scaled version of the Gaussian function and is right skewed. We can also predict the citations based on the keywords by using this universal curve.
{"title":"Empirical Study on Citation Count Prediction of Research Articles","authors":"M. Enduri, V. U. Sankar, K. Hajarathaiah","doi":"10.5530/jscires.11.2.17","DOIUrl":"https://doi.org/10.5530/jscires.11.2.17","url":null,"abstract":"Citation is a measure that quantifies the impact of the researcher, research article and journal’s quality. Investigating the citation of articles and/or researchers is one of the important tasks in the research community. So, understanding and predicting citation patterns of research articles has become popular in scientific research fields. In this work, we give a machine learning approach to predict the citations of research articles using the keywords. We study the citation impact based on keywords motioned in the articles using the data set of publications which are published in the various physical review journals from 1985-2012. In this dataset, for each publication is allocated some PACS codes (keywords) by their authors which represent a sub-field of Physics. In this work, we are investigating the impact of PACS codes of article on article’s citation. We are performing our analysis on the first (sub-field of physics), second (sub area of sub-field of physics) and third level of PACS codes. We observed that compared to the first level, every pair of citation patterns of the second level is highly correlated. We also obtained a universal approximation curve for the third level that matches with the average value of the first level. This curve looks like a shifted and scaled version of the Gaussian function and is right skewed. We can also predict the citations based on the keywords by using this universal curve.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"13 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78918057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Despite being received increasing attention from academic scholars, there have yet any review study on the topic of start-up success. This work fulfills this research gap by investigating 1554 start-up success documents collected from Scopus dataset between 1981 and 2019. Using bibliometric analysis, we reveal that the topic of start-up success only receives more attention from academic scholars since 2011 onwards. Regarding geographical distribution, the US, Germany, and the UK are the three countries contributing the highest number of start-up success related documents. Besides, it’s revealed that 305 (or 19.6%) start-up success documents were published in the top 20 journals. The co-author analysis found that the research groups of start-up success are still small and dispersed and there was a lack of continuity in the research. The science mapping identified six main topics of start-up success, including: (1) Business in General, (2) Start-up Ecosystem, (iii) Academic Start-up, (iv) Drivers of Start-up Success, (v) Resources for start-up, and (vi) Start-up Model. The study’s findings provide implications for stakeholders, academic
{"title":"A Bibliometric Analysis of Studies on ‘Start-up Success’ Covering the Period 1981-2019","authors":"T. Le, Hiep-Hung Pham, Van Binh Tran","doi":"10.5530/jscires.11.2.23","DOIUrl":"https://doi.org/10.5530/jscires.11.2.23","url":null,"abstract":"Despite being received increasing attention from academic scholars, there have yet any review study on the topic of start-up success. This work fulfills this research gap by investigating 1554 start-up success documents collected from Scopus dataset between 1981 and 2019. Using bibliometric analysis, we reveal that the topic of start-up success only receives more attention from academic scholars since 2011 onwards. Regarding geographical distribution, the US, Germany, and the UK are the three countries contributing the highest number of start-up success related documents. Besides, it’s revealed that 305 (or 19.6%) start-up success documents were published in the top 20 journals. The co-author analysis found that the research groups of start-up success are still small and dispersed and there was a lack of continuity in the research. The science mapping identified six main topics of start-up success, including: (1) Business in General, (2) Start-up Ecosystem, (iii) Academic Start-up, (iv) Drivers of Start-up Success, (v) Resources for start-up, and (vi) Start-up Model. The study’s findings provide implications for stakeholders, academic","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"32 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85846670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Muhammad Shahid Iqbal, Mohd Faizal Mohd Isa, Fadzli Shah Abd Aziz
The discussion on the high-performance organization (HPO) emerged in early 1984. The terminology of the high-performance organization has attracted scholars to study the concept of the HPO, its related factors, and its outcome toward the organization’s goals. Since then, scholars have frequently used the term “High-Performance Organization” further to investigate the development of the concept in this area. The objective of this study is to depict the systematic review of literature on high-performance organizations which had been published in the Scopus journals from 1984 to 2020. Based on the Scopus database, all published articles related to high organization performance were compiled and integrated as the data. VOS viewer (visualization of similarities) Publish or Perish and Microsoft Exel software has been used to process the collected data. A total of 199 documents were analyzed and found much of the high-performance organization-related work was conducted in the United States and the Netherlands. Mainly, business management and social sciences have been focused in high-performance organization literature however other important areas such as Material science, Pharmaceutics, Chemical Engineering, Chemistry, and Mathematics have been ignored and paid less attention. This study examines the history of the HPO scientific literature and identifies current research objectives, as well as future research paths and dimensions in the field. Success, Performance.
关于高性能组织(HPO)的讨论出现于1984年初。高绩效组织的术语吸引了学者们对高绩效组织的概念、相关因素及其对组织目标的影响进行研究。此后，学者们频繁使用“高性能组织”这一术语来进一步研究这一概念在这一领域的发展。本研究的目的是对1984年至2020年在Scopus期刊上发表的关于高绩效组织的文献进行系统回顾。以Scopus数据库为基础，对所有已发表的与组织高绩效相关的文章进行整理和整合作为数据。使用VOS查看器(相似度可视化)Publish or Perish和Microsoft Exel软件对收集到的数据进行处理。总共分析了199份文件，发现许多与组织有关的高绩效工作是在美国和荷兰进行的。企业管理和社会科学主要集中在高性能组织文献中，而其他重要领域，如材料科学、制药学、化学工程、化学和数学，则被忽视和关注较少。本研究考察了HPO科学文献的历史，并确定了当前的研究目标，以及该领域未来的研究路径和维度。成功,性能。
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