Library Hi TechPub Date : 2023-11-30DOI: 10.1108/lht-09-2022-0420
Mehdi Dadkhah, F. Rahimnia, A. Memon
{"title":"Facilitators and barriers to dealing with questionable journals in management science","authors":"Mehdi Dadkhah, F. Rahimnia, A. Memon","doi":"10.1108/lht-09-2022-0420","DOIUrl":"https://doi.org/10.1108/lht-09-2022-0420","url":null,"abstract":"PurposeScientific publishing has recently faced challenges in dealing with questionable (predatory and hijacked) journals. The presence of questionable journals in any field, including management science, will yield junk science. Although there are studies about questionable journals in other fields, these journals have not yet been examined in the field of business and management. This study aims to identify facilitators and barriers to dealing with questionable journals in management science.Design/methodology/approachA Delphi research method consisting of three rounds was used in this study. Data were collected from 12 experts in the first two rounds, and ten experts in the final round.FindingsThe present study shows that management science is vulnerable to questionable journals. A total of 18 barriers and eight facilitators to dealing with questionable journals in management science were found. The present study also identifies some new barriers and facilitators for avoiding questionable journals, which are specific to management science and have not been identified in previous research. Most of these barriers and facilitators were identified as “important” or “very important”. Publishers and scientific databases, government, the research community and universities and research centers were identified as critical players in overcoming challenges posed by questionable journals.Originality/valueThe number of articles that investigate predatory journals in management science is limited, and there is no research focused specifically on hijacked journals in this field. This study identifies facilitators and obstacles to dealing with predatory and hijacked journals in the field of management, by gathering opinions from experts. Thus it is the first study to examine hijacked journals in the field of management science. It is also one of the few studies that examine predatory and hijacked journals by conducting exploratory research rather than with a descriptive/conceptual approach.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139200527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Library Hi TechPub Date : 2023-11-07DOI: 10.1108/lht-12-2023-590
Kevin K. W. Ho, Dickson K. W. Chiu
{"title":"Editorial: Special selection on advances in learning technologies","authors":"Kevin K. W. Ho, Dickson K. W. Chiu","doi":"10.1108/lht-12-2023-590","DOIUrl":"https://doi.org/10.1108/lht-12-2023-590","url":null,"abstract":"","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139283888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Library Hi TechPub Date : 2023-11-06DOI: 10.1108/lht-06-2023-0219
Hoi Ching Cheung, Yan Yin Marco Lo, Dickson K.W. Chiu, Elaine W.S. Kong
{"title":"Development of smart academic library services with Internet of Things technology: a qualitative study in Hong Kong","authors":"Hoi Ching Cheung, Yan Yin Marco Lo, Dickson K.W. Chiu, Elaine W.S. Kong","doi":"10.1108/lht-06-2023-0219","DOIUrl":"https://doi.org/10.1108/lht-06-2023-0219","url":null,"abstract":"Purpose This study examines academic librarians' perceptions and attitudes toward Internet of Things (IoT) applications in Hong Kong academic libraries and the problems and possible improvements in using IoT technologies to strengthen library services. Design/methodology/approach This qualitative research used video conferencing software for semi-structured, one-on-one interviews. Participants were given introductory material about the IoT and asked to complete an interview. The data were analyzed using inductive theme clustering for this study. Findings The analysis identified three themes: perception about applying IoT technology to the library, problems and improvements in using IoT. Participants were generally optimistic about the potential benefits of IoT for improving library operations and providing personalized services. However, they also expressed concerns about privacy and security, errors and extra efforts for information literacy training. They suggested improvements such as incorporating facial recognition technology, advanced RFID technology and collections identification technology to enhance user experience. Originality/value Most studies examined users' views rather than librarians' on IoT applications, which few studies cover, especially in East Asia.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135585247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Library Hi TechPub Date : 2023-10-30DOI: 10.1108/lht-06-2023-0265
Suhans Bansal, Naval Garg, Jagvinder Singh
{"title":"Perpetrators' perspective on cyberbullying: a qualitative systematic review with bibliometric analysis","authors":"Suhans Bansal, Naval Garg, Jagvinder Singh","doi":"10.1108/lht-06-2023-0265","DOIUrl":"https://doi.org/10.1108/lht-06-2023-0265","url":null,"abstract":"Purpose Cyberbullying has become one of the reasons behind the increase in psychological and medical problems. A need to prevent recurrences of cyberbullying incidents and discourage bullies from further bullying the victims has risen. This problem has attracted the attention of all stakeholders across the globe. Various researchers have developed theories and interventions to detect and stop bullying behavior. Previously, researchers focused on helping victims, but as the times have changed, so has the focus of researchers. This study aims to analyze scientific research articles and review papers to understand the development of the knowledge base on the topic. Design/methodology/approach This study analyzes the performance of literature on cyberbullying perpetration (CBP) using the widely accepted bibliometric analysis techniques: performance analysis and science mapping. The study is based on a dataset extracted from the Web of Science database. Initially, 2,792 articles between 2007 and 2022 were retrieved, which were filtered down to 441. The filter was based on various criteria, but primarily on CBP. VOSViewer and MS Excel were used to analyze the data. In addition, VOSViewer was used to create “bibliometric citations, co-citations, and co-word maps.” Findings The findings include publication and citation quantum and trends, the top 20 active countries, the most significant research articles and leading journals in this domain. Major themes or clusters identified were “Cyberbullying and victim behavior,” bullying behavior, adolescents and intervention, “cyberbullying associations,” and “cyberbullying personality associations.” Originality/value The study is unique because it analyses research articles based on cyberbullies, whereas past studies explored only the victims' side. Further, the present study used the Web of Science database, whereas most studies use the Scopus database.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136105933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Library Hi TechPub Date : 2023-10-23DOI: 10.1108/lht-02-2023-0063
Rongying Zhao, Weijie Zhu, He Huang, Wenxin Chen
{"title":"Social mediametrics: the mention laws and patterns of scientific literature","authors":"Rongying Zhao, Weijie Zhu, He Huang, Wenxin Chen","doi":"10.1108/lht-02-2023-0063","DOIUrl":"https://doi.org/10.1108/lht-02-2023-0063","url":null,"abstract":"Purpose Social mediametrics is a subfield of measurement in which the emphasis is placed on social media data. This paper analyzes the trends and patterns of paper comprehensively mentions on Twitter, with a particular focus on Twitter's mention behaviors. It uncovers the dissemination patterns and impact of academic literature on social media. The research has significant theoretical and practical implications. Design/methodology/approach This paper explores the fundamental attributes of Twitter mentions by means of analyzing 9,476 pieces of scholarly literature (5,097 from Nature and 4,379 from Science), 1,474,898 tweets and 451,567 user information collected from Altmetric.com database and Twitter API. The study uncovers assorted Twitter mention characteristics, mention behavior patterns and data accumulation patterns. Findings The findings illustrate that the top academic journals on Twitter have a wider range of coverage and display similar distribution patterns to other academic communication platforms. A large number of mentioners remain unidentified, and the distribution of follower counts among the mention users exhibits a significant Pareto effect, indicating a small group of highly influential users who generate numerous mentions. Furthermore, the proportion of sharing and exchange mentions positively correlates with the number of user followers, while the incidence of supportive mentions has a negative correlation. In terms of country-specific mention behavior, Thai scholars tend to utilize supportive mentions more frequently, whereas Korean scholars prefer sharing mentions over communicating mentions. The cumulative pattern of Twitter mentions suggests that these occur before official publication, with a half-life of 6.02 days and a considerable reduction in the number of mentions is observed on the seventh day after publication. Originality/value Conducting a multi-dimensional and systematic analysis of Twitter mentions of scholarly articles can aid in comprehending and utilizing social media communication patterns. This analysis can uncover literature's distribution patterns, dissemination effects and social significance in social media.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135366133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Library Hi TechPub Date : 2023-10-16DOI: 10.1108/lht-10-2022-0473
Chien-Wen Shen, Phung Phi Tran
{"title":"An assessment of blockchain academia and news developments: a bibliometric and text-mining analysis","authors":"Chien-Wen Shen, Phung Phi Tran","doi":"10.1108/lht-10-2022-0473","DOIUrl":"https://doi.org/10.1108/lht-10-2022-0473","url":null,"abstract":"Purpose This study aims to provide a more complete picture of blockchain development by combining numerous methodologies with diverse data sources, such as academic papers and news articles. This study displays the developmental status of each subject based on the interrelationships of each topic cluster by analyzing high-frequency keywords extracted from the collected data. Moreover, applying above methodologies will help understanding top research topics, authors, venues, institutes and countries. The differences of blockchain research and new are identified. Design/methodology/approach To identify and find blockchain development linkages, researchers have used search terms such as co-occurrence, bibliographic coupling, co-citation and co-authorship to help us understand the top research topics, authors, venues, institutes and countries. This study also used text mining analysis to identify blockchain articles' primary concepts and semantic structures. Findings The findings show the fundamental topics based on each topic cluster's links. While “technology”, “transaction”, “privacy and security”, “environment” and “consensus” were most strongly associated with blockchain in research, “platform”, “big data and cloud”, “network”, “healthcare and business” and “authentication” were closely tied to blockchain news. This article classifies blockchain principles into five patterns: hardware and infrastructure, data, networking, applications and consensus. These statistics helped the authors comprehend the top research topics, authors, venues, publication institutes and countries. Research limitations/implications Since Web of Science (WoS) and LexisNexis Academic data are used, the study has few sources. Others advise merging foreign datasets. WoS is one of the world's largest and most-used databases for assessing scientific papers. Originality/value This study has several uses and benefits. First, key concept discoveries can help academics understand blockchain research trends so they can prioritize research initiatives. Second, bibliographic coupling links academic papers on blockchain. It helps information seekers search and classify the material. Co-citation analysis results can help researchers identify potential partners and leaders in their field. The network's key organizations or countries should be proactive in discovering, proposing and creating new relationships with other organizations or countries, especially those from the journal network's border, to make the overall network more integrated and linked. Prominent members help recruit new authors to organizations or countries and link them to the co-authorship network. This study also used concept-linking analysis to identify blockchain articles' primary concepts and semantic structures. This may lead to new authors developing research ideas or subjects in primary disciplines of inquiry.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136078432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Library Hi TechPub Date : 2023-10-13DOI: 10.1108/lht-07-2023-0322
Mohd Afjal
{"title":"ChatGPT and the AI revolution: a comprehensive investigation of its multidimensional impact and potential","authors":"Mohd Afjal","doi":"10.1108/lht-07-2023-0322","DOIUrl":"https://doi.org/10.1108/lht-07-2023-0322","url":null,"abstract":"Purpose The aim of the study is to understand the transformative impact of ChatGPT on artificial intelligence (AI) research, its applications, implications, challenges and potential to shape future AI trends. The study also seeks to assess the relevance and quality of research output through citation and bibliographic coupling analysis. Design/methodology/approach This study employed a comprehensive bibliometric analysis using Biblioshiny and VOSviewer to investigate the research trends, influential entities and leading contributors in the domain of AI, focusing on the ChatGPT model. Findings The analysis revealed a high prevalence of AI-related terms, indicating a significant interest in and engagement with ChatGPT in AI studies and applications. “Nature” and “Thorp H.H.” emerged as the most cited source and author, respectively, while the USA surfaced as the leading contributor in the field. Research limitations/implications While the findings provide a comprehensive overview of the ChatGPT research landscape, it is important to note that the conclusions drawn are only as current as the data used. Practical implications The study highlights potential collaboration opportunities and signals areas of research that might benefit from increased focus or diversification. It serves as a valuable resource for researchers, practitioners and policymakers for strategic planning and decision-making in AI research, specifically in relation to ChatGPT. Originality/value This study is one of the first to provide a comprehensive bibliometric analysis of the ChatGPT research domain, its multidimensional impact and potential. It offers valuable insights for a range of stakeholders in understanding the current landscape and future directions of ChatGPT in AI.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135804786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Library Hi TechPub Date : 2023-09-15DOI: 10.1108/lht-04-2022-0168
Kaili Wang, Ke Dong, Jiachun Wu, Jiang Wu
{"title":"Patterns of artificial intelligence policies in China: a nationwide perspective","authors":"Kaili Wang, Ke Dong, Jiachun Wu, Jiang Wu","doi":"10.1108/lht-04-2022-0168","DOIUrl":"https://doi.org/10.1108/lht-04-2022-0168","url":null,"abstract":"Purpose The purpose of this paper is to identify the historical trends and status of the national development of artificial intelligence (AI) from a nationwide perspective and to enable governments at different administrative levels to promote AI development through policymaking. Design/methodology/approach This paper analyzed 248 Chinese AI policies (36 issued by the state agencies and 212 by the regional agencies). Policy bibliometrics, policy instruments and network analysis were used to reveal the AI policy patterns. Three aspects were analyzed: the spatiotemporal distribution of issued policies, the policy foci and instruments of policy contents and the cooperation and citation among policy-issuing agencies. Findings Results indicate that Chinese AI development is still in the initial phase. During the policymaking processes, the state and regional policy foci have strong consistency; however, the coordination among state and regional agencies is supposed to be strengthened. According to the issuing time of AI policies, Chinese AI development is in accordance with the global situation and has witnessed unprecedented growth in the last five years. And the coastal provinces have issued more targeted policies than the middle and western provinces. Governments at the state and regional levels have emphasized familiar policy foci and played the role of policymakers, along with regional governments that also functioned as policy executors as well. According to the three-dimension instruments coding, the authors found an uneven structure of policy instruments at both levels. Furthermore, weak cooperation appears at the state level, while little cooperation is found among regional agencies. Regional governments cite state policies, thus leading to the formation of top-down diffusion, lacking bottom-up diffusion. Originality/value The paper contributes to the literature by characterizing policy patterns from both external attributes and semantic contents, thus revealing features of policy distribution, contents and agencies. What is more, this research analyzes Chinese AI policies from a nationwide perspective, which contributes to clarifying the overall status and multi-level relationships of policies. The findings also benefit the coordinated development of governments during further policymaking processes.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135354037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Library Hi TechPub Date : 2023-09-12DOI: 10.1108/lht-02-2023-0076
Sumei Yao, Fan Wang, Jing Chen, Quan Lu
{"title":"Utilizing health-related text on social media for depression research: themes and methods","authors":"Sumei Yao, Fan Wang, Jing Chen, Quan Lu","doi":"10.1108/lht-02-2023-0076","DOIUrl":"https://doi.org/10.1108/lht-02-2023-0076","url":null,"abstract":"Purpose Social media texts as a data source in depression research have emerged as a significant convergence between Information Management and Public Health in recent years. This paper aims to sort out the depression-related study conducted on the text on social media, with particular attention to the research theme and methods. Design/methodology/approach The authors finally selected research articles published in Web of Science, Wiley, ACM Digital Library, EBSCO, IEEE Xplore and JMIR databases, covering 57 articles. Findings (1) According to the coding results, Depression Prediction and Linguistic Characteristics and Information Behavior are the two most popular themes. The theme of Patient Needs has progressed over the past few years. Still, there is a lesser focus on Stigma and Antidepressants. (2) Researchers prefer quantitative methods such as machine learning and statistical analysis to qualitative ones. (4) According to the analysis of the data collection platforms, more researchers used comprehensive social media sites like Reddit and Facebook than depression-specific communities like Sunforum and Alonelylife. Practical implications The authors recommend employing machine learning and statistical analysis to explore factors related to Stigmatization and Antidepressants thoroughly. Additionally, conducting mixed-methods studies incorporating data from diverse sources would be valuable. Such approaches would provide insights beneficial to policymakers and pharmaceutical companies seeking a comprehensive understanding of depression. Originality/value This article signifies a pioneering effort in systematically gathering and examining the themes and methodologies within the intersection of health-related texts on social media and depression.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135824533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Library Hi TechPub Date : 2023-09-12DOI: 10.1108/lht-04-2023-0138
Yunfei Xing, Yuming He, Justin Z. Zhang
{"title":"Examining themes of social media users' opinion on remote work during COVID-19 pandemic: a justice theory perspective","authors":"Yunfei Xing, Yuming He, Justin Z. Zhang","doi":"10.1108/lht-04-2023-0138","DOIUrl":"https://doi.org/10.1108/lht-04-2023-0138","url":null,"abstract":"Purpose The coronavirus disease 2019 (COVID-19) pandemic caused significant disruption to the global labor market, resulting in a rapid transition toward remote work, e-commerce and workforce automation. This shift has sparked a considerable amount of public discussion. This study aims to explore the online public's sentiment toward remote work amid the pandemic. Design/methodology/approach Based on justice theory, this paper examines user-generated content on social media platforms, particularly Twitter, to gain insight into public opinion and discourse surrounding remote work during the COVID-19 pandemic. Employing content analysis techniques such as sentiment analysis, text clustering and evolutionary analysis, this study aims to identify prevalent topics, temporal patterns and instances of sentiment polarization in tweets. Findings Results show that people with positive opinions focus mainly on personal interests, while others focus on the interests of the company and society; people's subjectivities are higher when they express extremely negative or extremely positive emotions. Distributive justice and interactional justice are distinguishable with a high degree of differentiation in the cluster map. Originality/value Previous research has inadequately addressed public apprehensions about remote work during emergencies, particularly from a justice-based perspective. This study seeks to fill this gap by examining how justice theory can shed light on the public's views regarding corporate policy-making during emergencies. The results of this study provide valuable insights and guidance for managing public opinion during such events.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135824705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}