Library Hi Tech最新文献

{"title":"Bibliometric analyses and network mapping on the smart library in Web of Science from 2003 to 2021","authors":"Dan Wang","doi":"10.1108/lht-08-2022-0361","DOIUrl":"https://doi.org/10.1108/lht-08-2022-0361","url":null,"abstract":"PurposeThis research conducts bibliometric analyses and network mapping on smart libraries worldwide. It examines publication profiles, identifies the most cited publications and preferred sources and considers the cooperation of the authors, organizations and countries worldwide. The research also highlights keyword trends and clusters and finds new developments and emerging trends from the co-cited references network.Design/methodology/approachA total of 264 records with 1,200 citations were extracted from the Web of Science database from 2003 to 2021. The trends in the smart library were analyzed and visualized using BibExcel, VOSviewer, Biblioshiny and CiteSpace.FindingsThe People’s Republic of China had the most publications (119), the most citations (374), the highest H-index (12) and the highest total link strength (TLS = 25). Wuhan University had the highest H-index (6). Chiu, Dickson K. W. (H-index = 4, TLS = 22) and Lo, Patrick (H-index = 4, TLS = 21) from the University of Hong Kong had the highest H-indices and were the most cooperative authors. Library Hi Tech was the most preferred journal. “Mobile library” was the most frequently used keyword. “Mobile context” was the largest cluster on the research front.Research limitations/implicationsThis study helps librarians, scientists and funders understand smart library trends.Originality/valueThere are several studies and solid background research on smart libraries. However, to the best of the author’s knowledge, this study is the first to conduct bibliometric analyses and network mapping on smart libraries around the globe.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42672635","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}

{"title":"The role of personality traits and the ability to detect fake news in predicting information avoidance during the COVID-19 pandemic","authors":"M. Mirzabeigi, Mahsa Torabi, Tahere Jowkar","doi":"10.1108/lht-03-2022-0150","DOIUrl":"https://doi.org/10.1108/lht-03-2022-0150","url":null,"abstract":"PurposeThe objective of this study was to investigate the impacts of personality traits and the ability to detect fake news on information avoidance behavior. It also examined the effect of personality traits on the ability to detect fake news.Design/methodology/approachThe sample population included Shiraz University students who were studying in the second semester of academic year 2021 in different academic levels. It consisted of 242 students of Shiraz University. The Big Five theory was used as the theoretical background of the study. Moreover, the research instrument was an electronic questionnaire consisting of the three questionnaires of the ability to detect fake news (Esmaeili et al., 2019, inspired by IFLA, 2017), the Big Five personality traits (Goldberg, 1999) and information avoidance (Howell and Shepperd, 2016). The statistical methods used to analyze the data were Pearson correlation and stepwise regression, which were performed through SPSS software (version 26).FindingsThe results showed that from among the five main personality factors, only neuroticism had a positive and significant effect on information avoidance. In addition, the ability to detect fake news had a significant negative effect on information avoidance behavior. Further analyses also showed positive and significant effects of openness to experience and extraversion on the ability to detect fake news. In fact, the former had more predictive power.Practical implicationsFollowing the Big Five theory considering COVID-19 information avoidance and the ability to detect COVID-19 fake news, this study shifted the focus from environmental factors to personality factors and personality traits. Furthermore, this study introduced the ability to detect fake news as an influential factor in health information avoidance behaviors, which can be a prelude for new research studies.Originality/valueThe present study applied the five main personality factors theory in the context of information avoidance behavior and the ability to detect fake news, and supported the effect of personality traits on these variables.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42230457","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}

{"title":"Opening the black box of Library Hi Tech: a social network and bibliometric analysis","authors":"Guijie Zhang, Fangfang Wei, Peixin Wang","doi":"10.1108/lht-12-2022-0556","DOIUrl":"https://doi.org/10.1108/lht-12-2022-0556","url":null,"abstract":"PurposeThis paper presents a comprehensive study using bibliometric and social network analysis (SNA) to depict the academic community, research hotspots and the correlation between research performance and social network measurements within Library Hi Tech.Design/methodology/approachPublications from Library Hi Tech between 2010 and 2022 are reviewed and analysed through coauthorship analysis, co-occurrence analysis, SNA and the Spearman rank correlation test.FindingsThe annual number of publications in Library Hi Tech increased from 2016 to 2022, indicating that this research has gradually gained global attention. The USA and China are the most significant contributors to the relevant publications. Scholars in this field mainly engage in small-scale cooperation. Academic libraries, digital libraries, libraries, information technology and COVID-19 were hot topics during the study period. In light of the COVID-19 pandemic, there was a marked increase in research on healthcare. Academic interest in the internet of Things and social media has proliferated recently and may soon attract more attention. Spearman rank correlation analysis shows that research performance (i.e. publication count and citation count) is significantly and positively correlated with social network measurements (i.e. degree centrality, betweenness centrality, closeness centrality and eigenvector centrality) in studies of Library Hi Tech.Originality/valueThis paper reveals a systematic picture of the research landscape of Library Hi Tech and provides a potential guide for future research. The relationship between scientific research performance and social network measurements can be objectively identified based on statistical knowledge.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46416816","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}

{"title":"Library book recommendation with CNN-FM deep learning approach","authors":"Xiaohua Shi, Chen Hao, Ding Yue, Hongtao Lu","doi":"10.1108/lht-08-2022-0400","DOIUrl":"https://doi.org/10.1108/lht-08-2022-0400","url":null,"abstract":"PurposeTraditional library book recommendation methods are mainly based on association rules and user profiles. They may help to learn about students' interest in different types of books, e.g., students majoring in science and engineering tend to pay more attention to computer books. Nevertheless, most of them still need to identify users' interests accurately. To solve the problem, the authors propose a novel embedding-driven model called InFo, which refers to users' intrinsic interests and academic preferences to provide personalized library book recommendations.Design/methodology/approachThe authors analyze the characteristics and challenges in real library book recommendations and then propose a method considering feature interactions. Specifically, the authors leverage the attention unit to extract students' preferences for different categories of books from their borrowing history, after which we feed the unit into the Factorization Machine with other context-aware features to learn students' hybrid interests. The authors employ a convolution neural network to extract high-order correlations among feature maps which are obtained by the outer product between feature embeddings.FindingsThe authors evaluate the model by conducting experiments on a real-world dataset in one university. The results show that the model outperforms other state-of-the-art methods in terms of two metrics called Recall and NDCG.Research limitations/implicationsIt requires a specific data size to prevent overfitting during model training, and the proposed method may face the user/item cold-start challenge.Practical implicationsThe embedding-driven book recommendation model could be applied in real libraries to provide valuable recommendations based on readers' preferences.Originality/valueThe proposed method is a practical embedding-driven model that accurately captures diverse user preferences.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41735479","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}

{"title":"Lockdowns during the COVID-19 pandemic among small island developing states and Guam","authors":"Leila C. Kabigting, M. Ruane, Kristina C. Sayama","doi":"10.1108/lht-12-2022-0574","DOIUrl":"https://doi.org/10.1108/lht-12-2022-0574","url":null,"abstract":"PurposeDuring the COVID-19 pandemic, lockdowns were implemented to achieve two goals: (1) to reduce the number of COVID-19 cases and (2) to reduce the number of COVID-19 deaths. In this paper, the authors aim to look at empirical evidence on how effectively lockdowns achieved these goals among small island developing states (SIDS) and for one specific SIDS economy, Guam.Design/methodology/approachThe authors reviewed existing studies to form two hypotheses: that lockdowns reduced cases, and that lockdowns reduced deaths. Defining a lockdown as a positive value for Oxford COVID-19 government response tracker, OxCGRT's stringency index, the authors tested the above hypotheses on 185 countries, 27 SIDS economies and Guam using correlation and regression analyses, and using different measures of the strictness, duration and timing of the lockdown.FindingsThe authors found no evidence to support the hypothesis that lockdowns reduced the number of cases based on data for all 185 countries and 27 SIDS economies. While the authors found evidence to support the hypothesis in the case of Guam, the result required an unrealistically and implausibly long time lag of 365 days. As to the second hypothesis that lockdowns reduced the number of deaths, the authors found no evidence to support it for 185 countries, 27 SIDS economies as well as Guam.Originality/valueFrom the review of the existing literature, the authors are the first to conduct this type of study among SIDS economies as a group and on Guam.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46426077","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}

{"title":"How gamification and social interaction stimulate MOOCs continuance intention via cognitive presence, teaching presence and social presence?","authors":"Yung-Ming Cheng","doi":"10.1108/lht-03-2022-0160","DOIUrl":"https://doi.org/10.1108/lht-03-2022-0160","url":null,"abstract":"PurposeThis study's purpose is to propose a research model based on the stimulus-organism-response (S-O-R) model to examine whether gamification and social interaction as environmental stimulus antecedents to learners' perceptions of presence can affect their continuance intention of massive open online courses (MOOCs).Design/methodology/approachSample data for this study were collected from learners who had experience in taking gamified MOOCs provided by the MOOC platform launched by a well-known university in Taiwan, and 353 usable questionnaires were analyzed using structural equation modeling (SEM).FindingsThis study demonstrated that learners' perceived gamification, learner–instructor interaction and learner–learner interaction in MOOCs positively affected their cognitive presence, teaching presence and social presence elicited by MOOCs, which jointly expounded their continuance intention of MOOCs. The results support all proposed hypotheses, and the research model accounts for 72.6% of the variance in learners' MOOCs continuance intention.Originality/valueThis study employs the S-O-R model as a theoretical umbrella to frame learners' MOOCs continuance intention as a series of the internal process, which is influenced by gamification and social interaction. Noteworthily, three psychological constructs of the community of inquiry model (i.e. cognitive presence, teaching presence and social presence) are adopted to represent learners' internal experiences of MOOCs usage. To date, hedonic/utilitarian concepts are more commonly adopted as organisms in prior studies based on the S-O-R model, whereas psychological constructs have received lesser attention. Hence, this study enriches the S-O-R model into an invaluable context.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46874384","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}

{"title":"Adoption of big data analytics for sustainability of library services in academic libraries of Pakistan","authors":"M. Azam, K. Ahmad","doi":"10.1108/lht-12-2022-0584","DOIUrl":"https://doi.org/10.1108/lht-12-2022-0584","url":null,"abstract":"PurposeThis paper aims to measure the adoption of big data analytics (BDA) to achieve sustainability in services being offered in university libraries in Pakistan.Design/methodology/approachThe study applied a unified theory of acceptance and use of technology (UTAUT) as a framework and used quantitative data collection and analysis method. In total, 246 university library professionals were surveyed using a questionnaire consisting of UTAUT factors. The gathered data were analyzed using partial least structural equation modeling (PLS-SEM).FindingsThe results showed that performance expectancy (PE), effort expectancy (EE) and social influence (SI) significantly impacted the behavioral intention (BI) to adopt BDA. Facilitating conditions (FCs) have a statistically significant influence on the adoption of big data in libraries, while BDA has a statistical influence on the sustainability of library services (SLS).Practical implicationsBDA assists libraries in making better decisions about demand-driven collection creation, library space management, usage tracking, and quality maintenance in routine and repetitive library tasks such as cataloging, indexing, archiving, administration, preservation and representation. BDA supports libraries in making more cost-effective, innovative, user-oriented services, resource transferring, social identity, resource utilization, healthier user experience, strategic planning, informed decision-making and state-of-the-art infrastructure.Originality/valueThe foundation of this study is based on information gathered from various sources and university libraries in Punjab to better understand the challenges associated with using BDA for the SLS in Pakistan.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49284189","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}

{"title":"School library reading support for students with dyslexia: a qualitative study in the digital age","authors":"Qingyun Li, Jenny Wong, Dickson K. W. Chiu","doi":"10.1108/lht-03-2023-0086","DOIUrl":"https://doi.org/10.1108/lht-03-2023-0086","url":null,"abstract":"PurposeThis paper investigates school library services in the digital age for students with dyslexia and explores the impact of current library services on students’ learning.Design/methodology/approachA qualitative study with semi-structured interviews was designed according to the LAFE (Look and listen, Assistance and accessibility, Format and fit, and Environment) framework for learners with dyslexia and the 5E instructional model and conducted with 11 school librarians.FindingsResults indicated that participants lacked knowledge of dyslexia for appropriate library services. Awareness, IT skills, school administration, funding and parental attitudes would influence the library’s tailored services to dyslexic children, despite the rich resources in these participants’ libraries, including paperbacks, digital resources and electronic devices. Adaptations are necessary to provide accessible services, especially by applying digital technologies, and school libraries can positively impact students’ reading interests, promote knowledge inquiry and strengthen information literacy skills.Originality/valueWhile students with dyslexia spend significant time in schools, limited studies focus on school library services in the digital age, especially in Asia. This study fills the gap by systematically exploring the issue with the 5E instructional model.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44196841","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}

{"title":"The shift in research trends related to artificial intelligence in library repositories during the coronavirus pandemic","authors":"Prasetyo Adi Nugroho, N. Anna, Noraini Ismail","doi":"10.1108/lht-07-2022-0326","DOIUrl":"https://doi.org/10.1108/lht-07-2022-0326","url":null,"abstract":"PurposeThis study sought to analyze the correlation between artificial intelligence (AI) and libraries and examine whether there were any shifts in research trends related to these two topics during the coronavirus pandemic.Design/methodology/approachThe study gathered secondary data from the Scopus website using the keywords “AI,” “library” and “repository,” from 1993 to 2022. Data were re-analyzed using the bibliometric software VOSviewer to examine the trending country's keyword relations and appearance and Biblioshiny to study the publication metadata.FindingsIndex keywords, such as “human,” “deep learning,” “machine learning,” “surveys” and “open-source software,” became popular during 2020, being closely related to digital libraries. Additionally, the annual scientific production of papers increased significantly in 2021. Words related to data mining also had the most significant growth from 2019 to 2022 because of the importance of data mining for library services during the pandemic.Practical implicationsThis study provides insight for librarians for the implementation of AI to support repositories during the pandemic. Librarians can learn how to maximize the AI-based repository services in academic libraries during the pandemic. Furthermore, academic libraries can create policies for repository services using AI.Social implicationsThis study can lead researchers, academicians and practitioners in conducting research on AI in library repositories.Originality/valueAs research on AI and digital repositories remains limited, the study identifies themes and highlights the knowledge gap existing in the field.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47756125","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}

{"title":"Voice search behavior under human–vehicle interaction context: an exploratory study","authors":"Shaobo Liang, Linfeng Yu","doi":"10.1108/lht-04-2022-0174","DOIUrl":"https://doi.org/10.1108/lht-04-2022-0174","url":null,"abstract":"PurposeAs voice search has progressively become a new way of information acquisition and human–computer interaction, this paper aims to explore the users' voice search behavior in human–vehicle interaction.Design/methodology/approachThis study employed mixed research methods, including questionnaires and interviews. A total of 151 Amazon MTurk volunteers were recruited to complete a questionnaire based on their most recent and impressive voice search experience. After the questionnaire, this paper conducted an online interview with the participants.FindingsThis paper studied users' voice search behavior characteristics in the context of the human–vehicle interaction and analyzed the voice search content, search need, search motivation and user satisfaction. In addition, this paper studied the barriers and suggestions for voice search in human–vehicle interaction through a content analysis of the interviews.Practical implicationsThis paper's analysis of users' barriers and suggestions has a specific reference value for optimizing the voice search interaction system and improving the service.Originality/valueThis study is exploratory research that seeks to identify users' voice search needs and tasks and investigate voice search satisfaction in human–vehicle interaction context.","PeriodicalId":47196,"journal":{"name":"Library Hi Tech","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2023-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42367832","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}