The Electronic Library

vLex
Publisher:
Emerald Group Publishing Limited
Publication date:
2021-02-01
ISBN:
0264-0473

Issue Number

Latest documents

  • What is effective digital reading? A systematic review of the effectiveness factors of digital reading

    Purpose: The rapid development of digital reading has made it a mainstream reading method for the public, and scholars have conducted research on its effectiveness.The purpose of this study is to systematically summarize and generalize the factors that affect the effectiveness of digital reading in current practical research. Design/methodology/approach: Retrieved the search results from the Web of Science database and the China National Knowledge Infrastructure database, collected the relevant literature in both Chinese and English on the effectiveness of digital reading, qualitatively coded the relevant literature, and conducted a systematic literature review analysis on the factors affecting the effectiveness of digital reading. Findings: There are 37 factors that influence the effectiveness of digital reading, forming five factor themes, namely, the reading subject, reading environment, organizational support, technical support and reading text. The five influencing factor themes are further divided into three types of functional mechanisms, namely, driving, supportive and assurance mechanisms. Based on this, a research framework is proposed, providing a comprehensive approach for the research positioning of digital reading effectiveness. Originality/value: A research framework is proposed, providing a comprehensive approach for the research positioning of digital reading effectiveness.

  • The effect of trust on user adoption of AI-generated content

    Purpose: The purpose of this study is to examine the effect of trust on user adoption of artificial intelligence-generated content (AIGC) based on the stimulus–organism–response. Design/methodology/approach: The authors conducted an online survey in China, which is a highly competitive AI market, and obtained 504 valid responses. Both structural equation modelling and fuzzy-set qualitative comparative analysis (fsQCA) were used to conduct data analysis. Findings: The results indicated that perceived intelligence, perceived transparency and knowledge hallucination influence cognitive trust in platform, whereas perceived empathy influences affective trust in platform. Both cognitive trust and affective trust in platform lead to trust in AIGC. Algorithm bias negatively moderates the effect of cognitive trust in platform on trust in AIGC. The fsQCA identified three configurations leading to adoption intention. Research limitations/implications: The main limitation is that more factors such as culture need to be included to examine their possible effects on trust. The implication is that generative AI platforms need to improve the intelligence, transparency and empathy, and mitigate knowledge hallucination to engender users’ trust in AIGC and facilitate their adoption. Originality/value: Existing research has mainly used technology adoption theories such as unified theory of acceptance and use of technology to examine AIGC user behaviour and has seldom examined user trust development in the AIGC context. This research tries to fill the gap by disclosing the mechanism underlying AIGC user trust formation.

  • A semantic network analysis of categorization in open government data portals

    Purpose: This study aims to evaluate the semantic relationships between category terms that are used in open government data (OGD) portals and those identified in policy documents through the implementation of a semantic network analysis. Design/methodology/approach: This study was conducted in three stages. Firstly, the study examined the semantic relationships between category terms in OGD portals by constructing a similarity matrix based on the terms’ co-occurrence and visualizing six-word groups. Secondly, the study investigated the semantic relationships among terms in OGD policy documents using latent semantic analysis and community detection methods, resulting in the identification and visualization of three network groups. Finally, the study used chi-squared and Z-tests to analyse differences in category terms between countries with and without redefined categories. Findings: The results indicate that the three-word groups were identified by community detection, covering various aspects of government. In addition, there is a significant difference between the two country groups, with category terms being more prevalent in countries with predefined categories. This emphasizes the impact of categorization on term prevalence within OGD portals. Originality/value: This study uniquely focuses on the categorization of government portals for sustainable open data management. The findings underscore the importance of effectively structuring and organizing data categories to enhance user discoverability and accessibility in OGD portals.

  • Editorial: Innovation measurement for scientific communication (IMSC) in the era of big data
  • Factors influencing the adoption of extended reality (XR) applications in libraries for sustainable innovative services: a systematic literature review (SLR)

    Purpose: This study aims to identify the factors influencing the adoption of extended reality (XR) applications in libraries for sustainable innovative services and reveal the challenges of adopting XR technology in libraries. Design/methodology/approach: A systematic literature review was applied to address the study’s objectives. The 26 most relevant seminal studies published in peer-reviewed journals were selected to conduct the study. Findings: The findings showed that access to digital collections, skill development, marketing, innovation and sustainable development factors influence the adoption of extended reality applications in libraries. The study illustrated that technical challenges, financial challenges, the unavailability of staff expertise and lack of institutional support caused barriers to the adoption of XR in libraries. Originality/value: The study has added valuable literature to the existing body of knowledge. It has provided a framework to efficiently adopt extended reality in libraries for the delivery of sustainable, innovative services to library patrons.

  • Impact of big data and data analytics on the provision of data services in academic libraries

    Purpose: The purpose of this study is to determine the level of awareness among library and information science (LIS) professionals regarding the perceived utility of big data (BD) and data analytics (DA) in academic libraries, as well as their influence on the provision of data services (DSs). Design/methodology/approach: A cross-sectional survey was carried out to collect the data for this study. The population of this study comprised LIS professionals working in public sector university libraries. A four-factor measurement model estimating the influence of BD and DA on the provision of DSs in academic libraries was tested using the structural equation modelling. Findings: The findings revealed that awareness (AW) (β = 0.141, CR = 2.534, p = 0.011) demonstrated a significant positive influence on the provision of DSs. The perceived utility of BD (β = 0.058, CR = 0.582, p = 0.561), and perceived utility of DA (β = 0.141, CR = 2.534, p = 0.905) exhibits a positive but statistically non-significant impact on the provision of DSs (β = 0.010, CR = 0.120, p = 0.905). The goodness of fit indices suggest a favourable fit for the model, as evidenced by the following values: χ2 = 1.400, DF = 164; p = 0.001; IFI = 0.954; TLI = 0.946; CFI = 0.953; GFI = 0.906; and RMSEA = 0.043. Originality/value: A new perspective on the use of BD and DA in academic libraries is presented in this study. It presents a four-factor measurement model on the influence of BD and DA on the provision of DSs in university libraries.

  • Revisiting the TAM: adapting the model to advanced technologies and evolving user behaviours

    Purpose: The purpose of this study is to examine the applicability of the technology acceptance model (TAM) in libraries considering the advanced technologies and users’ behaviour. Design/methodology/approach: The research uses a critical reflective approach to review and synthesize a body of recent academic literature on the use of TAM in libraries. The review included assessing TAM’s historical evolution, its limitations and how it could be improved. Findings: The findings indicated that, although TAM can be viewed as an appropriate theoretical model to explain the users’ intention towards technology acceptance, it is limited in explaining both the users’ attitude towards advanced technology and their behaviour in advanced library settings. Research limitations/implications: To enhance the practicality of TAM in libraries, several recommendations for strategic advancements have been proposed such as contextualizing TAM to libraries, exploring AI-driven adoption, integrating library-specific constructs, understanding cultural differences and using holistic research approaches. Originality/value: The findings contribute to a deeper understanding of technology adoption in libraries and to the future possibilities of TAM.

  • An assessment of whether educated non-researcher audiences understand how to reuse research data

    Purpose: The purpose of this study is to assess whether educated non-researcher audiences understand how to reuse research data stored in a data repository. Design/methodology/approach: A total of 44 participants in two user studies were asked to study a data set accessed from re3data.org. The participants were non-researcher audiences of the disciplines of the selected data sets. They were asked to figure out whether they understood how to reuse a data set after reading all the metadata or contextual information about the data set. Findings: Most participants reported that they figured out how to reuse the data, although their self-reports can be an overestimated assessment. However, the participants understand how to reuse a data set either numerically or statistically significantly worse than what the data set is, how it was collected or created and its purpose. Data set type tends to play a role in understanding how to reuse data sets and the purpose of data sets. Participants reported that unless a data set is self-explanatory, instructions on data set reuse and the purpose of data set were necessary for understanding how to reuse data set. However, because data reuse requires domain knowledge and data processing skills, some non-researcher audiences who lack domain knowledge and data processing skills may not understand how to reuse the data set in any way. Research limitations/implications: This study’s findings enrich the theoretical framework of data sharing and reuse by expanding the necessary information to be included in data documentation to support non-researchers’ data reuse. The findings of the study complement previous literature. Practical implications: This study extended previous literature by suggesting detailed data reuse instructions be included in data documentation if data producers and data curators wish to support educated non-researchers’ data reuse. This study’s findings enable policymakers of research data management (RDM) to formulate guidelines for supporting non-researchers’ data reuse. If data curators need to work with data producers to prepare the instructions on data reuse for non-researcher audiences, they probably need computing and data processing skills. This has implications for Library and Information Science schools to educate data librarians. Originality/value: The research question is original because non-researcher audiences in the context of RDM have not been studied before. This study extended previous literature by suggesting detailed data reuse instructions be included in data documentation if data curators and data producers and data curators wish to support educated non-researchers’ data reuse. This study’s findings enable policymakers of RDM to formulate guidelines for supporting non-researchers’ data reuse.

  • Determinants of ChatGPT adoption among students in higher education: the moderating effect of trust

    Purpose: ChatGPT is a cutting-edge chatbot powered by artificial intelligence that could revolutionise and advance the teaching and learning process. Drawing on the technology acceptance model (TAM) and information system (IS) success model, this study aims to investigate determinants of students’ intention to use ChatGPT for education purposes. Design/methodology/approach: The partial least squares technique was used to analyse 406 usable data collected from university students in Malaysia. Findings: The results confirmed the relationships between perceived usefulness (PU), perceived ease of use (PEU), attitude and intention to use proposed by TAM. PU and PEU are influenced by system quality. Surprisingly, trust in information moderates negatively the influences of PEU and PU on attitude. Practical implications: The findings provide insight for higher education institutions, unit instructors and ChatGPT developers on what may promote the use of ChatGPT in higher education. Originality/value: The study contributes to the literature by exploring the determinants of ChatGPT adoption, extending the TAM model by incorporating IS success factors and assessing the moderating effect of trust in information.

  • Analysis of knowledge services efficiency and influencing factors of public libraries in China: a mixed study based on the SBM model and dynamic QCA

    Purpose: The core objective of this study is to provide an in-depth quantitative assessment of the efficiency of public library knowledge services (PLKS) in China and to scrutinize the factors that have a significant impact on the efficiency of PLKS. Furthermore, this study also aims to examine the characteristics and evolving patterns of PLKS in China and to propose strategies for enhancing the quality of services provided by public libraries. The findings of this paper are expected to provide valuable references for current academic research and practice areas, guiding and promoting exploration and development in related fields. Design/methodology/approach: To analyse and evaluate the operation mechanism and efficiency of PLKS, this study creatively constructs a multi-stage PLKS efficiency evaluation model and provides related indicators. Based on this process, the super-efficiency network slacks-based measure model was used to analyse the efficiency, and dynamic qualitative comparative analysis was adopted to analyse the recipes about the influencing factors of PLKS. Ultimately, through a comprehensive interpretation of the measured data and the integration of extant societal development conditions, the authors put forth relevant recommendations. Findings: In the first stage, PLKS in China meets the basic requirements, but in the second stage, there is evident resource wastage. In addition, there are five recipes in PLKS of China. These five recipes reveal the configuration relationship between the factors that affect PLKS. The results show that PLKS in China are different in different regions, and the effects of the influencing factors are also different. Originality/value: In this study, the authors provide an exhaustive deconstruction and interpretation of PLKS, thereby proposing a three-stage PLKS efficiency conversion process. Furthermore, the authors have identified a set of readily accessible and quantifiable indicators. It is worth emphasizing that the authors have taken a unique approach to analyse the elements affecting PLKS from the perspective of configuration, which has significantly broadened the boundaries and depth of PLKS research.

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