{"title":"从UTAUT2的角度看,是什么推动了澳大利亚大学图书馆采用数据分析技术?","authors":"","doi":"10.1016/j.acalib.2024.102927","DOIUrl":null,"url":null,"abstract":"<div><p>This study investigates the adoption of data analytics in Australian university libraries from the UTAUT2 perspective, focusing on the factors that influence library professionals' acceptance of analytics. As technology advances, data has become a valuable resource, and the emergence of analytics is often considered a recent development driven by accessible computing power. However, there is a lack of comprehensive research on adopting analytics in Australian university libraries, highlighting the need for a deeper understanding of the factors that influence university library professionals’' perceptions of adopting analytics. This research addresses the main question: What factors drive the adoption of data analytics in Australian university libraries? This qualitative study employs a single case study approach with multiple sites involving 16 university libraries and 25 participants. Data collection methods included document analysis and semi-structured interviews with university librarians and analytics experts. The results show that all UTAUT2 constructs - performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, and habit - influence librarians' attitudes and motivations towards adopting analytics applications. Additionally, this study reveals additional factors beyond the original UTAUT2 model, including the absence of data analytics in LIS education curriculums, algorithm training, and data privacy concerns. The study identifies various benefits of analytics adoption in university libraries, such as enhanced collection development planning, insights into user behaviour, improved financial management, and demonstrating library value. However, challenges like skill shortages, complex IT configurations, and privacy legislation must be addressed to effectively implement data analytics. The findings contribute to our understanding of user acceptance of analytics in university libraries, providing valuable insights for library administrators and analytics vendors. By applying the UTAUT2 model, this research enriches our knowledge of technology adoption in the context of university libraries' analytics.</p></div>","PeriodicalId":47762,"journal":{"name":"Journal of Academic Librarianship","volume":null,"pages":null},"PeriodicalIF":2.5000,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0099133324000880/pdfft?md5=b5faf0f6d733606d0f8864c90156263e&pid=1-s2.0-S0099133324000880-main.pdf","citationCount":"0","resultStr":"{\"title\":\"What drives the adoption of data analytics at Australian university libraries in the perspective of UTAUT2?\",\"authors\":\"\",\"doi\":\"10.1016/j.acalib.2024.102927\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This study investigates the adoption of data analytics in Australian university libraries from the UTAUT2 perspective, focusing on the factors that influence library professionals' acceptance of analytics. As technology advances, data has become a valuable resource, and the emergence of analytics is often considered a recent development driven by accessible computing power. However, there is a lack of comprehensive research on adopting analytics in Australian university libraries, highlighting the need for a deeper understanding of the factors that influence university library professionals’' perceptions of adopting analytics. This research addresses the main question: What factors drive the adoption of data analytics in Australian university libraries? This qualitative study employs a single case study approach with multiple sites involving 16 university libraries and 25 participants. Data collection methods included document analysis and semi-structured interviews with university librarians and analytics experts. The results show that all UTAUT2 constructs - performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, and habit - influence librarians' attitudes and motivations towards adopting analytics applications. Additionally, this study reveals additional factors beyond the original UTAUT2 model, including the absence of data analytics in LIS education curriculums, algorithm training, and data privacy concerns. The study identifies various benefits of analytics adoption in university libraries, such as enhanced collection development planning, insights into user behaviour, improved financial management, and demonstrating library value. However, challenges like skill shortages, complex IT configurations, and privacy legislation must be addressed to effectively implement data analytics. The findings contribute to our understanding of user acceptance of analytics in university libraries, providing valuable insights for library administrators and analytics vendors. By applying the UTAUT2 model, this research enriches our knowledge of technology adoption in the context of university libraries' analytics.</p></div>\",\"PeriodicalId\":47762,\"journal\":{\"name\":\"Journal of Academic Librarianship\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2024-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0099133324000880/pdfft?md5=b5faf0f6d733606d0f8864c90156263e&pid=1-s2.0-S0099133324000880-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Academic Librarianship\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0099133324000880\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"INFORMATION SCIENCE & LIBRARY SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Academic Librarianship","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0099133324000880","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 0
摘要
本研究从UTAUT2的角度调查了澳大利亚大学图书馆采用数据分析的情况,重点关注影响图书馆专业人员接受分析的因素。随着技术的进步,数据已成为一种宝贵的资源,而分析技术的出现通常被认为是由可获得的计算能力推动的最新发展。然而,目前缺乏对澳大利亚大学图书馆采用分析技术的全面研究,这凸显了深入了解影响大学图书馆专业人员对采用分析技术的看法的因素的必要性。本研究探讨的主要问题是哪些因素推动了澳大利亚大学图书馆采用数据分析技术?本定性研究采用单一案例研究方法,涉及 16 所大学图书馆和 25 名参与者。数据收集方法包括文档分析以及对大学图书馆员和分析专家的半结构化访谈。研究结果表明,UTAUT2 的所有建构--绩效预期、努力预期、社会影响、便利条件、享乐动机、价格价值和习惯--都会影响图书馆员采用分析应用程序的态度和动机。此外,本研究还揭示了UTAUT2 原始模型之外的其他因素,包括图书情报学教育课程中数据分析的缺失、算法培训和数据隐私问题。研究指出了大学图书馆采用分析技术的各种益处,如加强馆藏发展规划、洞察用户行为、改善财务管理和展示图书馆价值。然而,要有效实施数据分析,必须应对技能短缺、复杂的 IT 配置和隐私立法等挑战。研究结果有助于我们了解用户对大学图书馆分析技术的接受程度,为图书馆管理人员和分析技术供应商提供有价值的见解。通过应用UTAUT2 模型,本研究丰富了我们对大学图书馆分析技术采用情况的了解。
What drives the adoption of data analytics at Australian university libraries in the perspective of UTAUT2?
This study investigates the adoption of data analytics in Australian university libraries from the UTAUT2 perspective, focusing on the factors that influence library professionals' acceptance of analytics. As technology advances, data has become a valuable resource, and the emergence of analytics is often considered a recent development driven by accessible computing power. However, there is a lack of comprehensive research on adopting analytics in Australian university libraries, highlighting the need for a deeper understanding of the factors that influence university library professionals’' perceptions of adopting analytics. This research addresses the main question: What factors drive the adoption of data analytics in Australian university libraries? This qualitative study employs a single case study approach with multiple sites involving 16 university libraries and 25 participants. Data collection methods included document analysis and semi-structured interviews with university librarians and analytics experts. The results show that all UTAUT2 constructs - performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, and habit - influence librarians' attitudes and motivations towards adopting analytics applications. Additionally, this study reveals additional factors beyond the original UTAUT2 model, including the absence of data analytics in LIS education curriculums, algorithm training, and data privacy concerns. The study identifies various benefits of analytics adoption in university libraries, such as enhanced collection development planning, insights into user behaviour, improved financial management, and demonstrating library value. However, challenges like skill shortages, complex IT configurations, and privacy legislation must be addressed to effectively implement data analytics. The findings contribute to our understanding of user acceptance of analytics in university libraries, providing valuable insights for library administrators and analytics vendors. By applying the UTAUT2 model, this research enriches our knowledge of technology adoption in the context of university libraries' analytics.
期刊介绍:
The Journal of Academic Librarianship, an international and refereed journal, publishes articles that focus on problems and issues germane to college and university libraries. JAL provides a forum for authors to present research findings and, where applicable, their practical applications and significance; analyze policies, practices, issues, and trends; speculate about the future of academic librarianship; present analytical bibliographic essays and philosophical treatises. JAL also brings to the attention of its readers information about hundreds of new and recently published books in library and information science, management, scholarly communication, and higher education. JAL, in addition, covers management and discipline-based software and information policy developments.