@inproceedings{9389b0d0b0224c1494f52b8c2b35a79d,
title = "Using Information System Success Model to Explore Graduate Students{\textquoteright} Satisfaction and Individual Impact Toward the Use of National Digital Library of Theses and Dissertations in Taiwan",
abstract = "The National Digital Library of Theses and Dissertations in Taiwan (NDLTD hereafter) is the largest and most comprehensive information system for academic theses and dissertations in Taiwan. It serves as a vital resource for numerous graduate students who seek to access and utilize relevant information during their research endeavors. By searching and browsing past research studies, students can further develop their own research topics. Moreover, upon completion of their studies, students can share their findings online with other researchers. Despite the extensive usage of NDLTD, there has been a lack of investigation into user satisfaction and its individual impact. Therefore, this study aims to explore the satisfaction levels and individual effects experienced by graduate students when using this system based on the Information System Success Model. This research seeks to provide insights into graduate students{\textquoteright} usage of the system and can serve as a reference for future system optimization and enhancements.",
keywords = "Information System Success Model, National Library, Theses and Dissertations System",
author = "Hung, {Wei Hsiang} and Hsieh, {Yi Shan} and Lin, {Chin Cheng} and Chen, {Bing Yi} and Ke, {Hao Ren}",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 25th International Conference on Asia-Pacific Digital Libraries, ICADL 2023 ; Conference date: 04-12-2023 Through 07-12-2023",
year = "2023",
doi = "10.1007/978-981-99-8088-8_5",
language = "English",
isbn = "9789819980871",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "62--68",
editor = "Goh, {Dion H.} and Shu-Jiun Chen and Suppawong Tuarob",
booktitle = "Leveraging Generative Intelligence in Digital Libraries",
}