Research on Factors Affecting Behavioral Intention of Graduate Students to Use Mobile Library in Suzhou, China
DOI:
https://doi.org/10.14456/shserj.2024.47Keywords:
System Quality, Information Quality, Attitude, Behavioral Intention, Mobile LibraryAbstract
Purpose: Mobile library or digital library has increasingly gained adoption each year from academic users in China. Thus, this research paper investigates the significant factors affecting the behavioral intention to use mobile libraries at Soochow University, Suzhou University of Science and Technology, and Xi'an Jiaotong-Liverpool University among graduate students. The framework considers the causal relationships between system quality, information quality, service quality, perceived ease of use, perceived usefulness, attitude, and behavior intention. Research design, data, and methodology: The study used a quantitative research method (n=500) to survey graduate students who experienced the mobile library. The sampling methods included judgmental, quota, and convenience sampling. The data analysis included structural equation modeling (SEM) and confirmatory factor analysis (CFA) for model fit, reliability, and construct validity. Results: The results reveal that attitude and perceived usefulness significantly affect students' intention to use the mobile library. Perceived ease of use has a significant effect on perceived usefulness and attitude. System quality, information quality, service quality, and perceived ease of use significantly affect behavioral intention. Conclusions: The study has successfully proven eight hypotheses, and the authors suggested that the types and contents of information resources in mobile libraries should be enriched.
References
Aharony, N. (2014). Mobile libraries: librarians' and students' perspectives. College & Research Libraries, 75(2), 202-217. https://doi.org/10.5860/crl12-415
Ajab Mohideen, Z., Sheikh, A., & Kaur, K. (2022). Developing an open-source mobile app in library services: the case of a national university in Malaysia. Digital Library Perspectives, 38(3), 283-300. https://doi.org/10.1108/DLP-08-2021-0064
Barnes, S. J., & Vidgen, R. T. (2014). Technology socialness and Web site satisfaction. Technological Forecasting and Social Change, 89, 12-25. https://doi.org/10.1016/j.techfore.2014.08.017
Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238.
https://doi.org/https://doi.org/10.1037/0033-2909.107.2.238
Bland, J. M., & Altman, D. G. (1997). Cronbach's alpha. BMJ, 314(7), 572-572.
Bridgett, D. J., Burt, N. M., Edwards, E. S., & Deater-Deckard, K. (2015). Intergenerational transmission of self-regulation: A multidisciplinary review and integrative conceptual framework. Psychological bulletin, 141(3), 602.
https://doi.org/10.1037/a0038662
Chaputula, A. H., & Mutula, S. (2018). Provision of library and information services through mobile phones in public university libraries in Malawi. Global Knowledge, Memory and Communication, 67(1/2), 52-69.
https://doi.org/10.1108/GKMC-05-2017-0048
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
Duncan, A. S. P. (2021). A library at the touch of a finger-tip: an analysis of mobile library services at the University of the West Indies, Mona campus. Library Hi Tech News, 38(1), 14-17. https://doi.org/10.1108/LHTN-06-2020-0059
Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019). Re-examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model. Information Systems Frontiers, 21, 719-734.
https://doi.org/10.1007/s10796-017-9774-y
Fam, K. S., Brito, P. Q., Gadekar, M., Richard, J. E., Jargal, U., & Liu, W. (2019). Consumer attitude towards sales promotion techniques: a multi-country study. Asia Pacific Journal of Marketing and Logistics, 31(2), 437-463.
https://doi.org/10.1108/APJML-01-2018-0005
Fan, L., Zhang, X., Rai, L., & Du, Y. (2021). Mobile payment: the next frontier of payment systems? an empirical study based on push-pull-mooring framework. Journal of theoretical and applied electronic commerce research, 16(2), 155-169.
https://doi.org/10.4067/S0718-18762021000200111
Farahany, N. A. (2015). Neuroscience and behavioral genetics in US criminal law: an empirical analysis. Journal of Law and the Biosciences, 2(3), 485-509. https://doi.org/10.1093/jlb/lsv059
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.2307/3151312
Gerber, N., Gerber, P., & Volkamer, M. (2018). Explaining the privacy paradox: A systematic review of literature investigating privacy attitude and behavior. Computers & security, 77, 226-261. https://doi.org/10.1016/j.cose.2018.04.002.
Heinrichs, J. H., Lim, K. S., Lim, J. S., & Spangenberg, M. A. (2014). Determining factors of academic library web site usage. Journal of the Association for Information Science & Technology, 58(14), 2325-2334. https://doi.org/10.1002/asi.20710.
Hess, T. J., McNab, A. L., & Basoglu, K. A. (2014). Reliability generalization of perceived ease of use, perceived usefulness, and behavioral intentions. Mis Quarterly, 38(1), 1-28. https://www.jstor.org/stable/26554866.
Ho, K. F., Ho, C. H., & Chung, M. H. (2019). Theoretical integration of user satisfaction and technology acceptance of the nursing process information system. PLoS One, 14(6), e0217622. https://doi.org/10.1371/journal.pone.0217622
Hoffman, D. L., & Novak, T. P. (2009). Flow online: lessons learned and future prospects. Journal of Interactive Marketing, 23(1), 23-34. https://doi.org/10.1016/j.intmar.2008.10.003
Hopwood, C. J., & Donnellan, M. B. (2010). How should the internal structure of personality inventories be evaluated? Personality and social psychology review, 14(3), 332-346. https://doi.org/10.1177/1088868310361240
Hu, J., & Zhang, Y. (2016). Chinese students’ behavior intention to use mobile library apps and effects of education level and discipline. Library Hi Tech, 34(4), 639-656. https://doi.org/10.1108/lht-06-2016-0061.
Huang, C. (2017). Time spent on social network sites and psychological well-being: A meta-analysis. Cyberpsychology, Behavior, and Social Networking, 20(6), 346-354. https://doi.org/10.1089/cyber.2016.0758
Huang, S., Weiler, B., & Assaker, G. (2015). Effects of interpretive guiding outcomes on tourist satisfaction and behavioral intention. Journal of Travel Research, 54(3), 344-358. https://doi.org/10.1177/0047287513517426.
Joo, S., & Choi, N. (2016). Understanding users’ continuance intention to use online library resources based on an extended expectation-confirmation model. The Electronic Library, 34(4), 554-571. https://doi.org/10.1108/EL-02-2015-0033
Koh, J. H. L., & Kan, R. Y. P. (2020). Perceptions of learning management system quality, satisfaction, and usage: Differences among students of the arts. Australasian Journal of Educational Technology, 36(3), 26-40.
https://doi.org/10.14742/ajet5187
Kroski, E. (2008). On the move with the mobile web: libraries and mobile technologies. Library technology reports, 44(5), 1-48. http://hdl.handle.net/10760/12463.
Landrum, H., Prybutok, V. R., & Zhang, X. (2010). The moderating effect of occupation on the perception of information services quality and success. Computers & Industrial Engineering, 58(1), 133-142. https://doi.org/10.1016/j.cie.2009.09.006
Lee, H. J., & Yang, K. (2013). Interpersonal service quality, self-service technology (sst) service quality, and retail patronage. Journal of Retailing & Consumer Services, 20(1), 51-57. https://doi.org/10.1016/j.jretconser.2012.10.005
Lee, J., & Kwon, K. H. (2022). Mobile shopping beauty live commerce changes in COVID‐19 pandemic focused on fun contents of MZ generation in Republic of Korea. Journal of Cosmetic Dermatology, 21(6), 2298-2306.
https://doi.org/10.1111/jocd.14442
Liao, J. J. Z. (2010). Sample size calculation for an agreement study. Pharmaceutical Statistics, 9(2), 125-132.
https://doi.org/10.1002/pst.382
Majumder, M. G., Gupta, S. D., & Paul, J. (2022). Perceived usefulness of online customer reviews: A review mining approach using machine learning & exploratory data analysis. Journal of Business Research, 150, 147-164.
https://doi.org/10.1016/j.jbusres.2022.06.012
Mansouri, A., & Asl, N. S. (2019). Assessing mobile application components in providing library services. The Electronic Library, 37(1), 49-66. https://doi.org/10.1108/EL-10-2018-0204
McKinney, V., Yoon, K., & Zahedi, F. M. (2002). The measurement of web-customer satisfaction: An expectation and disconfirmation approach. Information systems research, 13(3), 296-315. https://doi.org/10.1287/isre.13.3.296.76
Min, Y., Yang, M., Huang, J., & Duangekanong, S. (2023). Influencing Factors of Behavior Intention of Master of Arts Students Towards Online Education in Chengdu Public Universities, China. Scholar: Human Sciences, 15(1), 1-10.
https://doi.org/10.14456/shserj.2023.1
Moon, J. W., & Kim, Y. G. (2001). Extending the tam for a world-wide-web context. Information & Management, 38(4), 217-230. https://doi.org/10.1016/S0378-7206(00)00061-6
Nikou, S. A., & Economides, A. A. (2017). Mobile-based assessment: Investigating the factors that influence behavioral intention to use. Computers & Education, 109, 56-73. https://doi.org/10.1016/j.compedu.2017.02.005
Noh, M. (2022). Effect of parental financial teaching on college students’ financial attitude and behavior: The mediating role of self-esteem. Journal of Business Research, 143, 298-304. https://doi.org/10.1016/j.jbusres.2022.01.054
Novita, D., & Husna, N. (2020). The influence factors of consumer behavioral intention towards online food delivery services. TECHNOBIZ: International Journal of Business, 3(2), 40-42. https://doi.org/10.33365/tb.v3i2.840
Ocran, T. K., Underwood, P. G., & Arthur, P. A. (2020). Strategies for successful implementation of mobile phone library services. The Journal of Academic Librarianship, 46(5), 102174. https://doi.org/10.1016/j.acalib.2020.102174
Parasuraman, A., Zeithaml, V. A., & Berry, L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12-40. https://www.researchgate.net/publication/200827786
Rickly, J. M. (2022). A review of authenticity research in tourism: Launching the Annals of Tourism Research Curated Collection on authenticity. Annals of Tourism Research, 92, 103349. https://doi.org/10.1016/j.annals.2021.103349
Safakli, V. O. (2007). The SERVQAL dimensions unique to commercial banks: Case of Northern Cyprus. Marketing, 38(4), 139-146. https://scindeks.ceon.rs/article.aspx?artid=0354-3471 0704139S
Saghapour, M., Iranmanesh, M., Zailani, S., & Goh, G. G. G. (2018). An empirical investigation of campus portal usage. Education and Information Technologies, 23, 777-795. https://doi.org/10.1007/s10639-017-9635-9
Sanchez-Sabate, R., & Sabaté, J. (2019). Consumer attitudes towards environmental concerns of meat consumption: A systematic review. International journal of environmental research and public health, 16(7), 1220.
https://doi.org/10.3390/ijerph16071220
Seeholzer, J., & Salem, J. A. (2011). Library on the go: A focus group study of the mobile web and the academic library. College & Research Libraries, 72(1), 9-20. https://doi.org/10.5860/crl-65r1
Shamdasani, P., Mukherjee, A., & Malhotra, N. (2008). Antecedents and consequences of service quality in consumer evaluation of self-service internet technologies. Service Industries Journal, 28(1), 117-138.
https://doi.org/10.1080/02642060701725669
Sharma, S., Mukherjee, S., Kumar, A., & Dillon, W. R. (2005). A simulation study to investigate the use of cutoff values for assessing model fit in covariance structure models. Journal of Business Research, 58(7), 935-943.
https://doi.org/10.1016/j.jbusres.2003.10.007
Shroff, R. H., Trent, J., & Ng, E. M. W. (2013). Using e-portfolios in a field experience placement: examining student-teachers' attitudes towards learning in relationship to personal value, control and responsibility. Australasian Journal of Educational Technology, 29(2), 143-160. https://doi.org/10.14742/ajet51
Siagian, H., Tarigan, Z., & Ubud, S. (2022). The effect of electronic word of mouth on online customer loyalty through perceived ease of use and information sharing. International Journal of Data and Network Science, 6(4), 1155-1168.
https://doi.org/10.5267/j.ijdns.2022.7.004
Sica, C., & Ghisi, M. (2007). The Italian versions of the Beck Anxiety Inventory and the Beck Depression Inventory-II: Psychometric properties and discriminant power. In M. A. Lange (Ed.), Leading-edge psychological tests and testing research (pp. 27-50). Nova Science Publishers.
Song, Y. S., & Lee, J. M. (2012). Mobile device ownership among international business students: a road to the ubiquitous library. Reference Services Review, 40(4), 574-588. https://doi.org/10.1108/00907321211277378
Tahar, A., Riyadh, H. A., Sofyani, H., & Purnomo, W. E. (2020). Perceived ease of use, perceived usefulness, perceived security and intention to use e-filing: The role of technology readiness. The Journal of Asian Finance, Economics and Business (JAFEB), 7(9), 537-547. https://doi.org/10.13106/jafeb.2020.vol7.no9.537
Thong, J. Y., Hong, S. J., & Tam, K. Y. (2006). The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. International Journal of human-computer studies, 64(9), 799-810.
https://doi.org/10.1016/j.ijhcs.2006.05.001
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 27(3) 425-478. https://doi.org/10.2307/30036540
Wang, C. L., & Ahmed, P. K. (2013). The development and validation of the organisational innovativeness construct using confirmatory factor analysis. European Journal of Innovation Management, 7(4), 303-313(11).
https://doi.org/10.1108/14601060410565056
Wang, X., Yang, M., Li, J., & Wang, N. (2018). Factors of mobile library user behavioral intention from the perspective of information ecology. The Electronic Library, 36(4), 705-720. https://doi.org/10.1108/EL-03-2017-0046
Ward, M. A., & Mitchell, S. (2004). A comparison of the strategic priorities of public and private sector information resource management executives. Government Information Quarterly, 21(3), 284-304. https://doi.org/10.1016/j.giq.2004.04.003
Wei, Q., Chang, Z., & Cheng, Q. (2015). Usability study of the mobile library App: an example from Chongqing University. Library Hi Tech, 33(3), 340-355. https://doi.org/10.1108/LHT-05-2015-0047
Wheaton, B., Muthen, B., Alwin, D. F., & Summers, G. F. (1977). Assessing reliability and stability in panel models. Sociological methodology, 8, 84-136. https://doi.org/10.2307/270754
Won, D., Chiu, W., & Byun, H. (2023). Factors influencing consumer use of a sport-branded app: The technology acceptance model integrating app quality and perceived enjoyment. Asia Pacific Journal of Marketing and Logistics, 35(5), 1112-1133.
https://doi.org/10.1108/APJML-09-2021-0709
Wu, J. H., & Wang, Y. M. (2006). Measuring KMS success: A respecification of the DeLone and McLean's model. Information & management, 43(6), 728-739. https://doi.org/10.1016/j.im.2006.05.002
Xue, H., Guo, K., & He, F. (2022). Research on Personalized Recommendation Service of Mobile Library Based on User Portrait. In 2022 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA),689-692.
https://doi.org/10.1109/ICAICA54878.2022.9844517
Yip, K. H. T., Lo, P., Ho, K. K. W., & Chiu, D. K. W. (2021). Adoption of mobile library apps as learning tools in higher education: a tale between Hong Kong and Japan. Online Information Review, 45(2), 389-405.
https://doi.org/10.1108/OIR-07-2020-0287
Zadeh, P. A., Wang, G., Cavka, H. B., Staub-French, S., & Pottinger, R. (2017). Information quality assessment for facility management. Advanced Engineering Informatics, 33, 181-205. https://doi.org/10.1016/j.aei.2017.06.003
Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (1996). The behavioral consequences of service quality. Journal of Marketing, 60(2), 31-46. https://doi.org/10.1177/002224299606000203
Zhao, D. X., & Liu, Y. J. (2010). A Study on the Effect Factors of the Rural Resident Tourism Consumption. Tourism Forum, 3(01), 23-27. https://doi.org/10.7666/d.D378425
Zhao, Y., Deng, S., Gao, T., & Zhou, R. (2016). Research on user needs for mobile information services in Chinese university libraries: Comparison between existing user and potential users. The Electronic Library, 34(4), 617-635.
