The College Students’ Behavioral Intention to Use Mobile Reading Apps in Sichuan, China

Main Article Content

Miao Hao

Abstract

Purpose: The purpose of this study is to investigate the college students’ behavioral intention to use mobile reading applications in Sichuan, China. The key variables include perceived usefulness, perceived ease of use, perceived value, perceived enjoyment, attitude, social influence, and behavioral intention. Research design, data, and methodology: The target population is 500 students from three universities in Sichuan. The quantitative research method used in this study was based on a questionnaire. The sampling technique contains judgmental, stratified random and convenience sampling. The content validity was confirmed by the index of item-objective congruence (IOC). The pilot test involves 50 participants to ensure reliability by Cronbach’s alpha. The data were analyzed by Confirmatory factor analysis (CFA) and Structural equation modeling (SEM). Results: The social influence presented the strongest effect on behavioral intention and proved that attitude directly influenced behavioral intention. The significant influences that support attitude are perceived ease of use, usefulness, value, and enjoyment. Conclusions: The research can help developers to develop effective mobile reading apps related to excellent traditional Chinese cultural knowledge. Educators can promote the dissemination of excellent traditional Chinese cultural knowledge can consider improving the influence of mobile phone reading content and software in society to help college students improve their learning efficiency.

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How to Cite
Hao, M. (2023). The College Students’ Behavioral Intention to Use Mobile Reading Apps in Sichuan, China. AU-GSB E-JOURNAL, 16(1), 121-130. https://doi.org/10.14456/augsbejr.2023.13
Section
Articles
Author Biography

Miao Hao

School of Literature, Journalist & Communication, Xihua University, China.

References

Abbad, M. M. (2013). E-banking in Jordan. Behavior and Information Technology, 32(7), 618-694.

Ajzen, I. (1989). Attitude structure and behavior. In A. R. Pratkanis, S. J. Breckler, & A. G. Greenwald (Eds.), Attitude structure and function (pp. 241–274). Lawrence Erlbaum Associates, Inc.

Allen, M., Titsworth, S., & Hunt, S. K. (2009). Quantitative Research Communication (1st ed.). Sage Publications.

Atanu, F., Avwioroko, O., Ilesanmi, O., & Oguche, M. (2019). Comparative Study of the Effects of Annona muricata and Tapinanthus globiferus Extracts on Biochemical Indices of Diabetic Rats. Journal in the field of Natural Products and Pharmacognosy, 11(6), 1365-1370.

Bagozzi, R., & Yi, Y. (1988). On the Evaluation of Structural Equation Models. Journal of the Academy of Marketing Sciences, 16, 74-94.

Bashir, I., & Madhavaiah, C. (2015). Consumer attitude and behavioural intention towards Internet banking adoption in India. Journal of Indian Business Research, 7(1), 67-102.

Benjangjaru, B., & Vongurai, R. (2018). Behavioral Intention of Bangkokians to Adopt Mobile Payment Services by Type of Users. AU-GSB E-JOURNAL, 11(1), 34-46.

Bigne, E., Ruiz, C., & Sanz, S. (2007). Key Drivers of Mobile Commerce Adoption. An Exploratory Study of Spanish Mobile Users. Electron. Commer, 2(2), 48-60.

Boonlert, J. (2020). Do monetary policy transparency and central bank communication reduce interest rate disagreement?. Journal of Forecasting, 39(3), 368-393.

Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen and J. S. Long (Eds.), Testing structural equation models (pp. 136-162). Sage.

Bruner, G. C., & Kumar, A. (2005). Explaining consumer acceptance of handheld internet devices. Journal of Business Research, 58(5), 553-558. https://doi.org/10.1016/j.jbusres.2003.08.002

Carla, Z., Piron, L., Turolla, A., & Agostini, M. (2009). Exercises for paretic upper limb after stroke: a combined virtual-reality and telemedicine approach. Journal of rehabilitation medicine, 41(12), 1016–1020.

Celik, H. (2008). What determines Turkish consumers’ acceptance of Internet banking?. International Journal of Bank Marketing, 26(5), 353-370.

Chalmers, A. (1976). What is This Thing Called Science (1st ed.). Open University Press.

Chong, A. Y., Ooi, K., Lin, B., & Tan, B. (2010). Online banking adoption: an empirical analysis. International Journal of Bank Marketing, 28(4). 267-287.

Clark-Carter, D. (2010). Quantitative Psychological Research: The Complete Student's Companion (3rd ed.). Taylor & Francis.

Cooper, D. R., & Schindler, P. S. (2011). Business Research Methods (11th ed.). Sage Publications.

Cronin, J. J., Brady, M. K., & Hult, G. T. M. (2000). Assessing the effects of quality, value, and customer satisfaction on consumer behavioral intentions in service environments. Journal of Retailing, 76(2), 193-218.

Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008

Ducoffe, R. (1996). Advertising value and advertising on the web. Journal of Advertising Research, 36(5), 21-39.

Filippini, R., & Forza, C. (1998). TQM impact on quality conformance and customer satisfaction: A causal model. International Journal of Production Economics, 55(1), 1-20.

Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research (1st ed.). Addison-Wesley.

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

Foroughi, B., Iranmanesh, M., & Hyun, S. S. (2019). Understanding the determinants of mobile banking continuance usage intention. Journal of Enterprise Information Management, 32(6), 1015-1033. https://doi.org/10.1108/jeim-10-2018-0237

Gao, L., & Bai, X. (2014). A unified perspective on the factors influencing consumer acceptance of internet of things technology. Asia Pacific Journal of Marketing and Logistics, 26(2), 211-231. https://doi.org/10.1108/APJML-06-2013-0061

Goldsmith, E. B. (2015). Social Influence and Sustainable Consumption (1st ed.). Springer.

Gu, J.-C., Lee, S.-C., & Suh, Y.-H. (2009). Determinants of behavioral intention to mobile banking. Expert Systems with Applications, 36(9), 11605-11616. https://doi.org/10.1016/j.eswa.2009.03.024

Hair, J. F., Arthur, H. M., Samouel, P., & Mike, P. (2007). Research Methods for Business (2nd ed.). John Wiley and Sons.

Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate Data Analysis (6th ed.). Pearson Prentice-Hall.

Hajli, M. N. (2014). A study of the impact of social media on consumers. International Journal of Market Research, 56(3), 387-404. https://doi.org/10.2501/ijmr-2014-025

Hernandez, A., Jiang, X., & Cubero, B. (2009). Mutants of the Arabidopsis thaliana cation/H+ antiporter AtNHX1 conferring increased salt tolerance in yeast: the endosome/prevacuolar compartment is a target for salt toxicity. J Biol Chem, 284(21), 14276-85.

Hua, G., & Haughton, D. (2009). Virtual worlds adoption: a research framework and empirical study. Online Information Review, 33(5), 889-900. https://doi.org/10.1108/14684520911001891

Igbaria, M., Guimaraes, T., & Davis, G. B. (1995). Testing the Determinants of Microcomputer Usage via a Structural Equation Model. Journal of Management Information Systems, 11(4), 87-114. https://doi.org/10.1080/07421222.1995.11518061

IResearch. (2019). China Mobile Reading Development Trend Report. www.iresearch.com.cns

Kim, S., & Garrison, G. (2009). Investigating Mobile Wireless Technology Adoption: An Extension of the Technology Acceptance Model. Information Systems Frontier, 11(3), 323-333.

Kitchen, P. J., Kerr, G., Mulhern, F., & Schultz, D. (2015). Does Traditional Advertising Theory Apply to the Digital World? A Replication Analysis Questions the Relevance of the Elaboration Likelihood Model. Journal of Advertising Research, 55(4), 390-400.

Kotler, P. (2000). Marketing Management (1st ed.). Prentice Hall.

Kucukusta, D., Law, R., Besbes, A., & Legohérel, P. (2015). Re-examining perceived usefulness and ease of use in online booking: The case of Hong Kong online users. International Journal of Contemporary Hospitality Management, 27(2), 185-198. https://doi.org/10.1108/ijchm-09-2013-0413

Kuo, Y.-F., & Yen, S.-N. (2009). Towards an understanding of the behavioral intention to use 3G mobile value-added services. Computers in Human Behavior, 25(1), 103-110. https://doi.org/10.1016/j.chb.2008.07.007

Lee, Y.-C. (2006). An empirical investigation into factors influencing the adoption of an e-learning system. Online Information Review, 30(5), 517-541. https://doi.org/10.1108/14684520610706406

Lee, Y.-K., Park, J.-H., Chung, N., & Blakeney, A. (2012). A unified perspective on the factors influencing usage intention toward mobile financial services. Journal of Business Research, 65(11), 1590-1599. https://doi.org/10.1016/j.jbusres.2011.02.044

Lin, H.-H., Wang, Y.-S., & Chang, L.-K. (2011). Consumer responses to online retailer's service recovery after a service failure: A perspective of justice theory. Managing Service Quality: An International Journal, 21(5), 511-534. https://doi.org/10.1108/09604521111159807

Malhotra, N. K. (2007). Marketing Research: An Applied Orientation (5th ed.). Pearson Prentice-Hall.

McDougall, G. H. G., & Levesque, T. (2000). Customer satisfaction with services: putting perceived value into the equation. Journal of Services Marketing, 14(5), 392-410. https://doi.org/10.1108/08876040010340937

McGowan, K., & Sternquist, B. (1998). Dimensions of price as a marketing universal: a comparison of Japanese and US consumers. Journal of International Marketing, 6(4), 49–65.

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

Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric Theory (3rd ed.). McGraw-Hill.

Paul, J., Modi, A., & Patel, J. D. (2015). Predicting green product consumption using theory of planned behavior and reasoned action. Journal of Retailing and Consumer Services, 29, 123-134

Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. (2004). Consumer acceptance of online banking: An extension of the Technology Acceptance Model. Internet Research, 14(3), 224-235.

Pinar, W. F. (2015). Educational Experience as Lived: Knowledge, History, Alterity (1st ed.). Routledge.

Pura, M. (2005). Linking perceived value and loyalty in location-based mobile services. Managing Service Quality, 15(6), 509-38.

Rama, M., Béteille, T., Li, Y., Mitra, P. K., & Newman, J. L. (2014). Addressing Inequality in South Asia, Addressing Inequality in South Asia. The World Bank,1(2), 11-20.

Rania, M., Maria, D., Carbone, E. A., & Greco, M. (2019). Brain-Behavior-Immune Interaction: Serum Cytokines and Growth Factors in Patients with Eating Disorders at Extremes of the Body Mass Index (BMI) Spectrum. Journal Nutrients, 11(9), 11-20.

Rui, H., Liu, Y., & Whinston, A. (2013). Whose and what chatter matters? The effect of tweets on movie sales. Decision Support Systems, 55(4), 863-870. https://doi.org/10.1016/j.dss.2012.12.022

Salois, M. J., & Reilly, A. (2014). Consumer Response to Perceived Value and Generic Advertising. Agricultural and Resource Economics Review, 43(1), 17-30. https://doi.org/10.1017/s1068280500006882

Sarmento, R., & Costa, V. (2019). Confirmatory Factor Analysis -- A Case study. Researchgate. 10(1), 11-23.

Sweeney, J. C., & Soutar, G. N. (2001). Consumer perceived value: The development of a multiple item scale. Journal of Retailing, 77(2), 203–220. https://doi.org/10.1016/S0022-4359(01)00041-0

Teo, T., Zhou, M., Fan, A. C. W., & Huang, F. (2019). Factors that influence university students' intention to use Moodle: a study in Macau. Educational Technology Research and Development, 67(3), 749-766. https://doi.org/10.1007/s11423-019-09650-x

Teo, T. S. H., & Pok, S. H. (2003). Adoption of the Internet and WAP-enabled phones in Singapore. Behaviour & Information Technology, 22(4), 281–289. https://doi.org/10.1080/0144929031000119385

Toft, M., Schuitema, G., & Thogersen, J. (2014). The importance of framing for consumer acceptance of the Smart Grid: A comparative study of Denmark, Norway and Switzerland. Energy Research & Social Science, 3, 113-123.

Turel, O., Serenko, A., & Bontis, N. (2007). User acceptance of wireless short messaging services: Deconstructing perceived value. Information & Management, 44(1), 63-73. https://doi.org/10.1016/j.im.2006.10.005

Vallerand, R. J. (1997). Toward a hierarchical model of intrinsic and extrinsic motivation. In M. P. Zanna (Ed.), Advances in experimental social psychology, Vol. 29, pp. 271–360). Academic Press. https://doi.org/10.1016/S0065-2601(08)60019-2

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.

Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1), 157-178.

Wang, H., Chung, J. E., Park, N., McLaughlin, M. L., & Fulk, J. (2012). Understanding Online Community Participation: A Technology Acceptance Perspective. Communication Research, 39(6), 781-801. https://doi.org/10.1177/0093650211408593

Watjatrakul, B. (2014). Factors affecting students' intentions to study at universities adopting the "student-as-customer" concept. International Journal of Educational Management, 28(6), 676-693. https://doi.org/10.1108/ijem-09-2013-0135

Webster, J., & Trevino, L. K. (1995). Rational and social theories as complementary explanations of communication media choices: Two policy-capturing studies. Academy of Management Journal, 38(6), 1544–1572. https://doi.org/10.2307/256843

Westerbeek, H. M., & Shilbury, D. (2003). A Conceptual Model for Sport Services Marketing Research: Integrating Quality, Value and Satisfaction. International Journal of Sports Marketing and Sponsorship, 5(1), 3-23. https://doi.org/10.1108/ijsms-05-01-2003-b002

Wu, B., & Zhang, C. (2014). Empirical study on continuance intentions towards E-Learning 2.0 systems. Behaviour & Information Technology, 33(10), 1027-1038. https://doi.org/10.1080/0144929x.2014.934291

Yin, R. K. (1994). Case Study Research Design and Methods: Applied Social Research and Methods Series (2nd ed.). Thousand Oaks.

Yoshida, M., & James, J. D. (2010). Customer Satisfaction With Game and Service Experiences: Antecedents and Consequences. Journal of Sport Management, 24(3), 338-361. https://doi.org/10.1123/jsm.24.3.338

Yousra, B. J., Mohammed, A. I., & Nabila, M. (2018). Gait-based human age classification using a silhouette model. IET Biometrics, 7(2), 116-124.

Zeithaml, V. A. (1988). Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence. Journal of Marketing, 52(3), 2-22. https://doi.org/10.1177/002224298805200302

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

Zeithaml, V. A., & Bitner, M. J. (1996). Customer Expectations of Service’s-Services Marketing (1st ed.). McGraw Hill.

Zhang, W. (2010). China's cultural future: from soft power to comprehensive national power. International Journal of Cultural Policy, 16(4), 383-402. https://doi.org/10.1080/10286630903134300

Zikmund, W. G. (2003). Business research methods (7th ed.). Thomas Learning.