The impact of flow, satisfaction and reputation on loyalty to MOOCs: the moderating role of extrinsic motivation

References

• Abdullatif, H., & Velázquez-Iturbide, J. Á. (2020). Relationship between motivations, personality traits and intention to continue using MOOCs. Education and Information Technologies, 25(5), 4417–4435. https://doi.org/10.1007/s10639-020-10161-z
   Web of Science ®Google Scholar
• Adam, S., & Nel, D. (2009). Blended and online learning: Student perceptions and performance. Interactive Technology and Smart Education, 6(3), 140–155. https://doi.org/10.1108/17415650911005366
   Google Scholar
• Adams Becker, S., Cummins, M., Davis, A., Freeman, A., Hall Giesinger, C., & Ananthanarayanan, V. (2017). NMC Horizon report: 2017 higher education edition. The New Media Consortium. https://www.sconul.ac.uk/sites/default/files/documents/2017-nmc-horizon-report-he-EN.pdf
   Google Scholar
• Alario-Hoyos, C., Estévez-Ayres, I., Pérez-Sanagustín, M., Kloos, C. D., & Fernández-Panadero, C. (2017). Understanding learners’ motivation and learning strategies in MOOCs. International Review of Research in Open and Distributed Learning, 18(3), 119–137. https://doi.org/10.19173/irrodl.v18i3.2996
   Web of Science ®Google Scholar
• Ali Abbasi, G., Kumaravelu, J., Goh, Y.-N., Singh, K., & Singh, D. (2021). Understanding the intention to revisit a destination by expanding the theory of planned behaviour (TPB). Spanish Journal of Marketing-ESIC, 25(2), 280–307. https://doi.org/10.1108/SJME-12-2019-0109
   Google Scholar
• Ali, F., Zhou, Y., Hussain, K., Nair, P. K., & Ragavan, N. A. (2016). Does higher education service quality effect student satisfaction, image and loyalty? A study of international students in Malaysian public universities. Quality Assurance in Education, 24(1), 70–94. https://doi.org/10.1108/QAE-02-2014-0008
   Web of Science ®Google Scholar
• Anderson, R. E., & Srinivasan, S. S. (2003). E-satisfaction and e-loyalty: A contingency framework. Psychology & Marketing, 20(2), 123–138. https://doi.org/10.1002/mar.10063
   Web of Science ®Google Scholar
• Arquero, J. L., Del Barrio-García, S., & Romero-Frías, E. (2017). What drives students’ loyalty-formation in social media learning within a personal learning environment approach? The moderating role of need for cognition. Journal of Educational Computing Research, 55(4), 495–525. https://doi.org/10.1177/0735633116672056
   Web of Science ®Google Scholar
• Barba, P. G., Kennedy, G. E., & Ainley, M. D. (2016). The role of students‘ motivation and participation in predicting performance in a MOOC. Journal of Computer Assisted Learning, 32(3), 218–231. https://doi.org/10.1111/jcal.12130
   Web of Science ®Google Scholar
• Bozkurt, A., Akgün-Özbek, E., & Zawacki-Richter, O. (2017). Trends and patterns in massive open online courses: Review and content analysis of research on MOOCs (2008-2015). International Review of Research in Open and Distance Learning, 18(5), 118–147. https://doi.org/10.19173/irrodl.v18i5.3080
   Google Scholar
• Brooker, A., Corrin, L., De Barba, P., Lodge, J., & Kennedy, G. (2018). A tale of two MOOCs: How student motivation and participation predict learning outcomes in different MOOCs. Australasian Journal of Educational Technology, 34(1), 73–87. https://doi.org/10.14742/ajet.3237
   Web of Science ®Google Scholar
• Casaló, L., Flavián, C., & Guinalíu, M. (2008). The role of perceived usability, reputation, satisfaction and consumer familiarity on the website loyalty formation process. Computers in Human Behavior, 24(2), 325–345. https://doi.org/10.1016/j.chb.2007.01.017
   Web of Science ®Google Scholar
• Castaño-Muñoz, J., Kalz, M., Kreijns, K., & Punie, Y. (2018). Who is taking MOOCs for teachers’ professional development on the use of ICT? A cross-sectional study from Spain. Technology, Pedagogy and Education, 27(5), 607–624. https://doi.org/10.1080/1475939X.2018.1528997
   Web of Science ®Google Scholar
• Chang, Y. P., & Zhu, D. H. (2012). The role of perceived social capital and flow experience in building users’ continuance intention to social networking sites in China. Computers in Human Behavior, 28(3), 995–1001. https://doi.org/10.1016/j.chb.2012.01.001
   Web of Science ®Google Scholar
• Chen, Y., Gao, Q., Yuan, Q., & Tang, Y. (2020). Discovering MOOC learner motivation and its moderating role. Behaviour & Information Technology, 39(12), 1257–1275. https://doi.org/10.1080/0144929X.2019.1661520
   Web of Science ®Google Scholar
• Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling: A Multidisciplinary Journal, 9(2), 233–255. https://doi.org/10.1207/S15328007SEM0902_5
   Web of Science ®Google Scholar
• Csikszentmihalyi, M. (1975). Beyond boredom and anxiety. Jossey-Bass.
   Google Scholar
• Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. Plenum Press.
   Google Scholar
• Dehghan, A., Dugger, J., Dobrzykowski, D., & Balazs, A. (2014). The antecedents of student loyalty in online programs. International Journal of Educational Management, 28(1), 15–35. https://doi.org/10.1108/IJEM-01-2013-0007
   Google Scholar
• Deshpande, A., & Chukhlomin, V. (2017). What makes a good MOOC: A field study of factors impacting student motivation to learn. American Journal of Distance Education, 31(4), 275–293. https://doi.org/10.1080/08923647.2017.1377513
   Web of Science ®Google Scholar
• Dick, A. S., & Basu, K. (1994). Customer loyalty: Toward an integrated conceptual framework. Journal of the Academy of Marketing Science, 22(2), 99–113. https://doi.org/10.1177/0092070394222001
   Google Scholar
• Doña Toledo, L., & Luque Martínez, T. (2020). How loyal can a graduate ever be? The influence of motivation and employment on student loyalty. Studies in Higher Education, 45(2), 353–374. https://doi.org/10.1080/03075079.2018.1532987
   Web of Science ®Google Scholar
• Downes, S. (2008). Places to go: Connectivism & connective knowledge. Innovate: Journal of Online Education, 5(1), 6. https://nsuworks.nova.edu/innovate/vol5/iss1/6
   Google Scholar
• Ebben, M., & Murphy, J. S. (2014). Unpacking MOOC scholarly discourse: A review of nascent MOOC scholarship. Learning, Media and Technology, 39(3), 328–345. https://doi.org/10.1080/17439884.2013.878352
   Web of Science ®Google Scholar
• Fırat, M., Kılınç, H., & Yüzer, T. V. (2018). Level of intrinsic motivation of distance education students in e‐learning environments. Journal of Computer Assisted Learning, 34(1), 63–70. https://doi.org/10.1111/jcal.12214
   Web of Science ®Google Scholar
• 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/10.1177/002224378101800104
   Web of Science ®Google Scholar
• George, B., & Prybutok, V. (2015). Development of a polar extreme method for use in partial least squares SEM. Quality & Quantity, 49(2), 471–488. https://doi.org/10.1007/s11135-014-0004-0
   Web of Science ®Google Scholar
• Ghani, J. A., & Deshpande, S. P. (1994). Task characteristics and the experience of optimal flow in human-computer interaction. The Journal of Psychology, 128(4), 381–391. https://doi.org/10.1080/00223980.1994.9712742
   Web of Science ®Google Scholar
• Guinaliu-Blasco, M., Hernández-Ortega, B., & Franco, J. L. (2019). The effect of cognitive absorption on marketing learning performance. Spanish Journal of Marketing-ESIC, 23(2), 249–271. https://doi.org/10.1108/SJME-10-2018-0048
   Google Scholar
• Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Prentice Hall.
   Google Scholar
• Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate data analysis (7th ed.). Pearson.
   Google Scholar
• Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2014). A primer on partial least squares structural equation modeling (PLS-SEM) (1st ed.). SAGE Publications.
   Google Scholar
• Han, H., & Ryu, K. (2009). The roles of the physical environment, price perception, and customer satisfaction in determining customer loyalty in the restaurant industry. Journal of Hospitality & Tourism Research, 33(4), 487–510. https://doi.org/10.1177/1096348009344212
   Web of Science ®Google Scholar
• Helm, S., Eggert, A., & Garnefeld, I. (2010). Modeling the impact of corporate reputation on customer satisfaction and loyalty using partial least squares. In V. E. Vinzi, W. W. Chin, J. Henseler, & H. Wang(Eds.), Handbook of partial least squares (pp. 515–534). Springer.
   Google Scholar
• Hernández-Mogollón, J. M., Di-Clemente, E., & Campón-Cerro, A. M. (2020). Culinary travel experiences, quality of life and loyalty. Spanish Journal of Marketing-ESIC, 24(3), 425–446. https://doi.org/10.1108/SJME-11-2019-0094
   Google Scholar
• Hsu, C. L., Wu, C. C., & Chen, M. C. (2013). An empirical analysis of the antecedents of e-satisfaction and e-loyalty: Focusing on the role of flow and its antecedents. Information Systems and e-Business Management, 11(2), 287–311. https://doi.org/10.1007/s10257-012-0194-8
   Web of Science ®Google Scholar
• Islam, A. A. (2014). Validation of the Technology Satisfaction Model (TSM) developed in higher education: The application of structural equation modeling. International Journal of Technology and Human Interaction, 10(3), 44–57. https://doi.org/10.4018/ijthi.2014070104
   Google Scholar
• Jin, B., Yong Park, J., & Kim, J. (2008). Cross-cultural examination of the relationships among firm reputation, e-satisfaction, e-trust, and e-loyalty. International Marketing Review, 25(3), 324–337. https://doi.org/10.1108/02651330810877243
   Web of Science ®Google Scholar
• Johnson, L., Adams Becker, S., Cummins, M., Estrada, V., Freeman, A., & Ludgate, H. (2013). NMC Horizon report: 2013 higher education edition. The New Media Consortium. https://library.educause.edu/resources/2013/2/2013-horizon-report
   Google Scholar
• Jones, M. A., & Suh, J. (2000). Transaction-specific satisfaction and overall satisfaction: An empirical analysis. Journal of Service Marketing, 14(2), 147–159. https://doi.org/10.1108/08876040010371555
   Google Scholar
• Jones, T. O., & Sasser, W. E. (1995). Why satisfied customers defect. Harvard Business Review, 73(6), 88–102. http://www.van-haaften.nl/images/documents/pdf/Why_satisfied_customers_defect.pdf
   Web of Science ®Google Scholar
• Joo, Y. J., So, H. J., & Kim, N. H. (2018). Examination of relationships among students’ self-determination, technology acceptance, satisfaction, and continuance intention to use K-MOOCs. Computers & Education, 122(July), 260–272. https://doi.org/10.1016/j.compedu.2018.01.003
   Google Scholar
• Junjie, Z. (2017). Exploring the factors affecting learners’ continuance intention of MOOCs for online collaborative learning: An extended ECM perspective. Australasian Journal of Educational Technology, 33(5), 123–135. https://doi.org/10.14742/ajet.2914
   Web of Science ®Google Scholar
• Khan, I. U., Hameed, Z., Yu, Y., Islam, T., Sheikh, Z., & Khan, S. U. (2018). Predicting the acceptance of MOOCs in a developing country: Application of task-technology fit model, social motivation, and self-determination theory. Telematics and Informatics, 35(4), 964–978. https://doi.org/10.1016/j.tele.2017.09.009
   Web of Science ®Google Scholar
• Kizilcec, R. F., & Schneider, E. (2015). Motivation as a lens to understand online learners: Toward data-driven design with the OLEI scale. ACM Transactions on Computer-Human Interaction (TOCHI), 22(2), 1–24. https://doi.org/10.1145/2699735
   Web of Science ®Google Scholar
• Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behaviour. Information Systems Research, 13(2), 205–223. https://doi.org/10.1080/10864415.2001.11044233
   Web of Science ®Google Scholar
• Lee, B. C., Yoon, J. O., & Lee, I. (2009). Learners’ acceptance of e-learning in South Korea: Theories and results. Computers & Education, 53(4), 1320–1329. https://doi.org/10.1016/j.compedu.2009.06.014
   Web of Science ®Google Scholar
• Lee, M. C., & Tsai, T. R. (2010). What drives people to continue to play online games? An extension of technology model and theory of planned behavior. International Journal of Human–Computer Interaction, 26(6), 601–620. https://doi.org/10.1080/10447311003781318
   Web of Science ®Google Scholar
• Littlejohn, A., Hood, N., Milligan, C., & Mustain, P. (2016). Learning in MOOCs: Motivations and self-regulated learning in MOOCs. The Internet and Higher Education, 29(April), 40–48. https://doi.org/10.1016/j.iheduc.2015.12.003
   Google Scholar
• Liu, M., Zou, W., Shi, Y., Pan, Z., & Li, C. (2019). What do participants think of today’s MOOCs: An updated look at the benefits and challenges of MOOCs designed for working professionals. Journal of Computing in Higher Education, 32(2), 307–329. https://doi.org/10.1007/s12528-019-09234-x
   Web of Science ®Google Scholar
• Martin, N., Kelly, N., & Terry, P. C. (2018). A framework for self-determination in massive open online courses: Design for autonomy, competence, and relatedness. Australasian Journal of Educational Technology, 34(2), 35–55. https://doi.org/10.14742/ajet.3722
   Web of Science ®Google Scholar
• Milligan, C., & Littlejohn, A. (2017). Why study on a MOOC? The motives of students and professionals. International Review of Research in Open and Distributed Learning, 18(2), 92–102. https://doi.org/10.19173/irrodl.v18i2.3033
   Web of Science ®Google Scholar
• Monferrer, D., Moliner, M. A., & Estrada, M. (2019). Increasing customer loyalty through customer engagement in the retail banking industry. Spanish Journal of Marketing-ESIC, 23(3), 461–484. https://doi.org/10.1108/SJME-07-2019-0042
   Google Scholar
• 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
   Web of Science ®Google Scholar
• Mulik, S., Srivastava, M., Yajnik, N., & Taras, V. (2020). Antecedents and outcomes of flow experience of MOOC users. Journal of International Education in Business, 13(1), 1–19. https://doi.org/10.1108/JIEB-10-2018-0049
   Web of Science ®Google Scholar
• Namestovski, Ž., Major, L., Molnár, G., Szűts, Z., Esztelecki, P., & Kőrösi, G. (2018). External motivation, the key to success in the MOOCs framework. Acta Polytechnica Hungarica, 15(6), 125–142. http://acta.uni-obuda.hu/Namestovski_Major_Molnar_Szuts_Esztelecki_Korosi_85.pdf
   Web of Science ®Google Scholar
• Nesset, E., & Helgesen, Ø. (2009). Modelling and managing student loyalty: A study of a Norwegian university college. Scandinavian Journal of Educational Research, 53(4), 327–345. https://doi.org/10.1080/00313830903043117
   Web of Science ®Google Scholar
• Nikou, S. A., & Economides, A. A. (2017). Mobile-based assessment: Integrating acceptance and motivational factors into a combined model of self-determination theory and technology acceptance. Computers in Human Behavior, 68(March), 83–95. https://doi.org/10.1016/j.chb.2016.11.020
   Google Scholar
• Oh, E. G., Chang, Y., & Park, S. W. (2019). Design review of MOOCs: Application of e-learning design principles. Journal of Computing in Higher Education, 32(3), 455–475. https://doi.org/10.1007/s12528-019-09243-w
   Web of Science ®Google Scholar
• Pérez-Sanagustín, M., Hilliger, I., Alario-Hoyos, C., Kloos, C. D., & Rayyan, S. (2017). H-MOOC framework: Reusing MOOCs for hybrid education. Journal of Computing in Higher Education, 29(1), 47–64. https://doi.org/10.1007/s12528-017-9133-5
   Web of Science ®Google Scholar
• Perin, M. G., Sampaio, C. H., Simões, C., & de Pólvora, R. P. (2012). Modeling antecedents of student loyalty in higher education. Journal of Marketing for Higher Education, 22(1), 101–116. https://doi.org/10.1080/08841241.2012.705797
   Google Scholar
• Romero-Frías, E., Arquero, J. L., & Del Barrio-García, S. (2020). Exploring how student motivation relates to acceptance and participation in MOOCs. Interactive Learning Environments, 1–17. https://doi.org/10.1080/10494820.2020.1799020
   Web of Science ®Google Scholar
• Rust, R. T., & Oliver, R. L. (1994). Service quality: New directions in theory and practice. SAGE Publications.
   Google Scholar
• Rust, R. T., & Zahorik, A. J. (2003). Customer satisfaction, customer retention, and market share. Journal of Retailing, 69(2), 193–215. https://doi.org/10.1016/0022-4359(93)90003-2
   Google Scholar
• Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78. https://doi.org/10.1037/0003-066X.55.1.68
   PubMed Web of Science ®Google Scholar
• Sánchez-Franco, M. J. (2005). El comportamiento del usuario en la Web. Un análisis del estado de flujo. Revista Española de Investigación de Marketing ESIC, 9(1), 65–97. https://doi.org/10.1016/j.compedu.2009.07.005
   Google Scholar
• Satorra, A., & Bentler, P. M. (2001). A scaled difference chi-square test statistic for moment structure analysis. Psychometrika, 66(4), 507–514. https://doi.org/10.1007/BF02296192
   Web of Science ®Google Scholar
• Shahzad, F., Xiu, G., Khan, I., Shahbaz, M., Riaz, M. U., & Abbas, A. (2020). The moderating role of intrinsic motivation in cloud computing adoption in online education in a developing country: A structural equation model. Asia Pacific Education Review, 21(1), 121–141. https://doi.org/10.1007/s12564-019-09611-2
   Web of Science ®Google Scholar
• Shapiro, H. B., Lee, C. H., Roth, N. E. W., Li, K., Çetinkaya-Rundel, M., & Canelas, D. A. (2017). Understanding the massive open online course (MOOC) student experience: An examination of attitudes, motivations, and barriers. Computers & Education, 110, 35–50. https://doi.org/10.1016/j.compedu.2017.03.003
   Web of Science ®Google Scholar
• Shoemaker, S., & Lewis, R. C. (1999). Customer loyalty: The future of hospitality marketing. International Journal of Hospitality Management, 18(4), 345–370. https://doi.org/10.1016/S0278-4319(99)00042-0
   Google Scholar
• Siemens, G. (2005). Connectivism: A learning theory for the digital age. International Journal of Instructional Technology and Distance Learning, 2(1), 3–10. http://www.itdl.org/Journal/Jan_05/article01.htm
   Google Scholar
• Sultan, P., & Wong, H. Y. (2014). An integrated-process model of service quality, institutional brand and behavioural intentions: The case of a University. Managing Service Quality, 24(5), 487–521. https://doi.org/10.1108/MSQ-01-2014-0007
   Google Scholar
• Szymanski, D. M., & Hise, R. T. (2000). e-Satisfaction: An initial examination. Journal of Retailing, 76(3), 309–322. https://doi.org/10.1016/S0022-4359(00)00035-X
   Web of Science ®Google Scholar
• Thibaut, J., & Kelley, H. (1959). The social psychology of groups. Wiley.
   Google Scholar
• Trevino, L. K., & Webster, J. (1992). Flow computer-mediated communication. Communication Research, 19(5), 539–573. https://doi.org/10.1177/009365092019005001
   Web of Science ®Google Scholar
• Vallerand, R. J., Pelletier, L.-G., Blais, M. R., Briere, N. M., Senecal, C., & Vallieres, E. F. (1992). The academic motivation scale: A measure of intrinsic, extrinsic, and amotivation in education. Educational and Psychological Measurement, 52(4), 1003–1007. https://doi.org/10.1177/0013164492052004025
   Web of Science ®Google Scholar
• Walsh, G., & Beatty, S. E. (2007). Customer-based corporate reputation of a service firm: Scale development and validation. Journal of the Academy of Marketing Science, 35(1), 127–143. https://doi.org/10.1007/s11747-007-0015-7
   Web of Science ®Google Scholar
• Watted, A., & Barak, M. (2018). Motivating factors of MOOC completers: Comparing between university-affiliated students and general participants. The Internet and Higher Education, 37(April), 11–20. https://doi.org/10.1016/j.iheduc.2017.12.001
   Google Scholar
• Webster, J., Trevino, L. K., & Ryan, L. (1993). The dimensionality and correlated of flow in human-computer interaction. Computers in Human Behavior, 9(4), 411–426. https://doi.org/10.1016/0747-5632(93)90032-N
   Web of Science ®Google Scholar
• Xiong, Y., Li, H., Kornhaber, M. L., Suen, H. K., Pursel, B., & Goins, D. D. (2015). Examining the relations among student motivation, engagement, and retention in a MOOC: A structural equation modeling approach. Global Education Review, 2(3), 23–33. https://eric.ed.gov/?id=EJ1074099
   Google Scholar
• Yang, M., Shao, Z., Liu, Q., & Liu, C. (2017). Understanding the quality factors that influence the continuance intention of students toward participation in MOOCs. Educational Technology Research and Development, 65(5), 1195–1214. https://doi.org/10.1007/s11423-017-9513-6
   Web of Science ®Google Scholar
• Yuan, L., & Powell, S. (2013). MOOCs and open education: Implications for higher education. A white paper. CETIS. http://publications.cetis.ac.uk/2013/667
   Google Scholar
• Zeithaml, V. A., Berry, L. L., & Parasuraman, S. (1996). The behavioral consequences of service quality. Journal of Marketing, 60(2), 31–46. https://doi.org/10.1177/002224299606000203
   Web of Science ®Google Scholar