The DOI matches its Crossref record; 89 of the 92 references it cites were found in a registry or an index.
The Integration of the Technology Acceptance Model and Value-Based Adoption Model to Study the Adoption of E-Learning: The Moderating Role of e-WOM
Open accessAbstract
The Technology Acceptance Model (TAM) has lately been utilized in a number of studies to investigate why people reject or adopt new technologies like mobile commerce or e-learning. However, several studies have found weaknesses in TAM’s ability to predict consumers’ purchase intention behavior. To compensate for TAM’s weaknesses, this study presents a model that integrates all of TAM’s components with the Value-Based Adoption Model (VAM). The perceived benefits and sacrifices were considered to provide a list of the implications for both researchers and e-learning service providers. Furthermore, the moderating role of e-word of mouth was utilized to examine the relationship between attitude, intention, perceived value, and intention toward e-learning, in order to match the current circumstances with the growing popularity of social networks. This study was conducted with a quantitative analysis by using data collected from survey 417 e-learning consumers. Except for perceived fee, which has a negative effect on perceived value, the results demonstrate that all hypotheses of latent correlations in TAM and VAM were strongly significant. Furthermore, attitude and perceived value have a significant role in determining consumer adoption of e-learning. Consumers’ perceived value will be driven by the high and low levels of the moderating influence of e-word of mouth, influencing their intention toward e-learning. Since e-learning is an effective sustainable education system, the result of this study can provide a good solution to facilitate e-learning in current and future conditions.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Chen et al. [11] and Liao et al. [28] used TAM to assess educators' acceptance of AI-driven educational tools, emphasizing the role of perceived usefulness in shaping positive attitudes and perceptions.”
From Modeling teachers’ acceptance of generative artificial intelligence use in higher education: the role of AI literacy, intelligent TPACK, and perceived trust (2024) · cites this paper as [28]
In the citing paper
“A growing body of research supports the notion that an inverse correlation exists between perceived risks and perceived value when predicting technology use intention [28,29,30,36,43]”
From ChatGPT in Learning: Assessing Students’ Use Intentions through the Lens of Perceived Value and the Influence of AI Literacy (2024) · cites this paper as [29]
In the citing paper
“Research indicates that the degree of perceived fees has a notable influence on customers’ perceived value [29,43,45,46,47].”
From ChatGPT in Learning: Assessing Students’ Use Intentions through the Lens of Perceived Value and the Influence of AI Literacy (2024) · cites this paper as [29]
In the citing paper
“Likewise, Liao et al. [29] confirmed that, in adopting an e-learning system, perceived value is strongly predicted by perceived usefulness.”
From ChatGPT in Learning: Assessing Students’ Use Intentions through the Lens of Perceived Value and the Influence of AI Literacy (2024) · cites this paper as [29]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Evaluating structural equation models with unobservable variables and measurement error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800104 · Cited by 109,190
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003) · Journal of Applied Psychology · doi:10.1037/0021-9010.88.5.879 · Cited by 82,194
A new criterion for assessing discriminant validity in variance-based structural equation modeling
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-014-0403-8 · Cited by 38,459
User Acceptance of Computer Technology: A Comparison of Two Theoretical Models
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989) · Management Science · doi:10.1287/mnsc.35.8.982 · Cited by 25,709
Pls-Sem: indeed a silver bullet
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011) · Journal of Marketing Theory and Practice · doi:10.2753/mtp1069-6679190202 · Cited by 21,631
A primer on partial least squares structural equation modeling (PLS-SEM)
Leguina, A. (2015) · International Journal of Research & Method in Education · doi:10.1080/1743727x.2015.1005806 · Cited by 18,921
Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence
Zeithaml, V. A. (1988) · Journal of Marketing · doi:10.1177/002224298805200302 · Cited by 18,292
(2014) · DigitalCommons - Kennesaw State University (Kennesaw State University) · Cited by 12,785
(1998) · Cited by 12,725
Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004) · Journal of Interactive Marketing · doi:10.1002/dir.10073 · Cited by 5,916
(2003) · International Journal of Electronic Commerce · doi:10.1080/10864415.2003.11044275 · Cited by 5,715
Agarwal, R., & Karahanna, E. (2000) · MIS Quarterly · doi:10.2307/3250951 · Cited by 4,726
A meta-analysis of the technology acceptance model
King, W. R., & He, J. (2006) · Information & Management · doi:10.1016/j.im.2006.05.003 · Cited by 2,906
Determinants of consumer engagement in electronic word-of-mouth (eWOM) in social networking sites
Chu, S.-C., & Kim, Y. (2011) · International Journal of Advertising · doi:10.2501/ija-30-1-047-075 · Cited by 2,311
Value-based Adoption of Mobile Internet: An empirical investigation
Kim, H.-W., Chan, H. C., & Gupta, S. (2007) · Decision Support Systems · doi:10.1016/j.dss.2005.05.009 · Cited by 2,084
Designing Research for Application
Calder, B. J., Phillips, L. W., & Tybout, A. M. (1981) · Journal of Consumer Research · doi:10.1086/208856 · Cited by 1,806
The Roles of Price, Performance, and Expectations in Determining Satisfaction in Service Exchanges
Voss, G. B., Parasuraman, A., & Grewal, D. (1998) · Journal of Marketing · doi:10.2307/1252286 · Cited by 1,122
Factors influencing teachers’ intention to use technology: Model development and test
Teo, T. (2011) · Computers & Education · doi:10.1016/j.compedu.2011.06.008 · Cited by 914 · cited 1×
“Besides, while PU plays an important role in the utilitarian dimension of PV, PE is an essential dimension in e-learning users’ perception of hedonic PV [44].”
BackgroundA multi-stage model of word-of-mouth influence through viral marketing
De Bruyn, A., & Lilien, G. L. (2008) · International Journal of Research in Marketing · doi:10.1016/j.ijresmar.2008.03.004 · Cited by 906
Grewal, D., Gotlieb, J. B., & Marmorstein, H. (1994) · Journal of Consumer Research · doi:10.1086/209388 · Cited by 797
Liu, I.-F., Chen, M. C., Sun, Y. S., Wible, D., & Kuo, C. (2009) · Computers & Education · doi:10.1016/j.compedu.2009.09.009 · Cited by 795
Investigating users’ perspectives on e-learning: An integration of TAM and IS success model
Mohammadi, H. (2015) · Computers in Human Behavior · doi:10.1016/j.chb.2014.07.044 · Cited by 779
Abdullah, F., Ward, R., & Ahmed, E. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.05.014 · Cited by 693
Learners’ acceptance of e-learning in South Korea: Theories and results
Lee, B.-C., Yoon, J.-O., & Lee, I. (2009) · Computers & Education · doi:10.1016/j.compedu.2009.06.014 · Cited by 683
Online Word-of-Mouth (or Mouse): An Exploration of Its Antecedents and Consequences
Sun, T., Youn, S., Wu, G., & Kuntaraporn, M. (2006) · Journal of Computer-Mediated Communication · doi:10.1111/j.1083-6101.2006.00310.x · Cited by 646
Sohn, K., & Kwon, O. (2020) · Telematics and Informatics · doi:10.1016/j.tele.2019.101324 · Cited by 646
Social eWOM: does it affect the brand attitude and purchase intention of brands?
Kudeshia, C., & Kumar, A. (2017) · Management Research Review · doi:10.1108/mrr-07-2015-0161 · Cited by 646
User acceptance of wearable devices: An extended perspective of perceived value
Yang, H., Yu, J., Zo, H., & Choi, M. (2015) · Telematics and Informatics · doi:10.1016/j.tele.2015.08.007 · Cited by 639
Šumak, B., Heričko, M., & Pušnik, M. (2011) · Computers in Human Behavior · doi:10.1016/j.chb.2011.08.005 · Cited by 602
User acceptance of YouTube for procedural learning: An extension of the Technology Acceptance Model
Lee, D. Y., & Lehto, M. R. (2013) · Computers & Education · doi:10.1016/j.compedu.2012.10.001 · Cited by 565
Chang, C., Hajiyev, J., & Su, C.-R. (2017) · Computers & Education · doi:10.1016/j.compedu.2017.04.010 · Cited by 533
Lien, C. H., & Cao, Y. (2014) · Computers in Human Behavior · doi:10.1016/j.chb.2014.08.013 · Cited by 513
The relationships among perceived quality, perceived risk and perceived product value
Snoj, B., Pisnik, A., & Mumel, D. (2004) · Journal of Product & Brand Management · doi:10.1108/10610420410538050 · Cited by 511
Meléndez, A. P., Obra, A. R. D. Á., & Garrido‐Moreno, A. (2012) · Computers & Education · doi:10.1016/j.compedu.2012.12.014 · Cited by 484
The use of social media in travel information search
Chung, N., & Koo, C. (2015) · Telematics and Informatics · doi:10.1016/j.tele.2014.08.005 · Cited by 474
Al-Rahmi, W. M., Yahaya, N., Aldraiweesh, A. A., Alamri, M. M., Aljarboa, N. A., Alturki, U., & Aljeraiwi, A. A. (2019) · IEEE Access · doi:10.1109/access.2019.2899368 · Cited by 435
Mailizar, M., Burg, D., & Maulina, S. (2021) · Education and Information Technologies · doi:10.1007/s10639-021-10557-5 · Cited by 420
Nikou, S. A., & Economides, A. A. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.11.020 · Cited by 416
Tang, K., Chang, C., & Hwang, G. (2021) · Interactive Learning Environments · doi:10.1080/10494820.2021.1875001 · Cited by 405
Shroff, R. H., Deneen, C. C., & Ng, E. M. W. (2011) · Australasian Journal of Educational Technology · doi:10.14742/ajet.940 · Cited by 399
Management of multi-purpose stadiums: importance and performance measurement of service interfaces
Höck, C., Ringle, C. M., & Sarstedt, M. (2010) · International Journal of Services Technology and Management · doi:10.1504/ijstm.2010.034327 · Cited by 386
Students’ Perception towards E-Learning during COVID-19 Pandemic in India: An Empirical Study
Khan, M. A., Vivek, V., Nabi, M. K., Khojah, M., & Tahir, M. (2020) · Sustainability · doi:10.3390/su13010057 · Cited by 375
Predictors of customer acceptance of and resistance to smart technologies in the retail sector
Roy, S. K., Balaji, M. S., Quazi, A. M., & Quaddus, M. (2018) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2018.02.005 · Cited by 370
Retail service quality and perceived value
Sweeney, J., Soutar, G. N., & Johnson, L. W. (1997) · Journal of Retailing and Consumer Services · doi:10.1016/s0969-6989(96)00017-3 · Cited by 350
Jang, J., Ko, Y., Shin, W. S., & Han, I. (2021) · IEEE Access · doi:10.1109/access.2020.3048708 · Cited by 334
Molinillo, S., Aguilar-Illescas, R., Anaya‐Sánchez, R., & Liébana-Cabanillas, F. J. (2021) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2020.102404 · Cited by 331
A study on the adoption of IoT smart home service: using Value-based Adoption Model
Kim, Y., Park, Y., & Choi, J. (2017) · Total Quality Management & Business Excellence · doi:10.1080/14783363.2017.1310708 · Cited by 328
Agudo-Peregrina, Á. F., Hernández-García, Á., & Pascual-Miguel, F. J. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2013.10.035 · Cited by 325
Ayeh, J. K. (2015) · Computers in Human Behavior · doi:10.1016/j.chb.2014.12.049 · Cited by 298
Chu, T.-H., & Chen, Y. (2015) · Computers & Education · doi:10.1016/j.compedu.2015.09.013 · Cited by 274
Al-Azawei, A., Parslow, P., & Lundqvist, K. Ø. (2016) · Australasian Journal of Educational Technology · doi:10.14742/ajet.2741 · Cited by 270
Tarhini, A., Arachchilage, N. A. G., Masa’deh, R. M. T., & Abbasi, M. S. (2015) · International Journal of Technology Diffusion · doi:10.4018/ijtd.2015100104 · Cited by 225
Usability factors predicting continuance of intention to use cloud e-learning application
Wang, L. Y. K., Lew, S.-L., Lau, S. H., & Leow, M.-C. (2019) · Heliyon · doi:10.1016/j.heliyon.2019.e01788 · Cited by 225
Wang, Y.-S., Yeh, C.-H., & Liao, Y.-W. (2013) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2012.09.004 · Cited by 222
Self-citationShehzadi, S., Nisar, Q. A., Hussain, M. S., Basheer, M. F., Hameed, W. U., & Chaudhry, N. I. (2020) · Asian Education and Development Studies · doi:10.1108/aeds-04-2020-0063 · Cited by 216
Empirical study on continuance intentions towards E-Learning 2.0 systems
Wu, B., & Zhang, C. (2014) · Behaviour and Information Technology · doi:10.1080/0144929x.2014.934291 · Cited by 207
Verma, P., & Sinha, N. (2017) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2017.08.013 · Cited by 207
Hsia, J.-W., Chang, C., & Tseng, A.-H. (2012) · Behaviour and Information Technology · doi:10.1080/0144929x.2012.702284 · Cited by 188
Why Is the Crowd Divided? Attribution for Dispersion in Online Word of Mouth
He, S. X., & Bond, S. (2015) · Journal of Consumer Research · doi:10.1086/680667 · Cited by 181
Alwahaishi, S., & Snåšel, V. (2013) · Journal of technology management & innovation · doi:10.4067/s0718-27242013000200005 · Cited by 180
Store brands’ purchase intention: Examining the role of perceived quality
Calvo-Porral, C., & Lévy-Mangín, J.-P. (2017) · European Research on Management and Business Economics · doi:10.1016/j.iedeen.2016.10.001 · Cited by 180
Ajibade, P. (2018) · San Jose State University Scholar Works (San Jose State University) · Cited by 174
Ifinedo, P. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.12.049 · Cited by 167
Balog, A., & Pribeanu, C. (2010) · Studies in Informatics and Control · doi:10.24846/v19i3y201011 · Cited by 167
Prasetyo, Y. T., Ong, A. K. S., Concepcion, G. K. F., Navata, F. M. B., Robles, R. A. V., Tomagos, I. J. T., Young, M. N., Diaz, J. F. T., Nadlifatin, R., & Redi, A. A. N. P. (2021) · Sustainability · doi:10.3390/su13158365 · Cited by 162
User acceptance of media tablets: An empirical examination of perceived value
Yu, J., Lee, H., Ha, I., & Zo, H. (2017) · Telematics and Informatics · doi:10.1016/j.tele.2015.11.004 · Cited by 161
Combined effects of valence and attributes of e-WOM on consumer judgment for message and product
Jeong, H.-J., & Koo, D. (2015) · Internet Research · doi:10.1108/intr-09-2013-0199 · Cited by 145
Wang, J., Wang, L., & Wang, M. (2018) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2018.01.011 · Cited by 138
E-Learning Services to Achieve Sustainable Learning and Academic Performance: An Empirical Study
Alam, M. M., Ahmad, N., Naveed, Q. N., Patel, A. A., Abohashrh, M., & Khaleel, M. A. (2021) · Sustainability · doi:10.3390/su13052653 · Cited by 126
Ho, N. T. T., Sivapalan, S., Pham, H., Nguyen, L. T. M., Pham, A. T. V., & Dinh, V. (2020) · Interactive Technology and Smart Education · doi:10.1108/itse-08-2020-0164 · Cited by 117
Business simulation games with and without supervision: An analysis based on the TAM model
García, J. P., Cañadillas, I. P., & Abando, J. C. (2015) · Journal of Business Research · doi:10.1016/j.jbusres.2015.10.046 · Cited by 113
Purchase intention in social commerce
Chen, C., Hsiao, K., & Wu, S.-J. (2018) · Library Hi Tech · doi:10.1108/lht-01-2018-0007 · Cited by 107
Farhan, W., Razmak, J., Demers, S., & Laflamme, S. (2019) · Technology in Society · doi:10.1016/j.techsoc.2019.101192 · Cited by 105
E-learning Personalization Systems and Sustainable Education
Klašnja‐Milićević, A., & Ivanović, M. D. (2021) · Sustainability · doi:10.3390/su13126713 · Cited by 91
Liang, T.-P., Lin, Y.-L., & Hou, H.-C. (2021) · Information & Management · doi:10.1016/j.im.2021.103471 · Cited by 83
Zhang, H., Liang, X.-N., & Qi, C.-Y. (2020) · Journal of business research · doi:10.1016/j.jbusres.2020.01.020 · Cited by 74
Why Internet Users Are Willing to Pay for Social Networking Services
Hsiao, K.-L. (2011) · Online information review (Print) · doi:10.1108/14684521111176499 · Cited by 61
Hsiao, K.-L., & Chen, C.-C. (2017) · Telematics and Informatics · doi:10.1016/j.tele.2016.09.004 · Cited by 58
Consumers' acceptance of smart virtual closets
Perry, A. L. (2016) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2016.08.018 · Cited by 58
Understanding e-learning adoption in Brazil: Major determinants and gender effects
Okazaki, S., & dos Santos, L. M. R. (2012) · The International Review of Research in Open and Distributed Learning · doi:10.19173/irrodl.v13i4.1266 · Cited by 52
Who is behind the message? The power of expert reviews on eWOM platforms
Naujoks, A., & Benkenstein, M. (2020) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2020.101015 · Cited by 51
Song, B. K. (2020) · Australasian Journal of Educational Technology · doi:10.14742/ajet.6126 · Cited by 49
Sustainable Education through E-Learning: The Case Study of iLearn2.0
Chen, F. (2021) · Sustainability · doi:10.3390/su131810186 · Cited by 47
Wu, H., Lin, Y.-C., & Hsu, F.-S. (2017) · DOAJ (DOAJ: Directory of Open Access Journals) · Cited by 43
Setiyani, L. (2021) · Utamax Journal of Ultimate Research and Trends in Education · doi:10.31849/utamax.v3i2.6746 · Cited by 43
An empirical analysis of mobile internet acceptance from a value-based view
Chong, X., Zhang, J., Lai, K. K., & Nie, L. (2012) · International Journal of Mobile Communications · doi:10.1504/ijmc.2012.048886 · Cited by 36
Study on mobile commerce customer based on value adoption
Chunxiang, L. (2014) · Journal of Applied Sciences · doi:10.3923/jas.2014.901.909 · Cited by 29
Lu, H., & Lin, K. (2012) · Journal of electronic commerce research · Cited by 29
A study of antecedents influencing eWOM for online lecture website
Lee, M.-S., & An, H. (2018) · Online Information Review · doi:10.1108/oir-10-2017-0275 · Cited by 21
Flagged first, then by citations
3 of the 92 references couldn’t be matched to a known paper.
Research works printed but not linked: 3
- Newel, F., and Newell-Lemon, K. (2001). Wireless Rules, McGraw-Hill.
- Kwon, 2013, Application of value-based adoption model to analyze saas adoption behavior in korean b2b cloud market, Int. J. Adv. Comput. Technol., 5, 368
- Fang, 2016, Consumer heterogeneity, perceived value, and repurchase decision-making in online shopping: The role of gender, age, and shopping motives, J. Electron. Commer. Res., 17, 116
Cited by
Sorted by citations
Use of ChatGPT in academia: Academic integrity hangs in the balance
Bin-Nashwan, S. A., Sadallah, M., & Bouteraa, M. (2023) · Technology in Society · doi:10.1016/j.techsoc.2023.102370 · Cited by 394
Promoting tourism business through digital marketing in the new normal era: a sustainable approach
Deb, S. K., Nafi, S. M., & Valeri, M. (2022) · European Journal of Innovation Management · doi:10.1108/ejim-04-2022-0218 · Cited by 252
Al-Abdullatif, A. M. (2024) · Education Sciences · doi:10.3390/educsci14111209 · Cited by 169
Al-Abdullatif, A. M., & Alsubaie, M. A. (2024) · Behavioral Sciences · doi:10.3390/bs14090845 · Cited by 126
“Studies have shown that the level of perceived fees significantly influences users’ perceived value of a service or product [29,43,45–47].”
InfluentialPark, D. Y., & Kim, H. (2023) · Sustainability · doi:10.3390/su15010872 · Cited by 132
Metadata
- Authors
- Liao, Y.-K., Wu, W.-Y., Le, T. Q., & Phung, T. T. T.
- Affiliations
- Nanhua University (TW)
- Ton Duc Thang University (VN)
- Corresponding author
- Le, Trang Quang
- Venue
- Sustainability
- Publisher
- MDPI AG
- Published
- 2022-01-12
- Volume
- 14
- Issue
- 2
- Pages
- 815
- ISSN
- 2071-1050 (ISSN-L)
- OpenAlex
- W4205109486
- Cited by
- 123
- References
- 92
- Citations by year
- 2026: 24 · 2025: 33 · 2024: 37 · 2023: 23 · 2022: 6
- FWCI
- 20.71
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Sustainability (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Education › Technology-Enhanced Education Studies
- Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
- Keywords
- e-learning adoption, technology acceptance model, value-based adoption model, e-word-of-mouth, perceived value, consumer attitudes, purchase intention, perceived cost, moderating effect, social networks
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review