Determining AI-Based Learning Adoption Model for Students in Entrepreneurship Education: A Design Thinking Approach
Article Sidebar
-
AI-based system, design thinking, entrepreneurship, planned behavior, technology acceptance
Abstract
Background: Student interest in entrepreneurial pursuits remains low, despite the significant contributions of entrepreneurship to economic growth.
Purpose: This study investigates the factors influencing IPB students' interest in adopting AI-based entrepreneurship learning through the lens of design thinking, emphasizing the role of communication methods and their impact on motivation and attitudes.
Methods: This study adopts a mixed-method design, combining quantitative and qualitative approaches. Quantitative data were collected via an online survey from 173 IPB students, with 166 valid responses after data cleaning. Quantitative analysis was conducted using descriptive statistics (SPSS 25) and Partial Least Squares Structural Equation Modeling (PLS-SEM). The qualitative aspect involved a SCAMPER analysis within the design thinking framework to explore AI integration in entrepreneurship education. The PICOS framework was applied to explore the factors influencing AI adoption in higher education comprehensively. This mixed-method approach provides a holistic understanding of AI adoption in educational contexts.
Findings: Results indicate that learning motivation significantly affects students' intentions to engage with AI-based systems, positively impacting attitudes toward AI. Perceived ease of use also positively influences learning motivation and perceived usefulness, although perceived usefulness does not directly impact learning motivation. Additionally, interpersonal interactions and mass media positively influence attitudes and perceived usefulness, while awareness does not have a significant effect.
Conclusion: Expanding AI adoption in entrepreneurship education requires strategic communication, mainly focusing on Design Thinking’s empathize phase to understand student challenges. By iteratively proposing AI tools through the prototype phase, institutions can develop user-friendly, engaging solutions tailored to student needs, fostering higher adoption and engagement in entrepreneurship learning.
Research implication: These insights suggest that targeted communication strategies, including design thinking principles, can support broader AI adoption, enhance students’ entrepreneurial learning experiences, and foster a new generation of tech-savvy entrepreneurs.
References
Acquah, B. Y. S., Arthur, F., Salifu, I., Quayson, E., & Nortey, S. A. (2024). Preservice Teachers’ Behavioral Intention to Use Artificial Intelligence in Lesson Planning: A Dual-Staged PLS-SEM-ANN Approach. Computers and Education: Artificial Intelligence, 7, 100307. https://doi.org/10.1016/j.caeai.2024.100307
Ahmed, A. A. A., & Ganapathy, A. (2021). Creation of automated content with embedded artificial intelligence: a study on learning management system for educational entrepreneurship. Academy of Entrepreneurship Journal, 27(3), 1-10. https://search.proquest.com/openview/03fefb391067ddf46d9d5681b80f9ea6/1?pq-origsite=gscholar&cbl=29726
Alharbi, A., & Alzahrani, A. (2023). The influence of media on students' perceptions of artificial intelligence: A qualitative study. Computers & Education, 203, 104032. https://doi.org/10.1016/j.compedu.2023.104032
Almulla, M. A. (2024). Investigating Influencing Factors of Learning Satisfaction in AI ChatGPT for Research: University Students Perspective. Heliyon, 10(11), e32220. https://doi.org/10.1016/j.heliyon.2024.e32220
Andini, T. P., Adawiyah, R., & Indriani, Y. (2023). Attitudes, decision making and purchasing patterns of online vegetable consumers. Journal of Consumer Sciences, 8(3), 296-317. https://doi.org/10.29244/jcs.8.3.296-317
Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl & J. Beckmann (Eds.), Action control (pp. 11–39). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-69746-3_2
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. https://doi.org/10.1016/0749-5978(91)90020-T
AlGerafi, M. A., Zhou, Y., Alfadda, H., & Wijaya, T. T. (2023). Understanding the factors influencing higher education students' intention to adopt artificial intelligence-based robots. IEEE Access, 12, 152812-152824. Retrieved from https://ieeexplore.ieee.org/abstract/document/10247529/citations
Apostu, S. A., Mukli, L., Panait, M., Gigauri, I., & Hysa, E. (2022). Economic growth through the lenses of education, entrepreneurship, and innovation. Administrative Sciences, 12(3), 74. https://doi.org/10.3390/admsci12030074
Baker, R. S., & Inventado, P. S. (2023). The role of technology in education: Bridging the gap between students and artificial intelligence. Educational Technology Research and Development, 71(2), 345-367. https://doi.org/10.1007/s11423-022-10123-4
Barua, B., & Urme, U. N. (2023). Assessing the online teaching readiness of faculty members. Journal of Research in Innovative Teaching & Learning, 11(2), 1926-1945. https://doi.org/10.1108/JRIT-10-2022-0070.
Blanco-González, A., García, M. L. S., Cachón-Rodríguez, G., & Nistal, A. G. (2024). Research in business education. Connecting research with the educational challenges of universities. Journal of Management and Business Education, 7(3), 379-395. https://doi.org/10.35564/jmbe.2024.0021
Bardales-Cárdenas, M., Cervantes-Ramón, E. F., Gonzales-Figueroa, I. K., & Farro-Ruiz, L. M. (2024). Entrepreneurship skills in university students to improve local economic development. Journal of Innovation and Entrepreneurship, 13(1), 55. https://doi.org/10.1186/s13731-024-00408-1
Bowden, J., & Mirzaei, A. (2021). Consumer engagement within retail communication channels: An examination of online brand communities and digital content marketing initiatives. European Journal of Marketing, 55(5), 1411-1439. https://doi.org/10.1108/EJM-01-2018-0007
Byrd, G. A., & Zhang, Y. B. (2023). Communication frequency, identity accommodation, and attitudes toward people with disabilities in the United States: Disability salience and intergroup anxiety. Language Sciences, 99, 101564. https://doi.org/10.1016/j.langsci.2023.101564
Cardoso, P. R., Jolluskin, G., Paz, L., Fonseca, M. J., & Silva, I. (2023). Effects of awareness campaigns against domestic violence: Perceived efficacy, adopted behavior, and word of mouth. Journal of Criminological Research, Policy and Practice, 9(3/4), 177-192. https://doi.org/10.1108/JCRPP-11-2022-0057
Cautela, C., Mortati, M., Dell'Era, C., & Gastaldi, L. (2019). The impact of artificial intelligence on design thinking practice: Insights from the ecosystem of startups. Strategic Design Research Journal, 12(1), 114-134. https://doi.org/10.4013/sdrj.2019.121.08
Chai, C. S., Wang, X., & Xu, C. (2020). An extended theory of planned behavior for the modeling of Chinese secondary school students' intention to learn artificial intelligence. Mathematics, 8(11), 2089. https://doi.org/10.3390/math8112089
Chih, W. H., Hsu, L. C., & Ortiz, J. (2020). The antecedents and consequences of the perceived positive eWOM review credibility. Industrial Management & Data Systems, 120(6), 1217–1243. https://doi.org/10.1108/IMDS-10-2019-0573
Chou, C. M., Shen, T. C., Shen, T. C., & Shen, C. H. (2022). Influencing factors on students' learning effectiveness of AI-based technology application: Mediation variable of the human-computer interaction experience. Education and Information Technologies, 27(6), 8723-8750. https://doi.org/10.1007/s10639-021-10866-9
Chou, S. F., Liu, C.H. S., & Lin, J.Y. (2022). Critical criteria for enhancing consumption intention in restaurants during COVID-19. British Food Journal, 124(10), 3094-3115. https://doi.org/10.1108/BFJ-05-2021-0532
Corrales-Estrada, M. (2020). Design thinkers' profiles and design thinking solutions. Academia Revista Latinoamericana de Administración, 33(1), 9-24. https://doi.org/10.1108/ARLA-01-2018-0028
Crudu, R. (2019). The role of innovative entrepreneurship in the economic development of EU member countries. Journal of Entrepreneurship, Management and Innovation, 15(1), 35-60. https://doi.org/10.7341/20191512
Cummings, J. J., & Ingber, A. S. (2024). Distinguishing social virtual reality: Comparing communication channels across perceived social affordances, privacy, and trust. Computers in Human Behavior, 161, 108427. https://doi.org/10.1016/j.chb.2024.108427
Dabbous, A., & Boustani, N. M. (2023). Digital explosion and entrepreneurship education: Impact on promoting entrepreneurial intention for business students. Journal of Risk and Financial Management, 16(1), 27. https://doi.org/10.3390/jrfm16010027
Davis, F. D. (1989). Mobile Money: décryptage d'une succes story africaine Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User Acceptance of Computer Technology: A Comparison of two theoretical models. Management Science, 35(8), 982-1003. https://doi.org/10.1287/mnsc.35.8.982
Deepa, R., & Baral, R. (2022). Is my employee still attracted to me? Understanding the impact of integrated communication and choice of communication channels on employee attraction. Corporate Communications: An International Journal, 27(1), 110-126. https://doi.org/10.1108/CCIJ-09-2020-0136
Deshpande, A., Raut, R., Gupta, K., Mittal, A., Raheja, D., & Ekbote, N. (2024). Predictors of continued intention of working professionals for pursuing e-learning courses for career advancement. Information Discovery and Delivery, 52(2), 175–184. https://doi.org/10.1108/IDD-11-2022-0120
Dong, X., Chang, Y., Wang, Y., & Yan, J. (2017). Understanding usage of Internet of Things (IOT) systems in China: Cognitive experience and affect experience as moderator. Information Technology & People, 30(1), 117-138. https://doi.org/10.1108/ITP-11-2015-0272.
Duffett, R. G., & Maraule, M. (2023). Customer engagement and intention to purchase attitudes of Generation Z consumers toward emojis in digital marketing communications. Young Consumers, 25(5), 607-624. https://doi.org/10.1108/YC-08-2023-1817
Dzidzornu, E., Angmorterh, S. K., Aboagye, S., Angaag, N. A., Agyemang, P. N., & Edwin, F. (2024). Communication channels of breast cancer screening awareness campaigns among women presenting for mammography in Ghana. Journal of the American College of Radiology, 21, 1201-1207. https://doi.org/10.1016/j.jacr.2024.04.005
Elkaseh, A. M., Wong, K. W., & Fung, C. C. (2016). Perceived ease of use and perceived usefulness of social media for e-learning in Libyan higher education: A structural equation modeling analysis. International Journal of Information and Education Technology, 6(3), 192. Retrieved from https://www.ijiet.org/show-64-767-1.html
Fabri, M. (2015). Thinking with a new purpose: Lessons learned from teaching design thinking skills to creative technology students. Lecture Notes in Computer Science, 9186, 32-43. https://doi.org/10.1007/978-3-319-20886-2_4
Flavián, C., Pérez-Rueda, A., Belanche, D., & Casaló, L. V. (2022). Intention to use analytical artificial intelligence (AI) in services-the effect of technology readiness and awareness. Journal of Service Management, 33(2), 293-320. https://doi.org/10.1108/JOSM-10-2020-0378
Galvão, A., Marques, C., & Ferreira, J. J. (2020). The role of entrepreneurship education and training programmes in advancing entrepreneurial skills and new ventures. European Journal of Training and Development, 44(6/7), 595-614. https://doi.org/10.1108/EJTD-10-2019-0174
Gonzalez, C., & de la Torre, J. (2020). The impact of educational videos on students' attitudes towards artificial intelligence. Computers in Human Behavior, 107, 106287. https://doi.org/10.1016/j.chb.2020.106287
Gupta, K. P. (2020). Investigating the adoption of MOOCs in a developing country: Application of technology-user-environment framework and self-determination theory. Interactive Technology and Smart Education, 17(4), 355–375. https://doi.org/10.1108/ITSE-06-2019-0033
Guzman, A. L., & Lewis, S. C. (2020). Artificial intelligence and communication: A human-machine communication research agenda. New Media & Society, 22(1), 70-86. https://doi.org/10.1177/1461444819858691
Hagger, A., Martin, S., & Mike, W. (2022). This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. 41, 155-167. https://doi.org/10.1037/hea0001153
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2019). Multivariate data analysis. Cengage learning. Hampshire, United Kingdom, 633.
Hair, J. F., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107. https://doi.org/10.1504/ijmda.2017.10008574
Hariyono, H. (2024). Building a Future Generation of Entrepreneurs: An Experimental Study of the Integration of PBL and AI in Entrepreneurial. EDUTEC: Journal of Education And Technology, 7(4), 444-453. https://doi.org/10.29062/edu.v7i4.921
Hermann, E. (2022). Artificial intelligence and mass personalization of communication content-An ethical and literacy perspective. New Media & Society, 24(5), 1258-1277. https://doi.org/10.1177/14614448211022702
Heryani, N., Sulistyaniningsih, E., Susilawati, S., & Tukiran, M. (2023). Pengaruh self efficacy dan literasi technopreneurship terhadap minat wirausaha mahasiswa prodi pendidikan ekonomi unindra. Research and Development Journal of Education, 9(1), 188. https://doi.org/10.30998/rdje.v9i1.15052
Horowitz, M. C., Kahn, L., Macdonald, J., & Schneider, J. (2024). Adopting AI: how familiarity breeds both trust and contempt. AI & society, 39(4), 1721-1735. Retrieved from https://link.springer.com/article/10.1007/s00146-023-01666-5
Hsieh, S. H., & Lee, C. T. (2021). Hey Alexa: Examining the effect of perceived socialness in usage intentions of AI assistant-enabled smart speakers. Journal of Research in Interactive Marketing, 15(2), 267-294. https://doi.org/10.1108/JRIM-11-2019-0179
Hubert, M., Blut, M., Brock, C., Zhang, R. W., Koch, V., & Riedl, R. (2019). The influence of acceptance and adoption drivers on smart home usage. European Journal of Marketing, 53(6), 1073-1098. doi/10.1108/EJM-12-2016-0794/full/html
Ivanov, S., Soliman, M., Tuomi, A., Alkathiri, N. A., & Al-Alawi, A. N. (2024). Drivers of generative AI adoption in higher education through the lens of the Theory of Planned Behaviour. Technology in Society, 77, 102521. https://doi.org/10.1016/j.techsoc.2024.102521
Kalinić, Z., Liébana-Cabanillas, F. J., Muñoz-Leiva, F., & Marinković, V. (2020). The moderating impact of gender on the acceptance of peer-to-peer mobile payment systems. International Journal of Bank Marketing, 38(1), 138-158. https://doi.org/10.1108/IJBM-01-2019-0012
Karletsos, D., Hutchinson, P., Leyton, A., & Meekers, D. (2021). The effect of interpersonal communication in tobacco control campaigns: A longitudinal mediation analysis of a Ghanaian adolescent population. Preventive Medicine, 142, 106373. https://doi.org/10.1016/j.ypmed.2020.106373
Kim, J., Hardin, A., & Lee, S. (2023). Factors influencing resistance to hospitality information system change. Journal of Hospitality and Tourism Insights, 6(5), 1926-1945. https://doi.org/10.1108/JHTI-04-2022-0129
Kshetri, N. (2021). The role of artificial intelligence in promoting financial inclusion in developing countries. Journal of Global Information Technology Management, 24(1), 1-6. https://doi.org/10.1080/1097198X.2021.1871273
Kumar, V., & Singh, R. (2022). Awareness campaigns on artificial intelligence: Effects on students' perceptions and adoption. International Journal of Information Management, 62, 102427. https://doi.org/10.1016/j.ijinfomgt.2021.102427
Labrague, L. J., Aguilar-Rosales, R., Yboa, B. C., & Sabio, J. B. (2023). Factors influencing student nurses' readiness to adopt artificial intelligence (AI) in their studies and their perceived barriers to accessing AI technology: A cross-sectional study. Nurse Education Today, 130, 105945. https://doi.org/10.1016/j.nedt.2023.105945
Lee, A., & Chung, T.-L. D. (2023). Transparency in corporate social responsibility communication on social media. International Journal of Retail & Distribution Management, 51(5), 590-610. https://doi.org/10.1108/IJRDM-01-2022-0038
Lee, Y. F., Hwang, G. J., & Chen, P. Y. (2022). Impacts of an AI-based chatbot on college students' after-class review, academic performance, self-efficacy, learning attitude, and motivation. Educational Technology Research and Development, 70(5), 1843-1865. Retrieved from https://oa.mg/work/10.1007/s11423-022-10142-8
Lee, H. K., & Park, J. E. (2021). Designing a new empathy-oriented prototyping toolkit for the design thinking process: Creativity and design sensibility. International Journal of Art & Design Education, 40(3), 524-536. https://doi.org/10.1111/jade.12345
Lestari, R. (2023). Impact of Entrepreneurship Education for Students in the Era of Globalization. Saskara Indonesian Journal of Society Studies, 3(2), 79-94. https://doi.org/10.21009/saskara.032.05
Li, K. (2023). Determinants of college students' actual use of AI-based systems: An extension of the technology acceptance model. Sustainability, 15(6), 5221. https://doi.org/10.3390/su15065221
Madjdian, D. S., van Asseldonk, M., Talsma, E. F., Amenu, K., Gemeda, B. A., Girma, S., Roesel, K., Grace, D., & Knight-Jones, T. J. D. (2024). Impact of a mass-media consumer awareness campaign on food safety behavior and behavioral determinants among women in Dire Dawa and Harar, Ethiopia. Food Control, 163, 110509. https://doi.org/10.1016/j.foodcont.2024.110509
Mafe, C. R., & Blas, J. (2010). A comparative study of mobile messaging services acceptance to participate in television programs. Journal of Service Management, 21(1), 69-102. https://doi.org/10.1108/09564231011025128.
Mannan, S., Nordin, S. M., Rafik-Galea, S., & Rizal, A. R. A. (2017). The ironies of new innovation and the sunset industry: Diffusion and adoption. Journal of Rural Studies, 55, 316-322. https://doi.org/10.1016/j.jrurstud.2017.07.015
Miller, J. D., & Hwang, J. (2022). Simplifying artificial intelligence: How relatable content can enhance student engagement. Journal of Educational Computing Research, 60(5), 1025-1045. https://doi.org/10.1177/07356331211012345
Mirra, G., & Pugnale, A. (2022). Expertise, playfulness and analogical reasoning: three strategies to train Artificial Intelligence for design applications. Springer Nature, 2(1), 111-127. https://doi.org/10.1007/s44150-022-00035-y
Mohr, S., & Kühl, R. (2021). Acceptance of artificial intelligence in German agriculture: an application of the technology acceptance model and the theory of planned behavior. Precision Agriculture, 22(6), 1816-1844. https://doi.org/10.1007/s11119-021-09814-x
Nabi, G., Liñán, F., Fayolle, A., Krueger, N., & Walmsley, A. (2017). The impact of entrepreneurship education in higher education: A systematic review and research agenda. Academy of Management Learning & Education, 16(2), 277-299. https://doi.org/10.5465/amle.2015.0026
Nedeljković, I., & Petrović, D. R. (2023). Student satisfaction and intention to use e-learning during the Covid-19 pandemic. International Journal of Information and Learning Technology, 40(3), 225–241. https://doi.org/10.1108/IJILT-05-2022-0119
Nguyen, T. M., & Malik, A. (2022). Employee acceptance of online platforms for knowledge sharing: Exploring differences in usage behaviour. Journal of Knowledge Management, 26(8), 1985–2006. https://doi.org/10.1108/JKM-06-2021-0420
Pipitwanichakarn, T., & Wongtada, N. (2021). Leveraging the technology acceptance model for mobile commerce adoption under distinct stages of adoption: A case of micro businesses. Asia Pacific Journal of Marketing and Logistics, 33(6), 1415-1436. https://doi.org/10.1108/APJML-10-2018-0448.
Prasetiawan, A., Sunarto, S., & Estuti, E. (2021). Assesment potensi diri sebagai wirausaha mahasiswa. Peningkatan Kinerja Berbasis Pada Kualitas Komunikasi Kepercayaan Dan Kerjasama Tim, 3(2), 229-241. https://doi.org/10.33747/capital.v3i2.131
Primandaru, N. (2017). The Factors Affecting the Entrepreneurial Intention of College Students. Jurnal Economia, 13(1), 68. https://doi.org/10.21831/economia.v13i1.13276
Putri, P. T., & Simanjuntak, M. (2020). The role of motivation, locus of control and financial literacy on women investment decisions across generations. Journal of Consumer Sciences, 5(2), 102-123. https://doi.org/10.29244/jcs.5.2.102-123
Radhakrishnan, J., & Chattopadhyay, M. (2020). Determinants and barriers of artificial intelligence adoption–A literature review. In Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation: IFIP WG 8.6 International Conference on Transfer and Diffusion of IT, TDIT 2020, Tiruchirappalli, India, December 18–19, 2020, Proceedings, Part I (pp. 89-99). Springer International Publishing.https://link.springer.com/chapter/10.1007/978-3-030-64849-7_9
Rokhim, R., Mayasari, I., Wulandari, P., & Haryanto, H. C. (2022). Analysis of the extrinsic and intrinsic aspects of the technology acceptance model associated with the learning management system during the COVID-19 pandemic. VINE Journal of Information and Knowledge Management Systems, 52(4), 312–340. https://doi.org/10.1108/VJIKMS-04-2022-0113
Roy, R., Babakerkhell, M. D., Mukherjee, S., Pal, D., & Funilkul, S. (2022). Evaluating the intention for the adoption of artificial intelligence-based robots in the university to educate the students. IEEE Access, 10, 125666-125678. doi: 10.1109/ACCESS.2022.3225555.
Rudhumbu, N. (2022). Applying the UTAUT2 to Predict the Acceptance of Blended Learning by University Students. Asian Association of Open Universities Journal, 17(1), 15-36. https://doi.org/10.1108/AAOUJ-08-2021-0084
Rusu, V. D., & Roman, A. (2022). Smes Under the Umbrella of Covid-19 Pandemic: Changes and Challenges. Finance, Economics and Tourism-FET 2022, 22, 119. Retrieved from https://www.researchgate.net/profile/Emmanuel-Mensah-15/publication/370025688
Rusu, V. D., Roman, A., & Tudose, M. B. (2022). Determinants of entrepreneurial intentions of youth: the role of access to finance. Engineering Economics, 33(1), 86-102. https://doi.org/10.5755/j01.ee.33.1.28716
Sagar, G., Anand, B., Perumalla Varalaxmi, A. S., & Raj, S. (2023). The role of entrepreneurship in economic growth and development. Journal of Survey in Fisheries Sciences, 10(1), 5940-5955. Retrieved from https://sifisheriessciences.com/journal/index.php/journal/article/view/2022
Saputra, A. D., Rahmatia, A., & Muslimah, M. (2021). How personal factors grow students' interest in entrepreneurship. Journal of Services Management and Marketing, 14(1), 61-76. Retrieved from https://www.e-journal.trisakti.ac.id/index.php/jasa/article/download/8336/6508
Sari, A., & Hairunisya, H. (2022). Pengaruh metode mengajar dosen dan perilaku belajar mahasiswa terhadap minat berwirausaha mahasiswa Universitas Bhinneka PGRI. Jurnal Economina, 1(3), 427-438. https://doi.org/10.55681/economina.v1i3.99
Sayaf, A. M., Alamri, M. M., Alqahtani, M. A., & Alrahmi, W. M. (2022). Factors influencing university students' adoption of digital learning technology in teaching and learning. Sustainability, 14(1), 493. https://doi.org/10.3390/su14010493
Shah, Z., & Wei, L. (2022). Interpersonal risk communication matters more than media risk communication in its impact on individuals’ trust and preventive behaviors during COVID-19. International Journal of Disaster Risk Reduction, 82, 103369. https://doi.org/10.1016/j.ijdrr.2022.103369
Shang, L., Zhou, J., & Zuo, M. (2021). Understanding older adults’ intention to share health information on social media: The role of health belief and information processing. Internet Research, 31(1), 100-122. https://doi.org/10.1108/INTR-12-2019-0512
Simamora, T. P., & Djamaludin, M. D. (2020). Analysis of intention to buy cinema e-tickets among IPB students with Theory of Planned Behavior (TPB) approach. Journal of Consumer Sciences, 5(1), 58-72. https://doi.org/10.29244/jcs.5.1.58-72
Sicilia, M., & Palazón, M. (2023). Developing customer engagement through communication consistency and channel coordination. Spanish Journal of Marketing - ESIC, 27(2), 241-260. https://doi.org/10.1108/SJME-02-2022-0022
Sohaib, M., & Han, H. (2023). Building value co-creation with social media marketing, brand trust, and brand loyalty. Journal of Retailing and Consumer Services, 74, 103442. https://doi.org/10.1016/j.jretconser.2023.103442
Singh, S., Sahni, M. M., & Kovid, R. K. (2020). What drives FinTech adoption? A multi-method evaluation using an adapted technology acceptance model. Management Decision, 58(8), 1675-1697. https://doi.org/10.1108/MD-09-2019-1318.
Stocchi, L., Michaelidou, N., & Micevski, M. (2019). Drivers and outcomes of branded mobile app usage intention. Journal of Product & Brand Management, 28(1), 28-49. https://doi.org/10.1108/JPBM-02-2017-1436.
Syed, R. T., Tariq, U., Arnaut, M., & Agrawal, R. (2024). Entrepreneurship educator: a vital cog in the wheel of entrepreneurship education and development in universities. Journal of Innovation and Entrepreneurship, 13(1), 66. https://doi.org/10.1186/s13731-024-00433-0
Tang, T., Li, P., & Tang, Q. (2022). New Strategies and Practices of Design Education Under the Background of Artificial Intelligence Technology: Online Animation Design Studio. Frontiers Media, 13, 767295. https://doi.org/10.3389/fpsyg.2022.767295
Tran, H. T. T., & Corner, J. (2016). The impact of communication channels on mobile banking adoption. International Journal of Bank Marketing, 34(1), 78-109. https://doi.org/10.1108/IJBM-06-2014-0073
Uribe, R., Buzeta, C., Manzur, E., & Celis, M. (2022). Celebrity endorsement using different types of new media and advertising formats. Academia Revista Latinoamericana de Administración, 35(3), 281-302. https://doi.org/10.1108/ARLA-08-2021-0167
Vocke, C., Constantinescu, C., & Popescu, D. (2019). Application potentials of artificial intelligence for the design of innovation processes. Procedia CIRP, 84, 810-813. https://doi.org/10.1016/j.procir.2019.04.230
Wamba-Taguimdje, S. L., Wamba, S. F., Kamdjoug, J. R. K., & Wanko, C. E. T. (2020). Influence of artificial intelligence (AI) on firm performance: the business value of AI-based transformation projects. Business process management journal, 26(7), 1893-1924. https://doi.org/10.1108/BPMJ-10-2019-0411
Wang, X. (2022). Attitudes toward COVID-19 vaccines and vaccine uptake intent in China: The role of collectivism, interpersonal communication, and the use of news and information websites. Current Research in Ecological and Social Psychology, 3, 100065. https://doi.org/10.1016/j.cresp.2022.100065
Winkler, C., Hammoda, B., Noyes, E., & Van Gelderen, M. (2023). Entrepreneurship education at the dawn of generative artificial intelligence. Entrepreneurship Education and Pedagogy, 6(4), 579-589. https://doi.org/10.1177/25151274231198799
Yen, Y.-S. (2023). Channel integration affects usage intention in food delivery platform services: The mediating effect of perceived value. Asia Pacific Journal of Marketing and Logistics, 35(1), 54-73. https://doi.org/10.1108/APJML-05-2021-0372
Zhou, X., Van Brummelen, J., & Lin, P. (2020). Designing AI learning experiences for K-12: emerging works, future opportunities and a design framework. arXiv preprint arXiv:2009.10228.. https://doi.org/10.48550/arxiv.2009.10228
Authors
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a
This work is licensed under a Creative Commons Attribution 4.0 International License. that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal. - Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
