Niat Melakukan Islamic Online Donation Pada Generasi Z: Peran Attitude Sebagai Mediator Pada Model UTAUT-3

Dewita Puspawati; Novel Idris Abas; Kurnia Rina Ariani

doi:10.22219/jrak.v14i3.35224

Authors

Dewita Puspawati Fakultas Ekonomi dan Bisnis, Universitas Muhammadiyah Surakarta, Surakarta, Indonesia
Novel Idris Abas Fakultas Ekonomi dan Bisnis, Universitas Muhammadiyah Surakarta, Surakarta, Indonesia
Kurnia Rina Ariani Fakultas Ekonomi dan Bisnis, Universitas Muhammadiyah Surakarta, Surakarta, Indonesia

DOI:

https://doi.org/10.22219/jrak.v14i3.35224

Keywords:

Digital, Donation, Habit, Islamic, Personal Innovativeness

Abstract

Purpose: This study aims to examine the effect of the UTAUT-3 model, namely performance expectancy, habit, and personal innovativeness on the intention to make Islamic online donations mediated by attitude in generation Z.

Methodology/ approach: This study uses a survey method by distributing questionnaires online. The sample in this study were 180 respondents. We use SEM-PLS to analyze data.

Findings: The results show that performance expectancy and personal innovativeness affect attitude, while habit does not affect. The intention to do Islamic online donation is influenced by performance expectancy, habit, personal innovativeness, and attitude. Attitude can mediate the relationship between performance expectancy and personal innovativeness with the intention to pay ZIS online. However, the effect of habit on online ZIS payment intentions cannot be mediated by attitude.

Practical implications: As Generation Z dominates the population in Indonesia, this generation has high potential in ZIS collection. ZIS Institutions can further promote the convenience of online ZIS payments.

Originality/value: This study uses personal innovativeness as a construct of UTAUT-3 in the intention to Islamic online donation.

Downloads

Download data is not yet available.

References

Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204–215.

Anjelina, E. D., Salsabila, R., & Fitriyanti, D. A. (2020). Peranan Zakat, Infak dan Sedekah dalam Meningkatkan Kesejahteraan Ekonomi Masyarakat. Jihbiz: Jurnal Ekonomi, Keuangan Dan Perbankan Syariah, 4(2), 136–147.

BAZNAS. (2023). Infaq dan Sedekah: Makna, Tujuan, dan Perbedaannya. .

Belanche, D., Casaló, L. V, & Flavián, C. (2019). Artificial Intelligence in FinTech: understanding robo-advisors adoption among customers. Industrial Management & Data Systems, 119(7), 1411–1430.

Bhattacherjee, A., & Premkumar, G. (2004). Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. MIS Quarterly, 229–254.

Bhuiyan, K. H., Ahmed, S., & Jahan, I. (2024). Consumer attitude toward using artificial intelligence (AI) devices in hospitality services. Journal of Hospitality and Tourism Insights, ahead-of-print.

Cao, J., Shang, Y., Mok, Q., & Lai, I. K.-W. (2019). The impact of personal innovativeness on the intention to use cloud classroom: an empirical study in China. Technology in Education: Pedagogical Innovations: 4th International Conference, ICTE 2019, Guangzhou, China, March 15-17, 2019, Revised Selected Papers 4, 179–188.

Childers, C., & Boatwright, B. (2021). Do digital natives recognize digital influence? Generational differences and understanding of social media influencers. Journal of Current Issues & Research in Advertising, 42(4), 425–442.

CNN Indonesia. (2023). Indonesia Jadi Negara Paling Dermawan di Dunia untuk Keenam Kalinya Baca artikel CNN Indonesia “Indonesia Jadi Negara Paling Dermawan di Dunia untuk Keenam Kalinya” selengkapnya di sini: https://www.cnnindonesia.com/gaya-hidup/20231122094358-277-1027392/indonesia-jadi-negara-paling-dermawan-di-dunia-untuk-keenam-kalinya.

Criollo-C, S., Guerrero-Arias, A., Jaramillo-Alcázar, Á., & Luján-Mora, S. (2021). Mobile learning technologies for education: Benefits and pending issues. Applied Sciences, 11(9), 4111.

Dawami, Q. (2020). Factors influencing the preference of customers towards Islamic banking: Evidence from Malaysia. Journal of Islamic Economic Laws, 3(1), 48–67.

Djimesah, I. E., Zhao, H., Okine, A. N. D., Li, Y., Duah, E., & Mireku, K. K. (2022). Analyzing the technology of acceptance model of Ghanaian crowdfunding stakeholders. Technological Forecasting and Social Change, 175, 121323.

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.

El Alfy, S., & Kehal, M. (2024). Investigating the factors affecting educators’ adoption of learning analytics using the UTAUT model. The International Journal of Information and Learning Technology.

Escobar-Rodríguez, T., & Carvajal-Trujillo, E. (2014). Online purchasing tickets for low cost carriers: An application of the unified theory of acceptance and use of technology (UTAUT) model. Tourism Management, 43, 70–88.

Farooq, M. S., Salam, M., Jaafar, N., Fayolle, A., Ayupp, K., Radovic-Markovic, M., & Sajid, A. (2017). Acceptance and use of lecture capture system (LCS) in executive business studies: Extending UTAUT2. Interactive Technology and Smart Education, 14(4), 329–348.

Ghalandari, K. (2012). The effect of performance expectancy, effort expectancy, social influence and facilitating conditions on acceptance of e-banking services in Iran: The moderating role of age and gender. Middle-East Journal of Scientific Research, 12(6), 801–807.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8. Baskı). Eight Edition, Cengage: Learning EMEA.

Hapsari, M. I., & Abidin, Z. (2016). Zakat distribution in maqasid al-shariah framework. Journal of Islamic Financial Studies, 2(02).

Hossain, A., Quaresma, R., & Rahman, H. (2019). Investigating factors influencing the physicians’ adoption of electronic health record (EHR) in healthcare system of Bangladesh: An empirical study. International Journal of Information Management, 44, 76–87.

Hossain, M. A., Amin, R., Masud, A. Al, Hossain, M. I., Hossen, M. A., & Hossain, M. K. (2023). What drives people’s behavioral intention toward telemedicine? an emerging economy perspective. SAGE Open, 13(3), 21582440231181390.

Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic Management Journal, 20(2), 195–204.

Janssen, D., & Carradini, S. (2021). Generation Z workplace communication habits and expectations. IEEE Transactions on Professional Communication, 64(2), 137–153.

Jiang, Y., Ahmad, H., Butt, A. H., Shafique, M. N., & Muhammad, S. (2021). QR digital payment system adoption by retailers: the moderating role of COVID-19 knowledge. Information Resources Management Journal (IRMJ), 34(3), 41–63.

Jocevski, M., Ghezzi, A., & Arvidsson, N. (2020). Exploring the growth challenge of mobile payment platforms: A business model perspective. Electronic Commerce Research and Applications, 40, 100908.

Kabir, M. R., Sobhani, F. A., & Kausar, A. (2017). Management of Sadaqah through social enterprises: A study on Anjuman Mufidul Islam Bangladesh.

Kasilingam, D. L. (2020). Understanding the attitude and intention to use smartphone chatbots for shopping. Technology in Society, 62, 101280.

Kelly, S., Kaye, S.-A., & Oviedo-Trespalacios, O. (2023). What factors contribute to the acceptance of artificial intelligence? A systematic review. Telematics and Informatics, 77, 101925.

Khan, S., Khan, S. U., Khan, I. U., Khan, S. Z., & Khan, R. U. (2023). Understanding consumer adoption of mobile payment in Pakistan. Journal of Science and Technology Policy Management, ahead-of-print.

Kim, M. J., & Hall, C. M. (2020). What drives visitor economy crowdfunding? The effect of digital storytelling on unified theory of acceptance and use of technology. Tourism Management Perspectives, 34, 100638.

Lattu, A., & Maulana, A. (2023). Determinant Factors of Personal Innovativeness in Information Technology of Ride-Hailing New Brand: The Role of Gender. International Journal of Health Engineering and Technology (IJHET), 2(2).

Lee, S., Jones-Jang, S. M., Chung, M., Kim, N., & Choi, J. (2024). Who is using ChatGPT and why? Extending the Unified Theory of Acceptance and Use of Technology (UTAUT) model. Information Research an International Electronic Journal, 29(1), 54–72.

Liébana-Cabanillas, F., Kalinic, Z., Muñoz-Leiva, F., & Higueras-Castillo, E. (2024). Biometric m-payment systems: A multi-analytical approach to determining use intention. Information & Management, 61(2), 103907.

Limayem, M., Hirt, S. G., & Cheung, C. M. K. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS Quarterly, 705–737.

Lin, R.-R., Zheng, Y., & Lee, J.-C. (2023). Artificial intelligence-based pre-implementation interventions in users’ continuance intention to use mobile banking. International Journal of Mobile Communications, 21(4), 518–540.

Mahmud, A., Sarower, A. H., Sohel, A., Assaduzzaman, M., & Bhuiyan, T. (2024). Adoption of ChatGPT by university students for academic purposes: Partial least square, artificial neural network, deep neural network and classification algorithms approach. Array, 21, 100339.

Milicevic, N., Kalas, B., Djokic, N., Malcic, B., & Djokic, I. (2024). Students’ Intention toward Artificial Intelligence in the Context of Digital Transformation. Sustainability, 16(9), 3554.

Mishra, A., Shukla, A., Rana, N. P., Currie, W. L., & Dwivedi, Y. K. (2023). Re-examining post-acceptance model of information systems continuance: A revised theoretical model using MASEM approach. International Journal of Information Management, 68, 102571.

Moriuchi, E. (2021). An empirical study of consumers’ intention to use biometric facial recognition as a payment method. Psychology & Marketing, 38(10), 1741–1765.

Muqtadiroh, F. A., Herdiyanti, A., & Puspitasari, N. (2020). The e-learning quality model to examine students’ behavioral intention to use online learning platform in a higher education institution. Khazanah Informatika: Jurnal Ilmu Komputer Dan Informatika, 6(2).

Najib, M., & Fahma, F. (2020). Investigating the adoption of digital payment system through an extended technology acceptance model: An insight from the Indonesian small and medium enterprises. International Journal on Advanced Science, Engineering and Information Technology, 10(4), 1702–1708.

Neal, D. T., Wood, W., & Drolet, A. (2013). How do people adhere to goals when willpower is low? The profits (and pitfalls) of strong habits. Journal of Personality and Social Psychology, 104(6), 959.

Nguyen, D. M., Chiu, Y.-T. H., & Le, H. D. (2021). Determinants of continuance intention towards banks’ chatbot services in Vietnam: A necessity for sustainable development. Sustainability, 13(14), 7625.

Nguyen, M. S. (2023). Factors affecting Gen Z’s intention to use QR Pay in Vietnam after Covid-19. Innovative Marketing, 19(3), 100.

Nimansa, A. T., & Kuruwitaarachchi, N. (2020). A Study on Finding the Factors, Hindering the use of digital wallets among youth in Developing Countries. Scholedge International Journal of Management & Development, 7(6).

Octavius, G. S., & Antonio, F. (2021). Antecedents of intention to adopt mobile health (mHealth) application and its impact on intention to recommend: An evidence from Indonesian customers. International Journal of Telemedicine and Applications, 2021(1), 6698627.

Oktavendi, T. W., & Mu’ammal, I. (2022). Acceptance model for predicting adoption of Zakat, Infaq, and Sodaqoh (ZIS) digital payments in Generation Z. Journal of Islamic Accounting and Business Research, 13(4), 684–700.

Ouellette, J. A., & Wood, W. (1998). Habit and intention in everyday life: The multiple processes by which past behavior predicts future behavior. Psychological Bulletin, 124(1), 54.

Patil, P., Tamilmani, K., Rana, N. P., & Raghavan, V. (2020). Understanding consumer adoption of mobile payment in India: Extending Meta-UTAUT model with personal innovativeness, anxiety, trust, and grievance redressal. International Journal of Information Management, 54, 102144.

Puspitasari, I., Wiambodo, A. N. R., & Soeparman, P. (2021). The impact of expectation confirmation, technology compatibility, and customer’s acceptance on e-wallet continuance intention. AIP Conference Proceedings, 2329(1).

Rana, N. P., Dwivedi, Y. K., Lal, B., Williams, M. D., & Clement, M. (2017). Citizens’ adoption of an electronic government system: towards a unified view. Information Systems Frontiers, 19, 549–568.

Rasiah, D., & Yen, Y. Y. (2020). User acceptance of ATM biometric authentication. Global Journal of Computer Sciences: Theory and Research, 10(1), 11–17.

Roh, T., Park, B. Il, & Xiao, S. S. (2023). Adoption of AI-enabled Robo-advisors in Fintech: Simultaneous Employment of UTAUT and the Theory of Reasoned Action. Journal of Electronic Commerce Research, 24(1), 29–47.

Rosli, M. S., Saleh, N. S., Md. Ali, A., & Abu Bakar, S. (2023). Factors determining the acceptance of E-wallet among gen Z from the lens of the extended technology acceptance model. Sustainability, 15(7), 5752.

Saktyadi, A., & Tricahyono, D. (2024). Examining Customer Behavior Influences on MyPertamina App Adoption: A UTAUT2 Model Study in South Banten Gas Stations. International Journal of Economics & Business Administration (IJEBA), 12(2), 113–131.

Salem, M. Z., & Rassouli, A. (2024). Analyzing the impact of trust in financial institutions on Palestinian consumer attitudes towards AI-powered online banking: understanding key influencing factors. Competitiveness Review: An International Business Journal, ahead-of-print.

Samila, A. R., Shabrina, N. P., & Rokanta, S. A. (2022). Factors Affecting Behavioral Intention and Use Behavior of E-Commerce Users from Gen-Z Using UTAUT2 Model. 2022 International Conference on Information Management and Technology (ICIMTech), 262–267.

Saqr, R. R., Al-Somali, S. A., & Sarhan, M. Y. (2023). Exploring the acceptance and user satisfaction of AI-driven e-learning platforms (Blackboard, Moodle, Edmodo, Coursera and edX): an integrated technology model. Sustainability, 16(1), 204.

Sari, S. P., & Cristiana, S. (2022). Penerapan Model UTAUT (Unified Theory of Acceptance and Use of Technology) Terhadap Minat Penggunaan Mobile Banking Pada Masa Pandemi Berbasis Data Google Trends. Prosiding Seminar Nasional Hukum, Bisnis, Sains Dan Teknologi, 2(1), 698.

Saxena, C., Kumar, P., Sarvaiya, R., & Khatri, B. (2023). Attitude, behavioral intention and adoption of AI driven chatbots in the banking sector. 2023 IEEE IAS Global Conference on Emerging Technologies (GlobConET), 1–8.

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.

Singh, N., Sinha, N., & Liébana-Cabanillas, F. J. (2020). Determining factors in the adoption and recommendation of mobile wallet services in India: Analysis of the effect of innovativeness, stress to use and social influence. International Journal of Information Management, 50, 191–205.

Strzelecki, A., Cicha, K., Rizun, M., & Rutecka, P. (2024). Acceptance and use of ChatGPT in the academic community. Education and Information Technologies, 1–26.

Sukmana, R., Trianto, B., & Zaimsyah, A. M. (2023). Determinant factor of crowdfunders’ behavior in using crowdfunding waqf model in Indonesia: two competing models. Journal of Islamic Marketing, 14(7), 1793–1816.

Tu, M., Wu, L., Wan, H., Ding, Z., Guo, Z., & Chen, J. (2022). The adoption of QR code mobile payment technology during COVID-19: A social learning perspective. Frontiers in Psychology, 12, 798199.

Utami, S. B., Bawono, A. D. B., & Sasongko, N. (2023). Pengaruh Privasi, Keamanan, Keandalan, dan Transparansi Terhadap Minat Penggunaan Payment Fintech UMKM di Watukelir. Widya Cipta: Jurnal Sekretari Dan Manajemen, 7(2), 228–239.

Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 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, 157–178.

Vuong, B. N. (2023). A model of factors influencing customers’ intention to use e-wallets during COVID-19 in Vietnam. International Journal of Electronic Marketing and Retailing, 14(4), 434–452.

Wei, M.-F., Luh, Y.-H., Huang, Y.-H., & Chang, Y.-C. (2021). Young generation’s mobile payment adoption behavior: Analysis based on an extended UTAUT model. Journal of Theoretical and Applied Electronic Commerce Research, 16(4), 618–637.

Wood, W., Quinn, J. M., & Kashy, D. A. (2002). Habits in everyday life: thought, emotion, and action. Journal of Personality and Social Psychology, 83(6), 1281.

Yu, C.-W., Chao, C.-M., Chang, C.-F., Chen, R.-J., Chen, P.-C., & Liu, Y.-X. (2021). Exploring behavioral intention to use a mobile health education website: an extension of the UTAUT 2 model. Sage Open, 11(4), 21582440211055720.

Zhou, T., Lu, Y., & Wang, B. (2010). Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in Human Behavior, 26(4), 760–767.