Amidst China’s burgeoning population and rapid technological strides, this study explores how elderly citizens navigate and embrace electronic governance (e-governance) platforms. Addressing a crucial gap in knowledge, we delve into their limited digital fluency and its impact on e-governance adoption. Our meticulously crafted online survey, distributed via WeChat across significant cities (Beijing, Shanghai, Tianjin, Changsha), yielded 396 responses (384 analyzable). Utilizing Structural Equation Modeling (SEM), we unearthed key influencers of subjective norms, including perceived ease and usefulness, trust, supportive conditions, and past tech exposure. These norms, in turn, positively shape attitudes. Crucially, educational background emerges as a moderator, amplifying the positive link between attitudes and e-governance engagement intent. This underscores the necessity of an inclusive, customized e-governance approach, offering valuable policy insights and advocating for holistic solutions for older adults. Our research yields empirical and theoretical contributions, paving the way for actionable Social Sustainability Marketing Technologies in China, particularly championing digital inclusivity for seniors.

Adjei-Bamfo, P., Domfeh, K. A., Bawole, J. N., Ahenkan, A., Maloreh-Nyamekye, T., Adjei-Bamfo, S., & Darkwah, S. A. (2020). An e-government framework for assessing readiness for public sector e-procurement in a lower-middle income country. Information Technology for Development, 26(4), 742–761. https://doi.org/10.1080/02681102.2020.1769542

Ahamd, M. (2019). State of the Art Compendium of Macro and Micro Energies. Advances in Science and Technology Research Journal, 13(1), 88–109. https://doi.org/10.12913/22998624/103425

Syed Ahmed, M., & Kabir, S. M. A. (2018). The Acceptance of Smartphone as a Mobile Learning Tool: Students of Business Studies in Bangladesh. Malaysian Online Journal of Educational Technology, 6(2), 38–47. https://doi.org/10.17220/mojet.2018.02.003

Alarcon, G. M., Lyons, J. B., Christensen, J. C., Bowers, M. A., Klosterman, S. L., & Capiola, A. (2018). The role of propensity to trust and the five factor model across the trust process. Journal of Research in Personality, 75, 69–82. https://doi.org/10.1016/j.jrp.2018.05.006

Albesher, A. S., & Stone, R. T. (2016). Current state of m-government research: identifying future research opportunities. International Journal of Electronic Governance, 8(2), 119. https://doi.org/10.1504/ijeg.2016.078118

Al-Gahtani, S. S., & King, M. (1999). Attitudes, satisfaction and usage: Factors contributing to each in the acceptance of information technology. Behaviour & Information Technology, 18(4), 277–297. https://doi.org/10.1080/014492999119020

Al-Gahtani, S. S., Hubona, G. S., & Wang, J. (2007). Information technology (IT) in Saudi Arabia: Culture and the acceptance and use of IT. Information & Management, 44(8), 681–691. https://doi.org/10.1016/j.im.2007.09.002

Ali, M., & Mujahid, N. (2015). Electronic government re-inventing governance: A case study of Pakistan. Electronic Government, 5(2).

Alneyadi, A., Hilmi, M. F., Ayub, M. A., & Abudaqa, A. (2022). The moderating role of online trust on the relationship between service dynamics, information awareness, citizen satisfaction to e_government services and continence intention: a case of uae. International Journal of Law, Government, and Communication, 7(29), 171–189. https://doi.org/10.35631/IJLGC.729013

Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423. https://doi.org/10.1037/0033-2909.103.3.411

Arbuckle, J. (2003). Amos 5.0 update to the Amos user’s guide. Marketing Department, SPSS Incorporated.

Babar, U., & Ahmed, S. (2023). Cultural Intermingling in Ahmad Ali’s “Twilight In Delhi”: A Post-Colonial Criticism. Journal of Advances in Humanities Research, 2(3), 84–96. https://doi.org/10.56868/jadhur.v2i3.130

Bell, J. (2005). A guide for first-time researchers in education, health and social science. Open University Press.

Bhattacherjee, A. (2000). Acceptance of e-commerce services: the case of electronic brokerages. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 30(4), 411–420. https://doi.org/10.1109/3468.852435

Birmingham, P., & Wilkinson, D. (2003). Using research instruments: A guide for researchers. Routledge.

Blackler, A., Popovic, V., & Mahar, D. (2010). Investigating users’ intuitive interaction with complex artefacts. Applied Ergonomics, 41(1), 72–92. https://doi.org/10.1016/j.apergo.2009.04.010

Blank, G., & Dutton, W. H. (2011). Age and Trust in the Internet: The Centrality of Experience and Attitudes Toward Technology in Britain. Social Science Computer Review, 30(2), 135–151. https://doi.org/10.1177/0894439310396186

Boontarig, W., Chutimaskul, W., Chongsuphajaisiddhi, V., & Papasratorn, B. (2012). Factors influencing the Thai elderly intention to use smartphones for e-health services. In: 2012, the IEEE Symposium on Humanities, science, and engineering research. pp. 479–483. IEEE.

Chen, L., & Aklikokou, A. K. (2019). Determinants of E-government Adoption: Testing the Mediating Effects of Perceived Usefulness and Perceived Ease of Use. International Journal of Public Administration, 43(10), 850–865. https://doi.org/10.1080/01900692.2019.1660989

Chong, A. Y.-L., Ooi, K.-B., Lin, B., & Bao, H. (2012). An empirical analysis of the determinants of 3G adoption in China. Computers in Human Behavior, 28(2), 360–369. https://doi.org/10.1016/j.chb.2011.10.005

Choudrie, J., Pheeraphuttranghkoon, S., & Davari, S. (2018). The Digital Divide and Older Adult Population Adoption, Use and Diffusion of Mobile Phones: a Quantitative Study. Information Systems Frontiers, 22(3), 673–695. https://doi.org/10.1007/s10796-018-9875-2

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

Donat, E., Brandtweiner, R., & Kerschbaum, J. (2009). Attitudes and the Digital Divide: Attitude Measurement as Instrument to Predict Internet Usage. Informing Science: The International Journal of an Emerging Transdiscipline, 12, 037–056. https://doi.org/10.28945/427.

Draheim, D., & Butt, S. (2019). Relevance of the UN e-Government surveys and the OECD Digital Government Index 2019 to e-government Stakeholders: The Case of Antigua and Barbuda.

Dugdale, J. S. (2018). Entropy And Its Physical Meaning. Taylor & Francis. https://doi.org/10.1201/9781315274324

El-Gayar, O. F., & Moran, M. (2006). College students’ Acceptance of tablet PCs: An application of the UTAUT model.

Fatima, T., Zalfaqar, M., Ali Mehdi, A., & Ahmed, S. (2023). Investigation of Professional, Spiritual and Emotional Intelligence on Organizational Learning. International Journal of Management Thinking, 1(1), 1–19. https://doi.org/10.56868/ijmt.v1i1.11

Feng, Y., Zhang, Y., Ying, C., Wang, D., & Du, C. (2015). Nanopore-based Fourth-generation DNA Sequencing Technology. Genomics, Proteomics & Bioinformatics, 13(1), 4–16. https://doi.org/10.1016/j.gpb.2015.01.009

Fishbein, M., & Ajzen, I. (1977). Belief, attitude, intention, and behaviour: An introduction to theory and research.

Gordon, N. P., & Hornbrook, M. C. (2018). A cross-sectional survey of older adults’ readiness to engage with eHealth patient education and self-care resources. BMC health services research, 18, 1-13. https://doi.org/10.1186/s12913-018-2986-0

Gronlund, A. (2002). Electronic government: design, applications and management. IGI Global.

Guo, X., Sun, Y., Wang, N., et al. (2013). The dark side of elderly Acceptance of preventive mobile health services in China. Electronic Markets, 23(1), 49–61. https://doi.org/10.1007/s12525-012-0112-4

Gustova, D. (2017). The impact of e-government strategy on economic growth and social development [Doctoral dissertation]. ISCTE-Instituto Universitario de Lisboa (Portugal).

Guner, H., & Acarturk, C. (2020). The use and acceptance of ICT by senior citizens: a comparison of technology acceptance model (TAM) for elderly and young adults. Universal Access in the Information Society, 19, 311-330.

Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis. Englewood cliff. New Jersey, USA, 5(3), 207.

Harris, M. T., & Rogers, W. A. (2023). Developing a healthcare technology acceptance model (H-TAM) for older adults with hypertension. Ageing & Society, 43(4), 814-834.

Hardill, I., & Olphert, C. W. (2012). Staying connected: Exploring mobile phone use amongst older adults in the UK. Geoforum, 43(6), 1306–1312. https://doi.org/10.1016/j.geoforum.2012.03.016

Hartanto, D., Dalle, J., Akrim, A., & Anisah, H. U. (2021). Perceived effectiveness of e-governance as an underlying mechanism between good governance and public trust: a case of Indonesia. Digital Policy, Regulation and Governance, 23(6), 598–616. https://doi.org/10.1108/dprg-03-2021-0046

Hong, J.-C., Lin, P.-H., & Hsieh, P.-C. (2017). The effect of consumer innovativeness on perceived value and continuance intention to use smartwatch. Computers in Human Behavior, 67, 264–272. https://doi.org/10.1016/j.chb.2016.11.001

Hou, F., Guan, Z., Li, B., & Chong, A. Y. L. (2019). Factors influencing people’s continuous watching intention and consumption intention in live streaming. Internet Research, 30(1), 141–163. https://doi.org/10.1108/intr-04-2018-0177

Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118

Jackson, C. M., Chow, S., & Leitch, R. A. (1997). Toward an Understanding of the Behavioral Intention to Use an Information System. Decision Sciences, 28(2), 357–389. Portico. https://doi.org/10.1111/j.1540-5915.1997.tb01315.x

Jeng, R., & Tseng, S. M. (2018). The relative importance of computer self-efficacy, perceived ease-of-use and reducing search cost in determining consumers’ online group-buying intention. International Journal of Human and Technology Interaction (IJHaTI), 2(1), 1–12.

Khaleel, R., & Hussain, A. (2023). Measurement Of Acute Poverty in Achini Bala-Peshawar, Pakistan; A Multidimensional Poverty Index (MPI) Approach. Journal of Advances in Humanities Research, 2(3), 146–169. https://doi.org/10.56868/jadhur.v2i3.175

Khan, U., Cheng, Y., Shah, Z. A., & Ullah, S. (2020). Resistance in disguise and the re-construction of identity: a case of the Pashtuns in Pakistan. Inter-Asia Cultural Studies, 21(3), 374–391. https://doi.org/10.1080/14649373.2020.1797121

Kurfalı, M., Arifoğlu, A., Tokdemir, G., & Paçin, Y. (2017). Adoption of e-government services in Turkey. Computers in Human Behavior, 66, 168–178. https://doi.org/10.1016/j.chb.2016.09.041

Lai, X., Zhang, Q., Chen, Q., Huang, Y., Mao, N., & Liu, J. (2018). The analytics of product-design requirements using dynamic internet data: application to Chinese smartphone market. International Journal of Production Research, 57(18), 5660–5684. https://doi.org/10.1080/00207543.2018.1541200

Lee, B., Chen, Y., & Hewitt, L. (2011). Age differences in constraints encountered by seniors in their use of computers and the internet. Computers in Human Behavior, 27(3), 1231–1237. https://doi.org/10.1016/j.chb.2011.01.003

Lee, J. B., & Porumbescu, G. A. (2019). Engendering inclusive e-government use through citizen IT training programs. Government Information Quarterly, 36(1), 69–76. https://doi.org/10.1016/j.giq.2018.11.007

Lin, C. A., & Kim, T. (2016). Predicting user response to sponsored advertising on social media via the technology acceptance model. Computers in Human Behavior, 64, 710–718. https://doi.org/10.1016/j.chb.2016.07.027

Lu, X., Hong, J., Zhang, L., Cooper, O. R., Schultz, M. G., Xu, X., Wang, T., Gao, M., Zhao, Y., & Zhang, Y. (2018). Severe Surface Ozone Pollution in China: A Global Perspective. Environmental Science & Technology Letters, 5(8), 487–494. https://doi.org/10.1021/acs.estlett.8b00366

Marengo, D., Sindermann, C., Häckel, D., Settanni, M., Elhai, J. D., & Montag, C. (2020). The association between the Big Five personality traits and smartphone use disorder: A meta-analysis. Journal of Behavioral Addictions, 9(3), 534–550. https://doi.org/10.1556/2006.2020.00069

Marinina, O., Kirsanova, N., & Nevskaya, M. (2022). Circular Economy Models in Industry: Developing a Conceptual Framework. Energies, 15(24), 9376. https://doi.org/10.3390/en15249376

Miller, L., Naidoo, M., Van Belle, J. P., & Chigona, W. (2006). School-level ICT adoption factors in the Western Cape schools. In Fourth IEEE International Workshop on Technology for Education in Developing Countries (TEDC'06). pp. 57–61. IEEE.

Mills, J. S. (2016). Evaluating teleworkers’ Acceptance of mobile technology: A study based on the utaut model [Doctoral dissertation] Capella University.

Ming, C., Chen, T., & Ai, Q. (2018). An empirical study of e-service quality and user satisfaction of public service centres in China. International Journal of Public Administration in the Digital Age (IJPADA), 5(3), 43-59. DOI: 10.4018/IJPADA.2018070104

Morris, M. G., & Venkatesh, V. (2000). Age differences in technology adoption decisions: Implications for a changing workforce. Personnel Psychology, 53(2), 375–403. https://doi.org/10.1111/j.1744-6570.2000.tb00206.x

Nawaz, F., Shakeel, S., Nawaz, Z., & Hamza, M. A. (2017). Logforum, 13(2). https://doi.org/10.17270/j.log.2017.2.3

Niederhauser, D. S., Howard, S. K., Voogt, J., Agyei, D. D., Laferriere, T., Tondeur, J., & Cox, M. J. (2018). Sustainability and Scalability in Educational Technology Initiatives: Research-Informed Practice. Technology, Knowledge and Learning, 23(3), 507–523. https://doi.org/10.1007/s10758-018-9382-z

Oliveira, T. A., Oliver, M., & Ramalhinho, H. (2020). Challenges for Connecting Citizens and Smart Cities: ICT, E-Governance and Blockchain. Sustainability, 12(7), 2926. https://doi.org/10.3390/su12072926

Pitchayadejanant, K. (2011). Intention to use the smartphone in Bangkok extended the UTAUT model by perceived value. In International Conference on Management (ICM 2011) proceeding. Conference Master Resources.

Poquiz, M. R., Hassan, R., & Ahmed, S. (2023). Gender Diversity Management Practices in the Hotel Industry: An Analysis of Philippine Hotel Industry. International Journal of Management Thinking, 1(1), 41–50. https://doi.org/10.56868/ijmt.v1i1.12

Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879–891. https://doi.org/10.3758/brm.40.3.879

Price, S. D., Holman, C. D. J., Sanfilippo, F. M., & Emery, J. D. (2014). Association Between Potentially Inappropriate Medications from the Beers Criteria and the Risk of Unplanned Hospitalization in Elderly Patients. Annals of Pharmacotherapy, 48(1), 6–16. https://doi.org/10.1177/1060028013504904

Renaud, K., & Van Biljon, J. (2008). Predicting technology acceptance and adoption by older people: a qualitative study. In Proceedings of the 2008 annual research conference of the South African Institute of Computer Scientists and Information Technologists on IT research in developing countries: riding the wave of technology. pp. 210-219.

Roque, N. A., & Boot, W. R. (2016). A New Tool for Assessing Mobile Device Proficiency in Older Adults: The Mobile Device Proficiency Questionnaire. Journal of Applied Gerontology, 37(2), 131–156. https://doi.org/10.1177/0733464816642582

Schmitter, P. C. (2018). Defining, Explaining and, then, Exploiting the Elusive Concept of “Governance.” Fudan Journal of the Humanities and Social Sciences, 12(4), 547–567. https://doi.org/10.1007/s40647-018-0236-9

Shareef, M. A., Kumar, V., Kumar, U., & Dwivedi, Y. K. (2011). e-Government Adoption Model (GAM): Differing service maturity levels. Government Information Quarterly, 28(1), 17–35. https://doi.org/10.1016/j.giq.2010.05.006

Siddique, W. (2016). Critical Success Factors Affecting E-Government Policy Implementation in Pakistan. JeDEM - EJournal of EDemocracy and Open Government, 8(1), 102–126. https://doi.org/10.29379/jedem.v8i1.398

Solinthone, P., & Rumyantseva, T. (2016). E-Government Implementation. MATEC Web of Conferences, 79, 01066. https://doi.org/10.1051/matecconf/20167901066

Sun, D., Lau, K. M., & Kafatos, M. (2008). Contrasting the 2007 and 2005 hurricane seasons: Evidence of possible impacts of Saharan dry air and dust on tropical cyclone activity in the Atlantic basin. Geophysical Research Letters, 35(15). Portico. https://doi.org/10.1029/2008gl034529

Tezci, E. (2011). Factors that influence pre-service teachers’ ICT usage in education. European Journal of Teacher Education, 34(4), 483–499. https://doi.org/10.1080/02619768.2011.587116

Tolston, M. T., Funke, G. J., Alarcon, G. M., et al. (2018). Have a heart: Predictability of trust in an autonomous agent teammate through team-level measures of heart rate synchrony and arousal. Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 62(1): 714–715. https://doi.org/10.1177/1541931218621162

Turban, E., King, D., Lee, J., & Viehland, D. (2004). Electronic Commerce: a managerial perspective 2004. Pearson Education.

Ursavaş, Ö. F., Yalçın, Y., & Bakır, E. (2019). The effect of subjective norms on preservice and in‐service teachers’ behavioural intentions to use technology: A multigroup multimodel study. British Journal of Educational Technology, 50(5), 2501–2519. Portico. https://doi.org/10.1111/bjet.12834

Venkatesh, V., & Bala, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Sciences, 39(2), 273–315. Portico. https://doi.org/10.1111/j.1540-5915.2008.00192.x

Venkatesh, & Ramesh. (2006). Web and Wireless Site Usability: Understanding Differences and Modeling Use. MIS Quarterly, 30(1), 181. https://doi.org/10.2307/25148723

Venkatesh, V., Chan, F. K. Y., & Thong, J. Y. L. (2011). Designing e‐government services: Key service attributes and citizens’ preference structures. Journal of Operations Management, 30(1–2), 116–133. Portico. https://doi.org/10.1016/j.jom.2011.10.001

Venkatesh, Morris, Davis, & Davis. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425. https://doi.org/10.2307/30036540

Yang, F. X. (2016). Effects of Restaurant Satisfaction and Knowledge Sharing Motivation on eWOM Intentions. Journal of Hospitality & Tourism Research, 41(1), 93–127. https://doi.org/10.1177/1096348013515918

Yildiz, M. (2007). E-government research: Reviewing the literature, limitations, and ways forward. Government Information Quarterly, 24(3), 646–665. https://doi.org/10.1016/j.giq.2007.01.002

Yu-Huei, C., Ja-Shen, C., & Ming-Chao, W. (2019). Why do older adults use wearable devices: a case study adopting the Senior Technology Acceptance Model (STAM). In: 2019 Portland International Conference on Management of Engineering and Technology (PICMET) (25-29 August 2019); Portland, OR, USA.

Zahid, H., Ali, S., Abu-Shanab, E., & Javed, H. M. U. (2022). Determinants of intention to use e-government services: An integrated marketing relation view. Telematics and Informatics, 68, 101778. https://doi.org/10.1016/j.tele.2022.101778

Zhang, Z., Jiménez, F. R., & Yang, S. (2022). The effect of country of origin on the perceived quality of e-services. International Journal of Electronic Marketing and Retailing, 13(4), 411. https://doi.org/10.1504/ijemr.2022.125584

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. https://doi.org/10.1016/j.chb.2010.01.013