The Behavioral Intention of Citizens to Finance Smart City Development in Indonesia through Civic Crowdfunding
DOI:
https://doi.org/10.14421/grieb.2023.112-06Keywords:
Civic Crowdfunding, Smart City, Financing, Technology Acceptance ModelAbstract
In order to foster the creation of sustainable and habitable urban areas that cater to the needs of all residents, it is imperative to construct new infrastructure and concurrently ensure the upkeep and modernization of existing ones. This is where the concept of smart cities becomes instrumental, exerting a profound impact on the broader urban landscape. However, a significant challenge lies in securing the financial resources required for the development of smart cities, particularly in the midst of the current economic downturn. As a solution to this challenge, the present study proposes the implementation of an Integrated Civic Crowdfunding Model (ICCM) to finance the development of smart cities in East Java, Indonesia. Based on this proposed model, the study delves into the willingness of citizens to adopt ICCM. To achieve this, an analysis is performed utilizing Partial Least Squares on primary data collected through a survey administered to residents of East Java, specifically in Surabaya (SmartPLS). Additionally, the study assesses the model's adoption in practice by incorporating an extended Technology Acceptance Model (TAM). The study's results reveal that factors such as the perceived usefulness, perceived ease of use, and perceived benefits positively influence residents' intentions to use ICCM, thereby contributing to the advancement of smart cities in Indonesia. Furthermore, there is a favorable correlation and direct impact of perceived ease of use on the perceived utility of ICCM among citizens. These findings can serve as a foundation for the development of a specialized framework for examining other aspects of the ICCM model and devising relevant intervention strategies for the enhancement of smart cities in East Java.
Originality/Value: The originality of this study lies in its introduction and application of the Integrated Civic Crowdfunding Model (ICCM) to finance the development of smart cities in East Java, Indonesia.
Downloads
Abstract viewed: 114 times
|
PDF downloaded = 107 times
References
Abbasi, A., Hossain, L., Uddin, S., & Rasmussen, K. J. R. (2011). Evolutionary dynamics of scientific collaboration networks: Multi-levels and cross-time analysis. Scientometrics, 89(2), 687-710.
Boyle, T. M. (2016). The city and the crowd: An exploration of civic crowdfunding disruption to local government led city planning and the quest to co-create liveability [Master Thesis, University of New England].
Breuer, J., Walravens, N., & Ballon, P. (2014). Beyond defining the smart city: Meeting top-down and bottom-up approaches in the middle. TeMA: Journal of Land Use, Mobility and Environment. http://doi.org/10.6092/1970-9870/2475
Carvalho, L. (2015). Smart cities from scratch? A socio-technical perspective. Cambridge Journal of Regions Economy and Society, 8(1), 43-60. https://www.doi.org/10.1093/cjres/rsu010
Cheng, E. W., Li, H., & Fox, P. (2007). Job performance dimensions for improving final project outcomes. Journal of Construction Engineering and Management, 133(8), 592-599.
Costa, S., Chira, C., Deambrogio, E., Horatz, M., Lindholm, P., Nielsen, D., Pasic, E., & Bhana, R. (2013). Using EU funding mechanisms for smart cities. In J. N. Ferrer (Ed.), Smart Cities Stakeholder Platform. Smart Cities and Communities.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13, 983-1003.
Doan, M. A., & Toledano, M. (2018). Beyond organization-centred public relations: Collective action through a civic crowdfunding campaign. Public Relations Review, 44(1), 37–46.
Farooq, M. S., & Radovic-Markovic, M. (2016). Modeling entrepreneurial education and entrepreneurial skills as antecedents of intention towards entrepreneurial behaviour in single mothers: A PLS-SEM approach. Entrepreneurship: Types, Current Trends and Future Perspectives, 198, 216.
Fornell, C., & Larcker, D. F., (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
Gefen, D., & Straub, D. W. (2004). Consumer trust in B2C e-Commerce and the importance of social presence: Experiments in e-Products and e-Services. Omega, 32(6), 407-424.
Gierczak, M. M., Bretschneider, U., Haas, P., Blohm, I. and Leimeister, J. M. (2015). Crowdfunding: Outlining the new era of fundraising. In O. Gajda, & Brüntje, D. (Eds.) Crowdfunding in Europe: State of the art in theory and practice. Springer.
Gkypali, A., Arvanitis, S., Tsekouras, K. (2018). Absorptive capacity, exporting activities, innovation openness and innovation performance: A SEM approach towards a unifying framework. Technological Forecasting and Social Change, 132(C), 143–155.
Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge management: An organizational capabilities perspective. Journal of Management Information Systems, 18(1), 185-214.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2013). A primer on partial least squares structural equation modeling (PLS-SEM). Sage.
Hair, J., Blake, W., Babin, B., & Tatham, R. (2006). Multivariate data analysis. Prentice Hall.
Hair Jr, 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), 107-123.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139-152.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135.
Indiegogo. (2015). Greek bailout fund. Indiegogo.
Kabbiri, R., Dora, M., Kumar, V., Elepu, G., & Gellynck, X. (2018). Mobile phone adoption in agri-food sector: Are farmers in Sub-Saharan Africa connected? Technological Forecasting and Social Change, 131, 253–261.
Kline, R. B. (2011). Convergence of structural equation modeling and multilevel modeling. The SAGE Handbook of Innovation in Social Research Methods, 562-589.
Kulkki, S. (2014). Cities for solving societal challenges towards human-centric socio-economic development? Interdisciplinary Studies Journal, 3(4), 8–14.
Manville, C., Cochrane, G., Cave, J., Millard, J., Pederson, J. K., Thaarup, R. K., Liebe, A., Wissner, M., Massink, R., & Kotterink, B. (2014). Mapping smart cities in the EU. European Parliament.
McKinnon, K., & Igonor, A. (2008, November). Explaining eLearning perceptions using the technology acceptance model and the theory of planned behavior. E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, 2994-2999. Association for the Advancement of Computing in Education (AACE).
Ndubisi, N. O., Jantan, M., & Richardson, S. (2001). Is the technology acceptance model valid for entrepreneurs? Model testing and examining usage determinants. Asian Academy of Management Journal, 6(2), 31-54.
Ngah, K. (2009). The future challenges of local authorities in Malaysia. Centre for Policy Research & International Studies, Universiti Sains Malaysia.
Neirotti, P., Marco, A. D., Cagliano, A. C., Mangano, G., & Scorrano, F. (2014). Current trends in smart city initiatives: Some stylised facts. Cities, 38, 25–36.
Praharaj, S., Han, J. H., & Hawken, S. (2018). Towards the right model of smart city governance in India. International Journal of Sustainable Development and Planning, 13(2), 171–186. http://doi.org/10.2495/SDP-V13-N2-171-186
Pearlson, K. E., & Saunders, C. S. (2006). Managing & using information systems: A strategic approach. John Wiley & Sons.
Pierce, P., & Andersson, B. (2017). Challenges with smart cities initiatives: A municipal decision makers perspective. Proceedings of the Hawaii International Conference on System Sciences, 2804–2813. Institute of Electrical and Electronics Engineers.
Ramayah, T., Ma’ruf, J. J., Jantan, M., & Osman, M. (2002). Technology acceptance model: Is it applicable to users and non-users of internet banking. Proceedings of the International Seminar, Indonesia-Malaysia, the Role of Harmonization of Economics and Business Discipline in Global Competitiveness, Banda Aceh, Indonesia, 14-15.
Ramayah, T., Jantan, M., Noor, M. N. M., Razak, R. C., & Koay, P. L. (2003). Receptiveness of internet banking by Malaysian consumers: The case of Penang. Asian Academy of Management Journal, 8(2), 1-29.
Ramayah, T., & Aafaqi, B. (2004). Role of self-efficacy in e-library usage among students of a public university in Malaysia. Malaysian Journal of Library & Information Science, 9(1), 39-57.
Ramayah, T., Ling, N. S., Taghizadeh, S. K., & Rahman, S. A. (2016). Factors influencing SMEs website continuance intention in Malaysia. Telematics and Informatics, 33(1), 150-164.
Ringle, C. M., & Sarstedt, M. (2016). Gain more insight from your PLS-SEM results: The importance-performance map analysis. Industrial Management & Data Systems, 116(9), 1865-1886.
Setijadi, E., Darmawan, A. K., Mardiyanto, R., Santosa, I., Hoiriyah, & Kristanto, T. (2019). a model for evaluation smart city readiness using structural equation modelling: A citizen's perspective. Fourth International Conference on Informatics and Computing (ICIC), 1-7. http://doi.org/10.1109/ICIC47613.2019.8985969
Shareef, M. A., Kumar, U., Kumar, V., Dwivedi, Y. K. (2009). Identifying critical factors for adoption of E-government. Electronic Government an International Journal, 6(1), 70–96. http://doi.org/10.1504/EG.2009.022594
Silva, B. N., Khan, M., & Han, K. (2018). Towards sustainable smart cities: A review of trends, architectures, components, and open challenges in smart cities. Sustainable Cities and Society, 38, 697–713. https://doi.org/10.1016/j.scs.2018.01.053
Venkatesh, V., Morris, M. G., & Ackerman, P. L. (2000). A longitudinal field investigation of gender differences in individual technology adoption decision-making processes. Organizational Behavior and Human Decision Processes, 83(1), 33-60.
Verma, P., & Sinha, N. (2018). Integrating perceived economic wellbeing to technology acceptance model: The case of mobile based agricultural extension service. Technological Forecasting and Social Change, 126, 207–216.
Vilajosana, I., Llosa, J., Martinez, B., Prieto, M. D., Angles, A., & Vilajosana, X. (2013). Bootstrapping Smart Cities through a Self-Sustainable Model Based on Big Data Flows. IEEE Communications Magazine, 51(6), 128-134. http://dx.doi.org/10.1109/MCOM.2013.6525605
Wenzlaff, K., Hoffmann, A., & Pachali, D. (2012). Freiwillig bezahlen? Crowdfunding und social payment im journalismus. In D. Pachali (Ed.), Öffentlichkeit Im Wandel: Medien, Internet, Journalismus (pp. 82–87). Heinrich-Böll-Stiftung.
Wenzlaff, K. (2020). Civic crowdfunding: Four perspectives on the definition of civic crowdfunding. In R. Shneor, L. Zhao, & B. T. Flåten (Eds), Advances in crowdfunding: Research and practice. Palgrave Macmillan.
Yi, Y., Wu, Z., & Tung, L. L. (2005). How individual differences influence technology usage behavior? Toward an integrated framework. Journal of Computer Information Systems, 46(2), 52-63.
Yong, H. K. (2017). Infrastructure financing in Malaysia. Nomura Journal of Asian Capital Markets, 1(2), 26-30.
Zanella, A., Bui, N., Castellani, A., Vangelista, L., & Zorzi, M. (2014). Internet of things for smart cities, IEEE Internet of Things Journal, 1(1), 22-32. https://www.doi.org/10.1109/JIOT.2014.2306328
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Global Review of Islamic Economics and Business is licensed under a
Creative Commons Attribution-ShareAlike 4.0 International License
