Identifying Costs and Benefits of Smart City Applications from End-users' Perspective
Keywords:
smart city applications, smart parking, water quality monitoring, air quality monitoring, real-time public transit information, integrated smart solutions, end-users perceptions, cost-benefit analysisAbstract
The widespread availability and adoption of various smart city solutions have benefited their users by providing new services and information generated in realtime. These solutions use different types of sensors and GPS to collect, process and display data within the web and/or mobile applications. Focusing on the determinants of the intentions to use an application or its success, a large number of researchers developed and validated models such as TAM, UTAUT, IS Success Model and similar ones. This paper presents an exploratory approach that is based on the cost-benefit analysis with end-users who were invited to express their perceptions of different smart city solutions. Qualitative data were collected to devise a research instrument in subsequent phases based on the feedback from second-year business students. For each of the selected four smart city applications (smart parking, water quality monitoring, air quality monitoring, and real-time traffic monitoring), respondents were asked to work in groups and create a list of benefits and costs from their perspective. The analysis resulted with the list of 98 different cost and benefit statements (16 costs common for four smart city applications, 12 benefits common for four smart city applications, 10 distinctive costs and 60 specific benefits).
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
References
Albino, V., Berardi, U., Dangelico, R. M. (2015), “Smart cities : definitions, dimensions, performance, and initiatives”, Journal of Urban Technology, Vol. 22, No. 1, pp. 3-21.
Althunibat, A., Alrawashdeh, T. A., Muhairat, M. (2014), “The acceptance of using M-government services in Jordan”, in Latifi, S. (Ed.), 11th International Conference on Information Technology: New Generations ITNG 2014, 7-9 April, IEEE, Las Vegas, NV, pp. 643-644.
Ćukušić, M., Jadrić, M., Mijač, T. (2019), “Identifying challenges and priorities for developing smart city initiatives and applications”, Croatian Operational Research Review, Vol. 10, No. 1, pp. 117-129.
Davis, F. D. (1989), “Perceived usefulness, perceived ease of use, and user acceptance of information technology”, MIS Quarterly, Vol. 13, No. 3, pp. 319-340.
DeLone, W. H., McLean, E. R. (2003), “The DeLone and McLean model of information systems success: a ten-year update”, Journal of Management Information Systems, Vol. 19, No. 4, pp. 9-30.
Drèze, J., Stern, N. (1987), “The theory of cost-benefit analysis”, in Auerbach, A. J., Feldstein, M. (Eds.), Handbook of Public Economics, Vol. 2, North Holland, Amsterdam, pp. 909-989.
Forkan, A. R. M., Kimm, G., Morshed, A., Jayaraman, P. P., Banerjee, A., Huang, W. (2019), “AqVision: A tool for air quality data visualisation and pollution-free route tracking for smart city”, in Wyeld, T. G., Banissi, E., Ursyn, A., Bannatyne, M., Datia, N., Sarfraz, M. (Eds.), 23rd International Conference in Information Visualization - Part II, 16-19 July, IEEE, Adelaide, Australia, pp. 47-51.
Frascella, A., Brutti, A., Gessa, N., De Sabbata, P., Novelli, C., Burns, M., Bhatt, V., Ianniello, R., He, L. (2018), “A minimum set of common principles for enabling smart city interoperability”, TECHNE-Journal of Technology for Architecture and Environment, No.1, pp. 56-61.
Gunawan, H. (2018), “Identifying factors affecting smart city adoption using the unified theory of acceptance and use of technology (UTAUT) method”, 2018 International Conference on Orange Technologies ICOT 2018, 23-26 October, IEEE, Nusa Dua, BALI, Indonesia, pp. 1-4.
Guo, G., Li, Y., Zheng, S. (2019), “Factors influencing university students' intention to redeem digital takeaway coupons - Analysis based on a survey in China”, 7th International Conference on Information Technology: IoT and Smart City, 20-23 December, Association for Computing Machinery, Shanghai, China, pp. 419-425.
Habib, A., Alsmadi, D., Prybutok, V. R. (2019), “Factors that determine residents' acceptance of smart city technologies”, Behaviour & Information Technology, Vol. 39, No. 6, pp. 610-623.
Lee, J. (2010), “10 year retrospect on stage models of e-government: a qualitative meta-synthesis”, Government Information Quarterly, Vol. 27, No. 3, pp. 220-230.
Liao, C. H., Tsou, C. W., Huang, M. F. (2007), “Factors influencing the usage of 3G mobile services in Taiwan”, Online Information Review, Vol. 31, No. 6, pp. 759-774.
Marangunić, N., Granić, A. (2015), “Technology acceptance model: a literature review from 1986 to 2013', Universal Access in the Information Society, Vol. 14, No. 1, pp. 81–95.
Masera, M., Bompard, E. F., Profumo, F., Hadjsaid, N. (2018), “Smart (electricity) grids for smart cities: assessing roles and societal impacts', Proceedings of the IEEE, Vol. 106, No. 4, pp. 613-625.
Mensah, I. K. (2018), “Citizens' readiness to adopt and use e-government services in the City of Harbin, China”, International Journal of Public Administration, Vol. 41, No. 4, pp. 297-307.
Prybutok, V. R., Zhang, X., Ryan, S. D. (2008), “Evaluating leadership, IT quality, and net benefits in an e-government environment”, Information & Management, Vol. 45, No. 3, pp. 143-152.
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, Vol. 19, No. 3, pp. 549-568.
Rogulj, D. (2017), “Warning: do not drink tap water in Split and surrounding areas today!”, available at: https://www.total-croatia-news.com/tell-me-something-about-split/23261-warning-do-not-drink-tap-water-in-split-and-surrounding-areas-today (5 May 2020)
Sepasgozar, S. M. E., Hawken, S., Sargolzaei, S., Foroozanfa, M. (2019), “Implementing citizen centric technology in developing smart cities: a model for predicting the acceptance of urban technologies”, Technological Forecasting and Social Change, Vol. 142, pp. 105-116.
Singh, G., Singh, V. (2018), “Citizen centric assessment framework for e-governance services quality”, International Journal of Business Information Systems, Vol. 27, No. 1, pp. 1-20.
Susanto, T. D., Diani, M. M., Hafidz, I. (2017), “User acceptance of e-government citizen report system (a case study of city113 app)”, Procedia Computer Science, Vol. 124, pp. 560-568.
Tan, C. W., Benbasat, I., Cenfetelli, R. T. (2013), “IT-mediated customer service content and delivery in electronic governments: an empirical investigation of the antecedents of service quality”, MIS Quarterly, Vol. 37, No. 1, pp. 77-109.
Tomitsch, M. (2018,) Making Cities Smarter, Jovis, Berlin.
Trencher, G., Karvonen, A. (2017), “Stretching “smart”: advancing health and well-being through the smart city agenda”, Local Environment, Vol. 24, No. 7, pp. 610-627.
Van Compernolle, M., Buyle, R., Mannens, E., Vanlishout, Z., Vlassenroot, E., Mechant, P. (2018), ““Technology readiness and acceptance model” as a predictor for the use intention of data standards in smart cities”, Media and Communication, Vol. 6, No. 4, pp. 127-139.
Venkatesh, V., Morris, M. G., Davis, G. B., Davis, F. D. (2003), “User acceptance of information technology: toward a unifies view”, MIS Quarterly, Vol. 27, No. 3, pp. 425-478.
Verdegem, P., Verleye, G. (2009), “User-centered e-government in practice: a comprehensive model for measuring user satisfaction”, Government Information Quarterly, Vol. 26, No. 3, pp. 487-497.
Weerakkody, V., Kapoor, K., Balta, M. E., Irani, Z., Dwivedi, Y. K. (2017), “Factors influencing user acceptance of public sector big open data”, Production Planning & Control, Vol. 28, No. 11-12, pp. 891-905.
Zuiderwijk, A., Janssen, M., Dwivedi, Y. K. (2016), “Acceptance and use predictors of open data technologies: drawing upon the unified theory of acceptance and use of technology”, Vol. 32, No. 4, pp. 429-440.