Tamás Dusek
 
 
Széchenyi István University, Győr, Egyetem tér 1, Hungary
DOI: https://doi.org/10.31410/ITEMA.2018.53

2nd International Scientific Conference on Recent Advances in Information Technology, Tourism, Economics, Management and Agriculture – ITEMA 2018 – Graz, Austria, November 8, 2018, CONFERENCE PROCEEDINGS published by the Association of Economists and Managers of the Balkans, Belgrade, Serbia; ISBN 978-86-80194-13-4

Abstract

Smart city initiatives, plans, missions have “mushroomed” in every continent in recent years. These projects want to apply the information technology for improving the efficiency and quality of local services and for providing new services for the inhabitants, visitors and the entrepreneurs of the settlements, or more safety, leisure and less pollution. Areas of applications are manifold, such as transportation (vehicle routing, road pricing, parking systems, traffic patterns, congestion reducement, smart traffic lights and so on), mobile workforce enablement (city surveyors, park maintenance, inspectors, health and social services), energy (street lighting, building control, demand for electricity, energy theft detection), utilities (smart meters, field service, customer service, maintenance optimization and so on), healthcare (reducement of waiting times, forecast of visit and admission rates, real-time alerting, telemedicine and so on), education, security and others.

These projects have mainly positive impact from technological point of view (for example, more information, quality improvement, more safety is engendered). However, in the evaluation of the projects, the cost benefit analysis, the comparison of implementation and maintenance costs and the realization of benefits is either missing or use doubtful, questionable nonmonetary categories for benefits. Moreover, it typically neglects the displacement effect and opportunity costs, therefore systematically biased toward greater positive impacts. The dominant rhetoric and propaganda is strongly influenced by the big information technology companies, which set its sights on local governments as a huge, untapped market.

The paper deals with the problem of creating composite index numbers for the evaluation of Smart city projects and for the comparison of “smartness” of cities. These composite indicators are popular tools of technocrats and bureaucrats, but the transformation of a multi-indicator system into a one-dimensional metric scale, in spite of the often use of a sophisticated mathematical technique, is a highly questionable practice.

Key words
Smart city, indicator analyses, multicriteria analyses, decision support tools, information technology.
References
[1] Nam, T., Pardo, T. A. (2011) Conceptualizing Smart City with Dimensions of Technology, People, and Institutions. Proc. 12th Conference on Digital Government Research, College Park, MD, June 12-15, 2011
[2] Allwinkle, S., Cruickshank, P. (2011) Creating smarter cities: an overview. Journal of Urban Technology, 18, 2, pp. 1-16
[3] Albino, V., Berardi, U., Dangelico, R. M. (2015) Smart Cities: Definitions, Dimensions, Performance, and Initiatives. Journal of Urban Technology, 22, 1, pp. 3–21.
[4] Mora, L., Bolici, R., Deakin, M. (2017) The first two decades of smart-city research: a bibliometric analysis. Journal of Urban Technology, 24, 1, pp. 2-27.
[5] Caragliu, A., De Bo, C., Nijkamp, P. (2011) Smart cities in Europe. Journal of Urban Technology, 18, 2, pp. 65-82.
[6] Dameri, R. P. (2013) Searching for Smart City definition: a comprehensive proposal. International Journal of Computers & Technology, 11, 5. pp. 2544-2551.
[7] Klauser, F., Paasche, T., Söderström, O. (2014) Michel Foucault and the smart city: power dynamics inherent in contemporary governing through code. Environment and Planning D: Society and Space, 32, pp. 869-885.
[8] Su, K., Li, J., Fu, H. (2011) Smart City and the applications. IEEE International Conference on Electronics, Communications and Control (ICECC), pp. 1028-1031.
[9] Hall, P. (2000) Creative cities and economic development. Urban Studies, 37, 4, pp. 633-649.
[10] Cretu, G. L. (2012) Smart Cities Design Using Event-driven Paradigm and Semantic Web. Informatica Economica, 16, 4, pp. 57–67
[11] Giffinger, R. (2007) Smart Cities: Ranking of European medium-sized cities. Centre of Regional Science, Vienna
[12] Haarstad, H. (2017) Constructing the sustainable city: examining the role of sustainability in the smart city discourse. Journal of Environmental Policy & Planing, 19, 4, pp. 423-437.
[13] Greenfield, A. (2013) Against the Smart City. New York: Do Projects.
[14] Krivy, M. (2018) Towards a critique of cybernetic urbanism: The smart city and the society of control. Planning Theory, 17, 1, pp. 8-30
[15] Zygiaris, S. (2013) Smart City Reference Model: Assisting Planners to Conceptualize the Building of Smart City Innovation Ecosystems. Journal of the Knowledge Economy, 4, 2, pp. 217–231.
[16] Lazaroiu, G. C., Roscia, M. (2012) Definition Methodology for the Smart Cities Model. Energy, 47, 1. pp. 326–332.
[17] Lombardi, P., Giordano, S., Farouh, H., Yousef, W. (2012) Modeling the Smart City Performance. Innovation: The European Journal of Social Science Research, 25, 2, pp. 137–149.
[18] Carli, R., Dotoli, M., Pellegrino, R., Ranieri, L. (2013) Measuring and Managing the Smartness of Cities: A Framework for Classifying Performance Indicators. Proceedings of IEEE Systems, Man, and Cybernetics, 2013.

dusek_the_problems_of_composite_index_numbers_of_smart_pp_53-58

Association of Economists and Managers of the Balkans – UdEkoM Balkan
179 Ustanicka St, 11000 Belgrade, Republic of Serbia