Factors Determining Usage-Based Insurance Acceptance - Poland and Spain Results

• Autorzy: Maria Forlicz , Tomasz Rólczyński
• Języki publikacji: EN

Abstrakty

EN

Usage-based insurance (UBI) is based on the idea that customers who are safer drivers should pay less for a policy than those who are less prudent. It is widely assumed that there is an incentive for insurers to use this technology, as it could make riskier drivers more likely to use non-telematics-based insurers. However, this hypothesis has not been verified empirically. In order to fill this research gap, a study (between December 2021 and March 2022) assessing the relationship between driving style and willingness to purchase a UBI-based policy and the relationship between risk propensity and willingness to purchase a UBI-based policy was conducted. The study, in the form of a questionnaire, was conducted in Poland and Spain. The samples consisted of 181 respondents in Poland and 51 in Spain. It was found that individual driving style was correlated with willingness to accept a UBI-based policy that included discounts and surcharges. It was also shown that propensity to risk influences willingness to purchase a UBI-based policy that offers discounts only to some extent. The study used suitable statistical measures and tests such as a chi-square test, U Mann-Whitney U test and a Kruskal-Wallis test. Results are significant for insurance companies that are going to introduce UBI. They allow shaping the product so that potential customers are interested in buying it, which, as research shows, may bring benefits to both insured and insurance companies. (original abstract)

Słowa kluczowe

EN

Insurances; Motor insurance; Telematics; Risk perception

PL

Ubezpieczenia; Ubezpieczenia komunikacyjne OC; Telematyka; Postrzeganie ryzyka

• Czasopismo: Journal of International Studies
• Rocznik: 2022
• Tom: 15
• Numer: nr 3
• Strony: 111--129

Twórcy

autor

Maria Forlicz

• Wrocław University of Economics, Poland

autor

Tomasz Rólczyński

• WSB University in Wroclaw, Poland

Bibliografia

• Abdel-Aty M.A., Radwan A.E.. (2000). Modeling traffic accident occurrence and involvement, Accident Analysis and Prevention, 32 (5), 633-642.
• Akerlof G.A. (1970). The Market for 'Lemons': Quality Uncertainty and the Market Mechanism. The Quarterly Journal of Economics, 84(3), 488-500.
• Anderloni, L., & Vandone, D. (2011). Risk of over-indebtedness and behavioural factors. In: Lucarelli C, Brighetti G (eds) Risk tolerance in financial decision making. Palgrave Macmillan Press, London, 113-132.
• Arvidsson, S. (2011). Reducing asymmetric information with usage-based automobile insurance. Swedish National Road; Transport Research Institute (VTI)
• Azadeh A., Zarrin M., Hamid M. (2016). A novel framework for improvement of road accidents considering decision-making styles of drivers in a large metropolitan area, Accident Analysis & Prevention, 87, 17-33.
• Battalio R. C., Kagel J. H., MacDonald D. N. (1985). Animals' choices over uncertain outcomes: Some initial experimental results, The American Economic Review, 75(4), 597-613.
• Becker J.G., Erny M., (2021). Attitudes towards personalized insurance tariff models: a survey among students, SML Working Paper; 17, doi: 10.21256/zhaw-21745, source: https://digitalcollection.zhaw.ch/handle/11475/21745, accessed January 16th 2022
• Belas, J., Koraus, M., & Gabcova, L. (2015). Electronic Banking, Its Use And Safety. Are There Differences In The Access Of Bank Customers By Gender, Education And Age? International Journal of Entrepreneurial Knowledge, 3(2), 16-28.
• Bernat T., Hawran K. Kowalik J. (2016). Asymetria informacji w modelu pryncypał-agent - wyniki badań eksperymentalnych. Przedsiębiorstwo i Region, 8, 65-75
• Blais, A.R., & Weber, E.U. (2006). A Domain-Specific Risk-Taking (DOSPERT) scale for adult populations. Judgment and Decision Making, 1, 33-47.
• Bolderdijk, J. W., Knockaert, J., Steg, E. M., & Verhoef, E. T. (2011). Effects of Pay-As-You-Drive vehicle insurance on young drivers' speed choice: Results of a Dutch field experiment. Accident Analysis & Prevention, 43(3), 1181-1186.
• Byrnes J. P., Miller D. C., Schafer W. D. (1999). Gender differences in risk taking: a meta-analysis. Psychological Bulletin 125(3), 367-383.
• Cather D.A. (2018). Cream Skimming: Innovations in Insurance Risk Classification and Adverse Selection. Risk Management and Insurance Review, 1(2), 335-366.
• Che, X., Liebenberg, A., & Xu, J. (2021). Usage-Based Insurance-Impact on Insurers and Potential Implications for InsurTech. North American Actuarial Journal, 1-28.
• Chiappori P.A., Salanie B. (2000). Testing for Asymmetric Information in Insurance Markets. Journal of Political Economy, 108(1), 56-78.
• Biener Ch., Eling M., Lehmann M. (2020). Balancing the desire for privacy against the desire to hedge risk, Journal of Economic Behavior & Organization, 180, 608-620.
• Dang J. (2022). The impact of telematics on the motor insurance landscape and on customer behaviour in the case of Italy, Bachelor Thesis, University of Zurich, source: https://www.business.uzh.ch/dam/jcr:6f2f17b3-dead-4be2-9965-038e8b3e3255/Dang_thesis.pdf, accessed January 17th 2022
• Dankiewicz R., Ostrowska-Dankiewicz A., & Bulut C. (2020). The attitudes of entrepreneurs of the small and medium-sized enterprises sector in Poland to key business risks. Equilibrium. Quarterly Journal of Economics and Economic Policy, 15(3), 511-536.
• Dankiewicz R. (2020). Single cover as a supplement to the product offer of trade credit insurers used in risk management processes in enterprises, International Journal Business Performance Management, 21(4), 400-416.
• Derikx, S., de Reuver, M., & Kroesen, M. (2016). Can privacy concerns for insurance of connected cars be compensated? Electronic Markets,26(1), 73-81.
• Dickerson A., Peirson J., Vickerman R.. (2000). Road accidents and traffic flows: an econometric investigation, Economica, 67(265), 101-121.
• Dionne, G., C. Gourieroux, and C. Vanasse, (2001). Testing for Evidence of Adverse Selection in the Automobile Insurance Market: A Comment, Journal of Political Economy, 109, 444-453.
• Ernst&Young. (2015). Usage Based Insurance. The New Normal?
• Fan C.K., Wu X., Zheng D, Lin W. (2016). A Market Analysis of Telematics-Based UBI in Taiwan, Journal of Applied Finance & Banking, 6(6), 71-89.
• Golob T.F., Recker W.W. (2003). Relationships among urban freeway accidents, traffic flow, weather, and lighting conditions, Journal of Transportation Engineering, 129 (4), 342-353.
• Guillen, M., Nielsen, J. P., Pérez-Marín, A. M., & Elpidorou, V. (2020). Can automobile insurance telematics predict the risk of near-miss events?. North American Actuarial Journal, 24(1), 141-152.
• Horvath, J., Gavurova, B., Bacik, R. & Fedorko, R. (2021). Identification of Uncertainty Factors in the Consumer Behaviour of the New Generation of Customers at the E-commerce Level. Journal of Tourism and Services, 22(12), 168-183.
• Jaspersen, J., Ragin, M., and J. Sydnor. (2022). Predicting insurance demand from risk attitudes. The journal of risk & insurance, 89(1), 63-96.
• Karapiperis D., Birnbaum B., Brandenburg A., Castagna S., Greenberg A., Harbage R. and A. Obersteadt (2015). Usage-Based Insurance and Vehicle Telematics: Insurance Market and Regulatory Implications, CIPR Study, source: https://content.naic.org/sites/default/files/inline-files/cipr_study_150324_usage_based_insurance_and_vehicle_telematics_study_series_1.pdf, accessed: January 15th 2022
• Kruger, J., & Dunning, D. (1999). Unskilled and unaware of it: How difficulties in recognizing one's own incompetence lead to inflated self-assessments. Journal of Personality and Social Psychology, 77(6), 1121-1134. https://doi.org/10.1037/0022-3514.77.6.1121
• Kwarteng, M. A., Pilik, M. (2016). Exploring consumers' propensity for online shopping in a developing country: A demographic perspective. International Journal of Entrepreneurial Knowledge, 4(1), 90-103.
• Lord D., Manar A., Vizioli A. (2005). Modeling crash-flow-density and crash-flow-V/C ratio relationships for rural and urban freeway segments, Accident Analysis and Prevention, 37 (1), 185-199.
• Mather, M., Mazar, N., Gorlick, M. A., Lighthall, N. R., Burgeno, J., Schoeke, A., & Ariely, D. (2012). Risk preferences and aging: The "certainty effect" in older adults' decision making. Psychology and Aging, 27(4), 801-816.
• McCormick, I. A., Walkey, F. H., & Green, D. E. (1986). Comparative perceptions of driver ability-a confirmation and expansion. Accident Analysis & Prevention, 18(3), 205-208.
• Nemanja M., š Milosavljević M., Benković S., Starčević D., and o Spasenić Ž. (2020). An Acceptance Approach for Novel Technologies in Car Insurance, Sustainability 12 (24), 10331. https://doi.org/10.3390/su12241033
• Paefgen, J., Staake, T., & Fleisch, E. (2014). Multivariate exposure modeling of accident risk: Insights from Pay-as-you-drive insurance data. Transportation Research Part A: Policy and Practice, 61, 27-40.
• Pugnetti C., Seitz M. (2021). Data-Driven Services in Insurance: Potential Evolution and Impact in the Swiss Market, Journal of Risk and Financial Management, MDPI, 14(5), 1-16.
• Quintero J. & Benenson Z. (2019). Understanding Usability and User Acceptance of Usage-Based Insurance from Users' View. In Proceedings of the 2019 2nd International Conference on Machine Learning and Machine Intelligence (MLMI 2019). Association for Computing Machinery, New York, NY, USA, 52-57. DOI:https://doi.org/10.1145/3366750.3366759
• Reimers I., Shiller B. (2018). Welfare Implications of Proprietary Data Collection: An Application to Telematics in Auto Insurance, Working Papers 119R, Brandeis University, Department of Economics and International Business School, source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3125049, accessed: January 15th 2022
• Rejikumar G. (2013). A pre-launch exploration of customer acceptance of usage based vehicle insurance policy, IIMB Management Review, 25(1), 19-27.
• Ronay, R., Kim, D. Y. (2006). Gender differences in explicit and implicit risk attitudes: A socially facilitated phenomenon. British Journal of Social Psychology, 45(2), 397-419.
• Rothschild, M., and Stiglitz, J. (1976). Equilibrium in Competitive Insurance Markets: An Essay on the Economics of Imperfect Information. Quarterly Journal of Economics, 90(4), 629-649.
• Sahebi, S., & Nassiri, H. (2017). Assessing public acceptance of connected vehicle systems in a new scheme of usage-based insurance. Transportation Research Record: Journal of the Transportation Research Board, 2625 ,62-69.
• Seger, F.; Figl, K. (2019): Influence Factors for Customer Acceptance of Data-Driven Contracts in Insurance Ecosystems. In: Proceedings ICIS 2019 Pre-Conference
• Siegelman P. (2004). Adverse Selection in Insurance Markets: An Exaggerated Threat, Yale Law Journal, 113(6), 1123-1281.
• Skłodowski, H. (2007). Psychologia kierowcy samochodowego. Toruń: Wydawnictwo Adam Marszałek.
• Śliwiński, A., & Kuryłowicz, Ł. (2021). Usage-based insurance and its acceptance: An empirical approach. Risk Management and Insurance Review, 24(1), 71-91, https://doi.org/10.1111/rmir.12165
• Soleymanian M., Weinberg C., Zhu T. (2021). Privacy Concerns, Economic Benefits, and Consumer Decisions: A Multi-Period Panel Study of Consumer Choices in the Automobile Insurance Industry (August 13, 2021). Available at SSRN: https://ssrn.com/abstract=3905034 or http://dx.doi.org/10.2139/ssrn.3905034, accessed January 17th 2022
• Studenski, R. (2004). Ryzyko i ryzykowanie. Katowice: Wydawnictwo Uniwersytetu Śląskiego.
• Svenson, O. (1981). Are we all less risky and more skillful than our fellow drivers?. Acta psychologica, 47(2), 143-148.
• Trimpop, R., & Kirkcaldy, B. (1997). Personality predictors of driving accidents. Personality and Individual Differences, 23(1), 147-152.
• Tselentis D., Theofilatos A., Yannis G., Konstantinopoulos M. (2018). Public opinion on Usage-Based Motor Insurance Schemes: a stated preference approach. Travel Behaviour and Society, 11, 111-118.
• Tyszka T., Domurat A., (2004). Czy istnieje ogólna skłonność jednostki do ryzyka?, Decyzje 2, 85-104.
• Wilson, M., & Daly, M. (1985). Competitiveness, risk taking, and violence: The young male syndrome. Ethology and sociobiology, 6(1), 59-73.
• Zhou L., Du S., Zhu H., Chen C., Ota K., Dong M. (2019). Location Privacy in Usage-Based Automotive Insurance: Attacks and Countermeasures, in IEEE Transactions on Information Forensics and Security, 14(1), 196-211.

Identyfikatory

DOI

10.14254/2071-8330.2022/15-3/8