IDEAS home Printed from https://ideas.repec.org/p/iim/iimawp/14618.html
   My bibliography  Save this paper

Development of Utility Function for Vehicle Insurance: Comparison of Logarithmic Goal Programming Method and Conjoint Analysis Method

Author

Listed:
  • Natesan, Sumeetha R.
  • Dutta, Goutam

Abstract

The increase in competition among the vehicle insurance sectors has increased the number of policy options available in the market. This study focuses on the development of a utility function for these policies that will aid policy holders and potential investors in comparing them based on various attributes. A comparison of various vehicle insurance policies can help the customers to compare and choose a vehicle insurance that is suitable to them. Although there are several methods for developing a utility function, in this study, we intend to develop a linear utility model for vehicle insurance policies using two approaches: Logarithmic Goal Programming Model (LGPM) and Conjoint Analysis Method (CAM). We propose to compare the similarities and differences between the results obtained from LGPM and CAM approaches, used for developing the utility function for vehicle insurance policies. We also derive a choice probability of the vehicles insurance policies available in market by developing a multinomial logit choice model. We also study the consistency indicators of the respondents. We will provide useful insights for the use both approaches as research tools.

Suggested Citation

  • Natesan, Sumeetha R. & Dutta, Goutam, 2020. "Development of Utility Function for Vehicle Insurance: Comparison of Logarithmic Goal Programming Method and Conjoint Analysis Method," IIMA Working Papers WP 2020-02-01, Indian Institute of Management Ahmedabad, Research and Publication Department.
  • Handle: RePEc:iim:iimawp:14618
    as

    Download full text from publisher

    File URL: https://www.iima.ac.in/sites/default/files/rnpfiles/15372270372020-02-01.pdf
    File Function: English Version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ming-Jyh Wang & Chieh-Hua Wen & Lawrence W Lan, 2010. "Modelling Different Types of Bundled Automobile Insurance Choice Behaviour: The Case of Taiwan*," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 35(2), pages 290-308, April.
    2. Vithala R. Rao, 2008. "Developments in Conjoint Analysis," International Series in Operations Research & Management Science, in: Berend Wierenga (ed.), Handbook of Marketing Decision Models, chapter 0, pages 23-53, Springer.
    3. Stewart, TJ, 1992. "A critical survey on the status of multiple criteria decision making theory and practice," Omega, Elsevier, vol. 20(5-6), pages 569-586.
    4. Vithala R. Rao, 2014. "Applied Conjoint Analysis," Springer Books, Springer, edition 127, number 978-3-540-87753-0, September.
    5. Maarten Ijzerman & Janine Til & John Bridges, 2012. "A Comparison of Analytic Hierarchy Process and Conjoint Analysis Methods in Assessing Treatment Alternatives for Stroke Rehabilitation," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 5(1), pages 45-56, March.
    6. Goutam Dutta & Priyanko Ghosh & Arushi Wanchoo Kaul, 2015. "A logarithmic goal programming approach to develop the utility function for a railway travel," International Journal of Revenue Management, Inderscience Enterprises Ltd, vol. 8(2), pages 153-164.
    7. G Dutta & S Basu & J John, 2010. "Development of utility function for life insurance buyers in the Indian market," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(4), pages 585-593, April.
    8. Sumeetha Natesan & Chhaya Singh & Goutam Dutta, 2019. "Utility function for airline travel in Nepal and its comparison with India," International Journal of Revenue Management, Inderscience Enterprises Ltd, vol. 11(1/2), pages 23-45.
    9. Goutam Dutta & Priyanko Ghosh, 2011. "Development of a utility function for airline travel: a logarithmic goal programming approach," International Journal of Revenue Management, Inderscience Enterprises Ltd, vol. 5(4), pages 277-289.
    10. Green, Paul E & Srinivasan, V, 1978. "Conjoint Analysis in Consumer Research: Issues and Outlook," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 5(2), pages 103-123, Se.
    11. Scholl, Armin & Manthey, Laura & Helm, Roland & Steiner, Michael, 2005. "Solving multiattribute design problems with analytic hierarchy process and conjoint analysis: An empirical comparison," European Journal of Operational Research, Elsevier, vol. 164(3), pages 760-777, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sumeetha R. Natesan & Goutam Dutta, 2022. "A comparison of logarithmic goal programming and conjoint analysis to generate priority point vectors: an experimental approach," OPSEARCH, Springer;Operational Research Society of India, vol. 59(2), pages 518-549, June.
    2. James Agarwal & Wayne DeSarbo & Naresh K. Malhotra & Vithala Rao, 2015. "An Interdisciplinary Review of Research in Conjoint Analysis: Recent Developments and Directions for Future Research," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 2(1), pages 19-40, March.
    3. Christian P Theurer & Andranik Tumasjan & Isabell M Welpe, 2018. "Contextual work design and employee innovative work behavior: When does autonomy matter?," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-35, October.
    4. Hein, Maren & Goeken, Nils & Kurz, Peter & Steiner, Winfried J., 2022. "Using Hierarchical Bayes draws for improving shares of choice predictions in conjoint simulations: A study based on conjoint choice data," European Journal of Operational Research, Elsevier, vol. 297(2), pages 630-651.
    5. Eunae Son & Song Soo Lim, 2021. "Consumer Acceptance of Gene-Edited versus Genetically Modified Foods in Korea," IJERPH, MDPI, vol. 18(7), pages 1-17, April.
    6. Jinsung Kim & Minseok Kim & Sehyeuk Im & Donghyun Choi, 2021. "Competitiveness of E Commerce Firms through ESG Logistics," Sustainability, MDPI, vol. 13(20), pages 1-15, October.
    7. Andrew R. Kamwendo & Mandusha Maharaj, 2022. "The Preferences of Consumers When Selecting Clothing Detergent Products," International Review of Management and Marketing, Econjournals, vol. 12(6), pages 23-36, November.
    8. Bragge, Johanna, 2001. "Premediation analysis of the energy taxation dispute in Finland," European Journal of Operational Research, Elsevier, vol. 132(1), pages 1-16, July.
    9. Lieven, Theo, 2015. "Policy measures to promote electric mobility – A global perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 78-93.
    10. Gabriela D. Oliveira & Luis C. Dias, 2020. "The potential learning effect of a MCDA approach on consumer preferences for alternative fuel vehicles," Annals of Operations Research, Springer, vol. 293(2), pages 767-787, October.
    11. Hajibaba, Homa & Boztuğ, Yasemin & Dolnicar, Sara, 2016. "Preventing tourists from canceling in times of crises," Annals of Tourism Research, Elsevier, vol. 60(C), pages 48-62.
    12. Jong Seok Kim, 2017. "Empirical Analysis Of Consumer Willingness To Pay For Smart Phone Attributes In Multi-Countries," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 21(02), pages 1-37, February.
    13. Kwarteng Michael Adu & Pilík Michal & Juřičková Eva, 2018. "Beyond cost saving. Other factor consideration in online purchases of used electronic goods: a conjoint analysis approach," Management & Marketing, Sciendo, vol. 13(3), pages 1051-1063, September.
    14. Winfried Steiner & Harald Hruschka, 2002. "A Probabilistic One-Step Approach to the Optimal Product Line Design Problem Using Conjoint and Cost Data," Review of Marketing Science Working Papers 1-4-1003, Berkeley Electronic Press.
    15. Bodo Herzog, 2018. "Valuation of Digital Platforms: Experimental Evidence for Google and Facebook," IJFS, MDPI, vol. 6(4), pages 1-13, October.
    16. Merja Halme & Kari Linden & Kimmo Kääriä, 2009. "Patients’ Preferences for Generic and Branded Over-the-Counter Medicines," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 2(4), pages 243-255, December.
    17. Tofallis, C., 1996. "Improving discernment in DEA using profiling," Omega, Elsevier, vol. 24(3), pages 361-364, June.
    18. Dufhues, T. & Buchenrieder, G., 2004. "Der Beitrag der Conjoint Analyse zur nachfrageorintierten Entwicklung des ländlichen Finanzsektors in Vietnam," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 39.
    19. Martinovici, A., 2019. "Revealing attention - how eye movements predict brand choice and moment of choice," Other publications TiSEM 7dca38a5-9f78-4aee-bd81-c, Tilburg University, School of Economics and Management.
    20. Mahesh Balan U & Saji K. Mathew, 2021. "Personalize, Summarize or Let them Read? A Study on Online Word of Mouth Strategies and Consumer Decision Process," Information Systems Frontiers, Springer, vol. 23(3), pages 627-647, June.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:iim:iimawp:14618. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/eciimin.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.