IDEAS home Printed from https://ideas.repec.org/a/taf/applec/v50y2018i5p545-558.html
   My bibliography  Save this article

Modelling preference heterogeneity for theatre tickets: a discrete choice modelling approach on Royal Danish Theatre booking data

Author

Listed:
  • Andrea Baldin
  • Trine Bille

Abstract

This article analyses the behavioural choice for theatre tickets using a rich data set for 2010–2013 from the sale system of the Royal Danish National Theatre. A consumer who decides to attend a theatre production faces multiple sources of price variation that involves a choice by the consumer among different ticket alternatives. Three modelling approaches are proposed in order to model ticket purchases: conditional logit with socio-demographic characteristics, nested logit and latent class. These models allow us explicitly to take into account consumers’ preference heterogeneity with respect to the attributes associated with each ticket alternative (quality of the seat and day of the performance). In addition, the willingness to pay of choice attributes is estimated. Final results suggest that customers’ characteristics in terms of age and frequency of theatre attendance characterize different patterns of behaviour in the choice of theatre ticket.

Suggested Citation

  • Andrea Baldin & Trine Bille, 2018. "Modelling preference heterogeneity for theatre tickets: a discrete choice modelling approach on Royal Danish Theatre booking data," Applied Economics, Taylor & Francis Journals, vol. 50(5), pages 545-558, January.
    • Handle: RePEc:taf:applec:v:50:y:2018:i:5:p:545-558
    DOI: 10.1080/00036846.2017.1335386
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00036846.2017.1335386
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00036846.2017.1335386?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kristien Werck & Bruno Heyndels, 2007. "Programmatic choices and the demand for theatre: the case of Flemish theatres," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 31(1), pages 25-41, March.
    2. Jose Grisolia & K. G. Willis, 2011. "An evening at the theatre: using choice experiments to model preferences for theatres and theatrical productions," Applied Economics, Taylor & Francis Journals, vol. 43(27), pages 3987-3998.
    3. Hausman, Jerry & McFadden, Daniel, 1984. "Specification Tests for the Multinomial Logit Model," Econometrica, Econometric Society, vol. 52(5), pages 1219-1240, September.
    4. Marta Zieba, 2009. "Full-income and price elasticities of demand for German public theatre," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 33(2), pages 85-108, May.
    5. Lopez Sintas, Jordi & Garcia Alvarez, Ercilia, 2005. "Four characters on the stage playing three games: performing arts consumption in Spain," Journal of Business Research, Elsevier, vol. 58(10), pages 1446-1455, October.
    6. Hetrakul, Pratt & Cirillo, Cinzia, 2013. "Accommodating taste heterogeneity in railway passenger choice models based on internet booking data," Journal of choice modelling, Elsevier, vol. 6(C), pages 1-16.
    7. Fernandez-Blanco, Victor & Orea, Luis & Prieto-Rodriguez, Juan, 2009. "Analyzing consumers heterogeneity and self-reported tastes: An approach consistent with the consumer's decision making process," Journal of Economic Psychology, Elsevier, vol. 30(4), pages 622-633, August.
    8. Bliemer, Michiel C.J. & Rose, John M., 2013. "Confidence intervals of willingness-to-pay for random coefficient logit models," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 199-214.
    9. Matthew J. Drake & Serhan Duran & Paul M. Griffin & Julie L. Swann, 2008. "Optimal timing of switches between product sales for sports and entertainment tickets," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(1), pages 59-75, February.
    10. José Grisolía & Kenneth Willis, 2012. "A latent class model of theatre demand," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 36(2), pages 113-139, May.
    11. K. Willis & J. Snowball, 2009. "Investigating how the attributes of live theatre productions influence consumption choices using conjoint analysis: the example of the National Arts Festival, South Africa," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 33(3), pages 167-183, August.
    12. Seaman, Bruce A, 2006. "Empirical Studies of Demand for the Performing Arts," Handbook of the Economics of Art and Culture, in: V.A. Ginsburgh & D. Throsby (ed.), Handbook of the Economics of Art and Culture, edition 1, volume 1, chapter 14, pages 415-472, Elsevier.
    13. Jani-Petri Laamanen, 2013. "Estimating demand for opera using sales system data: the case of Finnish National Opera," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 37(4), pages 417-432, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Danny Blom & Rudi Pendavingh & Frits Spieksma, 2022. "Filling a Theater During the COVID-19 Pandemic," Interfaces, INFORMS, vol. 52(6), pages 473-484, November.
    2. Aleksandra Wiśniewska & Ewa Zawojska & Andrea Baldin & Joanna Rachubik, 2023. "Reliability of international benefit transfer in cultural economics: Non-market valuation of theater in Denmark and Poland," Working Papers 2023-19, Faculty of Economic Sciences, University of Warsaw.
    3. Aleksandra Wiśniewska & Wiktor Budziński & Mikołaj Czajkowski, 2018. "Publicly funded cultural institutions – a comparative economic valuation study," Working Papers 2018-22, Faculty of Economic Sciences, University of Warsaw.
    4. McKenzie, Jordi & Crosby, Paul & Cox, Joe & Collins, Alan, 2019. "Experimental evidence on demand for “on-demand” entertainment," Journal of Economic Behavior & Organization, Elsevier, vol. 161(C), pages 98-113.
    5. Andrea Baldin & Trine Bille & Andrea Ellero & Daniela Favaretto, 2018. "Revenue and attendance simultaneous optimization in performing arts organizations," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 42(4), pages 677-700, November.
    6. Andrea Baldin & Trine Bille & Andrea Ellero & Daniela Favaretto, 2016. "Multiobjective optimization model for pricing and seat allocation problem in non profit performing arts organization," Working Papers 20, Department of Management, Università Ca' Foscari Venezia.

    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. Evgeniy M. Ozhegov & Alina Ozhegova, 2018. "Segmentation of Theatre Audiences: A Latent Class Approach for Combined Data," HSE Working papers WP BRP 198/EC/2018, National Research University Higher School of Economics.
    2. José Grisolía & Kenneth Willis, 2012. "A latent class model of theatre demand," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 36(2), pages 113-139, May.
    3. Alina R. Buzanakova & Evgeniy M. Ozhegov, 2016. "Demand for Performing Arts: The Effect of Unobserved Quality on Price Elasticity," HSE Working papers WP BRP 156/EC/2016, National Research University Higher School of Economics.
    4. Wiśniewska Aleksandra, 2019. "Quality attributes in the non-market stated-preference based valuation of cultural goods," Central European Economic Journal, Sciendo, vol. 6(53), pages 132-150, January.
    5. Ozhegova, Alina & Ozhegov, Evgeniy M., 2020. "Segmentation of theatre audiences: A latent class approach for combined data," Journal of choice modelling, Elsevier, vol. 37(C).
    6. Marta Zieba, 2017. "Cultural participation of tourists – Evidence from travel habits of Austrian residents," Tourism Economics, , vol. 23(2), pages 295-315, March.
    7. Junlong Wu & Keshen Jiang & Chaoqing Yuan, 2019. "Determinants of demand for traditional Chinese opera," Empirical Economics, Springer, vol. 57(6), pages 2129-2148, December.
    8. José M. Grisolía & Kenneth G. Willis, 2016. "Consumer choice of theatrical productions: a combined revealed preference–stated preference approach," Empirical Economics, Springer, vol. 50(3), pages 933-957, May.
    9. Ozhegova, A. & Ozhegov, E., 2018. "Estimation of Demand Function for Performing Arts: Empirical Analysis," Journal of the New Economic Association, New Economic Association, vol. 37(1), pages 87-110.
    10. Concetta Castiglione, 2019. "Revealed individual attendance at Italian theatre: a microeconomic investigation," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 36(3), pages 731-759, October.
    11. Jani-Petri Laamanen, 2013. "Estimating demand for opera using sales system data: the case of Finnish National Opera," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 37(4), pages 417-432, November.
    12. Aleksandra Wiśniewska, 2019. "‘Quality food’ for cultural policies. Quality attributes in the non-market stated-preference based valuation of cultural goods," Working Papers 2019-03, Faculty of Economic Sciences, University of Warsaw.
    13. Eric Kolhede & J. Tomas Gomez-Arias & Anna Maximova, 2023. "Price elasticity in the performing arts: a segmentation approach," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(3), pages 523-550, September.
    14. Pablo De la Vega & Sara Suarez-Fernández & David Boto-García & Juan Prieto-Rodríguez, 2020. "Playing a play: online and live performing arts consumers profiles and the role of supply constraints," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 44(3), pages 425-450, September.
    15. Alina Ozhegova & Evgeniy M. Ozhegov, 2018. "Heterogeneity in demand for performances and seats in the theatre," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 17(3), pages 131-145, June.
    16. Víctor Fernández-Blanco & Ana Rodríguez-Álvarez & Aleksandra Wiśniewska, 2019. "Measuring technical efficiency and marginal costs in the performing arts: the case of the municipal theatres of Warsaw," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 43(1), pages 97-119, March.
    17. Aleksandra Wiśniewska & Wiktor Budziński & Mikołaj Czajkowski, 2018. "Publicly funded cultural institutions – a comparative economic valuation study," Working Papers 2018-22, Faculty of Economic Sciences, University of Warsaw.
    18. Aleksandra Wiśniewska & Mikołaj Czajkowski, 2015. "Utilizing the Discrete Choice Experiment Approach for Designing a Socially Efficient Cultural Policy: The case of municipal theaters in Warsaw," Working Papers 2015-36, Faculty of Economic Sciences, University of Warsaw.
    19. Paul Crosby, 2019. "Don’t judge a book by its cover: examining digital disruption in the book industry using a stated preference approach," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 43(4), pages 607-637, December.
    20. David Throsby & Anita Zednik & Jorge E. Araña, 2021. "Public preferences for heritage conservation strategies: a choice modelling approach," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 45(3), pages 333-358, September.

    More about this item

    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:taf:applec:v:50:y:2018:i:5:p:545-558. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEC20 .

    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.