IDEAS home Printed from https://ideas.repec.org/a/eee/eejocm/v44y2022ics1755534522000276.html
   My bibliography  Save this article

Testing for saliency-led choice behavior in discrete choice modeling: An application in the context of preferences towards nuclear energy in Italy

Author

Listed:
  • Contu, Davide
  • Strazzera, Elisabetta

Abstract

This work proposes a discrete choice model that jointly accounts for heterogeneity in preferences and in decision making procedures adopted by respondents, as well as for non-linearities in the utility function, allowing for the potential effect of salient attributes in choice experiments. We present an innovative application in the context of preferences towards nuclear energy, with data obtained from a nationwide online survey conducted in Italy. Results show that most of the variation in the choice data is indeed due to heterogeneity in the decision process, where the saliency heuristic plays an important role. Furthermore, the proposed model provides more conservative monetary valuations as opposed to standard models, potentially leading to substantial differences in cost-benefit analysis. Implications for choice modeling practitioners are discussed, emphasizing the need to account for saliency effects when modeling the choice data.

Suggested Citation

  • Contu, Davide & Strazzera, Elisabetta, 2022. "Testing for saliency-led choice behavior in discrete choice modeling: An application in the context of preferences towards nuclear energy in Italy," Journal of choice modelling, Elsevier, vol. 44(C).
  • Handle: RePEc:eee:eejocm:v:44:y:2022:i:c:s1755534522000276
    DOI: 10.1016/j.jocm.2022.100370
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1755534522000276
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jocm.2022.100370?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. Sun, Chuanwang & Zhu, Xiting, 2014. "Evaluating the public perceptions of nuclear power in China: Evidence from a contingent valuation survey," Energy Policy, Elsevier, vol. 69(C), pages 397-405.
    2. Sandorf, Erlend Dancke & Campbell, Danny & Hanley, Nick, 2017. "Disentangling the influence of knowledge on attribute non-attendance," Journal of choice modelling, Elsevier, vol. 24(C), pages 36-50.
    3. Liao, Shu-Yi & Tseng, Wei-Chun & Chen, Chi-Chung, 2010. "Eliciting public preference for nuclear energy against the backdrop of global warming," Energy Policy, Elsevier, vol. 38(11), pages 7054-7069, November.
    4. Ferrini, Silvia & Scarpa, Riccardo, 2007. "Designs with a priori information for nonmarket valuation with choice experiments: A Monte Carlo study," Journal of Environmental Economics and Management, Elsevier, vol. 53(3), pages 342-363, May.
    5. Kelvin Balcombe & Michail Bitzios & Iain Fraser & Janet Haddock-Fraser, 2014. "Using Attribute Importance Rankings Within Discrete Choice Experiments: An Application to Valuing Bread Attributes," Journal of Agricultural Economics, Wiley Blackwell, vol. 65(2), pages 446-462, June.
    6. Ellen J Van Loo & Rodolfo M NaygaJr & Danny Campbell & Han-Seok Seo & Wim Verbeke, 2018. "Using eye tracking to account for attribute non-attendance in choice experiments," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 45(3), pages 333-365.
    7. Hess, Stephane & Train, Kenneth, 2017. "Correlation and scale in mixed logit models," Journal of choice modelling, Elsevier, vol. 23(C), pages 1-8.
    8. Nick Hanley & Susana Mourato & Robert E. Wright, 2001. "Choice Modelling Approaches: A Superior Alternative for Environmental Valuatioin?," Journal of Economic Surveys, Wiley Blackwell, vol. 15(3), pages 435-462, July.
    9. Hole, Arne Risa, 2011. "A discrete choice model with endogenous attribute attendance," Economics Letters, Elsevier, vol. 110(3), pages 203-205, March.
    10. Davide Contu & Susana Mourato & Ozgur Kaya, 2020. "Individual preferences towards nuclear energy: the transient residency effect," Applied Economics, Taylor & Francis Journals, vol. 52(30), pages 3219-3237, June.
    11. Byun, Hyunsuk & Lee, Chul-Yong, 2017. "Analyzing Korean consumers’ latent preferences for electricity generation sources with a hierarchical Bayesian logit model in a discrete choice experiment," Energy Policy, Elsevier, vol. 105(C), pages 294-302.
    12. Stephane Hess & David Hensher, 2013. "Making use of respondent reported processing information to understand attribute importance: a latent variable scaling approach," Transportation, Springer, vol. 40(2), pages 397-412, February.
    13. Murakami, Kayo & Ida, Takanori & Tanaka, Makoto & Friedman, Lee, 2015. "Consumers' willingness to pay for renewable and nuclear energy: A comparative analysis between the US and Japan," Energy Economics, Elsevier, vol. 50(C), pages 178-189.
    14. Contu, Davide & Strazzera, Elisabetta & Mourato, Susana, 2016. "Modeling individual preferences for energy sources: The case of IV generation nuclear energy in Italy," Ecological Economics, Elsevier, vol. 127(C), pages 37-58.
    15. Chorus, Caspar G. & Arentze, Theo A. & Timmermans, Harry J.P., 2008. "A Random Regret-Minimization model of travel choice," Transportation Research Part B: Methodological, Elsevier, vol. 42(1), pages 1-18, January.
    16. Michael Siegrist & Heinz Gutscher & Timothy C. Earle, 2005. "Perception of risk: the influence of general trust, and general confidence," Journal of Risk Research, Taylor & Francis Journals, vol. 8(2), pages 145-156, March.
    17. Riccardo Scarpa & Mara Thiene & David A. Hensher, 2010. "Monitoring Choice Task Attribute Attendance in Nonmarket Valuation of Multiple Park Management Services: Does It Matter?," Land Economics, University of Wisconsin Press, vol. 86(4), pages 817-839.
    18. Stephane Hess & Amanda Stathopoulos & Andrew Daly, 2012. "Allowing for heterogeneous decision rules in discrete choice models: an approach and four case studies," Transportation, Springer, vol. 39(3), pages 565-591, May.
    19. Jun, Eunju & Joon Kim, Won & Hoon Jeong, Yong & Heung Chang, Soon, 2010. "Measuring the social value of nuclear energy using contingent valuation methodology," Energy Policy, Elsevier, vol. 38(3), pages 1470-1476, March.
    20. Balbontin, Camila & Hensher, David A. & Collins, Andrew T., 2019. "How to better represent preferences in choice models: The contributions to preference heterogeneity attributable to the presence of process heterogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 218-248.
    21. Swait, Joffre, 2001. "A non-compensatory choice model incorporating attribute cutoffs," Transportation Research Part B: Methodological, Elsevier, vol. 35(10), pages 903-928, November.
    22. Daniel, Aemiro Melkamu & Persson, Lars & Sandorf, Erlend Dancke, 2018. "Accounting for elimination-by-aspects strategies and demand management in electricity contract choice," Energy Economics, Elsevier, vol. 73(C), pages 80-90.
    23. Carol Mansfield & George L. Van Houtven & Joel Huber, 2002. "Compensating for Public Harms: Why Public Goods Are Preferred to Money," Land Economics, University of Wisconsin Press, vol. 78(3), pages 368-389.
    24. Judith I. M. de Groot & Elisa Schweiger & Iljana Schubert, 2020. "Social Influence, Risk and Benefit Perceptions, and the Acceptability of Risky Energy Technologies: An Explanatory Model of Nuclear Power Versus Shale Gas," Risk Analysis, John Wiley & Sons, vol. 40(6), pages 1226-1243, June.
    25. Motz, Alessandra, 2021. "Consumer acceptance of the energy transition in Switzerland: The role of attitudes explained through a hybrid discrete choice model," Energy Policy, Elsevier, vol. 151(C).
    26. William H. Greene & David A. Hensher, 2013. "Revealing additional dimensions of preference heterogeneity in a latent class mixed multinomial logit model," Applied Economics, Taylor & Francis Journals, vol. 45(14), pages 1897-1902, May.
    27. Heiner, Ronald A, 1983. "The Origin of Predictable Behavior," American Economic Review, American Economic Association, vol. 73(4), pages 560-595, September.
    28. Vincenzina Caputo & Ellen J. Van Loo & Riccardo Scarpa & Rodolfo M. Nayga & Wim Verbeke, 2018. "Comparing Serial, and Choice Task Stated and Inferred Attribute Non†Attendance Methods in Food Choice Experiments," Journal of Agricultural Economics, Wiley Blackwell, vol. 69(1), pages 35-57, February.
    29. Nicolás C. Bronfman & Esperanza López Vázquez, 2011. "A Cross‐Cultural Study of Perceived Benefit Versus Risk as Mediators in the Trust‐Acceptance Relationship," Risk Analysis, John Wiley & Sons, vol. 31(12), pages 1919-1934, December.
    30. Michelle S Segovia & Marco A Palma, 2021. "Testing the consistency of preferences in discrete choice experiments: an eye tracking study," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 48(3), pages 624-664.
    31. Strazzera, Elisabetta & Mura, Marina & Contu, Davide, 2012. "Combining choice experiments with psychometric scales to assess the social acceptability of wind energy projects: A latent class approach," Energy Policy, Elsevier, vol. 48(C), pages 334-347.
    32. Riccardo Scarpa & Raffaele Zanoli & Viola Bruschi & Simona Naspetti, 2013. "Inferred and Stated Attribute Non-attendance in Food Choice Experiments," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(1), pages 165-180.
    33. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, Oxford University Press, vol. 69(1), pages 99-118.
    34. Campbell, Danny & Boeri, Marco & Doherty, Edel & George Hutchinson, W., 2015. "Learning, fatigue and preference formation in discrete choice experiments," Journal of Economic Behavior & Organization, Elsevier, vol. 119(C), pages 345-363.
    35. Fabrizio Iaccarino, 2010. "Resurgence of Nuclear Energy in Italy," Nuclear Law Bulletin, OECD Publishing, vol. 2009(2), pages 65-80.
    36. Ali Chalak & Mohamad Abiad & Kelvin Balcombe, 2016. "Joint use of attribute importance rankings and non-attendance data in choice experiments," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 43(5), pages 737-760.
    37. John M. Rose & Stephane Hess & Andrew T. Collins, 2013. "What if My Model Assumptions are Wrong? The Impact of Non-standard Behaviour on Choice Model Estimation," Journal of Transport Economics and Policy, University of Bath, vol. 47(2), pages 245-263, May.
    38. Robert J. Johnston & Kevin J. Boyle & Wiktor (Vic) Adamowicz & Jeff Bennett & Roy Brouwer & Trudy Ann Cameron & W. Michael Hanemann & Nick Hanley & Mandy Ryan & Riccardo Scarpa & Roger Tourangeau & Ch, 2017. "Contemporary Guidance for Stated Preference Studies," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 4(2), pages 319-405.
    39. Stephane Hess & Amanda Stathopoulos & Danny Campbell & Vikki O’Neill & Sebastian Caussade, 2013. "It’s not that I don’t care, I just don’t care very much: confounding between attribute non-attendance and taste heterogeneity," Transportation, Springer, vol. 40(3), pages 583-607, May.
    40. Strazzera, Elisabetta & Meleddu, Daniela & Atzori, Rossella, 2022. "A hybrid choice modelling approach to estimate the trade-off between perceived environmental risks and economic benefits," Ecological Economics, Elsevier, vol. 196(C).
    41. Cantillo, Víctor & Heydecker, Benjamin & de Dios Ortúzar, Juan, 2006. "A discrete choice model incorporating thresholds for perception in attribute values," Transportation Research Part B: Methodological, Elsevier, vol. 40(9), pages 807-825, November.
    42. Greene, William H. & Hensher, David A., 2003. "A latent class model for discrete choice analysis: contrasts with mixed logit," Transportation Research Part B: Methodological, Elsevier, vol. 37(8), pages 681-698, September.
    43. Wang, Qiang & Chen, Xi & Yi-chong, Xu, 2013. "Accident like the Fukushima unlikely in a country with effective nuclear regulation: Literature review and proposed guidelines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 17(C), pages 126-146.
    44. Robin Gregory & Howard Kunreuther & Doug Easterling & Ken Richards, 1991. "Incentives Policies to Site Hazardous Waste Facilities," Risk Analysis, John Wiley & Sons, vol. 11(4), pages 667-675, December.
    45. Truelove, Heather Barnes, 2012. "Energy source perceptions and policy support: Image associations, emotional evaluations, and cognitive beliefs," Energy Policy, Elsevier, vol. 45(C), pages 478-489.
    46. Cicia, Gianni & Cembalo, Luigi & Del Giudice, Teresa & Palladino, Andrea, 2012. "Fossil energy versus nuclear, wind, solar and agricultural biomass: Insights from an Italian national survey," Energy Policy, Elsevier, vol. 42(C), pages 59-66.
    47. David Hensher & John Rose & William Greene, 2005. "The implications on willingness to pay of respondents ignoring specific attributes," Transportation, Springer, vol. 32(3), pages 203-222, May.
    48. Lock, Simon J. & Smallman, Melanie & Lee, Maria & Rydin, Yvonne, 2014. "“Nuclear energy sounded wonderful 40 years ago”: UK citizen views on CCS," Energy Policy, Elsevier, vol. 66(C), pages 428-435.
    49. Yves Schneider & Peter Zweifel, 2013. "Spatial Effects in Willingness to Pay for Avoiding Nuclear Risks," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 149(III), pages 357-379, September.
    50. Erdem, Seda & Campbell, Danny & Thompson, Carl, 2014. "Elimination and selection by aspects in health choice experiments: Prioritising health service innovations," Journal of Health Economics, Elsevier, vol. 38(C), pages 10-22.
    51. Hess, Stephane & Train, Kenneth E. & Polak, John W., 2006. "On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice," Transportation Research Part B: Methodological, Elsevier, vol. 40(2), pages 147-163, February.
    52. Campbell, Danny & Hensher, David A. & Scarpa, Riccardo, 2014. "Bounding WTP distributions to reflect the ‘actual’ consideration set," Journal of choice modelling, Elsevier, vol. 11(C), pages 4-15.
    53. Mylene Lagarde, 2013. "Investigating Attribute Non‐Attendance And Its Consequences In Choice Experiments With Latent Class Models," Health Economics, John Wiley & Sons, Ltd., vol. 22(5), pages 554-567, May.
    54. Hayashi, Masatsugu & Hughes, Larry, 2013. "The policy responses to the Fukushima nuclear accident and their effect on Japanese energy security," Energy Policy, Elsevier, vol. 59(C), pages 86-101.
    55. Araña, Jorge E. & León, Carmelo J. & Hanemann, Michael W., 2008. "Emotions and decision rules in discrete choice experiments for valuing health care programmes for the elderly," Journal of Health Economics, Elsevier, vol. 27(3), pages 753-769, May.
    56. Hess, Stephane & Palma, David, 2019. "Apollo: A flexible, powerful and customisable freeware package for choice model estimation and application," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    57. Contu, Davide & Mourato, Susana, 2020. "Complementing choice experiment with contingent valuation data: Individual preferences and views towards IV generation nuclear energy in the UK," Energy Policy, Elsevier, vol. 136(C).
    58. Kim, Junghun & Park, Stephen Youngjun & Lee, Jongsu, 2018. "Do people really want renewable energy? Who wants renewable energy?: Discrete choice model of reference-dependent preference in South Korea," Energy Policy, Elsevier, vol. 120(C), pages 761-770.
    59. Ian J. Bateman & Richard T. Carson & Brett Day & Michael Hanemann & Nick Hanley & Tannis Hett & Michael Jones-Lee & Graham Loomes, 2002. "Economic Valuation with Stated Preference Techniques," Books, Edward Elgar Publishing, number 2639.
    60. Sung-Yoon Huh & JongRoul Woo & Chul-Yong Lee, 2019. "What Do Potential Residents Really Want When Hosting a Nuclear Power Plant? An Empirical Study of Economic Incentives in South Korea," Energies, MDPI, vol. 12(7), pages 1-17, March.
    61. Wouter Poortinga & Nick F. Pidgeon, 2003. "Exploring the Dimensionality of Trust in Risk Regulation," Risk Analysis, John Wiley & Sons, vol. 23(5), pages 961-972, October.
    62. Leong, Waiyan & Hensher, David A., 2012. "Embedding multiple heuristics into choice models: An exploratory analysis," Journal of choice modelling, Elsevier, vol. 5(3), pages 131-144.
    63. Riccardo Scarpa & Timothy J. Gilbride & Danny Campbell & David A. Hensher, 2009. "Modelling attribute non-attendance in choice experiments for rural landscape valuation," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 36(2), pages 151-174, June.
    64. Apergis, Nicholas & Payne, James E. & Menyah, Kojo & Wolde-Rufael, Yemane, 2010. "On the causal dynamics between emissions, nuclear energy, renewable energy, and economic growth," Ecological Economics, Elsevier, vol. 69(11), pages 2255-2260, September.
    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. Kim, Kyungah & Moon, Sungho & Kim, Junghun, 2023. "How far is it from your home? Strategic policy and management to overcome barriers of introducing fuel-cell power generation facilities," Energy Policy, Elsevier, vol. 182(C).

    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. Contu, Davide & Strazzera, Elisabetta & Mourato, Susana, 2016. "Modeling individual preferences for energy sources: The case of IV generation nuclear energy in Italy," Ecological Economics, Elsevier, vol. 127(C), pages 37-58.
    2. Gonçalves, Tânia & Lourenço-Gomes, Lina & Pinto, Lígia M. Costa, 2022. "The role of attribute non-attendance on consumer decision-making: Theoretical insights and empirical evidence," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 788-805.
    3. Logar, Ivana & Brouwer, Roy & Campbell, Danny, 2020. "Does attribute order influence attribute-information processing in discrete choice experiments?," Resource and Energy Economics, Elsevier, vol. 60(C).
    4. Sandorf, Erlend Dancke & Crastes dit Sourd, Romain & Mahieu, Pierre-Alexandre, 2018. "The effect of attribute-alternative matrix displays on preferences and processing strategies," Journal of choice modelling, Elsevier, vol. 29(C), pages 113-132.
    5. Jourdain, Damien & Lairez, Juliette & Striffler, Bruno & Lundhede, Thomas, 2022. "A choice experiment approach to evaluate maize farmers’ decision-making processes in Lao PDR," Journal of choice modelling, Elsevier, vol. 44(C).
    6. Erlend Dancke Sandorf & Danny Campbell, 2019. "Accommodating satisficing behaviour in stated choice experiments," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 46(1), pages 133-162.
    7. Sandra Notaro & Maria De Salvo & Roberta Raffaelli, 2022. "Estimating Willingness to Pay for Alpine Pastures: A Discrete Choice Experiment Accounting for Attribute Non-Attendance," Sustainability, MDPI, vol. 14(7), pages 1-15, March.
    8. David Hensher, 2014. "Attribute processing as a behavioural strategy in choice making," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 12, pages 268-289, Edward Elgar Publishing.
    9. Gonçalves, Tânia & Lourenço-Gomes, Lina & Pinto, Lígia M. Costa, 2020. "Dealing with ignored attributes through an inferred approach in wine choice experiments," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 87(C).
    10. David Hensher & Andrew Collins & William Greene, 2013. "Accounting for attribute non-attendance and common-metric aggregation in a probabilistic decision process mixed multinomial logit model: a warning on potential confounding," Transportation, Springer, vol. 40(5), pages 1003-1020, September.
    11. Gonçalves, Tânia & Pinto, Lígia M. Costa & Lourenço-Gomes, Lina, 2020. "Attribute non-attendance in wine choice: Contrasts between stated and inferred approaches," Economic Analysis and Policy, Elsevier, vol. 66(C), pages 262-275.
    12. Edenbrandt, Anna Kristina & Lagerkvist, Carl-Johan & Lüken, Malte & Orquin, Jacob L., 2022. "Seen but not considered? Awareness and consideration in choice analysis," Journal of choice modelling, Elsevier, vol. 45(C).
    13. Richard Yao & Riccardo Scarpa & John Rose & James Turner, 2015. "Experimental Design Criteria and Their Behavioural Efficiency: An Evaluation in the Field," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 62(3), pages 433-455, November.
    14. Espinosa-Goded, María & Rodriguez-Entrena, Macario & Salazar-Ordóñez, Melania, 2021. "A straightforward diagnostic tool to identify attribute non-attendance in discrete choice experiments," Economic Analysis and Policy, Elsevier, vol. 71(C), pages 211-226.
    15. Stephane Hess, 2014. "Latent class structures: taste heterogeneity and beyond," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 14, pages 311-330, Edward Elgar Publishing.
    16. Daniel, Aemiro Melkamu, 2020. "Towards Sustainable Energy Consumption Electricity Demand Flexibility and Household Fuel Choice," Umeå Economic Studies 971, Umeå University, Department of Economics.
    17. Chen, Xuqi & Shen, Meng & Gao, Zhifeng, 2017. "Impact of Intra-respondent Variations in Attribute Attendance on Consumer Preference in Food Choice," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258509, Agricultural and Applied Economics Association.
    18. Motz, Alessandra, 2021. "Consumer acceptance of the energy transition in Switzerland: The role of attitudes explained through a hybrid discrete choice model," Energy Policy, Elsevier, vol. 151(C).
    19. Danny Campbell & Seda Erdem, 2015. "Position Bias in Best-worst Scaling Surveys: A Case Study on Trust in Institutions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(2), pages 526-545.
    20. Mara Thiene & Riccardo Scarpa & Jordan Louviere, 2015. "Addressing Preference Heterogeneity, Multiple Scales and Attribute Attendance with a Correlated Finite Mixing Model of Tap Water Choice," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 62(3), pages 637-656, November.

    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:eee:eejocm:v:44:y:2022:i:c:s1755534522000276. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/journal-of-choice-modelling .

    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.