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The landscape of econometric discrete choice modelling research

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  • Haghani, Milad
  • Bliemer, Michiel C.J.
  • Hensher, David A.

Abstract

Econometric modelling of choice now constitutes a major cross-over between multiple fields of research in which quantitative valuation of human preferences is of interest. The methods are pervasively used by consumer, environmental and health economists as well as transportation researchers and beyond. This work analyses the scholarly literature on econometric discrete choice modelling developed in the last fifty years. The literature is estimated to have grown beyond 14,000 research items while an excess of 1,000 new items have been published each year since 2015. This trend has essentially doubled the size of this literature within the last five years. While the largest portion of this literature is concentrated in the transportation sector, the methods are currently most trendy in health economics. This is striking given that health economists come late to adopt econometric choice methods compared to other major disciplines. Since 2014, more applications of discrete choice models have been reported in health-related studies than any other domain. Also, while the number of applications in consumer and transportation studies have been fluctuating over the past few years, applications in environmental studies are steadily on the rise at a rate comparable to that of health. Activities in the methodological cluster of this field have rather notably slowed down during the recent years although not extinct. Also, despite slowing down of choice modelling applications in transportation compared to the previous decades, such applications have not disappeared from the transportation sector. A particular area of transportation research where applications of choice modelling methods are still notably trending is electric and automated mobility. Pioneering studies, most influential studies and various streams of choice modelling research along with their time of emergence and duration of trendiness are also objectively determined using a document co-citation analysis. Further analyses are also conducted on patterns of collaboration in this field. These outcomes document the history of development of choice modelling literature at a macro scale and provide a holistic understanding of various divisions of this field along with its influential entities.

Suggested Citation

  • Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
  • Handle: RePEc:eee:eejocm:v:40:y:2021:i:c:s1755534521000361
    DOI: 10.1016/j.jocm.2021.100303
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    4. Haghani, Milad & Bliemer, Michiel C.J. & Rose, John M. & Oppewal, Harmen & Lancsar, Emily, 2021. "Hypothetical bias in stated choice experiments: Part I. Macro-scale analysis of literature and integrative synthesis of empirical evidence from applied economics, experimental psychology and neuroimag," Journal of choice modelling, Elsevier, vol. 41(C).
    5. Conti, G.; & Giustinelli, P.;, 2022. "For Better or Worse? Subjective Expectations and Cost-Benefit Trade-Offs in Health Behavior: An Application to Lockdown Compliance in the United Kingdom," Health, Econometrics and Data Group (HEDG) Working Papers 22/14, HEDG, c/o Department of Economics, University of York.
    6. Pérez-Troncoso, Daniel, 2022. "Optimal sequential strategy to improve the precision of the estimators in a discrete choice experiment: A simulation study," Journal of choice modelling, Elsevier, vol. 43(C).
    7. Gabriella Conti & Pamela Giustinelli, 2023. "For better or worse? Subjective expectations and cost-benefit trade-offs in health behavior," IFS Working Papers W23/19, Institute for Fiscal Studies.
    8. Boxebeld, Sander, 2024. "Ordering effects in discrete choice experiments: A systematic literature review across domains," Journal of choice modelling, Elsevier, vol. 51(C).
    9. Buonocore, Ciro & Carlucci, Fabio & Ciciarelli, Lucia & Papola, Andrea & Tinessa, Fiore & Tocchi, Daniela & Trincone, Barbara, 2023. "Accessibility analysis in spatial planning: A case of special economic zones (SEZs) in Campania, Southern Italy," Land Use Policy, Elsevier, vol. 132(C).
    10. Gu, Yu & Chen, Anthony & Kitthamkesorn, Songyot, 2022. "Weibit choice models: Properties, mode choice application and graphical illustrations," Journal of choice modelling, Elsevier, vol. 44(C).
    11. Haghani, Milad & Bliemer, Michiel C.J. & de Bekker-Grob, Esther W., 2022. "Applications of discrete choice experiments in COVID-19 research: Disparity in survey qualities between health and transport fields," Journal of choice modelling, Elsevier, vol. 44(C).
    12. Isler, Cassiano Augusto & Blumenfeld, Marcelo & Caldeira, Gabriel Pereira & Roberts, Clive, 2024. "Long-Distance railway mode choice in Brazil: Evidence from a discrete choice experiment," Research in Transportation Economics, Elsevier, vol. 104(C).

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