Destination Choice Models for Rock Climbing in the Northeastern Alps: A Latent-Class Approach Based on Intensity of Preferences

By Riccardo Scarpa, M. Thiene. Land Economics, 2005

418 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Social Psychology, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/61cced7d89369954a2ce353ab38354bfdfa886b7

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Citations in the corpus

Using Angler Characteristics and Attitudinal Data to Identify Environmental Preference Classes: A Latent-Class Model (2006, neutral): “Applications of latent-class models in environmental economics are rare; examples include Boxall and Adamowicz (2002), Provencher et al. (2002), Scarpa et al. (2003), Shonkwiler and Shaw (2003), and Scarpa and Thiene (2005) .”
Modeling preference heterogeneity in stated choice data: an analysis for public goods generated by agriculture (2009, background): “When different criteria indicate different preferred numbers of segments, Scarpa and Thiene (2005) note that selection " must also account for significance of parameter estimates and be tempered by the analyst's own judgement on the meaning of the parameter signs " .”
Valuing animal genetic resources: a choice modeling application to indigenous cattle in Kenya (2007, methodology): “More recently, latent class models have been used in travel cost revealed preference studies (e.g., Morey et al., 2006; Provencher et al., 2002; Scarpa and Thiene, 2005) and stated preference applications (for an application in food choice see Hu et al., 2004).”
Valuing biodiversity enhancement in New Zealand's planted forests: Socioeconomic and spatial determinants of willingness-to-pay (2014, background): “For example, Scarpa and Thiene (2005) failed to identify any socio-economic variable to have an effect on membership probabilities in a latent class model of choice of destination for mountain visitation by climbers in the European Alps.”
Latent lifestyle preferences and household location decisions (2007, background): “10; Swait and Sweeney 2000) and has now permeated other fields including economics, transport, and geography (see, for example, Gopinath 1995; Boxall and Adamowicz 2002; Greene and Hensher 2003; Scarpa and Thiene 2005; Milon and Scrogin 2006).”
What’s in a name? The use of quantitative measures versus ‘Iconised’ species when valuing biodiversity (2008, methodology): “Recent advances in the use of Mixed Logit models (Hensher and Greene 2003) and the latent-class models are relevant tools of analysis to this end (Boxall and Adamowicz 2002; Greene and Hensher 2003; Scarpa and Thiene 2005; Morey et al. 2006, Louviere 2006).”
Utility in Willingness to Pay Space: A Tool to Address Confounding Random Scale Effects in Destination Choice to the Alps (2008, methodology): “Technical information about the algorithm can be found in Train and Sonnier (2005) and Train (2003).6 4 The only other study we know of on the region is Scarpa and Thiene (2005) and it focused on rock-climbers and not generic day-out visitors.”
Investigating farmers' preferences for the design of agri-environment schemes: a choice experiment approach (2008, methodology): “As a guide to the selection of the optimal model, a number of authors have suggested the use information theoretic criteria tempered by the analyst’s own judgement (e.g. Swait 1994, Boxal and Adamowicz 2002, Scarpa and Thiene 2005).”
The influence of social relationships on pro-environment behaviors (2012, background): “To determine the number of latent classes among the models that fit the data, we use the Bayesian information criterion (BIC) based on the model’s log- 8 Recent applications in the economics literature of latent models (also known as finite-mixture models) include Clark, Etile, Postel-Vinay, Senik a”
Contemporary Guidance for Stated Preference Studies (2017, background): “…guide the choice of distributions (Train 1998, 2009; Hensher and Greene 2003), and empirical guidance on distributions can be gleaned by examining the posterior distributions of individual-specific coefficients (Huber and Train 2001; Greene, Hensher, and Rose 2005; Scarpa and Thiene 2005).”
Adoption of renewable heating systems: An empirical test of the diffusion of innovation theory (2017, methodology): “The membership probability equation can take on a semi-parametric form only dependent on a constant term [50].”
Preferences for urban green spaces and peri-urban forests: An analysis of stated residential choices (2016, background): “The LC model classifies espondents into several classes and formulates their preference ariation with a discrete distribution (Boxall & Adamowicz, 2002; osenius, 2010; Scarpa & Thiene, 2005).”