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Abstract

A discrete choice experiment is an attribute based method that gives further insight into how individuals develop preferences for particular attributes. These are used in the traditional areas in health economics, transportation, and marketing and increasingly beyond these areas. These experiments enable researchers to model choice in an explicit competitive context, thus realistically emulating market decisions. A choice designconsists of choice sets composed of several alternatives, each defined as combinations of different attribute levels. A good choice design is efficient, meaning that the parameters of the choice model are estimated with maximum precision.Here, method of obtaining discrete choice sets using factorial combinations has been described.

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The importance of natural soundscapes and natural quiet to the recreational experience in protected areas is well established. While a growing body of research examines how recreationists are impacted by anthropogenic noise that inhibits their experience of natural soundscapes, a very limited amount of research examines recreationists’ preferences for soundscape management. In fact, sparse research examines park visitors’ preferences concerning the management of road noise—perhaps the greatest source of noise pollution in protected areas. It is therefore the purpose of this study to bridge a significant gap in the protected area soundscape literature by examining how varying road noise management actions—including quiet pavement—impact recreationist utility. In this research, the results of a field-based choice experiment in Death Valley National Park (USA) are used to analyze how visitors navigate the tradeoff between natural quiet and freedom and how varying management actions impact recreationist utility. Results show that recreationists require substantial gains in quietness to relinquish freedom; and quiet pavement and reduced speed limits have the least negative impact on recreationist utility. Implications of these results include improved management of road noise in protected areas and considerations for future research of park soundscapes. Management implications This research highlights the important roles natural quiet and freedom play in hikers’ experiences in parks and protected areas. In this case of road noise mitigation, quiet pavement and reduced speed limits represent management actions that can achieve reduced road noise while remaining relatively unobtrusive to the recreationist experience and not leading to substantial losses in freedom. However, park managers must also consider the demographics and noise sensitivity of their visitors when assessing their soundscape management options, as the impacts of management actions and noise dispersion vary across nationality and noise sensitivities.
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For two-level choice experiments, we obtain a simple form of the information matrix of a choice design for estimating the main effects, and provide D- and MS-optimal paired choice designs with distinct choice sets under the main effects model for any number of choice sets. It is shown that the optimal designs under the main effects model are also optimal under the broader main effects model. We find that optimal choice designs with a choice set size two often outperform their counterparts with larger choice set sizes.
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The most comprehensive and applied discussion of stated choice experiment constructions available. The Construction of Optimal Stated Choice Experiments provides an accessible introduction to the construction methods needed to create the best possible designs for use in modeling decision-making. Many aspects of the design of a generic stated choice experiment are independent of its area of application, and until now there has been no single book describing these constructions. This book begins with a brief description of the various areas where stated choice experiments are applicable, including marketing and health economics, transportation, environmental resource economics, and public welfare analysis. The authors focus on recent research results on the construction of optimal and near-optimal choice experiments and conclude with guidelines and insight on how to properly implement these results. Features of the book include: Construction of generic stated choice experiments for the estimation of main effects only, as well as experiments for the estimation of main effects plus two-factor interactions. Constructions for choice sets of any size and for attributes with any number of levels. A discussion of designs that contain a none option or a common base option. Practical techniques for the implementation of the constructions. Class-tested material that presents theoretical discussion of optimal design. Complete and extensive references to the mathematical and statistical literature for the constructions. Exercise sets in most chapters, which reinforce the understanding of the presented material. The Construction of Optimal Stated Choice Experiments serves as an invaluable reference guide for applied statisticians and practitioners in the areas of marketing, health economics, transport, and environmental evaluation. It is also ideal as a supplemental text for courses in the design of experiments, decision support systems, and choice models. A companion web site is available for readers to access web-based software that can be used to implement the constructions described in the book.
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We vary the complexity of choice sets used in stated preference methods to evaluate the impact on choice consistency. We define five measures of complexity that capture either the amount of information or the correlational structure of information in a choice set. Using these measures as randomly assigned treatments in a large experiment, we analyze the consistency of respondents' choices using a heteroskedastic multinomial logit model. We find that: (i) all of our measures of choice set complexity affect choice consistency, (ii) changes in the correlational structure of information have the largest impact on choice consistency, and (iii) choice complexity significantly distorts welfare estimates. Our results confirm economists' initial worry that moving from contingent valuation to conjoint methods will increase complexity-induced choice inconsistency. However, our analysis also shows that these negative impacts may be mitigated if precautions are taken at the design and estimation stages of stated preference methods.
Guidelines for Stated Preference Experiment Design, M.BA. Dissertation, School of International Management
  • N Sanko
Sanko, N. (2001). Guidelines for Stated Preference Experiment Design, M.BA. Dissertation, School of International Management,EcoleNationale des PontsetChaussées.