Bayesian analysis, Choice modeling, Willingness-to-pay, C11, M31,

The emergence of Bayesian methodology has facilitated respondent-level conjoint models, and deriving utilities from choice experiments has become very popular among those modeling product line decisions or new product * Co-chairs. Author order is alphabetical. ALLENBY ET AL.introductions. This review begins with a paradox of why experimental choices should mirror market behavior despite clear differences in content, structure and motivation. It then addresses ways to design the choice tasks so that they are more likely to reflect market choices. Finally, it examines ways to model the results of the choice experiments to better mirror both underlying decision processes and potential market choices.

No abstract

Genomic tools are now available for most livestock species and are used routinely for genomic selection (GS) in cattle. One of the most important developments resulting from the introduction of genomic testing for dairy cattle is the application of reasonably priced low-density single nucleotide polymorphism technology in the selection of females. In this context, combining genome testing and reproductive biotechnologies in young heifers enables new strategies to generate replacement and elite females in a given period of time. Moreover, multiple markers have been detected in biopsies of preimplantation stage embryos, thus paving the way to develop new strategies based on preimplantation diagnosis and the genetic screening of embryos. Based on recent advances in GS, the present review focuses on new possibilities inherent in reproductive technologies used for commercial purposes and in genetic schemes, possible side effects and beneficial impacts on reproductive efficiency. A particular focus is on the different steps allowing embryo genotyping, including embryo micromanipulation, DNA production and quality assessment.

Direct utility models of consumer choice are reviewed and developed for understanding consumer preferences. We begin with a review of statistical models of choice, posing a series of modeling challenges that are resolved by considering economic foundations based on constrained utility maximization. Direct utility models differ from other choice models by directly modeling the consumer utility function used to derive the likelihood of the data through Kuhn-Tucker conditions. Recent advances in Bayesian estimation make the estimation