Social shopping is one of the latest trends on the Internet. Websites dedicated to social networking with a focus on shopping have been emerging on the web for a few years. The basic idea is that consumers are looking for product information on the Internet and social shopping sites provide a place for consumers to find this information from other consumers. These sites provide a place for their users to engage in socialization and shopping simultaneously, sometimes following recommendations of premier users, who are labeled from other users. However, purchases aren't made through these sites. So, there may still be something missing from the experience. For these sites, social pricing mechanisms may be implemented to provide revenue. Major ecommerce websites have begun focusing on increasing social features throughout the transaction process. For example, more websites are including ratings, reviews and recommendations of products and services by other consumers. However, pure ecommerce websites do not provide functionality that allows consumers to communicate in real time. Hence, there are some features missing from the social experience. Also, the social functionality included in pure e-commerce websites, tends to be utilized for the benefit of the Web site, as opposed to the consumers. Both social shopping sites and ecommerce sites have seen independently successful though few sites have been able to truly integrate these together at this point. It may be more beneficial to the end user if these sites could work in unison. This thesis is an exploratory study of the emerging social shopping phenomenon. The contributions of this work include analysis of the social shopping phenomenon and identifying metrics and Web sites that incorporate social shopping, a survey of academic literature related to social shopping and social pricing and a review of current recommender system algorithms with a discussion on how to incorporate social networking data into the algorithms to improve recommendations. Improvement suggestions include incorporating customer purchase history with social networking information. Potential future research ideas are included.

Les enquêtes préférences déclarées (EPD) reposent sur des mises en situation hypothétiques. Face à une situation de choix construite de toute pièce par l’analyste, chaque répondant doit déclarer le choix qu’il ferait s’il y était confronté en réalité. Chaque situation se présente comme la combinaison de plusieurs paramètres. Face à chacune des diverses situations qui lui sont présentées successivement, l’enquêté va devoir faire le choix de celles lui convenant le mieux. Au fil du questionnaire, ses réponses révèleront l’importance qu’il donne à chaque paramètre et contribueront à une meilleure appréhension de ses préférences et de ses choix. Ce travail s’articule autour de trois études de cas mises en œuvre dans le cadre d’études menées par des opérateurs de transport (SNCF – thème : réforme de tarification sociale), des gestionnaires d’infrastructure (RFF – thème : effets du cadencement sur l’attractivité du train) ou des organismes de recherche (LET et PREDIT – thème : impact de politiques de rationnement du carburant sur la mobilité automobile). L’objet de ces études nécessitait la mise en œuvre d’enquêtes préférences déclarées. La conception, la mise en œuvre et l’analyse des EPD ont été réalisées dans le cadre de cette thèse avec un soucis permanent de contrôle de chacun des paramètres en vue de garantir la qualité des résultats obtenus.Selon les objectifs de l’étude, des traitements économétriques divers ont été utilisés pour analyser les données récoltées.Finalement, chacune de ces mises en place a contribué à renforcer notre conviction que les EPD constituent un outil complet. Ce travail contribue finalement, à son échelle, à crédibiliser un peu plus les méthodes de préférences déclarées et invite à repositionner cet outil d’analyse comme pivot de toute réflexion complexe dont le protocole est à réinventer lors de chaque construction, plutôt que tel qu’un procédé connu, livré clé en main, dont l’application suit une logique mécanique. / Stated preference surveys are based on choice sets composed by the analyst and proposed to some respondents. Each situation of the choice set is the combination of pre-determined attributes. While declaring the choice they would make if they were confronted to the same situation in reality, respondents reveal their preferences and their perceptions of the attributes.This Phd work presents the results of three stated preference surveys applied in the camp of public transportation. All surveys form a part of more general research programs handled for the sake: of the French railway operator, known as the SNCF (2006/2007) ; of the French railway network administrator, called RFF (2008) ; and of the French research, experimentation and innovation program in land transport, named PREDIT (2010). The use of stated preference methodology was required in order to deal efficiently with the issues of each of those research programs (respectively treating of social pricing ; train supply policy ; fuel rationing policies). The conception, the implementation and the analysis of the surveys have all been carried out during this Phd work in order to warranty control of each parameter and thus high quality results.In accordance with program research objectives, different econometrics treatments have been implemented.This Phd work shows how stated preference surveys may deal with different complex issues and therefore promote the use of this method. Each of these studies have finally strengthened the conviction that stated preferences constitute an efficient and complete tool.