In this work, we focus on two attractive crowd-based business models, i.e., user-generated content creation and freight-matching long-haul trucking. First, as elaborated in CHAPTER 2, we consider a game theoretical modeling approach for understanding the operation of non-profit UGC platforms that rely on users to create content and maintain financial sustainability. In particular, we examine several interesting research questions with practical importance and unique contributions to the literature. These research questions mainly investigate how changes in critical business factors influence the platforms' strategic effort allocation, user participation, and overall performance. Second, in CHAPTER 3, we focus on the flourishing freight-matching businesses that rely on crowdsourced drivers for long-haul trucking. In particular, although the practice suggests that shippers' ordering behaviors of freight-matching services may remarkably impact crowdsourced drivers' bidding behaviors, the literature has yet to examine this issue formally. Therefore, we collect industrial data and construct a strict empirical schema for understanding the association between shippers' order timing and freight-matching performance. Besides, by deliberately building a theoretical modeling framework and using a data-driven estimation of model parameters, we are able to simulate the freight-matching performance of adopting our empirical findings and evaluate the practical value of our study. By investigating these two prominent business models, we aim to understand the advantages of crowdsourcing businesses and the role of crowds in nowadays' business innovations. Besides, we also provide valuable managerial insights for business runners who are interested in this "young" market of crowdsourcing businesses. / Business Administration/Strategic Management

Le but de ce travail est l'étude du problème de gestion de flot de conteneurs et de véhicules dans un réseau multimodal. Nous proposons une formulation du problème sous forme d'un modèle mathématique réaliste qui prend en considération les différents aspects liés au transport et au stockage des conteneurs et dont l'objectif est de minimiser le coût global de transport. Pour la résolution des grandes instances une approche de résolution bi-niveaux est proposée. Dans un premier niveau nous construisons un modèle agrégé plus facile à résoudre pour en extraire les décisions liées aux déplacements des trains et des barges ainsi qu'une borne duale de notre problème de base. Ces informations sont utilisées dans un deuxième niveau pour avoir des solutions de bonne qualité de notre problème par rapport aux solutions données par CPLEX en résolvant directement le modèle de base. Des résultats numériques sur des instances générées aléatoirement sont présentés et ils prouvent l'intérêt de l'approche de résolution proposée dans cette thèse. / The aim of this work is the study of the problem of managing the flow of containers and vehicles in a multimodal network. We propose a formulation of the problem under the form of a realistic mathematical model that takes into account the different aspects related to container transport and storage and whose objective is to minimize the overall cost of transport. For large-scale resolution, a two-level resolution approach is proposed. In a first level we build an aggregated model easier to solve to extract the decisions related to the movements of trains and barges as well as a dual terminal of our basic problem. This information is used in a second level to have good quality solutions of our problem compared to the solutions given by CPLEX by directly solving the basic model. Numerical results on randomly generated instances are presented and prove the value of the proposed resolution approach.