Behavior and agent-based
systems modeling

Generalized matching theory in two-sided networks; hierarchical multi-stakeholder modeling and mechanism design in public-private partnership for sustainable and resilient infrastructure systems;

Intellectual Merits:

Bilateral interactions in two-sided network are universal phenomena in the areas of many applications such as regional and international trade, e-commerce, share economy, transportation, and urban planning. For instance, in trade and supply chain analysis, buyers and sellers interact via a two-sided network in order to satisfy their purchasing/selling needs; in transportation and urban planning, travelers and migrants move from origins via physical and social networks to destinations for various purposes. As customer-oriented service and human-centered design become more feasible in the information age, theories and models that capture and represent individual behaviors are crucial and essential for the studies of two-sided networks, i.e. in understanding the observations of two-sided interactions, forecasting future activities, and designing policies, platforms, markets and mechanisms to achieve desirable outcomes. Matching theory utilizes game theory to study the behaviors of intelligent agents who, according to their preferences and subject to individual and bilateral constraints, decide to match or trade with their counterparts on the other side of the network. This line of CUTES research on behavior and generalized matching theory in two-sided networks aims to contribute to the matching literature by proposing and studying generalized matching, which expands the existing matching theory to multi-unit many-to-many matching with quota constraints. This is a more general and realistic framework for matching that happens in real world. First, models for two-sided and one-sided matching with newly defined preference relationships and solution concepts are developed for analyzing multi-unit and multi-partner matching with quota constraints. The corresponding new matching mechanisms are then designed to produce stable and favorable matching outcomes. Second, a hybrid model for generalized matching is established to encompass both one-sided and two-sided matching under the generalized framework. Again, the corresponding hybrid matching mechanism with desired properties is proposed and discussed. Next, linking the newly proposed theoretical work to empirical application, a novel bi-level estimation model is proposed for generalized matching to make inferences of agents’ matching behaviors/decisions.

On the other hand, the problem of financing critical infrastructure for sustainability and smart living is of fundamental importance. On the theoretical front for infrastructure financing, we propose novel mechanism design approaches to modeling public-private partnership. Mechanism design is a theory that focuses on design of institutions to achieve certain objectives, with the assumption that all the players will act strategically and hold private information necessary in decision making. Mechanism design in PPP enables us to deal with privately held information and hence to model the whole project and determine key parameters more precisely, directly and easily. In our study, we mathematically model PPP to discuss whether government could achieve social optimum for free in urban highway PPP project. Previous modeling methods in PPP share two common shortcomings: over-simplified assumption on behavior of users and owners of the highway and insufficient attention to privately-held information. In our study we create a new form of PPP, improved Investment Public-Private Partnership using mechanism design as a multi-leader-multi-follower (MLMF) Stackelberg game. The implementability in MLMF Stackelberg game in dominant strategy and Bayesian equilibria is derived and the feasibility of the model is proved through these theories. This research is then further extended to studying the low procurement efficiency in the context of private participation in infrastructure procurement. Based on hierarchical principal-agent model and highway pricing model, contributions from this research are three-fold. First, a framework connecting two dimensions (i.e., horizontally the stakeholder management, decentralization and agency problems; vertically the engineering and economic models) is established. Second, the corruption problems in post-tender phase of infrastructure project are addressed, given that previous research in this field is limited. Finally, important policy insights and recommendations are provided regarding corruption detection and prevention.