Agriculture is undergoing extreme change. The introduction of new generation agricultural products has generated an increased need for efficient and accurate product segregation across a number of Canadian agricultural sectors. In particular, monitoring, controlling and preventing commingling of various wheat grades is critical to continued agri-food safety and quality assurance in the Canadian grain handling system. The Canadian grain handling industry is a vast regional supply chain with many participants. Grading of grain for blending had historically been accomplished by the method of Kernel Visual Distinguishability (KVD). KVD allowed a trained grain grader to distinguish the class of a registered variety of wheat solely by visual inspection. While KVD enabled rapid, dependable, and low-cost segregation of wheat into functionally different classes or quality types, it also put constraints on the development of novel traits in wheat. To facilitate the introduction of new classes of wheat to enable additional export sales in new markets, the federal government announced that KVD was to be eliminated from all primary classes of wheat as of August 1, 2008. As an alternative, the Canadian Grain Commission has implemented a system called Variety Eligibility Declaration (VED) to replace KVD. As a system based on self-declaration, the VED system may create moral hazard for misrepresentation. This system is problematic in that incentives exist for farmers to misrepresent their grain. Similarly, primary elevators have an incentive to commingle wheat classes in a profitable manner. Clearly, the VED system will only work as desired for the grain industry when supported by a credible monitoring system. That is, to ensure the security of the wheat supply chain, sampling and testing at some specific critical points along the supply chain is needed. While the current technology allows the identification of visually indistinguishable grain varieties with enough precision for most modern segregation requirements, this technology is relatively slow and expensive. With the potential costs of monitoring VED through the current wheat supply chain, there is a fundamental tradeoff confronting grain handlers, and effective handling strategies will be needed to maintain historical wheat uniformity and consistency while keeping monitoring costs down. There are important operational issues to efficiently testing grain within the supply chain, including the choice of the optimal location to test and how intensively to test. The testing protocols for grain deliveries as well as maintaining effective responsiveness to information feedback among farmers will certainly become a strategic emphasis for wheat handlers in the future. In light of this, my research attempts to identify the risks, incentives and costs associated with a functional declaration system. This research tests a series of incentives designed to generate truthful behavior within the new policy environment. In this manner, I examine potential and easy to implement testing strategies designed to maintain integrity and efficiency in this agricultural supply chain. This study is developed in the first instance by using an analytic model to explore the economic incentives for motivating farmer’s risk control efforts and handlers’ optimal handling strategies with respect to testing cost, penalty level, contamination risks and risk control efforts. We solve for optimal behavior in the supply chain assuming cost minimization among the participants, under several simplifying assumptions. In reality, the Canadian grain supply chain is composed of heterogeneous, boundedly rational and dynamically interacting individuals, and none of these characteristics fit the standard optimization framework used to solve these problems. Given this complex agent behavior, the grain supply chain is characterized by a set of non-linear relationships between individual participants, coupled with out of equilibrium dynamics, meaning that analytic solutions will not always identify or validate the set of optimized strategies that would evolve in the real world. To account for this inherent complexity, I develop an agent-based (farmers and elevators) model to simulate behaviour in a more realistic but virtual grain supply chain. After characterizing the basic analytics of the problem, the grain supply chain participants are represented as autonomous economic agents with a certain level of programmed behavioral heterogeneity. The agents interact via a set of heuristics governing their actions and decisions. The operation of a major portion of the Canadian grain handling system is simulated in this manner, moving from the individual farm up through to the country elevator level. My simulation results suggest testing strategies to alleviate misrepresentation (moral hazard) in this supply chain are more efficient for society when they are flexible and can be easily adjusted to react to situational change within the supply chain. While the idea of using software agents for modeling and understanding the dynamics of the supply chain under consideration is somewhat novel, I consider this exercise a first step to a broader modeling representation of modern agricultural supply chains. The agent-based simulation methodology developed in my dissertation can be extended to other economic systems or chains in order to examine risk management and control costs. These include food safety and quality assurance network systems as well as natural-resource management systems. Furthermore, to my knowledge there are no existing studies that develop and compare both analytic and agent-based simulation approaches for this type of complex economic situation. In the dissertation, I conduct explicit comparisons between the analytic and agent-based simulation solutions where applicable. While the two approaches generated somewhat different solutions, in many respects they led to similar overall conclusions regarding this particular agricultural policy issue.

The network externality function plays a very important role in the study of economic network industries. Moreover, the consumer group dynamic interactions coupled with network externality concept is going to play a dominant role in the network goods in the 21st century. The existing literature is stemmed on a choice of externality function with certain quantitative properties. The utility function coupled with the network externality function is used to investigate static properties of rational equilibrium. The aim of this work is to systematically initiate a development of quantitative effects of the concept of network externality and its influence on the characteristics of network market equilibrium. We introduce several basic concepts, notably, network externality process and network goods. Formulating a principle of network externality, we developed a mathematical dynamic model (1) for the network externality process. A closed form solution of the mathematical model was determined and analyzed (2). The presented qualitative and quantitative analysis provides a systematic and unified way of constructing the existing network externality function. The solution process is called "Generalized Network Externality Function (GNEF)". Moreover, our study of quantitative description, parametric representation of attributes and sensitivity analysis of network externality process provides a tool for planning, policy and performance for network goods (3). In the absence of desired data set, we presented an illustration to exhibit the significance of GNEF. We used two types of data sets on the US banking asset and deposit. Employing nonlinear regression methods and data sets, we developed statistical models for the US banking asset and deposit, and constructed two normalized the US banking deposit models (4). Finally, using the concept of theory of relative growth and GNEF (4), we developed two dynamic models for the network externality for the US banking asset with respect to the US banking deposit as a financial market share (5). Incorporating the GNEF (2) in the consumer utility function, a concept of market share adjustment function is introduced and utilized to develop dynamic models for existing rational and static expectation processes (6). In fact, the role and scope of dynamic models of market share adjustment process are extended to the well-known adaptive expectation and its extension process (7). Using a fixed point theorem and the method of upper and lower solutions of discrete time processes, the existence of equilibrium states of developed dynamic models of market share adjustment processes are established in a systematic way (8). Furthermore, the qualitative properties (stability and oscillatory) of equilibrium states are investigated in terms of model and speed of adjustment parameters. Moreover, the system parameter space is decomposed according to qualitative properties (stability, instability and oscillatory) and the type of expectation processes. Very recently, the idea of local network externality is utilized to characterize the rational equilibrium (under fulfilled expectation assumptions). From the study on two-scale network dynamic model of human mobility process an eco-socio-culture interactions, we note that heterogeneity in the network goods consumer community generates a local network externality. Furthermore, dynamic models of adaptive expectation processes (6,7) for network goods provide tool to extend the characterization of rational equilibrium study to static, current and lagged adaptive types equilibriums. Here, we treat the consumer decision to be a dynamic process. We formulate a dynamic structural representation of a consumer network structure, structure of utility function and decision rule under the influence of local network externality concept (9). For the consumer network structure, we generalize the one-dimensional Hotelling location line model to multi-dimensional location (10). This formulation generates a mathematical model for a consumer decision dynamic process (11). The byproduct of the dynamic model leads to an agent-based simulation model (12). The simulation model is employed to investigate different types of consumer decision dynamic market equilibriums. Moreover, prototype illustrations are given to exhibit the association between network attributes and its market equilibriums. We extend the work of two firms (duopoly) into multi-firms (oligopoly and monopolistic competition). This work shed light on the policies for manager to meet performance goal of their firm in network goods industry. In future, we propose to extend this work to incorporate random fluctuations, to remove restrictions and the local and global economic framework in the 21st century.

Chronic pain has no cure. It is a lifelong condition presenting a growing concern due to its high occurrence and effects on every facet of life. It cost about $635 billion each year in medical treatment and lost productivity (IOM, 2011). The management of chronic pain using prescription painkiller opioids has increased drastically in the last two decades, leading to a consequential increase in deaths from chronic opioid use. This Plan-Do-Study-Act quality improvement project investigates the problem of the prevalence of opioid prescription using agent-based computational modeling method. The simulation models the interaction of 50 patient-agents with pain self-management messages in an episode of 50 patient iterations (visits) for 10 simulated years. This interaction generates health benefit and risk outcomes represented by wellness data obtained when messages are processed. As the simulation runs, data are dynamically captured and visualized using wellness charts, time series plots, and benefit and risk regression plots. The result of the project provides evidence for research and practice on the process of achieving more impact of programs based on administering pain self-management education to patients with chronic non-cancer pain who are currently on opioid therapy and on the process of customizing interventions that might take advantage of the conditions of behavior change driven by pain self-management messages. The tools and the evidences in this project are highly recommended to nurse practitioners primary care providers involve with providing care to the vulnerable groups of patient with chronic non-cancer pain. These evidences might inform the formation of self-management interventions that might lead to a decline in opioid use and prescription and accelerate the acceptance of self-management practices.

The thesis focuses on the use of multiagent systems to model the rental housing market. At first the aim was to create the simulation, which would bring a new perspective on the development of the entire market. For this purpose I selected a relatively young methodology titled Agentology, which was subjected to the criticism of a model after finishing the model. That was a secondary principal objective of this thesis. The work is divided into two parts. In the first theoretical part the rental housing market is described and there are discussed the most important factors affecting its state. Simultaneously the chapter describes the most significant State interventions into the market, as we know them from the official housing policies. In the next stage the reader is made familiar with the basic principles of multi-agent modeling. In this chapter there is also an overview of selected methodologies of multiagent systems and one of them is selected and applied in further phases of this work. The second part refers to the multi-agent model. Using the Agentology methodology market model is assembled. The methodology accompanies all stages of model development from the task formulation, through conceptual and technological level to the final evaluation. This work strictly adheres to the methodology and all its recommendations. In the end, the result represents a model whose functionality has been verified by analyzing the output data. Finally the thesis deals with criticism of the Agentology methodology. This criticism is a result of experience gained from previous development. It concerns evaluation of concrete steps and also of methodology as a whole in terms of admittance, integrity and practicality.