The goal of this dissertation is to investigate the enabling role that agent based simulation plays in business and policy. The aforementioned issue has been addressed in this dissertation through three distinct, but related essays. The first essay is a literature review of different research applications of agent based simulation in various business disciplines, such as finance, economics, information systems, management, marketing and accounting. Various agent based simulation tools to develop computational models are discussed. The second essay uses an agent-based simulation approach to study important properties of the widely used most popular news recommender systems (NRS). This essay highlights the major limitations of most popular NRS in terms of: (i) susceptibility towards manipulation and (ii) unduly penalizing the article which may have "just" missed making the cutoff in most popular list. A probabilistic variant of recommendation has been introduced as an alternative to most popular list. Classical results from urn models are used to derive theoretical results for special cases, and to study specific properties of the probabilistic recommender. In addition to simulations, various statistical methodologies are used, such as regression based methodologies as part of a broader decision analysis tool. The third essay views firms as agents in building regression based empirical models to investigate the impact of outsourcing on firms. Using an economy wide panel data of outsourcing expenses of firms, the third essay first investigates the value addition by the IT backgrounds of project owners in managing IT related projects. Then it investigates the impact of peer-pressure on a firm's outsourcing behavior.

This thesis provides a general methodology for classifying and describing many combinatoric problems, systematising and finding theoretical expressions for quantities of interest, and investigating their feasible numerical evaluation. Unifying notation and definitions are provided. Our knowledge of random allocations is also extended. This is achieved by investigating new processes, generalising known processes, and by providing a formal structure and innovative techniques for analysing them. The random allocation models described in this thesis can be classified as occupancy urn models, in which we have a sequence of urns and throw balls into them, and investigate static, waiting-time and dynamic processes. Various structures are placed on the relationship(s) between cells, balls, and the selection of items being distributed, including varieties, batch arrivals, taboo sets and blocking sets. Static, waiting-time and dynamic processes are investigated. Both without-replacement and with-replacement sampling types are considered. Emphasis is placed on the distributions of waiting-times for one or more events to occur measured from the time a particular event occurs; this begins as an abstraction and generalisation of a model of departures of cars parked in lanes. One of several additional determinations is the platoon size distribution. Models are analysed using combinatorial analysis and Markov Chains. Global attributes are measured, including maximum waits, maximum room required, moments and the clustering of completions. Various conversion formulae have been devised to reduce calculation times by several orders of magnitude. New and extended applications include Queueing in Lanes, Cake Displays, Coupon Collector's Problem, Sock-Sorting, Matching Dependent Sets (including Genetic Code Attribute Matching and the game SET), the Zig-Zag Problem, Testing for Randomness (including the Cake Display Test, which is a without-replacement test similar to the standard Empty Cell test), Waiting for Luggage at an Airport, Breakdowns in a Network, Learning Theory and Estimating the Number of Skeletons at an Archaeological Dig. Fundamental, reduction and covering theorems provide ways to reduce the number of calculations required. New combinatorial identities are discovered and a well-known one is proved in a combinatorial way for the first time. Some known results are derived from simple cases of the general models. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1309598 / Thesis (Ph.D.) -- University of Adelaide, School of Mathematical Sciences, 2007

This thesis provides a general methodology for classifying and describing many combinatoric problems, systematising and finding theoretical expressions for quantities of interest, and investigating their feasible numerical evaluation. Unifying notation and definitions are provided. Our knowledge of random allocations is also extended. This is achieved by investigating new processes, generalising known processes, and by providing a formal structure and innovative techniques for analysing them. The random allocation models described in this thesis can be classified as occupancy urn models, in which we have a sequence of urns and throw balls into them, and investigate static, waiting-time and dynamic processes. Various structures are placed on the relationship(s) between cells, balls, and the selection of items being distributed, including varieties, batch arrivals, taboo sets and blocking sets. Static, waiting-time and dynamic processes are investigated. Both without-replacement and with-replacement sampling types are considered. Emphasis is placed on the distributions of waiting-times for one or more events to occur measured from the time a particular event occurs; this begins as an abstraction and generalisation of a model of departures of cars parked in lanes. One of several additional determinations is the platoon size distribution. Models are analysed using combinatorial analysis and Markov Chains. Global attributes are measured, including maximum waits, maximum room required, moments and the clustering of completions. Various conversion formulae have been devised to reduce calculation times by several orders of magnitude. New and extended applications include Queueing in Lanes, Cake Displays, Coupon Collector's Problem, Sock-Sorting, Matching Dependent Sets (including Genetic Code Attribute Matching and the game SET), the Zig-Zag Problem, Testing for Randomness (including the Cake Display Test, which is a without-replacement test similar to the standard Empty Cell test), Waiting for Luggage at an Airport, Breakdowns in a Network, Learning Theory and Estimating the Number of Skeletons at an Archaeological Dig. Fundamental, reduction and covering theorems provide ways to reduce the number of calculations required. New combinatorial identities are discovered and a well-known one is proved in a combinatorial way for the first time. Some known results are derived from simple cases of the general models. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1309598 / Thesis (Ph.D.) -- University of Adelaide, School of Mathematical Sciences, 2007