Decision, Operations & Information Technologies Theses and Dissertations

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The Effect of Perceived Attitude Similarity on Performance Ratings
(1983) Feren, Dena Beatrice; Carroll, Stephen J.; Digital Repository at the University of Maryland; University of Maryland (College Park, Md)
This research consists of a laboratory study designed to test the notion that variance in performance ratings can be accounted for by the perception of the rater that the persons/he is evaluating is attitudinally similar or dissimilar to himself or herself. Student subjects were led to believe that a certain manager either agreed or disagreed with them on a number of attitudinal issues. Subjects then viewed a videotaped performance of the manager conducting a performance review with one of his problem subordinates. Subjects were asked to rate his performance using two different rating instruments -- a trait rating scale and a Behavior Observation Scale -- and to indicate personal liking for the manager. Extent of attitude similarity was manipulated on two levels with a control group . That is, some subjects were led to believe that the ratee was attitudinal l y similar to self, others that the ratee was dissimilar to self, and a third group received no information about the ratee's attitudes. The ratee's performance was manipulated on three levels. Some subjects viewed only a high performin1; manager, others viewed a moderate performer, and a third group viewed a lo w performing manager. Three different vignettes were prepared to represent the three levels of performance. Finally, a hard-performance-data condition was included to test the robustness of the attitude similarity effect. Some subjects received hard performance data, in the form of bar graphs, that was consistent with the level of performance portrayed in their videotaped vignette (i.e., those viewing the low performer received hard data indicative of low performance). It was hypothesized that perceived attitude similarity would have its greatest effect when performance was moderate, and when subjects did not receive hard performance data. The results did not support these predictions. The effect of perceived attitude similarity on performance ratings was not significant under any of the experimental conditions. Perceived similarity had a small, but significant effect on attraction; however, level of performance accounted for a far greater proportion of variance in attraction measures than perceived similarity. It was concluded that the rating task in this experiment failed to create the conditions under which perceived similarity would be most likely to exert an influence on ratings. Specifically, the rating task was not sufficiently ambiguous for student raters.
THREE ESSAYS ON MORTGAGE BACKED SECURITIES: HEDGING INTEREST RATE AND CREDIT RISKS
(2003-12-05) Chen, Jian; Fu, Michael C.; Decision and Information Technologies
This dissertation includes three essays on hedging the interest rate and credit risks of Mortgage-Backed Securities (MBS). Essay one addresses the problem of how to efficiently estimate interest rate sensitivity parameters of MBS. To do this in Monte Carlo simulation, we derive perturbation analysis (PA) gradient estimators in a general setting. Then we apply the Hull-White interest rate model and a common prepayment model to derive the corresponding specific PA estimators, assuming the shock of interest rate term structure takes the form of a trigonometric polynomial series. Numerical experiments comparing finite difference (FD) estimators with our PA estimators indicate that the PA estimators can provide better accuracy than FD estimators, while using much lower computational cost. Using the estimators, we analyze the impact of term structure shifts on various mortgage products. Based these analysis, we propose a new product to mitigate interest rate risk. Essay two addresses the problem of how to measure interest rate yield curve shift more realistically, and how to use these risk measures to hedge the interest rate risk of MBS. We use a Principal Components Analysis (PCA) approach to analyze historical interest rate data, and acquire the volatility factors we need in Heath-Jarrow-Morton interest rate model simulation. Then we propose a hedging algorithm to hedge MBS, based on PA gradient estimators derived upon these PCA factors. Our results show that the new hedging method can achieve much better hedging efficiency than traditional duration and convexity hedging. Essay three addresses the application a new regression method on credit spread data. Previous research has shown that variables in traditional structural model have limited explanatory power in credit spread regression. We argue that this is partially due to the non-constancy of the credit spread gradients to state variables. We use a Random Coefficient Regression (RCR) model to accommodate this problem. The explanatory power increases dramatically with the new RCR model, without adding new independent variables. This is the first work to address the dependence between credit spread sensitivities and state variables of structural in a systematic way. Also our estimates are consistent with prediction from Merton’s structural model.
Design of Online Auction System with Alternative Currencies
(2004-05-05) Deshpande, Vainateya Suresh; Lucas, Henry; Decision and Information Technologies
The University of Maryland has one of the most popular Basketball programs in the region. About 35,000 students seek 4,000 free student tickets allocated for every home game. An auction-based system provides a procedure to achieve and equitable and fair distribution of a high-demand resource. In an auction-based system, goods being sold end up with the person who values them the most. This is a very desirable scenario for a ticket distribution system that aims at maximizing attendance for home games. People who bid high have high values for the tickets and are more likely to attend a game than someone who receives a ticket through a random draw. The thesis lays out the framework for an auction based system to distribute home game tickets.
EVALUATION OF SETUP ECONOMIES IN CELLULAR MANUFACTURING
(2004-08-04) Kramer, Steven; Assad, Arjang A; Decision and Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
This dissertation addresses two research questions relating to the role of setups in discrete parts manufacturing. The first research topic uses a carefully designed simulation study to investigate the role of setup economies in the factory-wide conversion of functional layouts (job shops) to cellular manufacturing. The model-based literature shows a wide dispersion in the relative performance of cellular manufacturing systems as compared to the original job-shop configurations, even when the key performance measure is flow time and the assessment tool used is simulation. Using a standardized framework for comparison, we show how this dispersion can be reduced and consistent results can be obtained as to when the conversion of the job shop is advantageous. The proposed framework standardizes the parameters and operational rules to permit meaningful comparison across different manufacturing environments, while retaining differences in part mix and demand characteristics. We apply this framework to a test bed of six problems extracted from the literature and use the results to assess the effect of two key factors: setup reduction and the overall shop load (demand placed on the available capacity). We also show that the use of transfer batches constitutes an independent improvement lever for reducing flow time across all data sets. Finally, we utilize the same simulation study framework to investigate the benefits of partial transformation, where only a portion of the job shop is converted to cells to work alongside a remainder shop. The second research question examines the role of dispatching rules in the reduction of setups. We use queueing models to investigate the extent of setup reduction analytically. We single out the Alternating Priority (AP) rule since it is designed to minimize the incidence of setups for a two-class system. We investigate the extent of setup reductions by comparing AP with the First-Come-First-Served (FCFS) rule. New results are obtained analytically for the case of zero setup times and extended to the case of non-zero setup time through computational studies.
IMPACT ASSESSMENT OF DYNAMIC SLOT EXCHANGE IN AIR TRAFFIC MANAGEMENT
(2004-12-09) Sankararaman, Ravi; Ball, Michael; Decision and Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Since the inception of Collaborative Decision Making (CDM), the Federal Aviation Administration and the airlines have been striving to improve utilization of critical resources such as arrival slots and reduce flight delays during Ground Delay Programs. Two of the mechanisms that have been implemented for increasing utilization at resource-constrained airports are those of Compression and Slot Credit Substitution (SCS). SCS is a conditional, dynamic means of inter-airline slot exchange while compression can be considered a static means of achieving slot utilization. This thesis will be an attempt to develop theoretical models to understand the performance of compression to slot exchange requests from airlines. This thesis will also address the trends in these slot exchange procedures, the benefits in terms of delay savings realized by the airlines, and avenues for future applications for improving efficiency of the National Airspace System.
DATA VISUALIZATION OF ASYMMETRIC DATA USING SAMMON MAPPING AND APPLICATIONS OF SELF-ORGANIZING MAPS
(2005-03-17) Li, Haiyan; Golden, Bruce L.; Decision and Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Data visualization can be used to detect hidden structures and patterns in data sets that are found in data mining applications. However, although efficient data visualization algorithms to handle data sets with asymmetric proximities have been proposed, we develop an improved algorithm in this dissertation. In the first part of the proposal, we develop a modified Sammon mapping approach that uses the upper triangular part and the lower triangular part of an asymmetric distance matrix simultaneously. Our proposed approach is applied to two asymmetric data sets: an American college selection data set, and a Canadian college selection data set which contains rank information. When compared to other approaches that are used in practice, our modified approach generates visual maps that have smaller distance errors and provide more reasonable representations of the data sets. In data visualization, self-organizing maps (SOM) have been used to cluster points. In the second part of the proposal, we assess the performance of several software implementations of SOM-based methods. Viscovery SOMine is found to be helpful in determining the number of clusters and recovering the cluster structure of data sets. A genocide and politicide data set is analyzed using Viscovery SOMine, followed by another analysis on the public and private college data sets with the goal to find out schools with best values.
STOCHASTIC OPTIMIZATION: ALGORITHMS AND CONVERGENCE
(2005-03-23) Xiong, Xiaoping; Fu, Michael C.; Decision and Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Stochastic approximation is one of the oldest approaches for solving stochastic optimization problems. In the first part of the dissertation, we study the convergence and asymptotic normality of a generalized form of stochastic approximation algorithm with deterministic perturbation sequences. Both one-simulation and two-simulation methods are considered. Assuming a special structure on the deterministic sequence, we establish sufficient conditions on the noise sequence for a.s. convergence of the algorithm and asymptotic normality. Finally we propose ideas for further research in analysis and design of the deterministic perturbation sequences. In the second part of the dissertation, we consider the application of stochastic optimization problems to American option pricing, a challenging task particularly for high-dimensional underlying securities. For options where there are a finite number of exercise dates, we present a weighted stochastic mesh method that only requires some easy-to-verify assumptions and a method to simulate the behavior of underlying securities. The algorithm provides point estimates and confidence intervals for both price and value-at-risk. The estimators converge to the true values as the computational effort increases. In the third part, we deal with an optimization problem in the field of ranking and selection. We generalize the discussion in the literature to a non-Gaussian correlated distribution setting. We propose a procedure to locate an approximate solution, which can be shown to converge to the true solution asymptotically. The convergence rate is also provided for the Gaussian setting.
INTEGRATED PRODUCTION-DISTRIBUTION SCHEDULING IN SUPPLY CHAINS
(2005-05-09) Pundoor, Guruprasad; Chen, Zhi-Long; Decision and Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
We consider scheduling issues in different configurations of supply chains. The primary focus is to integrate production and distribution activities in the supply chain in order to optimize the tradeoff between total cost and service performance. The cost may be based on actual expenses such as the expense incurred during the distribution phase, and service performance can be expressed in terms of time based performance measures such as completion times and tardiness. Our goal is to achieve the following objectives: (i) To propose various integrated production-distribution scheduling models that closely mirror practical supply chain operations in some environments. (ii) To develop computationally effective optimization based solution algorithms to solve these models. (iii) To provide managerial insights into the potential benefits of coordination between production and distribution operations in a supply chain. We analyze four different configurations of supply chains. In the first model, we consider a setup with multiple manufacturing plants owned by the same firm. The manufacturer receives a set of distinct orders from the retailers before a selling season, and needs to determine the order assignment, production schedule, and distribution schedule so as to optimize a certain performance measure of the supply chain. The second model deals with a supply chain consisting of one supplier and one or more customers, where the customers set due dates on the orders they place. The supplier has to come up with an integrated production-distribution schedule that optimizes the tradeoff between maximum tardiness and total distribution cost. In the third model, we study an integrated production and distribution scheduling model in a two-stage supply chain consisting of one or more suppliers, a warehouse, and a customer. The objective is to find jointly a cyclic production schedule at each supplier, a cyclic delivery schedule from each supplier to the warehouse, and a cyclic delivery schedule from the warehouse to the customer so that the customer demand for each product is satisfied fully at minimum total production, inventory and distribution cost. In the fourth model, we consider a system with one supplier and one customer with a set of orders placed at the beginning of the planning horizon. Unlike the earlier models, here each order can have a different size. Since the shipping capacity per batch is finite, we have to solve an integrated production-distribution scheduling and order-packing problem. Our objective is to minimize the number of delivery batches subject to certain service performance measures such as the average lead time or compliance with deadlines for the orders.
The Value of IT-Enabled Retailer Learning: Can Personalized Product Recommendations (PPRs) Improve Customer Store Loyalty in Electronic Markets?
(2005-08-24) Zhang, Tongxiao; Agarwal, Ritu; Lucas, Hank; Decision and Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Personalization is a strategy that has been widely adopted by online retailers to enhance their customers' shopping experience, with the ultimate goal of building a strong and enduring customer relationship. Personalized product recommendations (PPRs) are product recommendations adapted to individual customers' preferences and taste. So far, very few empirical studies have ever investigated the impact of PPRs from a consumer behavior perspective. Whether PPRs generate any value for consumers and ultimately, retailers, is still an open question. To fill this gap in the literature, in this study, drawing upon the household production function model in the consumer economics literature, I develop a theoretical framework that explains the mechanism through which PPRs influence customer store loyalty in electronic markets. Online shopping can be viewed as a household production process and customer store loyalty is driven by shopping efficiency. Building upon retailer learning, higher quality PPRs can increase consumers' online product brokering efficiency, which in turn increases their repurchase intention. A two-phase lab experiment was conducted among 253 undergraduate students in the business school. The subjects completed a simulated purchase at Amazon.com and the quality of PPRs they received was manipulated. Empirical analyses indicate that higher quality PPRs improve consumers' online product brokering quality, which in turn increases their repurchase intention. Consumers make higher quality purchase decisions and experience more fun during the online product brokering process. A surprising finding is that higher quality PPRs increase consumer online product brokering cost. Consumers spend more time on decision making and have more difficulty reaching a purchase decision. Implications, limitations, and contributions of this study are discussed and areas for future research are suggested.
IT Design for Sustaining Virtual Communities: an Identity-based Approach
(2005-08-31) Ma, Meng; Agarwal, Ritu; Lucas, Henry; Decision and Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
A variety of information technology (IT) artifacts, such as those supporting reputation management and digital archives of past interactions, are commonly deployed to support virtual communities. Despite the ubiquity of these artifacts, research on the impact of various IT-based features on virtual community communication is still limited. Without such research, the mechanisms through which information technologies influence community success are not well understood, limiting the design of community infrastructures that can enhance interaction in the community and minimize dysfunction. This dissertation proposes that identity management is a critical imperative in virtual communities and concerns related to communication of identity serve to shape an individual's interactions and perceptions in the community. Sensitivity to this perspective can help in drawing design guidelines for the IT infrastructure supporting the community. Drawing upon the social psychology literature, I propose an identity-based view to understand how the use of IT-based features in virtual communities can improve community sustainability. Specifically, identity consonance, defined as the perceived fit between a focal person's belief of his or her identity and the recognition and verification of this identity by other community members, is proposed as a core construct that mediates the relationship between the use of community IT artifacts and member satisfaction and knowledge contribution. To test the theoretical model, I surveyed two online communities: Quitnet.com and myIS.com. The former is an online community for people who wish to quit smoking, and the latter is a site for Lexus IS300 sport sedan enthusiasts. The results from surveys support the positive effects of community IT artifacts on identity consonance. The empirical study also finds that a high level of identity consonance is linked to member satisfaction and knowledge contribution. This dissertation offers a fresh perspective on virtual communities and suggests important implications for the design of the supporting IT infrastructure.
Strategic IT Partnerships in Transformational Outsourcing as a Distinctive Source of IT Value: A Social Capital Perspective
(2005-09-07) Ye, Fei; Agarwal, Ritu; Decision and Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Firms increasingly acquire needed information technology (IT) products and services from external sources through the formation of partnerships. In spite of the ubiquity of IT outsourcing practice in today's organizations however, theoretical understanding of IT partnerships in outsourcing is limited. Extant research has largely focused on the economic or strategic aspects of IT outsourcing, using transaction cost economics (TCE) and the resource-based view (RBV) as dominant theoretical frameworks. This dissertation adopts a social perspective to examine the IT outsourcing phenomenon. It focuses on IT partnerships in transformational outsourcing relationships that are interorganizational engagements formed to rapidly and substantially improve performance at the organizational level. By synthesizing the knowledge based view of the firm with the concept of social capital, I attempt to explain how IT outsourcing relationships generate value for organizations. I argue that IT outsourcing partnerships constitute a form of social capital for the firm that chooses to outsource, that facilitates knowledge exchange and transfer. The increased knowledge stock as a result of knowledge exchange and transfer, in turn, forms the foundation for IT value, which is manifested as success in business operations and IT-enabled innovation. To empirically test the theoretical model, I surveyed 151 client firms and 79 outsourcing service providers in China. Results suggest that both social capital and knowledge acquisition are crucial to the success of IT outsourcing. Evidence from the survey responses also indicates that different aspects of social capital play different roles in the process of IT value creation. Specifically, the structural dimension (partner resource endowment) and the cognitive dimension of social capital (shared vision and shared cognition) have a strong impact on knowledge acquisition; whereas the relational dimensions of social capital (social interaction and trust) has strong direct effects on successful outcomes of IT outsourcing. This study presented evidence that helps further our understanding of the IT outsourcing phenomenon through an alternative theoretical lens, and emphasizes the value other than immediate cost-related benefits that organizations may garner through IT outsourcing partnerships.
Effect of Transaction Cost and Coordination Mechanisms on the Length of the Supply Chain
(2005-12-05) Iyengar, Deepak; Bailey, Joseph P.; Evers, Philip T.; Decision and Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
A drastic reduction in the cost of transmitting information has tremendously increased the °ow and availability of information. Greater availability of information increases the ¯rm's ability to manage its supply chain and, therefore, increases its operational performance. However, current literature is ambiguous about whether increased information °ows leads to either a reduction or increase in transaction cost, which enable supply chains to migrate towards more market-based transactions or hierarchal-based transactions. This research empirically demonstrates that the governance structure of the supply chains changes towards market-based transactions due to a lowering of transaction costs after 1987. Much of the results is based on the theory of Transaction Cost Economics (TCE) and the role of asset speci¯city, uncertainty, and frequency in determin- ing whether or not industries are moving towards markets or hierarchies. Unlike previous supply chain management literature that focuses on relatively short supply chains consisting of two or three supply chain members, Input-Output tables allow for analysis of supply chains with many more members. This paper uses the 1982, 1987, 1992, and 1997 U.S. Benchmark Input-Output tables published by the Bureau of Economic Analysis to analyze supply chains. In so doing, this dissertation not only provides insight into how supply chain structures are changing but also o®ers a sample methodology for other researchers interested in using Input-Output analysis for further supply chain management research. The second part of the dissertation focuses on looking at the e®ect of di®erent coordination mechanisms on supply chain length and supply chain performance using simulation. Three di®erent heuristics that model ordering policies are used to simulate coordination mechanisms. E±ciency is measured on the basis of minimized total net stock for each heuristic used. The results are checked for robustness by using four di®erent demand distributions. The results indicate that if a supply chain has minimized its net stock, then the heuristic used by various echelons in the supply chain need not be harmonized. Also, disintermediation helps in improving the performance of the supply chain.
Optimization of Contemporary Telecommunications Networks: Generalized Spanning Trees and WDM Optical Networks
(2005-12-05) Stanojevic, Daliborka; Raghavan, Subramanian; Decision and Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
We present a study of two NP-hard telecommunications network design problems - the prize-collecting generalized minimum spanning tree problem (PCGMST) and the design of optical networks with wavelength division multiplexing. The first problem, the PCGMST problem, involves the design of regional backbone networks, where a set of local area networks (LANs) need to be connected by a minimum cost tree network using exactly one gateway site from each LAN. We present several polynomial time heuristics for the PCGMST problem and show that these algorithms, at best, provide only modest quality solutions. We also present two metaheuristics - a local search procedure and a genetic algorithm, and show that these procedures provide compelling high-quality results on a large set of test problems. Our study of the PCGMST problem is concluded by a presentation of two exact solution procedures that can be used to find optimal solutions in networks of moderate size. The second problem studied in this dissertation is a more complex network design problem that involves optical networks with wavelength division multiplexing (WDM). These networks provide an abundance of transmission bandwidth, but require the use of expensive equipment, which, in turn, mandates careful use of the resources available for their design. The novel aspect of WDM optical networks is that they require simultaneous design of two network layers. The first layer is the virtual topology that requires routing of logical paths over the physical layer of optical fibers. The second layer involves routing and grooming of traffic requests over the logical paths established in the virtual topology. This problem has been extensively studied in the last 10 years, but due to its notoriously hard nature, only few exact solution procedures for relaxed versions of this problem were developed so far. We propose one exact and two approximate branch-and-price algorithms for two versions of the WDM optical network design problem and present results of the computational study involving two different design objectives. Finally, we propose two classes of valid inequalities for our branch-and-price algorithms, and discuss applicability of our algorithms to different versions of the WDM optical network design problem.
Essays on Agility in Software Development Teams: Process and Governance Perspectives
(2006-04-19) Maruping, Likoebe Mohau; Agarwal, Ritu; Venkatesh, Viswanath; Decision and Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Software project teams are often faced with the potential for changing requirements during software development. Such changes present a significant challenge to software project teams often resulting in cost overruns, missed deadlines, and faulty code. While the phenomenon of requirements changes by itself is not new, the frequency with which such changes occur has increased in recent years. Software project teams continue to be challenged by the uncertainty caused by the potential for such changes. Flexibility has been identified as a desirable characteristic of teams in this type of environment. This dissertation is made up of two essays that examine the processes and governance mechanisms that can potentially enable software project teams to achieve greater flexibility. The first essay provides a team process-oriented view of the problem. Specifically, agile programming practices and boundary spanning activities are argued to enhance software project team effectiveness by receiving customer feedback and incorporating requirements changes on an on-going basis. A longitudinal field study of 56 software development teams provides support for these arguments. The second essay adopts a team governance lens. Specifically, formal and informal control modes are posited to influence software project team effectiveness. Control mechanisms that promote team autonomy and flexibility are argued to positively influence software project team effectiveness. Further, team leader behaviors are also expected to play a critical role in facilitating software project team effectiveness. These arguments are tested and largely supported. Together, the two essays shed light on how software project teams can be designed to have greater flexibility--an important stepping stone for managing software development in the face of requirements uncertainty.
Coordinating Demand Fulfillment With Supply Across A Dynamic Supply Chain
(2006-04-25) Chen, Maomao; Ball, Michael; Decision and Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Today, technology enables companies to extend their reach in managing the supply chain and operating it in a coordinated fashion from raw materials to end consumers. Order promising and order fulfillment have become key supply chain capabilities which help companies win repeat business by promising orders competitively and reliably. In this dissertation, we study two issues related to moving a company from an Available to Promise (ATP) philosophy to a Profitable to Promise (PTP) philosophy: pseudo order promising and coordinating demand fulfillment with supply. To address the first issue, a single time period analytical ATP model for n confirmed customer orders and m pseudo orders is presented by considering both material constraints and production capacity constraints. At the outset, some analytical properties of the optimal policies are derived and then a particular customer promising scheme that depends on the ratio between customer service level and profit changes is presented. To tackle the second issue, we create a mathematical programming model and explore two cases: a deterministic demand curve or stochastic demand. A simple, yet generic optimal solution structure is derived and a series of numerical studies and sensitivity analyses are carried out to investigate the impact of different factors on profit and fulfilled demand quantity. Further, the firm's optimal response to a one-time-period discount offered by the supplier of a key component is studied. Unlike most models of this type in the literature, which define variables in terms of single arc flows, we employ path variables to directly identify and manipulate profitable and non-profitable products. Numerical experiments based on Toshiba's global notebook supply chain are conducted. In addition, we present an analytical model to explore balanced supply. Implementation of these policies can reduce response time and improve demand fulfillment; further, the structure of the policies and our related analysis can give managers broad insight into this general decision-making environment.
Satellite Network, Design, Optimization, and Management
(2006-08-07) Gamvros, Ioannis; Raghavan, Subramanian; Decision and Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
We introduce several network design and planning problems that arise in the context of commercial satellite networks. At the heart of most of these problems we deal with a traffic routing problem over an extended planning horizon. In satellite networks route changes are associated with significant monetary penalties that are usually in the form of discounts (up to 40%) offered by the satellite provider to the customer that is affected. The notion of these rerouting penalties requires the network planners to consider management problems over multiple time periods and introduces novel challenges that have not been considered previously in the literature. Specifically, we introduce a multiperiod traffic routing problem and a multiperiod network design problem that incorporate rerouting penalties. For both of these problems we present novel path-based reformulations and develop branch-and-price-and-cut approaches to solve them. The pricing problems in both cases present new challenges and we develop special purpose approaches that can deal with them. We also show how these results can be extended to deal with traffic routing and network design decisions in other settings with much more general rerouting penalties. Our computational work demonstrates the benefits of using the branch-and-price-and-cut procedure developed that can deal with the multiperiod nature of the problem as opposed to straightforward, myopic period-by-period optimization approaches. In order to deal with cases in which future demand is not known with certainty we present the stochastic version of the multiperiod traffic routing problem and formulate it as a stochastic multistage recourse problem with integer variables at all stages. We demonstrate how an appropriate path-based reformulation and an associated branch-and-price-and-cut approach can solve this problem and other more general multistage stochastic integer multicommodity flow problems. Finally, we motivate the notion of reload costs that refer to variable (i.e., per unit of flow) costs for the usage of pairs of edges, as opposed to single edges. We highlight the practical and theoretical significance of these cost structures and present two extended graphs that allow us to easily capture these costs and generate strong formulations.
Weight Annealing Heuristics for Solving Bin Packing and other Combinatorial Optimization Problems: Concepts, Algorithms and Computational Results
(2006-10-23) Loh, Kok-Hua; Golden, Bruce L.; Decision and Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
The application of weight annealing to combinatorial optimization problems is relatively new, compared to applications of well-known optimization techniques such as simulated annealing and tabu search. The weight annealing approach seeks to expand a neighborhood search by creating distortions in different parts of the search space. Distortion is controlled through weight assignment based on insights gained from one iteration of the search procedure to the next with a view towards focusing computational efforts on the poorly solved regions of the search space. The search for the global optimum should be accelerated and the solution quality should be improved with weight annealing. In this dissertation, we present key ideas behind weight annealing and develop algorithms that solve combinatorial optimization problems. Our weight annealing-based heuristics solve the one-dimensional bin packing problem and the two-dimensional bin packing problem with and without guillotine cutting and item orientation constraints. We also solve the maximum cardinality bin packing problem and the multidimensional multiple knapsack problem with our heuristics.
Electronic Mediation, Transformation, and Business Value: Three Essays in the Retail Auto Industry
(2006-10-25) Kuruzovich, Jason Nicholas; Agarwal, Ritu; Decision and Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
This dissertation seeks to answer the following research questions: (1) what properties enable some organizations to generate more value from information technology (IT) than others? and (2) through what mechanisms do organizations generate value through IT? It examines the role of technology in value creation through three essays using three different aspects of organizational performance. Chapter 1: Responding to Technology-Enabled Organizational Transformation: The Role of Strategic Change Orientation Essay one examines the role of strategic change orientation and three change enablers--IT capabilities, climate for IT use, and mindfulness of IT adoption--in influencing business process performance during a period of IT-enabled transformation. The data source for this essay is a survey of auto retailers facilitated by a leading online infomediary. Chapter 2: Profiting From the Internet Channel: The Complementarity of Electronic Commerce Capabilities and Business Process Change Essay two accesses the joint role of electronic commerce capabilities and business process change in a model that examines the value firms derive from the Internet channel. The data source for this essay is a survey of auto retailers conducted by a leading market research firm. Chapter 3: Understanding Retailer Use of Online Auction Channels: Strategies In Repeated Search Processes Essay three examines sellers' use of the online auction market and the resulting value obtained for a given product through the theoretical lens of search theory. We model sellers' repeated listing of unsold products and adjustment of reserve price as a process of searching for high valuation customers. The data source for this essay is transactional data from a leading online auction site specializing in automobiles.
Air Transportation System Performance: Estimation and Comparative Analysis of Departure Delays
(2006-11-22) Tu, Yufeng; Ball, Michael; Jank, Wolfgang; Decision and Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
The U.S. National Airspace System (NAS) is inherently highly stochastic. Yet, many existing decision support tools for air traffic flow management take a deterministic approach to problem solving. In this study, we focus on the flight departure delays because such delays serve as inputs to many air traffic congestion prediction systems. Modeling the randomness of the delays will provide a more accurate picture of the airspace traffic situation, improve the prediction of the airspace congestion and advance the level of decision making in aviation systems. We first develop a model to identify the seasonal trend and daily propagation pattern for flight delays, in which we employ nonparametric methods for modeling the trends and mixture distribution for the residual errors estimation. This model demonstrates reasonable goodness of fit, robustness to the choice of the model parameters, and good predictive capabilities. We emphasize that a major objective is to produce not just point estimates but estimates of the entire distribution since the congestion estimation models envisioned require delay distribution functions, e.g. to produce probability of certain delays or expected traffic levels for arbitrary time intervals. Local optima problems are typically associated with mixture distribution estimation. To overcome such problems, we develop a global optimization version of the Expectation Maximization algorithm, borrowing ideas from Genetic Algorithms. This optimization algorithm shows the ability to escape from local traps and robustness to the choice of parameters. Finally, we propose models to estimate the so called "wheels-off delays" for flights within the NAS while incorporating a dynamic update capability. Approaches are evaluated based on their ability to reduce variance and their predictive accuracy. We first show that how a raw histogram can be misleading when a trend is present and how variance can be reduced by trend estimation. Then, various techniques are explored for variance reduction. The multiple seasonal trends method shows great capability for variance reduction while staying parsimonious in parameters. The downstream ripple effect method further enhances the variance reduction capability and makes real-time prediction practical and accurate. A rolling horizon updating procedure is described to accommodate the arrival of new information. Finally different models are compared with the current model adopted by the ETMS systems and the predictive capabilities of all models are shown.
Mindful Use as a Link Between Social Capital and Organizational Learning: An Empirical Test of the Antecedents and Consequences of Two New Constructs
(2006-11-28) Adams, Heather Lynn; Lucas, Hank; Decision and Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
The motivation for this research is that information systems are not often used to their full potential - individuals often fail to use valuable features of systems not allowing firms to maximize their return from investments in these technologies. Additionally, there have been recent calls for new conceptualizations of system use and for research that examines post-adoption use. Therefore, the current research develops two new conceptualizations of system use: full appropriation and heedful use. These new concepts can help address under-utilization issues and fill gaps in the current literature. Full appropriation is fully exploiting applicable features of a system and heedful use is interacting with a system in a way that considers the needs of others within an organization. These conceptualizations are developed from psychological theories on mindfulness which have not been used to study system use. It is expected that a mindful approach to technology can lead to many positive benefits in the workplace. The first step in the current research was to develop and validate measures for these two new forms of use. Then the predictors of full appropriation and heedful use were examined with a social capital lens. The final step of this research was to examine the influence that these broader forms of use have on organizational learning since it has been suggested that organizational learning is the missing link between IT and firm performance. Data from 591 subjects from two separate organizations provided evidence of construct validity of the two newly developed scales and provided support for the overall model indicating a relationship between social capital and mindful use and a relationship between mindful use and organizational learning.

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