Decision, Operations & Information Technologies Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2761
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Item ROBUST REVENUE MANAGEMENT WITH LIMITED INFORMATION : THEORY AND EXPERIMENTS(2009) Lan, Yingjie; Ball, Michael O; Karaesmen, Itir A; Business and Management: Decision & Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Revenue management (RM) problems with full probabilistic information are well studied. However, as RM practice spreads to new businesses and industries, there are more and more applications where no or only limited information is available. In that respect, it is highly desirable to develop models and methods that rely on less information, and make fewer assumptions about the underlying uncertainty. On the other hand, a decision maker may not only lack data and accurate forecasting in a new application, but he may have objectives (e.g. guarantees on worst-case profits) other than maximizing the average performance of a system. This dissertation focuses on the multi-fare single resource (leg) RM problem with limited information. We only use lower and upper bounds (i.e. a parameter range), instead of any particular probability distribution or random process to characterize an uncertain parameter. We build models that guarantee a certain performance level under all possible realizations within the given bounds. Our methods are based on the regret criterion, where a decision maker compares his performance to a perfect hindsight (offline) performance. We use competitive analysis of online algorithms to derive optimal static booking control policies that either (i) maximize the competitive ratio (equivalent to minimizing the maximum regret) or (ii) minimize the maximum absolute regret. Under either criterion, we obtain closed-form solutions and investigate the properties of optimal policies. We first investigate the basic multi-fare model for booking control, assuming advance reservations are not cancelled and do not become no-shows. The uncertainty in this problem is in the demand for each fare class. We use information on lower and upper bounds of demand for each fare class. We determine optimal static booking policies whose booking limits remain constant throughout the whole booking horizon. We also show how dynamic policies, by adjusting the booking limits at any time based on the bookings already on hand, can be obtained. Then, we integrate overbooking decisions to the basic model. We consider two different models for overbooking. The first one uses limited information on no-shows; again the information being the lower and upper bound on the no-show rate. This is appropriate for situations where there is not enough historical data, e.g. in a new business. The second model differs from the first by assuming the no-show process can be fully characterized with a probabilistic model. If a decision-maker has uncensored historical data, which is often the case in reality, he/she can accurately estimate the probability distribution of no-shows. The overbooking and booking control decisions are made simultaneously in both extended models. We derive static overbooking and booking limits policies in either case. Extensive computational experiments show that the proposed methods that use limited information are very effective and provide consistent and robust results. We also show that the policies produced by our models can be used in combination with traditional ones to enhance the system performance.Item Impact of Leadership on Continued Participation in Online Groups(2008-11-20) Johnson, Steven L.; Faraj, Samer; Business and Management: Decision & Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Online groups formed by volunteer members are increasingly recognized as sources of innovative ideas, as producers of information goods, and as a critical component for successful product marketing. Compared to formal organizations, online groups appear as anarchic collections of individuals largely devoid of formal authority. Yet online groups develop strong group norms, successfully generate information goods, and satisfy member needs--outcomes that seem impossible without some form of leadership by influential members. Research on open-membership voluntary online groups has consistently found that contribution to online groups is dominated by a small percentage of participants. The goal of this research is to better understand the role of leadership in online groups and to evaluate the impact of leadership in maintaining online groups by supporting continued participation intentions of existing members. I explored three related questions regarding leadership in online groups. First, does member interaction with group leaders contribute to continued participation intentions over and above a model based on past participation? Second, do shared context and direct communication with leaders impact continued participation intentions? And third, do group characteristics--group psychological safety, group size, and perceived number of leaders--moderate the relationship between group members and group leaders? I collected 535 survey responses from members of thirty-three different online groups (average of sixteen members per group) and also analyzed group communication history (a total of 135,477 messages). This cross-level analysis furthers our understanding of the relationship between interaction with group leadership, psychological safety, participation role intentions, and turnover intentions. I found that leadership in online groups is a determinant of online group outcomes. Online group leaders shape the group context, including psychological safety, which encourages or discourages participation. This study shows that leadership processes, group context, and differentiation among dimensions of participation intentions are all important considerations for further understanding of online groups.Item Information Technology and Its Transformational Effect on the Health Care Industry(2007-04-25) Angst, Corey M; Agarwal, Ritu; Business and Management: Decision & Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation examines the adoption of health IT by addressing the barriers to adoption from the perspective of multiple stakeholders. I examine three different phenomena using alternative methodologies and theoretical lenses. Essay 1: The Impact of Firm Characteristics and Spatial Proximity on the Diffusion of Electronic Medical Records: A Hazard Modeling Analysis. This study, positioned at the inter-organizational level, draws upon adoption and diffusion literature to predict the likelihood of EMR adoption by hospitals. I theorize that adoption is driven by factors such as the concentration and experience with complementary HIT and an environmental factor, spatial proximity. Using a hazard model fitted to data from a sample drawn from almost 4,000 hospitals, I find support for a positive relationship between IT concentration and likelihood of adoption. I also find that spatial proximity explains variance in adoption and that its effect diminishes as distance increases. Essay 2: Isolating the Effects of IT on Performance: An Empirical Test of Complementarities and Learning. An issue at the organizational level is whether benefits result from investment in HIT. I apply a knowledge-based lens to the examination of IT adoption and process-level value, incorporating the effects of learning occurring through complementary IT adoption. I test hypotheses using data from almost 400 nationally-representative hospitals matched with quality and financial performance data and find that learning associated with more experience with IT leads to superior performance. Essay 3: Adoption of Electronic Medical Records in the Presence of Privacy Concerns: The Elaboration Likelihood Model and Individual Persuasion. At the individual level, privacy concerns can inhibit the adoption of EMRs. I draw from literature on attitude change to develop hypotheses that individuals can be persuaded to support the use, and ultimately opt-in to EMRs, even in the presence of significant privacy concerns if compelling arguments about the value of EMRs are presented. Using a quasi-experimental methodology, I find that privacy concerns interact with argument framing and issue involvement to affect attitudes toward the use of EMRs. In addition, results suggest that attitude towards EMR use and CFIP directly impact the likelihood of adoption of EMR technology.Item Three Essays on Stochastic Optimization Applied in Financial Engineering and Inventory Management(2007-04-19) Zhang, Huiju; Fu, Michael C; Business and Management: Decision & Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Stochastic optimization methods are now being widely used in a multitude of applications. This dissertation includes three essays on applying stochastic optimization methods to solve problems in inventory management and financial engineering. Essay one addresses the problem of simultaneous price determination and inventory management. Demand depends explicitly on the product price p, and the inventory control system operates under a periodic review (s, S) ordering policy. To minimize the long-run average loss, we derive sample path derivatives that can be used in a gradient-based algorithm for determining the optimal values of the three parameters (s, S, p) in a simulation-based optimization procedure. Numerical results for several optimization examples via different stochastic algorithms are presented, and consistency proofs for the estimators are provided. Essay two considers the application of stochastic optimization methods to American-style option pricing. We apply a randomized optimization algorithm called Model Reference Adaptive Search (MRAS) to pricing American-style options through parameterizing the early exercise boundary. Numerical results are provided for pricing American-style call and put options written on underlying assets following geometric Brownian motion and Merton jump-diffusion processes. We also price American-style Asian options written on underlying assets following geometric Brownian motion. The results from the MRAS algorithm are compared with the cross-entropy (CE) method, and MRAS is found to be an efficient method. Essay three addresses the problem of finding the optimal importance sampling measure when simulating portfolios of credit risky assets. We apply a gradient-based stochastic approximation method to find the parameters in the minimum variance problem when importance sampling is used. The gradient estimator is obtained under the original measure. We also employ the CE method to solve the same variance minimization problem. Numerical results illustrating the variance reduction are presented for the estimation of the portfolios' expected loss, unexpected loss and quantiles.Item 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.Item 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.Item 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.Item 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.Item 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.Item 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.