Robert H. Smith School of Business

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End date: 2009Subject: search.filters.subject.Business Administration, General

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    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.
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    The Impact of Globalization on Inventory and Financial Performance: A Firm-Level and Industry-Level Analysis
    (2009) Han, Chaodong; Dresner, Martin E; Dong, Yan; Business and Management: Logistics, Business & Public Policy; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    This dissertation investigates how globalization affects inventory and financial performance from both firm and industry perspectives. Drawing upon elements from classic inventory models, transaction costs, geographic economics, and international business and strategy literatures, this dissertation aims to contribute to the construction of a theory of global supply chain management through an empirical testing of hypotheses on the effects of global sourcing, exports and manufacturing offshoring (i.e., foreign subsidiaries) on inventory performance and financial performance, using data from multinational firms and U.S. manufacturing industries. Motivated by the lack of empirical research on inventory management in a global context, and an uncertain relationship between globalization and financial performance reported in the international business and strategy literature, the first essay examines how globalization affects firm financial performance directly and indirectly through inventory management. Globalization is further examined by a two-dimensional measure: global intensity and extensity. Due to increased uncertainties associated with global supply chains, globalization may significantly increase firm inventory levels. Even though manufacturing offshoring may benefit multinational firms through economies of scale and geographic diversification, escalating transaction costs and shrinking arbitrage opportunities may overwhelm benefits and lead to reduced financial performance. This direct-indirect effect model is tested using a large panel dataset of thousands of multinational firms over 1987-2007, collected from the COMPUSTAT global and segment databases. Essay 1 contributes to the supply chain management literature by providing a two-dimensional measure of globalization: foreign market penetration (depth) and geographic expansion (breadth), and may enhance our understanding of global supply chains. The second essay analyzes the impact of global inbound and outbound supply chains on inventory performance within the U.S. economy. This research argues that global activity (i.e., global sourcing and exports) has offsetting effects on domestic inventory levels: an increasing impact due to risk considerations and a decreasing impact due to cost pressure from rising inventory costs. According to location theory, rooted in geographic economics, and "new trade theory" on intra-firm trade, firms may be able to efficiently allocate inventories to low cost regions along their global supply chains. To the extent that allocative efficiency may only be realized once a certain level of global activity is reached, it is hypothesized that the impact of international trade on domestic inventory is inverted-U shaped. i.e., as globalization increases, inventory levels first increase due to the longer and more complex supply chains, then decrease as firms determine how to more efficiently allocate their inventory across borders. The hypotheses are tested using inventories at all three stages (raw materials, finished goods and work-in-process inventory) and industry operating data from U.S. manufacturers over the period 1997-2005. Regression results indicate a strong invert-U shaped relationships existing between import intensity (measured by imported raw materials as a percentage of industry total cost of materials) and raw materials inventory in days of supply, and between export intensity (measured by exported finished goods as a percentage of total value of industry shipments) and finished goods inventory in days of supply. Essay 2 makes two contributions: theoretically, it is the first effort to connect international trade with inventory performance; empirically, results based on all U.S. manufacturers over a recent nine-year period may provide a benchmark for management when designing global inventory strategy. In summary, this dissertation comprehensively investigates the impact of global supply chains on inventory performance and financial performance in the context of multinational firms and U.S. domestic manufacturers and hence is expected to enhance our understanding of global supply chain management theory and practices.
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    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.
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    Supply Chain Disruption Management: A Conceptual Framework and Theoretical Model
    (2008-11-06) Macdonald, John R; Corsi, Thomas M; Business and Management: Logistics, Business & Public Policy; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Severe supply chain disruptions have a great impact on the firm. They can cause loss of sales to customers and lead to changes in the design and strategy of the supply chain. This research works focuses on supply chain disruption management. It presents an overall conceptual framework and a theoretical model, highlighting the decision making process of disruption recovery. First, the literature concepts surrounding supply chain disruptions - risk management, mitigation, crisis management, supply chain resilience, supply chain security, business continuity planning, and sustainability - are defined and differentiated, since these concepts often have overlapping factors that can cause confusion. After defining each of these concepts and the latest research findings, a framework for understanding the relationships among the concepts is developed. Second, this framework reveals a gap in the literature surrounding the disruption recovery and decision making process. While an initial disruption management model can be built using factors from the literature, data are collected by conducting multiple interviews and analyzed using a structured grounded theory methodology to produce a more complete model. This also has the effect of building theory from which propositions are developed surrounding discovery of the disruption, recovery team composition, decision making, and others. These propositions can be tested empirically in future research.
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    Firm Decision Making Under Financial Distress: A Study of U.S. Air Fares and an Analysis of Inventories in U.S. Manufacturing Industries
    (2007-07-09) Hofer, Christian; Dresner, Martin E; Windle, Robert J; Business and Management: Logistics, Business & Public Policy; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    This dissertation investigates the effects of firm financial distress on two key firm decision variables: sales prices and inventories. These analyses contribute to the Structure-Conduct-Performance paradigm literature. Specifically, the feedback loop between financial distress, a result of poor past performance, and two firm conduct parameters, prices and inventories, is explored in great detail. The first essay is motivated by the ambiguity of prior research on the relationship between firm financial distress and prices. The extant economics, corporate finance and strategic management literatures differentially approach this relationship, and empirical research has found only limited, at times ambiguous support for any single theoretical contention. These theoretical perspectives are reviewed and an attempt is made to reconcile the apparent conflict by adopting a strategic contingency perspective that identifies in which way and in what instances firm financial distress may impact prices. The model is empirically tested using data from the U.S. airline industry. The results indicate that firm financial distress and prices are generally negatively related. Moreover, this effect is substantially stronger for firms operating under Chapter 11 protection than for firms approaching bankruptcy. It is further shown that the magnitude of the effect of financial distress on prices depends on firm factors such as operating costs, market power, and firm size, as well as on competitive characteristics such as market concentration and the financial condition of competitors. The second essay analyzes the impact of firm distress on firm inventories and investigates if this relationship is impacted by a firm's power relative to its upstream and downstream supply chain partners. Building on prior work in the economics field, this research is not only based on microeconomics theory, but also draws on inventory theory as well as on prior work on supply chain relationships. A comprehensive inventory estimation model is specified, and novel measures of inventory determinants and power are developed. The hypotheses are tested using panel data from the U.S. manufacturing industry. It is shown that distressed firms hold less inventory and that a firm's power within the supply chain will determine to what extent inventory ownership is reduced during times of financial distress. Implications for supplier selection and supply chain cooperation are discussed. In summary, this research significantly enhances researchers' understanding of why, how, and when firm financial distress affects prices and inventories.
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    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.
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    Strategic Behaviors and Market Outcomes: Two Essays
    (2007-04-19) Zou, Li; Dresner, Martin E; Windle, Robert J; Business and Management: Logistics, Business & Public Policy; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    This dissertation is comprised of two essays related, broadly, to themes of competitive dynamics and economic consequences. In Essay One, "Many Fields of Battle: How Cost Structure Affects Competition across Multiple Markets," a conjectural variation model is developed to examine what role cost structure and product differentiation play in affecting the mutual forbearance outcome arising from multi-market contact. The analytical results show that the degree of collusion (as measured by the price level) enhanced through multimarket contact is greater when multimarket contact occurs between firms with similar production costs and undifferentiated products. This hypothesis is then tested using data from the U.S. airline industry. The empirical results provide support for the view suggesting that multimarket contact blunts the edge of competition between firms. Moreover, it is found that rival carriers with similar production costs are more likely to experience such collusion facilitating effects from multimarket contact than those with dissimilar production costs. The second essay in this dissertation is entitled, "A Two-Location Inventory Model with Transshipments in a Competitive Environment." In this study, an analytical model is developed to assess the impact of transshipments on inventory replenishment decisions and the implications for firm profitability in a competitive, uncertain market environment. To incorporate the competition between stocking locations, the analytical model developed in this paper uses a marketing variable, customer's switching rate, to measure the probability of an individual consumer choosing an alternative source of supply in the event of stockout. In such an environment, firms not only cooperate through the practice of transshipments but also compete for business. A number of interesting conclusions are drawn from numerical optimization results. For instance, it is found that when firms differ in market demand, small firms benefit more from transshipments than do large firms. In addition, it is shown that there is an inverted u-shaped relationship between transshipment price and the profit improvements that large firms gain through transshipments, whereas such benefits are monotonically decreasing with transshipment price for small firms. These findings provide several managerial implications with regard to the role of transshipment price in creating benefits for participating firms.
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    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.
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    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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    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.