bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessing User Competence: Conceptualization and Measurement
Authors: Marcolin Barbara L. , Compeau Deborah R. , Munro Malcolm C. , Huff Sid L.
Published: April 2003

Organizations today face great pressure to maximize the bene its from their investments in information technology (IT). They are challenged not just to use IT, but to use it as effectively as possible. Understanding how to assess the competence of users is critical in maximizing the effectiveness of IT use. Yet the user competence construct is largely absent from prominent technology acceptance and it models, poorly conceptualized, and inconsistently measured. We begin by presenting a conceptual model of the assessment of user competence to organize and clarify the diverse literature regarding what user competence means and the problems of assessment. As an illustrative study, we then report the findings from an experiment involving 66 participants. The experiment was conducted to compare empirically two methods (paper and pencil tests versus self-report questionnaire), across two different types of software, or domains of knowledge (word processing versus spreadsheet packages), and two different conceptualizations of competence (software knowledge versus self-efficacy). The analysis shows statistical significance in all three main effects. How user competence is measured, what is measured, what measurement context is employed:all influence the measurement outcome. Furthermore, significant interaction effects indicate that different combinations of measurement methods, conceptualization, and knowledge domains produce different results. The concept of frame of reference, and its anchoring effect on subjects' responses, explains a number of these findings. The study demonstrates the need for clarity in both defining what type of competence is being assessed and in drawing conclusions regarding competence, based upon the types of measures used. Since the results suggest that definition and measurement of the user competence construct can change the ability score being captured, the existing information system (IS) models of usage must contain the concept of an ability rating. We conclude by discussing how user competence can be incorporated into the Task-Technology Fit model, as well as additional theoretical and practical implications of our research.
Opening the “Black Box” of Network Externalities in Network Adoption
Authors: Kauffman Robert J. , McAndrews James , Wang Yu-Ming
Published: April 2003

Recent theoretical work suggests that network externalities are a determinant of network adoption. However, few empirical studies have reported the impact of network externalities on the adoption of networks. As a result, little is known about the extent to which network externalities may influence network adoption and diffusion. Using electronic banking as a context and an econometric technique called hazard modeling, this research examines empirically the impact of network externalities and other influences that combine to determine network membership. The results support the network externalities hypothesis. We find that banks in markets that can generate a larger effective network size and a higher level of externalities tend to adopt early, while the size of a bank's own branch network (a proxy for the opportunity cost of adoption)decreases the probability of early adoption.
Productivity of Information Systems in the Healthcare Industry
Authors: Menon Nirup M. , Lee Byungtae , Eldenburg Leslie
Published: April 2003

This research paper analyzes the impact of information technology (IT)in a healthcare setting using a longitudinal sample of hospital data from 1976 to 1994. We classify production inputs into labor and capital categories. Capital is classified into three components—medical IT capital, medical capital, and IT capital—and labor is classified into two components, medical labor and IT labor. Results provide evidence that IT contributes positively to the production of services in the healthcare industry.
Using Repertory Grids to Conduct Cross-Cultural Information Systems Research
Authors: Hunter M. Gordon , Beck John E.
Published: April 2003

As more business is being conducted internationally and corporations establishthemselves globally, the impact of cross-cultural aspects becomes an important research issue. The need to conduct cross-cultural research is perhaps even more important in the relatively newly emerging and quickly changing information systems (IS)field. This article presents issues relating to qualitative research, emic versus etic approaches, and describes a structured, yet flexible, qualitative research interviewing technique, which decreases the potential for bias on the part of the researcher. The grounded theory technique presented in this article is based on Kelly's Repertory Grid (RepGrid), which concentrates on “laddering,” or the further elaboration of elicited constructs, to obtain detailed researchparticipant comments about an aspect within the domain of discourse. The technique provides structure to a “one-to-one” interview. But, at the same time, RepGrids allow sufficient flexibility for the research participants to be able to express their own interpretation about a particular topic. This article includes a brief outline of a series of research projects that employed the RepGrid technique to examine similarities and differences in the way in which “excellent” systems analysts are viewed in two different cultures. Also included is a discussion of the technique's applicability for qualitative researchin general and cross-cultural studies specifically. The article concludes by suggesting ways in which the RepGrid technique addresses some of the major methodological issues in cross-cultural research.
Research Commentary: The Organizing Logic for an Enterprise's IT Activities in the Digital Era—A Prognosis of Practice and a Call for Research
Authors: Sambamurthy V. , Zmud Robert W.
Published: April 2003

Prior research has generated considerable knowledge about the design of effective IT organizational architectures. Today, however, increasing signs have accumulated that this wisdom might be inadequate in shaping appropriate insights for contemporary practice. This essay seeks to direct research attention toward the following question: How should firms organize their IT activities in order to manage the imperatives of the business and technological environments in the digital economy? We articulate the platform logic as a conceptual framework for both viewing the organizing of IT management activities as well as for framing important questions for future research. In articulating this logic, we aim to shift thinking away from the traditional focus on governance structures (i.e., choice of centralized, decentralized, or federal forms) and sourcing structures (i.e., insourcing, outsourcing) and toward more complex structures that are reflective of contemporary practice. These structures are designed around important IT capabilities and network architectures.
The Role of Multimedia in Changing First Impression Bias
Authors: Lim Kai H. , Benbasat Izak , Ward Lawrence M.
Published: April 2003

First impression bias refers to a limitation of human information processing in which people are strongly influenced by the first piece of information that they are exposed to, and that they are biased in evaluating subsequent information in the direction of the initial influence. The psychology literature has portrayed first impression bias as a virtually “inherent” human bias. Drawing from multimedia literature, this study identifies several characteristics of multimedia presentations that have the potential to alleviate first impression bias. Based on this literature, a set of predictions was generated and tested through a laboratory experiment using a simulated multimedia intranet.

Half of the 80 subjects were provided with a biased cue. Subjects were randomly assigned to four groups: (1) text with first impression bias cue, (2) multimedia with first impression bias cue, (3) text without biased cue, and (4) multimedia without biased cue. The experimental task involved conducting a five-year performance appraisal of a department head. The first impression bias cue was designed to provide incomplete and unfavorable information about the department head, but the information provided subsequently was intended to be favorable of his performance.

Results show that the appraisal score of the text with biased cue group was significantly lower than the text only (without biased cue) group. On the other hand, the appraisal score of the multimedia with biased cue group was not significantly different from the multimedia only (without biased cue) group. As a whole, the results suggest that multimedia presentations, but not text-based presentations, reduce the influence of first impression bias.
Mean-Risk Trade-Offs in Inductive Expert Systems
Authors: Mookerjee Vijay S. , Mannino Michael V.
Published: April 2003

Notably absent in previous research on inductive expert systems is the study of meanrisk trade-offs. Such trade-offs may be significant when there are asymmetries such as unequal classification costs, and uncertainties in classification and information acquisition costs. The objective of this research is to developmodels to evaluate mean-risk trade-offs in value-based inductive approaches. We develop a combined mean-risk measure and incorporate it into the Risk-Based induction algorithm. The mean-risk measure has desirable theoretical properties (consistency and separability) and is supported by empirical results on decision making under risk. Simulation results using the Risk-Based algorithm demonstrate: (i) an order of magnitude performance difference between mean-based and risk-based algorithms and (ii) an increase in the performance difference between these algorithms as either risk aversion, uncertainty, or asymmetry increases given modest thresholds of the other two factors.
The Production of Information Services: A Firm-Level Analysis of Information Systems Budgets
Authors: Gurbaxani Vijay , Melville Nigel , Kraemer Kenneth
Published: April 2003

Previous research has demonstrated that the production of information services can be characterized at the aggregate economy-wide level by the Cobb-Douglas production function. However, the underlying production process at the firm level has not yet been ascertained. The objective of this paper is to determine the form of the production process for information systems services at the firm level by conducting an empirical analysis of IS budget data. The production of information services is modeled using a production function with two inputs, hardware and personnel. We estimate various econometric specifications to determine several characteristics of the provision of information services, including the allocation of the information systems budget to its two largest components—hardware and personnel—and its implications for the form of the production function. After controlling for industry sector, we find that the ratio of personnel to hardware is independent of scale, which indicates a homothetic production function. We also find that the ratio of factor shares is constant with time, consistent with the Cobb-Douglas production function.We conclude that the underlying form of the production function is the same at the level of both the firm and the economy. Our analysis demonstrates how the application of production theory to the production of information services can yield useful insights from both a theoretical and managerial perspective.
Integrating User Preferences and Real-Time Workload in Information Services
Authors: Konana Prabhudev , Gupta Alok , Whinston Andrew B.
Published: April 2003

We propose priority pricing as an on-line adaptive resource scheduling mechanism to manage real-time databases within organizations. These databases provide timely information for delay sensitive users. The proposed approach allows diverse users to optimize their own objectives while collectively maximizing organizational benefits. We rely on economic principles to derive priority prices by modeling the fixed-capacity real-time database environment as an economic system. Each priority is associated with a price and a delay, and the price is the premium (congestion toll resulting from negative externalities) for accessing the database. At optimality, the prices are equal to the aggregate delay cost imposed on all other users of the database. These priority prices are used to control admission and to schedule user jobs in the database system. The database monitors the arrival processes and the state of the system, and incrementally adjusts the prices to regulate the flow. Because our model ignores the operational intricacies of the real-time databases (e.g., intermediate queues at the CPU and disks, memory size, etc.) to maintain analytical tractability, we evaluate the performance of our pricing approach through simulation. We evaluate the database performance using both the traditional real-time database performance metrics (e.g., the number of jobs serviced on time, average tardiness) and the economic benefits (e.g., benefits to the organization). The simulation results, under various database workload parameters, show that our priority pricing mechanism not only maximizes organizational benefits but also outperforms in all aspects of traditional performance measures compared to frequently used database scheduling techniques, such as first-come-first-served, earliest deadline first and least slack first.
Innovation and Control in Standards Architectures: The Rise and Fall of Japan's PC-98
Authors: West Joel , Dedrick Jason
Published: April 2003

For more than a decade NEC dominated the Japanese PC market with its PC-98 architecture, which was incompatible both with its major Japanese rivals and the global PC standard. However, NEC was powerless to prevent the introduction of Japanese versions of Windows 3.1 and 95 that ran on its competitors' architectures as well as on the PC-98, unifying the Japanese PC market and creating a common set of application programming interfaces for all Intel-based Japanese PCs. The introduction of Windows rendered obsolete the large DOS-based software library that had provided strong positive externalities for the NEC architecture. Absent those advantages, the market share of the PC-98 standard fell from 60% to 33% in five years, and NEC finally abandoned the PC-98 in favor of the global standard. An examination of the unusual rise and fall of the PC-98 shows how victory in a standards competition can be negated by the introduction of a new architectural layer that spans two or more previously incompatible architectures.
Market Entry Strategy Under Firm Heterogeneity and Asymmetric Payoffs
Authors: Narasimhan Chakravarthi , Zhang Z. John
Published: April 2003

How should a firm decide whether or not to enter an untested market when a competing firm is vying for the same market? Should a firm always speed to the market in an effort to capitalize on pioneering advantages? We address those questions by developing a simple game-theoretical model that captures the most essential factors in a firm's market entry decision, such as market uncertainty, firm heterogeneity, competition, cannibalization, and order-of-entry effects.

Our analysis shows that in a competitive context, both pioneering advantages and laggard's disadvantages can motivate a firm to speed to an untested market. Therefore, pioneering advantages alone are not an adequate guide for a firm to formulate its market entry strategy. The optimal decision may call for a firm to be a prudent laggard when pioneering advantages to the firm are substantial, or to become a market pioneer when facing pioneering disadvantages. We characterize different patterns of market entry as equilibrium outcomes for different configurations of the market reward structure and offer a conceptual framework for formulating market entry strategies that go beyond the conventional dichotomy: speed or wait. We show that the paradoxical phenomenon of “disadvantaged pioneers” can arise in a competitive context as the outcome of rational firms making rational choices.

To show that pioneering advantages alone are not the right litmus test for market entry decisions, we apply our general framework to a concrete case where consumer preference or the premium that consumers are willing to pay for the pioneering brand gives rise to pioneering advantages and laggard's disadvantages. We conclude that the firm with a larger pioneering premium may choose to wait, while a firm with a smaller pioneering premium speeds to the market.

Our analysis also sheds light on empirical research on pioneering advantages. Because firms may race into a market solely to avoid laggard's disadvantages rather than to capture pioneering advantages, pioneers are not necessarily the firms best positioned to establish, exploit, and maintain pioneering advantages. Therefore, it is not surprising that a significant percentage of pioneers fail, as documented by recent empirical research. Our normative investigation further suggests that this predicament in empirical research will not disappear even if we have complete data, use the right measurements, and employ perfect statistical techniques. Therefore, it is perhaps more fruitful to redirect our research effort in the search for pioneering advantages.

Finally, we extend our analysis to incorporate the effect of cannibalization on an incumbent firm's market entry strategy. We conclude that cannibalization can motivate an incumbent firm to wait, as the conventional wisdom suggests, but it can also be an impetus for a firm to become a market pioneer. We offer supporting evidence for our analysis and discuss managerial implications of our conclusions.
An Inexact Hybrid Generalized Proximal Point Algorithm and Some New Results on the Theory of Bregman Functions
Authors: Solodov M. V. , Svaiter B. F.
Published: April 2003

We present a new Bregman-function-based algorithm which is a modification of the generalized proximal point method for solving the variational inequality problem with a maximal monotone operator. The principal advantage of the presented algorithm is that it allows a more constructive error tolerance criterion in solving the proximal point subproblems. Furthermore, we eliminate the assumption of pseudomonotonicity which was, until now, standard in proving convergence for paramonotone operators. Thus we obtain a convergence result which is new even for exact generalized proximal point methods. Finally, we present some new results on the theory of Bregman functions. For example, we show that the standard assumption of convergence consistency is a consequence of the other properties of Bregman functions, and is therefore superfluous.
A Comparison of Formulations for the Single-Airport Ground-Holding Problem with Banking Constraints
Authors: Hoffman Robert , Ball Michael O.
Published: April 2003

Both the single-airport ground-holding problem (GH) and the multi-airport ground-holding problem can be extended by the addition of banking constraints to accommodate the hubbing operations of major airlines. These constraints enforce the desire of airlines to land certain groups of flights, called banks, within fixed time windows, thus preventing the propagation of delays throughout their entire operation. GH can be formulated as a transportation problem and readily solved. But in the presence of banking constraints, GH becomes a difficult integer programming problem. In this paper, we construct five different models of the single-airport ground-holding problem with banking constraints (GHB). The models are evaluated both computationally and analytically. For two of the models, we show that the banking constraints induce facets of the convex hull of the set of integer solutions. In addition, we explore a linear transformation of variables and a branching technique.
Airline Fleet Assignment with Time Windows
Authors: Rexing Brian , Barnhart Cynthia , Kniker Tim , Jarrah Ahmad , Krishnamurthy Nirup
Published: April 2003

Recognizing that allowing variability in scheduled flight departure times can result in improved flight connection opportunities and a more cost effective fleet assignment, we present a generalized fleet assignment model for simultaneously assigning aircraft types to flights and scheduling flight departures. Our model, a simple variant of basic fleet assignment models, assigns a time window to each flight and then discretizes each window, allowing flight departure times to be optimized. Because problem size can become formidable, much larger than basic fleet assignment models, we develop two algorithmic approaches for solving the model. Our direct solution approach is good for speed and simplicity, whereas our iterative technique minimizes memory usage. Using data from a major U.S. airline, we show that our model can solve real, large-scale problems, and we evaluate the effects of schedule flexibility. In every test scenario, the model produces a fleet assignment with significantly lower costs than the basic model, and, in a separate analysis, the model is used to tighten the schedule, potentially saving aircraft.
A New Heuristic for the Traveling Salesman Problem with Time Windows
Authors: Calvo Roberto Wolfler
Published: April 2003

The aim of this paper is to present a new heuristic method for the Traveling Salesman Problem with Time Windows, based on the solution of an auxiliary problem. The idea is to solve an assignment problem with an ad hoc objective function to obtain a solution close enough to a feasible solution of the original problem. Given this solution, made by a long main tour containing the depot and few small subtours, it is easy to insert all the subtours into the main path using a greedy insertion procedure. The algorithm described applies the proposed constructive scheme and then uses a local search procedure to improve the initial solution. The computational results show the effectiveness of this approach.
Alternative Approaches for Real-Time Estimation and Prediction of Time-Dependent Origin–Destination Flows
Authors: Ashok K. , Ben-Akiva M. E.
Published: April 2003

This paper examines two different approaches for real-time estimation/prediction of time-dependent Origin–Destination (O–D) flows. Both approaches lend themselves to formulation as state-space models. The first approach is an extension of previous work by the authors. The key idea in this approach is to define the state-vector in terms of deviations in O–D flows instead of the O–D flows themselves. We demonstrate that approximations to this model make the real-time estimation process computationally more tractable with little deterioration in quality of estimates. In the second approach, the state vector is defined in terms of deviations of departure rates from each origin and the shares headed to each destination. This approach attempts to capture the differential variation of departure rates and shares over time. Performance of the proposed models is evaluated using actual traffic data from different sources. Preliminary results indicate that the filtering procedure is robust and that, compared to the original model, a formulation based on departure rates and shares yields better predictions with some loss of accuracy in filtered estimates.
A Linear Programming Model for the Single Destination System Optimum Dynamic Traffic Assignment Problem
Authors: Ziliaskopoulos Athanasios K.
Published: April 2003

Recently, Daganzo introduced the cell transmission model—a simple approach for modeling highway traffic flow consistent with the hydrodynamic model. In this paper, we use the cell transmission model to formulate the single destination System Optimum Dynamic Traffic Assignment (SO DTA) problem as a Linear Program (LP). We demonstrate that the model can obtain insights into the DTA problem, and we address various related issues, such as the concept of marginal travel time in a dynamic network and system optimum necessary and sufficient conditions. The model is limited to one destination and, although it can account for traffic realities as they are captured by the cell transmission model, it is not presented as an operational model for actual applications. The main objective of the paper is to demonstrate that the DTA problem can be modeled as an LP, which allows the vast existing literature on LP to be used to better understand and compute DTA. A numerical example illustrates the simplicity and applicability of the proposed approach.
Adaptive Labeling Algorithms for the Dynamic Assignment Problem
Authors: Powell Warren B. , Snow Wayne , Cheung Raymond K.
Published: April 2003

We consider the problem of dynamically routing a driver to cover a sequence of tasks (with no consolidation), using a complex set of driver attributes and operational rules. Our motivating application is dynamic routing and scheduling problems, which require fast response times, the ability to handle a wide range of operational concerns, and the ability to output multiple recommendations for a particular driver. A mathematical formulation is introduced that easily handles real-world operational complexities. Two new optimization-based heuristics are described, one giving faster performance and the second providing somewhat higher solution quality. Comparisons to optimal solutions are provided, which measure the quality of the solutions that our algorithms provide. Experimental tests show that our algorithms provide high quality solutions, and are fast enough to be run in real-time applications.
On the Value of Optimal Myopic Solutions for Dynamic Routing and Scheduling Problems in the Presence of User Noncompliance
Authors: Powell Warren B. , Towns Michael T. , Marar Arun
Published: April 2003

The most common approach for modeling and solving routing and scheduling problems in a dynamic setting is to solve, as close to optimal as possible, a series of deterministic, myopic models. The argument is most often made that, if the data changes, then we should simply reoptimize. We use the setting of the load matching problem that arises in truckload trucking to compare the value of optimal myopic solutions versus varying degrees of greedy, suboptimal myopic solutions in the presence of three forms of uncertainty: customer demands, travel times, and, of particular interest, user noncompliance. A simulation environment is used to test different dispatching strategies under varying levels of system dynamism. An important issue we consider is that of user noncompliance, which is the effect of optimizing when users do not adopt all of the recommendations of the model. Our results show that (myopic) optimal solutions only slightly outperform greedy solutions under relatively high levels of uncertainty, and that a particular suboptimal solution actually outperforms optimal solutions under a wide range of conditions.
Dynamic Routing for Priority Shipments in LTL Service Networks
Authors: Cheung Raymond K. , Muralidharan B.
Published: April 2003

Currently, less-than-truckload (LTL) carriers route both the regular and the priority shipments through their service networks using some fixed route patterns, known as load plans. In this paper, we consider an alternative strategy for routing priority shipments in LTL networks. This strategy exploits the stochasticity and dynamism embedded in the routing process where the real-time information at the current terminal (such as the loading status of trailers and the arrival of shipments) and the expected travel times from its neighboring terminals to the destination are used to route shipments adaptively. We show that this strategy can be approximated by the problem of finding dynamic shortest paths over a network with random arc costs. We develop an efficient algorithm to compute the expected travel times of these paths. These times can then be used when we implement the proposed strategy. In the numerical testing with real data, we observe that the level of service for priority shipments can be improved significantly.
Stochastic Vehicle Routing Problem with Restocking
Authors: Yang Wen-Huei , Mathur Kamlesh , Ballou Ronald H.
Published: April 2003

In this paper, a stochastic vehicle routing problem is considered. In particular, customer demand is assumed to be uncertain, and actual demand is revealed only upon the visit to the customer. Instead of adopting the simple recourse action of returning to the depot whenever the vehicle runs out of stock, the points along the route at which restocking is to occur are designed into the route. The restocking points may be before a stockout actually occurs. Two heuristic algorithms are developed to construct both single and multiple routes that minimize total travel cost. The computational results show that the heuristic procedures produce quality solutions and are efficient.
A Benders Decomposition Approach for the Locomotive and Car Assignment Problem
Authors: Cordeau Jean-François , Soumis François , Desrosiers Jacques
Published: April 2003

One of the many problems faced by rail transportation companies is to optimize the utilization of the available stock of locomotives and cars. In this paper, we describe a decomposition method for the simultaneous assignment of locomotives and cars in the context of passenger transportation. Given a list of train legs and a fleet composed of several types of equipment, the problem is to determine a set of minimum cost equipment cycles such that every leg is covered using appropriate equipment. Linking constraints, which appear when both locomotives and cars are treated simultaneously, lead to a large integer programming formulation. We propose an exact algorithm, based on the Benders decomposition approach, that exploits the separability of the problem. Computational experiments carried on a number of real-life instances indicate that the method finds optimal solutions within short computing times. It also outperforms other approaches based on Lagrangian relaxation or Dantzig–Wolfe decomposition, as well as a simplex-based branch-and-bound method.
A Multiplier Adjustment Method for Dynamic Resource Allocation Problems
Authors: Carvalho Tassio A. , Powell Warren B.
Published: April 2003

Dynamic fleet management problems (with a homogeneous fleet) are classically formulated as dynamic networks, or linear programs with side constraints. Recently, a new dynamic control approach was introduced, called a logistics queueing network. Instead of a large linear program, the problem is decomposed into small subproblems that are guided by two control variables that push these local problems to produce a solution that is close to a global optimum. In prior work, these control variables were updated using a subgradient approximation. In this paper, we propose a multiplier adjustment method for solving the same problem. Numerical experiments show that this method produces better solutions with greater stability. The new method is somewhat slower, and is more difficult to implement. We believe that both methods will represent reasonable choices for solving the problem.
Catastrophe Avoidance Models for Hazardous Materials Route Planning
Authors: Erkut Erhan , Ingolfsson Armann
Published: April 2003

The most-widely used definition of risk in the hazardous materials transportation literature is the expected consequence of an incident (accident resulting in a release), which, for each edge of the network, is equal to the product of the incident probability and a quantifiable consequence (such as number of people evacuated). This definition ignores the risk-averse attitudes of many decision-makers when dealing with low probability/high consequence events. We suggest that avoiding a catastrophe (an incident with a very large consequence) may be a relevant issue in routing hazardous materials, and we introduce three different catastrophe-avoidance models. In the first model, catastrophe avoidance is achieved by minimizing the maximum population exposure. In the second model, the variance of the route consequence is incorporated into the decision. In the third model, an explicit disutility function is used. We show that all three models reduce to a standard shortest path problem. Each model avoids high-population areas of the transport network. We give numerical examples and discuss the similarities and the differences among the three models. The first of the three models suggested may be the most intuitive, and is the most tractable computationally. Implementation of the other two models may be difficult due to scaling issues. Nevertheless, these models offer theoretical insight that may be valuable to researchers.
Scheduling Aircraft Landings—The Static Case
Authors: Beasley J. E. , Krishnamoorthy M. , Sharaiha Y. M. , Abramson D.
Published: April 2003

In this paper, we consider the problem of scheduling aircraft (plane) landings at an airport. This problem is one of deciding a landing time for each plane such that each plane lands within a predetermined time window and that separation criteria between the landing of a plane and the landing of all successive planes are respected. We present a mixed-integer zero–one formulation of the problem for the single runway case and extend it to the multiple runway case. We strengthen the linear programming relaxations of these formulations by introducing additional constraints. Throughout, we discuss how our formulations can be used to model a number of issues (choice of objective function, precedence restrictions, restricting the number of landings in a given time period, runway workload balancing) commonly encountered in practice. The problem is solved optimally using linear programming-based tree search. We also present an effective heuristic algorithm for the problem. Computational results for both the heuristic and the optimal algorithm are presented for a number of test problems involving up to 50 planes and four runways.
Least Expected Time Paths in Stochastic, Time-Varying Transportation Networks
Authors: Miller-Hooks Elise D. , Mahmassani Hani S.
Published: April 2003

We consider stochastic, time-varying transportation networks, where the arc weights (arc travel times) are random variables with probability distribution functions that vary with time. Efficient procedures are widely available for determining least time paths in deterministic networks. In stochastic but time-invariant networks, least expected time paths can be determined by setting each random arc weight to its expected value and solving an equivalent deterministic problem. This paper addresses the problem of determining least expected time paths in stochastic, time-varying networks. Two procedures are presented. The first procedure determines the a priori least expected time paths from all origins to a single destination for each departure time in the peak period. The second procedure determines lower bounds on the expected times of these a priori least expected time paths. This procedure determines an exact solution for the problem where the driver is permitted to react to revealed travel times on traveled links en route, i.e., in a time-adaptive route choice framework. Modifications to each of these procedures for determining least expected cost (where cost is not necessarily travel time) paths and lower bounds on the expected costs of these paths are given. Extensive numerical tests are conducted to illustrate the algorithms' computational performance as well as the properties of the solution.
A Continuous Equilibrium Model for Estimating Market Areas of Competitive Facilities with Elastic Demand and Market Externality
Authors: Yang Hai , Wong S. C.
Published: April 2003

We consider a heterogeneous two-dimensional space where a given set of competitive facilities is located. Customers are assumed to be scattered continuously over the space, and each customer is assumed to choose a facility to minimize individual total cost of receiving service. The total cost consists of both the congested travel time to the facility and a cost associated with the congestion externality at the facility. Furthermore, customer demand at any location is assumed to be a function of the total cost of receiving service. Given these assumptions, it is of interest to estimate the market areas and market shares captured by each competitive facility. This problem is formulated here as a calculus of variations problem, and its optimality conditions are shown to be equivalent to the spatial customer choice equilibrium conditions with elastic demand and market externality. The model is solved by an efficient finite element method and illustrated with a numerical example.
Incorporating Observed and Unobserved Heterogeneity in Urban Work Travel Mode Choice Modeling
Authors: Bhat Chandra R.
Published: April 2003

An individual's intrinsic mode preference and responsiveness to level-of-service variables affects her or his travel mode choice for a trip. The mode preference and responsiveness will, in general, vary across individuals based on observed (to an analyst) and unobserved (to an analyst) individual characteristics. The current paper formulates a multinomial logit-based model of travel mode choice that accommodates variations in mode preferences and responsiveness to level-of-service due to both observed and unobserved individual characteristics. The model parameters are estimated using a maximum simulated log-likelihood approach. The model is applied to examine urban work travel mode choice in a multiday sample of workers from the San Francisco Bay area.
The Traffic Flow Management Rerouting Problem in Air Traffic Control: A Dynamic Network Flow Approach
Authors: Bertsimas Dimitris , Patterson Sarah Stock
Published: April 2003

We address the problem of determining how to reroute aircraft in the air traffic control system when faced with dynamically changing weather conditions. The overall objective of this problem is the minimization of delay costs. This problem is of primary concern in the European air traffic control system and in particular regions within the US air traffic control system. We present an integrated mathematical programming approach that consists of several methodologies. To address the high dimensionality, we begin by presenting an aggregate model, in which the problem is formulated as a dynamic, multicommodity, integer network flow problem with certain side constraints. Using Lagrangian relaxation, we generate aggregate flows. We decompose the aggregate flows into a collection of flight paths for individual aircraft using a randomized rounding heuristic. This collection of paths is then used in a packing integer programming formulation, the solution of which generates feasible and near-optimal routes for individual flights. The overall Lagrangian Generation Algorithm is used to solve real problems in the southwestern portion of United States. In computational experiments, the solutions returned by our algorithm are within 1% of the corresponding lower bounds.
Scheduling Direct and Indirect Trains and Containers in an Intermodal Setting
Authors: Newman Alexandra M. , Yano Candace Arai
Published: April 2003

The focus of our research is on rail transportation of intermodal containers. We address the problem of determining day-of-week schedules for both direct and indirect (via a hub) trains and allocating containers to these trains for the rail (linehaul) portion of the intermodal trip. The goal is to minimize operating costs, including a fixed charge for each train, variable transportation and handling costs for each container and yard storage costs, while meeting on-time delivery requirements. We formulate the problem as an integer program and develop a novel decomposition procedure to find near-optimal solutions. We also develop a method to provide relatively tight bounds on the objective function values. Finally, we compare our solutions to those obtained with heuristics designed to mimic current operations, and show that a savings of between 5 and 20% can be gained from using our solution procedure.
The Rollon–Rolloff Vehicle Routing Problem
Authors: Bodin Lawrence , Mingozzi Aristide , Baldacci Roberto , Ball Michael
Published: April 2003

In this paper, a sanitation routing problem called the Rollon–Rolloff Vehicle Routing Problem (RRVRP) is defined. In the RRVRP, tractors move large trailers between locations and a disposal facility. The trailers are so large that the tractor can only transport one trailer at a time. In this paper, the RRVRP is defined, a mathematical programming formulation is presented, and two lower bounds and four heuristic algorithms are developed and tested on 20 different problems. Conclusions are derived and recommendations for further research are presented.
A Bilevel Model and Solution Algorithm for a Freight Tariff-Setting Problem
Authors: Brotcorne Luce , Labbé Martine , Marcotte Patrice , Savard Gilles
Published: April 2003

We consider a bilevel programming formulation of a freight tariff-setting problem where the leader consists in one among a group of competing carriers and the follower is a shipper. At the upper level, the leader's revenue corresponds to the total tariffs levied, whereas the shipper minimizes its transportation cost, given the tariff schedule set by the leader. We propose for this problem a class of heuristic procedures whose relative efficiencies, on small problem instances, could be validated with respect to optimal solutions obtained from a mixed integer reformulation of the mathematical model. We also present numerical results on large instances that could not be solved to optimality by an exact method.
A Pareto Improving Strategy for the Time-Dependent Morning Commute Problem
Authors: Daganzo Carlos F. , Garcia Reinaldo C.
Published: April 2003

This research shows that certain time-dependent congestion reduction schemes involving tolls have the potential for benefiting every driver even if the collected revenues are not returned to the payers. The paper considers a population of commuters who use a single bottleneck during the morning rush hour and try to arrive at work on time. It is assumed that the number of commuters is fixed (independent of the control strategy) and that each commuter wishes to pass through the bottleneck at a given time, which may differ across commuters. Commuters are otherwise identical. Each of them chooses his/her arrival time at the bottleneck so as to minimize a linear combination of monetary cost (tolls), queuing time, and deviation from the desired passage time. A time-dependent toll is applied during a time window, but some commuters are exempted from paying it. Every day, each commuter is classified as either “free” or “paying.” The classification method is such that, in the long-run, the fraction of days, f, that a commuter is free is the same for all commuters, and the fraction of free commuters is f every day. Free commuters are allowed to use the bottleneck without paying the toll, whereas paying commuters can avoid the toll only if they pass through the bottleneck outside the time window. It is shown that, if commuters wish to pass through the bottleneck close together, then the toll, the window, and the fraction of free commuters can be chosen in a way that will benefit everyone by inducing an equilibrium where the “peak is smoothed out” in a particular way. Up to 25% of the total user cost can be eliminated in this way.
The Shortest Path Problem with Time Windows and Linear Waiting Costs
Authors: Desaulniers Guy , Villeneuve Daniel
Published: April 2003

This paper considers the shortest path problem with waiting costs (SPWC) as an extension to the shortest path problem with time windows. The problem consists of finding the minimum cost path in a network, where cost and time are two independent quantities associated with a path. Path feasibility is constrained by time windows at each node and a linear cost penalty is imposed for each unit of time spent waiting along the path. Starting from a known, nonlinear, integer programming formulation, we propose two alternative formulations for which algorithms already exist. First, we indicate how to transform the SPWC into a shortest path problem with time windows and linear node costs. Second, we prove that the SPWC can also be formulated as a two-resource generalized shortest path problem with resource constraints. Computational results used to compare these alternative formulations are presented.
National Airspace Sector Occupancy and Conflict Analysis Models for Evaluating Scenarios under the Free-Flight Paradigm
Authors: Sherali Hanif D. , Smith J. Cole , Trani Antonio A. , Sale Srinivas
Published: April 2003

Free-Flight is a paradigm of aircraft operations that permits the selection of more cost-effective routes for flights rather than simple traversals between designated way-points, from various origins to different destinations. In this paper, we consider the effect of this paradigm on sector workloads and potential conflicts or collision risks, based on current and projected levels of commercial air traffic. To accomplish this task, we first develop an Airspace Sector Occupancy Model (AOM) that identifies the occupancies of flights within three-dimensional (possibly nonconvex) regions of space called sectors, by utilizing an iterative procedure to trace each flight's progress through sector modules, that constitute the sectors. Next, we develop an Aircraft Encounter Model (AEM), which uses the information obtained from AOM to efficiently estimate the number and nature of blind-conflicts (i.e., conflicts under no avoidance or resolution maneuvers) resulting from a selected mix of flight plans. Besides identifying the existence of a conflict, AEM also provides useful information on the severity of the conflict and its geometry, such as the faces across which an intruder enters and exits the protective shell or envelope of another aircraft, the duration of intrusion, its relative heading, and the point of closest approach. For purposes of evaluation and assessment, we also develop a metric that provides a summary of the conflicts in terms of severities and difficulty of resolution. Finally, we apply these models to real data provided by the Federal Aviation Administration (FAA) for evaluating several Free-Flight scenarios under wind-optimized conditions. This study constitutes the first phase of a project undertaken by a joint FAA/Eurocontrol Collision Risk Modeling Group to develop tasks for investigating air traffic control strategies and related workload and collision risk consequences under various scenarios. Follow-on work will incorporate pilot blunders, random deviations, and air traffic control man-in-the-loop maneuvers within the context of the Free-Flight paradigm, using the basic tools developed in the present study.
Airline Crew Recovery
Authors: Lettovský Ladislav , Johnson Ellis L. , Nemhauser George L.
Published: April 2003

An airline schedule rarely operates as planned. It is often disrupted by maintenance problems or severe weather conditions. In a typical day, several flights may be delayed or canceled, and aircraft and crews may miss the rest of their assigned flights. Airline coordinators have to find a minimal cost reassignment of aircraft and crews that satisfies all required safety rules, has little impact on passengers, and minimizes operational difficulties for the airline. The size of the entire schedule and the real-time nature of the problem rule out a full-scale optimization. It is necessary to reduce the complexity and the size of the problem before an optimization approach can be applied. In this paper, we focus on the problem of airline crew recovery. A new solution framework is developed, implemented, and tested. It provides, in almost real time, a recovery plan for reassigning crews to restore a disrupted crew schedule. Preprocessing techniques are applied to extract a subset of the schedule for rescheduling. A fast crew-pairing generator is built that enumerates feasible continuations of partially flown crew trips. Several branching strategies are presented that allow fast generation of integer solutions. We disturb the current schedule as little as possible, exploiting the fact that the planned schedule is optimal. The proposed framework has been implemented using tree-based data structures for efficient storage and data access. Computational results using a schedule from a major air carrier are presented.