William B. Richmond
George Mason University
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Featured researches published by William B. Richmond.
decision support systems | 1992
William B. Richmond; Abraham Seidmann; Andrew B. Whinston
Abstract Outsourcing is the subcontracting of some or all the information systems functions by one firm to another. An incomplete contracting framework is used to examine the relative merits of outsourcing certain information systems development tasks. The focus is on investigating the effects of information asymmetry and different profit sharing rules on the decision of whether to outsource or to use an internal development team. The modeling indicates that the value generated from outsourcing the development effort comes primarily from the specific investments made by the external group, and that outsourcing dominates internal development when this investment is relatively more important than investments by the internal user group. This provides one economic explanation for the coexistence of both internal development teams and of various outsourcing services.
Journal of Management Information Systems | 1993
William B. Richmond; Abraham Seidmann
We address the case where a user contracts for the delivery of a new information system from an independent vendor, both of whom are risk-neutral. The delivery task is partitioned into two consecutive stages: system design and software development. The parties can contract for each stage separately or specify an initial contract that covers both stages. We compare the impact of different contracting structures on prices, project value, project completion probability, and the value to the developer of obtaining the first stage of the contract. Specifically, we show that a two-stage contracting can lead to a higher business value than stage-by-stage contracting. When there is competition for the design stage, the vendors bear more of the software development risk, and the probability the system will be completed depends on the contract structure.
ACM Transactions on Database Systems | 1990
James C. Moore; William B. Richmond; Andrew B. Whinston
We present the file search problem in a decision-theoretic framework, and discuss a variation of it that we call the common index problem. The goal of the common index problem is to return the best available record in the file, where best is in terms of a class of user preferences. We use dynamic programming to construct an optimal algorithm using two different optimality criteria, and we develop sufficient conditions for obtaining complete information.
Computational Economics | 1988
James C. Moore; William B. Richmond; Andrew B. Whinston
We investigate the relationship between algorithm construction and optimal decision processes. We provide a sufficient condition, a linear ordering over the experiment set, for when we can efficiently use an optimization approach for selecting a decision strategy. We demonstrate the linear ordering condition within the context of the file search problem; however, any problem whose representation satisfies the linear ordering condition is amenable to the optimization approach.
Information Technology & Management | 2006
William B. Richmond; Paul Nelson; Sanjog Misra
This paper presents an empirical analysis of the life span of over 180 systems aimed at developing a model for determining the planning horizon for new software at the business case stage of software acquisition. At this early stage, the firm has limited knowledge about the project, but must make crucial decisions, such as scope (breadth of requirements), approach (both insource vs. outsource and custom vs. package) and technology, including fit with standards (adhere to current vs. adopt new technology). These decisions are associated with different system lifetimes that, in turn, impact both the costs incurred and benefits received from the system. The failure to explicitly and properly address these differences can lead to the implementation of systems better left undone or to unintended consequences, such as the Y2K problem. We find that technology and approach, but not scope decisions are strongly related to system lifetime. In particular, systems that use an operating system that conforms to the firm’s standard or are acquired using a blended team entail longer system life. On the other hand, shorter system life is indicated if the system is technically complex, custom developed or uses an older programming language. Furthermore, modified packaged software is shorter lived than is a vanilla package. In addition, environmental variables also impact the appropriate horizon. For example, as one would expect, strategic systems are used longer. On the other hand, somewhat surprisingly, systems sponsored by executives last less long and despite the quickening pace of technological and business process advancement, a small trend toward longer lived systems is uncovered.
Journal of Economic Dynamics and Control | 1990
James C. Moore; William B. Richmond; Andrew B. Whinston
Abstract Economic decision theory, information economics, and computer algorithm theory are combined to develop sufficient conditions for using an optimization approach to the construction of algorithms or decision processes. Two algorithms are constructed based on composite experiments, each composite experiment being composed of primary experiments. The composite experiment can be viewed as being executed on a parallel computer. The parallel computer can in turn be viewed as an organization or team. Under this interpretation, we provide a sufficient condition for optimally delegating a task to a group of subordinates.
European Journal of Operational Research | 1996
Hsing K. Cheng; Marshall Freimer; William B. Richmond; Ushio Sumita
Abstract This paper presents the optimal allocation and backup of computing resources in a multidivisional firm in the presence of asymmetric information and incentive incompatibility. A game-theoretic model is developed and transformed to a linear programming problem. The solution to this linear programming problem enables the corporate headquarters to design a resource allocation scheme such that the revelation principle prevails and all divisions tell the truth. To cope with the combinatorial explosion of complexity caused by the resource constraint, a greedy-type algorithm and an averaged version of the original linear programming problem are developed to provide the upper and lower bounds. The greedy-type algorithm generates exact solutions for a wide range of instances. The lower bounds coincide with the exact solutions for the cases where the computer resource is either scarce or abundant. The averaged-version resource allocation model with slight modifications solves the optimal computer backup capacity problem. It determines how much back up capacity the firm should purchase when the firms computer breaks down.
Computers & Operations Research | 1998
Hsing K. Cheng; Marshall Freimer; William B. Richmond; Ushio Sumita
Abstract This paper presents the optimal repair policy of a firms fault-tolerant computer system where asymmetric information and incentive incompatibility problems in allocating the computing resources are prevalent. Traditional maintenance optimization theory focuses on optimization models for repair, replacement, and inspection of machines (computers) subject to breakdowns or deterioration, without considering the allocation of such resources. Likewise, performance evaluation literature of fault-tolerant computers concentrates on deriving reliability and availability measures. This paper is a first attempt to jointly examine both the resource allocation and repair problems of a firms fault-tolerant computer system. This paper presents the optimal repair policy of a firms computer system in the presence of asymmetric information and incentive incompatibility. It applies the resource allocation model developed by Cheng et al. [Cheng, H. K., Freimer, M., Richmond, W., Sumita, U., Optimal allocation and backup of computer resources under asymmetric information and incentive incompatibility. European Journal of Operational Research , 1992, 91 , 411–426] to analyze the impact of asymmetric information and incentive incompatibility on the repair policy of a firms fault-tolerant computer system whose capacity degrades over time. A general methodology is presented for deriving the optimal repair policy for the firms computer system by integrating the results from the resource allocation problem and the stochastic model describing the degrading capacity behavior of the computer system. The optimal repair policy is demonstrated via numerical results that offer useful insights. In particular, the conventional wisdom of having a largest asymptotic expected computer capacity does not guarantee a desirable long-run minimum cost to the organization.
Archive | 1994
James C. Moore; William B. Richmond; Andrew B. Whinston
We present a decision model that can be interpreted as an economic decision model for a decision maker under bounded rationality; as a behavioral decision model where the decision maker makes tradeoffs between the accuracy of the decision and the effort to make the decision; as a general model of computation amenable to both von Neuman computers and parallel computers; as a model for constructing information systems from a library of reusable code or objects; and as a model of organizational decision making. Although the model is general enough to encompass these (plus other) areas, it is powerful enough to achieve interesting results when properly specialized.
Journal of Information Technology Teaching Cases | 2018
Robert B. Carton; William B. Richmond
This case is a set of leadership role-plays that address several critical IT issues including understanding (1) differing objectives of critical project stakeholders; (2) concepts of change management and their importance and process; (3) escalation issues of when and how to do it; and (4) issues arising from client/customer communication. The case combines role-plays with traditional case discussion. The scenario is an IT manager of a large university leading an ERP implementation that must satisfy differing stakeholders including academic, administrative, and curriculum leadership. The case highlights problems of objective alignment, execution, and communication.