Decision Support for Bus Operations in a Mass Transit System*

A computerized system has been developed for assigning, parking, and dispatching buses so that each operator in the St. Louis metropolitan transit system generally drives the same bus each day. Combinations of optimizing routines, mathematical heuristics, decision rules from experienced personnel, and human intervention are used to manage the bus operations efficiently. This paper describes the tools created for this task and documents significant improvements in maintenance that occurred after the system became operational.     

Interactive Multiple Objective Decision Support for Sales Force Sizing and Deployment*

An interactive decision aid is introduced for the deployment of two sales resources: salespeople and sales support staff. The aid consists of a normative sales resource allocation model with five objectives and an interactive multiple objective programming solution procedure. The specific decision problem addressed involves the assignment of salespeople and sales support people to customer accounts and the allocation of the time they spend on these accounts. The authors contribute to the existing sales resource modeling literature by dealing with the deployment of two sales resources and interactively solving this problem with respect to five short-run and long-run objectives of the firm. This approach differs from existing sales force modeling efforts in which the solution is found noninteractively by optimizing a single sales resource model with respect to a single objective, often short-run sales. An application of the decision aid to the deployment problem of an industrial sales force manager is presented. Furthermore, useful extensions of the basic sales resource allocation model are discussed.     

Data Driven Modeling: An Application in Scheduling

This paper presents a data driven modeling (DDM) approach to certain types of optimization problems. DDM relinquishes control of the completed model to the user department rather than the operations research (OR) staff. The approach emphasizes development of models that are dependent on data maintained and understood by the users. The data base consists of coded user rules which describe when changes will occur in the problem structure and data which captures the generalization of the problem. Both the rules and data can be updated by user department personnel. These data drive a matrix generator controlled by the rules which uses the data base as input to generate the specific model formulation. This DDM system is designed by OR consultants or staff to allow independence of use along with low-cost and minimal-effort maintenance. The DDM approach is illustrated with an application to a real-world medical scheduling problem.     

Use and Abuse of Weights in Multiple Objective Decision Support Models*

This paper examines difficulties with the use of weights to solve multiple objective decision support models: misunderstanding of the meaning of weights, issues of commensurability and, most important, the likely inability of weights alone to isolate the decision maker's most-preferred point. The constraint method is shown to be an attractive alternative.     

A Decision Support System for Production/ Distribution Planning in Continuous Manufacturing

This paper presents a decision support system (DSS) for managing production/distribution planning in a continuous manufacturing environment. The vendor has multiple plants and distribution centers (DCs). The trading partners have widely varying independent demand patterns. The DSS is designed for use in a multiproduct environment with overlapping raw materials and processing requirements. The production and distribution lead times at plants may span multiple planning periods. The impact of any manual override of a suggested solution can also be evaluated. The DSS is based on a linear programming model with a rolling horizon and was originally designed for a large process industry. Results of a pilot implementation using actual data are also presented, which show potential for significant savings for the company.     

Relative Objective Functions in Multiobjective Decision Support Models*

This paper considers the importance of using the nondominated minimum in forming relative objective functions. Other minima can prevent the decision maker from reaching a preferred decision. They disturb the zero and distort the scale, thereby misguiding the decision maker by falsifying trade-off possibilities. Worse, some of these other minima can inadvertently hide whole regions of preferred solutions. Zeleny's multiple criteria simplex method is used to find the nondominated minimum for the linear case.     

A Computerized Approach to Decision Process Tracing for Decision Support System Design*

We propose the use of computerized process tracing (CPT) tools as an appropriate approach for monitoring the information acquisition and evaluation phase of specific decision processes. CPT tools are unobtrusive and seem particularly relevant for evaluating certain decision tasks that may be supported by decision support systems (DSS). CPT tools can be an important component of DSS development. An information systems research taxonomy developed by previous researchers [29] [36] is used to position research work involving the methodology of CPT. Using a critique suggested by Libby [28], CPT tools are evaluated and compared to alternative process tracing tools. A brief empirical example using CPT is provided, and future uses relative to DSS are suggested. The appendix includes an example of a specific CPT tool.     

Assigning Students to Groups: A Multi-Criteria Decision Support System Approach*

MCADSS is a multi-criteria allocation decision support system for assisting in the task of allocating students to groups. Based on multiple criteria, MCADSS's goal is to maximize the diversity of members within groups, while minimizing the average differences between groups. The project may be viewed from several perspectives: as a multi-criteria decision-making problem, as a “reverse'’clustering problem, or as a personnel assignment problem. The system is currently being used to allocate M.B.A. students into sections and study teams at The European Institute of Business Administration (INSEAD). This paper describes the rationale for MCADSS, design criteria, system methodology, and application results. It also suggests how this approach could be used for further applications.     

Strategic Assessment Model (SAM): A Multiple Criteria Decision Support System for Evaluation of Strategic Alternatives*

The evaluation of strategic alternatives is a particularly difficult task. This difficulty is due to the complexities inherent in the evaluation process and the lack of structured information. The evaluation process must consider a multitude of relevant information from both the internal and external environments of the organization. Various analytical and normative models have helped decision makers utilize large volumes of information in strategic evaluation; however, most of these models have some limitations. We present a multiple criteria decision support system, called strategic assessment model (SAM), that addresses some of the limitations inherent in the existing models. SAM captures the decision maker's beliefs through a series of sequential, rational, and analytical processes. The environmental forces—decomposed into internal, task, general opportunities, and threats—are used along with the analytic hierarchy process (AHP), subjective probabilities, the entropy concept, and utility theory to enhance the decision maker's intuition in evaluating a set of strategic alternatives.     

Supply Chains in Sub‐Saharan Africa: A Decision Support System for Small‐Scale Seed Entrepreneurs*

It is necessary to infuse a consistent supply of improved seed varieties into local sub‐Saharan African crop production to improve low crop yields. The best distribution channel for the improved seed varieties may be small‐scale commercial seed companies, but local entrepreneurs struggle to determine whether such businesses are viable. Using a multi‐echelon supply chain approach, a decision support system (DSS) was designed to help African seed entrepreneurs make informed decisions about small‐scale seed chain businesses. Specifically, entrepreneurs make decisions about where to locate seed enterprises, with which farmers to contract, and where to store seed. Optimization and simulation modeling are used to evaluate infrastructure variables such as distance, transportation cost, and storage loss and cost in three development level areas. Currently, the decision tool is used in Mozambique, Malawi, Kenya, and Tanzania. The model has supported the start‐up of at least 17 small seed companies that are now introducing improved seed varieties into villages and farms. The DSS applies decision science research in a humanitarian application and offers important managerial implications about supply chain infrastructure to nongovernmental organizations and humanitarian groups. Such applications are vital as groups such as USAID, the Gates Foundation, and the International Crops Research Institute for the Semi‐Arid Tropics (ICRISAT) continue to move toward micro‐enterprise, value chain, and market‐oriented development programs.     

Linking Objectives to Actions: A Decision Support Approach Based on Cause–Effect Linkages

The process of translating objectives into actions is a difficult task. This difficulty is due to the wide range of possibilities and the lack of structured information. Managers must take into account relevant information and generate a range of options before a decision is reached. So far, little is available to guide managers in translating a set of objectives into actions. This paper presents a three‐stage action‐planning process to address this gap. The process, supported by a software tool, takes managers through the stages of model building, action generation, and action evaluation and selection. A case study illustrates the application of the process. The paper concludes by discussing the implication of this work for managers and academics.     

Decision support systems for production scheduling tasks- Part I of a case study: Analysis and task redesign

The first three steps of a new design method for decision support systems in production scheduling tasks are applied to a large bulk terminal. The operational characteristics of the company largely correspond with those of typical semiprocess industries. The design model used consists of five steps: production analysis, task analysis, task redesign, decision support design and decision support implementation. The results of the application of the design model up to the task redesign step are described.     

Automating Knowledge Acquisition and Refinement for Decision Support: A Connectionist Inductive Inference Model*

An important application of expert systems technology is to provide support for nonstructured decision making. Usually, nonstructured decision making is characterized by heavy reliance on heuristic knowledge, which is very difficult to articulate or document, and therefore traditional knowledge acquisition approaches are not very successful. The quality and effectiveness of an expert system supporting unstructured decision making is affected when traditional knowledge acquisition approaches are used. To alleviate this problem a model is proposed that combines inductive inference and neural network computing, and an example is presented that illustrates the potential of this model in unstructured decision support.     

An Evaluation of the Role and Performance of a Decision Support System in Business Education*

With the rapid growth in end-user computing, there has been an increasing demand on business schools to train managers in the use of computers for effective decision support. While computer-aided instruction (CAI) has been in vogue for over a decade, there are very few studies that evaluate the impact of computers on decision-making skills in a business education context. The study makes use of a controlled experiment to evaluate the impact of computers on the accuracy and quality of decision making in a business decision support context. It also addresses the relationships between decision performance and various student characteristics such as aptitude, attitude, domain experience, domain expertise, gender, and system experience. The study revealed that computer support positively influenced both dimensions of decision performance.     

Decision Models for Robot Selection: A Comparison of Ordinary Least Squares and Linear Goal Programming Methods

The profusion of robot designs, the cost of testing, and the fact that robot operational parameter maximums are often mutually exclusive are factors that create a complex selection decision for the potential user. While formal robot testing standards are now in place, formal techniques to select robots for the testing process have not been addressed. A linear goal programming model is an effective tool for the decision maker for optimizing the robot selection process in terms of requirement priorities. It is also shown that this model provides a more stable result than the ordinary least squares estimator in the presence of statistical outliers of robot parameters. The methodology is illustrated through the use of current robot specifications.     

The Design of a Knowledge-Based Decision Support System to Support the Information Analyst in Determining Requirements

Decision support system (DSS) researchers and designers continue to look for unstructured organizational tasks where there is a critical need for intelligent computer-based support. One such decision task is information requirements determination. Requirements determination is recognized as the most crucial phase of the systems development life cycle. Unfortunately, most methodologies and CASE tools focus only on how to specify the requirements once they are determined. There is very little computer support for the process of determining requirements. This paper discusses the conceptual design and development of a knowledge-based DSS to support information analysts in the critical decision task of determining requirements for the design of effective information systems. The expert modeling support system has the expertise to assist the analyst in studying the organization as a whole and in modeling the system under study in the context of the overall organization's goals and needs. The focus of the paper is on the problems associated with building the knowledge base component of the intelligent decision support system. A prototype implementation of the system is described.     

An Empirical Investigation of Information Search Strategies with Implications for Decision Support System Design

Understanding how people search through and combine information before making decisions is an important concern in the study of decision making and in the design of decision support systems (DSS). The purpose of this study is to examine DSS search strategies in relation to the body of empirical research on information load. Prior research is examined in relation to basic empirically-testable hypotheses and compared to the results of this study as a way of validating the procedures used here. The transfer of information load empirical research to a DSS scenario is confirmed statistically. Then, results of an analysis of information search patterns under DSS conditions are described. Finally, implications for DSS design are discussed in terms of possible search support mechanisms for specific search strategies.     

Decision Making in an Automated Environment: The Effects of Anonymity and Proximity with a Group Decision Support System*

Recent advances in information systems technology have made it possible to support the work of interacting groups using networked personal computers. A laboratory experiment was conducted using a group decision support system to evaluate effects of anonymity and proximity on group process in automated group problem solving. Twenty groups of four persons each performed an idea-generating task using an interactive electronic brainstorming program. This experiment's main findings were: (1) Group members working anonymously and apart generated more comments. (2) Working in the same room increased satisfaction. (3) Highest levels of perceived system effectiveness were reported under anonymity.     

A Prototype Expert Decision Support System for the Market Appraisal of the Single Family Residence

The assessment of the current market value of residential property is a potential source of anxiety for the typical homeowner. Common criticisms of the existing appraisal process include excessive subjectivity and inconsistency across properties and through time. This paper examines the nature of decision support required for valuation decisions and the appropriateness of applying expert system technologies to evaluate the recoverable value of the single-family residence. The expert system approach allows for the integration of the qualitative and quantitative aspects of appraisal, while introducing the beneficial dimensions of increased objectivity, comprehensiveness, and consistency. A prototype expert system is offered that enables the end user to conduct a market analysis of a subject property. Unlike most expert system applications that seek a diagnostic or classification response, this study explores a numerical intent for the system, in a decision-making environment that is traditionally viewed as highly judgmental. The system's early validation results show promise of proving effective as such an evaluation aid.     

Knowledge Representation and Reasoning in a Real-Time Operational Control System: The Shipboard Piloting Expert System (SPES)*

This paper describes a knowledge representation approach and reasoning implementation in a real-time knowledge-based control system (KBCS) for navigating ships in restricted waters. This shipboard piloting expert system (SPES) is being developed as an intelligent node in Sperry Marine's ExxBridge integrated ship's bridge system (IBS) for Exxon Shipping Company tankers. The SPES is intended to provide decision support to ships' navigation officers while piloting large vessels in restricted waters, and to reduce the information overload under which they labor, by incorporating local, transit-specific, and shiphandling knowledge, and by providing requisite decision support in a timely fashion. As such, the system provides decision support to (1) senior ships' pilots training junior pilots; (2) ships' masters training junior deck officers in the essentials of good piloting and shiphandling; and (3) watchstanding deck officers utilizing the system's on-line reminder and assist capabilities, or off-line simulation and contingency planning functionality.