Education DEVELOPMENT AND VALIDATION OF A TOOL FOR ASSIGNING STUDENTS TO GROUPS FOR CLASS PROJECTS*

Group project work is an integral part of many university courses. Assigning students to project groups can be difficult because of the students' diverse backgrounds. Many instructors therefore decide not to assign group projects. This paper develops and validates an instrument that assigns both experienced and inexperienced students to different project groups, thereby creating a balanced, fair environment. The instrument is checked for reliability and validity and then is used to assign students to different project groups. Based on group performance, the end-of-the-semester results also are provided. Path analysis is used to test a causal model. Conclusions and implications for future research are presented.     

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.     

Generalized symmetric weight assignment technique: Incorporating managerial preferences in data envelopment analysis using a penalty function

In this paper, we generalize the Symmetric Weight Assignment Technique to incorporate all managerial preferences in Data Envelopment Analysis (DEA). This is a method that promotes managerial preferences, while not changing the feasibility region of the nominal DEA model, unlike standard techniques such as cone ratio and assurance region that potentially yield infeasible problems. We discuss how this generalization is motivated by a real word problem where the decision maker's preference is not precisely known. We also discuss how we are using our generalization in solving a workforce allocation problem for the United States Navy.     

A LARGE-SCALE PERSONNEL ASSIGNMENT MODEL FOR THE NAVY*

The U.S. Navy has been trying for years to develop a model to automate its personnel assignment process The requirement of rotating navy personnel frequently between sea duty and shore duty in accordance with multiple policies makes modeling efforts difficult. However, without a model to optimize assignments with regard to multiple policies, navy managers do not know the real impact of personnel assignments. This limits their ability to make effective decisions. This paper summarizes our effort to develop a large-scale network model for the navy's assignment problem. The navy has accepted this model for implementation, replacing the current manual assignment process. The approach in this paper can be generalized to a wide variety of perosnnel assignment problems.     

Solving the Multidimensional Assignment Problem by a Cross-Entropy method

The Multidimensional Assignment Problem (MAP) is a higher dimensional version of the linear assignment problem, where we find tuples of elements from given sets, such that the total cost of the tuples is minimal. The MAP has many recognized applications such as data association, target tracking, and resource planning. While the linear assignment problem is solvable in polynomial time, the MAP is NP-hard. In this work, we develop a new approach based on the Cross-Entropy (CE) methods for solving the MAP. Exploiting the special structure of the MAP, we propose an appropriate family of discrete distributions on the feasible set of the MAP that allow us to design an efficient and scalable CE algorithm. The efficiency and scalability of our method are proved via several tests on large-scale problems with up to 5 dimensions and 20 elements in each dimension, which is equivalent to a 0–1 linear program with 3.2 millions binary variables and 100 constraints.     

Improving coordination in an engineer-to-order supply chain using a soft systems approach

An empirical study in the ship-building sector has been undertaken to understand the problems associated with the coordination of engineer-to-order (ETO) supply chains and to reveal insights into opportunities for improvements based on the application of soft systems methodology. A number of alternatives to improve coordination of supply chain have been proposed based on the comparison between a soft systems model and actual practice. These alternatives were summarised into seven general principles that help define the role of individual companies in coordinating ETO supply chains, highlighting the company’s structures and interdependencies that lead to project tardiness. Due to the specific nature of a project which changes according to the context, it is difficult to generalise the soft systems model. Nevertheless, future research can further explore some of the principles proposed to deal with coordination problems experienced in other types of ETO project operations, such as construction and oil and gas.     

College student bereavement experience in a Christian university

As part of the National College Grief Study, college student bereavement experience was examined specifically in a Christian university climate. Sex, year in school, and closeness to the deceased were measured in terms of academic and mental health outcomes and resources utilized. Females reported more mental health problems when close to the deceased, and seniors were less likely than first year students to utilize personal support resources of family and religion. During close losses, students experienced more mental health problems and negative social outcomes, but they did not access more resources. Recommendations for university personnel and suggestions for further research are given.     

DECISION SUPPORT SYSTEMS FOR ILL-STRUCTURED PROBLEMS: AN EMPIRICAL STUDY

Decision support systems (DSSs) are more complex than most other traditional decision-aid systems. For what types of problems are they more effective, and what design characteristics make them more effective? The laboratory experiment reported here examined the effect of three design characteristics of these systems in the context of decision makers faced with ill-structured problems. The characteristics were presence or absence of decision-aid heuristics, degree of interaction between the user and the system, and whether or not the system was computerized. The dependent variables were (1) quality of user performance, (2) user productivity of ideas, (3) user confidence in the quality of his/her performance, (4) user satisfaction with the decision aid or support system, (5) changes in user attitude toward the problem addressed, and (6) changes in user attitude toward computers. Use of heuristics and increased interaction had positive effects on decision quality, user productivity, and attitude toward computers; they had negative effects on user confidence, satisfaction, and attitude toward the problem addressed. Whether or not the system was computerized did not have a significant effect on any dependent variable. The findings concerning negative effects, in particular, suggest the need for research on the design of heuristics for addressing ill-structured problems—heuristics that will deliver the positive but not the negative effects observed in this study. The findings also suggest the need for research on how to benefit from computers in the context of solving ill-structured problems.     

Integrated project operations and personnel scheduling with multiple labour classes

The main theme of this paper is improving project schedules by integrating the scheduling of project jobs and labour resources. An ILP model is presented of the integrated project operations and personnel scheduling problem with multiple labour categories. Traditionally, this problem is solved in two steps: first, operations are scheduled by solving the resource-constrained project scheduling problem; then, labour categories are scheduled by solving the personnel days-off scheduling problem. The proposed model combines the two stages into an integrated problem, which is solved in one step. Using 48 test problems, the two methods were compared in terms of total cost, labour cost and scheduling efficiency. The results clearly indicate that the integrated model outperforms the traditional two-step method.     

DUAL-RESOURCE PARALLEL QUEUES WITH SERVER TRANSFER AND INFORMATION ACCESS DELAYS*

Dual-resource constrained queuing systems contain fewer servers than service facilities. This study uses computer simulation to evaluate several server assignment procedures in a dual-resource system. A field study serves as the basis for developing a model with two service facilities in parallel, a single server, and deterministic information access and transfer delays that can be applied to job shops, computer operating systems, and elevators. Several findings, useful in server assignment decision making, resulted from the study. If first-come, first-served sequencing is used, delaying server assignment at a facility until all jobs are completed reduces both the mean and the variance of job flow time. If shortest-process-time-first sequencing is used, an assignment rule is tested that delays a server at a facility until a sufficiently short job is estimated to have arrived elsewhere. This rule performs best overall in terms of both the mean and variance of flow time. Methods to implement this decision rule easily are discussed.     

Exact and heuristic approaches for the automated design of medical trainees rotation schedules

This article addresses the problem of designing rotation schedules for the training of medical students in a healthcare institution in Colombia. Rotations are carried out along the course of a six months time period during which students rotate through different services both during one or multiple fortnightly periods. The hospital receives trainees from different universities that present heterogeneous requirements, and must accomplish different rotations constraints even in those cases when they come from the same university. Two different approaches are proposed to tackle the problem. First, a mathematical programming model is considered. Secondly, a metaheuristic approach based on Variable Neighborhood Search is adapted to solve the problem in an efficient manner. In both cases the objective function is proposed to be either a linear or a quadratic function that seeks a stable allocation of personnel to the services all along the considered time horizon. The proposed techniques are implemented as a part of a basic spreadsheet that helps personnel in charge generate, validate and fix the proposed plans as needed. The effectiveness of the methodology is tested through ex-post analysis, comparing it against schedules generated by the personnel in charge at the hospital, and over simulated data. The results indicate that the applied metaheuristic is competitive against specialized optimization software and facilitates the work of optimization for the health professionals in charge, reducing the planning tasks from several days to minutes.     

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.     

System Development Project Effectiveness: Problem-Solving Competence as a Moderator Variable*

In spite of end-user programming, for the foreseeable future users and information systems (IS) specialists will build systems together. A better understanding of this partnership (which has a troubled history) will help IS managers and users improve their management skills. This study investigates the relative contributions to project effectiveness of problem-solving competence, the quality of the working relationship, and the quality of the development process. Seventy-five medium-sized projects in 16 organizations were investigated using individual, one hour, structured interviews with the IS project leader and with the primary user. Results suggest that more complex models should be used to study system development. Moreover, problem-solving competence demonstrated a complex effect on project effectiveness.     

Production System Development for Expert Systems Using a Recursive Partitioning Induction Approach: An Application to Mortgage,Commercial, and Consumer Lending

The concepts of expert systems and decision support systems have received considerable attention recently. While systems have been proposed for various problem areas in business, difficulties still exist in the knowledge acquisition phase of development. This paper presents a recursive partitioning analysis (RPA) approach to knowledge acquisition. The RPA production system approach was applied to data sets representing the mortgage, commercial, and consumer lending problems. Comparison of the classification rates across these problems to the results of a generalized inductive inference production system (Quinlan's ID3 algorithm) and across the mortgage and commercial lending problems to traditional statistical modeling approaches indicated that the RPA approach provided superior results while using fewer variables.     

How Software Project Risk Affects Project Performance: An Investigation of the Dimensions of Risk and an Exploratory Model*

To reduce the high failure rate of software projects, managers need better tools to assess and manage software project risk. In order to create such tools, however, information systems researchers must first develop a better understanding of the dimensions of software project risk and how they can affect project performance. Progress in this area has been hindered by: (1) a lack of validated instruments for measuring software project risk that tap into the dimensions of risk that are seen as important by software project managers, and (2) a lack of theory to explain the linkages between various dimensions of software project risk and project performance. In this study, six dimensions of software project risk were identified and reliable and valid measures were developed for each. Guided by sociotechnical systems theory, an exploratory model was developed and tested. The results show that social subsystem risk influences technical subsystem risk, which, in turn, influences the level of project management risk, and ultimately, project performance. The implications of these findings for research and practice are discussed.     

MATHEMATICAL FORMULATION OF THE TASK SEGREGATION PROBLEM IN INTERNAL CONTROL SYSTEM DESIGN*

Segregation of tasks is an important factor in the determination of internal control system reliability. In assigning tasks within an organization, the impact on internal control system reliability must be considered. This paper uses reliability modeling as the basis of a method for formulating the design problem. Formulation of the problem in this manner facilitates development of a knowledge base for auditors' judgments and the use of such knowledge in the design problem. It is demonstrated that under certain conditions the problem can be solved easily. This is useful not only in task assignment but also in manpower decisions. New concepts such as reliability degradation and a task combination matrix are introduced in developing the formulation.     

A NOTE ON THE RELATIONSHIPS AMONG FINENESS,GARBLING, AND SUFFICIENCY FOR THE COMPARISON OF INFORMATION SYSTEMS*

Choice among competing information systems is an important problem for both the providers and users of information. When the attributes of the decision makers and decision problems for which information is produced are unknown or heterogeneous, it is difficult to choose among alternative information sources. Three criteria for such comparisons of information systems are available in the theory of information economics. These criteria may be distinguished by the differing restrictions that they impose on the generality of the studies in which they are used. This note explicates the relationships among these criteria and discusses the various limitations that they impose on generality.     

A UNIVERSITY EXAMINATION-SCHEDULING MODEL TO MINIMIZE MULTIPLE-EXAMINATION DAYS FOR STUDENTS

Scheduling university examinations is often done with the objective of spreading a student's required examinations over an examination week. That is the equivalent of the problem of minimizing the number of examinations a student must take on any one day. An approach to scheduling exams which relates the problem to the classical assignment problem is discussed. The model developed is a symmetry-constrained assignment model, and the solution method requires use of a branch-and-bound algorithm. Results from application of the algorithm to six semesters of actual data are presented.     

Dogmatism and Systems Development Personnel Performance

This research explores the relationship between the personal variable, dogmatism, and the performance evaluations of systems analysts within a Fortune 500 company. The Rokeach Dogmatism Scale was used to measure the analysts’ level of dogmatism. The analysts’ performance measurement was the product of the company's annual evaluation process. The results of the research indicate that personnel with the highest dogmatism scores generally receive the extreme performance ratings. The results of this study provide further support to consider dogmatism as an important personal variable influencing systems analyst job performance.     

A KNOWLEDGE-BASED DSS FOR MANAGERIAL PROBLEM DIAGNOSIS

A knowledge-based system supporting managerial problem diagnosis is described. The system provides the capability to monitor values of selected variables for problem situations. When problems are located, a list of problem symptoms is delivered to a problem processor for structuring and diagnosis. Problem structuring is based on a combination of concepts from expert systems and structural modeling. User assertions about cause-effect relationships between pairs of variables are maintained in a semantic network. Problem diagnosis uses the relationships in the semantic network to construct causation trees, the branches of which represent potential explanations of the problem symptoms. Mathematical models are constructed based on causation-tree branches, and values from the data base are used to test whether the model confirms the diagnosis. If so, the source of the problem has been located and it is then up to the user to resolve the problem. If the model fails to explain the problem, the model apparently is deficient and the user may perform “what if…” type scenarios in attempts to improve the model and search for problem causes. Realistic applications in the accounting and health care areas are discussed.