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FROM THE BOOKSHELF

ANDREW RUPPEL, Feature Editor, McIntire School of Commerce,
University of Virginia

Some 1997 Releases of Note

by Andrew Ruppel, Feature Editor

The incorporation of solver routines into the various PC spreadsheet packages enabled them to move out of the confines of financial statement construction and statistical data analysis into the broader arena of management science. Cliff Ragsdale's Spreadsheet Modeling and Decision Analysis (Course Technology, 1995) was one of the first full-length textbooks to take advantage of this advance (as implemented in Microsoft Excel). Two additional full-length management science textbooks exploiting Excel and its solver have become available that instructors should also give consideration tožone by Rick Hesse and the other by Whinston & Albright.

Managerial Spreadsheet Modeling and Analysis
Rick Hesse
Irwin, 1997
685 pages, http://www.irwin.com


Practical Management Science: Spreadsheet Modeling and Applications
Wayne L. Winston and S. Christian Albright
Duxbury, 1997
796 pages, http://www.thomson.com


The scope of each volume is pretty much identical to the other, with linear programming topics dominating the coverage. Both have forecasting, simulation, and decision analysis chapters plus an opening section of what modeling is all about. Hesse strives to employ a four-step approach throughout his book: Picture & Paraphrase, Compose a Verbal Model, Write an Algebraic Model, and Formulate the Spreadsheet Model. This approach has the advantage of bringing both sides of the brain into play in problem-finding and framing. Additionally, it's a good process to use with the team approach, because team members usually have different backgrounds and ways of looking at problems. The explicitness forced by first sketching, writing, and then manipulating symbols is likely to yield more creative problem structuring and ultimate solution finding.

Winston & Albright opt for a seven-step modeling process: Definition, Data Collection, Formulation, Verification & Prediction, Selection, Presentation, and Implementation & Evaluation. They do not, however, use the seven steps per se to roll out their material over the course of the whole book.

Both texts provide numerous examples, problems, and cases, along with data disks. Winston & Albright bring in more cases and examples from outside sources and provide tie-in exercises and references. (Contributor Mark Broadie helped them out on the case studies.) Nice touches in the Winston & Albright text include an inside-cover list of examples by functional area (operations management dominates, followed by finance, then marketing) and clear screen reproductions. The Hesse text provides check figures for students on selected exercises, a handy end-of-chapter roster of the templates used, and a key-terms list. At the risk of over-generalizing, Winston & Albright's text is more traditionally academic, while Hesse's is more personally pedagogic.


A wider variety of software is available for teaching statistics than for teaching management science, but Excel appears to be making inroads in statistics instruction as well. The following new release is a good example.

Statistics for Managers Using Microsoft Excel
David M. Levine, Mark L. Berenson, and David Stephan
Prentice-Hall, 199
716+ pages, http://www.prenhall.com


An attractively presented treatment of basic business statistics that effectively and comprehensively weaves Excel procedures into the discussion. Its 13 chapters cover the customary topics of descriptive and inferential statistics plus quality control techniques, regression, and time series forecasting. The forecasting chapter is confined to examining annual data (thus one is puzzled why exponential smoothing is covered here). And the multiple regression chapter tells of multicollinearity, but not how to deal with it. There is a good front-end introduction for the Excel material. Here the concept of what-if analysis is introduced very early on. This is a plus for subsequent examination of variations in input data in the different statistical techniques. Curiously, a photograph of a deck of cards, splayed out by suit, appears in the probability chapter and there is an appendix reviewing arithmetic and algebra. (Is this saying something about the expected background of tomorrow's would-be managers??) End-of chapter items include flowchart summaries, key terms, problems, cases, and team projects. A data disk also comes with the book.


Excel also makes an appearance, albeit a suitably supplementary one, in this updated introductory text by Jim Evans.

Production/Operations Management, 5th ed.
James R. Evans
West Publishing, 1997
790+ pages, http://www.westpub.com


An established text in the field, the 5th edition brings in more application examples and a more concentrated emphasis on quality, performance, and value. The nineteen chapters are organized into five sections: Foundations, Strategic issues, followed by one each on managing processes, managing materials, and managing time (i.e., planning and scheduling). Additionally, there are five supplements covering the usual quantitative topics associated with POM. Thus, instructors are afforded flexibility in course design; they can either take a quantitative route or a strategic route using this text.


Excel makes no appearance inside the pages of the next two titles.

Organizational Decision Making
Zur Shapira, ed.
Cambridge University Press, 1997
397 pages, http://www.cup.org


eading this volume is a good way for hard decision scientists to catch up on what those from the soft side have been thinking about. Sponsored by the Society for Judgment and Decision Making, it contains 16 chapters (by a total of 23 authors), each with an extensive list of references, covering the psychological and social science aspects of decisions in organizations. The chapters are organized into five sections: Introduction, Information Processing and Attention Allocation, Preference Processing, Decision Processes, and Alternatives Approaches. This last section includes an essay by Cannily & Kaput on ``naturalistic decision making,'' which turns out to be a grab-bag of ways to think about (but not necessarily resolve) the shortcomings of utility-measure approaches in time-pressured, yet often strung-out, multi-ambiguous decision settings. Another essay, by E.S. O'Connor, looks at decision episodes from a narrative, story-telling viewpoint. To this reader, these last two essays don't provide enough closure to be satisfying.

Three of the chapters that were satisfying to this reviewer were: James March's ``Understanding how decisions happen in organizations;'' Fischoff & Johnson's ``The possibility of distributed decision making;'' and Xueguang Zhou's ``Organizational decision making as rule following.'' March's preoccupation with organizational decision making does not prevent him from appreciating the individual's perspective, as this quote from his essay indicates: ``Decision making is a prime arena for developing and enjoying an interpretation of life and one's position in it.'' Research on decisions by individuals is recapped nicely in the essay by Fischoff & Johnson before they move on to discussing how distributed decision making is differentžnamely, the decisions are made by individuals who are interdependent but responsible for in completely overlapping portions of perhaps more than one problem. The challenge thus becomes how to create ``shared mental models of the system.'' Readers interested in group decision making should obviously find this particular essay of interest. Zhou's chapter sees organizational decision making dominated more by the logic of appropriateness than by the logic of optimization. Zhou is clearly tuning in to the well-recognized distinction of structured (or programmed) decision versus ill-structured (and therefore, non-programmable) ones. Rules help manage conflict and uncertainty, and help the organization retain its learning. They help to economize on information needs and eliminate alternatives. Thus to the notion of bounded rationality, Zhou adds collective and contextual rationality. Overall, this collection of essays fulfills its sponsor's ambition of providing a richer (yet still question-filled) understanding of organizational decision making.

Making Multi-Objective Decisions
Mansooreh Mollaghasemi and Julia Pet-Edwards
IEEE Computer Society Press, 1997
91 pp., http://www.computer.org


Here's a handy monograph, providing as it does a useful summary of methods for multiple criteria decision making (MCDM). In five chapters it covers 13 methods grouped into three categories based on the timing of preference articulation: those with preferences expressed in advance, those done along the way, and those done afterwards. The first category includes the Analytic Hierarchy Process. The second category includes interactive methods linked to mathematical programming. In the third category, the authors focus on Data Envelopment Analysis. They see DEA more as an aid to further choice as opposed to identifying a specific choice. At least one application, as reported in the literature, is given for each of the models discussed. In the final chapter, the authors discuss the pros and cons of the various methods, including commentary on available software (only three of the 13 methods require special software). Each chapter includes an annotated bibliography as well as a list of references cited. The book has no index, but its clear organization makes one unnecessary. Every decision science doctoral student should have this slim volume in their personal library.