William Remus, Ph.D.
Department of
Remus@hawaii.edu
William Remus is an Emeritus
Professor of Information Technology Management at the
Overall he has published over 100 scientific papers including over 60 refereed
journal articles, 5 books, and 5 book chapters. The best of this work has
appeared in Management Science, Management Information Systems Quarterly, Organizational Behavior and Human Decision Processes,
and International Journal of Forecasting. A
1996 citation analysis of the research on Decision Support ranks him 6th in the
world in his contribution to research in cognitive factors and 10th in the
world in research on interface design (Eom in Decision
Support Systems, 1996). His work has been described in the Wall Street
Journal and The Chronicle of Higher Education.
William Remus is an award winning researcher and
teacher. He has won numerous teaching awards including the
Dr. Remus is the past Graduate Chair of the Interdisciplinary Doctoral Program in Communication and Information Science. Also he was involved in the Global Information Technology Management Doctoral Program.
For relaxation, he plays the music of Indonesia with the Gamelan Ensemble; they
play Gamelan in the style of Surakarta, Yogjarkarta,
and Bali.
Human
Judgement
O'Connor, M., Remus, W., and K. Griggs, Does Updating Judgmental Forecasts Improve Forecast Accuracy? International Journal of Forecasting, 2000, 16, 101-109.
In this study we determined that it is worthwhile to update forecasts only when some meaningful structural changes has occurred. Otherwise the update only adds to the forecast error.
Nelson, M., T. Hill, W. Remus and M. O'Connor, Time Series Forecasting Using Neural Networks: Should the Data Be Deseasonalized First? Journal of Forecasting, 1999, 18(5/6), 359-370.
Neural networks are universal approximators but require additional nodes for additional approximations of deseasonalization of data. Thus our simulations demonstrate that it is better to do the deseasonalization by ordinary means then automatically using neural networks.
Remus, W., O'Connor, M. and K. Griggs, The Impact of Incentives on the Accuracy of Subjects in Judgmental Forecasting Experiments, International Journal of Forecasting, 1998, 14, 515-522.
Behavioral studies are often attacked on the grounds that the subjects may not be adequately motivated to do the experimental task well. Here we review the literature and conduct a study to assess the impact of incentives of subject's forecast accuracy. The incentives did not improve the subject's forecast accuracy.
Remus, W., O'Connor, M. and K. Griggs, The Impact of Information of Unknown Correctness on the Judgmental Forecasting Process, International Journal of Forecasting, 1998, 14, pp. 313-322.
In the study, people are asked to extrapolate times series when major changes occur in the time series structure and both correct and misinformation provided. We found that the more correct information, the better the forecast accuracy. However, there was no difference between misinformation and no information at all. Thus the forecasters were not misled by misinformation.
W. Remus and J. Kottemann, J., Towards a Theory of Cognitive Style in Decision Making, Journal of Psychological Type, 1998, 46, pp. 6-12.
This reviews the literature on cognitive style in decision making and reports an experiment that tests a model for cognitive factors (Myers Briggs Type Indicator and Risk Avoidance) in steady state managerial decision making. JP and TF turn out to effect consistency that in turn effects economic performance.
O'Connor, M., W. Remus and K. Griggs, Going up - going down: how good are people at forecasting trends and changes in trends? Journal of Forecasting, 1997, 16, pp. 165-176.
People tend to react differently to upwardly and downwardly trending data. This paper reviews the literature on this topic and tests it in the context of judgmental forecasting. The effect is found to occur in judgmental forecasting.
W. Remus, M. O'Connor, and K. Griggs, Does Feedback Improve the Accuracy of Recurrent Judgmental Forecasts? Organizational Behavior and Human Decision Processes, 1996, 66(1), pp. 22-30.
This article finds new and effective ways to improve people's ability to make forecasts - the use of task feedback.
W. Remus, M. O'Connor, and K. Griggs, Will Reliable Information Improve the Judgmental Forecasting Process? International Journal of Forecasting, 1995, 11, pp. 285-293.
In this study, people are asked to extrapolate times series when major changes occur in the time series structure and various levels of reliable information provided. We replicated our earlier work finding models superior to humans in this task (International Journal of Forecasting, 1993). We also found that the more reliable the information the better the forecasts; however, simple forecasting models still did better than people.
Remus, W. and J. Kottemann, A Test of the Anchor & Adjustment Model for Decision Making, Decision Support Systems, 1995, 15, pp. 63-74.
The Kahnemann & Tversky anchor and adjustment model was operationalized several ways and compared with several other models for managerial decision making. It neither fit their decisions well nor did it yield low costs.
Davis, F., J. Kottemann and W. Remus, Computer Assisted Decision Making: Performance, Beliefs, and the Illusion of Control, Organizational Behavior and Human Decision Processes, 1994, 57, pp. 26-37.
This paper reports an experiment that found that what-if analysis could cause managers not to perform better but instead to become overconfident.
O'Connor, M., W. Remus and K. Griggs, Judgmental Forecasting in Times of Change, International Journal of Forecasting, 1993, 9(2), pp. 163-172.
People are often preferred to forecasting models when structural changes in the forecasting environment are expected to occur. In the study we tested that axiom; people were asked to extrapolate times series when major changes occur in the time series structure. Humans did not do as well as forecasting models.
Kottemann, J. and W. Remus, The Effect of Planning Horizon on the Effectiveness of What-If Analysis, Omega, The International Journal of Management Science, 1992, 20(3), pp. 295-301.
This paper reports an experiment that found that what-if analysis could cause managers to be overconfident but this effect was a function of the planning horizon. The longer the horizon, the worse the effect.
Remus, W., Criterion Referenced Judgmental Forecasting Models, Journal of Forecasting, 1991, 10(4), pp. 415-424.
This article provides the mathematical basis for the selection of the best judgmental forecasting model where U-shaped criterion functions exist.
Kottemann, J. and W. Remus, A Study of the Relationship Between Decision Model Naturalness and Performance, Management Information Systems Quarterly, 1989, 13(2), pp. 171-182.
This article found that the fit and performance of a decision model are not related. This means that models that fit better may not perform as well as those that have a lesser fit. This is the second part of the National Science Foundation study.
Remus, W., A Study of Graphical and Tabular Displays and Their Interaction with Environmental Complexity, Management Science, 1987, 33(9), pp. 1200-1205.
This is the follow-on to the earlier Management Science article. It replicates the earlier study plus shows a significant interaction between display type and environmental complexity.
Remus, W. and J. Kottemann, Semi-structured Recurring Decisions: An Experimental Study of Decision Making Models and Some Suggestions for DSS, Management Information Systems Quarterly, 1987, 11(2), pp. 233-244.
The study finds tracking artifacts (the "range" effect and lag) in managerial decision making. These artifacts may show anchoring-and-adjustment to be occurring. The first part of the National Science Foundation study.
Remus, W., P. L. Carter and L. O. Jenicke, Improving Decision Making Using Performance Feedback, Operations Research Letters, 1984, 3(2), pp. 105-110.
In this empirical study we examined the effectiveness of feedback in improving decision making. When the environment punishes poor decision making more (i.e. quadratic costs), feedback is more effective. There is, however, a level of feedback beyond which decision making degrades. This result is consistent with several information processing theories.
Remus, W., An Empirical Investigation of the Impact of Graphical and Tabular Data Representations on Decision Making, Management Science, 1984, 30(5), pp. 533-542.
This article reports an empirical study to determine whether graphical or tabular aids are better for aiding decision making. When the error variance was greatly reduced through statistical methodology, tabular aids performed significantly better.
Remus, W., P. L. Carter and L. O. Jenicke, Regression Models in Unstable Environments, Journal of Business Research, 1979, 7(2), pp. 187-196.
In this empirical research study, decision rules were found to be effective in capturing managerial decision making even in the face of instabilities in cost information. During the unstable periods, the rules tracked the changing environment and modeled the learning taking place.
Carter, P. L., W. Remus and L.O. Jenicke, Production Scheduling Decision Rules in Changing and Nonlinear Environments, International Journal of Production Research, 1978, 16(6), pp. 493-496.
In this empirical research study production scheduling rules were found to be more effective in quadratic than in non-quadratic costs. This may explain why this method is not used in industry. Also these rules were found to be effective when the underlying quadratic cost structure changes.
Remus, W., Testing Bowman's Managerial Coefficient Theory Using a Competitive Gaming Environment, Management Science, 1978, 24(8), pp. 827-835.
This paper demonstrates the effectiveness of testing a decision theory by using a competitive gaming environment. All postulates of theory were found to hold. In particular, erratic decision making (variance) was more costly than poor intuitions (bias).
Remus, W. and L. O. Jenicke, Unit and Random Linear Models in Decision Making, Multivariate Behavioral Research, 1978, 13, pp. 215-221.
This article reports a simulation study done to refute the contentions of Dawes and Corrigan about unit and random linear models which was reported in Psychological Bulletin. While correlations were equivalent for regression and unit rules, regression rules yielded lower costs than unit rules.
Remus, W., Bias and Variance in Bowman's Managerial Coefficient Theory, Omega, The International Journal of Management Science, 1978, 5(3), pp. 349-351.
This article provides the mathematical condition under which Bowman's managerial coefficient theory's third postulate holds. It then provides empirical data to show this condition is met in realistic decision making situations.
Artificial Intelligence
Nelson, M., T. Hill, W. Remus and M. O'Connor, Time Series Forecasting Using Neural Networks: Should the Data Be Deseasonalized First? Journal of Forecasting, 1999, 18(5/6), 359-370.
This research determines if deseasonalizing data prior model estimation improves the performance of neural network time series forecasting models. In spite of arguments in the literature to the contrary, deseasonalization does improve forecasting accuracy.
Hill, T., M. O'Connor and W. Remus, Neural Networks for Time Series Forecasting, Management Science, 1996, 42 (7), pp. 1082-1091.
This research compares neural network models with numerous standard forecasting models in forecasting the Makridakis 111 data series. The neural networks did better for both monthly and quarterly series; they were particularly good with discontinuous time series.
Marquez, L., T. Hill, M. O'Connor, and W. Remus, Artificial Neural Networks for Forecasting and Decision Making, International Journal of Forecasting, 1994, 10, pp. 5-15.
In this paper we reviewed all studies comparing neural networks and classical models for forecasting and decision making. They perform comparably (which turns out to be a controversial result and makes many people unhappy).
Hill, T. and W. Remus, Neural Networks for Composite Managerial Judgment, Decision Support Systems, 1994, 11, pp. 449-459.
In this paper we compared several neural networks with linear regression in capturing composite managerial judgment. Neural networks give superior cost performance in the production scheduling task.
Remus, W. and T. Hill, Neural Networks of Managerial Judgment, Advances in Artificial Intelligence in Economics, Finance, and Management, 1994, 1, 177-191.
In this article we compared several neural networks with linear regression in capturing managerial judgment. Linear regression fit a little better but both gave similar cost performance in the production scheduling task.
Kottemann, J. and W. Remus, Evidence and Principles of Functional and Dysfunctional DSS, Omega, The International Journal of Management Science, 1987, 15(2), pp. 135-143.
This provides a review of the literature of the impact of various factors on DSS performance.
Remus, W. and J. Kottemann, Toward Intelligent Decision Support Systems: A Proposal for an Artificially Intelligent Statistician, Management Information System Quarterly, 1986, 10(4), pp. 403-418.
The article proposes how statistical rules, heuristics, and data could be handled by an Artificially Intelligent statistician. The article also suggests how this might reduce cognitive limitations of human decision makers.
Farwell, D. and W. Remus, A Decision Support System for Business School Accreditation, Journal of Computer Information Systems, 1985, 15(2), pp.10-12.
This article reports the use of a DSS to prepare
the
Issues
in Research Methodology
Remus, W., O'Connor, M. and K. Griggs, The Impact of
Incentives on the Accuracy of Subjects in Judgmental Forecasting Experiments, International
Journal of Forecasting, 1998, 14, 515-522.
Prior to this study it was not clear whether or not monetary incentives improved the forecasting accuracy of subjects in judgmental forecasting experiments. It turns out that neither payments nor prizes improve forecasting accuracy.
Remus, W., Will Information Systems Research Generalized to Managers? Managerial and Decision Economics, 1996, 17, pp. 93-101.
This paper reports an experiment that compares the decision performance of undergraduate students and business people. The latter perform better and are more consistent.
Remus, W., The Robustness of a Linear Model of the Admissions Decision, Omega, The International Journal of Management Science, 1986, 14(2), pp. 185-187.
Moskowitz et al. replicated our earlier study on linear models of the production scheduling problem. Their generalizations were extended to the admissions decision.
Remus, W., An Empirical Test of the Use of Graduate Students as Surrogates for Managers in Experiments on Business Decision Making, Journal of Business Research, 1986, 14(1), pp. 20-30.
The literature is rife with concern about whether experimental results apply to real businesses because the experimental subjects are students (not businessmen). The study finds no differences in decision making between graduate students and managers making the production scheduling decision.
Remus, W., Experimental Designs for Analyzing Data from Games: Or, Even the Best Statistical Methods Do Not Replace Good Experimental Control, Simulation and Games, 1981, 12(1), pp. 3-14.
This article is a general view on the experimental design literature with a particular emphasis on the ways of dealing with confounding. These issues were placed in the context of doing research on gaming and interpreting the existing literature on gaming.
Remus, W., Measures of Fit for Unit Rules, American Psychologist, 1980, 35(7), pp. 678-680.
In July of 1979 Robin Dawes published an article in this journal advocating unit rules. I point out in my article the methodological failings of which led him to make his erroneous prescription of unit rules. My article also suggests how he could clean up his methodology.
Other
Articles
UNIVERSITY ADMINISTRATION:
Johnson, L. and W. Remus, A Comparison of the Problems Faced by First Year Men and Women Graduate Business Students, College Student Journal, 1985, 19(4), pp. 432-437.
This article finds little difference in the problems faced by men and women. The crucial dimensions of ethnicity and marital status were more meaningful predictors.
Remus, W. and C. Wong, The Impact of Grade Inflation on Five Admission Criteria, College Student Journal, 1984, 18(4), pp. 359-363.
This article builds on our earlier paper by examining whether removing grade point inflation improves the predictions of five common business school admission criteria. It doesn't.
Isa, D. and W. Remus, Predicting Who Will Actually Attend Your MBA Program, College Student Journal, 1983, 17(2), pp. 137-140.
This article illustrates the effectiveness of discriminant analysis in predicting graduate student enrollments. The data used was from the 1974-75 Hawaii MBA Programs. Not surprising, local residents and those given financial aids were the most likely to enroll.
Remus, W. and C. Wong, An Evaluation of 5 Models for the Admission Decision, College Student Journal, 1982, 16(1), pp. 53-59.
This article reports a comparative evaluation of five models (regression, discriminant, and three a priori models) in predicting student success in the MBA program. None improve upon the decisions made by the admissions officer.
Gilbert, P. and W. Remus, Design and Evaluation of a Computerized Registration System, International Journal of Instructional Media, 1978, 5(3), pp. 241-249.
This article reports the data gathered when
implementing the
RESEARCH ON TEACHING:
Remus, W. and A. Edge, Does Adding a Formal Leader Improve the Performance of a Team in a Business Simulation? Simulation and Games, 1991, 22(4), pp. 498-501.
This study compared teams of 3 peers with teams with one supervisor and three subordinates. When controlling for industry and country, both types of teams performed equally well.
Remus, W., Consistency in Business Games, Simulation and Games, 1983, 14(2), pp. 155-162.
This article reports an empirical study in which the different competitive settings created by different industries in a business simulation game were found to be characterized by different levels of erratic decision making even after rank, time, and rank-time interaction were blocked upon. This explained the results of a study by Makridakis and Hogarth on consistency in decision making.
Remus, W. and S. Jenner, The Expectations and Realities of Playing Business Games, Simulation and Games, 1981, 12(4), pp. 480-488.
This paper reports a study using a pre and post test design to identify the changes in students' attitudes caused by playing business games. In general, students find business games more enjoyable than expected but less realistic than desired.
Remus, W. and S. Jenner, Playing Business Games: Attitudinal Different Students Playing a Business Game Singly and As Teams, Simulation and Games, 1979, 10(3), pp. 75-86.
This article replicates and extends my "Who likes Business Games?" article which also appeared in this journal. Many of the same effects noted earlier also occur when student teams play business games. The social dynamics of the team game, however, cause these effects not to be so strong.
Remus, W., An Effective Learning System for Large Quantitative Methods Courses, International Journal of Mathematical Education in Science and Technology, 1978, 9(1), pp. 51-64.
This article is an elaboration and extension of earlier papers on teaching by objectives. It includes an extensive discussion of using systems analysis of the data I had gathered on course dynamics.
Remus, W., Who Likes Business Games? Simulation and Games, December, 1977, 8(1), pp. 64-68.
This article reports the results of an empirical study on the relationship between students performance in a game and their attitudes toward the game. Student satisfaction with the game turned out to be a linear function of their team's final rank. This result is consistent with the behavioral research on the relationship between performance and satisfaction.
OTHER EMPIRICAL STUDIES:
Remus, W. and L. Kelley, Evidence of Sex Discrimination: In Similar Populations, Men Are Better Paid than Women, American Journal of Economics and Sociology, 1983, 42(2), 149-151.
This paper is an extensive analysis using log-linear models of data reported in Women's Working Paper Series. The paper also contains an extensive review of the literature on sex-pay discrimination. Even though factors such as education, major, ethnicity, and type of job were controlled, sex-pay discrimination still occurs. Women earn 81% of the salary of men.
Kelley, L. and W. Remus, A Comparative Study of Occupational Success of Young Asian American Business Professionals in Hawaii, Social Processes in Hawaii, 1981, 28, pp. 58-72.
Most studies reporting income and employment of minority groups do not establish the controls necessary to see the influence of sex and ethnicity. The present study controls for sex, education, age, and location. The data shows Caucasian members to have higher median incomes that Chinese or Japanese young business professionals. It is not clear, however, to what degree these results from differing choices of fields of study, occupation, industry, or employment mobility.
Kelley, L. and W. Remus, Business Women in
This study examines differences in income between
men and women aged 23 to 28 who graduated from the
MISCELLANEOUS:
Grinnel, D. and W. Remus, How Many Waiters Do I Need Today? Journal of Hospitality Education, 1983, 7(2), pp. 51-62.
This paper is a managerial level presentation of how to use decision trees to analyze restaurant-staffing problems.
Remus, W., Why Academic Journals Are Unreadable: The Referee's Crucial Role, Interfaces, 1980, 10(2), pp. 87-90.
This paper presents the many tactics used by referees to give inadequate reviews. It suggests counter-tactics for authors to use to get good papers published. This journal is one of the top four in my area of specialization.
Remus, W., Strategies for a Publish or Perish World, IEEE Transactions on Professional Communication, December, 1978, 21(4), pp. 141-144.
Dr. R. J. Joenk, editor of this journal, requested and obtained the right to reprint this article from Interfaces.
Remus, W., Strategies for a Publish or Perish World, Interfaces, 1977, 8(4), pp. 469-480.
This article is a tongue-in-cheek analysis of the many "strategies" used for publishing articles in the social and hard sciences.
Remus, W., The Organization and Management of the Transcendental Meditation Movement, Indian Administrative and Management Review, 1975, 7(1), pp. 1-7.
This article analyzes the management of the TM organization established by Maharishi Mahesh Yogi. In particular, the impact of the "master-devotee" relationship upon the organizations functioning is examined. This is a significant contribution to the management literature since no other case study of this type of organization appears in the literature.
Management
Science
Hill, T., M. O'Connor and W. Remus, Neural Networks for Time Series Forecasting, Management Science, 1996, 42 (7). pp. 1082-1091.
This research compares neural network models with numerous standard forecasting models in forecasting the Makridakis 111 data series. The neural networks did better for both monthly and quarterly series; they were particularly good with discontinuous time series.
Remus, W., A Study of Graphical and Tabular Displays and Their Interaction with Environmental Complexity, Management Science, 1987, 33(9), pp. 1200-1205.
This is the follow-on to the earlier Management Science article. It replicates the earlier study plus shows a significant interaction between display type and environmental complexity.
Remus, W., An Empirical Investigation of the Impact of Graphical and Tabular Data Representations on Decision Making, Management Science, 1984, 30(5), pp. 533-542.
This article reports an empirical study to determine whether graphical or tabular aids are better for aiding decision making. When the error variance was greatly reduced through statistical methodology, tabular aids performed significantly better.
Remus, W., Testing Bowman's Managerial Coefficient Theory Using a Competitive Gaming Environment, Management Science, 1978, 24(8), pp. 827-835.
This paper demonstrates the effectiveness of testing a decision theory by using a competitive gaming environment. All postulates of theory were found to hold. In particular, erratic decision making (variance) was more costly than poor intuitions (bias).
Management
Information Systems Quarterly
Kottemann, J. and W. Remus, A Study of the Relationship Between Decision Model Naturalness and Performance, Management Information Systems Quarterly, 1989, 13(2), pp. 171-182.
This article found that the fit and performance of a decision model are not related. This means that models that fit better may not perform as well as those that have a lesser fit. This is the second part of the National Science Foundation study.
Remus, W. and J. Kottemann, Semi-structured Recurring Decisions: An Experimental Study of Decision Making Models and Some Suggestions for DSS, Management Information Systems Quarterly, 1987, 11(2), pp. 233-244.
The study finds tracking artifacts (the "range" effect and lag) in managerial decision making. These artifacts may show anchoring-and-adjustment to be occurring. The first part of the National Science Foundation study.
Remus, W. and J. Kottemann, Toward Intelligent Decision Support Systems: A Proposal for an Artificially Intelligent Statistician, Management Information System Quarterly, 1986, 10(4), pp. 403-418.
The article proposes how statistical rules, heuristics, and data could be handled by an Artificially Intelligent statistician. The article also suggests how this might reduce cognitive limitations of human decision makers.
Organizational
Behavior and Human Decision Processes
W. Remus, M. O'Connor, and K. Griggs, Does Feedback Improve the Accuracy of Recurrent Judgmental Forecasts? Organizational Behavior and Human Decision Processes, 1996, 66(1), pp. 22-30.
This article finds new and effective ways to improve people's ability to make forecasts - the use of task feedback.
Davis, F., J. Kottemann and W. Remus, Computer Assisted Decision Making: Performance, Beliefs, and the Illusion of Control, Organizational Behavior and Human Decision Processes, 1994, 57, pp. 26-37.
This paper reports an experiment that found that what-if analysis could cause managers not to perform better but instead to become overconfident.
The
International Journal of Forecasting
O'Connor, M., Remus, W., and K. Griggs, Does Updating Judgmental Forecasts Improve Forecast Accuracy? International Journal of Forecasting, 2000, 16, 101-109.
In this study we determined that it is worthwhile to update forecasts only when some meaningful structural changes has occurred. Otherwise the update only adds to the forecast error.
Remus, W., O'Connor, M. and K. Griggs, The Impact of Incentives on the Accuracy of Subjects in Judgmental Forecasting Experiments, International Journal of Forecasting, 1998, 14, 515-522.
Behavioral studies are often attacked on the grounds that the subjects may not be adequately motivated to do the experimental task well. Here we review the literature and conduct a study to assess the impact of incentives of subject's forecast accuracy. The incentives did not improve the subject's forecast accuracy.
Remus, W., O'Connor, M. and K. Griggs, The Impact of Information of Unknown Correctness on the Judgmental Forecasting Process, International Journal of Forecasting, 1998, 14, pp. 313-322.
In the study, people are asked to extrapolate times series when major changes occur in the time series structure and both correct and misinformation provided. We found that the more correct information, the better the forecast accuracy. However, there was no difference between misinformation and no information at all. Thus the forecasters were not misled by misinformation.
W. Remus, M. O'Connor, and K. Griggs, Will Reliable Information Improve the Judgmental Forecasting Process? International Journal of Forecasting, 1995, 11, pp.285-293.
In the study, people are asked to extrapolate times series when major changes occur in the time series structure and various levels of reliable information provided. We replicated our earlier work finding models superior to humans in this task (IJF, 93). We also found that the more reliable the information the better the forecasts; however, simple forecasting models still did better than people.
Marquez, L., T. Hill, M. O'Connor, and W. Remus, Artificial Neural Networks for Forecasting and Decision Making, International Journal of Forecasting, 1994, 10, pp. 5-15.
In this paper we reviewed all studies comparing neural networks and classical models for forecasting and decision making. They perform comparably (which turns out to be a controversial result and makes many people unhappy).
O'Connor, M., W. Remus and K. Griggs, Judgmental Forecasting in Times of Change, International Journal of Forecasting, 1993, 9(2), pp. 163-172.
People are often preferred to forecasting models when structural changes in the forecasting environment are expected to occur. In the study we people were asked to extrapolate times series when major changes occur in the time series structure. Humans did not do as well as forecasting models.
Awards
PROFESSIONAL HONORS: TEACHING
Fulbright Fellow at the National University of Malaysia, 1980.
Honored with the Presidential Citation for Meritorious Teaching, 1990.
Honored for Teaching Excellence by College Student Journal, 1984.
Selected Professor of the Year by the MBA Association in 1985, 1980, and 1978.
Runner-Up for this award in 1987, 1986, and 1977.
Finalist for Manoa campus Outstanding Teacher Award, 1985 and 1979.
Selected for the College's Teaching Excellence Award, 1996, 1990 and 1988.
PROFESSIONAL HONORS: RESEARCH
Honored with the Erskine Fellowship to the University of Canterbury, 1994.
National Science Foundation Grant for Research in Decision Making, 1984-85.
Associate Editor, Management Information Systems Quarterly, 1990-93.
Editorial Board, International Journal of Commerce and Management, 1989- .