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- J. Scott Armstrong (58)
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Articles 31 - 60 of 88
Full-Text Articles in Physical Sciences and Mathematics
Introduction To Paper And Commentaries On The Delphi Technique, J. Scott Armstrong
Introduction To Paper And Commentaries On The Delphi Technique, J. Scott Armstrong
J. Scott Armstrong
Rowe and Wright’s paper "The Delphi Technique as a Forecasting Tool" was initially reviewed by four experts in the area of judgmental forecasting. Following three rounds of revisions, the paper was accepted for publication. It was then sent for commentary by Professors Ayton, Ferrell, and Stewart. The lead paper should be of interest to researchers because it identifies important aspects of the Delphi procedure that have not yet been studied. In particular, there are few validation studies and these often omit descriptions of the relevant conditions. This makes it difficult to identify which aspects of Delphi are related to accuracy …
Research Needs In Forecasting, J. Scott Armstrong
Research Needs In Forecasting, J. Scott Armstrong
J. Scott Armstrong
The demand for research on forecasting is strong. This conclusion is based on the high number of citations to papers published about research on forecasting, and upon the number of subscriptions for journals devoted to forecasting. The supply of research papers is also large, following a rapid growth in the 1960s and 1970s. This research has produced important findings. Despite this, a comparison of published research versus the needs expressed in two surveys of academics and practitioners showed that numerous gaps still exist. A review of the literature also supported this conclusion that the research being produced does not match …
Review Of Ravi Batra, The Great Depression Of 1990, J. Scott Armstrong
Review Of Ravi Batra, The Great Depression Of 1990, J. Scott Armstrong
J. Scott Armstrong
The Great Depression of 1990 was on the New York Times best-seller list for non-fiction in the summer of 1987. It follows a standard formula for best sellers in forecasting: Forecast a great disaster, and include a formula for redemption. If the disaster occurs, you can say, "I told you so." If it doesn't occur, you say, "It is good that they listened to my advice. I saved them." How can you lose? When I first saw this book, it occurred to me that it was a hoax.
Brand Trial After A Credibility Change, J. Scott Armstrong, David B. Montgomery
Brand Trial After A Credibility Change, J. Scott Armstrong, David B. Montgomery
J. Scott Armstrong
In most frequently purchased, branded product markets, the consumer has little to choose from in terms of significantly differentiated products. The staggering array of manufacturers' claims and counter claims of brand superiority seems to leave consumers somewhat bewildered or cynical. What would happen if the credibility of the appeals made on behalf of one brand should suddenly be enhanced by a seemingly legitimate authority? More specifically, what would characterize consumers who would respond to such a change in credibility?
Decomposition By Causal Forces: A Procedure For Forecasting Complex Time Series, J. Scott Armstrong, Fred Collopy, J. Thomas Yokum
Decomposition By Causal Forces: A Procedure For Forecasting Complex Time Series, J. Scott Armstrong, Fred Collopy, J. Thomas Yokum
J. Scott Armstrong
Causal forces are a way of summarizing forecasters' expectations about what will happen to a time series in the future. Contrary to the common assumption for extrapolation, time series are not always subject to consistent forces that point in the same direction. Some are affected by conflicting causal forces; we refer to these as complex times series. It would seem that forecasting these times series would be easier if one could decompose the series to eliminate the effects of the conflicts. Given forecasts subject to high uncertainty, we hypothesized that a time series could be effectively decomposed under two conditions: …
On The Interpretation Of Factor Analysis, J. Scott Armstrong, Peer Soelberg
On The Interpretation Of Factor Analysis, J. Scott Armstrong, Peer Soelberg
J. Scott Armstrong
The importance of the researcher’s interpretation of factor analysis is illustrated by means of an example. The results from this example appear to be meaningful and easily interpreted. The example omits any measure of reliability or validity. If a measure of reliability had been included, it would have indicated the worthlessness of the results. A survey of 46 recent papers from 6 journals supported the claim that the example is typical, two-thirds of the papers provide no measure of reliability. In fact, some papers did not even provide sufficient information to allow for replication. To improve the current situation some …
Brief Vs. Comprehensive Descriptions In Measuring Intentions To Purchase, J. Scott Armstrong, Terry Overton
Brief Vs. Comprehensive Descriptions In Measuring Intentions To Purchase, J. Scott Armstrong, Terry Overton
J. Scott Armstrong
Introduction: In forecasting demand for expensive consumer goods, direct questioning of potential consumers about their future purchasing plans has had considerable predictive success [1, 2, 4]. Any attempt to apply such "intention to purchase" methods to forecast demand for proposed products or services must determine some way to convey product information to the potential consumer [3]. Indeed, all the prospective consumer knows about the product or service is what he may infer from the information given to him by the researcher. This paper presents a study of the effect upon intention to purchase of this seemingly crucial element—the extent and …
Global Warming: Forecasts By Scientists Versus Scientific Forecasts, Kesten C. Green, J. Scott Armstrong
Global Warming: Forecasts By Scientists Versus Scientific Forecasts, Kesten C. Green, J. Scott Armstrong
J. Scott Armstrong
In 2007, the Intergovernmental Panel on Climate Changes Working Group One, a panel of experts established by the World Meteorological Organization and the United Nations Environment Programme, issued its updated, Fourth Assessment Report, forecasts. The Report was commissioned at great cost in order to provide policy recommendations to governments. It included predictions of dramatic and harmful increases in average world temperatures over the next 92 years. Using forecasting principles as our guide we asked, are these forecasts a good basis for developing public policy? Our answer is "no." To provide forecasts of climate change that are useful for policy-making, one …
Causal Forces: Structuring Knowledge For Time Series Extrapolation, J. Scott Armstrong, Fred Collopy
Causal Forces: Structuring Knowledge For Time Series Extrapolation, J. Scott Armstrong, Fred Collopy
J. Scott Armstrong
This paper examines a strategy for structuring one type of domain knowledge for use in extrapolation. It does so by representing information about causality and using this domain knowledge to select and combine forecasts. We use five categories to express causal impacts upon trends: growth, decay, supporting, opposing, and regressing. An identification of causal forces aided in the determination of weights for combining extrapolation forecasts. These weights improved average ex ante forecast accuracy when tested on 104 annual economic and demographic time series. Gains in accuracy were greatest when (1) the causal forces were clearly specified and (2) stronger causal …
Management Science: What Does It Have To Do With Management Or Science?, J. Scott Armstrong
Management Science: What Does It Have To Do With Management Or Science?, J. Scott Armstrong
J. Scott Armstrong
This paper is an edited version of the College of Business Studies Silver Jubilee Commemoration lecture, given as part of celebrations recognizing 25 years of teaching and research in the Faculty of Business Studies, now the College of Business, at Massey University.
Should We Redesign Forecasting Competitions?, J. Scott Armstrong
Should We Redesign Forecasting Competitions?, J. Scott Armstrong
J. Scott Armstrong
The M3-Competition continues to improve the design of forecasting competitions: It examines more series than any previous competition, improves error analyses and includes commercial forecasting programs as competitors. To judge where to go from here, I step back to look at the M-Competitions as a whole. I discuss the advantages of the M-Competitions in hopes that they will be retained, describe how to gain additional benefit from future competitions, and finally, describe a low-cost approach to competitions.
Return Postage In Mail Surveys: A Meta Analysis, J. Scott Armstrong, Edward J. Lusk
Return Postage In Mail Surveys: A Meta Analysis, J. Scott Armstrong, Edward J. Lusk
J. Scott Armstrong
This paper describes a five-step procedure for meta-analysis. Especially important was the contacting of authors of prior papers. This was done primarily to improve the accuracy of the coding; it also helped to identify unpublished research and to supply missing information. Application of the five-step procedure to the issue of return postage in mail surveys yielded significantly more papers and produced more definitive conclusions than those derived from traditional reviews. This meta-analysis indicated that business reply postage is seldom cost effective because first class postage yields an additional 9% return. Business reply rates were lower than for other first class …
Effects Of Portfolio Planning Methods On Decision Making: Experimental Results, J. Scott Armstrong, Roderick J. Brodie
Effects Of Portfolio Planning Methods On Decision Making: Experimental Results, J. Scott Armstrong, Roderick J. Brodie
J. Scott Armstrong
Subjects (n = 1015) working individually in the role of managers were asked to choose between investment opportunities that would either double their investment or cause the loss of half of it. Six administrators ran experiments on 27 occasions in six countries over a five-year period. Information about the BCG matrix increased the subjects' likelihood of selecting the project that was clearly less profitable. Of subjects exposed to the BCG matrix, 64% selected the unprofitable investment. Of subjects who used the BCG matrix in their analysis, 87% selected the less profitable investment.
Findings From Evidence-Based Forecasting: Methods For Reducing Forecast Error, J. Scott Armstrong
Findings From Evidence-Based Forecasting: Methods For Reducing Forecast Error, J. Scott Armstrong
J. Scott Armstrong
Empirical comparisons of reasonable approaches provide evidence on the best forecasting procedures to use under given conditions. Based on this evidence, I summarize the progress made over the past quarter century with respect to methods for reducing forecasting error. Seven well-established methods have been shown to improve accuracy: combining forecasts and Delphi help for all types of data; causal modeling, judgmental bootstrapping and structured judgment help with cross-sectional data; and causal models and trend-damping help with time-series data. Promising methods for cross-sectional data include damped causality, simulated interaction, structured analogies, and judgmental decomposition; for time-series data, they include segmentation, rule-based …
Evidence On The Value Of Strategic Planning In Marketing: How Much Planning Should A Marketing Planner Plan?, J. Scott Armstrong, David J. Reibstein
Evidence On The Value Of Strategic Planning In Marketing: How Much Planning Should A Marketing Planner Plan?, J. Scott Armstrong, David J. Reibstein
J. Scott Armstrong
What evidence exists on the value of formal planning for strategic decision-making in marketing? This paper reviews the evidence. This includes two tests of face validity. First, we use the market test: Are formal procedures used for marketing planning? Next, we examine expert prescriptions: What do they say is the best way to plan? More important than face validity, however, are tests of construct or predictive validity: What empirical evidence exists on the relative value of formal and informal approaches to marketing planning? The paper concludes with suggestions on the types of research that would be most useful for measuring …
Identification Of Asymmetric Prediction Intervals Through Causal Forces, J. Scott Armstrong, Fred Collopy
Identification Of Asymmetric Prediction Intervals Through Causal Forces, J. Scott Armstrong, Fred Collopy
J. Scott Armstrong
When causal forces are specified, the expected direction of the trend can be compared with the trend based on extrapolation. Series in which the expected trend conflicts with the extrapolated trend are called contrary series. We hypothesized that contrary series would have asymmetric forecast errors, with larger errors in the direction of the expected trend. Using annual series that contained minimal information about causality, we examined 671 contrary forecasts. As expected, most (81%) of the errors were in the direction of the causal forces. Also as expected, the asymmetries were more likely for longer forecast horizons; for six-year-ahead forecasts, 89% …
Review Of Philip E. Tetlock, Expert Political Judgment: How Good Is It? How Can We Know?, Adrian E. Tschoegl, J. Scott Armstrong
Review Of Philip E. Tetlock, Expert Political Judgment: How Good Is It? How Can We Know?, Adrian E. Tschoegl, J. Scott Armstrong
J. Scott Armstrong
The book assaults common sense with evidence. In order to mount his assault on accepted wisdom, Tetlock spends some 238 pages of text explaining his methods and findings, and considering and refuting many alternative explanations, and adds some 75 pages of technical appendices. The downside of this approach is that some readers may find the book too demanding. That would be a pity as his findings are important. Tetlock’s book reports the results of a two-decade long study of expert predictions. He recruited 284 people whose professions included "commenting or offering advice on political and economic trends." He asked them …
A Comparative Study Of Methods For Long-Range Market Forecasting, J. Scott Armstrong, Michael C. Grohman
A Comparative Study Of Methods For Long-Range Market Forecasting, J. Scott Armstrong, Michael C. Grohman
J. Scott Armstrong
The following hypotheses about long-range market forecasting were examined: Hl Objective methods provide more accuracy than do subjective methods. H2 The relative advantage of objective over subjective methods increases as the amount of change in the environment increases. H3 Causal methods provide more accuracy than do naive methods. H4 The relative advantage of causal over naive methods increases as the amount of change in the environment increases. Support for these hypotheses was then obtained from the literature and from a study of a single market. The study used three different models to make ex ante forecasts of the U.S. air …
Predicting The Outcome Of Marketing Negotiations: Role-Playing Versus Unaided Opinions, J. Scott Armstrong, Philip D. Hutcherson
Predicting The Outcome Of Marketing Negotiations: Role-Playing Versus Unaided Opinions, J. Scott Armstrong, Philip D. Hutcherson
J. Scott Armstrong
Role-playing and unaided opinions were used to forecast the outcome of three negotiations. Consistent with prior research, role-playing yielded more accurate predictions. In two studies on marketing negotiations, the predictions based on role-playing were correct for 53% of the predictions while unaided opinions were correct for only 7% (p < 0.001).
Integration Of Statistical Methods And Judgment For Time Series Forecasting: Principles From Empirical Research, J. Scott Armstrong, Fred Collopy
Integration Of Statistical Methods And Judgment For Time Series Forecasting: Principles From Empirical Research, J. Scott Armstrong, Fred Collopy
J. Scott Armstrong
We consider how judgment and statistical methods should be integrated for time-series forecasting. Our review of published empirical research identified 47 studies, all but four published since 1985. Five procedures were identified: revising judgment; combining forecasts; revising extrapolations; rule-based forecasting; and econometric forecasting. This literature suggests that integration generally improves accuracy when the experts have domain knowledge and when significant trends are involved. Integration is valuable to the extent that judgments are used as inputs to the statistical methods, that they contain additional relevant information, and that the integration scheme is well structured. The choice of an integration approach can …
The Value Of Surprising Findings For Research On Marketing, J. Scott Armstrong
The Value Of Surprising Findings For Research On Marketing, J. Scott Armstrong
J. Scott Armstrong
In the work of Armstrong (Journal of Business Research, 2002), I examined empirical research on the scientific process and related these to marketing science. The findings of some studies were surprising. In this reply, I address surprising findings and other issues raised by commentators.
Review Of Scott Plous, The Psychology Of Judgment And Decision Making, J. Scott Armstrong
Review Of Scott Plous, The Psychology Of Judgment And Decision Making, J. Scott Armstrong
J. Scott Armstrong
Where can one find basic marketing principles? Up to now, my favorite source has been Influence(Cialdini 1984, 1993). In The Psychology of Judgment and Decision Making, Plous (rhymes with house) adds to Cialdini by summarizing important principles in an effective manner. The book contains a wonderful selection of the classic studies on psychology. These are organized into six sections: (1) perception, memory, and context; (2) how questions affect answers; (3) models of decision making; (43 heuristics and biases; (5) the social side of judgment and decision making; and (6) common traps.
Statistical Significance Tests Are Unnecessary Even When Properly Done And Properly Interpreted: Reply To Commentaries, J. Scott Armstrong
Statistical Significance Tests Are Unnecessary Even When Properly Done And Properly Interpreted: Reply To Commentaries, J. Scott Armstrong
J. Scott Armstrong
The three commentators on my paper agree that statistical tests are often improperly used by researchers and that even when properly used, readers misinterpret them. These points have been well established by empirical studies. However, two of the commentators do not agree with my major point that significance tests are unnecessary even when properly used and interpreted.
Why We Don’T Really Know What "Statistical Significance" Means: A Major Educational Failure, Raymond Hubbard, J. Scott Armstrong
Why We Don’T Really Know What "Statistical Significance" Means: A Major Educational Failure, Raymond Hubbard, J. Scott Armstrong
J. Scott Armstrong
The Neyman-Pearson theory of hypothesis testing, with the Type I error rate, α, as the significance level, is widely regarded as statistical testing orthodoxy. Fisher’s model of significance testing, where the evidential p value denotes the level of significance, nevertheless dominates statistical testing practice. This paradox has occurred because these two incompatible theories of classical statistical testing have been anonymously mixed together, creating the false impression of a single, coherent model of statistical inference. We show that this hybrid approach to testing, with its misleading p &#; α statistical significance criterion, is common in marketing research textbooks, as well as …
Forecasting With Econometric Methods: Folklore Versus Fact, J. Scott Armstrong
Forecasting With Econometric Methods: Folklore Versus Fact, J. Scott Armstrong
J. Scott Armstrong
Evidence from social psychology suggests that econometricians will avoid evidence that disconfirms their beliefs. Two beliefs of econometricians were examined: (1) Econometric methods provide more accurate short-term forecasts than do other methods; and (2) more complex econometric methods yield more accurate forecasts. A survey of 21 experts in econometrics found that 95% agreed with the first statement and 72% agreed with the second. A review of the published empirical evidence yielded little support for either of the two statements in the 41 studies. The method of multiple hypotheses was suggested as a research strategy that will lead to more effective …
Principles For Examining Predictive Validity: The Case Of Information Systems Spending Forecasts, Fred Collopy, Monica Adya, J. Scott Armstrong
Principles For Examining Predictive Validity: The Case Of Information Systems Spending Forecasts, Fred Collopy, Monica Adya, J. Scott Armstrong
J. Scott Armstrong
Research over two decades has advanced the knowledge of how to assess predictive validity. We believe this has value to information systems (IS) researchers. To demonstrate, we used a widely cited study of IS spending. In that study, price-adjusted diffusion models were proposed to explain and to forecast aggregate U.S. information systems spending. That study concluded that such models would produce more accurate forecasts than would simple linear trend extrapolation. However, one can argue that the validation procedure provided an advantage to the diffusion models. We reexamined the results using an alternative validation procedure based on three principles extracted from …
Review Of Noel Capon, John U. Farley And James M. Hulbert, Corporate Strategic Planning, Bernard J. Jaworski, J. Scott Armstrong
Review Of Noel Capon, John U. Farley And James M. Hulbert, Corporate Strategic Planning, Bernard J. Jaworski, J. Scott Armstrong
J. Scott Armstrong
Corporate Strategic Planning (CSP) reports on an important study of planning practices and the value of those practices. Though it is a long book, nearly 500 pages, one can get almost the full benefit by reading about 200 pages. In fact, CSP contains an excellent summary (Chapter 11) that is only 33 pages; this chapter should be sufficient for most readers. My review assesses what the book has to offer and provides a guide to the potential reader.
A Note On The Use Of Markov Chains In Forecasting Store Choice, J. Scott Armstrong, John U. Farley
A Note On The Use Of Markov Chains In Forecasting Store Choice, J. Scott Armstrong, John U. Farley
J. Scott Armstrong
Ehrenberg's sweeping criticism of Markov brand switching models [3] highlights many shortcomings of these models for aggregate analysis of consumer behavior. While it has been pointed out that some of his criticisms are not entirely correct [13], one of Ehrenberg's themes is unquestionably valid. The models tend to break down empirically due to violations of important Markovian stability assumptions [14]. A situation in which the assumptions of the model appear less restrictive is short-run forecasting of store choice behavior of individual families.
Publishing Standards For Research On Forecasting (Editorial), J. Scott Armstrong, Estella Bee Dagum, Robert Fildes, Spyros Makridakis
Publishing Standards For Research On Forecasting (Editorial), J. Scott Armstrong, Estella Bee Dagum, Robert Fildes, Spyros Makridakis
J. Scott Armstrong
When we first began publication of the International Journal of Forecasting, we reviewed policies that were used by other journals and also examined the research on scientific publishing. Our findings were translated into a referee's rating form that was published in the journal [Armstrong (1982a)]. These guidelines were favorably received. Most referees used the Referee's Rating Sheet (Exhibit 1 provides an updated version)and some of them wrote to tell us that they found it helpful in communicating the aims and criteria of the journal.
Error Measures For Generalizing About Forecasting Methods: Empirical Comparisons, J. Scott Armstrong, Fred Collopy
Error Measures For Generalizing About Forecasting Methods: Empirical Comparisons, J. Scott Armstrong, Fred Collopy
J. Scott Armstrong
This study evaluated measures for making comparisons of errors across time series. We analyzed 90 annual and 101 quarterly economic time series. We judged error measures on reliability, construct validity, sensitivity to small changes, protection against outliers, and their relationship to decision making. The results lead us to recommend the Geometric Mean of the Relative Absolute Error (GMRAE) when the task involves calibrating a model for a set of time series. The GMRAE compares the absolute error of a given method to that from the random walk forecast. For selecting the most accurate methods, we recommend the Median RAE (MdRAE)when …