Papers by Shelby McIntyre
A knowledge distilled attention-based latent information extraction network for sequential user behavior
Multimedia Tools and Applications
Alan Budd London Business School, UK
International Journal of Forecasting, 1987
Research on forecasting is extensive and includes many studies that have tested alternative metho... more Research on forecasting is extensive and includes many studies that have tested alternative methods in order to determine which ones are most effective. We review this evidence in order to provide guidelines for forecasting for marketing. The coverage includes intentions, Delphi, role playing, conjoint analysis, judgmental bootstrapping, analogies, extrapolation, rule-based forecasting, expert systems, and econometric methods. We discuss research about which methods are most appropriate to forecast market size, actions of decision makers, market share, sales, and financial outcomes. In general, there is a need for statistical methods that incorporate the manager's domain knowledge. This includes rule-based forecasting, expert systems, and econometric methods. We describe how to choose a forecasting method and provide guidelines for the effective use of forecasts including such procedures as scenarios. FIG 6.2. Characteristics of forecasting methods and their relationships (dotted lines represent possible relationships) Expert Systems Conjoint Analysis Intentions Expert Opinions Econometric Models Multivariate Models Judgmental Bootstrapping judgmental statistical role no role univariate theory-based data-based Extrapolation Models multivariate Analogies Role Playing Knowledge Source self others Increasing judgmental/ statistical integration Rule-Based Forecasting Methods Based on Judgment Intentions With intentions surveys, people are asked to predict how they would behave in various situations. Intentions surveys are widely used when sales data are not available, such as for new product forecasts. There is much empirical research about the best way to assess intentions and Morwitz (2001) draws upon this to develop principles for using intentions in forecasting. Role playing A person's role may be a dominant factor in some situations, such as in predicting how someone in a firm would behave in negotiations. Role playing is useful for making forecasts of the behavior of individuals who are interacting with others, and especially when the situation involves conflict. The key principle here is to provide a realistic simulation of the interactions. It is a method that has considerable potential for forecasting although, currently, it is seldom used (Armstrong, 2001b). Expert opinions Expert opinion studies differ substantially from intentions surveys. When an expert is asked to predict the behavior of a market, there is no need to claim that this is a representative expert. Quite the contrary, the expert may be exceptional. One principle is to combine independent forecasts from a group of experts, typically 5 to 20 (Ashton and Ashton, 1985). The required level of expertise is surprisingly low (Armstrong 1985). The preferred procedure is to weight each expert's forecast equally.
Motivation of User-Generated Content: Social Connectedness Moderates the Effects of Monetary Rewards
Marketing Science, 2017
The creation and sharing of user-generated content such as product reviews has become increasingl... more The creation and sharing of user-generated content such as product reviews has become increasingly “social,” particularly in online communities where members are connected. While some online communities have used monetary rewards to motivate product review contributions, empirical evidence regarding the effectiveness of such rewards remains limited. We examine the possible moderating effect of social connectedness (measured as the number of friends) on publicly offered monetary rewards using field data from an online review community. This community saw an (unexpected) overall decrease in total contributions after introducing monetary rewards for posting reviews. Further examination across members finds a strong moderating effect of social connectedness. Specifically, contributions from less-connected members increased by 1,400%, while contributions from more-connected members declined by 90%. To corroborate this effect, we rule out multiple alternative explanations and conduct robustness checks. Our find...
In Search of Sustainable Social Mission Ventures to Alleviate Poverty
Alleviating Poverty through Business Strategy, 2008
Implementing the Marketing Concept Through a Program of Customer Visits
Using Market Knowledge
Emerging technology in retailing: challenges and opportunities for the 1990s
Journal of Applied Psychology, 1977
To predict earnings S and 10 years after graduation for MBAs, regression models were developed on... more To predict earnings S and 10 years after graduation for MBAs, regression models were developed on a sample of 266 graduates and validated against a new set of 70. The predictors included personality tests administered shortly after entrance into the MBA program, age at graduation, business aptitude tests, grade point average, and earnings at graduation and S and 10 years after graduation. Separate analyses were run for predictors available (a) at entrance, (b) at graduation, and (c) S years after graduation. The cross-validated multiple correlations for predicting 10-year earnings were .38, .45, and .65, respectively. Significant predictor variables included Harrell's High Earner's Scale and second-year grade point average. Age at graduation was significant in predicting 5-year but not 10-year earnings.
Personal values: A cross cultural assessment of self values and values attributed to a distant cultural stereotype
Personal values: A cross cultural assessment of self values and values attributed to a distant cu... more Personal values: A cross cultural assessment of self values and values attributed to a distant cultural stereotype. J Michael Munson, Shelby H McIntyre Advances in Consumer Research 5:11, 160-166, Association for Consumer Research, 1978.
Issues and perspectives on retail productivity
ABSTRACT Retail productivity continues to be of significant concern to many organizations across ... more ABSTRACT Retail productivity continues to be of significant concern to many organizations across the country. However, the various perspectives in the literature often imply inconsistent definitions and measurementofkey productivity-related concepts. The thrust of this paper is to provide definitional and conceptual clarity to the area and to discuss some significant productivity measurement problems.
Growing ventures can anticipate marketing stages
One of the primary tasks for commercial recommender systems is to predict the probabilities of us... more One of the primary tasks for commercial recommender systems is to predict the probabilities of users clicking items, e.g., advertisements, music and products. This is because such predictions have a decisive impact on profitability. The classic recommendation algorithm, collaborative filtering (CF), still plays a vital role in many industrial recommender systems. However, although straight CF is good at capturing similar users’ preferences for items based on their past interactions, it lacks regarding (1) modeling the influences of users’ sequential patterns from their individual history interaction sequences and (2) the relevance of users’ and items’ attributes. In this work, we developed an attention-based latent information extraction network (ALIEN) for click-through rate prediction, to integrate (1) implicit user similarity in terms of click patterns (analogous to CF), and (2) modeling the low and high-order feature interactions and (3) historical sequence information. The new ...
Correction: Huang et al. An Attention-Based Recommender System to Predict Contextual Intent Based on Choice Histories across and within Sessions. Appl. Sci. 2018, 8, 2426
Applied Sciences, 2021
We, the authors, wish to make the following corrections to our paper [1] [...]
Applied Sciences
Recent years have witnessed the growth of recommender systems, with the help of deep learning tec... more Recent years have witnessed the growth of recommender systems, with the help of deep learning techniques. Recurrent Neural Networks (RNNs) play an increasingly vital role in various session-based recommender systems, since they use the user’s sequential history to build a comprehensive user profile, which helps improve the recommendation. However, a problem arises regarding how to be aware of the variation in the user’s contextual preference, especially the short-term intent in the near future, and make the best use of it to produce a precise recommendation at the start of a session. We propose a novel approach named Attention-based Short-term and Long-term Model (ASLM), to improve the next-item recommendation, by using an attention-based RNNs integrating both the user’s short-term intent and the long-term preference at the same time with a two-layer network. The experimental study on three real-world datasets and two sub-datasets demonstrates that, compared with other state-of-the-...
Maximing Profits from Periodic Department Store Promotions
Productivity Measurement and the Output of Retailing
Journal of Retailing, Sep 9, 1985
ABSTRACT It is easy to equate the output of a retail establishment with the value of its sales (e... more ABSTRACT It is easy to equate the output of a retail establishment with the value of its sales (e.g., revenue). The simplicity of this approach is clearly the reason that it is so often used. However, we have argued that to do this is conceptually inappropriate because it confuses output and demand two distinct phenomena (Achabal, Heineke, and Mcintyre 1984).Goodman (1985) once again asserts the, "value as output," point of view for retailers, and we feel that it is important to clarify several issues in light of his comments. With few exceptions, all points raised by Goodman fall in the same category; he would require that, "meaningful," measures of productivity be measures of the value of the product or service.We have divided this paper into two sections. The first section contains general comments on Goodman's discussion of output measures for retail establishments. The second section addresses appropriate methods for using market data to estimate retail production functions.
Rod Brodie University of Auckland, New Zealand
Hindsight bias occurs when people tend to falsely believe, after the fact, that they knew the ans... more Hindsight bias occurs when people tend to falsely believe, after the fact, that they knew the answer to a question beforehand. Given the tendency for people to say 'I already knew that' after being presented with new information, it would appear that the hindsight bias has the potential to significantly compromise the value of a communication. To overcome this problem, respondents were asked to guess a fact before the actual value was divulged and compared with those asked to indicate what they would have guessed only after seeing the actual value. It is shown that such pre-guessing about a result leads to that result being rated as more interesting, more informative, and more surprising. However, there was no such impact on the ratings of how valuable the information was, nor on any of the potential decision outcomes we measured. Reasons why the guessing affected the judged impact of that information but not the influence of it on decisions are discussed. These general findings have implications for improving the impact of communications, and particularly in terms of addressing the problem of the hindsight bias. Suggestions are made for using this approach in several marketing settings as well as in the presentation of marketing research findings to client audiences.
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Papers by Shelby McIntyre