William R Dillon

• Southern Methodist University

Throughout a distribution channel, multiple sales platforms and technologies are leveraged to expand market reach and manage offering assortments. Yet, the literature is limited on how buyers who are channel intermediaries make purchase decisions across sales platforms particularly when platforms vary in their degree of technology enablement. This...

In this study, we develop a new methodology that extends multilevel structural equation model techniques by considering both temporal variation and unit-level random effects simultaneously for nested repeated cross-sectional samples. Our modeling approach essentially uses a state-space model form and a multilevel structural equation form to “marry”...

Purpose Joint space multidimensional scaling (MDS) maps are often utilized for positioning analyses and are estimated with survey data of consumer preferences, choices, considerations, intentions, etc. so as to provide a parsimonious spatial depiction of the competitive landscape. However, little attention has been given to the possibility that con...

We focus on destination categories, so named because they have the greatest impact on where households choose to shop and, more generally, on how category positioning affects which store a household chooses. We propose a reduced-form model-based analytical approach to identify categories that fill the destination role. Our approach determines which...

Attribute ratings often contain a holistic or global impression of the brand, commonly referred to as "halo." A halo response can occur when perceptions of a brand's performance on an attribute are influenced by performance perceptions on another attribute or by a global impression of the brand. Using cross-national survey data from consumers in Ar...

A 2-way clustering approach to multiple correspondence analysis is proposed to account for cluster-level heterogeneity of both respondents and variable categories in multivariate categorical data. Specifically, in the proposed method, multiple correspondence analysis is combined with k-means in a unified framework in which "k"-means is applied twic...

Latent class analysis and, more generally, finite mixture models have seen increased use in marketing since the early 1980s. The popularity of latent class and finite mixture models can, in large measure, be traced to the important role individual differences (i.e., heterogeneity) play in understanding marketing and consumer behavior phenomenon. At...

The validity and reliability of students’ evaluation of teaching effectiveness has been debated since the 1970s. One concern is the extent to which the ratings are influenced by halo, and if so, how does halo affect the interpretation of the ratings? This study seeks to assess the degree to which the halo affects the diagnosticity of individual tea...

Multiple correspondence analysis (MCA) is a useful tool for exploring the interdependencies among multiple-choice variables. However, MCA is not geared for explicitly investigating whether or not heterogeneous subgroups of respondents exist in the population with qualitatively distinct patterns of choice behaviour. We extend MCA to capture such clu...

This research focuses on the consequences of and potential remedies for incorporating zero brand sales observations when calibrating choice models on the basis of household panel data. As the authors show both analytically and empirically, including or excluding zero brand sales observations can bias price elasticities, even in cases in which the d...

An extension of multiple correspondence analysis is proposed that takes into account cluster-level heterogeneity in respondents’ preferences/choices. The method involves combining multiple correspondence analysis and k-means in a unified framework. The former is used for uncovering a low-dimensional space of multivariate categorical variables while...

In this paper, we used simulations to investigate the effect of sample size, number of indicators, factor loadings, and factor correlations on frequencies of the acceptance/rejection of models (true and misspecified) when selected goodness-of-fit indices were compared with prespecified cutoff values. We found the percent of true models accepted whe...

One of the nagging issues in using discrete choice models is how softer attributes, such as attitudes and perceptions, that are not explicitly manipulated within the context of the choice experiment can be accommodated. In many cases, it is reasonable to expect that the choice of a particular alternative may be influenced by non-product-related att...

Although brand ratings capture the favorability of brand associations, they often do not enable marketing managers to disentangle brand-specific associations from other effects. In this article, the authors present a decompositional model for analyzing brand ratings that addresses this nagging problem and provide insights for understanding the sour...

Customer relationship management (CRM) initiatives have gained much attention in recent years. With the aid of data mining technology, businesses can formulate specific strategies for different customer bases more precisely. Additionally, personalisation is another important issue in CRM - especially when a company has a huge product range. This pa...

In this article, the authors develop a class of models to reconstruct brand-transition probabilities when individual brand purchase sequence information is not available. The authors introduce two general model forms by assuming different underlying mechanisms for individual heterogeneity in brand switching. The first model form captures individual...

This paper presents two probabilistic models based on the logistic and the normal distribution for the analysis of dependencies in individual paired comparison judgments. It is argued that a core assumption of latent class choice models, independence of individual decisions, may not be well-suited for the analysis of paired comparison data. Instead...

Despite the enormous amounts of resources devoted to concept and product testing and the continued use of pretest market (PTM) modeling procedures, estimates of new product failures are still alarmingly high. The primary objectives of PTM modeling are to forecast the market share/sales volume of a new product and to determine the sources of new pro...

It is an everyday marketplace occurrence that brands lose and gain share. However, a brand's sales gain or loss can be attributable to very different factors, and thus understanding the sources of sales gain or loss would seem to be an important aspect of a brand manager's job. The primary purpose of this research is to develop a model that can ans...

Our paper provides a brief review and summary of issues and advances in the use of latent structure and other finite mixture models in the analysis of choice data. Focus is directed to three primary areas: (1) estimation and computational issues, (2) specification and interpretation issues, and (3) future research issues. We comment on what latent...

Describes an extended Bradley-Terry-Luce (BTL) model (R. A. Bradley and M. E. Terry, 1952) of simultaneous segmentation and estimation for paired comparisons (PDCs). The model can also accommodate descriptor variables, if available. An empirical application of the model involving 550 women is provided. The procedure extends methods for analyzing PD...

The method of paired comparisons addresses the problem of determining the scale values of a set of stimuli on a preference continuum that is not directly observable. The conventional approach in analyzing paired comparisons is to view all individuals as homogeneous and estimate a single vector of scale values for the stimuli. The authors describe a...

First-order confirmatory factor analytic models have had widespread use in the analysis of multitrait-multimethod (MTMM) data. In contrast to the usual first-order confirmatory factor analytic model for the analysis of MTMM data, other covariance structure models have recently been proposed and advocated. Two such models are Wothke's covariance com...

First-order confirmatory factor analytic models have had widespread use in the analysis of multitrait-multimethod (MTMM) data. In contrast to the usual first-order confirmatory factor analytic model for the analysis of MTMM data, other covariance structure models have recently been proposed and advocated. Two such models are Wothke's covariance com...

In applied research it is important to understand the implications of the factor analytic model used to represent the covariance structure underlying a set of observed measures. Here the focus is on the use of confirmatory measurement models in the analysis of multiple-informant reports. By effecting a variance decomposition that partitions the var...

In applied research it is important to understand the implications of the factor analytic model used to represent the covariance structure underlying a set of observed measures. Here the focus is on the use of confirmatory measurement models in the analysis of multiple-informant reports. By effecting a variance decomposition that partitions the var...

Investigated the behavior of alternative covariance structure estimation procedures in the presence of nonnormal data. Monté Carlo simulation experiments were conducted with a factorial design involving 3 levels of skewness, 3 levels of kurtosis, and 3 different sample sizes. For normal data, among all the elliptical estimation techniques, elliptic...

The authors report some results on the behavior of alternative covariance structure estimation procedures in the presence of non-normal data. They conducted Monté Carlo simulation experiments with a factorial design involving three levels of skewness, three level of kurtosis, and three different sample sizes. For normal data, among all the elliptic...

Examination of the properties of component scores in the presence of group structure shows that the first few components extracted, typically viewed as most informative regarding total variance, do not necessarily contain the most information across group differences. A method for identifying informative components that account for across group dif...

A general, flexible LAtent Discriminant model is described. LADI is a model-based clustering procedure, derived from a specific conceptualization in which the discrimination problem is viewed in a latent mixture context. The basic model yields maximum likelihood (ML) estimates of mixing parameters and structural parameters that define the latent cl...

A general, flexible LAtent DIscriminant model is described. LADI is a model-based clustering procedure, derived from a specific conceptualization in which the discrimination problem is viewed in a latent mixture context. The basic model yields maximum likelihood (ML) estimates of mixing parameters and structural parameters that define the latent cl...

Recently there has been a change in focus from the study of one organism over time to the study of the social interaction between organisms. This change in focus has brought with it a renewed interest in what is generally referred to as sequential analysis (Altman 1965; Blurton-Jones, 1972; Gottman 1980a, 1980b; Gottman & Ringland, 1981; Wilson, 19...

This paper discusses a technique called spectral decomposition which can be effectively used to gain insights into interbrand/product competition. The technique is based on singular value decomposition of a transition matrix. If the assumption of stationary first-order Markov process is made for brand switching, the first component of the spectral...

The authors demonstrate a general, flexible constrained discrimination method for testing hypotheses about the segmentability of a target population using categorical descriptors when additional information is available. The method applies the principle of minimum discrimination information (MDI) to the estimation of multinomial probabilities under...

The authors address the criticisms raised by Anderson, Gerbing, and Hunter. In this context they consider several conceptual issues involved in using covariance structure analysis.

The authors address the criticisms raised by Anderson, Gerbing, and Hunter. In this context they consider several conceptual issues involved in using covariance structure analysis.

The authors demonstrate a general, flexible constrained discrimination method for testing hypotheses about the segmentability of a target population using categorical descriptors when additional information is available. The method applies the principle of minimum discrimination information (MDI) to the estimation of multinomial probabilities under...

The authors report the results of some theoretical investigations of interactions that occur in the simultaneous estimation of parameters. Under the assumptions of a perfectly specified model for a set of non-overlapping indicators and no sampling fluctuations, an overall consistency criterion is developed showing that though measurement and struct...

The authors report the results of some theoretical investigations of interactions that occur in the simultaneous estimation of parameters. Under the assumptions of a perfectly specified model for a set of non-overlapping indicators and no sampling fluctuations, an overall consistency criterion is developed showing that though measurement and struct...

In this article we discuss, illustrate, and compare the relative efficacy of three recommended approaches for handling negative error variance estimates (i.e., Heywood cases): (a) setting the offending estimate to zero, (b) adopting a model parameterization that ensures positive error variance estimates, and (c) using models with equality constrain...

Confirmatory factor analysis and structural equation modeling with unobservable variables have recently become prominent tools in the investigation and expression of behavioral- and social-science theory. The increased use of this more sophisticated methodology can, in large measure, be traced to the recognition that many variables of frequent inte...

In this paper a methodology for hierarchical market structure analysis is derived and illustrated. A probabilistic model is developed which provides a general, flexible framework which can be used to test hypothesized hierarchical market structures. Because the general probabilistic model can be translated in terms of a it can be easily implemented...

Reexamined the empirical tests reported by R. P. Bagozzi and R. E. Burnkrant (see record 1980-30231-001) and by M. Fishbein and I. Ajzen (see record 1974-24385-001) concerning the convergent and nomological validity of the multicomponent and single-component models of attitude. The present authors conclude that although Bagozzi and Burnkrant's 2-...

This paper considers decisions that face consumer researchers as they implement a perceptual product space analysis based on multi-attribute rating data. Decisions that affect the structure of the derived perceptual product space solution can be grouped into six major categories relating to issues of (1) data input, (2) mode, (3) preprocessing tran...

Increasingly behavioral researchers are soliciting cognitive responses in addition to standard attitudinal measures when attempting to assess the effects of persuasive communications. The coding of the elicited cognitive responses generally involves some sort of categorization, typically undertaken by independent judges, and the quality of the data...

Concludes that the editorial presentation of a story can have significant effects on an audience's perceptions of a story's target. (FL)

Removing distortion in perceptual judgments has been the subject of several recent research studies. The authors examine the issue of identifying and removing perceptual distortions in product space analysis. The purpose of the article is to show how a simple data transformation can purge the influence of the common general factor which typically s...

Removing distortion in perceptual judgments has been the subject of several recent research studies. The authors examine the issue of identifying and removing perceptual distortions in product space analysis. The purpose of the article is to show how a simple data transformation can purge the influence of the common general factor which typically s...

Traditionally, transportation demand studies have, for the most part, viewed modal choice in terms of an aggregate system-wide function. However, it seems reasonable to expect that the travel decision may be influenced by a composite of factors that include not only availability conditions, but determinants relating to neighborhood characteristics...

Demonstrates how a class of modeling techniques, commonly referred to as latent structure analysis, can be used in an informative way to study the character of sequential categorical data. Using this procedure, the authors show how to investigate (a) the lagged dependence between 2 actors, (b) dependency across populations, and (c) the issue of dom...

We demonstrate how latent structure analysis can be used to model rating scale data that have ordered categories, and propose a modification of the basic latent structure approach to analyze response errors in the context of a traditional multitrait-multimethod matrix. The extended approach provides the researcher with the ability to (1) use formal...

The authors illustrate the use of latent structure analysis to test, in a confirmatory sense, causal hypotheses in an experimental design setting. Two latent factors conceptualized as arousal and yielding are hypothesized to explain the linkages in a communication hierarchy of effects model. A stagewise analysis is proposed which can help in the an...

The authors illustrate the use of latent structure analysis to test, in a confirmatory sense, causal hypotheses in an experimental design setting. Two latent factors conceptualized as arousal and yielding are hypothesized to explain the linkages in a communication hierarchy of effects model. A stagewise analysis is proposed which can help in the an...

Recently interest has centered on extending decompositional methods for modeling consumer preferences to include group-level effects. The motivation for this effort is the general belief that respondent background characteristics and situation variables frequently interact with product attributes in jointly influencing preferences over a set of mul...

Recently interest has centered on extending decompositional methods for modeling consumer preferences to include group-level effects. The motivation for this effort is the general belief that respondent background characteristics and situation variables frequently interact with product attributes in jointly influencing preferences over a set of mul...

Because of the availability of easy-to-use canned computer software packages such as SPSS and BMDP, the marketing practitioner is likely to continue to rely on the linear discriminant function (LDF) when faced with a discrimination problem. However, results of prior simulation studies suggest that when categorical predictors are used in the LDF its...

Because of the availability of easy-to-use canned computer software packages such as SPSS and BMDP, the marketing practitioner is likely to continue to rely on the linear discriminant function (LDF) when faced with a discrimination problem. However, results of prior simulation studies suggest that when categorical predictors are used in the LDF its...

The feasibility of modeling the effects of alternative growth strategies on market performance is the subject of this report. Intensive growth strategy alternatives are discussed in terms of key products and market variables and implied growth opportunities. Microanalytic relationships among growth strategy components are developed and then reformu...

Negative publicity about products and companies has become increasingly problematic for many firms. This study took the Chrysler/Consumers Union controversy concerning the alleged handling problems of the Plymouth Horizon and Dodge Omni automobiles into the laboratory to examine its effects. Original videotapes of the negative news story, the compa...

This paper explores the potential role of subculture (religious) and personality (Rockeach Dogmatism Scale) characteristics in explaining differences in the extent of consumer acculturation. The survey results suggest that for a complex and heterogeneous nation like Nigeria, there are significant within-nation differences that may influence consume...

The marketing manager faces several dilemmas when analyzing multivariate frequency data. If the choice is to analyze a series of two-dimensional condensed tables, the interrelationships between those factors not in the table will be lost and biased inferences can result. If the decision is to analyze the complete multiway table, many of the cells m...

The marketing manager faces several dilemmas when analyzing multivariate frequency data. If the choice is to analyze a series of two-dimensional condensed tables, the interrelationships between those factors not in the table will be lost and biased inferences can result. If the decision is to analyze the complete multiway table, many of the cells m...

This paper investigates the relative competitive position of a firm with a view toward determining those marketing effort dimensions that significantly influence market share. The study differs from previously published reports in that it utilizes the Profit Impact of Marketing Strategy (PIMS) data base on relative marketing effort to identify key...

This study discusses a simple variable selection procedure, similar in nature to the "F-to-enter" criterion used in stepwise multiple regression, suitable for multidimensional contingency tables having one criterion variable. The procedure is applied to an illustrative set of marketing data and contrasted with other, better-known methods.

The setting for this study is the two-group multinomial classification problem. Based on a measure of the log odds in favor of one particular group, a large sample confidence interval for a measure of separability is derived. The asymptotic result employed assumes that all states have positive observed frequencies. Realizing that this assumption is...

This paper discusses a recently developed variable selection procedure suitable when the available data have discrete components. In the context of the new product problem, a modification to the basic methodology is proposed with a view of identifying product profiles closely associated with success or early failure. A comparative analysis is also...

This study discusses a simple variable selection procedure, similar in nature to the “F-to-enter” criterion used in stepwise multiple regression, suitable for multidimensional contingency tables having one criterion variable. The procedure is applied to an illustrative set of marketing data and contrasted with other, better-known methods.

This article is a review of the results, as are available, on the performance of the linear discriminant function in situations where the assumptions of multivariate normality and equal group dispersion structures are violated. Some new results are discussed for the case of classification using discrete variables, and in the case of both binary and...

This article is a review of the results, as are available, on the performance of the linear discriminant function in situations where the assumptions of multivariate normality and equal group dispersion structures are violated. Some new results are discussed for the case of classification using discrete variables, and in the case of both binary and...

Mice bearing the BW7756 hepatoma were passively immunized using rabbit antiserum to murine alpha-fetoprotein (AFP) administered in constant or increasing doses. Control tumor-bearing mice were inoculated with saline or nonimmune rabbit serum (NRS) (constant or increasing doses), or were left untreated. The tumor growth curves from mice receiving co...

This article presents and discusses a new multinomial classification procedure based on a discrete distributional distance. Its performance along with other commonly used classification procedures is assessed through Monte Carlo sampling experiments under different population structures. In addition to reporting results consistent with the work of...

Buyer usage behavior data are used to compare the relative performance of a linear discriminant analysis and several multinomial classification methods. The potential shortcomings of each of the procedures investigated are cited, and a new method for determining the contribution of a variable to discrimination in the context of the multinomial clas...

Buyer usage behavior data are used to compare the relative performance of a linear discriminant analysis and several multinomial classification methods. The potential shortcomings of each of the procedures investigated are cited, and a new method for determining the contribution of a variable to discrimination in the context of the multinomial clas...

The impact of marketing information systems (MIS) has not been substantial and developed systems have not been highly utilized. Borrowing the theory of self-concept from the behavioral sciences, 46 system users' self-images, ideal self-images, and the images of a significant other (one who facilitates usage of the MIS) are measured and related to t...

A stepwise variable selection procedure for multinomial discrimination is presented and discussed. Based upon the work of Kullback and Hills, stopping rules are proposed and illustrated for a set of data on communication buyer behavior.