Meta-analyses using information reweighting: An application to online advertising

Because technology-enabled marketing research has led to information arriving at a rapid pace, methods in marketing that allow for coherent, sequential and fast information integration are needed. We propose in this research a new approach to information integration: Information Reweighted Priors (IRPs). It is a sample reweighting approach which utilizes the output from a Bayesian model fit using Markov Chain Monte Carlo, with no restrictions on the likelihood, prior distributions, or data structure; hence a general purpose tool. We demonstrate the approach with simulated datasets and an online advertising dataset with external information obtained from i) previous advertising studies in the industry from a major online advertising portal, ii) past academic studies of online adverting and iii) out-of-sample summaries of the dataset.     

Children's Understanding of TV Advertising: Effects of Age, Gender, and Parental Influence

Parents, consumer organizations, and policy makers are generally concerned about effects of TV advertising directed towards children. These effects might be mediated by children's understanding of TV advertising, that is their ability to distinguish between TV programmes and commercials and their comprehension of advertising intent. In this paper, we investigate children's understanding of TV advertising, using verbal and non-verbal measurements. The sample consists of 153 Dutch children, ranging from 5 to 8 years old, and their parents. The results based on non-verbal measures suggest that most children are able to distinguish commercials from programmes and that they have some insight into advertising intent. The results based on verbal measures are not as conclusive; the percentage of children who show understanding of TV advertising is then substantially lower. Effects of age, gender, and parental influence are assessed using MURALS, a regression analysis technique for categorical and continuous variables, and CHAID, a technique for identifying homogeneous segments on the basis of the relationship between categorical dependent and explanatory variables. The age of a child turns out to have a positive effect. The effects of gender and parent- child interaction are rather small, both for verbal and for non-verbal measures of understanding of TV advertising. A high level of parental control of TV viewing may result in lower understanding of TV advertising. Implications for consumer policy and directions for future research are discussed.     

Estimating Discrete Joint Probability Distributions for Demographic Characteristics at the Store Level Given Store Level Marginal Distributions and a City-Wide Joint Distribution

This paper provides a solution to the problem of estimating a joint distribution using the associated marginal distributions and a related joint distribution. The particular application we have in mind is estimating joint distributions of demographic characteristics corresponding to market areas for individual retail stores. Marginal distributions are generally available at the census tract level, but joint distributions are only available for Metropolitan Statistical Areas which are generally much larger than the market for a single retail store. Joint distributions over demographics are an important input into mixed logit demand models for aggregate data. Market shares that vary systematically with demographics are essential for relieving the restrictions imposed by the Independence from Irrelevant Alternative property of the logit model.We approach this problem by formulating a parametric function that incorporates both the city-wide joint distributional information and marginal information specific to the retail stores market area. To estimate the function, we form moment conditions equating the moments of the parametric function to observed data, and we input these into a GMM objective. In one of our illustrations we use four marginal demographic distributions from each of eight stores in Dominicks Finer Foods data archive to estimate a four dimensional joint distribution for each store. Our results show that our GMM approach produces estimated joint distributions that differ substantially from the product of marginal distributions and emit marginals that closely match the observed marginal distributions. Mixed logit demand estimates are also presented which show the estimates to be sensitive to the formulation of the demographics distribution.The views expressed are not purported to reflect those of the United States Department of Justice     

A brand choice model for TV advertising management using single-source data

A brand choice model for TV advertising management using single-source data is proposed. The model replaces household-specific advertising exposure, which is often used as a covariate in a brand choice model, with gross rating points (GRP), a managerial control variable for advertising. In particular, given daily GRP, a probabilistic model of advertising exposure for heterogeneous customers is integrated into a brand choice model with advertising threshold under a Bayesian framework. Through hierarchical modeling, demographic information on panels provides managerial insights into advertising planning.     

Modeling heterogeneous effective advertising stock using single-source data

This paper presents a nonlinear modeling of market response between advertising stock and direct utility with heterogeneous parameters using single-source data. We examine advertising threshold effects and measure the effective advertising stock at the individual consumer level. Two kinds of information, i.e., TV advertising exposure data and consumer’s purchase history data, are combined for the modeling. The former is used for constructing advertising stock over calendar time via heterogeneous carryover parameters and the latter is applied to the choice model. The Markov chain Monte Carlo (MCMC) method is applied to estimate these heterogeneous parameters. Compared to other possible nonlinear specifications, it is shown that the proposed threshold utility function model with discontinuity at the threshold performs better than other smooth market response models. The empirical results support the existence of an advertising threshold and suggest the pulsing or “on/off” policy for our datasets. In terms of the effective reach, implying the reach after suspending the ad exposure to investigate how it is damping out for a possible “on/off” advertising policy, the optimal “off” interval was measured to be quite short to support a high-frequency pulsing policy, because the carryover parameter as well as the difference of ad stock and threshold are not large enough for our datasets.      

The determinants of international investment and attention allocation: Using internet search query data

This paper explores the joint determination of home bias and attention allocation. We overcome the typical challenge associated with evaluating attention allocation theories by using a new internet search query dataset to measure how much information investors decide to process. Employing an instrumental variables approach, we find empirical evidence of a two-way causality between home bias and attention. Our estimates suggest that if all countries were to receive the same level of attention as the U.S., then the average home bias by U.S. investors would fall from 85.2% to 57.3%.     

Value‐at‐Risk bounds with two‐sided dependence information

Value‐at‐Risk (VaR) bounds for aggregated risks have been derived in the literature in settings where, besides the marginal distributions of the individual risk factors, one‐sided bounds for the joint distribution or the copula of the risks are available. In applications, it turns out that these improved standard bounds on VaR tend to be too wide to be relevant for practical applications, especially when the number of risk factors is large or when the dependence restriction is not strong enough. In this paper, we develop a method to compute VaR bounds when besides the marginal distributions of the risk factors, two‐sided dependence information in form of an upper and a lower bound on the copula of the risk factors is available. The method is based on a relaxation of the exact dual bounds that we derive by means of the Monge–Kantorovich transportation duality. In several applications, we illustrate that two‐sided dependence information typically leads to strongly improved bounds on the VaR of aggregations.     

The Effectiveness of a Buzz Marketing Approach Compared to Traditional Advertising: An Exploration

Marketers are now willing to go anyplace they can find a captive audience to espouse the virtues of their products. The success of the “buzz” marketing approach is linked to the consumer being lured into doing the advertising by spreading the message to others. This study compares students’ responses to a traditional advertising and a buzz approach. Using a factor analysis to identify variables, the results show that subjects perceive a buzz approach to be more influential than a traditional advertising. However, they do not perceive a buzz approach to be authentic. This finding is consistent with practitioners’ argument that, although a buzz approach may be effective in the short-term, once consumers recognize its selling intent, the program may have a “boomerang effect.”     

Who's afraid of that ad? Applying segmentation to the protection motivation model

The protection motivation model has contributed usefully to researchers' understanding of fear appeals in advertising. However, the empirical evidence reported to date in the literature has been mixed. This article proposes and tests a revised model including two segmenting variables as a means to resolve some of the differences evident in past research. With the use of data derived from an experimental study of juveniles' response to a range of antismoking advertising treatments, empirical support was found for the mediating role of fear in predicting behavioral intentions and for the influence of individual differences. The results, however, did not confirm the moderating role of response or self‐efficacy. Future research is clearly needed to further validate the revised protection motivation model. © 2004 Wiley Periodicals, Inc.     

Time heals many wounds – explaining the immediate and delayed effects of message sidedness

This study investigates the immediate and delayed effects of advertising messages including both positive and negative information. A two-sided message has a negative effect on message attitudes due to two mediating variables with trade-off effects: valence and balance. These two variables are also responsible for the alignment of the effect of sidedness on message attitudes and purchase intentions over time: the negative effects of two-sided messages are neutralized over time because negative information is reevaluated, improving the valence of the message. The results explain the negative effects of message sidedness that have been found in prior research and they show that a two-sided message in advertising is not necessarily inferior to a one-sided message despite unfavorable short-term effects.     

Developmental antecedents to children’s responses to online advertising

Many critics have raised concerns about online advertising directed to children. This study investigated the role of several antecedent variables that may impact children’s attitudinal and behavioural responses to online advertising. Specifically, online ad scepticism, family communication patterns, time spent on the internet, and perceived internet competency were examined as factors that may impact children’s online advertising attitudes and behaviours. A survey conducted with a dyad sample of 381 parents-preteens in South Korea revealed that children with high scepticism towards online advertising, who spent less time using the internet and who perceived lower levels of confidence about their internet skills were more likely to have a negative attitude towards online advertising and less likely to disclose personal information to online marketers. However, the relationship between family communication and children’s responses to online advertising found in this study was inconsistent with the previous empirical findings. Implications of findings are discussed and directions for future research suggested.     

A Primer on Using Behavioral Data for Testing Theories in Advertising Research

Interactions with and between customers in digital, social, and mobile environments are commonly recorded, producing behavioral data that have the potential to advance advertising research. This article provides an accessible guide on how to leverage such data for advertising researchers who may have thus far relied mostly on lab experiment or survey data. Specifically, we suggest potential sources for behavioral data and present a process for analyzing and interpreting behavioral data. Each step of the process is discussed: exploring, understanding and preparing data; specifying and estimating models; and interpreting and presenting the results. Some fundamental issues with using multiple regression to analyze such data are covered, including standardization, outliers, transformations, multicollinearity, and the omitted variable bias. We also discuss issues that are especially problematic with using behavioral data in advertising research, including endogeneity, count data, data with many zeros, and grouped data. More advanced versions of regression that address these issues are surveyed, including instrumental variables, propensity scoring, generalized linear models, and mixed models. General advice for thinking about behavioral data is provided.     

E-mail Advertising in Syria: Assessing Beliefs,Attitudes, and Behaviors

The present study aimed at assessing Syrian consumers' beliefs regarding, attitude, and behavioral responses toward e-mail advertising and investigating the relationships among those variables. A cross-sectional survey was conducted and it yielded 273 valid responses. The proposed model was analyzed and tested using a structural equation modelling approach. Our findings showed that both informativeness and entertainment beliefs positively predicted Syrian consumers' attitudes toward e-mail advertising. Additionally, attitude was found to fully mediate the relationship between beliefs regarding and behavioral responses toward e-mail advertising.     

Opportunities for and Pitfalls of Using Big Data in Advertising Research

This editorial introduces the special section on big data. We define big data by examining how it is, or will be, created in advertising environments. We propose a conceptual framework for understanding the different types of digital advertising touch points that create big data, and use the framework for identifying research opportunities. We discuss the types of research questions that big data can inform, including developing and testing theories, identifying insights, and optimizing the delivery of messages. New methods that advertisers will need to use big data are identified. Recommendations are provided for how to think about and approach big data. Using the framework, we identify specific opportunities for advertising researchers to use big data. We also discuss pitfalls in using big data.     

Advertising value and advertising processing

Advertising value research is rooted in the view that advertising messages are potential communications exchanges between advertisers and consumers. Since some level of processing effort on the part of receivers is necessary for successful exchanges to occur, it is proposed that advertising processing decisions are based on initial, spontaneous, categorical evaluations that combine to form an expected advertising value (EAV) assessment. If sufficiently positive, individuals devote additional processing effort to the advertisement and more detailed ad-related factors become the focus. Once processing ends after some or all of an advert has been taken in, an evaluation of whether or not the effort was actually worthwhile - designated as outcome advertising value (OAV) - should be a measurable outcome. Factors that account for OAV and its relationship to attitude-toward-the-advertisement (A ad ) are also discussed.     

How does ad relevance affect consumers' attitudes toward personalized advertisements and social media platforms? The role of information co-ownership,vulnerability, and privacy cynicism

Consumers' responses to the use of their personal data for personalized advertising by platform providers are paradoxical. Drawing from psychological ownership theory and the collective information boundary, this study examines how the social relevance and personal relevance of ads impact consumers' attitudes toward advertisements and social media platforms. Basing on 350 responses, we confirm that perceptions of information co-ownership and feelings of vulnerability play a serial mediating role in the positive relationship between ad relevance and consumer attitudes. Specifically, ad relevance increases consumers' perceptions of social media platforms as co-owners of their personal information, which in turn reduces feelings of vulnerability and improves their attitudes toward personalized advertisements and social media platforms. Privacy cynicism negatively moderates the indirect effects of information co-ownership perceptions on two attitude variables mediated through feelings of vulnerability. Our research findings provide a new perspective on the personalization–privacy paradox and offer platform providers new insights into improving their personalized advertising performance and user–platform relationships.     

Attitudes toward Use of Advertising and Various Media Practices by Physicians

Advertising by physicians is a relatively recent phenomenon. The purposes of this study were to determine (a) consumers’ attitudes toward advertising by physicians; (b) whether certain potential consumer demographic variables account for any significant difference in attitudes toward physicians who advertise; and (c) which media consumers feel are appropriate for physicians’ advertising. The intent was to discover information that would be useful to physicians in planning promotional strategies and improving the quality of their advertising. The study seems to confirm the belief of many professionals that advertising and promotion clearly have a place in the future of health care services.     

大数据在海基测控联合信息环境中的应用构想

针对海基测控领域存在的信息化烟囱、数据孤岛、信息安全等问题，开展了大数据在海基测控领域的应用研究，提出了基于大数据构建海基测控联合信息环境的系统架构和运行模式，对构建联合信息环境的相关技术进行了探索分析，应用大数据技术实现广域分布式环境下数据、信息和信息技术服务共享，将数据优势转换为信息优势，进而发挥决策优势。     

Factors that Influence Adolescents to Smoke

Predictor variables previously examined in separate studies (prior beliefs, peer pressure, family smoking, advertising, and antismoking information) were combined in a single study, surveying 246 adolescents. The variables were found to be significant predictors of smoking level, but the importance of each predictor varied by grade level, gender, and ethnicity. Overall, family smoking behavior, peer pressure, and prior beliefs were more important in predicting smoking level than were advertising and antismoking information. Public policy implications are discussed.