Digital Advertising offers a detailed and current overview of the field that draws on current research and practice by introducing key concepts, models, theories, evaluation practices, conflicts, and issues. With a balance of theory and practice, this book helps provide the tools to evaluate and understand the effects of digital advertising and promotions campaigns. New to this edition is discussion of big data analysis, privacy issues, and social media, as well as thought pieces by leading industry practitioners. This book is ideal for graduate and upper-level undergraduate students, as well as academics and practitioners.

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Digital Advertising
Theory and Research
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Subtopic
History & Theory in PsychologyIndex
BusinessPart I
Research Foundations
1
Revisiting the Interactive Advertising Model (IAM) after 15 Years
An Analysis of Impact and Implications
Introduction
The Interactive Advertising Model (IAM), developed by Rodgers and Thorson (2000), was one of the first models that theorized about the interactions between internet users and online advertisements. In the 15+ years since its inception and initial publication, the model has been widely referenced by scholars from various academic disciplines (advertising, marketing, IT, etc.), and is recognized as an effective model for understanding how interactive advertising āworksā (Kim, Hayes, Avant, & Reid, 2014).
Despite the growing number of scholarly publications and articles citing the IAM, it is both necessary and beneficial to evaluate the IAMās impact and influence on scholarship by examining how scholars have used and critiqued the IAM over the past 15 years. This examination allows quantification of the impact of the IAM and enhances further understanding of the explanatory power of the model in digital advertising, as well as other contexts. This analysis also sheds insights on how the IAM may be revised and adapted to the fast-changing landscape of digital advertising.
The objectives of the present chapter are two-fold: First, we quantitatively assess the impact of the IAM by analyzing all peer-reviewed articles citing the IAM over a 15-year period (2000 to 2015). Second, we use the content analysis findings to identify themes, trends, and potential challenges associated with the IAM. Chapter 2 then builds on the results of this chapter by presenting an extended version of the IAM that attempts to fill gaps identified by research reported in Chapter 1.
The remainder of this chapter is organized as follows. First, we briefly review the IAM and its various components. Next, we provide an explanation of the methodology used to analyze articles that cite the IAM. Then, results of our analysis are provided, followed by a discussion of theoretical implications going forward. Based on our results, we conclude that the IAM remains useful for understanding how people perceive and process advertising in a Web 1.0 environment; however, the model may need to be revised and updated to reflect the current and dynamic Web 2.0 and even Web 3.0 technologies.
Overview of the IAM
Rodgers and Thorson (2000) conceptualized the Interactive Advertising Model, or IAM, as an integrative process, based on three dominant paradigms or schools of thought: functional, structural, and information processing (see Figure 1 from Rodgers & Thorson, 2000). The authors argued that a theoretical integration of multiple paradigms could serve to better understand and interpret the complex nature of the interactive environment, as the internet itself was an āintegrated mediumā (Rodgers & Thorson, 2000, p. 43).
Both function and structure could determine the internet usersā information processing of advertising in cyberspace. The functionalist view explains how (mode) and why (motive) users use the internet, as well as the various stages of information processing (attention, brand liking, etc.), consumerās attitudes (e.g., form attitudes toward the ad), and behaviors (e.g., click on the ad) as outcomes influenced by online ads. The structural view, on the other hand, helps to understand the basic components (ad types, formats, and features) of the stimulus environment primarily controlled by advertisers at the time of the modelās inception.
Function
From a functionalist perspective, the IAM proposed that internet users control the initiation of internet activity, as they enter cyberspace with specific goals in mind and constantly adjust to the interactive environment to fulfill these goals. Internet motives, the inner drive to carry out the internet activity, can explain why individuals use the internet. Four categories of reasons were identified as the primary motives for entering cyberspace (Rodgers & Sheldon, 2002): researching, communicating, surfing, and shopping. The categories of internet motives were suggested to not only influence consumer responses to online ads differently, but also to help advertisers determine the most effective ad appeal and ad type. However, users could have more than one internet motive in mind before entering cyberspace and switch motives during their online activities when seeing an unexpected stimulus, or for some other reason.
Mode, the extent of a userās goal-directedness of internet activities, conjointly determines the level of ad processing with motive, as internet motive will influence the mode in which users use the internet. For example, researchers tend to be āseriousā with a highly goal-directed mode, while surfers tend to be āplayfulā without a specific goal in mind.
As discussed, individuals are also expected to experience several stages of information processing of online ads: attend to, remember, and develop attitudes toward internet ads, as well as actions taken in response to internet ads. In terms of evaluating consumer responses to online ads, almost all measures used in traditional advertising could be applied to interactive advertising, such as attitude toward the ad or purchase intention. In addition, new types of measures were available to examine effects of online ads, e.g., hits, click-through rates, and time spent on websites.
Structure
The IAM argued that information processing of online ads would be influenced by the presentation of the interactive ad, as well as characteristics of the stimulus environment. Thus, the structural view was provided to complement the functional view in terms of understanding how physical features could interact with usersā motive or mode. As a result, the IAM provided a classification of all the āthen availableā ad types and formats 15+ years ago and discussed some common ad features at that time.
Ad Type
Ad type represents the general structure of any advertisement and was classified into five main categories according to Thorson (1996): product/service, PSA, issue, corporate, and political. The IAM argues that ad type can predict whether, or how much, cognitive effort is involved in processing online ads and how different ad types can often indicate consumer responses to the ad.
Ad Format
Ad format is the manner in which the online ad appears. The IAM argued that different formats would result in differential processing and outcomes. Several then-popular interactive ad formats were examined using the IAM model: banners, interstitials (pop-ups), sponsorships, hyperlinks, and websites.
Ad Feature
The internet was conceptualized as having more ad features than broadcast or print media because the medium itself was more complex than traditional media. The IAM provides a comprehensive list of two subjective ad features, structures based on consumer responses (e.g., āattitude towards the websiteā and āinterestā), and objective ad features (e.g., color, size, or typeface) across print, broadcast, and the internet. The IAM suggests that both objective and subjective ad features would have an impact on consumer responses and would interact with usersā motives as well. In addition, interactivity was seen as the most salient ad feature made possible by the internet, and it would allow users to be involved in the persuasion process by changing the structural elements.
Methodology
Now that the basic components of the IAM have been reviewed, the next step was to conduct a search of the literature to collect scholarly articles that cite the IAM. This was accomplished with a literature search on Google Scholar with the aim to collect peer-reviewed literature citing the IAM. Compared to other databases, Google Scholar not only has relatively accurate citation counts, but also covers a larger collection of conference proceedings and international journals (Meho & Yang, 2007). A total of 385 citing articles were found, at the writing of this chapter, using a ācited-byā search in Google Scholar, and the citation details (i.e., author, publication, title, and year) were exported using Zotero for further content analysis.
Of the 385 articles identified by a Google Scholar search, 243 were scholarly journal articles (63.1%), 71 were theses or dissertations (18.4%), 39 were book chapters or sections in books (10.1%), and 32 were conference proceedings (8.3%). We report results from all sources citing the IAM, as presented; however, several sources were not read for this analysis because they were written in languages other than English.
A codebook was then developed for a content analysis of all 385 cited articles. There were five main coding categories, adapted from Kim et al. (2014, p. 1): 1) basic information (title, item type, publication, year, author, university, and locale); 2) methodology (research approach, reasoning, method type, method, theory presence, and theory); 3) data collection (sampled population, unit of analysis, data collection method, big data, and technology); 4) research details (independent variables, dependent variables, phenomenon, topic area, media effect type, ad format examined, and social media examined); and 5) IAM contribution (IAM use, IAM citing aspect, IAM citing detail, implications of broader research, and implications of IAM).
Two graduate students were the coders. Inter-coder reliabilities were taken at the beginning and ending of the content analysis, and an overall intercoder reliability of .788 (Scottās pi) was achieved.
Results
IAM Citation Trends
As shown in Figure 1.1, the past five years have seen an increase in citations of the IAM, particularly between 2011 and 2014, during which more than 160 articles were published citing the IAM. The number of citing articles appears to peak in 2011 (42 articles).

Figure 1.1 Number of Journal Articles Citing the IAM Since 2000 (Total N=385)
Publication | No. Of Citing Articles |
Journal of Interactive Advertising | 23 |
Journal of Advertising | 9 |
International Journal of Advertising | 9 |
Int. Journal of Internet Marketing and Advertising | 5 |
Journal of Marketing Communications | 3 |
Advances in Consumer Research | 3 |
Journal of Current Issues & Research in Advertising | 3 |
Three journals that contributed the most in terms of the number of published citing articles include Journal of Interactive Advertising (23 articles), Journal of Advertising (9 articles), and International Journal of Advertising (9 articles). In addition, the IAM appeared three or more times in the following advertising journals: International Journal of Internet Marketing and Advertising (5 articles), Journal of Marketing Communications (3 articles), Advances in Consumer Research (3 articles), and Journal of Current Issues and Research in Advertising (3 articles).
In terms of international impact, first authors affiliated with non-U.S. institutions contributed to more than 65% of the 372 articles linked to a known university. International scholars represent 75 countries and regions, among which scholars from Spain, South Korea, Germany, China, and Taiwan authored more than 100 citing articles combined. In addition, more than 50 journal articles citing the IAM were written in languages other than English.
Evaluation of the IAMās Contribution
To accurately evaluate the contribution of the IAM, the content analysis examined the extent to which the articles referenced the IAM (IAM use), how other scholars used the IAM (IAM citing aspects), and what specific topics were discussed in reference to the IAM (IAM citing detail). Results showed that over 35 percent of all citing articles used the IAM to provide evidence to support the discussion of two main aspects: hypothesis development and/or research results. About 12 articles (4.3%) applied the IAM as a theoretical framework to develop a hypothesis or test prepositions and make predictions from the original article (Rodgers & Thorson, 2000). For example, the study by Burns (2006) looked at how audience attitudes varied by six different digital ad formats, which was supported by a major implication of the IAM regarding the variation of processing outcomes of different ad formats. The rest of the articles (60.6%) briefly mentioned or referenced the IAM to inform the background or discussion of internet advertising.
Most Cited Aspects of the IAM
The original IAM model proposed two ways of looking at the interactive processing of online ads: consumer-controlled aspects or advertiser-controlled aspects. The results from the content analysis suggest that about 35.3 percent of citing articles focused on consumer-controlled aspects, while 25.2 percent focused on advertiser-controlled aspects of online ads. The remainder of the articles did not have a clear emphasis on either consumer- or advertiser-controlled aspects.
Several citing aspects emerged as themes that were frequently referenced by the articles: internet motives and modes (30.3%), ad formats and ad features (23.0%), consumer responses and outcomes (21.1%), and interactivity (9.6%).
Internet Modes and Motives
The aspect of the IAM that has received the most scholarly attention relates to the functional aspects presented by the model, i.e., internet motives and modes. Amo...
Table of contents
- Cover
- Title
- Copyright
- Dedication
- Contents
- About the Contributors
- Foreword
- Preface
- Acknowledgments
- Part I Research Foundations
- Part II Theory Breakthroughs
- Part III New Approaches to Research
- Part IV Digital MediaāRadiating Voices
- Part V Evaluating Digital Advertising
- Part VI Future Research Trends and Opportunities
- Index
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