1. Molton J., (Winter 2010) Costly Mistakes. American Journalism Review, Vol. 32 Issue 4, p64-64, 1p. Retrieved from EBESCO, University of Washington
This paper talks about the steps that US newspaper industry could have taken to mitigate the declining revenue because of the Internet in the period of 1990-2000. It focuses on the measures that were taken by newspapers to compete with Internet advertising and these measures are seen to have increased the problem since it led to the decline in the quality of journalism. This paper helps in identifying how newspapers started losing money and Internet being the generator of more content became the prime property for advertising for marketers.
2. Lee, S.Y., Cho Y. (Sep 2010) Do Web Users Care About Banner Ads Anymore? The Effects of Frequency and Clutter in Web Advertising. Journal of Promotion Management; Jul-Sep2010, Vol. 16 Issue 3, p288-302, 15p. Retrieved from EBESCO, University of Washington
This paper discusses the effects of frequency of exposure to banner ads and ad clutter in web pages and online users’ corresponding psychological responses. It also conducts quantitative analysis to prove effects of online advertising on users. The perception of users as indicated in this paper, can be used in predicting the trends in online advertising in the future and especially the type of advertising would user respond to and those that will disappear over time.
3. Dingxi , Q. (April 2009) Quantifying the Indirect Effects of a Marketing Contact. Expert Systems with Applications; Apr2009 Part 2, Vol. 36 Issue 3, p6446-6452, 7p Retrieved from EBESCO, University of Washington.
This paper is focused on understanding the effects of a marketing contact in Online Advertising. In this reference, the contact could have both direct effects like buying or indirect effects like brand awareness. The paper conducts quantitative analysis to collecting data from an Internet service provider and is modeled with decaying function over time since the prospect gets into the system. The analysis used in this paper tells us the usage patterns of consumers of online advertising and can be directly applied to the uses and gratification theory to understand why users get into the marketing cycle and the impact that it creates, helping understand the current advertising ecosystem with respect to consumers.
4. Chen J. (Feb 2009) The Effect of Types of Banner Ad, Web Localization, and Customer Involvement on Internet Users’ Attitudes. CyberPsychology & Behavior; Vol. 12 Issue 1, p71-73, 3p. Retrieved from EBESCO, University of Washington.
This research shows that animated (rather than static) banner ads, localized versions (rather than a standardized version) of Web sites, and high (rather than low) product involvement led to favorable attitudes toward the site. This research was conducted in Taiwan where users were shown different set of ads on websites and there reactions were recorded. This research explains the impact of certain forms of online advertising and would be useful in analyzing the future forms of advertising.
5. Tao M., Hua X., Li S. (Dec 2009) VideoSense: A Contextual In-Video Advertising System. IEEE Transactions on Circuits & Systems for Video Technology; Dec2009, Vol. 19 Issue 12, p1866-1879 Retrieved from EBESCO, University of Washington
This research shows that given a Web page containing an online video, the product ‘VideoSense’ is able to extract the surrounding text related to this video, detect a set of candidate ad insertion positions based on video content discontinuity and attractiveness, select a list of relevant candidate ads according to multimodal relevance. To support contextual advertising, this task is formulated as a nonlinear 0-1 integer-programming problem by maximizing contextual relevance while minimizing content intrusiveness at the same time. This research is useful in understanding online video advertising as an effective alternative to the popular text based video advertising. By understanding the effectiveness of these new strategic forms of video advertising, inferences can be made about its impact on the users and inferences can be drawn about the future of online video as an advertising medium.
6. Kim C., Park S., Chang Y., Chang W. (Aug2011) Random effects model for estimating effectiveness of advertising in online marketplaces. Expert Systems with Applications; Aug2011, Vol.38 Issue 8, p9867-9878. Retrieved from EBESCO, University of Washington
This paper presents an application of the Bayesian Markov Chain Monte Carlo (MCMC) used to select cost-effective ad spots in online marketplaces. This paper would be useful in understanding the effective cost structure of current online advertising modules and predicting the future cost models and how they would change and impact advertising.
7. Rodgers S., Thorson E. (Fall 2000) The Interactive Online Model: How Users Perceive and Process Online Ads. Journal of Interactive Advertising, Vol 1 No 1 pp. 42‐61. Retrieved From http://www.benschweitzer.org/
This research uses various structures of understand the effectiveness of any kind of online advertising efforts. Various variables are found to be motives to switching motivations, conjoint analysis is performed to understand the users mode (highly motivated to playful) and a model is created to understand the reason and tipping point for any advertising campaign. This research will help in understanding the motivations for viewing online advertising and thus help in simulating a advanced model that will help in understanding the future need patterns of online users.