1. APA Citation:
Tam, K. Y., & Ho, S. Y. (2006). Understanding the impact of web personalization on user information processing and decision outcomes. Mis Quarterly
(4), 865–890. PDF
2. Purpose of the Research: To understand the impact of personalized content on user information processing and decision making, because little is known about the effectiveness of web personalization and the link between the IT artifact (the personalization agent) and the effects it exerts on a user’s information processing and decision making.
3. Methods: Theoretically develops and empirically tests a model of web personalization. The model is grounded on social cognition and consumer research theories. The research model depicts the different stages of web processing as (1) attention, (2) cognitive processing, (3) decision, and (4) evaluation of decision. The model highlights two sets of variables hypothesized to have an impact on these four stages. The two sets of variables are related to (1) web personalization and (2) goal specificity. The variables related to web personalization are: self reference and content relevance. Hypotheses were generated from the research model, and were empirically tested in a laboratory experiment and a field study.
The hypotheses are (also refer to the figure bellow):
Hypotheses related to Self Reference in Web Personalization:
H1: Users attend to self-reference web content to a larger extent than they attend to non-self-reference web content.
H2a: Users recall self-referent web content faster and more accurately than they recall non-self-referent web content.
H3a: Users exposed to self-referent web content will seek less information and spend less time on decision making than when they are exposed to non-self-referent web content.
H4a: Users accept offeres associated with self-referent web content to a larger extent than they accept offers associated with non-self-referent web content.
Hypotheses related to Content Relevance in Web Personalization:
H2b: Users recall web content relevant to their processing goal faster and more accurately than they recall irrelevant web content.
H4b: Users accept offers associated with relevant web content to a larger extent than they accept offers associated with irrelevant web content.
Hypotheses related to Processing Goal Specificity:
H2c: There is a larger difference in recall accuracy and response time between relevant and irrelevant web content for users with more-specific processing goals than for those with less-specific processing goals.
Hypotheses related to Evaluation:
H5a: Users evaluate self-referent web content more highly than they evaluate non-self-referent web content.
H5b: Users evaluate relevant web content more highly than they evaluate irrelevant web content.
The controlled lab experiment focuses on the tree variables hypothesized to attract users’ attention, affect their level of cognitive processing, and bias their decisions. The field study is based on a music download site and lasting for 6 weeks. They examined users’ behaviors by analyzing their web activities. Contents of the music site were driven by a commercial personalization agent and all activities of the web site were logged for the entire 6-week period.
4. Main Findings: The findings from the lab experiment and field study indicate that content relevance, self reference, and goal specificity affect the attention, cognitive processes, and decisions of web users in various ways. Also users are found to be receptive to personalized content and find it useful as a decision aid. Major findings are summarized in the table bellow. Only H2a is not supported (while content relevance leads to better re-call of the content, this is not obvious for self-relevance), and all other hypotheses are supported with statistical significance.
5. Analysis: This article provide good information on web personalization and how it impacts users’ decision outcomes. It also provides a snapshot on other related research of this line. Most research on web personalization comes from business management, e-commerce, marketing, etc. No matter what they do is to understand consumers, or to better design the personalization agents, or anything else, the ultimate goal is to maximize business opportunities, to sell products and to gain profit. They do not usually consider other side effect of personalization, such as echo chamber effect. I am not sure whether echo chamber effect will negatively or positively affect companies’ business. This may affect some small companies to get their new products rolling because it’s difficult for new things to get into the bubble of the consumers. However, maybe big companies who already got the consumers around their products love this to happen. As far as I know, the after effect to consumers, and the large impact to society of personalization are usually not considered in this line of research. Indeed, these issues may be a little out of scope of e-commerce research, and they may be usually addressed in other fields.