Quality, value, satisfaction, trust, a

short period of time because shoppers can place an order or request additional information
instantly and directly via Internet rather than having to order through another method (Cho,
1999).
As involvement in purchase decision has been conceptualized as pre-purchase intentions, we can propose that in the hierarchy-of-effects
model, this factor can considered as a step before purchase intention with a conative dimension:
H9: When consumers surf the Web, involvement in purchase decisions is positively related to purchase intentions.
The model we propose in this study is shown in figure 2. To facilitate its comprehension, we
did not drawn either the non-significant paths or those whose p is less than 0.10.
[insert figure 2 around here]
4. Data and Methodology
We test the structure of the proposed model in the context of a pharmaceutical Web site.
Health care is one sector of the economy where the Internet has become an invaluable tool for
communication. For wired consumers, healthcare ranks as the fourth most popular topic on the
Web (Bellman, Lohse and Johnson, 1999), while among women and seniors, health sites are the
second most popular destination (Cyber Dialogue, 1999). Obviously, the objectives of
pharmaceutical companies are geared more towards influencing consumer attitude, rather than
immediate online purchasing. As we mentioned in the introduction, the majority of the research
to date is on online retailing, but the empirical context is justified by our objective of developing
a comprehensive model of the effectiveness of the Web site through its content and its
informational design (Internet atmospherics), which are represented by navigational
characteristics, entertainment, informativeness, effectiveness and structure of the Web site.
The data for the study were collected from the homepage of an OTC drug from one of the
largest, well-known pharmaceutical companies in North America. (A recent study by Ipsos
PharmTrends reported that this OTC drug was number two with a 23% U.S. market share,
compared to the leader’s 32% share).
Here, we propose a Web-based methodology that minimizes biases of existing ad testing
methods. Our methodology is based on an experimental method that is totally clear and
unobtrusive to each respondent. We measured their answers which reflect their flow and viewing
behavior on a given Web site after they did their normal surfing activities on it. Hence,
measurements are based on actual respondent behavior and do not suffer from any experimental
effects or any self-report biases. The methodology is designed to test the effectiveness of
207