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concern implies higher volumes of user cancelled
online spending. A Pearson correlation test did not
reveal significant results (p=0.735, r= -0.157). Thus,
this hypothesis was not supported and could not be
accepted.
H7 suggests that a higher degree of online
privacy concern implies a higher level of refraining
from surfing to certain Web sites. A Pearson
correlation revealed a significant correlation
between the two variables (r=0.663, p=0.001), thus
hypothesis H7 was accepted.
H8 states that there is a negative relationship
between the degree of privacy concern and the
volume of online spending (the more the user is
concerned with privacy, the less he or she is going to
spend in e-commerce). Based on a correlation test
(r=-0.024, p=0.735), hypothesis H8 could not be
accepted.
6 CONCLUSIONS
This study attempted to gain a better understanding
of the privacy concern. Among its findings, the
novelty of the Internet environment by itself was
found not to affect the degree of online privacy
concern, meaning that web skills and experience
with the web were not related to the degree of that
concern. On the other hand, web usage and the
degree of online privacy concern were found to be
positively related.
The study found that people who suffered
previous online privacy invasions were likely to
purchase much less than persons who didn’t suffer
any previous online privacy invasion. Also, people
with a high degree of online privacy concern were
more likely to refrain from surfing in specific sites
for privacy reasons, and to purchase less products
and services online.
The results of this study imply some efforts that
should be taken by governments, businesses and
individuals in order to protect privacy and enable
online transactions. These include:
• Voluntary observance of fair information
practices including the role of trade
associations:
Since persons with previous experience of online
privacy invasions have higher levels of online
privacy concern, the observance of fair information
practices is vital..
• Technological approaches:
Today’s privacy enhancing technologies are
primitive in nature. Such technologies are often
cumbersome to use, unfriendly and require a degree
of knowledge exceeding that of the common Internet
consumer. The low level of usage of privacy
enhancing technologies found in this study evidence
this fact. Consequently, new, user-friendly,
technology-based approaches should be developed
to provide consumers with a greater control over the
disclosure of their personal information.
• Government as a customer:
The government can impact privacy concerns
through market forces, promoting strong privacy
laws for both the public and private sectors,
establishing independent privacy commissions to
oversee the implementation of these laws, educating
the public about privacy issues and encouraging
business self-regulation. In addition, the
government is also a major customer and has an
opportunity to influence the private sector through
its e-procurement policies.
REFERENCES
Bartel, S.K., & Grubbs, H.M. (2000). Dimensions of
privacy concerns among online consumers. Journal of
Public Policy & Marketing, 19(1), Spring, 62-73.
Bartel, S.K., & Grubbs, H.M. (1999). Flaming,
complaining, abstaining: How online users respond to
privacy concerns. Journal of Advertising, 28(3), Fall.
Bennett, M. (2000). Online privacy: Europe and America.
Giga Information Group, Giga World IT Forum 2000,
47461-MB99.
Cranon, R., Reagle, C.J., & Ackerman, H. (1999). Beyond
concern: Understanding net user’s attitudes about
online privacy. AT&T Labs Technical Research
Report TR99.4.3, April.
Foxman, R., & Kilcoyne, P. (1993). Information
technology, marketing practice, and consumer privacy:
Ethical issues. Journal of Public Policy & Marketing,
12(1), Spring, 106-119.
Hatch, O.G. (2000). Privacy in the digital age: A resource
for Internet users. U.S Senate Judiciary Committee.
http://judiciary.senate.gov/privacy.htm
Huainqing, W., Matthew, K.O.L., & Chen, W. (1998).
Consumer privacy concerns about Internet marketing.
Communications of the ACM, 41(3), March, 63-70.
Igbaria, M. (1990). End-user computing effective-ness: A
structural equation model. Omega, 18, 637-652.
Moon, Y. (2000). Intimate exchanges: Using computers to
elicit self-disclosure from consumers. Journal of
Consumer Research, 26, March, 323-338.
Novak, T.P., Hoffman, D.L., & Yung, Y. (2000).
Measuring the customer experience in online
environments: A structural modeling approach.
Marketing Science, 19(1), Winter, 22-42.
Wayner, P. (1999). Technology for anonymity: Names by
other Nyms. The Information Society, 15(2), 91-97.
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