Exploring the
Demographics of Online Security Concerns
Sasan Rahmatian,
Department of Information Systems and Decision Sciences
The Sid Craig School of Business, California
State University Fresno, Fresno, CA 93740
559.278.4376,
sasan_rahmatian@csufresno.edu
The level of popularity of e-business depends, among other things,
on customers’ concerns about the transmission of sensitive data in the conduct
of electronic transactions. Although
more business is being conducted online overall, it is not known whether
certain segments of the population are more hesitant to purchase online for
fear of possible theft or misuse of their sensitive data. This research investigates whether
demographic differences exist among e-commerce users regarding online security
concerns. Specifically, it explores
whether differences such as age, income, and relative distance to shopping
areas are related to the user’s perceptions of data security while transmitting
personal and/or financial data over the Internet.
First, if e-business owners and
managers have information that identifies areas of weak participation in
e-commerce, they might be better prepared to structure their marketing
campaigns towards inclusion of those groups.
It is hypothesized that:
H1:
demographic differences exist relating to perceptions of the security risk of e-commerce
transactions.
Second, knowledge about demographic differences and the perceptions of risk could possibly be used to predict use of e-commerce. It is hypothesized that:
H2: demographic factors and perceptions of
security risks can be used to predict use of e-commerce.
Third, it could be argued that e-commerce knowledge of their potential customers’ computer activities and demographic factors could be used to identify their differences in e-commerce use. It is hypothesized that:
H3: Differences in the use of e-commerce are
related to the amount of computer use and demographic factors.
Methodology
The goal was to survey a representative cross section of individuals that use, or might in the future use, e-commerce for purchases. One hundred seventy-three people participated in this survey. Of those surveyed, 81% owned a computer and 43.4% used a computer at work very often. 38.9% indicated that they did not make purchases on the Internet, while 29.1 % indicated they sometimes made purchases for themselves or their family on the Internet.
Of the participants, 44% were males and 56% were females. The largest age group represented at 51.4% was 16 - 30 years of age. Whites, at 53.7%, represented the largest ethnic group followed by Hispanics at 34.9%. Forty-four participants have had some college courses while 17.1% have an Associate degree, and 20.6% have Graduate degrees. Income levels range from 30.9% at the lowest income level, (0 to $15,000) to .6% at the highest income level, (over $75,000). Also observed were that 42.9% live in the suburbs and 39.4% drive no further than 1 to 5 miles to shop for non-grocery items.
The questionnaire asked the participants to indicate for each question the answer that most closely represents facts or their feelings/beliefs about themselves and their concerns about passing sensitive information during an e-commerce transaction. The questionnaire provided multiple-response alternatives to any single question.
The participants were asked specific questions that identify their gender, age, ethnicity, average hours of work per week, yearly income, marital status, number of dependents, and the distance to shopping.
Participants were asked specific questions that relate to how they believe the sensitive data they pass over the Internet might be intercepted during transmission, and if they believed their data would be misused by the e-business to which they were sending it. The participants were also asked about their willingness or reluctance to buy online, and the frequency with which they make purchases online. For these measures the same scale was used (a = not at all, e = very often).
The study required approximately two to five minutes of the participant’s time to complete. A set of instructions was conveyed to the participants either in written form or verbally. The directions asked the participants to respond to questions by indicating an appropriate answer that most closely represents their feelings or beliefs or facts about themselves and their concerns about passing sensitive information concerning potential e-commerce purchases.
The first hypothesis predicted that demographic differences exist relating to perceptions of the security risk of e-commerce transactions. The chi-square analysis was used to test for a relationship between demographic factors and the perception that sensitive data would be intercepted during transmission. The test showed a statistically significant result (p < .05) for ethnicity, marginally significant for gender differences (p < .10), but not statistically significant for age.
The chi-square analysis was also used to test for a relationship between demographic factors and the perception that sensitive data would be misused after transmission. It showed results that were not statistically significant. The preceding tests showed mixed results. This would lead to the conclusion that Hypothesis one was partially supported.
The second hypothesis predicted that
demographic factors and perceptions of security risks can be used to predict
use of e-commerce.
A multiple regression analysis was used to determine if demographic factors and perceptions of security risks could predict use of e-Commerce. The overall regression was statistically significant (p < .05). Hypothesis two was supported. Among all the factors entered, the significant indicators were gender, income level, and number of dependents.
The third hypothesis predicted that differences in e-commerce use are related to the amount of computer use and demographic factors. Consistent with hypothesis three, a significant correlation between the use of e-commerce and amount of computer use at work was found (r = .34, p < .01). Hypothesis three was supported.
A t-test on the use of e-commerce between those who own a computer and those who do not own a computer was also significant (t(169) = 5.74, p < .01). The chi-square analysis on the use of e-commerce by gender (Χ2(4) = 21.48, p < .05) and ethnicity (Χ2(16) = 76.34, (p < .05)) were also significant. The chi-square analysis for age (Χ2(12) = 9.91, (p > .05)) was not significant. The analyses show that overall Hypothesis 3 was supported.
E-businesses could utilize this survey’s results to affect the use of e-commerce by using target marketing techniques that would capitalize on factors concerning potential e-commerce user’s security concerns. By knowing what concerns are important to e-consumers, businesses can structure marketing techniques to address the issues concerning perceptions of online security. By doing so, they might increase their sales. They could also focus on under-represented groups in the e-commerce users demographically.
The statistical significance of this study would indicate that there is reason for e-businesses globally to be aware and react to potential e-customers security concerns. In spite of the attempt to collect data from a diverse sample, the data collected for this survey is dominated by college students and is geographically restricted to the Central and Southern California areas.
Some relevant variables were not examined in this study. This study did not examine, for instance, participants’ reasons for preferring to buy at a traditional “brick and mortar” establishment to an e-business site.
Further, this study did not examine the risks or benefits that might sway e-consumers’ perceptions of factors other than security concerns that might lead to their increased or decreased purchasing online.