Avoiding the Privacy Paradox Using Preference-Based Segmentation: A Conjoint Analysis Approach
Abstract
:1. Introduction
2. Literature Review
2.1. Online Social Networks and Privacy
2.2. Privacy Paradox
3. Materials and Methods
3.1. Conjoint Analysis Design
3.2. Privacy-Related Survey Design
- Purpose of using OSNs and their primary choice of OSN;
- Frequency of activities such as establishing new friendships, chatting, general information sharing, finding information about social events, etc. on OSNs;
- Intentions of sharing personal data (real name, profile picture, e-mail, phone number, date of birth, place of residence, relationship status) within OSNs; users are usually more concerned about their privacy compared to other online situations. Therefore, content sharing is one of the key features in OSNs.
- Privacy-related behavior.
4. Results
4.1. Respondents’ Behavior in Using OSNs
4.2. Respondents’ Concerns for Data Privacy and Safety
4.3. Aggregated Respondents’ Preferences
4.4. Cluster Analysis
4.4.1. Cluster 1: Fundamentalists
4.4.2. Cluster 2: Pragmatists Tending to Privacy Control
4.4.3. Cluster 3: Pragmatists
4.4.4. Cluster 4: Socially Oriented Pragmatists
4.4.5. Cluster 5: Unconcerned
5. Comparison of WPSI and CA Clusters
- 54.55% of individuals never access applications that try to collect data (the sample average is 39.6%), while others do it occasionally, and none of them do it always;
- As many as 72.73% individuals do not access their profile from public computers (the average is 62.99%);
- 63.64% do not accept friendship requests from unknown persons;
- More than half of the group allows access to personal data only to certain friends (the sample average is 28.35%);
- None of these respondents allow access to photos online, and 36.36% allow access only to particular friends (the average is 24.67%);
- No one had any experience with abuse and violation of privacy on OSNs;
- No one would continue to use the same OSNs in case they needed to pay (most would choose some of them);
- When it comes to concern for personal and friend data, average scores are 2.91 and 2.36, respectively.
- 10% always and 50% occasionally access applications that try to collect data;
- Significantly lower percentages never access their profile from public computers (40% compared to an average of 62.99%);
- 50% of these respondents accept friendship requests from unknown persons occasionally or always;
- As many as 30% allow access to their personal data to everyone on the OSN (sample average is 9.73%);
- As many as 50% would continue to use all OSNs in case they needed to pay;
- They show much less concern for both personal data and information about friends. Average scores for these criteria are 2.2 and 1.7.
6. Discussions and Conclusions
- Benefit variable (such as perceived benefit) which corresponds to utility in our conjoint analysis study.
- Privacy risk variable (such as information privacy concerns) corresponding to the factor “Information used by the OSN provider”.
- Coping variable (such as self-efficacy and privacy control) corresponding to the factor “User privacy control”.
- Research based on OSN users’ preferences is extended and the body of knowledge on privacy attitudes and behavior is enriched.
- Heterogeneity of OSN user preferences was identified and five cluster are isolated.
- A new more sophisticated categorization of OSN users is proposed, allowing for a more accurate prediction of privacy behavior.
Author Contributions
Funding
Conflicts of Interest
Appendix A
Cluster 1 | Cluster 2 | Cluster 3 | Cluster 4 | Cluster 5 | Sample | |
---|---|---|---|---|---|---|
Gender (p = 0.024) *** | ||||||
Male | 28.72% | 23.53% | 25.17% | 34.24% | 50.00% | 28.59% |
Female | 71.28% | 76.47% | 74.83% | 65.76% | 50.00% | 71.41% |
Age (p = 0.007) ** | ||||||
16–19 | 14.54% | 12.25% | 24.50% | 11.96% | 13.64% | 15.18% |
20–25 | 52.84% | 58.33% | 43.71% | 63.59% | 40.91% | 54.57% |
26–35 | 18.44% | 14.22% | 12.58% | 11.96% | 31.82% | 15.30% |
36–45 | 9.22% | 12.75% | 14.57% | 10.33% | 9.09% | 11.27% |
>45 | 4.96% | 2.45% | 4.64% | 2.17% | 4.55% | 3.68% |
Education (p = 0.007) ** | ||||||
Primary school | 2.48% | 1.47% | 12.58% | 4.35% | 4.55% | 4.51% |
High school | 42.55% | 44.12% | 36.42% | 40.76% | 40.91% | 41.40% |
Undergraduate | 34.75% | 37.75% | 32.45% | 32.61% | 36.36% | 34.64% |
Master degree | 18.09% | 15.20% | 16.56% | 19.57% | 18.18% | 17.44% |
PhD degree | 2.13% | 1.47% | 1.99% | 2.72% | 0.00% | 2.02% |
Occupation (p = 0.000) * | ||||||
Students (high school) | 4.96% | 2.94% | 17.22% | 4.89% | 4.55% | 6.64% |
Students (university) | 54.26% | 64.22% | 48.34% | 65.22% | 50.00% | 57.89% |
Unemployed | 7.45% | 6.86% | 5.30% | 4.89% | 9.09% | 6.41% |
Employed | 33.33% | 25.49% | 29.14% | 24.46% | 36.36% | 28.83% |
Retired | 0.00% | 0.49% | 0.00% | 0.54% | 0.00% | 0.24% |
Cluster 1 | Cluster 2 | Cluster 3 | Cluster 4 | Cluster 5 | Sample | |
---|---|---|---|---|---|---|
Sharing Intentions | ||||||
Personal Data (Real Name, Date of Birth...) * (p = 0.000) * | ||||||
All OSN users | 8.51% | 8.82% | 6.62% | 13.04% | 27.27% | 9.73% |
Friends and their friends | 5.32% | 4.90% | 7.28% | 6.52% | 31.82% | 6.52% |
Just friends | 53.19% | 59.31% | 50.99% | 60.33% | 36.36% | 55.40% |
Selected friends | 32.98% | 26.96% | 35.10% | 20.11% | 4.55% | 28.35% |
Photos (p = 0.015) ** | ||||||
All OSN users | 3.90% | 3.43% | 3.97% | 3.80% | 13.64% | 4.03% |
Friends and their friends | 8.87% | 6.86% | 10.60% | 10.87% | 27.27% | 9.61% |
Just friends | 59.93% | 61.76% | 58.94% | 67.39% | 54.55% | 61.68% |
Selected friends | 27.30% | 27.94% | 26.49% | 17.93% | 4.55% | 24.67% |
Posts (p = 0.051) *** | ||||||
All OSN users | 6.03% | 5.88% | 7.28% | 4.89% | 13.64% | 6.17% |
Friends and their friends | 5.32% | 6.37% | 9.93% | 7.61% | 22.73% | 7.35% |
Just friends | 65.96% | 62.25% | 57.62% | 70.11% | 54.55% | 64.18% |
Selected friends | 22.70% | 25.49% | 25.17% | 17.39% | 9.09% | 22.30% |
Privacy Related Behaviour | ||||||
I Access Applications that Collect PersonalData ***(p = 0.098) | ||||||
Never | 42.91% | 40.69% | 39.07% | 32.07% | 40.91% | 39.26% |
Sometimes | 54.26% | 55.39% | 54.97% | 64.13% | 45.45% | 56.58% |
Always | 2.84% | 3.92% | 5.96% | 3.80% | 13.64% | 4.15% |
I Access My Profile from Public Computers **(p = 0.003) | ||||||
Never | 67.02% | 68.63% | 59.60% | 55.98% | 40.91% | 62.99% |
Sometimes | 32.62% | 29.41% | 36.42% | 41.30% | 50.00% | 34.88% |
Always | 0.35% | 1.96% | 3.97% | 2.72% | 9.09% | 2.14% |
I Accept Friend Requests from Strangers *(p = 0.000) | ||||||
Never | 66.31% | 69.61% | 56.29% | 60.33% | 50.00% | 63.58% |
Sometimes | 32.98% | 29.41% | 42.38% | 37.50% | 36.36% | 34.88% |
Always | 0.71% | 0.98% | 1.32% | 2.17% | 13.64% | 1.54% |
Respondents’ Concerns aboutPrivacy and Safety *(p = 0.000) | ||||||
Own personal data | 3.24 | 3.1 | 2.98 | 2.9 | 2.05 | 3.05 |
friends’ personal data | 2.72 | 2.71 | 2.62 | 2.44 | 1.55 | 2.60 |
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Dimension | Factor | Level | Code |
---|---|---|---|
I Popularity | OSN popularity among acquaintances | 25% | N1 |
50% | N2 | ||
75% | N3 | ||
II Customizability | Possibility to customize OSN environment | Yes | C1 |
No | C2 | ||
III Privacy | Privacy Control options given to users | All or friends | O1 |
Predefined groups | O2 | ||
Particular friend | O3 | ||
Information used by OSN provider | No information | P1 | |
Demographic | P2 | ||
All information | P3 |
Demographic | Category | Number | Percent |
---|---|---|---|
Gender | Male (M) | 241 | 28.59% |
Female (F) | 602 | 71.41% | |
Age | 16–19 | 128 | 15.18% |
20–25 | 460 | 54.57% | |
26–35 | 129 | 15.30% | |
36–45 | 95 | 11.27% | |
>45 | 31 | 3.68% | |
Level of education | Primary school | 38 | 4.51% |
High school | 349 | 41.40% | |
Undergraduate | 292 | 34.64% | |
Master degree | 147 | 17.44% | |
PhD degree | 17 | 2.02% | |
Employment status | Students (high school) | 56 | 6.64% |
Students (university) | 488 | 57.89% | |
Unemployed | 54 | 6.41% | |
Employed | 243 | 28.83% | |
Retired | 2 | 0.24% | |
Relationship status | Single | 417 | 49.47% |
In relationship | 311 | 36.89% | |
Married | 115 | 13.64% |
Factor | Level | Utility Estimate | Std. Error | Importance Scores |
---|---|---|---|---|
OSN popularity | 25% | −0.639 | 0.035 | 32.61% |
50% | 0.200 | 0.035 | ||
75% | 0.438 | 0.035 | ||
OSN environment customizability acoording own preferences | Yes | 0.029 | 0.026 | 10.51% |
No | −0.029 | 0.026 | ||
Privacy control by User | All/Friends only | −0.370 | 0.035 | 25.15% |
Predefined groups | −0.037 | 0.035 | ||
Particular friend | 0.407 | 0.035 | ||
Information used by OSN provider | No information used | 0.466 | 0.035 | 31.73% |
Demography only | 0.173 | 0.035 | ||
All information | −0.639 | 0.035 | ||
(Constant) | - | 2.729 | 0.026 | - |
Factor | Level | Cluster 1 n = 282 (33.45%) | Cluster 2 n = 204 (24.20%) | Cluster 3 n = 151 (17.91%) | Cluster 4 n = 184 (21.83%) | Cluster 5 n = 22 (2.61%) |
---|---|---|---|---|---|---|
Part-Worth Utilities | ||||||
OSN popularity | 25% | −0.558 | −0.548 | −0.372 | −1.011 | −1.237 |
50% | 0.245 | 0.202 | 0.077 | 0.248 | 0.066 | |
75% | 0.313 | 0.346 | 0.295 | 0.763 | 1.172 | |
Customizability | Yes | 0.030 | −0.011 | 0.093 | 0.026 | −0.015 |
No | −0.030 | 0.011 | −0.093 | −0.026 | 0.015 | |
Privacy control by user | All/Friends only | −0.331 | −0.651 | −0.286 | −0.232 | 0.005 |
Predefined groups | −0.031 | −0.069 | −0.038 | −0.016 | 0.005 | |
Particular friend | 0.362 | 0.720 | 0.324 | 0.248 | −0.010 | |
Information used by OSN provider | No information used | 0.794 | 0.365 | 0.260 | 0.295 | 0.035 |
Demography only | 0.285 | 0.142 | 0.057 | 0.154 | −0.025 | |
All information | −1.079 | −0.507 | −0.316 | −0.449 | −0.010 | |
Relative Factor Importance | ||||||
OSN popularity | 24.56% | 27.36% | 24.76% | 49.86% | 94.06% | |
Customizability | 7.59% | 6.63% | 23.59% | 9.68% | 1.14% | |
Privacy control by user | 20.17% | 40.06% | 26.40% | 17.97% | 1.95% | |
Information used by OSN provider | 47.68% | 25.95% | 25.25% | 22.49% | 2.86% | |
Privacy Total | 67.85% | 66.01% | 51.65% | 40.46% | 4.81% |
WPSI | Privacy Fundamentalists | Pragmatists | Privacy Unconcerned | Total | |
---|---|---|---|---|---|
CA | |||||
Fundamentalists | 143 (38.86%) | 128 (29.09%) | 11 (31.43%) | 282 (33.5%) | |
Pragmatists tending to privacy control | 80 (21.74%) | 116 (26.36%) | 8 (22.86%) | 204 (24.2%) | |
Pragmatists | 62 (16.85%) | 80 (18.18%) | 9 (25.71%) | 151 (17.9%) | |
Socially oriented pragmatists | 73 (19.84%) | 105 (23.86%) | 6 (17.14%) | 184 (21.8%) | |
Unconcerned | 10 (2.72%) | 11 (2.50%) | 1 (2.86%) | 22 (2.6%) | |
Total | 368 (43.7%) | 440 (52.2%) | 35 (4.2%) | 843 |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Kuzmanovic, M.; Savic, G. Avoiding the Privacy Paradox Using Preference-Based Segmentation: A Conjoint Analysis Approach. Electronics 2020, 9, 1382. https://doi.org/10.3390/electronics9091382
Kuzmanovic M, Savic G. Avoiding the Privacy Paradox Using Preference-Based Segmentation: A Conjoint Analysis Approach. Electronics. 2020; 9(9):1382. https://doi.org/10.3390/electronics9091382
Chicago/Turabian StyleKuzmanovic, Marija, and Gordana Savic. 2020. "Avoiding the Privacy Paradox Using Preference-Based Segmentation: A Conjoint Analysis Approach" Electronics 9, no. 9: 1382. https://doi.org/10.3390/electronics9091382