Breaching the contract? Using social contract theory to explain individuals’ online behavior to safeguard privacy

Figures & data

Table 1. Average Variance Extracted (AVE), the square root of the AVE (Diagonal in Bold) and zero-order correlations between constructs (Off-Diagonal).

		Latent construct
Latent construct	AVE	1.	2.	3.
1. Privacy concerns	.74	.86
2. Trust perceptions	.62	−.33***	.79
3. Risk perceptions	.47	.59***	−.45***	.68

The discriminant validity was assessed using the Fornell and Larcker criterion (1981) by comparing the square root of each AVE in the diagonal with the zero-order correlations (off-diagonal) for each construct. As the levels of the square root of the AVE for each construct are greater than the zero-order correlation involving the construct, the discriminant validity can be accepted for this measurement model. Abbreviations: AVE = average variance extracted.

***p < .001.

Table 2. LCA results with different fit indices.

No. of classes	LL	BIC	No. par	LRT p-value	Entropy
1	– 6039.447	12,121.544	6	N/A	N/A
2	– 5695.052	11,461.186	10	0.0000	0.728
3	– 5610.866	11,321.247	14	0.0000	0.797
4	– 5570.313	11,268.575	18	0.0017	0.817
5	– 5525.343	11,207.066	22	0.0270	0.755
6	– 5500.593	11,186.000	26	0.5148	0.785

The different fit-indices: LL = log likelihood, BIC = Bayesian Information Criterion, No. par = number of parameters, LRT = Lo-Mendell-Rubin Adjusted LRT Test.

Table 3. Class count, proportions, and average latent class probabilities for most likely membership (Row) by Class (Column).

			Class
Class	Count	Proportions	1.	2.	3.	4.	5.
1. Ambivalent user	57	.047	.806	.000	.059	.032	.103
2. Carefree user	58	.047	.000	.877	.123	.000	.000
3. Neutral user	513	.420	.011	.020	.867	.000	.102
4. Highly-concerned user	252	.206	.012	.000	.000	.889	.099
5. Wary user	342	.280	.035	.000	.139	.079	.747

The values in bold indicate the average latent class probabilities for each assigned class.

Table 4. Estimated means, standard errors, and confidence intervals for privacy concerns, trust perceptions, and risk perceptions for the five-class solution.

	Ambivalent user (n = 57)	Carefree user (n = 58)	Neutral user (n = 513)	Highly-concerned user (n = 252)	Wary user (n = 342)
	M (SE) [95% CI]	M (SE) [95% CI]	M (SE) [95% CI]	M (SE) [95% CI]	M (SE) [95% CI]	F-test (df)	p-value
Privacy concerns	2.81 (.12)^b [2.57, 3.05]	1.96 (.11)^a [1.74, 2.18]	3.94 (.04)^c [3.87, 4.02]	6.32 (.05)^e [6.22, 6.41]	5.30 (.05)^d [5.21, 5.39]	596.90 (4)	< .001
Trust perceptions	3.07 (.16)^b [2.75, 3.39]	4.03 (.22)^c [3.60, 4.47]	3.82 (.04)^c [3.74, 3.89]	2.07 (.07)^a [1.94, 2.20]	3.32 (.06)^b [3.21, 3.43]	135.55 (4)	< .001
Risk perceptions	6.12 (.07)^d [5.98, 6.26]	2.83 (.08)^a [2.67, 2.99]	4.22 (.02)^b [4.18, 4.26]	6.52 (.03)^e [6.46, 6.58]	5.32 (.02)^c [5.27,5.37]	1380.99 (4)	< .001

Different superscripts indicate statistically significant differences between figures in a row at p < .001. Lowest figures in a row are assigned “a,” then “b,” etc. Abbreviation: 95% CI = 95% Confidence intervals.

Figure 1. Estimated means of privacy concerns, trust and risk for each type.

Table 5. Multinomial regression predicting membership of the classes using socio-demographics, knowledge, and online buying habits.

	Ambivalent user (n = 57)	Carefree user (n = 58)	Highly-concerned user (n = 252)	Wary user (n = 342)
	b (SE)	b (SE)	b (SE)	b (SE)
Constant	– 1.42 (.99)	– .75 (.93)	– 1.22* (.57)	– .60 (.49)
Female	– .38 (.29)	– .02 (.28)	– .24 (.16)	– .06 (.14)
Age	.02^† (.01)	– .01 (.01)	.02*** (.01)	.01* (.00)
Educational level	– .09 (.10)	.02 (.10)	.04 (.06)	.01 (.05)
Knowledge	– .10 (.33)	– .03 (.33)	.60** (.19)	.45** (.17)
Online buying habits	– .27* (.13)	– .36** (.12)	– .33*** (.07)	– .17** (.06)

***p < .001. **p < .01. *p < .05; ^†p < .10. The “Neutral User” (n = 513) is the reference category. R² = .076 (Nagelkerke).

Table 6. Predicting change in adaptive behavior to safeguard privacy.

	Adaptive behaviorwave 2
	B (Bootstrap SE)
Constant	1.20 (.21)***
Adaptive behaviorwave 1	.49 (.03)***
Ambivalent user (reference = Neutral user)	.28 (.15)^†
Carefree user	– .09 (.11)
Highly-concerned user	.21 (.07)**
Wary user	.10 (.06)^†
Female	.09 (.05)^†
Age	.00 (.00)
Educational level	– .05 (.02)**
Online buying habits	– .06 (.02)**
Knowledge	– .05 (06)
N	1060
R^2	.3148

***p < .001. **p < .01. *p < .05. ^†p < .10. SE = Standard Error, bootstrapping (with 5,000 bootstrap samples).

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 39–50. Retrieved from www.jstor.org/stable/3151312

 Web of Science ®Google Scholar