Evaluating If Trust and Personal Information Privacy Concerns Are Barriers to Using Health Insurance That Explicitly Utilizes AI

Figures & data

Figure 1. Trust face to face, online, online with AI.

Figure 2. Research approach.

Figure 3. Research model and hypotheses.

Table 1. Constructs and their indicators.

Role	Construct	Item	Source of construct items
Enablers	Perceived Ease of Use	PEOU1B1/ PEOU1B2	(Davis 1989)
	Perceived Usefulness	PU1B1/ PU1B2	(Davis 1989)
Barriers	Trust in AI	T1B1/T1B2	(McKnight, Choudhury, and Kacmar 2002; McKnight et al. 2011)
	Personal Information Privacy Concerns from AI	PIPC1B1/PIPC1B2	(Dinev et al. 2013; Xu et al. 2008)
Outcome	Usage of insurance utilizing AI	UI1B1/UI1B2	(Zhao, Ni, and Zhou 2018; Wu, Li, and Fu 2011; Hoque and Sorwar 2017)

Table 2. Demographic information for both groups.

	AI not visible (ß1)	AI visible (ß2)
Gender
Female	98	106
Male	123	111
Age
Under 18	11	14
18–24	96	92
25–39	80	74
40–59	26	18
60 or older	8	19
Education level
Without educational level	8	12
High school	77	81
Undergraduate university degree	80	94
Post-graduate university degree	56	30
Income (in British Pounds)
No regular income	13	15
400–1200	26	16
1201–3000	71	85
3001–5000	84	81
> 5000	27	20
Total	221	217

Table 3. Mean values for both groups.

	Perceived Ease of Use	Perceived Usefulness	Trust	Perceived Info. Privacy Concern	Use of Health Insurance
AI not visible (ß1)	3.891	3.910	4.017	3.879	3.561
AI visible (ß2)	3.739	4.000	3.704	4.158	3.670

Table 4. Results of the measurement model analysis.

Items		AI not visible/AI visible
		Loadings	CR	AVE	Discriminant validity heterogeneity
					PU	PEOU	U	T	PIPC
Perceived Usefulness	PU-1	0.836/0.818	0.899/0.882	0.748/0.714
	PU-2	0.877/0.827
	PU-3	0.881/0.889
Perceived Ease of Use	PEOU-1	0.782/0.735	0.862/0.838	0.676/0.633	0.720/0.833
	PEOU-2	0.803/0.857
	PEOU-3	0.879/0.792
Use of Health Insurance	UI-1	0.861/0.773	0.874/0.869	0.698/0.690	0.416/0.759	0.215/0.189
	UI-2	0.804/0.851
	UI-3	0.840/0.865
Trust	T-1	0.842/0.891	0.896/0.898	0.741/0.747	0.243/0.402	0.084/0.189	0.842/0.819
	T-2	0.840/0.827
	T-3	0.899/0.873
Perceived Info. Privacy Concern	PIPC-1	0.879/0.896	0.914/0.923	0.779/0.798	0.004/0.184	0.064/0.189	0.592/0.587	0.576/0.573
	PIPC-2	0.881/0.916
	PIPC-3	0.888/0.868

Table 5. Test for measurement invariance.

Items	Outer Loadings-diff (AI not visible-AI visible)	p-Value
Perceived Usefulness
PU-1	0.019	.294
PU-2	0.050	.064
PU-3	0.008	.639
Perceived Ease of Use
PEOU-1	0.047	.225
PEOU-2	0.053	.886
PEOU-3	0.087	.010
Use of Health Insurance
UI-1	0.087	.008
UI-2	0.045	.850
UI-3	0.026	.829
Trust
T-1	0.048	.969
T-2	0.013	.358
T-3	0.025	.128
Perceived Info. Privacy Concern
PIPC-1	0.016	.789
PIPC-2	0.035	.909
PIPC-3	0.019	.227

Table 6. Multi-group comparison test results.

Path	Coefficients		Hypotheses	PLS-MGA: p-value (ß1vs ß2)
	AI not visible	AI visible
T-UI	0.536	0.414	H1: ß1 > ß2	.048
PIPC-UI	−0.221	−0.205	H2: ß1 < ß2	.576
PEOU-T	0.066	0.163	H3: ß1 = ß2	.827
PEOU-PIPC	0.060	0.135	H4: ß1 = ß2	.762
PEOU-PU	0.582	0.647	H5: ß1 = ß2	.858
PU-UI	0.237	0.443	H6: ß1 = ß2	.994
PEOU-UI	0.010	−0.019	H7: ß1 = ß2	.372

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