Interrelationships among predictors of automated vehicle acceptance: a structural equation modelling approach

Figures & data

short-legendFigure 1. Automated shuttle by Robosoft on a public road in a mixed traffic situation in Trikala, Greece.

Figure 2. Significant structural path relationships in second model. Dashed arrows denote moderation effects.

Table 1. Measurement of study variables.

Construct	Measurement	Source
Performance expectancy (PE)	PE1: I find the ARTS a useful mode of transport. PE2: Using the ARTS to travel helps me to achieve things that are important to me.	Davis, 1989; Madigan et al. 2016; Venkatesh, Thong, and Xu 2012
Effort expectancy (EE)	EE1: My interaction with the ARTS is clear and understandable. EE2: I find the ARTS easy to use EE3: Learning to use an ARTS is easy for me.	Davis, 1989; Madigan et al. 2016; Venkatesh, Thong, and Xu 2012
Social influence (SI)	SI1: People who are important to me think that I should use ARTS. SI2: People who influence my behavior think that I should use ARTS. SI3: People whose opinions I value would like me to use ARTS.	Davis, 1989; Madigan et al. 2016; Venkatesh, Thong, and Xu 2012
Facilitating conditions (FC)	FC1: I have the resources necessary to use ARTS. FC2: I have the knowledge necessary to use ARTS.	Davis, 1989; Madigan et al. 2016; Venkatesh, Thong, and Xu 2012
Hedonic motivation (HM)	HM1: Using ARTS is fun. HM2: Using ARTS is entertaining. HM3: Using ARTS is enjoyable.	Davis, 1989; Madigan et al. 2016; Venkatesh, Thong, and Xu 2012
Behavioural intention (BI)	BI1: Assuming that I had access to ARTS, I predict that I would use it in the future. BI2: If ARTS become available permanently, I plan to use it. BI3: I intend to use ARTS again during the demonstration period.	Davis, 1989; Madigan et al. 2016; Venkatesh, Thong, and Xu 2012
Car use (CU)	CU1: Days a week using a car	Welch, 2015
Public transport use (PTU)	PTU1: Days a week using any form of public transport
Technology savviness (TS)	TS1: When it comes to trying a new technology product, I am generally: a) among the last, b) in the middle, c) among the first.	Merat and Barnard 2010; Merat et al. 2018
Automated shuttle experience (AS–EXP)	AS–EXP1: Number of interactions with the automated shuttle	Karahanna, Agarwal, and Angst 2006
	AS–EXP2: Number of times using the automated shuttle

Table 2. Descriptive statistics and results of the confirmatory factor analysis.

Latent variable	Observed variable	M	SD	ƛ	p-value	αv > 0.7	CR > 0.7	AVE > 0.5	VIF < 3.3
Performance expectancy (PE)		3.62	0.84			0.77	0.78	0.64	2.36
	PE1: I find the ARTS a useful mode of transport.			0.83
	PE2: Using the ARTS to travel helps me to achieve things that are important to me.			0.77	0.000
Effort expectancy (EE)		3.92	0.71			0.88	0.89	0.72	1.70
	EE1: My interaction with the ARTS is clear and understandable.			0.81
	EE2: I find the ARTS easy to use.			0.91	0.000
	EE3: Learning to use an ARTS is easy for me.			0.83	0.000
Social influence (SI)		3.37	0.79			0.89	0.89	0.74	2.22
	SI1: People who influence my behaviour think that I should use ARTS.			0.83
	SI2: People who are important to me think that I should I should use ARTS.			0.89	0.000
	SI3: People whose opinions I value would like me to use ARTS.			0.85	0.000
Facilitating conditions (FC)		3.91	0.75			0.85	0.84	0.73	1.97
	FC1: I have the resources necessary to use ARTS.			0.84
	FC2: I have the knowledge necessary to use ARTS.			0.87	0.000
Hedonic motivation (HM)		3.82	0.74			0.87	0.87	0.68	2
	HM1: Using ARTS is fun.			0.84
	HM2: Using ARTS is entertaining.			0.86	0.000
	HM3: Using ARTS is enjoyable.			0.79	0.000
Behavioural intention (BI)		3.74	0.74			0.90	0.90	0.75	–
	BI1: Assuming that I had access to ARTS, I predict that I would use it in the future.			0.80
	BI2: If ARTS become available permanently, I plan to use it.			0.90	0.000
	BI3: I intend to use ARTS again during the demonstration period.			0.89	0.000
CFI	0.97
RMSEA	0.06
SRMR	0.03
χ^2/df	2.26

Note: M = Mean, SD = Standard deviation, ƛ = Lambda, factor loading, α = Cronbach alpha, CR = Composite reliability, AVE = Average variance extracted, VIF = Variance inflation factor, ARTS = Automated Rapid Transit Systems.

Table 3. Inter-construct correlation matrix.

Construct	Performance expectancy	Effort expectancy	Social influence	Facilitating conditions	Hedonic motivation	Behavioural intention
Performance expectancy	0.80
Effort expectancy	0.62	0.85
Social influence	0.44	0.38	0.86
Facilitating conditions	0.54	0.68	0.33	0.79
Hedonic motivation	0.51	0.69	0.45	0.64	0.82
Behavioural intention	0.60	0.59	0.51	0.59	0.68	0.87

Note: The diagonal values represent the square root of the average variance extracted (AVE).

Table 4. Structural equation models: hypothetical path, standardized path coefficients (β), and variance explained (R ² ).

Hypothetical path	First model: Effect β	Confidence interval		Second model: Effect β	Confidence interval
		5%	95%		5%	95%
H1: Performance expectancy → behavioural intention (b)*	0.37***	0.127	0.423	0.41***	0.139	0.390
H2a: Effort expectancy → behavioural intention (c)*	-0.23, n.s.	-0.443	0.007	-0.29*	-0.506	-0.046
H2b: Effort expectancy → performance expectancy (a)*	0.66***	0.575	1.135	0.51***	0.414	1.084
H2b: Indirect effect = a* b	0.24**	0.078	0.391	0.22**	0.060	0.349
H2b: Total = c + (a* b)	0.02, n.s.	-0.153	0.187	-0.08, n.s.	-0.290	0.139
H3: Social influence → behavioural intention	0.12*	0.004	0.201	0.09, n.s.	-0.003	0.211
H4: Facilitating conditions → behavioural intention	0.21*	0.023	0.370	0.33*	0.010	0.592
H5: Hedonic motivation → behavioural intention	0.48***	0.256	0.604	0.43***	0.195	0.579
H6: Facilitating conditions → performance expectancy	0.17, n.s.	-0.058	0.479	-0.25, n.s.	0.106	0.795
H7: Facilitating conditions → effort expectancy	0.47***	0.296	0.617	0.79***	0.552	0.947
H8: Facilitating conditions → hedonic motivation	0.67***	0.566	0.831	0.84***	0.732	0.954
H9: Social influence → performance expectancy	0.27***	0.176	0.450	0.31***	0.409	0.757
H10: Social influence → effort expectancy	0.01, n.s.	-0.080	0.096	-0.00, n.s.	-0.100	0.093
H11: Social influence → facilitating conditions	0.37***	0.227	0.454	0.51***	0.562	0.796
H12: Social influence → hedonic motivation	0.24***	0.134	0.336	0.12**	0.054	0.277
H13: Hedonic motivation → effort expectancy	0.42***	0.231	0.548	0.17, n.s	-0.028	0.347
H14: Hedonic motivation → performance expectancy	-0.13, n.s.	-0.414	0.099	-0.18, n.s.	-0.536	0.039
H15: Car use → performance expectancy	-0.03, n.s.	-0.036	0.018	-0.02, n.s.	-0.037	0.018
H16: Car use → effort expectancy	-0.01, n.s.	-0.020	0.016	-0.02, n.s.	-0.023	0.012
H17: Car use → facilitating conditions	0.08, n.s.	-0.009	0.043	0.04, n.s.	-0.010	0.038
H18: Car use → hedonic motivation	-0.08, n.s.	-0.040	0.002	-0.06, n.s.	-0.039	0.002
H19: Car use → behavioural intention	-0.16***	-0.053	-0.018	-0.12***	-0.054	-0.018
H20: Public transport use → performance expectancy	-0.03, n.s.	-0.019	0.010	-0.02, n.s.	-0.019	0.010
H21: Public transport use → effort expectancy	0.01, n.s.	-0.008	0.011	0.02, n.s.	-0.006	0.012
H22: Public transport use → facilitating conditions	-0.09, n.s.	-0.025	0.002	-0.06, n.s..	-0.024	0.002
H23: Public transport use → hedonic motivation	0.03, n.s.	-0.008	0.015	0.03, n.s.	-0.006	0.016
H24: Public transport use → behavioural intention	0.00, n.s.	-0.009	0.009	0.00, n.s.	-0.009	0.009
H25: Technology savviness → performance expectancy	-0.12*	-0.254	-0.028	0.10*	0.045	0.340
Interaction of social influence × technology savviness → performance expectancy	–	–	–	-0.23***	-0.137	-0.070
H26: Technology savviness → effort expectancy	−0.00, n.s.	−0.076	0.073	-0.01, n.s.	-0.100	0.071
H27: Technology savviness → social influence	0.16**	0.040	0.277	0.16**	0.040	0.277
H28: Technology savviness → facilitating conditions	0.20**	0.080	0.293	0.44***	0.492	0.699
Interaction of social influence × technology savviness → facilitating conditions	–	–	–	-0.42***	-0.155	-0.107
H29: Technology savviness → hedonic motivation	0.04, n.s.	-0.051	0.128	0.01, n.s.	-0.083	0.119
H30: Technology savviness → behavioural intention	0.02, n.s.	-0.058	0.090	0.01, n.s.	-0.071	0.097
H31–1: Number of interactions → performance expectancy	-0.03, n.s.	-0.068	0.034	-0.02, n.s.	-0.066	0.037
H32–1: Number of interactions → effort expectancy	0.06, n.s.	-0.011	0.055	0.05, n.s.	-0.006	0.059
H33–1: Number of interactions → facilitating conditions	-0.08, n.s.	-0.081	0.015	-0.04, n.s.	-0.067	0.023
H34–1: Number of interactions → hedonic motivation	0.08, n.s.	-0.005	0.074	0.05, n.s.	-0.007	0.069
H35–1: Number of interactions → behavioural intention	-0.05, n.s.	-0.051	0.014	-0.03, n.s.	-0.050	0.015
H31–2: Number of uses → performance expectancy	0.07, n.s.	-0.018	0.099	0.04, n.s.	-0.019	0.097
H32–2: Number of uses → effort expectancy	-0.06, n.s.	-0.064	0.012	-0.03, n.s.	-0.056	0.019
H33–2: Number of uses → facilitating conditions	-0.06, n.s.	-0.087	0.025	-0.04, n.s.	-0.067	0.023
H34–2: Number of uses → hedonic motivation	-0.01, n.s.	-0.052	0.041	0.01, n.s.	-0.041	0.047
H35–2: Number of uses → behavioural intention	0.06, n.s.	-0.011	0.064	0.04, n.s.	-0.010	0.065
CFI	0.96			0.66
RMSEA	0.06			0.19
SRMR	0.05			0.25
χ^2/df	1.96			12.13
R^2 of BI	0.719			0.856
R^2 of PE	0.667			0.881
R^2 of EE	0.699			0.879
R^2 of FC	0.219			0.699
R^2 of SI	0.024			0.024
R^2 of HM	0.639			0.853

Notes:

 *0.05,

**p < 0.01,

***p< 0.001.

  n.s. = not significant

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