Figures (5)  Tables (13)

    • Figure 1. 

      The three main adopted categories of behavioural theories. (a) TAM, (b) TPB, and (c) UTAUT.

    • Figure 2. 

      The proposed extended technology acceptance model.

    • Figure 3. 

      Automated driving BRT in Lingang New City, Shanghai, China.

    • Figure 4. 

      Initial structural equation model of the extended TAM.

    • Figure 5. 

      The results of the path coefficients.

    • The behavioural theory model adopted Important influencing factors Sample size Measurement method Sources
      Extended TAM Trust, perceived ease of use, perceived safety, perceived usefulness, Intention to use, and attitudes towards use 300 PLS-SEM Xu et al.[17]
      Extended TAM Perceived usefulness, perceived ease of use, perceived risk, perceived comfort, trust, attitudes, intention to use 401 SEM Wu et al.[18]
      TAM and TPB Attitudes, trust, subjective norms, perceived usefulness, compatibility 173 SEM Rahman et al.[19]
      Extended UTAUT Performance expectations, effort expectations, social influence, facilitating conditions, anxiety, perceived price, and individual innovativeness − − Lee & Jung[20]
      Extended UTAUT Performance expectations, hedonic motivation, social influence, facilitating conditions 315 Factor analysis Madigand et al.[5]
      Extended TAM Trust, perceived usefulness, perceived ease of use, external control factors 552 SEM Choi & Ji[21]
      Extended TAM Individual differences, systemic influences, social characteristics, perceived usefulness, perceived ease of use, attitudes towards use, intention to use 268 SEM Herrenkind et al.[22]
      Extended TAM Perceived security risk, perceived privacy and security, perceived usefulness, perceived ease of use, attitudes towards use, intention to use 216 SEM Zhang et al.[23]
      Extended TAM Life choices, subjective well-being, travel quality factors, life domains, perceived usefulness, perceived ease of use, attitudes towards use, intention to use 268 PLS-SEM Herrenkind et al.[24]
      Extended TAM Personality innovation, driving pleasure, trust, perceived usefulness, perceived ease of use. 369 SEM Hegner et al.[25]
      Extended TPB Subjective norms, perceived behavioural control, perceived risk, attitudes, autonomous driving knowledge, Intention to use 906 SEM Jing et al.[26]
      Extended TAM Trust, social influence, personal characteristics, perceived ease of use, perceived usefulness, intention to use 647 PLS-SEM Zhang et al.[27]
      Extended TAM Environmental concerns, green perceived usefulness, perceived ease of use, intention to use 470 SEM Wu et al.[28]

      Table 1. 

      Studies on the acceptance of autonomous driving based on behavioural theory.

    • Anchoring theory Object Major factor Sources
      TAM Autonomous shuttle Extended using trust and perceived enjoyment. Chen[9]
      Autonomous electric buses Extended social impact, individual differences and system characteristics, Herrenkind et al.[22]
      Autonomous buses Perceived safety, bus service quality, and moderator variable Yan et al.[29]
      Autonomous buses Perceived risk, trust Wu et al.[18]
      UTAUT Automated road transport systems Performance expectancy, effort expectancy, social influence, socio-demographics Madigan et al.[30]
      UTAUT2 Autonomous public transport systems performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, habit, trust and safety, perceived usefulness, perceived risk, and behavioural intention Korkmaz et al.[31]
      TAM and TPB Autonomous shuttle Relative advantage, compatibility, complexity, trialability, observability, attitude, intention to use Moták et al.[32]
      UTAUT, TTF, and trust Autonomous buses Performance expectancy, effort expectancy, social influence, facilitating conditions, perceived risk, trust, task technology fit Cai et al.[16]
      UTAUT2 Autonomous modular transit Performance expectancy, social influence, hedonic motivations, trust, green perceived usefulness Rejali et al.[33]
      TIB Autonomous shuttle Social factors, feelings, safety perception, operation environment, behavioural intention Salonen & Haavisto[34]

      Table 2. 

      Representative studies on acceptance of autonomous buses.

    • Sources Trust Safety Cognition of technology Impact to PU and PEOU Multi-group analysis
      Chen[9] ○ √ √ √ ○
      Herrenkind et al.[22] ○ √ √ ○ √
      Yan et al.[29] √ ○ √ ○ ○
      Wu et al.[18] ○ √ √ √ ○
      Madigan et al.[30] √ √ ○ √ ○
      Korkmaz et al.[31] ○ ○ ○ √ ○
      Cai et al.[16] ○ √ √ √ ○
      Salonen & Haavisto[34] √ √ ○ √ √
      Current study ○ ○ ○ ○ ○

      Table 3. 

      Factors considered in different models.

    • Name of latent variable Measuring
      variable      		 Question item
      Perceived technology level ptl1 Automated and connected vehicle technologies have begun to proliferate
      ptl2 Automated BRT systems are very advanced.
      ptl3 Automated and connected vehicle technologies can be applied to regular public transit.
      Perceived safety ps1 Automated BRT has a high level of safety quality.
      ps2 If there is a malfunction or danger, I believe that automated driving technology can protect my safety well.
      ps3 Automated BRT equipped with safety officers would make me feel very reassured.
      ps4 Automated rapid transit equipped with safe ride guidance (safety videos, posters, etc.) would make me feel very reassured.
      Perceived usefulness pu1 Automated BRT is convenient for my daily travel.
      pu2 The autonomous driving BRT runs smoothly.
      pu3 The autonomous driving BRT operates at a faster speed.
      pu4 The waiting time for the autonomous driving BRT is shorter compared to other modes of transportation.
      Perceived ease of use peou1 The process of taking the autonomous driving BRT is simple; even if I have never taken it before, I can easily take a ride.
      peou2 The station locations are very prominent and easy to find, so I can easily walk to the station.
      peou3 I can easily find the automated BRT route that I need to take to reach my destination.
      peou4 I am willing to take the autonomous driving BRT even if it requires transferring between different lines to reach my destination.
      Attitude towards use atu1 I support autonomous driving BRT.
      atu2 I think riding the autonomous driving BRT is a demonstration of support for new technologies.
      atu3 Autonomous driving technology will make public transportation more attractive to me.
      Intention to use itu1 I am willing to ride on the autonomous driving BRT.
      itu2 I am willing to recommend the autonomous driving BRT to others.
      itu3 I would prefer to take the autonomous driving BRT.

      Table 4. 

      Latent variables of the model and question items design.

    • Variable Title item Frequency Percentage (%)
      Gender Male 191 45.05
      Female 233 54.95
      Age (year) 18–24 46 10.85
      25–34 235 55.42
      35–50 127 29.95
      51–65 15 3.54
      65+ 1 0.24
      Monthly income (CNY) < 5,000 29 6.84
      5,000–10,000 150 35.38
      10,001–20,000 178 41.98
      20,001–30,000 49 11.56
      > 30,000 18 4.25
      Academic qualifications High school and below 12 2.83
      3-year college degree 38 8.96
      bachelor's degree 328 77.36
      Masters' degree and above 46 10.85
      Occupation Civil servant 5 1.18
      Company employee 341 80.42
      Public sector employee 34 8.02
      Self-employed 9 2.12
      Students 27 6.37
      Retiree 6 1.42
      Others 2 0.47
      Family structure Single 71 16.75
      Husband and wife 47 11.08
      Couple living with children 269 63.44
      Couple living with parents 37 8.73
      Private car Yes 355 83.73
      No 69 16.27
      Driving licence Yes 374 88.21
      No 50 11.79

      Table 5. 

      Description of sample feature distribution.

    • Latent variable Measured variable Standard load Cronbach alpha CR AVE
      Attitude towards use atu1 0.814 0.697 0.831 0.622
      atu2 0.725
      atu3 0.823
      Intention to use itu1 0.833 0.751 0.858 0.668
      itu2 0.796
      itu3 0.821
      Perceived ease of use peou1 0.751 0.723 0.828 0.546
      peou2 0.758
      peou3 0.728
      peou4 0.719
      Perceived safety ps1 0.815 0.703 0.818 0.532
      ps2 0.779
      ps3 0.600
      ps4 0.706
      Perceived technology level ptl1 0.762 0.672 0.820 0.603
      ptl2 0.753
      ptl3 0.814
      Perceived usefulness pu1 0.710
      pu2 0.731 0.708 0.820 0.533
      pu3 0.742
      pu4 0.735
      Underline means the measured variable does not well support the latent variable.

      Table 6. 

      Tests and analysis of model reliability.

    • Attitude towards use Perceived safety Perceived
      technology level      		 Perceived
      ease of use      		 Perceived
      usefulness      		 Intention to use
      Attitude towards use − − − − − −
      Perceived safety 0.635 − − − − −
      Perceived technology level 0.555 0.667 − − − −
      Perceived ease of use 0.671 0.675 0.613 − − −
      Perceived usefulness 0.671 0.733 0.600 0.726 − −
      Intention to use 0.706 0.704 0.623 0.722 0.712 −
      Arithmetic square root of AVE 0.789 0.795 0.777 0.739 0.730 0.817

      Table 7. 

      Discriminant validity test results.

    • Path relationships p-value Path factor Significance
      Attitude towards use →
      Intention to use      		 0.000 0.468 Significant
      Perceived safety →
      Attitude towards use      		 0.038 0.129 Significant
      Perceived safety → Intention to use 0.000 0.275 Significant
      Perceived technology level →
      Attitude towards use      		 0.057 0.090 Not significant
      Perceived technology level → Perceived safety 0.000 0.667 Significant
      Perceived technology level → Perceptual ease of use 0.000 0.613 Significant
      Perceived technology level → Perceived usefulness 0.000 0.249 Significant
      Perceived ease of use →
      Attitude towards use      		 0.000 0.262 Significant
      Perceived ease of use →
      Perceived usefulness      		 0.000 0.574 Significant
      Perceived usefulness →
      Attitude towards use      		 0.000 0.368 Significant
      Perceived usefulness →
      Intention to use      		 0.001 0.180 Significant
      Underline means the path factor is not significant in the model.

      Table 8. 

      Model path coefficients and hypothesis testing results.

    • Path relationship Direct effect Indirect effect Total
      affect      		 Sequence
      Attitude towards use → Intention to use 0.467 − 0.467 2
      Perceived safety →
      Intention to use      		 0.275 0.077 0.352 4
      Perceived technology level → Intention to use − 0.530 0.530 1
      Perceived ease of use → Intention to use − 0.338 0.338 5
      Perceived safety →
      Attitude towards use      		 0.166 − − −
      Perceived technology level → Perceived safety 0.667 − − −
      Perceived technology level → Perceived ease of use 0.613 − − −
      Perceived ease of use → Perceived usefulness 0.248 − − −
      Perceived ease of use → Attitude towards use 0.284 − − −
      Perceived ease of use → Perceived usefulness 0.574 − − −
      Perceived usefulness → Attitude towards use 0.379 − − −
      Perceived usefulness → Intention to use 0.180 0.177 0.357 3

      Table 9. 

      Influence factor coefficients.

    • Path relationships Gender p-value Standardised estimate
      Attitude towards use →
      Intention to use      		 Male 0.000 0.465
      Female 0.000 0.445
      Perceived safety →
      Attitude towards use      		 Male 0.979 −0.002
      Female 0.001 0.287
      Perceived safety →
      Intention to use      		 Male 0.007 0.189
      Female 0.000 0.340
      Perceived technology level → Perceived safety Male 0.000 0.622
      Female 0.000 0.696
      Perceived technology level → Perceived ease of use Male 0.000 0.562
      Female 0.000 0.644
      Perceived technology level → Perceived usefulness Male 0.000 0.249
      Female 0.001 0.234
      Perceived ease of use →
      Attitude towards use      		 Male 0.000 0.306
      Female 0.002 0.227
      Perceived ease of use →
      Perceived usefulness      		 Male 0.000 0.582
      Female 0.000 0.584
      Perceived usefulness →
      Attitude towards use      		 Male 0.000 0.483
      Female 0.000 0.333
      Perceived usefulness →
      Intention to use      		 Male 0.001 0.270
      Female 0.055 0.129

      Table 10. 

      Results of path effects regarding the impact of gender for each group.

    • Path relationship Age (year) p-value Standardised estimate
      Attitude towards use → Intention to use < 35 0.000 0.463
      > 35 0.000 0.459
      Perceived safety →
      Attitude towards use      		 < 35 0.014 0.203
      > 35 0.330 0.096
      Perceived safety →
      Intention to use      		 < 35 0.000 0.310
      > 35 0.001 0.218
      Perceived technology level → Perceived safety < 35 0.000 0.653
      > 35 0.000 0.700
      Perceived technology level → Perceived ease of use < 35 0.000 0.654
      > 35 0.000 0.529
      Perceived technology level → Perceived usefulness < 35 0.003 0.176
      > 35 0.000 0.351
      Perceived ease of use → Attitude towards use < 35 0.000 0.326
      > 35 0.019 0.240
      Perceived ease of use → Perceived usefulness < 35 0.000 0.629
      > 35 0.000 0.513
      Perceived usefulness → Attitude towards use < 35 0.000 0.295
      > 35 0.000 0.502
      Perceived usefulness → Intention to use < 35 0.000 0.296
      > 35 0.069 0.127

      Table 11. 

      Results of path effects regarding the impact of age for each group.

    • Path relationship Monthly
      income (CNY)      		 p-value Standardised estimate
      Attitude towards use → Intention to use < 10,000 0.000 0.543
      ≥ 10,000 0.000 0.395
      Perceived safety →
      Attitude towards use      		 < 10,000 0.010 0.257
      ≥ 10,000 0.156 0.100
      Perceived safety →
      Intention to use      		 < 10,000 0.000 0.246
      ≥ 10,000 0.000 0.283
      Perceived technology level → Perceived safety < 10,000 0.000 0.689
      ≥ 10,000 0.000 0.655
      Perceived technology level → Perceived ease of use < 10,000 0.000 0.608
      ≥ 10,000 0.000 0.626
      Perceived technology level → Perceived usefulness < 10,000 0.001 0.239
      ≥ 10,000 0.000 0.262
      Perceived ease of use → Attitude towards use < 10,000 0.000 0.310
      ≥ 10,000 0.002 0.254
      Perceived ease of use → Perceived usefulness < 10,000 0.000 0.605
      ≥ 10,000 0.000 0.545
      Perceived usefulness → Attitude towards use < 10,000 0.009 0.281
      ≥ 10,000 0.000 0.456
      Perceived usefulness → Intention to use < 10,000 0.013 0.161
      ≥ 10,000 0.004 0.220

      Table 12. 

      Results of path effects regarding the impact of income for each group.

    • Path relationship Academic qualifications p-value Standardised estimate
      Attitude towards use → Intention to use Lower than a bachelor's degree 0.000 0.411
      Bachelor's degree and above 0.000 0.477
      Perceived safety → Attitude towards use Lower than a bachelor's degree 0.710 0.084
      Bachelor's degree and above 0.006 0.184
      Perceived safety → Intention to use Lower than a bachelor's degree 0.164 0.204
      Bachelor's degree and above 0.000 0.275
      Perceived technology level → Perceived ease of use Lower than a bachelor's degree 0.000 0.723
      Bachelor's degree and above 0.004 0.659
      Perceived technology level → Perceived ease of use Lower than a bachelor's degree 0.000 0.716
      Bachelor's degree and above 0.000 0.601
      Perceived technology level → Perceptual usefulness Lower than a bachelor's degree 0.510 0.110
      Bachelor's degree and above 0.000 0.261
      Perceived ease of use → Attitude towards use Lower than a bachelor's degree 0.011 0.485
      Bachelor's degree and above 0.000 0.255
      Perceived ease of use → Perceived usefulness Lower than a bachelor's degree 0.000 0.688
      Bachelor's degree and above 0.000 0.564
      Perceived usefulness → Attitude towards use Lower than a bachelor's degree 0.379 0.207
      Bachelor's degree and above 0.000 0.396
      Perceived usefulness → Intention to use Lower than a bachelor's degree 0.042 0.316
      Bachelor's degree and above 0.002 0.169

      Table 13. 

      Results on academic qualifications effects for each group.