User acceptance of autonomous public transport systems: Extended UTAUT2 model (SSCI)


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Korkmaz H., Fidanoğlu A., Özçelik S., Okumuş A.

JOURNAL OF PUBLIC TRANSPORTATION, cilt.24, sa.100013, ss.1-14, 2022 (SSCI)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 24 Sayı: 100013
  • Basım Tarihi: 2022
  • Doi Numarası: 10.5038/2375-0901.23.1.5.
  • Dergi Adı: JOURNAL OF PUBLIC TRANSPORTATION
  • Derginin Tarandığı İndeksler: Social Sciences Citation Index (SSCI), Scopus
  • Sayfa Sayıları: ss.1-14
  • İstanbul Üniversitesi Adresli: Evet

Özet

The purpose of this study is to investigate the factors affecting the acceptance and use of autonomous public transport systems (APTS) by potential users. To achieve this, an integrated and expanded user acceptance model is introduced to explain the factors affecting behavioral intention to use APTS. A total of 316 surveys were conducted from 275 participants online and 41 participants by face-to-face interviews. With data acquired from public transportation (PT) users in Istanbul, the unified theory of acceptance and use of technology 2 (UTAUT2) model is modified and performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, habit, trust and safety, perceived usefulness, perceived risk, and behavioral intention constructs are utilized in the model. Age, gender, and frequency of PT usage are included in the model to examine the moderating effect on the constructs while the model is tested with structural equation modeling (SEM). The proposed model explains 72% of the variances in this study, which proves that the model has stronger predictive power compared with the previous technology acceptance model (TAM) and UTAUT model. Performance expectancy, social influence, habit, and trust and safety constructs are concluded to have significant positive effects on behavioral intention. Public usage and acceptance are necessary for the complete utilization of APTS. The findings of this study can guide decision makers in the PT industry by helping them understand the factors affecting the use and acceptance of autonomous public transport systems.