2026-10-14T02:53:33Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33900496 2026-09-17T16:09:17Z category_1136 portal_316 item_type_3 month_year_09_2026

Table 1_Awareness without intention, attitude without action: a multi-method (SEM–ANN–fsQCA) study of Gen Z sustainable transport adoption in smart cities.xlsx Shankar Chanagala (25033777) Sri Yogi Kottala (24435272) Madhusudan Kumar Kota (25033780) Srinivas Bolagani (25033783) G. N. P. V. Babu (25033786) N. Roopalatha (25033789) Urban and Regional Planning not elsewhere classified adoption intention artificial neural networks SDG 11 smart cities social influence structural equation modelling sustainable urban transport <p>The study investigates the factors affecting sustainable urban transport adoption among in the context of smart cities and ‘Sustainable Development Goal 11 (SDG 11)’. While the concept of sustainable transport is attracting attention, previous studies have mainly adopted linear analysis methods, which fail to explain various aspects of transport behavior. In response, this research employs a multi-pronged approach using a combination of ‘Structural Equation Modelling (SEM)’, ‘Artificial Neural Networks (ANN)’ and ‘fuzzy-set Qualitative Comparative Analysis (fsQCA)’. The study surveyed 433 Generation Z participants with a questionnaire. SEM findings highlight the importance of ‘perceived sustainability’, ‘perceived behavioural control and social influence’ in predicting adoption intention, which in turn has a strong association with use intention, with no significant direct effects observed for attitude and environmental awareness. ANN findings, by accounting for the effects of non-linearity, further improve the predictive powers by considering environmental awareness as the strongest predictor and perceived sustainability as the second strongest. The fsQCA results also show that there are multiple configurations that result in high intention, confirming equifinality and suggesting that no single factor is sufficient to explain intention. All methods show perceived sustainability and perceived behavioral control to be critical factors in predicting, while attitude is shown to be weak and dependent on other factors. This research advances knowledge by providing a holistic view of sustainable transport adoption by combining explanatory, predictive and configurational analyses. The current research provides theoretical contributions and policy suggestions to encourage Gen Z to use sustainable transport in smart cities.</p> 2026-09-17T16:09:17Z Dataset Dataset 10.3389/frsc.2026.1867418.s002 https://figshare.com/articles/dataset/Table_1_Awareness_without_intention_attitude_without_action_a_multi-method_SEM_ANN_fsQCA_study_of_Gen_Z_sustainable_transport_adoption_in_smart_cities_xlsx/33900496 CC BY 4.0