Diyi Liu

Dr. Diyi Liu

Nankai University, Tianjin, China
orcid

Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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30 December 2021 in Journal of Advanced Transportation
Verified
Journal Article
Open access
PDF file
XZXinyuan Zhang
Xinyuan Zhang
DLDiyi Liu
Diyi Liu
YWyuning wang
yuning wang
HDHuibin Du
Huibin Du
Understanding the behavioral intentions of public transit passengers during the COVID-19 pandemic is important for transmission control interventions oriented towards public transport system travel behavior. This paper studies the relationship between passengers’ intentions to use public transport, a set of psychological variables, and the influence of transport management policies (POLs) under COVID-19. Specifically, this study presents a framework integrating the theory of planned behavior (TPB) and customer satisfaction (CS) theory and uses partial least squares structural equation modeling (PLS-SEM) applied to the survey responses of 983 residents of Tianjin, China. The empirical results support the validity of this integrated model of public transit use intentions by confirming several hypothesized relationships among the psychological variables studied. Moreover, POLs under COVID-19 are shown to enhance commuters’ intentions primarily via subjective norms (SNs), perceived behavioral control (PBC), perceived service quality (PSQ), and CS. These findings reveal the psychological mechanism through which passengers adjust their public transport travel intentions during the COVID-19 period. Based on the results, some feasible suggestions are proposed to help restore confidence in public transport after the pandemic.


23 April 2020 in Rock Mechanics and Rock Engineering
Verified
Journal Article
Closed access
PDF file
LHLiu He
Liu He
ZZZhiming Zhao
Zhiming Zhao
JCJia-Yi Chen
Jia-Yi Chen
DLDiyi Liu
Diyi Liu

18 January 2023 in Energy Policy
Verified
Journal Article
Closed access
DLDiyi Liu
Diyi Liu
SQSuntong Qi
Suntong Qi
Tiantong XuTiantong Xu
Tiantong Xu

29 November 2022 in Energies
Verified
Journal Article
Open access
PDF file
XLXin-tao Li
Xin-tao Li
XXXue’er Xu
Xue’er Xu
DLDiyi Liu
Diyi Liu
MHMengqiao Han
Mengqiao Han
SLSiqi Li
Siqi Li
Concerns about the environment and renewable energy are growing. Improving the perception of renewable energy in urban and rural households is required to promote green development and to learn about consumer preferences for renewable energy based on the gradual reduction in financial subsidies for photovoltaic (PV) power generation. This paper aims to estimate the willingness of consumers to pay for a Household PV system and explores the factors that affect consumers’ product selection, which is conducive to optimizing Household PV products and policies and is important for achieving the carbon peaking and carbon neutrality goals. Using a discrete choice model, this paper surveyed 765 urban and rural residents without installing Household PV systems in Tianjin, China. Subsequently, the respondents’ attribute preferences and willingness to pay (WTP) for a Household PV system were analyzed using a logit regression analysis model. The influence of respondents’ socio-economic characteristics on WTP was analyzed. The empirical results showed that (1) price significantly impacts consumers’ PV adoption behaviors and consumers tend to choose cheaper PV products; (2) consumers are more willing to pay for the after-sales service (3959 USD/level) and traceable information (2176 USD/level), indicating their preference for these two attributes when considering options; (3) socio-economic variables, including gender and the number of minor children (i.e., children under the age of 18) at home, significantly impact consumers’ PV adoption behaviors. Males and consumers without minor children at home will pay more attention when selecting the products. Our research findings will provide valuable insights into policy making and the wide-ranging use of Household PV systems.

8 February 2024 in Applied Mathematical Modelling
Verified
Journal Article
Closed access
Tiantong XuTiantong Xu
Tiantong Xu
DLDiyi Liu
Diyi Liu
LMLipo Mo
Lipo Mo