Study on the Psychology of Drivers Dealing with Illegal Parking Behavior

Song, Ki-Wook; Jeon, Sang-Min; Park, Ki-Jun; Shin, Yong-Eun

doi:10.1007/s12205-022-1823-5

Cited by 7 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition to these primary factors, research has also highlighted latent variables, which are not directly observable, such as safety [22,23], privacy [24][25][26], attitudes [27,28], and social influence [29][30][31][32][33]. These latent variables are grounded in well-established theoretical frameworks, such as the theory of planned behavior (TPB), the technology acceptance model (TAM), and privacy calculus theory (PCT), which provide a solid foundation for exploring the relationships between these latent factors and parking intentions.…”

Section: Literature Reviewmentioning

confidence: 99%

Investigating Factors for Travelers’ Parking Behavior Intentions in Changchun, China, under the Influence of Smart Parking Systems

Zhang,

Song,

Tao

et al. 2023

Sustainability

View full text Add to dashboard Cite

Unraveling the determinants of travelers’ parking behavior intentions is critical to the widespread adoption of smart parking systems (SPSs), which hold the promise of greatly enhancing parking efficiency and optimizing resource allocation within urban spaces. Our study pioneers the use of an integrated methodology combining structural equation modeling (SEM) and hierarchical regression modeling (HRM) to dissect the complex interplay of these determinants. We found that, in the structural equation model, social influence notably stood out as having the most significant impact on the intention to utilize SPSs. Notably, while perceived privacy concerns may have ranked lower in terms of influence among these factors, their role was relatively crucial, particularly given the contemporary emphasis on data security. Moreover, within the hierarchical regression model, driving experience was found to play a crucial role in determining the intention to use SPSs. Equally important, our research revealed a divergence in parking intentions between individuals with children and those without. This points towards the imperative need for personalized strategies that can cater to the diverse requirements of different user demographics. This research offers guidance for operators of SPSs aiming to formulate targeted approaches.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Investigating Factors for Travelers’ Parking Behavior Intentions in Changchun, China, under the Influence of Smart Parking Systems

Zhang,

Song,

Tao

et al. 2023

Sustainability

View full text Add to dashboard Cite

show abstract

“…TPB has also been frequently studied in relation to unethical and illegal behaviors [ 19 ]. TPB has often been verified as a theoretical model for predicting content use behavior or digital piracy [ 20 – 24 ].…”

Section: Introductionmentioning

confidence: 99%

Verifying the usefulness of the theory of planned behavior model for predicting illegal use of online content: the role of outcome expectancies and social loafing

Choi

Suh

2022

BMC Psychol

View full text Add to dashboard Cite

Background Currently, laypeople can earn profit by producing content; therefore, it should be noted that the unauthorized use of intellectual creations or possessions can cause legal issues and undermine the producers’ desire to create. This study verified the usefulness of the theory of planned behavior (TPB) model for predicting the illegal use of online content among South Korean college students and examined the roles played by outcome expectancies and social loafing in this model. Methods The participants, 369 male and female Korean college students, were aged between 18 and 31 years (M = 22.12, SD = 2.33). We measured the illegal use of online content and the factors of the TPB model, as well as outcome expectancies and social loafing with regard to participants’ illegal use of online content. Correlational analysis, stepwise regression analysis, path analysis for the TPB model, and analyses of the moderated model were performed using SPSS and AMOS. Results All TPB factors, outcome expectancies, and social loafing were positively correlated with the illegal use of online content. Stepwise regression analysis showed that intention, social loafing, outcome expectancies, and perceived behavioral control were significant predictors of the illegal use of online content. A TPB model, including a direct path from perceived behavioral control to behavior, was validated to analyze the illegal use of online content. This model was found to be moderated by outcome expectancy. Conclusion This study suggests that the TPB is useful for predicting the illegal use of online content and that outcome expectancies and social loafing also play an important role in the illegal use of online content among college students. The findings of this study provide useful information for future research and could aid in preventing illegal online content use among adolescents and young adults.

show abstract

What Causes Curbside Illegal Parking Behavior: A Method Based on Structural Equation Model

Yan

Zhou

2023

KSCE Journal of Civil Engineering

View full text Add to dashboard Cite

Study on the Psychology of Drivers Dealing with Illegal Parking Behavior

Cited by 7 publications

References 9 publications

Investigating Factors for Travelers’ Parking Behavior Intentions in Changchun, China, under the Influence of Smart Parking Systems

Investigating Factors for Travelers’ Parking Behavior Intentions in Changchun, China, under the Influence of Smart Parking Systems

Verifying the usefulness of the theory of planned behavior model for predicting illegal use of online content: the role of outcome expectancies and social loafing

What Causes Curbside Illegal Parking Behavior: A Method Based on Structural Equation Model

Contact Info

Product

Resources

About