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In this chapter we interpret traffic safety culture (TSC) in terms of data on beliefs, attitudes, and behaviors from the fourth wave of the SARTRE study to find out whether they can be interpreted in a perspective. The SARTRE study is a European-wide survey that started in 1991 and collects information on mobility, risk perceptions, attitudes, behaviors, and experiences on the road (Cauzard, 1998, 2004; Cestac & Delhomme, 2012). The chapter focuses on the group of car drivers.

A principal component factor analysis was conducted to explore the underlying structure of the data set. Results suggest an underlying structure of five components which explain more than 55% of the variance. These dimensions were labeled (1) acceptance of technology and enforcement, (2) risk attitudes, (3) experienced and self-exerted behavioral control, (4) personal concern, (5) perception of other road users’ safety performance.

The influence of these five factors on safety performance (fatality rates) was estimated by regression analysis. Results show that only the second factor (risk attitudes) has a significant effect on fatality rates. As a consequence, expressive and instrumental attitudes about risk-taking should be addressed in driver training as well as information campaigns in order to improve safety culture at the level of individual car drivers.

A lesson has been learned from the pandemic experience that less damages to the environment and realizing more social responsibilities would be the direction of the post-pandemic period globally. The purpose of this study is to focus on identifying the appropriate determinants of the proposed urban travel behavior model to develop Smart Mobility in Smart Cities to protect the environment. Potential to realize Smart Cities with infrastructure development has been explored in this study if road users are keen to combat climatic change which is clear from the challenges of flattening the infection rate through the enforcement of rules and regulations by the various government.

The proposed urban travel behavior model includes sub-drivers for each of the main drivers in the theory of interpersonal behavior (TIB). These sub-drivers emphasize in forming intentions to perform the behavioral changes while driving on urban roads during COVID-19 and post-pandemic periods. A primary online survey was conducted among road commuters in the most crowded place in Malaysia, the Greater Kuala Lumpur. A total of 383 respondents who frequently drive on road during the past one year were surveyed for this study. This data analysis of this quantitative study applied a partial least squares-structural equation modeling approach to determine the significant findings and results.

The significant findings of the study reveal that environmental consciousness and timely deviation in driving during traffic congestion are positively and significantly influencing the travel behavior performance (TBP) of commuters on urban roads. On the other hand, wet conditions due to weather, narrow road infrastructure and habits of road commuters are negatively influencing TBP. Social responsibility is positively and significantly influencing TBP through the mediating effect of the intention of road commuters’ behavior.

The current environmental concerns and societal adherence efforts in breaking the chain of the infectious COVID-19 among people can be manifested to develop Smart Cities with less air and noise pollution in the future. In this context, the present study proposes an urban travel behavior model and tests for its suitability of a greener and cleaner environment for the benefit of future generations. The limitation of the present study is that travel hazards are not included in the framework, as it is a topic of its own volume.

It is timely to implement Smart Mobility on road business models for Smart Cities as the consequences of the pandemic make us to realize the importance of environmental concerns and the social responsibilities of everyone. TIB considers four drivers, namely, attitude, subjective norm, affect and habit which induce intention to perform behavioral decisions. The novelty of the present study is the development of sub-drivers for these four drivers in the context of the urban travel behavior model.

Using an online survey design and a primary data collection of police officers working in a large city in the southern United States, the current study finds evidence that officers perceptions of police legitimacy can be divided into two types: self-identification and perceived external legitimacy. The study investigates the role of perceived organizational support, leader–member exchange and demographic factors in predicting perceptions of self-identification and perceived external legitimacy.

The police legitimacy literature has focused primarily on the public's perceptions of the legitimacy of police. There is limited understanding of the components of officers' attitudes towards police legitimacy, or the predictors of those components.

Results of the Ordinary Least Squares regression models indicate perceived organizational support mediates the relationship between leader–member exchange and self-identification and perceived external legitimacy. Exploratory mediation analyses indicate perceived organizational support mediates both of those relationships.

The results provide further evidence that the two types of self-perceived legitimacy are analytically distinct. They differ from previous work in that demographic and organizational variables predict each type similarly, and that one predictor (POS) mediates the influence of another (LMX). The results have implications for future police self-legitimacy research.