The efficiency of the same vehicle can vary in different regions, posing unique challenges and implications for electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) within a country. However, most studies have regarded countries as single entities, and it is difficult to assess differences in efficiency between similar entities by simply using the life cycle analysis (LCA) method. To provide the specific environmental efficiency of vehicles in each region, in this study, we used data from 100 cities in 30 provinces in China (4 provinces are not discussed due to a lack of data) and constructed a new road congestion indicator that simulated different road conditions at different times and in different regions. A more effective method, which consisted of LCA, two-stage data envelopment analysis (DEA) and a slack-based model (SBM), was integrated to reflect the phases of LCA more clearly. The results show that the well-to-wheel (WTW) emission range of internal combustion engine vehicles (ICEVs) is 288.28–217.40 CO₂-eq g/km, while it is 248.20–26.67 CO₂-eq g/km for EVs, which means the WTW carbon emissions of EVs are generally lower than those of ICEVs (except in Heilongjiang Province). Furthermore, it was concluded that provinces with a high proportion of hydropower and a high degree of power autonomy could adjust the proportion of thermal power and inter-provincial power transmission to enhance environmental sustainability, and this would not change provincial environmental efficiency. The analysis suggests that provinces should consider both environmental protection and electricity sustainability when planning their own power development, rather than only focusing on improving environmental efficiency.

Privacy by design (PbD) has attracted considerable attention from researchers and information security experts due to its enormous potential for protecting private information and improving the privacy and security quality of information technology products. The adoption of PbD among information engineers is currently limited owing to its innovativeness and the distinctive traits of the information technology industry. Utilising the Technology Acceptance Model as a framework, this study innovatively explores the pivotal factors and mechanisms that influence information engineers’ decision-making in the adoption of PbD from the viewpoint of the perceived work risk. In this empirical research, professional information engineers were invited to complete a questionnaire survey. After analysing the data using partial least squares structural equation modelling, the results reveal that information engineers’ perceived work risk in PbD (PWRP) negatively affects their perceptions of the usefulness and ease of use of PbD. This negative perception subsequently reduces their intention to implement PbD (INTP) and adversely impacts their attitudes towards implementing PbD (ATTP). Furthermore, the study findings reveal that a positive ATTP among engineers boosts their INTP and positively influences their behaviours regarding information security. This study provides an in-depth examination of these findings and lays a solid theoretical groundwork for the further promotion and implementation of PbD in information technology enterprises. Moreover, the findings offer invaluable support for management decisions in both information technology companies and information security regulatory authorities, significantly contributing to the expansion and deepening of research in the field of PbD.