The transport sector is the leading source of growing greenhouse gas (GHG) emissions globally. To consider environmental degradation aspects due to transport, electric vehicles (EVs) have the prospect to lead road transport to electric mobility from conventional petroleum vehicles. Despite various eco-friendly benefits, the EV market penetration ratio is very low, especially in developing countries. The primary reason for low penetration is consumer limited motivation and knowledge about the EVs features. This paper uses a unified theory of acceptance and technology (UTAUT) model to assess consumer motivation and environmental knowledge towards EVs. This research used convenience random sampling to collect data and analyzed the results using the Partial Least Squares (PLS) method on the example of 199 respondents from Malaysia. The study results revealed that factors identified in the motivational context significantly influence consumer intentions to purchase EVs. Perceived environmental knowledge and technophilia have been included in UTAUT from a motivational perspective. Furthermore, a significant relationship between effort expectancy, social influence, technophilia, perceived environmental knowledge, and purchase intention towards electric vehicles has been observed, without performance expectancy. The study findings serve to inform policymakers and automakers to formulate effective marketing strategies to enhance consumer motivation, knowledge, and value creation for EVs in a sustainable era. Ultimately, the policies will help to encourage consumers to buy eco-friendly vehicles that will help reduce transport carbon emissions and attain sustainable development goals (SDGs).

This study investigates the significance of self-management in academic staff stress management related to social networking sites (SNS). It emphasizes particularly on reducing social media exhaustion and increasing job effectiveness. The research applies the stressor-strain-outcome theory and the Smart PLS (partial least squares) analytical approach to examine data from 391 respondents. The study’s goal is to provide empirical data on the efficacy of self-control management in reducing SNS stress and its effects on academic staff’s psychological wellbeing and job performance. Data is collected by survey using online email platforms among academic employees, and the collected data is examined utilizing the Smart PLS approach. This approach allows for an investigation of the proposed links and their statistical importance. This research’s ramifications are important for academic institutions since its results can help academic personnel effectively cope with SNS-related stress. Academic employees can better limit their SNS usage and avoid social media tiredness by promoting self-control management practices. As a result, academic employees’ job performance and overall wellbeing may increase. The study’s findings help to comprehend how self-management might reduce SNS stress and improve staff performance in the academic sector.