Environmental and societal problems related to energy use have spurred the development of sustainable energy technologies, such as wind mills, carbon capture and storage, and hydrogen vehicles. Public acceptance of these technologies is crucial for their successful introduction into society. Although various studies have investigated technology acceptance, most technology acceptance studies focused on a limited set of factors that can influence public acceptance, and were not based on a comprehensive framework including key factors influencing technology acceptance. This paper puts forward a comprehensive framework of energy technology acceptance, based on a review of psychological theories and on empirical technology acceptance studies. The framework aims to explain the intention to act in favor or against new sustainable energy technologies, which is assumed to be influenced by attitude, social norms, perceived behavioral control, and personal norm. In the framework, attitude is influenced by the perceived costs, risks and benefits, positive and negative feelings in response to the technology, trust, procedural fairness and distributive fairness. Personal norm is influenced by perceived costs, risks and benefits, outcome efficacy and awareness of adverse consequences of not accepting the new technology. The paper concludes with discussing the applicability of the framework.

Widespread adoption of electric vehicles (EVs) may contribute to the alleviation of problems such as environmental pollution, global warming and oil dependency. However, the current market penetration of EV is relatively low in spite of many governments implementing strong promotion policies. This paper presents a comprehensive review of studies on consumer preferences for EV, aiming to better inform policy-makers and give direction to further research. First, we compare the economic and psychological approach towards this topic, followed by a conceptual framework of EV preferences which is then implemented to organise our review. We also briefly review the modelling techniques applied in the selected studies. Estimates of consumer preferences for financial, technical, infrastructure and policy attributes are then reviewed. A categorisation of influential factors for consumer preferences into groups such as socioeconomic variables, psychological factors, mobility condition, social influence, etc. is then made and their effects are elaborated. Finally, we discuss a research agenda to improve EV consumer preference studies and give recommendations for further research.

Managing large-scale transportation infrastructure projects is difficult due to frequent misinformation about the costs which results in large cost overruns that often threaten the overall project viability. This paper investigates the explanations for cost overruns that are given in the literature. Overall, four categories of explanations can be distinguished: technical, economic, psychological, and political. Political explanations have been seen to be the most dominant explanations for cost overruns. Agency theory is considered the most interesting for political explanations and an eclectic theory is also considered possible. Nonpolitical explanations are diverse in character, therefore a range of different theories (including rational choice theory and prospect theory), depending on the kind of explanation is considered more appropriate than one all-embracing theory.

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For developing sustainable travel policies, it may be helpful to identify multimodal travelers, that is, travelers who make use of more than one mode of transport within a given period of time. Of special interest is identifying car drivers who also use public transport and/or bicycle, as this group is more likely to respond to policies that stimulate the use of those modes. It is suggested in the literature that this group may have less biased perceptions and different attitudes towards those modes. This supposition is examined in this paper by conducting a latent class cluster analysis, which identifies (multi)modal travel groups based on the selfreported frequency of mode use. Simultaneously, a membership function is estimated to predict the probability of belonging to each of the five identified (multi)modal travel groups, as a function of attitudinal variables in addition to structural variables. The results indicate that the (near) solo car drivers indeed have more negative attitudes towards public transport and bicycle, while frequent car drivers who also use public transport have less negative public transport attitudes. Although the results suggest that in four of the five identified travel groups, attitudes are congruent with travel mode use, this is not the case for the group who uses public transport most often. This group has relatively favorable car attitudes, and given that many young, low-income travelers belong to this group, it may be expected that at least part of this group will start using car more often once they can afford it. Based on the results, challenges for sustainable policies are formulated for each of the identified (multi)modal travel groups.