Abstract

With the increasing environmental problems, sustainable consumption is an important consumer behavior. Therefore, it is important to investigate further the significant drivers to and barriers against sustainable consumption, in order to increase the share of sustainable consumption and understanding of consumer behavior. This dissertation identifies two gaps. The first is in understanding consumer positive and negative anticipated emotions as an important factor influencing high-involvement sustainable consumption. The second gap relates to the lack of understanding about the associations between anticipated emotions and personal moral norms in high-involvement sustainable consumption. Against this background, the aim is to contribute to the sustainable consumption literature by investigating the roles and relations of anticipated emotions, personal moral norms, and weighing costs and benefits as drivers to and barriers against consumer adoption of a high-involvement sustainable product. A literature review and two empirical studies were conducted. Consumer adoption of alternative fuel vehicles is the specific sustainable consumption. Using quantitative methods, this phenomenon is investigated in the empirical studies conducted in Sweden. It was shown that anticipated emotions have direct effects on consumers' intention to adopt alternative fuel vehicles. Moreover, positive anticipated emotions (e.g. pride, pleasure, happiness) are drivers of sustainable consumption, while negative anticipated emotions (e.g. regret, embarrassment) are barriers against the sustainable consumption. This dissertation suggests an extension to the norm activation model, and shows that moral norms, ascription of responsibility, and awareness of environmental problems influence consumers' intentions through consumers’ anticipated emotions. For people who perceive high social norms related to decreasing the environmental impacts of car driving, the influence of positive anticipated emotions and personal moral norms are stronger. This points toward the social aspect of sustainable consumption and suggests that targeting the consumers who perceive high social norms is an important step to promoting sustainable consumption. Findings would be of relevance to marketers, policymakers and environmental organizations. Creating awareness and communicating personal responsibilities and moral norms related to the environment and consumption are important drivers for consumer adoption of sustainable products. However, it is noteworthy that consumer anticipated emotions about high-involvement sustainable products (such as alternative fuel vehicle) have also important influence on the sustainable consumption. Thus, consumer anticipated emotions should be considered in designing promotion programs.

Abstract

This paper presents an initial investment cost analysis of public transportation systems operating with wireless charging electric vehicles (EVs). There are three different types of wireless charging systems, namely, stationary wireless charging (SWC), in which charging happens only when the vehicle is parked or idle, quasi-dynamic wireless charging (QWC), in which power is transferred when a vehicle is moving slowly or in stop-and-go mode, and dynamic wireless charging (DWC), in which power can be supplied even when the vehicle is in motion. This analysis compares the initial investment costs for these three types of charging systems for a wireless charging-based public transportation system. In particular, this analysis is focused on the energy logistics cost in transportation, which is defined as the cost of transferring and storing the energy needed to operate the transportation system. Performing this initial investment analysis is complicated, because it involves considerable tradeoffs between the costs of batteries in the EV fleet and different kinds of battery-charging infrastructure. Mathematical optimization models for each type of EV and infrastructure system are used to analyze the initial costs. The optimization methods evaluate the minimum initial investment needed to deploy the public transportation system for each type of EV charging solution. To deal with the variable cost estimates for batteries and infrastructure equipment in the current market, a cost-sensitivity analysis is performed. The goal of this analysis is to identify the market cost conditions that are most favorable for each type of wireless charging solution. Furthermore, the cost analysis quantitatively verifies the qualitative comparison of the three different wireless charging types conducted in the previous research. Document type: Article

Abstract

This paper presents a new practical approach to optimally allocate charging stations in large-scale transportation networks for electric vehicles (EVs). The problem is of particular importance to meet the charging demand of the growing fleet of alternative fuel vehicles. Considering the limited driving range of EVs, there is need to supply EV owners with accessible charging stations to reduce their range anxiety. The aim of the Route Node Coverage (RNC) problem, which is considered in the current paper, is to find the minimum number of charging stations, and their locations in order to cover the most probable routes in a transportation network. We propose an iterative approximation technique for RNC, where the associated Integer Problem (IP) is solved by exploiting a probabilistic random walk route selection, and thereby taking advantage of the numerical stability and efficiency of the standard IP software packages. Furthermore, our iterative RNC optimization procedure is both pertinent and straightforward to implement in computer coding and the design technique is therefore highly applicable. The proposed optimization technique is applied on the Sioux-Falls test transportation network, and in a large-scale case study covering the southern part of Sweden, where the focus is on reaching the maximum coverage with a minimum number of charging stations. The results are promising and show that the flexibility, smart route selection, and numerical efficiency of the proposed design technique, can pick out strategic locations for charging stations from thousands of possible locations w ithout numerical difficulties. ©2019 Hie Authors. Published by Elsevier B.V. "p"open acce

Abstract

Understanding public responses to environmental policies can"br/"help in achieving a move towards more renewable energy. Focusing on two"br/"types of public responses to a policy, namely public acceptance and"br/"public support, this study utilizes a survey of car owners (N=1,422) to"br/"explore public responses to an environmental transport policy in Sweden."br/"The results demonstrate higher levels of public acceptance than support"br/"for the policy and that adopters of Alternative Fuel Vehicles (AFVs) are"br/"more prone to accept and support the policy by expressing higher"br/"intentions for continuous AFV adoption. Results of regression analyses"br/"show that policy acceptance can be explained by environmental beliefs and"br/"previous experience with AFVs. In addition, public support is also"br/"explained by public acceptance, even when controlling for other factors,"br/"which lends support to the deduction that policy acceptance can be"br/"theorized as antecedent to policy support. This study emphasizes the"br/"importance of understanding different types of public responses to an"br/"energy policy in order to recognize drivers for, and barriers against,"br/"successfully implementing a policy and communicating it with the public.