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Autonomy loss, privacy invasion and data misuse as psychological barriers to peer-to-peer collaborative car use
Abstract
The present study aimed to identify psychological barriers which potentially prevent individuals from implementing collaborative car use in their every-day mobility behaviour. We suggested a model consisting of four psychological barriers: Autonomy Loss, Privacy Invasion, Interpersonal Distrust, and Data Misuse. Perceived Financial Benefit was included as a main incentive for collaborative car use. Using two samples, a community (N = 176) and a student sample (N = 265), three forms of peer-to-peer collaborative car use were examined: lending your own car to another private person (Lending To), renting a car from another private person (Renting From) and sharing rides with others (Ridesharing). For all three forms, a standardised questionnaire was developed which included the psychological barriers, self-reported collaborative car use intention and behaviour, and evaluations of scenarios. The results showed that different barriers predicted specific forms of collaborative car use: Autonomy Loss was connected negatively with Ridesharing and Privacy Invasion predicted Lending To negatively. Data Misuse was related negatively with Renting From, when the renting was arranged via internet. Interpersonal Distrust showed no predictive value for collaborative car use. Perceived Financial Benefit was a consistent incentive for all forms of collaborative car use. Overall, the results confirm the relevance of psychological barriers for collaborative car use. Practical implications to overcome the psychological barriers are discussed.
... Furthermore, the psychological need for car ownership was found to be negatively related to the intention to use car sharing systems (Paundra et al., 2017). Moreover, the personal importance to protect the environment as well as the personal ecological norm was found to be positively correlated to shared mobility behaviors (Burghard & Scherrer, 2022;Hunecke et al., 2021). ...
... Data of the first study was collected in December 2018 during a research project with a focus on psychological barriers of shared car use (see details in Hunecke et al., 2021). To address RQ1 in the present study, we performed new analyzes in a subsample of the data, specifically the variables of the TPB. ...
... Additionally, we posted invitations in student groups on social media platforms and distributed paper-pencil versions of the survey in seminars. Our rationale for collecting about 200 cases was due to the goals of the project this survey was part of (see details in Hunecke et al., 2021). Overall, we collected 342 completed surveys. ...
Shared mobility behaviors potentially decrease negative environmental effects of the transport sector. Models such as the Theory of Planned Behavior have been widely used to explain primarily individual private-sphere pro-environmental behaviors (PEB). However, as shared mobility behaviors are not completely limited to the private-sphere, but require social collaboration, it is an open question if the TPB-variables are sufficient in explaining shared mobility behaviors. Solidarity-focused variables that put a stronger focus on social interactions may complement the TPB-variables meaningfully. In two university samples (Study 1: N = 261, Study 2: N = 1411), we tested associations between the TPB-variables and shared mobility behavioral intention using Structural Equation Modelling (SEM). Both studies confirmed attitude and social norms as significant predictors. However, perceived behavioral control was not related to shared mobility intention. Study 2 additionally investigated whether social responsibility, collective response efficacy and social identity are related to shared mobility. Results showed that social responsibility as well as collective response efficacy positively predicted shared mobility intention. In Logistic regressions, the psychological variables showed no consistent connections to self-reported shared mobility behavior. We discuss the scope of solidarity-oriented variables to complementarily explain PEB beyond the private-sphere that need social collaboration.
... So far, the TPB has been successfully applied to a large variety of proenvironmental behaviors (Bamberg and Möser, 2007), e.g., in the mobility context (Gardner and Abraham, 2010;Donald et al., 2014;Jones and Woolley, 2019;Hunecke et al., 2021). These studies point to differences in predictive power of TPB constructs depending on the investigated travel mode. ...
... However, applying the TPB in the mobility context proved helpful in terms of explaining current mobility behavior (cf. Gardner and Abraham, 2010;Hunecke et al., 2021). Including items on different modes of transport (i.e., cars, bicycles) also allowed to compare and combine results with respect to the new vehicle concept. ...
Current mobility systems put a burden on people and the environment, e.g., through greenhouse gas emissions, and depletion of natural resources. Therefore, a mobility transition including changes in legislation, infrastructure , and behavior as well as socio-technical innovations is required. Against this backdrop, the inter-and transdisciplinary project presented in this article aims at developing a new vehicle for individual everyday travel. Target characteristics of the vehicle are: resource-efficient, low in harmful substances in its components, and low on greenhouse gas emissions while driving. To inform the vehicle's development, n = 730 citizens of a medium-sized university city and its surrounding areas in central Germany took part in a survey on their mobility behavior, intention to switch to the new vehicle, their preferences for possible product features, payment models, and road use. Regression analyses revealed that socioeconomic factors (income, children in the household), individual travel characteristics (travel distance, motorization of vehicle), and psychological factors (innovativeness, weather resistance, travel habit strength, attitudes towards cars and bicycles) explained significant portions of the observed variance in participants' intention to switch from current travel modes to the new vehicle. Furthermore, our results suggest that the new vehicle may be particularly attractive to potential users if it combines advantageous characteristics of bicycles and cars. Compared to sustainability-relevant aspects of vehicle usage, participants ascribed less importance to aspects of vehicle production and disposal. These learnings provide valuable insights for actors in industry, politics, design, and research striving to promote socio-technical innovations for a transition towards more sustainable mobility.
... Marcel Hunecke, Nadine Richter, Holger Heppner [6] have introduced to perceived financial benefit included as the main incentive for collaborative car use. Autonomy loss, privacy invasion, interpersonal distrust, and data misuse were considered barriers to sharing rides with others. ...
... Web, Blockchain Autonomy loss, privacy invasion, and data misuse as psychological barriers to peer-topeer collaborative car use [6] Carpooling functions are most suitable for people who live where transit service may be restricted or non-existent and compared to other alternatives, carpooling may better suit the schedule. Many open-source protocol layers permit enterprises to construct on public or private Ethereum networks, ensuring that their key meets all regulatory and security measures. ...
The car-sharing demand is continuously developing and lately it has evolved even more widespread than car right. However, the classic car-sharing scheme is founded on a centralized database server which can often lead to cracker attacks or password leaks. As noticed nowadays from a lot of use matters, the best solution to these challenging issues is to use blockchain technology. Blockchain as a decentralized, immutable, public ledger provides customers with security that is impossible to tamper with. A blockchain is basically a digital ledger of trades that is replicated and spread across the entire web of computer systems on the blockchain. User’s data is sensitive and crucial, and blockchain can significantly change how user’s critical information is viewed, by creating a record that can’t be altered and is encrypted end-to-end, blockchain helps prevent fraud and unauthorized activity. The previous research's many flaws were revealed with a quick skim. The existing systems offered a solution to develop and implement peer-to-peer short-term car-sharing applications founded on blockchain technology and smart contracts. For the execution of smart contracts, the Solidity programming language is used. Solidity works with the Ethereum blockchain. The fundamental originality of this system is presenting a peer-to-peer car-sharing service without a central authority, which reflects a decrease in costs and an increase in data clarity in that system. Also, token-based solutions give us the power to protect business-to-business (B2B) and business-to-customer (B2C) use cases.
... This is evidenced by the reality that P2P ridesharing is becoming one of the most revenue generating sectors of the sharing economy (Bucchiarone et al., 2021) and those who use these services have been identified as the more likely to adopt new mobility solutions-such as MaaS (Alonso-González et al., 2020). While some advantages of P2P ride sharing include affordability, fare transparency, dynamic routing, responsiveness, ease of payment, productivity, reduced travel time, and global availability, some have expressed concern regarding both personal and data privacy, resource unavailability, and competition across modes (Contreras and Paz, 2018;Neunhoeffer and Teubner, 2018;Lavieri and Bhat, 2019;Hunecke et al., 2021). ...
Under the umbrella concept of smart mobility, new transport innovations such as peer-to-peer transport, shared autonomous vehicles, and mobility-as-a-service have been identified for their potential to improve accessibility and bridge the first/last-mile gap between origin, destination, and good quality public transport. Any future mobility plan, nevertheless, will need to appeal to a population reluctant to break habits. This study explores quantitative data collected from major Australian cities to provide a geographic context between attitudes towards smart mobility with a particular focus on eight attitudinal factors—i.e., technology, public transport, sharing, multimodality, peer-to-peer transport, smart phones and apps, environmental consciousness, and reducing private vehicle use. The quantitative analysis disclosed that regardless of location, overcoming private vehicle use, user aversion to multimodality, and reluctance to share rides with strangers' presence significant barriers to some smart mobility options. Furthermore, respondents in inner ring areas of cities have more positive views towards public transport, the environment, and smart phones, while the middle/outer ring residents on the contrary have more positive views towards private vehicles. The study findings offer policy insights and potential opportunities and challenges associated with the implementation of smart mobility in urban areas.
... e big data analytic process is widely used in the psychological quality assessment process that contains numerous numbers of datasets. e major impact of big data in psychological quality assessment is to collect data and perform analysis process at need time to reduce the latency rate in the computation process [8]. e big data analytic process reduces the error and risk rates in the classification and identification process. ...
Psychological big data is observed based on behavior or habitual features of people for determining the influencing factors. The influencing factor information is used for analysis in treatment, recommendation, and diagnosis of psychological disorders, depression, etc. Identifying the influencing factors is challenging due to irregular behaviors and responses from young people. However, for organizing the quality of observation, this article introduces a behavioral pattern recognition method (BPRM) with associating quality (AQ) identification. This method observes the different day-to-day behaviors of young people and recurrently associates them. The observations are aided through conventional wireless networks for swift interconnection and information sharing. The association is organized based on the transfer learning state processing model. Based on the state processing, the behavior-based psychological data are classified as abnormal and normal. If the association throughout the state changes remains the same, then it is organized or else the new data are identified as an influencing factor. The state changes are validated using random observation intervals that result in series data associations. Based on the actual data extraction, the proposed method improves the prediction accuracy and reduces false rate and processing time, whereas it improves the organization precision.
In recent years with the improvement of information communication technology (ICT) and wireless communication, Online Trading Environment (OTE) has become a popular E-commerce platform to connect sellers and buyers in an efficient way. As, OTE’s are increasing in a wider range, the authentication and verification of entities in OTE network becomes a challenging task. Although, some authentication schemes exist in OTE’s, they have flaws such as account creation delays, authentication delays, communication cost and user privacy. In this work, a trustworthy and secure anonymous authentication scheme is proposed to prevent malicious users to enter into the OTE network. In addition, our proposed scheme provides conditional privacy to users until they maintain a genuine relationship with other entities without compromising. If any dispute occurs, then the system will revoke the access of that particular entity. Moreover, the security and performance analysis in this work concludes that our scheme ensures a secure interface to provide sustainable trading experience to users by taking less computation cost and communication delay when compared to other existing authentication schemes.
Ein wichtiger Hebel, um unsere Mobilität nachhaltiger zu gestalten, ist der Berufsverkehr. Mehr als die Hälfte der Beschäftigten fahren tagtäglich mit dem eigenen Pkw zur Arbeit – meistens allein. Mobilitätsgenossenschaften, die die gemeinsame Nutzung von Fahrzeugen organisieren, sind hier ein vielversprechendes Konzept. Wie dieses Konzept auch in großen Organisationen umgesetzt werden kann, zeigt das Beispiel der Ruhr-Universität Bochum.
The increasing volume of personal motorized vehicles (PMVs) in cities has become a serious issue leading to congestion, noise, air pollution and high land consumption. To ensure the sustainability of urban transportation, it is imperative to transition the current transportation paradigm toward a more sustainable state. Transitions within socio-technical systems often arise from niche innovation. Therefore, this paper pursues the technical optimization of such a niche innovation by applying a technical sustainability perspective on an innovative mobility and logistics concept within a case study. This case study is based on a centrally managed connected, automated, shared and electric (CASE) vehicle fleet which might replace PMV use in urban city centers of the future. The key technical system components of the envisioned mobility and logistics concept are analyzed and optimized with regard to economic, ecological and social sustainability dimensions to maximize the overall sustainability of the ecosystem. Specifically, this paper identifies key challenges and proposes possible solutions across the vehicle components as well as the orchestration of the vehicles’ operations within the envisioned mobility and logistics concept. Thereby, the case study gives an example of how different engineering disciplines can contribute to different sustainability dimensions, highlighting the interdependences. Finally, the discussion concludes that the early integration of sustainability considerations in the technical optimization efforts of innovative transportation systems can provide an important building block for the transition of the current transportation paradigm to a more sustainable state.
This paper reviews the most recent literature on the optimization of car-sharing systems. Unlike other surveys, we do not focus on a single aspect of car-sharing systems, but we consider a wide range of optimization problems with a global view. Our aim is threefold. First, we revise the classic decision problems arising in car-sharing systems with conventional and electric vehicles, such as the fleet size, the station location, and the vehicle relocation. Then, we discuss some of the most recent decision problems arising in more innovative car-sharing systems, like those with autonomous vehicles, with mixed fleets, and the multi-modal and the time-dependent ones. Finally, we focus on new perspectives arising in the optimization of some innovative car-sharing services that are not yet (or little) investigated in the literature and that are worthy of attention from the operations research point of view. For each of them, we also highlight new and challenging open decision problems that deserve academic attention. © 2023 The Authors. International Transactions in Operational Research published by John Wiley & Sons Ltd on behalf of International Federation of Operational Research Societies.
Electric vehicle sharing is necessary for achieving carbon neutrality. The self-service electric vehicle mode offers unique advantages in terms of freedom of movement and privacy protection. Meanwhile, this mode requires a high-quality service guarantee because of the separation of management and use. The purpose of this study is to propose a framework for the risk control and service optimization of self-service electric vehicles, which includes service life cycle analysis, risk assessment by using a newly integrated fuzzy failure mode and effect analysis, and a consumer satisfaction survey based on the Kano model. Sixteen services were extracted through the service life cycle analysis and online review study, and their corresponding service failures were then ranked through risk assessment. The risk assessment showed that the reliability of vehicle-related services has the greatest impact on safety, followed by financial-related and driving-safety-related services. A Kano model-based survey showed that all kinds of service failures brought significant customer non-satisfaction, while different service improvements brought differentiated satisfaction. To deeply improve service satisfaction, a Risk-Satisfaction analysis was conducted, indicating that services with high risk and high satisfaction deserve further investment.
Free-floating car sharing (FFCS) offers greater flexibility than station-based car sharing but seems to affect car ownership less. This study looks into characteristics of people who changed or did not change car ownership over time and how an increase or decrease relates to FFCS membership, demographic and attitudinal factors. The study is based on FFCS users (n = 776) and non-users (n = 720) in Copenhagen surveyed two times within a 2.5-year period. Five population segments were created: car dependents, car avoiders, and car limiters who showed constant but different levels of car ownership; car aspirers who increased, and car sellers who decreased car ownership over time. The segments' profiles range from car dependents who show high affective car motives, high perceived mobility necessities and car dependency at the one end, and car avoiders who seem more driven by environmental norms and an instrumental relation to the car, at the other end of the scale. A multinomial regression predicting whether car owners increased or decreased the number of cars in the household during the project period found a positive effect of FFCS membership for decreasing car ownership. However, the effect was no longer significant when adding the intention to reduce car ownership at the time of the first survey. Main factors that remained significant for changed car ownership included a change in household composition, access to a private parking space and the initial number of cars in the household. The paper discusses strategies to increase the contribution of FFCS to car ownership reduction.
Sharing does not need to involve corporate providers but can also happen on a peer‐to‐peer (P2P) basis. P2P sharing platforms who match private providers and users are thus dealing with two different customer segments. An example of this is carpooling, the sharing of a car journey. Recent years have seen considerable research on why people use sharing services. In contrast, there is little knowledge of why people may offer a good for sharing purposes. Drawing on identity theory, this paper suggests that users and providers of carpooling need to be addressed differently. A pilot study and two studies, including both actual car owners and nonowners confirm that the extent to which one identifies as an environmentalist predicts car owners' willingness to offer carpooling, but does not affect nonowners' willingness to use carpooling services. These findings remain robust when controlling for various potential confounds. Furthermore, Study 2 suggests that an environmentalist identity plays an important role for car owners' actual decision to offer a ride via an online platform. These results suggest that marketers of P2P platforms need to pursue different strategies when addressing potential users and providers on the same platform.
Mobility as a Service (MaaS) is expected to significantly change mobility patterns, yet it is still not clear who will embrace this new mobility paradigm and how MaaS will impact passengers' transportation. In the paper, we identify factors relevant for MaaS adoption based on a survey comprised of over thousand respondents in the Netherlands. We find five clusters in relation to individuals' inclinations to adopt MaaS in the context of urban mobility. We characterize each of the clusters, allowing for the examining of different customer segments regarding MaaS. The cluster with the highest inclination for future MaaS adoption is also the largest cluster (re-presenting one third of respondents). Individuals in this cluster have multimodal weekly mobility patterns. On the contrary, current unimodal car users are the least likely to adopt MaaS. We identify high (mobility) ownership need and low technology adoption (present in three of the five clusters) as the main barriers that can hinder MaaS adoption. Policies that directly address these two barriers can stimulate MaaS adoption.
This paper presents a classification of motives considered as relevant when selecting a mode of transport, and it examines the relative importance of driving habits, car attitudes, descriptive norms and motives for transport mode choices for commuting, shopping, leisure and child-related trips. A survey was sent by post to 3000 Swedish residents in metropolitan, semi-rural and rural areas (with a response rate of 34.6%). Through an ordinal factor analysis, three classes of motives were extracted: Perceived outcomes, Symbolic and Instrumental motives. Hierarchical proportional odds logistic regression and hierarchical linear regression models assess the relative importance of socio-demographic variables, motives, descriptive norms, car attitudes and driving habits for each kind of trip. These models indicate that the impact of socio-demographic and psychological variables varies across trip purposes. Commuting and child- related trips were primarily predicted by socio-demographic variables. Leisure and shopping trips were mostly predicted by driving habit. Driving habit was a common and strong predictor among all trip purposes. These results are evidence of the power of script-based trips to generate habitual travel behaviours across different trip purposes. Conclusions are made in the light of the usefulness of these results to practitioners and researchers who aim to foster sustainable transportation and to reduce private car use.
At present, many policymakers and practitioners are searching for actions that could facilitate Mobility as a Service (MaaS) developments. A potential action, which has received a lot of attention, is to introduce Intermediary MaaS Integrators; that is intermediate actors that assemble the offerings from Transport Service Providers (TSPs) and distribute these to MaaS Operators. However, little is known about if and how TSPs and MaaS Operators would appreciate the introduction of Intermediary MaaS Integrators. To address this knowledge gap, this paper explores an attempt to establish a national Intermediary MaaS Integrator in Sweden. The contribution to transportation research is twofold. Firstly, the paper advances the conceptual understanding of Intermediary MaaS Integrators by identifying four defining dimensions: Activities, Management, Processes and Context. Secondly, it deepens the knowledge of Intermediary MaaS Integrators’ value propositions by detailing TSPs’ and prospective MaaS Operators’ hopes and fears vis-à-vis them. Lastly, practical implications for how to facilitate acceptance and adoption are proposed. Intermediary MaaS Integrators should only be introduced if basic incentives for using their services are in place, and if introduced, they should preferably: go beyond offering technical services; have clear, declared objectives; be impartial and capable actors; and carefully consider their launch strategies.
This paper aims to review variables and behavioural theories originating from social and environmental psychology as applied to transport research, to better understand decision-making mechanisms, information processing and modal choice. The first section provides an overview of the main psycho-social variables which explain behaviour and, notably, pro-environment behaviour. The analysis shows the relations among variables, highlighting some potential cause-effect mechanism or, at least, the influence that such variables can have on behaviour. Furthermore, the strengths and weaknesses of using psycho-social variables to predict travel behaviour are discussed. Such analysis feeds the section related to the behavioural theories. These are reviewed with a focus on potential application to transport sector, showing the would-be added value of introducing a socio-psychological approach in the current vision, focused on stochastic models based on maximisation of personal utility. To this end, attention is paid to the data collection and analysis, basic for any models and even more challenging to collect when they deal with personal characteristics of individuals. Finally, the concept of attitude and intention is discussed, opening the doors between disciplines to overcome the attitude-behaviour gap.
Transportation network companies (TNCs) have introduced shared-ride versions of their ordinary services, such as UberPool or Lyft Line. The concept is simple: passengers pay less in fares for an incremental increase in time spent picking up and dropping off other riders. This paper focuses on the social and behavioral considerations of shared rides, which have not been explored as thoroughly as time and cost trade-offs in transportation. A survey of TNC users conducted through Mechanical Turk in June and July of 2016, which had 997 respondents across the United States, found that (a) users of dynamic ridesharing services reported that social interactions were relevant to mode choice, although not as much as traditional factors such as time and cost; (b) overall, the possibility of having a negative social interaction was more of a deterrent to use of dynamic ridesharing than the potential of having a positive social interaction was an incentive; (c) there was evidence that a substantial number of riders harbored feelings of prejudice toward passengers of different social class and race, and these passengers were much more likely to prefer having more information about potential future passengers; (d) most dynamic ridesharing users were motivated by ease and speed, compared with walking and public transportation; and (e) safety in dynamic ridesharing was an important issue, especially for women, many of whom reported feeling unsafe and preferred to be matched with passengers of the same sex.
Users and potential users of the sharing economy need to place a considerable amount of trust in both the person and the platform with which they are dealing. The consequences of transaction partners' opportunism may be severe, for example damage to goods or endangered personal safety. Trust is, therefore, a key factor in overcoming uncertainty and mitigating risk. However, there is no thorough overview of how trust is developed in this context. To understand how the trust of users in the sharing economy is influenced, we performed a systematic literature review. After screening, 45 articles were included in a qualitative synthesis in which the results were grouped according to a well-established trust typology. The results show various antecedents of trust in the sharing economy (e.g. reputation, trust in the platform, and interaction experience) related to multiple entities (i.e. seller, buyer, platform, interpersonal, and transaction). Trust in this economy is often reduced to the use of reputation systems alone. However, our study suggests that trust is much more complex than that and extends beyond reputation. Furthermore, our review clearly shows that research on trust in the sharing economy is still scarce and thus more research is needed to understand how trust is established in this context. Our review is the first that brings together antecedents of trust in online peer-to-peer transactions and integrates these findings within an existing framework. Additionally, the study suggests directions for future research in order to advance the understanding of trust in the sharing economy.
Car sharing services gain momentum as a potential alternative to various modes of transportation, including privately owned cars. This trend goes hand in hand with a renewed interest in the sharing economy, which has as essential premise that product ownership is of minor relevance. Using an online experiment, this study investigates if individual differences in psychological ownership influence the effects of well-known instrumental car attributes (price, parking convenience, and car type) on people's intention to select a shared car. Results confirmed that instrumental attributes generally impact preferences for car sharing services, and that a low psychological ownership may lead to a higher preference for a shared car under specific circumstances. This suggests that not only instrumental car attributes, but also psychological disposition, specifically psychological ownership, of potential customers need to be taken into consideration when developing measures to stimulate car sharing services in society.
Peer-to-peer carsharing is an innovative approach to vehicle sharing in which vehicle owners temporarily rent their personal automobiles to others in their surrounding area. Peer-to-peer carsharing belongs to the larger sharing economy, an economic model premised on the notion of collaborative consumption as opposed to ownership. This study examined public perception of peer-to-peer carsharing and potential market characteristics through an intercept survey conducted in the San Francisco Bay Area, California. Three hundred respondents from 14 locations in San Francisco (n = 150) and Oakland (n = 150), California, were polled on their existing attitudes toward and perceptions of classic carsharing, peer-to-peer carsharing, and the sharing economy. The survey results indicate that there remains a low awareness of peer-to-peer carsharing, with fewer than 50% of San Francisco respondents and 25% of Oakland respondents having heard of the term. Approximately 25% of surveyed vehicle owners would be willing to share their personal vehicles through peer-to-peer carsharing, citing liability and trust concerns as primary deterrents. Those who drove almost every day were less open to renting through peer-to-peer, while those who used public transit at least once per week expressed a greater interest in it. Overall, the results of this study indicate considerable interest in peer-to-peer carsharing: 60% of San Francisco respondents and 75% of Oakland respondents without vehicle access would consider renting a peer-to-peer vehicle. The top three reasons for using peer-to-peer carsharing are convenience and availability, monetary savings, and expanded mobility options. Further outreach and education are needed to raise awareness of this mobility innovation.
Personal mobility vehicles (PMVs) have increasingly attracted research interest as new individual transportation vehicles that are environmentally friendly, compact, and convenient to use. It is important to ensure the safety and comfort of pedestrians sharing space with PMVs. In this paper, we developed a simulation model considering the interaction between a PMV and pedestrians, and investigated the effects of a PMV in pedestrian flows using the concept of personal space (PS), which is the space in which invasion by others induces a psychological strain. To estimate the mutual effects of a PMV and nearby pedestrians, the invasion ratio and crossing time are introduced as indexes. Furthermore, to ensure pedestrians are comfortable in the presence of a PMV, we proposed an assistance system for a PMV. Simulation results revealed that the invasion of PS increases with increasing pedestrian density. Additionally, experimental results showed that the levels of discomfort and fear that pedestrians felt toward a PMV are also affected by pedestrian density. Finally, the effectiveness of the assistance system was confirmed, particularly for low pedestrian densities.
Research dealing with various aspects of* the theory of planned behavior (Ajzen, 1985,
1987) is reviewed, and some unresolved issues are discussed. In broad terms, the theory is
found to be well supported by empirical evidence. Intentions to perform behaviors of different
kinds can be predicted with high accuracy from attitudes toward the behavior, subjective
norms, and perceived behavioral control; and these intentions, together with perceptions of
behavioral control, account for considerable variance in actual behavior. Attitudes, subjective
norms, and perceived behavioral control are shown to be related to appropriate sets of salient
behavioral, normative, and control beliefs about the behavior, but the exact nature of these
relations is still uncertain. Expectancy value formulations are found to be only partly
successful in dealing with these relations. Optimal rescaling of expectancy and value
measures is offered as a means of dealing with measurement limitations. Finally, inclusion of
past behavior in the prediction equation is shown to provide a means of testing the theory*s
sufficiency, another issue that remains unresolved. The limited available evidence concerning
this question shows that the theory is predicting behavior quite well in comparison to the
ceiling imposed by behavioral reliability.
Due to the rise of businesses utilizing the sharing economy concept, it is important to better understand the motivational factors that drive and hinder collaborative consumption in the travel and tourism marketplace. Based on responses from 754 adult travellers residing in the US, drivers and deterrents of the use of peer-to-peer accommodation rental services were identified. Factors that deter the use of peer-to-peer accommodation rental services include lack of trust, lack of efficacy with regards to technology, and lack of economic benefits. The motivations that drive the use of peer-to-peer accommodation include the societal aspects of sustainability and community, as well as economic benefits. Based on the empirical evidence, this study suggests several propositions for future studies and implications for tourism destinations and hospitality businesses on how to manage collaborative consumption.
In this paper, the effects of a inter-urban carsharing program on users’ mode choice behaviour were investigated and modelled through specification, calibration and validation of different modelling approaches founded on the behavioural paradigm of the random utility theory. To this end, switching models conditional on the usually chosen transport mode, unconditional switching models and holding models were investigated and compared. The aim was threefold: (i) to analyse the feasibility of a inter-urban carsharing program; (ii) to investigate the main determinants of the choice behaviour; (iii) to compare different approaches (switching vs. holding; conditional vs. unconditional); (iv) to investigate different modelling solutions within the random utility framework (homoscedastic, heteroscedastic and cross-correlated closed-form solutions).
The set of models was calibrated on a stated preferences survey carried out on users commuting within the metropolitan area of Salerno, in particular with regard to the home-to-work trips from /to Salerno (the capital city of the Salerno province) to/from the three main municipalities belonging to the metropolitan area of Salerno. All of the involved municipalities significantly interact each other, the average trip length is about 30 Km a day and all are served by public transport. The proposed carsharing program was a one-way service, working alongside public transport, with the possibility of sharing the same car among different users, with free and/or dedicated parking slots and free access to the existent restricted traffic areas.
Results indicated that the inter-urban carsharing service may be a substitute of the car transport mode, but also it could be a complementary alternative to the transit system in those time periods in which the service is not guaranteed or efficient. Estimation results highlighted that the conditional switching approach is the most effective one, whereas travel monetary cost, access time to carsharing parking slots, gender, age, trip frequency, car availability and the type of trip (home-based) were the most significant attributes. Elasticity results showed that access time to the parking slots predominantly influences choice probability for bus and carpool users; change in carsharing travel costs mainly affects carpool users; change in travel costs of the usually chosen transport mode mainly affects car and carpool users.
Structural equation modeling (SEM) is a vast field and widely used by many applied researchers in the social and behavioral sciences. Over the years, many software pack-ages for structural equation modeling have been developed, both free and commercial. However, perhaps the best state-of-the-art software packages in this field are still closed-source and/or commercial. The R package lavaan has been developed to provide applied researchers, teachers, and statisticians, a free, fully open-source, but commercial-quality package for latent variable modeling. This paper explains the aims behind the develop-ment of the package, gives an overview of its most important features, and provides some examples to illustrate how lavaan works in practice.
Ultrafine particles (UFPs; diameter less than 100 nm) are ubiquitous in urban air, and an acknowledged risk to human health. Globally, the major source for urban outdoor UFP concentrations is motor traffic. Ongoing trends towards urbanisation and expansion of road traffic are anticipated to further increase population exposure to UFPs. Numerous experimental studies have characterised UFPs in individual cities, but an integrated evaluation of emissions and population exposure is still lacking. Our analysis suggests that the average exposure to outdoor UFPs in Asian cities is about four-times larger than that in European cities but impacts on human health are largely unknown. This article reviews some fundamental drivers of UFP emissions and dispersion, and highlights unresolved challenges, as well as recommendations to ensure sustainable urban development whilst minimising any possible adverse health impacts.
This article is concerned with how to conceptualize and theorize the nature of the ‘car system’ that is a particularly key, if surprisingly neglected, element in ‘globalization’. The article deploys the notion of systems as self-reproducing or autopoietic. This notion is used to understand the origins of the 20th-century car system and especially how its awesome pattern of path dependency was established and exerted a particularly powerful and self-expanding pattern of domination across the globe. The article further considers whether and how the 20th-century car system may be transcended. It elaborates a number of small changes that are now occurring in various test sites, factories, ITC sites, cities and societies. The article briefly considers whether these small changes may in their contingent ordering end this current car system. The article assesses whether such a new system could emerge well before the end of this century, whether in other words some small changes now may produce the very large effect of a new post-car system that would have great implications for urban life, for mobility and for limiting projected climate change.
Most people think climate change and sustainability are important problems, but too few global citizens engaged in high-greenhouse-gas-emitting behavior are engaged in enough mitigating behavior to stem the increasing flow of greenhouse gases and other environmental problems. Why is that? Structural barriers such as a climate-averse infrastructure are part of the answer, but psychological barriers also impede behavioral choices that would facilitate mitigation, adaptation, and environmental sustainability. Although many individuals are engaged in some ameliorative action, most could do more, but they are hindered by seven categories of psychological barriers, or "dragons of inaction": limited cognition about the problem, ideological worldviews that tend to preclude pro-environmental attitudes and behavior, comparisons with key other people, sunk costs and behavioral momentum, discredence toward experts and authorities, perceived risks of change, and positive but inadequate behavior change. Structural barriers must be removed wherever possible, but this is unlikely to be sufficient. Psychologists must work with other scientists, technical experts, and policymakers to help citizens overcome these psychological barriers.
We review conjoint analysis (CA) usage in recent entrepreneurship research to assess how researchers have used the method to study entrepreneurial decision making. We first provide a brief overview of the method and present an exemplar study. We next examine how 16 studies published in leading entrepreneurship journals from 1999 to 2008 used CA, highlight topics these studies have investigated most frequently, and suggest reasons why studies, in general, have not used the method with greater frequency, despite its many advantages in studying decision making. We conclude by suggesting potential future research applications in an attempt to encourage greater CA usage in entrepreneurship research.
Relying on the theory of planned behavior (Ajzen, 1991), a longitudinal study investigated the effects of an intervention-introduction of a prepaid bus ticket-on increased bus use among college students. In this context, the logic of the proposition that past behavior is the best predictor of later behavior was also examined. The intervention was found to influence attitudes toward bus use, subjective norms, and perceptions of behavioral control and, consistent with the theory, to affect intentions and behavior in the desired direction. Furthermore, the theory afforded accurate prediction of intention and behavior both before and after the intervention. In contrast, a measure of past behavior improved prediction of travel mode prior to the intervention, but lost its predictive utility for behavior following the intervention. In a test of the proposition that the effect of past on later behavior is due to habit formation, an independent measure of habit failed to mediate the effects of past on later behavior. It is concluded that choice of travel mode is largely a reasoned decision; that this decision can be affected by interventions that produce change in attitudes, subjective norms, and perceptions of behavioral control; and that past travel choice contributes to the prediction of later behavior only if circumstances remain relatively stable.
In the context of continuous worldwide practices in building smart cities and promoting smart mobilities, the literature on the reproduction of transport inequality caused by unequal access to smartphone use is gradually increasing. In addition to physical access to smartphone use, this study contributes a new perspective from the privacy concern on (motivational access) and lack of knowledge (skill access) in using location-based service (LBS) to the understanding of unequal access to transport information during the transition to smart cities or mobilities. The study found that women are vulnerable to restricted access to smart transport information due to the privacy concern on and lack of knowledge of using LBS based on a dataset collected from two Chinese cities using a two-stage modeling approach. People aged over 50 tend to be restricted to the traditional source of transport information due to the lack of knowledge of using LBS. Moreover, city-sensitive factors should be considered. Muslims in Urumqi are vulnerable to restricted access to smart transport information compared with Han Chinese because of the lack of knowledge of using LBS. In Wuhan, manual workers/attendants are vulnerable to restricted access to smart transport information compared with those working in offices for the same reason. The lack of knowledge affects the transformation from a traditional to a smart source user, whereas the privacy concern restrains individuals from using multiple smart sources. From these findings, policy recommendations for mitigating the smartness-induced unequal access to transport information are proposed.
Trust is the lubricant of the sharing economy. This is true especially in peer-to-peer carsharing, in which one leaves a highly valuable good to a stranger in the hope of getting it back unscathed. Nowadays, ratings of other users are major mechanisms for establishing trust. To foster uptake of peer-to-peer carsharing, connected car technology opens new possibilities to support trust-building, e.g., by adding driving behavior statistics to users' profiles. However, collecting such data intrudes into rentees' privacy. To explore the tension between the need for trust and privacy demands, we conducted three focus group and eight individual interviews. Our results show that connected car technologies can increase trust for car owners and rentees not only before but also during and after rentals. The design of such systems must allow a differentiation between information in terms of type, the context, and the negotiability of information disclosure.
This paper has two objectives. First, the paper aims to advance knowledge on factors that lead to the choice of car sharing, by proposing, for the first time a different perspective based upon the attitude towards the use of private car. Second, the study helps to understand the connection between the rate of penetration of car sharing services and the attitude towards the use of the private car, analysing also the socio-demographic influences on car-sharing behaviour.
The paper draws on the findings from a telephone-structured questionnaire we carried out in this under-explored market area in four urban metropolitan cities in Italy (Rome, Milan, Turin and Genoa). For this purpose, we firstly made an exploratory factor analysis to determine the key dimensions of private car behaviour. We then performed a logistic regression model in order to analyse which factors may affect the dependent variable.
With the rapid development and popularization of mobile and wireless communication technologies, ridesourcing companies have been able to leverage internet-based platforms to operate e-hailing services in many cities around the world. These companies connect passengers and drivers in real time and are disruptively changing the transportation industry. As pioneers in a general sharing economy context, ridesourcing shared transportation platforms consist of a typical two-sided market. On the demand side, passengers are sensitive to the price and quality of the service. On the supply side, drivers, as freelancers, make working decisions flexibly based on their income from the platform and many other factors. Diverse variables and factors in the system are strongly endogenous and interactively dependent. How to design and operate ridesourcing systems is vital—and challenging—for all stakeholders: passengers/users, drivers/service providers, platforms, policy makers, and the general public. In this paper, we propose a general framework to describe ridesourcing systems. This framework can aid understanding of the interactions between endogenous and exogenous variables, their changes in response to platforms’ operational strategies and decisions, multiple system objectives, and market equilibria in a dynamic manner. Under the proposed general framework, we summarize important research problems and the corresponding methodologies that have been and are being developed and implemented to address these problems. We conduct a comprehensive review of the literature on these problems in different areas from diverse perspectives, including (1) demand and pricing, (2) supply and incentives, (3) platform operations, and (4) competition, impacts, and regulations. The proposed framework and the review also suggest many avenues requiring future research.
This paper makes a critical contribution to the discussion about the transition from an automobile society to a multimodal society in Western transport and mobility research, which is characterised by a flexible use of different transport options. This discussion is fuelled, in particular, by the emergence of smart mobility, in which information and communication technologies (ICTs) – e.g., the smartphone – are used to switch flexibly between new interconnected mobility services (such as carsharing, ridesharing, bikesharing, bus or train). The starting point for the scepticism towards this transition is the research on transport poverty, which problematizes social exclusions from participation in mobility due to the unequal distribution of mode options. This paper suggests a change of perspective from the real mode choice to potential/optional mode choice in order to account for this scepticism in the research on multimodal behaviours. Multioptionality is conceptualised as a necessary precondition for multimodal behaviours to achieve this change of perspective. Based on this conceptualisation, three theses result from a quantitative analysis of a data set from an area in the Rhine-Main region in Germany. The theses challenge the often-postulated potential ubiquity of multimodal behaviours: (i) Transport poverty – represented by a lack of mode options – inhibits the potential production of multimodal behaviours, particularly by socially marginalised people (low income, low education, precarious job situation, etc.). (ii) A multimodal divide describes the reproduction of transport poverty in the guise of modernisation, as the transport poor – with few mode options – also lack certain ICTs that provide central access media to smart mobility. (iii) Another (perfidious) form of social exclusion from participation in smart mobility concerns critical thinkers who avoid installing mobility applications to protect their privacy. This exclusion occurs because these apps do not have an alternative as access software to smart mobility.
Peer-to-peer (P2P) carsharing is a system where car owners rent their vehicle out to other individuals, usually through a facilitating company. One public policy objective of carsharing is to reduce vehicle miles travelled (VMT), which happens as members (renters) reduce car ownership. With a P2P system, VMT reductions could also occur if vehicle owners leave their car to be rented when they would normally drive. This paper assesses how participation in P2P carsharing affects the driving behavior of participating car owners. Data are from 235 car owners in Portland, Oregon who enrolled in a P2P program. The analysis is based on surveys, vehicle use data collected via in-vehicle GPS, and in-depth interviews. Overall, vehicle owners made very few changes to their driving behavior according to the GPS data, with average vehicle use increasing slightly. However, a subset of owners (39%) did decrease their driving by 10% or more one year after the baseline. Factors associated with this reduction in use included higher baseline vehicle use, higher rental activity, income constraints, and more flexibility in daily travel. In addition, some owners appear to use P2P as a catalyst to change travel behavior, including increased use of other modes.
The negative impact of motorized private mobility on the environment can be decreased successfully by encouraging more people to carpool. From a psychological perspective, only little is known about the determinants of carpooling. Therefore, this study investigated car- pooling behavior based on a theoretical background that integrates (1) the theory of planned behavior, (2) the norm activation model, and (3) dispositional trust. Additionally, we studied carpooling from two separate perspectives: Passengers sharing rides, and the drivers offering rides. We conducted a survey with a representative sample of 342 participants in Switzerland. The results showed that for both, passengers and dri- vers, normative aspects such as descriptive and personal norms, in combination with per- ceived behavioral control predicted carpooling intention. Attitude toward carpooling behavior, however, did not have any predictive power regarding carpooling intention, nei- ther for passengers nor drivers. Dispositional trust displayed an indirect effect on intention to carpool as a passenger or driver via perceived behavioral control. Based on these results, we discuss practical implications for designing measures to promote carpooling success- fully in the future.
Activity-travel choices of individuals are influenced by spatial dependency effects. As individuals interact and exchange information with, or observe the behaviors of, those in close proximity of themselves, they are likely to shape their behavioral choices accordingly. For this reason, econometric choice models that account for spatial dependency effects have been developed and applied in a number of fields, including transportation. However, spatial dependence models to date have largely defined the strength of association across behavioral units based on spatial or geographic proximity. In the current context of social media platforms and ubiquitous internet and mobile connectivity, the strength of associations among individuals is no longer solely dependent on spatial proximity. Rather, the strength of associations among individuals may be based on shared attitudes and preferences as well. In other words, behavioral choice models may benefit from defining dependency effects based on attitudinal constructs in addition to geographical constructs. In this paper, frequency of usage of car-sharing and ride-hailing services is modeled using a generalized heterogeneous data model (GHDM) framework that incorporates multi-dimensional dependencies among decision-makers. The model system is estimated on the 2014–2015 Puget Sound Regional Travel Study survey sample, with proximity in latent attitudinal constructs defined by a number of personality trait variables. Model estimation results show that social dependency effects arising from similarities in attitudes and preferences are significant in explaining shared mobility service usage. Ignoring such effects may lead to erroneous estimates of the adoption and usage of future transportation technologies and mobility services.
Australians are one of the world’s highest per capita emitters of greenhouse gases, yet the country’s target for emissions reductions by 2030 remains modest. This paper looks at policy options for Australian cities to deliver faster emissions reductions than the national commitment level. The main focus is on an accelerated reduction in emissions from urban road transport, through technological improvements and behaviour changes. Targets are proposed for improved emissions intensities, to bring Australia much closer to US and EU performance expectations. A range of behaviour change measures is then tested on Melbourne and Sydney, the Sydney analysis using MetroScan-TI, an integrated evaluation framework, to explore how behaviour changes might enhance emissions outcomes. The potential contribution of public transport is a particular focus. The paper concludes that, with sufficient political will, Australia could reduce its 2030 road transport emissions to 40% below 2005 levels. This is a much larger reduction than the current 26-28% Australian emissions but is more consistent with longer term pathways to acceptable carbon budgets.
Personal car use is increasing globally and is an important contributor to poor air quality and global greenhouse gas emissions. Although individuals have little direct control over some emission sources (e.g. heavy industry), they can modify their car use thereby reducing their own contribution. There have been many attempts to understand the psychology of personal car use and identify ways in which individuals might be encouraged to adopt more environmentally friendly travel modes. The aims of this study were (1) to review available psychological theories and models and their applications to understanding car use, (2) to assess the quality of empirical tests of relevant theories and (3) to develop an integrated conceptual overview of potentially modifiable antecedents that could inform future intervention design and further theoretical research. Fifteen psychological theories were identified from thirty-two unique studies but most theories were applied only once. Although two theories in particular (the Comprehensive Action Determination Model and Stage Model of Self-Regulated Behaviour Change) are both relatively comprehensive and have empirical support, our review suggests there are mechanisms of behavioural regulation relevant to car use that are not included in either theory. Integrating theories, we developed an integrative conceptual framework, referred to as the CAr USE (or CAUSE) framework of cognitive and emotional antecedents of car use. This framework is likely to be applicable to other ecologically-relevant behaviour patterns. Implications for research and practice are discussed.
Mobility represents a relevant topic from the standpoint of environmental degradation, health-related consequences and social inclusion. Since private mobility is responsible for the greatest share of polluting emissions, it is necessary to gain deeper understanding of the mechanisms underpinning the choice of individuals to use either cars or alternative, environment-friendly transport modes. A meta-analysis on 58 primary studies is conducted to synthesize evidence on the determinants of travel mode choice, as regards both behavioral intentions and actual behaviors. Results suggest that, besides intentions, habits and past use represent the most relevant predictor, followed by constructs referring to the Theory of Planned Behavior framework. Environmental variables, on the other hand, play a relevant role in shaping behavioral intentions while their effect on actual behaviors is negligible, so that a deep intention behavior gap emerges. A moderator analysis is performed to explain the high heterogeneity in the results. Behaviors’ operationalization and measurement emerges as the moderator affecting heterogeneity of outcomes the most; trip purpose, sample type and year of the study also show a moderate effect on heterogeneity, while location does not appear to be a relevant moderator.
Reduced private car use can limit greenhouse gas emissions and improve public health. It is unclear, however, how promotion of alternative transport choices can be optimised. A systematic review and meta-analysis was conducted to identify potentially modifiable cognitive mechanisms that have been related to car use and use of alternative transport modes. A qualitative synthesis of measures of potentially modifiable mechanisms based on 43 studies yielded 26 conceptually distinct mechanism categories. Meta-analyses of associations between these mechanisms and car use/non-use generated 205 effects sizes (Pearson’s r) from 35 studies. The strongest correlates of car use were intentions, perceived behavioural control, attitudes and habit. The strongest correlates of alternative transportation choices were intentions, perceived behavioural control and attitudes. Implications for researchers and policy implementation are discussed.
A field experiment investigated the prediction and change in repeated behaviour in the domain of travel mode choices. Car use during seven days was predicted from habit strength (measured by self-reported frequency of past behaviour, as well as by a more covert measure based on personal scripts incorporating the behaviour), and antecedents of behaviour as conceptualized in the theory of planned behaviour (attitude, subjective norm, perceived behavioural control and behavioural intention). Both habit measures predicted behaviour in addition to intention and perceived control. Significant habit x intention interactions indicated that intentions were only significantly related to behaviour when habit was weak, whereas no intention-behaviour relation existed when habit was strong. During the seven-day registration of behaviour, half of the respondents were asked to think about the circumstances under which the behaviour was executed. Compared to control participants, the behaviour of experimental participants was more strongly related to their previously expressed intentions. However, the habit-behaviour relation was unaffected. The results demonstrate that, although external incentives may increase the enactment of intentions, habits set boundary conditions for the applicability of the theory of planned behaviour.
Ultrafine particles (UFPs; diameter less than 100 nm) are ubiquitous in urban air, and an acknowledged risk to human health. Globally, the major source for urban outdoor UFP concentrations is motor traffic. Ongoing trends towards urbanisation and expansion of road traffic are anticipated to further increase population exposure to UFPs. Numerous experimental studies have characterised UFPs in individual cities, but an integrated evaluation of emissions and population exposure is still lacking. Our analysis suggests that the average exposure to outdoor UFPs in Asian cities is about four-times larger than that in European cities but impacts on human health are largely unknown. This article reviews some fundamental drivers of UFP emissions and dispersion, and highlights unresolved challenges, as well as recommendations to ensure sustainable urban development whilst minimising any possible adverse health impacts.
Information and communication technologies (ICTs) are hypothesized to replace or change the use of the transport system by facilitating new or different activities. This article offers a review of more than 40 years of research regarding the relationship between ICTs and urban mobility. We discuss the expectations for the changes in travel demand, travel patterns, and the urban form as a result of the development and introduction of ICTs. Much of the interest in the relationships between ICTs and mobility is premised on the expectation of substitution effects, but empirical findings often suggest more complex effects than direct substitution. Although research on single types of travel activity may sometimes indicate simple substitution effects, examination of the broader impacts may also reveal travel generation effects as well. As such, ICTs do not simply substitute mobility patterns but change them. A growing body of research focuses on changing mobility patterns (in terms of time and space), changes in the experience of travel and changes in the perceptions of travel costs due to the interaction between old and new technologies for overcoming distance. ICTs are gradually becoming embedded within the transport system, enabling flexibility, multitasking, and an increase in human activities.
This study examines the potential for a social network peer-to-peer-based carpooling system called FacePorter for the University of Calgary staff and students. In this study, a survey that combined both revealed and stated preferences was designed and distributed randomly among students and staff. The survey consisted of a sample of 210 responses, which were divided into two groups of stated preference respondents: (i) auto drivers, who were given the choice between driving alone and carpooling as drivers; and (ii) transit riders, who were given the choice between public transport and carpooling as passengers. A binomial logit model and two ordinal logit models (one for ride offerors and one for ride seekers) were calibrated to examine the impacts of various examined socio-economic, psychological, and travel characteristic variables on the propensity to participate in the hypothetical carpooling program. The results of the models clearly demonstrated that many factors have significant impacts on FacePorter demand: occupation, income, marital status, working schedule flexibility, trip characteristics (i.e., distance, travel time, and number of required transfers when riding transit), weather condition, carpooling fee, perceived rider and driver profiles, and carpooling fee would significantly influence the market demand of the examined carpooling system. Copyright © 2015 John Wiley & Sons, Ltd.
We describe experimental vignette methodology (EVM) as a way to address the dilemma of conducting experimental research that results in high levels of confidence regarding internal validity but is challenged by threats to external validity versus conducting nonexperimental research that usually maximizes external validity but whose conclusions are ambiguous regarding causal rela-tionships. EVM studies consist of presenting participants with carefully constructed and realistic scenarios to assess dependent variables including intentions, attitudes, and behaviors, thereby enhancing experimental realism and also allowing researchers to manipulate and control indepen-dent variables. We describe two major types of EVM aimed at assessing explicit (i.e., paper people studies) and implicit (i.e., policy capturing and conjoint analysis) processes and outcomes. We offer best practice recommendations regarding the design and implementation of EVM studies based on a multidisciplinary literature review, discuss substantive domains and topics that can benefit from implementing EVM, address knowledge gaps regarding EVM such as the need to increase realism and the number and diversity of participants, and address ways to overcome some of the negative perceptions about EVM by pointing to exemplary articles that have used EVM successfully. Keywords research design, experimental design, quasi-experimental design Understanding the direction and nature of causal relationships is the cornerstone of science (Shadish, Cook, & Campbell, 2002). While the majority of management research provides evidence regarding covariation between antecedent and outcome variables, covariation alone does not answer two important questions crucial for establishing causality: (a) Did the antecedent occur temporally
Social trust is usually treated as a dichotomy between particularized and generalized trust. In this article it is argued that a third distinct form, community trust, is neither particularized nor generalized and bounded in space rather than persons. Factor analysis of survey data from 33 Swedish municipalities (N = 6,453) distinguishes between particularized, generalized and community trust. Furthermore, regression analyses show that the three trust forms have partly distinct antecedents and linked to different types of behaviours. While generalized trust best predicts leaps of faith in relation to strangers, community trust is the only trust form significantly predicting taking part in local problem solving. Finally, multilevel analysis shows that community trust is the trust form most vulnerable to changes with respect to ethnic diversity and socioeconomic equality.
Although ridesharing can provide a wealth of benefits, such as reduced travel costs, congestion, and consequently less pollution, there are a number of challenges that have restricted its widespread adoption. In fact, even at a time when improving communication systems provide real-time detailed information that could be used to facilitate ridesharing, the share of work trips that use ridesharing has decreased by almost 10% in the past 30 years.
In this paper we present a classification to understand the key aspects of existing ridesharing systems. The objective is to present a framework that can help identify key challenges in the widespread use of ridesharing and thus foster the development of effective formal ridesharing mechanisms that would overcome these challenges and promote massification.
Recently, carsharing has entered a phase of commercial mainstreaming as carsharing providers and urban transportation planners aim at broadening the customer base. In this context, knowledge about the motives of carsharing usage is essential for further growth. Based on a qualitative means-end chain analysis this paper therefore explores usage motives, thus expanding the existing insights from analyses of usage behavior. In a series of laddering interviews with users of a US carsharing service, the underlying hierarchical motive structure is uncovered and four motivational patterns are identified: value-seeking, convenience, lifestyle, and environmental motives. Implications are drawn for applying these insights.
In this study, the relevance of psychological variables as predictors of the ecological impact of mobility behavior was investigated in relation to infrastructural and sociodemographic variables. The database consisted of a survey of 1991 inhabitants of three large German cities. In standardized interviews attitudinal factors based on the theory of planned behavior, further mobility-related attitude dimensions, sociodemographic and infrastructural characteristics as well as mobility behavior were measured. Based on the behavior measurement the ecological impact of mobility behavior was individually assessed for all participants of the study. In a regression analysis with ecological impact as dependent variable, sociodemographic and psychological variables were the strongest predictors, whereas infrastructural variables were of minor relevance. This result puts findings of other environmental studies into question which indicate that psychological variables only influence intent-oriented behavior, whereas impact-oriented behavior is mainly determined by sociodemographic and household variables. The design of effective intervention programs to reduce the ecological impact of mobility behavior requires knowledge about the determinants of mobility-related ecological impact, which are primarily the use of private motorized modes and the traveled distances. Separate regression analyses for these two variables provided detailed information about starting points to reduce the ecological impact of mobility behavior.
Mass transit users frequently experience crowding during their commutes. In this study of 139 urban passenger train commuters during rush hour, we found that the density of the train car was inconsequential for multiple indices (self-report, salivary cortisol, performance aftereffects) of stress whereas the immediate seating density proximate to the passenger significantly affected all three indices. When people had to sit close to other passengers, they experienced adverse reactions. These results are consistent with prior work indicating that individual spacing among persons that leads to personal space invasions is a more salient environmental condition than density per se. The findings also have implications for the design of mass transit vehicles.
[I do not have an electronic copy of this chapter. You can find many pages of it online at
https://books.google.co.il/books?redir_esc=y&id=lEgM5N6rIKwC&q=normative+influences+on+altruism#v=snippet&q=normative%20influences%20on%20altruism&f=false
Central to the theoretical model of personal normative influences on altruism presented in this chapter is the idea that altruistic behavior is causally influenced by feelings of moral obligation to act on one's personally held norms. Research supporting this central tenet of the model has demonstrated associations between personal norms and behavior rather than causal relations. These associations are partly causal because the associations appear primarily in the presence of personality conditions conducive to norm activation and are absent when personality conditions are conducive to deactivation, and attributes of personal norms (e.g., centrality, stability, and intensity) relate to altruism singly or in combination, in ways predicted when the causal impact of anticipated moral costs on behavior is assumed. Studies show that variations in situational conditions conducive to activation of moral obligation also influence the relationship between personal norms and behavior. There is ample evidence that variables that foster movement through the activation process—according to the theoretical model—are themselves related to altruistic behavior (e.g., seriousness of need and uniqueness of responsibility). The study of how personal norms are related to altruism is a part of a larger enterprise—the investigation of attitude–behavior relations in general. [I do not have an electronic copy of this chapter. You can find many pages of it online at
https://books.google.co.il/books?redir_esc=y&id=lEgM5N6rIKwC&q=normative+influences+on+altruism#v=snippet&q=normative%20influences%20on%20altruism&f=false]