The economic impact of the ATA/Southwest Airlines code-share agreement

This paper examines the economic impact of the code-sharing agreement between ATA and Southwest Airlines, the first time Southwest has chosen to enter markets via a code-share alliance rather than direct entry. We examine the impact of complementary code-sharing on incumbent airline's fares and passenger volumes and also the overall impact on consumer welfare in Denver airline markets. Empirical results show that air fares decreased and passenger volumes increased for incumbent carriers operating on code-shared routes. Further, we find evidence that this code-sharing arrangement increased both consumer and producer surplus. Thus, the well-known “Southwest Effect” is observed not only when Southwest enters a route directly, but also when it enters a route via a code-share agreement with another airline.     

Extracting patterns from Twitter to promote biking

Emphasis on non-motorized travel modes (for example, biking) reduces motorized trips and provides positive effects on the environment and the quality of human life. Understanding factors that influence people to biking or bike commuting can help decision makers, transportation planners, and bike commuting networks. Historically, conventional methods like surveys and crash data analyses were conducted to understand relevant factors. Survey and crash data analysis are difficult to perform in broad scale due to data availability and efforts. An innovative approach to determining these factors is to conduct social media mining to understand sentiments or motivations of bike commuters. People use terms (with hashtag at the beginning of the term) in Twitter, a popular social media network, to express their thoughts, activities or information. This study developed a framework for using Twitter data in understating the sentiments of the bikers with minimal effort. In this study, Twitter data associated with bike commuting hashtags were obtained for eight years (2009–2016). This study provided a framework of data collection and application of various natural language processing (NLP) tools (for example, text mining, sentiment analysis) to extract knowledge from the unstructured text data. Findings show that biking is associated with weather and seasonal patterns. The general sentiment towards biking is positive. However, negative sentiments are associated with bad weather, crime, and other challenges. The polarity scores indicate somewhat positiveness in the recent few years. The developed framework and the findings of this study will help planners and decision makers to promote biking on a broader scale.     

Transport pricing and Public-Private Partnerships in theory: Issues and Suggestions

This chapter offers a theoretical examination of the following questions: what are the issues that arise when Social Marginal Cost Pricing is to be incorporated in Public-Private Partnerships (PPPs); and how may these issues be dealt with?We first briefly discuss Public-Private Partnerships in transport: what are the defining characteristics and what are the main types that exist in the different modes of transport? Next we consider the economics of Public-Private Partnerships, in particular from the viewpoint of incentives. Subsequently we identify and examine the issues that arise when Social Marginal Cost Pricing is to be incorporated in PPPs as a regulation with regard to pricing in the transport sector. Lastly, we investigate the possibilities of resolving these issues.     

论人身保险合同订立中保险人的答复义务

人身保险合同订立中,作为要约书面形式的投保书通常未标明有效期限,为合理分担合同未成立前的风险,保证交易的安全,实现当事人间利益的平衡和社会正义,应当强制保险人在法定时间或合理期限内答复, 而无论承诺与否;否则,即构成默示承诺。     

Application of multi-criteria decision analysis methods for assessing walkability: A case study in Porto Alegre,Brazil

The concept of walkability refers to the extent to which a neighbourhood is walking-friendly. Several walkability indexes have been developed to quantify and evaluate the pedestrian environment. These indexes differ in terms of type of data, methods and goals. The indexes variables may present either uniform or distinct weights, defined by arbitrary, empirical or other diverse weighting methods. This paper pursues the determination of a weighted walkability index, constructed on the basis of the relative importance of their attributes. Weights were determined by the application of the Fuzzy Analytic Hierarchy Process (FAHP), a robust multi-criteria method which considers the experts’ uncertainty in decision making. Moreover, FAHP weights were compared with the attribute weights obtained from other simpler methods, and a chi-square test for homogeneity was computed to compare the obtained values. The three most important walkability attributes were: Public Security, Traffic Safety and Pavement Quality, similar results to the ones found in the literature. The application to a case study in the city of Porto Alegre, Brazil, allowed categorizing the studied neighbourhoods and to analyse the effect of changes on attributes in walkability.     

What drives people to accept automated vehicles? Findings from a field experiment

This field study aims at understanding the influence of direct experience of an automated vehicle (AV, Level 3) and explaining and predicting public acceptance of AVs through a psychological model. The model includes behavioral intention (BI) to use self-driving vehicles (SDVs, Level 5), willingness to re-ride (WTR) in our AV (Level 3), and their four potential determinants, namely perceived usefulness (PU), perceived ease of use (PEU), trust related to SDVs, and perceived safety (PS) while riding in our AV. The last two determinants are largely ignored, but we consider them critical in the context of AVs. Three-hundred students were invited as participants (passengers) to experience the AV. The trust, PU, PEU, and BI of the participants were recorded prior to their experiencing the AV; after this experience, all the constructs of the psychological model were recorded. The participants’ experience with the AV was found to increase their trust, PU and PEU (but not BI), the consistency between PU/PEU and BI, and the explanatory power of BI. The model explained 55% of the variance in BI and 40% in WTR. PU, trust, and PS were found to be steady and direct predictors of both the acceptance measures; PEU predicted BI only after the participants’ AV experience. Mediation analysis showed that trust also can indirectly affect AV acceptance through other determinants. Out-of-sample prediction confirmed the model’s predictive capability for AV acceptance. The theoretical contributions and practical implications of the findings are discussed.     

Role model advocacy for sustainable transport

Individual aspirations of associating with role models are routinely harnessed by marketers, who for instance, use celebrity endorsement in selling brands and products. It appears there has been no research to date, however, on the potential for celebrity activism, or role model advocacy beyond celebrities, such as from politicians, to form effective interventions for encouraging sustainable transport behavior. This is despite studies suggesting that celebrity endorsement is a potential gateway for transforming public opinion on carbon intensive transport modes. The present paper consequently offers a critical review of the literature on role model advocacy and celebrity activism, and how these concepts have been harnessed to address environmental issues, in order to conceptually assess the potential for extending these intervention techniques to the context of sustainable transport. The scope of the paper includes the potential that high profile politicians/celebrities might play as role models in exercising referent power to influence social norms surrounding sustainable transport, given that the success of social marketing interventions are closely tied to the need for changes in the policy landscape. Key dimensions of role model endorsement in transport are identified and applied to a series of examples of how celebrity and political role models have influenced transport cultures. In addition to offering an original application of a theoretical framework to a new context, in order to help address the increasingly important societal issue of transport’s growing contribution to climate change, the paper discusses the challenges associated with the neoliberal framing of this approach.     

Connectivity’s impact on mandatory lane-changing behaviour: Evidences from a driving simulator study

The connected environment provides driving aids to help drivers making efficient and safe driving decisions. The literature to date is devoid of conclusive evidences of the connected environment’s impact on drivers’ mandatory lane-changing (MLC) behaviour. As such, the objective of this study is to examine MLC behaviour through a driving simulator experiment using the CARRS-Q Advanced Driving Simulator. Participants with diverse background performed the experiment in randomised driving conditions: baseline (without the driving aids), connected environment with perfect communication, and connected environment with communication delay. Repeated measure ANOVA in the form of linear mixed model and Generalized Estimation Equation (GEE) are employed to analyse various driving performance indicators during MLC event. We find that drivers in the connected environment tend to wait longer, increase the initial speed, and maintain a larger spacing, compared to when they are driving in the baseline condition. In addition, drivers in the connected environment are likely to reject fewer number of gaps and select relatively bigger gap sizes. Furthermore, post-encroachment time (PET) in the connected environment is higher across different gap sizes, indicating that the connected environment makes MLC safer. The GEE model on gap acceptance suggests that the perfect communication and communication delay has positive and negative impact on the accepted gap size, respectively, and the GEE model on lane-change duration indicates that lane-change duration tends to increase in the connected environment.     

An empirical investigation on consumers’ intentions towards autonomous driving

Major steps towards implementation of autonomous and connected transport are being taken nowadays. The trend of automation technology being used in vehicles by the most important vehicle manufacturing industries is expected to move closer to high or fully Autonomous Vehicles (AVs) through technological advancements in sectors of robotics and artificial intelligence. Vehicles with autonomous driving capabilities are planning to be available on market, in full scale, in the next years. In the longer term substantial benefits are mainly expected for accessibility to transport, safety, traffic flow, emissions, fuel use and comfort. All these potential societal benefits will not be achieved unless AVs are accepted and used by a critical mass of people. Addressing these challenges, this paper: (a) proposes a technology acceptance modelling process by extending the original Technology Acceptance Model (TAM) to explain and predict consumers’ intensions towards AVs, (b) based on the proposed TAM-extended framework, a 30-question survey was conducted in order to investigate the factors influencing consumers’ intensions to use and accept AVs. Results show that the constructs of perceived usefulness, perceived ease to use, perceived trust and social influence, are all useful predictors of behavioral intentions to have or use AVs, with perceived usefulness having the strongest impact. The insights derived from this study could significantly contribute to ongoing research related to technology acceptance of AVs and are expected to allow automobile industries to improve their design and technology.     

Social welfare analysis of investment public–private partnership approaches for transportation projects

This paper has two objectives: (i) to introduce a new approach in order to gain widespread support for road pricing; and (ii) to develop a detailed social welfare analysis for road pricing schemes. We first describe our novel approach that stimulates public support for road pricing, which we refer to as an investment public–private partnership, or IP3. This approach returns a significant portion of the economic value created by road pricing back to the citizens who own the newly priced facility. We then present a social welfare framework that estimates the benefits and costs of using the IP3 approach on an urban transportation network. A P3 project’s impact on overall social welfare provides a more comprehensive evaluation criterion than the often-used Value for Money (VfM) analysis. Apart from several theoretical studies, a detailed social welfare analysis that includes all major P3 project stakeholders is absent from the literature. We use Fresno, California as our case study in order to conduct a welfare analysis on IP3s. Our results show that system-optimal tolling favors average users, but that government—and consequently taxpayers—should pay for costly tolling systems (negative profits). In contrast, unlimited profit-maximizing tolls raise substantial profits for government, for the infrastructure’s citizen-owners, and for the private sector, but the average user is worse off. From a social-welfare perspective, one should search for a Pareto improvement under which all major stakeholders are better off. Our estimates indicate that a mixed public and private tolling scheme offers such an improvement.