Why early adopters engage in interpersonal diffusion of technological innovations: An empirical study on electric bicycles and electric scooters

Early adopters promoting electric vehicles in their social network may speed up market uptake of this technology. Apart from their opinion leader status, few previous research details the motivations which turn early adopters into advocates for innovation who approach the non-adopters among their family and friends, or casual acquaintances.Drawing on a survey among 1398 e-bike and 133 e-scooter early adopters in Austria, personal drivers of engagement in interpersonal diffusion are investigated. Longitudinal data one year later for 157 e-bike users allows tests of causal relations. A complementary sample of 33 network peers illustrates the early adopters’ social impact.Early adopters engage actively in discussing product features, instigating trial behavior and recommending purchase. Analyses by structural equation modeling show that efforts at interpersonal diffusion are driven by opinion leadership, experienced product performance, and perceived normative expectations of others toward pro-environmental technologies. Mediator and moderator analyses underline that opinion leadership is conveyed upon early adopters because personal norms and technophilia qualify them as credible and competent for the specific topic of e-vehicles. Social norm interrelations point to dynamic interactions and discourse between early adopters and their addressees. Evidence from the peer sample suggests though that the persuasive impact of early adopters is small.To accelerate market entry of electric vehicles, public or private agencies should foremost approach early adopters scoring high in the identified drivers, and empower them in their role as multiplicators by providing pre-prepared product information and encouraging them to continuously address peers.     

Social influences on household location, mobility and activity choice in integrated micro-simulation models

Agent-based approaches to simulating long-term location and mobility decisions and short-term activity and travel decisions of households and individuals are receiving increasing attention in land-use and transportation interaction (LUTI) models to predict land-use changes and travel behaviour in mutual interaction. Social interactions between households and between individuals potentially have an influence on a wide range of the long-term and short-term choices involved in these systems. In this paper we identify the areas in which social interactions play a role and address the question how these influences can be modelled in the context of agent-based LUTI models. We distinguish impacts on activity participation (joint activity participation, support-and-help activities) and impacts on decision making (information exchange, social adaptation of preferences and aspirations) as the two main areas of social influence. A prototype of a LUTI model is proposed that accounts for impacts of the social network on longer-term mobility decision making through information exchange and social adaptation of preferences and aspirations. The model is demonstrated in a numerical simulation.     

Factors associated with proportions and miles of bicycling for transportation and recreation in six small US cities

The majority of bicycling in the US is for recreation rather than transportation purposes but few studies have examined the question of bicycling purpose. We use data from an online survey conducted in 2006 in six small cities in the western US to examine factors affecting bicycling for transportation compared to bicycling for recreation. The results indicate that individual, social-environment, and physical-environment factors have important influences on the balance between transportation and recreational bicycling and on miles of bicycling for each purpose. Bicycling comfort and an aversion to driving are associated with more transportation bicycling. A culture of utilitarian bicycling and short distances to destinations are also key factors for transportation bicycling. Bicycle infrastructure appears to play an indirect role through its effect on perceived bicycling safety and through the self-selection effect, by attracting bicycling-inclined people to bicycling-supportive communities.     

The factors influencing bicycling in the Bangalore city

Bicycling, in an urban context, have many benefits, compared with motorized transports, like reduced carbon footprint, and lower maintenance, health, social and infrastructural costs. The present paper analyses the various factors contributing to a low percentage of bicycling in the Bangalore city and elicits certain policy aspects to improve the attractiveness of bicycling. The study focuses mainly on the behavioral aspects of commuters pertaining to their childhood and current scenario, and uses a face-to-face questionnaire survey for data collection. These behavioral aspects indicated a commuter’s perception about social expectation, convenience and bicycling infrastructure using a 5-point Likert scale measurement. Information is also collected about factors that might motivate bicycling, and about demographic variables like age, gender, income, etc. The study used a statistical z-test to identify the most influential attitudinal factors and to check whether the various factors are significantly different. The results gave a clear picture about the most dominant attitudinal factors that resulted in the stoppage of bicycling during a commuter’s childhood, and that acted as a deterrent to their bicycle usage in a current scenario. The study determined a need for changing the attitude of people towards cycling by programs that would create a positive image for cycling. There was also a need for segregated cycle lanes and signals at intersections so that people could feel safe while travelling on cycles.     

Investigating heterogeneity in social influence by social distance in car-sharing decisions under uncertainty: A regret-minimizing hybrid choice model framework based on sequential stated adaptation experiments

The present study is designed to investigate social influence in car-sharing decisions under uncertainty. Social influence indicates that individuals’ decisions are influenced by the choices made by members of their social networks. An individual may experience different degrees of influence depending on social distance, i.e. the strength of the social relationship between individuals. Such heterogeneity in social influence has been largely ignored in the previous travel behavior research. The data used in this study stems from an egocentric social network survey, which measures the strength of the social relationships of each respondent. In addition, a sequential stated adaptation experiment was developed to capture more explicitly the effect of social network choices on the individual decision-making process. Social distance is regarded as a random latent variable. The estimated social distance and social network choices are incorporated into a social influence variable, which is treated as an explanatory variable in the car-sharing decision model. To simultaneously estimate latent social distance and the effects of social influence on the car-sharing decision, we expand the hybrid choice framework to incorporate the latent social distance model into discrete choice analysis. The estimation results show substantial social influence in car-sharing decisions. The magnitude of social influence varies according to the type of relationship, similarity of socio-demographics and the number of social interactions.     

Crowdsourced data for bicycling research and practice

ABSTRACT

Cities are promoting bicycling for transportation as an antidote to increased traffic congestion, obesity and related health issues, and air pollution. However, both research and practice have been stalled by lack of data on bicycling volumes, safety, infrastructure, and public attitudes. New technologies such as GPS-enabled smartphones, crowdsourcing tools, and social media are changing the potential sources for bicycling data. However, many of the developments are coming from data science and it can be difficult evaluate the strengths and limitations of crowdsourced data. In this narrative review we provide an overview and critique of crowdsourced data that are being used to fill gaps and advance bicycling behaviour and safety knowledge. We assess crowdsourced data used to map ridership (fitness, bike share, and GPS/accelerometer data), assess safety (web-map tools), map infrastructure (OpenStreetMap), and track attitudes (social media). For each category of data, we discuss the challenges and opportunities they offer for researchers and practitioners. Fitness app data can be used to model spatial variation in bicycling ridership volumes, and GPS/accelerometer data offer new potential to characterise route choice and origin-destination of bicycling trips; however, working with these data requires a high level of training in data science. New sources of safety and near miss data can be used to address underreporting and increase predictive capacity but require grassroots promotion and are often best used when combined with official reports. Crowdsourced bicycling infrastructure data can be timely and facilitate comparisons across multiple cities; however, such data must be assessed for consistency in route type labels. Using social media, it is possible to track reactions to bicycle policy and infrastructure changes, yet linking attitudes expressed on social media platforms with broader populations is a challenge. New data present opportunities for improving our understanding of bicycling and supporting decision making towards transportation options that are healthy and safe for all. However, there are challenges, such as who has data access and how data crowdsourced tools are funded, protection of individual privacy, representativeness of data and impact of biased data on equity in decision making, and stakeholder capacity to use data given the requirement for advanced data science skills. If cities are to benefit from these new data, methodological developments and tools and training for end-users will need to track with the momentum of crowdsourced data.     

Factors associated with bicycle ownership and use: a study of six small U.S. cities

As a means of transportation and as a form of physical activity, bicycling generates benefits to the bicyclist as well as to the community as a whole. Bicycling now accounts for less than 1 percent of all trips for all purposes in the U.S., but evidence from other western countries suggests that under the right conditions, bicycling levels can be significantly higher. Indeed, the experiences of some U.S. cities suggest that it is possible to create conditions conducive to higher levels of bicycling even in the U.S. However, the extent to which bicycle investments have contributed to bicycling levels in these communities has not been rigorously assessed. The purpose of this study is to provide a better understanding of the determinants of bicycle ownership and use as a basis for identifying ways to promote bicycling. A cross-sectional study of six cities was designed to test the importance of bicycle infrastructure and other physical environment factors relative to individual factors and social environment factors, using a nested logit model to examine ownership and use decisions jointly. The results show strong effects of individual attitudes and physical and social environment factors on bicycle ownership and use.     

The objective versus the perceived environment: what matters for bicycling?

This paper examines the relationship between the objectively measured and perceived built environment, and the relative strength of their association with bicycling behavior. By drawing on socio-cognitive theory, a conceptual model was proposed to explain the relationships between the objective environment, perceived environment, and bicycling behavior. Objective and perceived bike environments were measured using two latent constructs and structural equation modeling was employed to estimate the models based on data from three neighborhoods in Portland, Oregon. Results of this study showed that the perception of the environment had a direct and significant effect on bicycling behavior, while the direct effect of the objective environment on bicycling behavior became insignificant when controlling for perception. We therefore concluded that the objective environment may only indirectly affect bicycling behavior by influencing perceptions. An objectively good environment for bicycling was necessary but not sufficient for bicycling. Intervention programs to improve people’s perceptions of the environment may be necessary to reap the full potential of planning and design policies.     

Why do you care what other people think? A qualitative investigation of social influence and telecommuting

The effect of social interactions on decision-making is a topic of current interest in the travel behavior literature. These interactions have been investigated primarily from an intra-household perspective, but increasingly too in other types of social settings. In the case of interactions within a workplace, it has been suggested that the decision to telecommute may have some important social components. Previous research has concentrated on social isolation, and the effect on job satisfaction of qualitatively different (i.e., telecommunications-mediated) relationships with managers and colleagues. A topic that remains unexplored is the way social norms, in effect the influence of other people’s behavior, may influence the decision to adopt telecommuting. In this paper we set to investigate, within a qualitative framework, the role of social contact in the process of acquiring information on, and making decisions about, telecommuting. The results indicate that social contact does play a subtle but non-trivial role in the adoption and continuation process, and offer some insights about the importance of the social dimension, institutional set-up, and how they interact to influence the decision to telecommute.     

Expanding scope of hybrid choice models allowing for mixture of social influences and latent attitudes: Application to intended purchase of electric cars

Recently, policy makers’ expectations about the role of electric cars in reducing emissions have risen substantially. In parallel, academic research on purchase intentions has dramatically increased. Originally, most studies have focused on utility attributes and price. More recently, several hybrid choice models have been estimated to include the impact of attitudes on choice probabilities. In addition, a few studies have caught the attention to social influence. In contributing to this line of research, this paper reports the results of an expanded hybrid choice, which simultaneously estimated all these different effects in a single integrated model of purchase intention. Results indicate that the model performs well. Costs considerations contribute most to the utility of electric cars. Social influence is less important, but there is also evidence that people tend to take it into consideration when there are positive public opinions about electric cars and the market share becomes almost half of friends of their social network. The intention to purchase an electric car is also influenced by attitudes about environmental concerns and technology acceptance.     

Mobility, social exclusion and well-being: Exploring the links

Building on a growing research foundation, transport policy makers have begun to associate the ability to be mobile with having a role in the facilitation of social inclusion. However, the further connection to well-being is not as well understood. This paper explores the association between a person’s travel patterns, their risk of social exclusion and self-assessed well-being. Key influences on social exclusion are discussed, with trip making emerging as a significant influence. Trip making is not a significant direct influence on well-being but does exercise an indirect influence through the impact on risk of social exclusion. The modelling process enables a value for additional trips to be estimated, the value being about four times the values derived from conventional generated traffic approaches. Similar high values are found in separate metropolitan and regional case studies, confirming the significance of the results.     

The effect of social comparisons on commute well-being

We study the effect of social comparisons on travel happiness and behavior. Social comparisons arise from exchanges of information among individuals. We postulate that the social gap resulting from comparisons is a determinant of “comparative happiness” (i.e. happiness arising from comparisons), which in turn affects subsequent behavior. We develop a modeling framework based on the Hybrid Choice Model that captures the indirect effect of social comparisons on travel choices through its effect on comparative happiness.We present an empirical analysis of one component of this framework. Specifically, we study how perceived differences between experienced commute attributes and those communicated by others affect comparative happiness and consequently overall commute satisfaction. We find that greater comparative happiness arising from favorable comparisons of one’s commute to that of others (e.g. shorter commute time than others, same mode as others for car commuters, and different mode than others for non-motorized commuters) increases overall commute satisfaction or utility.The empirical model develops only the link between social comparisons and happiness in the comparisons-happiness-behavior chain. It is anticipated that the theoretical framework that considers the entire chain will enhance the behavioral realism of “black box” models that do not account for happiness in the link between comparisons and behavior.     

Development of pictograms for dynamic traffic control systems in South Korea

This study developed a set of pictograms for lane control systems, to provide additional information to drivers on weather and traffic incidents. The results suggest that in the design of traffic signs, it is important to consider local context and not simply adopt standards and practices that are developed elsewhere. The differences in the social and cultural environments may affect the ease of reading and comprehension by local drivers. However, the study also showed that not all locally developed signs were rated higher for their ease of reading than others… Since some design characteristics are more salient, whereas others tend to be more dependent on the local context, it is important to conduct simple experiments and exploratory research to find the optimal designs to be used.     

Urban transport in Germany: providing feasible alternatives to the car

With the second highest level of car ownership in the world, and the third highest population density in Europe, Germany has adopted a range of policies to balance the many private benefits of car use with its serious social and environmental problems. In order to ‘tame’ the car, most German cities have implemented a twofold strategy of expanding and improving pedestrian, bicycling and public transport alternatives simultaneously with restricting car use and making it more expensive. That has increased political acceptability since the car‐restrictive measures are not perceived as mere punishment of car drivers. The results of this coordinated urban transport strategy have been impressive. Germany, as a whole, has managed to increase public transport use and to stabilize the car share of modal split. Some cities, of course, have been more successful than others, and this paper examines three of the most successful cities: Münster, Freiburg and Munich. In each of the cities, the percentage of travel by bicycling, walking and public transport has been raised over the past 20 years, while the car's share of modal split has fallen. This article documents the range of policies used to restrict car use, both in Germany as a whole, and in the three case‐study cities in particular. The key to success is found to be mutually reinforcing transport and land‐use policies. It is the combination of a whole set of coordinated policies that explains the dramatic success in changing travel behavior.     

Correcting for endogeneity in behavioral choice models with social influence variables

While psychologists and behavioral economists emphasize the importance of social influences, an outstanding issue is how to capture such influences in behavioral models used to inform urban planning and policy. In this paper we focus on operational models that do not require explicit knowledge of the individual networks of decision makers. We employ a field effect variable to capture social influences, which is calculated as the percent of population in the peer group that has chosen the specific alternative. We define the peer group based on socio-economic status and spatial proximity of residential location. As in behavioral economics and psychology, the concept is that one is influenced by the choices made by one’s peers. However, using such a social influence variable in a behavioral model causes complications because it is likely endogenous; unobserved factors that impact the peer group also influence the decision maker, yielding correlation between the field effect variable and the error. The contribution of this paper is the use of the Berry, Levinsohn, and Pakes (BLP) method to correct the endogeneity in a choice model. The two-stage BLP introduces constants for each peer group to remove the endogeneity from the choice model (where it is difficult to deal with) and insert it into a linear regression model (where endogeneity is relatively easier to deal with). We test the method using a mode choice data set from the Netherlands and readily available software and find there is an upward bias of the field effect parameter when endogeneity is not corrected. The procedure outlined presents a practical and tractable method for incorporating social influences in choice models.     

A threshold model of social contagion process for evacuation decision making

Individual evacuation decisions are often characterized by the influence of one’s social network. In this paper a threshold model of social contagion, originally proposed in the network science literature, is presented to characterize this social influence in the evacuation decision making process. Initiated by a single agent, the condition of a cascade when a portion of the population decides to evacuate has been derived from the model. Simulation models are also developed to investigate the effects of community mixing patterns and the initial seed on cascade propagation and the effect of previous time-steps considered by the agents and the strength of ties on average cascade size. Insights related to social influence include the significant role of mixing patterns among communities in the network and the role of the initial seed on cascade propagation. Specifically, faster propagation of warning is observed in community networks with greater inter-community connections.     

The symbolism of ‘eco cars’ across national cultures: Potential implications for policy formulation and transfer

Transport choices are not merely practical decisions but steeped in cultural and societal perceptions. Understanding these latent drivers of behaviour will allow countries to develop and import policies to more successfully promote sustainable transport. Transport symbolism – what people believe their ownership or use of a mode connotes to others about their societal position – has been shown to be one such, non-trivial, hidden motivator. In the case of hybrid and electric cars (‘eco cars’), studies have demonstrated how their symbolic value varies within a society among different social groups. As yet, however, there has been scant research into comparing how the symbolism of a mode varies across national cultures, horizontally, between individuals with similar socio-demographic characteristics. Through qualitative thematic analysis, this study utilises two of Hofstede’s cross-cultural indices – power differential and individualism versus collectivism – to develop and strengthen theory on how the differing symbolism of eco cars currently varies between four cultural clusters – Anglo, Nordic, Confucian and South Asian. It also deliberates how observed symbolic qualitative differences may influence an individual or group choice to procure eco cars. Finally, it discusses how policy development, transfer and marketing, within the context of eco cars, may need to be modified by national governments, in the Confucian and South Asian cultures, so as to encourage uptake and modal shift.     

Exploring the links between personal networks, time use, and the spatial distribution of social contacts

Although the study of the role of the social context in travel behavior and activity patterns has recently gained attention, the empirical evidence supporting the relationship between social networks and the temporal and spatial characteristics of social activities is still limited. With this motivation, this paper studies the link between “longer term” (social networks) and “shorter term” (social activities) social decisions, by exploring the intertwined relationship between the individuals’ personal networks attributes, and the spatiotemporal characteristics of their daily social activities. The paper contributes to the literature by adding two key aspects to the study of the role of social networks on travel behavior: the social networks’ structure, and the spatiality of all individuals participating on the social activities. Based on data which link people’s personal networks and time use, and using a structural equation modeling approach, the paper studies the influence of individual and interactional attributes on the duration, distance, and number of people involved in social daily activities. The results show that aspects such as tie social closeness, gender and age similarity, and network density, help to understand social activity duration and distance, complementing traditional socio-demographic aspects such as income, occupation, and accessibility to services. In this way, socio-demographic attributes are not enough to explain the spatiotemporal dimension of daily activities which makes necessary to include variables related to the social context to explain with a higher level of accuracy both the duration and distance traveled to the activity.     

Gender inequality in mobility and mode choice in Pakistan

Using the nationally representative dataset of the 2007 Pakistan Time-Use Survey, this paper examines gender differences in daily trip rate, mode choice, travel duration, and purpose of travel, which are previously unreported because of limited data availability. Wide gender mobility gaps are observed in the country, where women are less likely to travel, are half as mobile as men and may rely heavily on walking. The particular social and cultural context of the country, that renders women as private, secluded and family honor, seems influential in shaping their mobility and choice of activities. Demographic factors such as age, household income, and marital status significantly decrease female mobility levels. Hence, these findings call for a gender-based culturally responsive transportation policy in the country.     

Framing the role of Decision Support in the case of Stockholm Congestion Charging Trial

Congestion charging was – as a trial – introduced in Stockholm from January 3rd to July 31st 2006. After the referendum in September 2006, the charging system was finally introduced as permanent from August 2007 with some adjustments to the Trial design. The idea of congestion charging is unique in a Swedish context, and the introduction of the Stockholm system has been highly controversial. Considerable efforts have therefore been undertaken to provide information that could serve as ‘Decision Support’ along the way. This has included e.g. modelling and forecasts before the Trial, a comprehensive evaluation programme during the Trial, extensive stakeholder consultations throughout, and various information and communication strategies. But what difference did this information input make, and what was its role in the process from initiating the system, to its final adoption? In this paper we pave the way for investigating the use and role of ‘Decision Support’ in the Stockholm Congestion Charging experiment. We adopt a definition of Decision Support as the systematic application of externally produced knowledge in transport planning and policy making processes. We then derive an analytical framework from the research literature on ‘knowledge utilization’ in policy making. This research has generally found that both ‘technical’, ‘communicative’, and ‘institutional’ aspects of the Decision Support matter for its influence on actual policy making processes and results. In our analysis we find a similar pattern. This high technical quality of the monitoring and evaluation programmes provided for solid verified results, while the institutional arrangements and the communication strategies helped to ensure the credibility and legitimacy of the information for the decision makers. The availability of rich contents coupled with strategies for the timely and targeted information delivery suggest that direct ‘instrumental’ use could have taken place. At a more general level the Trial represents an advanced form of ‘Decision Support’ that goes beyond the mere application of calculated results to encompass a process where the decision parameters themselves become part of the change process.