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The Shift toward a Sustainable Urban Mobility through Decision Support Systems


The term smart city is not an easy one to characterize. There is no universally accepted definition but an authentic multitude of definitions, which tend to highlight different aspects of an issue with many facets. A smart city is "a city well performing in six characteristics, built on the "smart" combination of endowments and activities of self-decisive, independent and aware citizens" (Giffinger et al. 2007). A city may only claim any such status "when investments in human and social capital and traditional (transport) and modern (ICT) communication infrastructure fuel sustainable economic growth and a high quality of life, with a wise management of natural resources, through participatory governance" (Caragliu et al. 2011). Others consider the smart city "as a city in which ICT is merged with traditional infrastructures, coordinated and integrated using new digital technologies" (Batty 2012).

Despite this proliferation of interpretations, the essence of the smart city issue is, for us, relatively simple: the urban population is expected to increase in the coming years to the point that many cities around the world will become megacities, with more than 10 million inhabitants. Furthermore, cities are the places in the world where the bulk of consumption of nonrenewable resources is concentrated; this implies that the innovations that must guide us toward a new model of sustainable development, that is, development that meets the needs of the present without compromising the ability of future generations to meet their own needs (WCED 1987), must be experimented first of all within cities, where they may cause more benefits.

For us, this is the key meaning of urban smartness. Accordingly, the smart city concept addresses the issues of urban development with an emphasis on social, economic, and environmental sustainability (Vesco and Ferrero 2015). Fulfilling the objective of being smart is a long journey and it may only be reached with an open innovation approach, that is, government, industry, academia, and citizens working together to co-create a sustainable future and drive structural changes far beyond the scope of what any one actor could do alone.

The smart city subject encompasses several application areas, among which urban mobility is a central theme. In fact, mobility in urban areas is affected by growing problems caused by increasing demand and inefficient services. These problems, summarized as congestion, more energy consumption, rising noise levels, and air pollution, produce a multitude of consequences on the whole urban system and imply significant economic losses both for the public/private sector and civil society (D'Orey and Ferreira 2014). For instance, road congestion in Europe, which is mainly located in urban areas, costs about 1% of the EU's total gross domestic product annually (D'Orey and Ferreira 2014). There is also an environmental cost related to urban mobility, estimated at 1.1% of gross domestic product in the EU and covering air pollution, noise, and global warming costs (D'Orey and Ferreira 2014). Moreover, given that the demand for mobility in urban areas will increase with the growth of people living in those areas, delivering mobility services to cope with this increasing demand requires the development of effective and, more than ever, sustainable solutions.

The transition toward a more sustainable mobility model not only comprises innovation at vehicle or infrastructure level, but also requires an open innovation approach to services supporting mobility such as monitoring, info-mobility, multimodal travel planning, and integrated ticketing, among the many public/private mobility services. Mobility services such as electric-car sharing, carpooling and bike sharing should be considered, with incentives to provide citizens with new, affordable, appealing, and sustainable solutions. These services indeed have the potential to push and entice citizens to reduce expensive and polluting mobility based on private cars. However, these new services need the right boundary conditions and policies from central and local authorities to penetrate and become an effective alternative.

Interdisciplinary and cross-sectorial expertise, together with information and communication technologies (ICTs), is an enabling factor of sustainable development. When ICTs are not the final goal but a means of the innovation process, they effectively facilitate the transition toward a more sustainable urban mobility. Under this condition, ICTs could effectively help local authorities, solution providers, and investment managers to adopt an integrated approach to the development of a sustainable urban mobility system.

Decision support systems (DSSs) are one of the most powerful applications of ICTs and could play a key role in this endeavor. These systems, which help to analyze complex phenomena, support the institutional bodies and the business sector in many different ways and with many different approaches to contribute to the development of sustainable mobility.

It is worth noting that institutional bodies and the business sector are not the sole key players in the innovation process aimed at the transition toward sustainable mobility. Great importance is placed on the citizen that, thanks to access to information and communications, through adequate engagement techniques and leveraging of custom DSSs, can change his or her habits and contribute to the shift toward more sustainable mobility.

In this chapter we (1) claim that DSSs are instrumental in the sustainable development of urban mobility, as they are useful to each decision maker to better predict, evaluate, and measure the impact of alternative solutions and to take informed and evidence-based decisions; and (2) present a number of DSSs explaining how sustainable mobility targets could be reached through these systems. [1] [2]

However, in recent decades, many methods for how experts and governments could engage citizens in the urban planning processes have been argued (Abdalla et al. 2015), favoring the transition of a city toward a smart and sustainable city. This approach is fostered by the diffused use of collaborative design tools, social media, and new technologies.

Within this framework, DSSs represent a tool that plays a key role in helping citizens (i.e., the users of the urban mobility system) to take decisions on how to commute daily in a more sustainable fashion. These kinds of DSSs typically come in the form of web or mobile apps that empower citizens to change (or not) their habits by proposing different alternatives and enlightening the sustainability implications of the available mobility choices.

  • [1] 14.2 Need for Decision Support Systems inDeveloping Sustainable Urban Mobility The development of today's mobility systems is not an easy task because urban mobility isa complex dynamic system. The different elements of the system are linked, meaning thata perturbation in a single element affects the whole system. Therefore, any variation in thesystem, such as the introduction of new policies or new mobility services, needs to be evaluated by considering the interconnected social, economic, and environmental implications.This issue requires several variables and outcomes to be taken into consideration or, in otherwords, to take a holistic and integrated approach to the planning and management challenge. A DSS is designed to increase the effectiveness of analysis because it provides support toall those who need to make strategic decisions in the face of complex problems. Its definition can be deduced from the name itself: • Decision: Indicates the attention paid to decision-making issues. • Support: Indicates that information technology helps in making decisions but doesnot replace the decision maker, who is the main actor.
  • [2] System: Highlights that these tools are designed to enable the integration betweenusers, computers, and methods of analysis. This definition provides evidence that a DSS allows decision makers to predict moreefficient initiatives to implement local strategies while reducing the risks associated withthe deployment of large-scale innovations in the urban context. Over the past decades, with the introduction and diffusion of sustainable urban development policies, academia, industry, and government, several DSSs have developed asevaluation tools to support the decision-making process in the field of sustainable urbanplanning (Gil and Duarte 2013). Due to the complexity of urban systems, there is a largevariety of DSSs. Differences are found in several factors, which are, among others, specificsustainability issues, different stages of the urban development process, system scales (i.e.,spatial or temporal), and type and number of users involved. When a DSS for sustainable urban mobility is properly integrated with different modeling and simulation techniques, it becomes an effective tool for the so-called scientificurban management, which means managing urban complexity with a strong scientificapproach. Moreover, the implementation of scientific urban management could enable theseamless interaction between all stakeholders involved in the innovation process of urbanmobility planning. Our discussion, until now, addresses DSSs as tools for the classical top-down approachto urban planning and management, where the local authorities, solution providers, andinvestment managers are the main stakeholders.
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