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Transportation and mobility in smart cities are undergoing a grave transformation as new ways of mobility are introduced to facilitate seamless traveling, addressing travelers’ needs in a personalized manner. A novel concept that has been recently introduced is Mobility-as-a-Service (MaaS), where mobility services are bundled in MaaS Plans and offered to end-users through a single digital platform. The present paper introduces a recommender system for MaaS Plans selection that supports travelers to select bundles of mobility services that fit their everyday transportation needs. The recommender filters out unsuitable plans and then ranks the remaining ones on the basis of their similarity to the users’ characteristics, habits and preferences. The recommendation approach is based on Constraint Satisfaction Problem (CSP) formalisms combined with cosine similarity techniques. The proposed method was evaluated in experimental settings and was further embedded in real-life pilot MaaS applications. The experimental results showed that the proposed approach provides lists of MaaS PlanMaaS Plans that users would choose in a real-life MaaS setting, in most of the cases. Moreover, the results of the real-life pilots showed that the majority of the participants chose an actual MaaS Plan from the top three places of the recommendation lists.

Rendering transport behaviours more sustainable is a pressing issue of our times. In this paper, we rely on the deep penetration of mobile phones in order to influence citizens’ behavior through data-driven mobility and persuasive profiles. Our proposed approach aims to nudge users on a personalized level in order to change their mobility behavior and make more sustainable choices. To achieve our goal, first we leverage pervasive mobile sensing to uncover users’ mobility patterns and use of transportation modes. Second, we construct users’ persuadability profiles by considering their personality and mobility behavior. With the use of the aforementioned information we generate personalized interventions that nudge users to adopt sustainable transportation habits. These interventions rely on persuasive technologies and are embedded in a route planning application for smartphones. A pilot study with 30 participants using the system for 6 weeks provided fairly positive evaluation results in terms of the acceptance of our approach and revealed instances of behavioural change.

The mobility landscape has changed over the last years with the advent of innovative transportation solutions which are being constantly deployed whereas more are set to emerge in the near future such as autonomous vehicles and flying taxis. In this landscape a new mobility paradigm has come to the forefront during the last years through Mobility as a Service (MaaS). This refers to a seamless integration of various forms of transport services accessible through one single digital platform. The concept of MaaS is aligned with Smart mobility, one of main Smart City components which refers to smart manners of people and goods mobility through the integration of all transport modes, ICT solutions, zero pollution and congestions and so on [1]. A key enabler for MaaS is technology that can provide the means for complex mobility ecosystems to be integrated, while allowing diverse service providers and related stakeholders (e.g. payment management organizations) to perform transactions between each other (for booking, invoicing, payment, etc.) as well as interact with the traveler, acquire and exchange operational data, and process it into information that can be used to support MaaS related business processes. Such an ecosystem can be centrally coordinated when all participants in the value chain have the same understanding of what needs to be delivered and accept to follow a common approach, which can be proprietary, customized and aligned to vendor specific guidelines. As the MaaS ecosystem expands and the coordination of an increasing number of mobility solutions comes into play, the complexity can be such that new decentralized solutions are required. In this work in progress paper we discuss the role of blockchain technology for enabling seamless mobility for MaaS.

In this paper, we study the effectiveness of personalized persuasive interventions to change urban travelers’ mobility behavior and nudge them towards more sustainable transport choices. More specifically, we embed a set of persuasive design elements in a route planning application and investigate how they affect users’ travel choices. The design elements take into consideration the style, the intensity, the target of persuasive interventions as well as users’ characteristics and the trip purpose. Our results show evidence that our proposed approach motivates users on a personal level to change their mobility behavior and make more sustainable choices. Furthermore, by personalizing the persuasive interventions while considering combinations of interventions styles (in our case messages and visualizations) as well as adjusting the intensity of persuasive interventions according to the trip purpose and the transport modes of the routes which the user is nudged to follow, the effects of the persuasive interventions can be increased.

Recent approaches on tackling the problem of sustainable transportation involve persuasive systems and applications. These systems focus on changing citizens’ behavior towards adopting transportation habits that rely more on the use of public transportation, bicycles and walking and less on private cars. A main drawback of existing applications is the limited use or lack of personalization aspects that consider differences in users’ susceptibility to persuasive strategies. In this paper, we explore two user traits that can be used for personalizing the persuasive strategies applied to end users: personality and mobility type. More specifically, we present the results of a study where we examined the perceived persuadability of eight persuasive strategies on users of five personality types and three mobility types.

We implemented a recommendation system that presents persuasive messages to commuters using a route planning application. Our aim is to nudge users towards following routes that are environmentally friendly with lower CO2 emissions than those they usually take. Our implementation leverages contextual information and transportation user profiles while the messages are defined based on a set of persuasive strategies. The recommender is integrated in a route planning application for android based smartphones and was used in a trial in the cities of Vienna and Dublin. Users' qualitative feedback showed that the feature was found interesting and provided insights for future improvements.

Communities within corporations can significantly contribute to innovation and the idea management process. The collection of ideas and aggregation of evaluation information from a community is a demanding task that requires the use of special methods. In this paper we explore the use of information aggregation markets (IAMs) in the fuzzy front-end of innovation. Furthermore, we identify and define a type of facilitation which we name 'market facilitation' and we assess its role in new idea generation at different levels of restrictiveness. The empirical results of a laboratory experiment indicate that IAMs enable the acquisition of more ideas than traditional brainstorming and of similar quality. Market facilitation forms entailing different levels of restrictiveness are found to affect the number and the quality of ideas acquired. As the level of market facilitation restrictiveness decreases, the number of acquired ideas increases and their quality deteriorates. To practitioners, our study provides empirical evidence on the advantages of IAMs over traditional electronic brainstorming as an alternative method for idea generation and evaluation.

Agents can exploit user-generated content available in social media by extracting user sentiments and assessments and using them to make informed transactions on the market.

In modern urban lifestyles the consumption of prepared food in restaurants and fast foods is increasing constantly and is becoming a habit among citizens. One side effect of this way of life concerns the increase of the Body Mass Index because citizens tend to choose more foods with high amounts of energy, fats and saturated fats and less healthy foods such as vegetables and fruits. In this paper we describe an intelligent application called DISYS that aims to offer personalized information to consumers when visiting a restaurant in order to support them to select a dish or a meal that is within their preferences but at the same time is healthy for them and in line with their dietary targets and their health conditions. DISYS is operated by restaurant managers who configure the meals and dishes their establishment offers, as well as the nutritional characteristics of each meal. Moreover, dieticians can support their customers by analysing their actions and interactions with the DISYS application with respect to food consumption habits.

Besides other popular strategies, such as feedback and (social) comparisons, challenges have been proposed and used to influence people’s behavior towards a targeted goal. However, only very limited data on the effectiveness of such approaches and how to best design them is available yet. In this work we report the findings of a two months field study analyzing the effectiveness and perception of challenges in the context of influencing personal mobility. Individual and collaborative approaches towards challenges were studied, and specific focus was laid on what aspect makes users willing to participate in these challenges. Our findings suggest that both individual and collaborative challenges have the potential to sustain the interest of users in using behavior change support systems, that collaborative and individual challenges seem to not attract different types of users, that individual challenges in general are preferred, and that challenges are only a useful means for a subset of users. Also, ICT-competence seems to be an important aspect of being willing to participate in electronically organized challenges.

The demo paper describes the Creative User Centric Inspirational Search, which aims to leverage user inspiration in information seeking activities. CRUISE is an interactive exploratory search tool that combines diversification of content and sources with a user interface design that visualizes cues from the social chatter generated with microblogging services such as Twitter and lets users interactively explore the available information space. The tool is based on the observation that users often use the social chatter to follow links and initiate information seeking activities which can lead to unexpected discoveries which can in turn inspire them.

In creative tasks, the user expects to acquire holistic information, to explore the space of available information and to come up with diverse views before converging to a solution for the creative task. We hypothesize that the implicit use of social chatter in information seeking activities can enhance the potential for novel, diverse and unexpected encounters which can in turn inspire users. We present an interactive exploratory search tool that combines diversification of content and sources with a user interface design that visualises cues from the social chatter generated with microblogging services such as Twitter and lets users interactively explore the available information space. A task-based user study comparing our system to a query-based baseline indicates that our system significantly improves inspirational discoveries by providing access to more interesting, novel and unexpected information.

In order to predict user behaviour recommender systems generate views of the world according to expressed and known user preferences resulting in 'filter bubbles'. This kind of bubbles generally help users to easily identify objects they like. However, it is becoming increasingly difficult for users to escape their personalized world and change their perspectives especially in domains such as music. In this work we present a methodology and related system that allows users to initiate explorations of music genres by taking a gradual path towards the desired genre while viewing the preferences of other users. The proposed methodology is based on identifying 'latent genres' and using user preference graphs for detecting optimal paths towards a selected target latent genre. In this process we generate suggestions of artists a user should listen to, aiming towards serendipitous and novel encounters. We have implemented our approach in a music recommendation system and evaluated it with encouraging results.

Serendipity, the process of making fortunate discoveries for which someone was not looking for, can play a crucial role in leveraging creativity in learning [1]. Serendipity enables creative connections to develop while it can have a role in revealing hidden connections or "hidden analogies", especially in a social context such as in most learning processes [2]. The results of a chance encounter can result in new ideas relevant to the learner's previous knowledge [3]. In previous work, we have reviewed the related literature and identified five enabling factors for serendipity [4]: diversity, unexpectedness or novelty, personalization, visualization, and social interaction. The aim of this paper is to construct an architectural framework based on the aforementioned factors that can be used as a guide in the development of information seeking systems aiming to leverage serendipity in learning.

Recommender Systems have emerged as a way to tackle the overload of information reflected in the increasing volume of information artefacts in the web and elsewhere. Recommender Systems analyse existing information on the user activities in order to estimate future preferences. However, in real life situations, different types of information can be found and their interpretation can vary as well. Each recommender system implements a different approach for utilizing the known information and predicting the user preferences. A problem is that of blending the recommendations in an adaptive, intuitive way while performing better than base recommenders. In this work we propose an approach based on information markets for the fusion of recommender systems. Information Markets have unique characteristics that make them suitable building blocks for ensemble recommenders. We evaluate our approach with the Movielens and Netflix datasets and discuss the results of our experiments.

Collaborative systems and methods are used within corporate environments to support innovation and management of new ideas. The aggregation of innovation-related information from a community of users is a non-trivial task that requires the use of specialized collaborative systems and methods. In this paper we explore the use of Prediction Markets for community-based idea management and present IDEM, a software system that is used for generating and evaluating new ideas utilizing the concept of Prediction Markets. In addition to trading, IDEM supports users submit new ideas, rate and comment on them. Academic experiments and industrial pilots reveal the perceived usefulness of the system.

Several methods and software tools exist for evaluating new ideas in corporate environments, which provide significant help to decision makers when selecting the most promising suggestions for innovation. In this paper, we identify five criteria for assessing idea evaluation methods (number and type of ideas, number and motivation of evaluators, type of feedback) and we use them to review prominent methods (multi-criteria analysis, statistical analysis, qualitative research, rapid prototyping, feasibility studies and Information Aggregation Markets). We identify Information Aggregation Markets as a prominent new method and we present a novel system that implements the concept of Information Aggregation Markets as well as early results from its evaluation.

Collaborative systems and methods are used in companies to support innovation and management of new ideas. The aggregation of innovation-related information from a community of users is a non-trivial task that requires the use of specialized collaborative systems and methods. In this paper we explore the use of information aggregation markets (IAMs) for community-based idea management and present IDeM, a novel software system that is used for generating and evaluating new ideas utilizing the concept of IAMs.

In recent years, persuasive interventions for inducing sustainable mobility behaviours have become an active research field. This review paper systematically analyses existing approaches and prototype systems as well as field studies and describes and classifies the persuasive strategies used for changing behaviours in the domain of mobility and transport. We provide a review of 44 papers on persuasive technology for sustainable transportation aiming to (i) answer important questions regarding the effectiveness of persuasive technology for changing mobility behaviours, (ii) summarize and highlight trends in the technology design, research methods, strategies and theories, (iii) uncover limitations of existing approaches and applications, and (iv) suggest directions for future research.

The continuing growth of urbanisation poses a real threat to the operation of transportation services in large metropolitan areas around the world. As a response, several initiatives that promote public transport and active travelling have emerged in the last few years. Mobility as a Service (MaaS) is one such initiative with the main goal being the provision of a holistic urban mobility solution through a single interface, the MaaS operator. The successful implementation of MaaS requires the support of a technology platform for travellers to fully benefit from the offered transport services. A central component of such a platform is a journey planner with the ability to provide trip options that efficiently integrate the different modes included in a MaaS scheme. This paper presents a heuristic that implements a scenario-based journey planner for users of MaaS. The proposed heuristic provides routes composed of different modes including private cars, public transport, bike-sharing, car-sharing and ride-hailing. The methodological approach for the generation of journeys is explained and its implementation using a microservices architecture is presented. The implemented system was trialled in two European cities and the analysis of user satisfaction results reveal good overall performance.