With the emergence of Human Smart Cities, the involvement and participation of citizens in city improvement projects has acquired the greatest relevance. To empower citizen participation, the implementation of co-production mechanisms that provide a balanced, equal, and transparent relationship between citizens and public sector in an evolving digital era is of utmost importance. This research proposes a framework to structure and facilitate collaboration between citizens and the public administration to solve problems linked to the city ecosystem, based on the concept and components of co-production. In our framework, the main point of contact between the public sector and citizens lies in different types of collaborative events and crowdsourcing campaigns. The opinions of citizens with respect to some details of the implementation of the proposed framework are also collected and analyzed.

There are many perspectives and conceptions about “Smart Cities”. One thing they have in common is the enrichment of city functions through the use of information technologies. However, often smart solutions are developed following a “top-down” approach [7] and besides, it seems that prioritizing efficiency and sustainability are not often the best way to address the needs of the citizens [11]. Thus, human-centered methods are necessary towards developing solutions that truly answer to the needs of the people. The scope of this tutorial is that of introducing smart cities (e.g., [1], [3], [4], [8], [10]) and ways of making them smarter - especially from the perspective of citizens - with a human-centered [9] approach. Methods for collecting people's opinions and data regarding the city ecosystem, as well as guidelines on how to use this information to go from raw data to useful, concrete and human-centered solutions, are fundamental for improving the livability of a city. In this tutorial, some of these methods will be presented, enriched by various practical examples and some basic information about smart cities. The participants of the tutorial will be able to test some of the proposed methods in interactive and hands-on sessions.

This case study introduces a new investment technique approach to make investment decisions in the stock market with minimum risk and reduced potential human intuition bias. The document introduces a fuzzy recommender system (FRS) and discusses its impact in generating positive revenue compared with decisions of real investors. The theoretical background, design and implementation of the FRS in a stock exchange platform are properly presented. The performance is evaluated with respect to the strategies used by real investors in weekly investment rounds, considering three different investment scenarios: conservative, explorer and adventurer. Finally, a proper discussion about the results of the investment via the stock exchange platform, where the FRS performed in the top three of the list of best investors during the evaluation period and improvement opportunity areas is presented.