Seamless design is an important dogma of dataism. Without unpredictable behaviour, however, there’s no data to retrieve. A wholly predictable future is just a continuous present, a tyranny of choices on offer.
MULTIFILE
Air transportation has grown in an unexpected way during last decades and is expected to increase even more in the next years. Traffic growth tendencies forecast an expansion in the demand and greater aviation connectivity, but also higher workload to the different airspace users, especially for airport and services. Therefore, it is essential to employ strategies designed to use efficiently valuable corporate resource. Airport authorities around the world are investing in large capital projects, including new or improved runways, terminal expansions, and entirely new airports. However, this effort is sometimes limited due to their geographic location. In this work, two main objectives are pursued: first, to highlight the importance of the industry by exposing the current situation and future trends all over the world focusing in the Mexican industry; and second, to introduce a simulation model which can be used as a decision making tool for the upcoming demand. The analysis of the scenarios illustrates how to develop strategies to cope with the different airspace user's needs.
MULTIFILE
Sensors in offices mainly measure environmental data, missing qualitative insights into office workers’ perceptions. This opens the opportunity for active individual participation in data collection. To promote reflection on office well-being while overcoming experience sampling challenges in terms of privacy, notification, and display overload, and in-the-moment data collection, we developed Click-IO. Click-IO is a tangible, privacy-sensitive, mobile experience sampling tool that collects contextual information. We evaluated Click-IO for 20-days. The system enabled real-time reflections for office workers, promoting self-awareness of their environment and well-being. Its non-digital design ensured privacy-sensitive feedback collection, while its mobility facilitated in-the-moment feedback. Based on our findings, we identify design recommendations for the evelopment of mobile experience sampling tools. Moreover, the integration of contextual data with environmental sensor data presented a more comprehensive understanding of individuals’ experiences. This research contributes to the development of experience sampling tools and sensor integration for understanding office well-being.