Information is an experience good, meaning that its value emerges upon use and varies based on individual perceptions. Augmented reality (AR) is a technology designed to deliver immersive informational experiences. This study investigates the impact of AR on the perceived value of information by people experiencing information as consumers or producers. Using Google Maps, we developed an AR mobile map called Tour-It-Yourself (TIY) for city navigation. The TIY app facilitates content consumption and production around local points of interest engagingly and interactively. We discuss the development of the research tool and results from two user studies (N = 37 teenagers and N = 51 students, respectively). Further, we highlight the economic valuation aspect by examining the effects of AR on Willingness-to-Pay and Willingness-to-Accept payment for information. The results indicate a significant main effect of participant experience (consumer/producer) and AR technology on the perceived evaluation of information. Moreover, the addition of AR technology to information improves knowledge regarding points of interest for producers. These findings contribute to our understanding of how AR shapes information value perception and have implications for designing interactive location-based information systems, benefiting tourism, education, and business, as well as fostering a sense of belonging in cities.

As basketball is one of the crowd's favorite invasion games, methods are being developed to enhance players' performance as technology improves. Recording large parts of training significantly reduces subjective training assessment compared to objective aspects. In this paper, basketball players and coaches use a mobile application based on image processing for achievements, measuring shooting the basket from different positions on the court and displaying feedback. The shooting technique and the percentage of success are measured using an algorithm that identifies the angle of the shot to the basket. The system monitors players' knowledge of results during training using one mobile phone camera. The paper describes the architecture and design of the mobile computing and application: Pre-training (define goals based on past performance and level of training difficulty), during training (data collection and compatible camera), and post-training (analysis and visualization of results). Finally, the paper discusses validation and implications.