The City Game Fit: The Reverse Engineering of Urban Games

Abstract

With the increasing mobility and connectivity of technological devices in smart cities, games are also used to address urban challenges like citizenship or equality. In my thesis, I argue that the design of many of these game solutions does not fit the challenge they try to address. For example, Pokémon Go ultimately became more a social facilitator than a pure for-profit app, while Geocaching for education purposes has proven ineffective. In order to assess the efficacy of the design of these solutions and suggest future improvements, I introduce an interdisciplinary method called ‘The Action Space Analysis’ which can be used to measure and judge how well the design fits with a challenge. First, I suggest a perspective on game design focused on the acceptance that whatever possible actions are contained in the game, some player will play them. Secondly, the city challenges are understood as the pursuit of a city model, an understanding of how you want the city to be. The action space analysis takes a game design and uncovers all possible actions of the game to check and score how well these actions fit the city model pursued. This checks how present the possibility is of players performing the desired actions from the city model. I check this for Geocaching, Ontdek Overvecht, Cities: Skylines, and Pokémon Go. The action space analysis works as validation method that allows designers to improve their games, critics to analyse city solutions better, and municipalities to pass informed judgment on suggested solutions.