Deploying Heuristics on Planning and Design in the Creation of Smart Cities

Abstract

Big data analytics provides support and insight in dealing with complex operational problems in cities. Heuristics can support problem solvers and decision makers address complex problems in various settings. In this paper, we argue that embedding big data with heuristics can enable users satisfice on addressing complex problems. The research draws from Volkema’s (1983) heuristics on problem solving in planning and design: problem expansion and problem reduction. A multi-source approach – secondary data and in-depth semi-structured interviews and participant observations from two smart city initiatives in the United Kingdom– formed the core the data collection. We develop an empirically driven qualitative heuristic on optimising big data for complex problem solving in the creation of smart cities. We argue that problem solving in cities can deploy big data to carry out problem expansion and problem reduction as means of making sense of problems and ultimately arriving at solutions.