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Effective waste management (WM) is one of the most significant environmental problems and a major challenge for any large city. While there are numerous studies describing individual aspects of WM systems in specific contexts, there is no general approach that would unite all the accumulated results into a single framework. The aim of this study is 1) to explore how to develop an IoT-based smart waste management (SWM) system that improves the waste management processes of a city and 2) to develop an SWM system improvement and evaluation decision support framework (DSF), that could provide recommendations about WM implementation in cities, based on the city objectives, the characteristics of the city and the current WM status in the city. To develop the SWM DSF, we used data obtained from 173 primary studies of a literature review, surveys performed in three different cities, and ideas from waste management hackathons. The developed DSF includes five parts 1) Framework guidelines, 2) Context setting, 3) Goal setting, 4) Challenges to be tackled, and 5) Recommendations (provides the recommendations for achieving the set goals and solving problems, taking into account the specific context of the city). The SWM DSF has been tested and evaluated in 2 stages of testing: 1) by researchers at a university, 2) by a panel of experts in the field of SWM and decision support systems, including professors from leading universities of Finland and representatives of companies specializing in SWM. The test results showed the plausibility and usability of the framework. The developed SWM DSF can be used by representatives of the city …