University of Twente Student Theses
Development of a Decision Support System for Modelling the Spatial Impact of Interrelated Socio-Technical Challenges
Risseeuw, Frank (2024) Development of a Decision Support System for Modelling the Spatial Impact of Interrelated Socio-Technical Challenges.
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| Abstract: | Dutch municipalities are facing several transition challenges that have large impacts on the infrastructures and public spaces, both above and below ground. Think of building and renovating sustainable houses, upgrading the electricity grid, deploying alternative heating solutions, creating retention areas for extreme rainfall events, and creating charging networks for mobility transitions. All these transitions have a major impact on public space and need to be executed swiftly to attain sustainable development goals (SDGs). However, they are instigated and managed by different policymaking departments in municipalities. Also, there is a lack of understanding of how those distinctive challenges affect the Urban Underground Space (UUS). Let alone that decision makers within the different public and private organisations, like municipalities and grid operators, have a holistic overview of all challenges (i.e. insight into the combined spatial impact of the challenges and their interfaces and conflicts). Because of this lack of insight, these infrastructure owners are unable to prioritise the work that needs to be executed. Instead of assigning physical space on a first-come-fist-serve basis, it is desired that informed trade-offs between spatial claims of challenges can be made. Literature suggests that the planning of USS should be carefully integrated into a city master plan. (Kuchler, Craig-Thompson, Alofe, & Tryggvason, 2024; von der Tann, Sterling, Zhou, & Metje, 2020). This strategic and integrated planning process depends on several meta-parameters (e.g. population density, GDP, land price) and comes with a lot of uncertainties (Lin, Zou, & Deng, 2023; Peng & Peng, 2018a, 2018b). For example, it is uncertain what additional physical space will be needed to fulfil the future needs of residents. This makes it hard to predict spatial claims and therefore plan the UUS. On an operational level, the uncertainties of spatial claims have been minimized. However, the fragmentation of information and the current way of siloed planning and execution of civil projects hampers an integrated planning process as well (Hehua Zhu, 2017; Kuchler et al., 2024). Currently, no mid-term, tactical-level, physical space modelling method exists. The goal of this study therefore was to develop a decision support system (DSS) that models the spatial impact of interrelated sectoral challenges and supports different types of decision-makers in understanding and jointly prioritising distinct scenarios. To demonstrate the value of this tool, three sectoral challenges have been selected for this study: electrification, heat transition, and climate adaptation. Following a design science research (DSR) methodology a prototype of this tool was developed. By interviewing experts on the sectoral challenges, combined with analysing policy documentation and literature, an architecture for the developed DSS was created. Then, the rules for defining the spatial claims of the three STCs were drafted. This was implemented in ArcGIS using Python to create a tool. Based on inputted data from the decision makers, it models various scenarios that capture the use of overground and underground space on a neighbourhood level. Overground space is visualized using polygon objects, while the use of underground space is conceptualized in a metric, which expresses the volume of used space per surface area in m3 /m2 . The tool was evaluated during a two-hour workshop with experts from each STC. The session aimed to measure the ‘value’ of the tool i.e. to what extent is the developed tool valuable for aiding the decision-makers in making decisions. For this, a demonstration was given presenting several modelled scenarios for the city centre of Enschede, from which the results were discussed. Also, a survey was conducted focusing on three evaluation criteria (i.e. information quality, perceived usefulness and decision support satisfaction). The decision-makers find the tool insightful in several ways. First, it shows them the complexity of the combined challenges by showing the (im)possibilities of different scenarios. Second, it is insightful for the decision-makers that spatial conditionality is an important factor to take into account for prioritising. All in all, the tool aids in the joint understanding of the problem domain by the different municipal clients and ‘ignites’ the conversation among them on prioritising different solution alternatives. Although the developed tool does gain insight into the complexity of the problem domain, it does not provide enough comprehensiveness to be used for prioritisation and thus decision-making. For this, additional data and decision-making factors should be included, STC models should be more accurate and visualisations should be more meaningful. Also, the organisation of an integrated planning process should be improved. A tool as developed should be embedded into this process. This means that regular alignment meetings should take place in which various modelled options are presented. Based on this, the municipal clients and other decision-makers can discuss them. It would be valuable for such a process as this would be standardised for many municipalities using the same tool to learn from one another. |
| Item Type: | Essay (Master) |
| Clients: | Gemeente Enschede, Nederland |
| Faculty: | ET: Engineering Technology |
| Subject: | 56 civil engineering |
| Programme: | Construction Management and Engineering MSc (60337) |
| Link to this item: | https://purl.utwente.nl/essays/104735 |
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