Data-driven decision support system for electric vehicle workplace charging

This repository contains the source code and supplementary materials for the paper “Navigating the Sustainable Mobility Transition: Designing a Data-Driven Decision Support System for Planning and Operating Electric Vehicle Workplace Charging Infrastructure” (submitted to Decision Support Systems). The open-source web application implements a decision support system (DSS) tailored to firms planning and operating EV workplace charging infrastructure. Using firm-specific electricity load data, shift patterns, EV adoption scenarios, and optimisation algorithms, the DSS quantifies trade-offs between three key objectives: (i) peak demand minimisation, (ii) cost reduction, and (iii) carbon emissions mitigation. The DSS was developed following a Design Science Research approach and iteratively refined over three design cycles. It was tested with eight medium-to-large German firms, using real-world electricity consumption data. Semi-structured interviews (n = 8 firms) revealed that the DSS helped executives surface trade-offs, foster cross-departmental dialogue, and shift their focus from short-term operational concerns to long-term strategic planning. Usability testing with the System Usability Scale (SUS) (n = 11 respondents) confirmed high adoption potential, with an overall score of 81.8 (‘excellent’). Supplementary material: Source code of the open-source web application (Streamlit-based interface, Python optimisation back-end) Interview quotes (Excel file, anonymised, structured by themes) Full System Usability Scale (SUS) calculations (Excel file) Interactive demo available at: https://ev-workplace-charging.streamlit.app/