Use of data analytics applications by Dutch municipalities to support policy making on socio-economic aspects of the local energy transition

Abstract

Introduction: Municipalities play a crucial role in operationalizing and realizing the energy transition and are increasingly adopting data analytics applications to enhance their data-driven policy making (DDPM) process. However, there remains a gap in understanding how socio-economic aspects in data analytics applications informs policy and how knowledge from both data analysts and policy makers is integrated in energy transition policy making. To address these gaps the aim of this study is to analyse the use of data analytics applications that support policy making on socio-economic aspects of the local energy transition, taking into account the integration of knowledge from both data analysts and policy makers. Theory: The framework of H. van der Voort et al. (2021) and the associated activities were utilized to analyse how the knowledge integration from data analysts and policy makers in the process of DDPM. Methods: To address the abovementioned gaps, a multiple-case study was conducted of six Dutch municipalities, where two connected data analytics applications used for energy policy making were investigated in each case. The cases were compared using first a within-case analysis and then a cross-case analysis. Results: The extensive collaboration between data analysts and policy makers throughout the process of DDPM enhances their knowledge integration. The knowledge derived from the applications facilitate and inform policy makers by monitoring the energy transition initiatives, and aids in the formulation of effective policies. In addition, socio-economic aspects, such as energy poverty, are increasingly considered in the data analytics applications, enabling policy makers to make informed decisions for prioritization of neighbourhoods for implementing natural gas-free heating, and more targeted measures. However, implementing data analytics applications on socio-economic aspects encounters challenges such as acquiring accurate socio-economic data, integrating social and technical data in a single data analytics application, and privacy concerns. Discussion/Conclusion: It is emphasized that data analytics applications including socio-economic aspects, offer a powerful tool for Dutch municipalities in their pursuit of sustainable energy transitions. By enhancing the knowledge integration from both data analysts and policy makers, utilizing the created knowledge of data analytics applications on socio-economic aspects of the energy transition, and addressing the challenges involved, municipalities can make more informed decisions and promote socio-economic equity, and just transitions. Future research directions in this field are conducting structured literature review and more case studies that include the provincial and national level of government to generate a wider geographical scope of the research.