###### Abstract  
This paper presents a new decision support method aimed at prioritizing processing for an intelligent road problem reporting service. The proposed method uses advanced georeferencing technology to extract the longitude and latitude coordinates in the metadata of photos taken with the smartphone application to capture the complaint scene. This method not only maps out the processing times, but also applies a spatiotemporal clustering technique to link the complaint types and locations with the actual complaint processing times. A validation study of the frequency of reported locations per priority reveals that the complaint-processing prioritization method developed in this study aligns realistically with actual field complaint processing. Furthermore, recognizing the significance of location in processing complaints, the georeferencing technique appears suitable for identifying complaint locations for each report and incorporating this into the decision-making framework.  
decision-making support model; clustering; public complaint management; road problem reporting system +
Footnote †: journal: Applied sciences  
0000-0001-6000-0000-0000-0000-0000-0000-0000-0000-00000-0000-00000-00000-00000-00000-00000-00000-00000-000000-00000-00000-000000-000000  
severity measurements, it does not adequately consider the geographic locations of the complaints. The severity assigned to potholes may vary significantly depending on their locations, i.e., a pothole on a busy highway lane poses a different level of risk compared to one on a less traveled local road shoulder, yet the previous method does not differentiate based on such criteria.  
This study addresses the need to factor in geographic data by utilizing geotagging technology, a cutting-edge tool that records the longitude and latitude coordinates in the metadata of photos taken with smartphones. This allows for identifying complaint locations such as roads, buildings, neighborhood facilities, social overhead capital (SOC) facilities, and railways. The analysis of complaints processed in 2021 and 2022 utilizes these coordinates to further classify road-related complaints according to a detailed road hierarchy: highway/trunk road, general national road, local road, roads in city/county/district, residential road/back road, pedestrian road, farm road/forest road, service road, and unclassified road. By linking the complaint types and locations with the actual outcomes of complaint processing, this study not only maps out the processing times, but also applies clustering techniques to the data. This methodology facilitates the formulation of recommendations for complaint prioritization based on the understanding of complaint processing times (CPT) across different types of locations.  
This paper is organized as follows: Following the introduction, the next section addresses a comprehensive review of relevant research efforts. The section of analysis presents an overview of the complaint data, providing both descriptive and comparative analyses to identify factors affecting the priorities of complaint processing. The details of the decision-making support model development are presented with the model results in the next section, followed by conclusions and recommendations.