Geo-Analytics of Citizen-Government Interaction: The Integration of Spatial Data Mining, Volunteered Geographic Information (VGI), And Geovisualization To Explore Non-emergency Requests in the State of Kuwait
MetadataShow full metadata
The rapid and continuous growth of population requires simultaneous provision of public services (or commons) at high spatial and temporal scales. In addition to the commons provision, governments are ought to maintain the commons to be at high quality standards. However, the rapid consumption of the urban commons, with the urban expansion in space, represented a challenge to local governments to sustain the provided services. Consequently, low quality services are expected to be detected by the community. Building on the sense of owning the space, or territoriality, citizens are interacting with local governments to report about the low-quality commons. In response, governments have established a centralized system for such reports, or non-emergency requests, and it was initiated by the U.S. government in 1996 known as the 311 system. Such centrality facilitated the process to report a complaint with no need of prior knowledge on whom and how to submit the complaint. However, such system does not exist globally and in such cases, citizens should obtain prior knowledge on whom they should contact to submit a complaint. An example would be the State of Kuwait.
In Kuwait, citizen complaints are received by the responsible agencies individually. Building on the territoriality theory, a group of volunteers leveraged the use of Social Media (SM) technologies to establish a centralized point of communication for Kuwait users to share their complaints with responsible agencies. Through their SM account, known as @Q8needsyou in Instagram, citizen complaints could be collected, organized, processed, and analysed to explore the spatiotemporal nature of the citizen-government interaction in Kuwait, which represents a contribution to the body of knowledge in such part of the world. The overall objectives of this dissertation where to: 1) design a structured relational database for citizen complaints, 2) identify the spatiotemporal cluster of citizen complaints at the global and temporal level, 3) identify the socioeconomic characteristics that influence the complaints volume and governmental responsiveness to complaints, and 4) explore the agencies interconnectivity nature through geovisualization. The data collected covered the year 2019.
In Chapter 4, the results of the spatiotemporal pattern analysis revealed several insights. The global pattern analysis results using Averaged Nearest Neighbor (ANN) have shown that complaints exhibited a clustered pattern during 2019 and during each season. Also, the same pattern was found when analyzing the top two complaint types. The results of the local pattern analysis using the Getis Ord, or Gi*, statistics at the neighborhood level revealed several findings. It was found that there are areas that exhibited high clusters of citizen complaints during 2019, and the high clusters vary spatially during each season. The same findings were identified when applying the analysis for the top two complaint types.
In Chapter 5, Factor Analysis (FA) and Multiple Regression (MR) were implemented to identify the significant socioeconomic factors that contributes to citizen complaints volume and governmental responsiveness (rate and response time). The findings, regarding complaints volume, were consistent with the literature where higher married population and higher education level tends to have more propensity to submit complaints. Regarding governmental responsiveness, factors such as population density, education level, and male population had a significant positive influence on responsiveness rate and time.
Finally, in Chapter 6 bivariate mapping methods have shown that gender digital participation exhibited spatial variation in 2019 and during each season. Also, the multivariate mapping approach revealed multiple insights were citizen-government interaction had varying patterns at the neighborhood level. Finally, using geovisualization to explore the agency interconnectivity revealed that connections among agencies, and the magnitude of the connection, varies at the governorate level.
Building on the findings of this dissertation, the necessity to establish a centralized system for citizen complaints gain its importance through time. The system should rely on the traditional (or authoritative) and digital media sources of requests to leverage the awareness on where and when to maintain the urban commons.