The purpose of this study is to investigate customer satisfaction with quality of service known as SERVQUAL improvement or service quality competitiveness in emerging markets. Using Indonesian government medical care as an example the author examines the satisfaction of patients. Information and data were collected through a survey of 399 BPJS users in Indonesia. All data were analyzed using Smart PLS. This study demonstrates that there is a negative value associated with the five-dimensional gap. As a result, the care provided to BPJS patients is below par. Specifically, the sensitivity dimension has the largest disparity at 0.15, while the physical evidence dimension has the smallest at 0.49. In order to raise the level of service provided, it may be necessary to take direct measures or examine tangible evidence. This study develops the relationship between different quality service models. There appears to be a substantial increase in the body of literature in the area of service quality, allowing for constant updates and the incorporation of the lessons learned from the experiences of the departed. These revised guidelines are intended to aid SERVQUAL study participants. The study gives practical support to academics and practitioners in directing service quality improvement through the use of data collected from large-scale surveys of patients and medical professionals as doctors in Indonesia.

This study delves into the evolving landscape of smart city development in Kazakhstan, a domain gaining increasing relevance in the context of urban modernization and digital transformation. The research is anchored in the quest to understand how specific technological factors influence the formation of smart cities within the region. To this end, the study adopts a Spatial Autoregressive Model (SAR) as its core analytical tool, leveraging data on server density, cloud service usage, and electronic invoicing practices across various Kazakhstani cities. The crux of the research revolves around assessing the impact of these selected technological variables on the smart city development process. The SAR model’s application facilitates a nuanced understanding of the spatial dynamics at play, offering insights into how these factors vary in influence across different urban areas. A key finding of this investigation is the significant positive correlation between the adoption of electronic invoicing and smart city development, a result that stands in contrast to the relatively insignificant impact of server density and cloud service usage. The conclusion drawn from these findings underscores the pivotal role of digital administrative processes, particularly electronic invoicing, in driving the smart city agenda in Kazakhstan. This insight not only contributes to the academic discourse on smart cities but also holds practical implications for policymakers and urban planners. It suggests a strategic shift towards prioritizing digital administrative innovations over mere infrastructural or technological upgrades. The study’s outcomes are poised to guide future smart city initiatives in Kazakhstan and offer a reference point for similar emerging economies embarking on their smart city journeys.

This study examines the spatial distribution and structure of traffic offences in the Northern Great Plain region. The research is unique in that it examines a specific area through the lens of geography. The research shows and demonstrates that the research area of crime and transport geography is much broader than previous researches has shown. At the beginning of the study, the authors clarified the conceptual framework, as the terms “violation” and “offence” are often confused even in technical materials. The research shows which routes are the most frequently used by road hauliers in the regions under study and what type of checks have been carried out on these routes by the Transport Authorities of the Government Offices. The type of administrative penalty detected and the nationality breakdown of the infringements are described. The study typifies the infringements involving administrative fines by nationality category.