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 analyzes the dynamic relationships between tourism, gross domestic product (GDP) per capita, exports, imports, and carbon dioxide (CO₂) emissions in five South Asian countries. A VAR-based Granger causality test is performed with time series data from Bangladesh, India, Nepal, Pakistan, and Sri Lanka. According to the results, both bidirectional and unidirectional relationships among tourism, economic growth, and carbon emissions are investigated. Specifically, tourism significantly impacts GDP per capita in Pakistan, Sri Lanka, and Nepal, yet it has no effect in Bangladesh or India. However, the GDP per capita shows a unidirectional relationship with tourism in Bangladesh and India. The unidirectional causal relationship from exports and imports to tourism in the context of India and a bidirectional relationship in the case of Nepal. In Pakistan, it is observed that exports have a one-way influence on tourism. The result of the panel Granger test shows a significant causal association between tourism, economic growth, and trade (import and export) in five South Asian economies. Particularly, there is a bidirectional causal relationship between GDP per capita and tourism, and a significant unidirectional causal relationship from CO₂ emissions, exports, and imports to tourism is explored. The findings of this study are helpful for tourism stakeholders and policymakers in the region to formulate more sustainable and effective tourism strategies.

The augmentation of firm performance via customer concentration is particularly indispensable for organizational evolution. Both trade credit financing and financing constraints play pivotal roles in the nexus between customer concentration and performance. This research constructs a moderated mediation model to rigorously investigate the impact of customer concentration on firm performance, positing trade credit financing as the mediating variable and financing constraints as the moderating variable. The relevant hypotheses are evaluated empirically using panel data compiled from listed manufacturing firms in China over the period 2013–2020, yielding 8 firm-year observations. The empirical outcomes denote that customer concentration exerts a positive influence on firm performance, albeit having a negative impact on trade credit financing. Trade credit financing serves as a partial mediator in the relationship between customer concentration and manufacturing firm performance. Financing constraints are found to positively moderate the mediating role of trade credit financing in the relationship between customer concentration and firm performance. This research broadens the understanding of the implications of customer relationships on trade credit financing and performance, thereby enriching the knowledge base for managing a firm’s financing channels more effectively.

Fire accidents are one of the serious security threats facing the metro, and the accurate determination of the index system and weights for fire assessment in underground stations is the key to conducting fire hazard assessment. Among them, the type and quantity of baggage, which varies with the number of passengers, is an important factor affecting the fire hazard assessment. This study is based on the combination of subjective and objective AHP (Analytic Hierarchy Process) with the available Particle Swarm Optimisation algorithm PSO (Particle Swarm Optimization) and the perfect CRITIC (Criteria Importance Through Intercriteria Correlation) empowered fuzzy evaluation method on the metro station fire hazard toughness indicator system and its weights were determined, and a fuzzy comprehensive evaluation model of metro station safety toughness under the influence of baggage was constructed. The practical application proves that the method provides a new perspective for the fire risk assessment of underground stations, and also provides a theoretical basis for the prevention and control of mobile fire load hazards in underground stations.