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 conducts a systematic literature review to analyze the integration of artificial intelligence (AI) within business excellence frameworks. An analysis of the findings in the reviewed articles yielded five major themes: AI technologies and intelligent systems; impact of AI on business operations, strategies, and models; AI-driven decision-making in infrastructure and policy contexts; new forms of innovation and competitiveness; and the impact of AI on organizational performance and value creation in infrastructure projects. The findings provide a comprehensive understanding of how AI can be integrated into organizational excellence emerged frameworks to address challenges in infrastructure governance, and sustainable development. Key questions addressed include: how AI affects consumer behavior and marketing strategies. What AI’s capabilities for businesses, especially marketing and digital strategies? How can organizations address the drivers and barriers to help make better use of AI in these business operations? Should organizations even do anything with these insights? These questions and more will be tackled throughout this discussion. This paper attempts to derive a comprehensive conceptual framework from several fields of human resources, operational excellence, and digital transformation, that can help guide organizations and policymakers in embedding AI into infrastructure and development initiatives. This framework will help practitioners navigate the complexities of AI integration, ensuring profitability and sustainable growth in a highly competitive landscape. By bridging the gap between AI technologies and development-related policy initiatives, this research contributes to the advancement of infrastructure governance, public management, and sustainable development.

Green Human Resource Management (HRM) is considered an emerging field of management that evaluates and ensures green performance and outcomes in organizations. In today’s dynamic business environment, work-life balance has become one of the key issues faced by many employees all over the world. Maintaining work-life balance is an issue increasingly recognized as of strategic importance to the organization and significance to employees. In doing so, the present study introduced independent and dependent variables to explain the underlying mechanisms of green HRM and work-life balance and its impact on employee performance. A total of 90 employees of the calibration services company have completed a set of questionnaires through Google Forms to provide data for the analysis. This study is using census method as one of the best probability sampling techniques to be used it’s a systematic method that collects and records the data about the members of the population and is suitable when the case-intensive study is required or the area is limited. This study has adopted the quantitative method in this research as the method allows the researcher to focus on the research. The data were analyzed through SPSS which facilitates descriptive statistics, correlation, and multiple regressions. Multiple regression analysis was used to test the hypotheses in this research. The findings showed that green HRM and work-life balance were the significant variables influencing employee performance in the study. In addition, the significance of the study included providing new knowledge from the theoretical perspective, obtaining a better understanding of the importance of green HRM and work-life balance from the perspective of employee performance, and contributing to the efforts made by the government to improve the probability of green culture in organizational and balancing professional life and family life employment of employees through policies from the perspective of the government. Lastly, recommendations for employers, employees, government, and future research are made to improve employee performance.

This research aims to analyze the relationship between dynamic capabilities and organizational performance, networking, and organizational performance, and to analyze the relationship between spiritual motivation variables and organizational performance. This research method is a quantitative survey. The respondent sampling technique used in this research is a purposive sampling technique, namely samples taken based on certain considerations. Responses to this study came from 567 Organization members of education. The data collection method used in this research is an online questionnaire which provides a written list of questions to respondents. The questionnaire was designed using a Likert scale of 1 to 7. In this study, the data was analyzed using the Partial Least Square (PLS) method with SmartPLS version 3.0 software. The stages of research data analysis are outer model testing, namely integrated validity and reliability testing, inner model testing, and hypothesis testing. The independent variables of this research are dynamic capabilities, collaborative networks, and spiritual motivation and the dependent variable is Organization performance. The results of this research are that dynamic capabilities have a significant and positive influence on organization performance, collaboration networks have a significant and positive influence on organization performance, and motivation has a significant and positive influence on organization performance. The managerial implication of the results of this research is that to improve the performance of educational organizations, managers can apply dynamic capability variables because dynamic variables have been proven to significantly encourage increased organizational performance. Organizations could improve the performance of educational organizations, and managers bu implement collaboration network variables because collaboration networks have been proven significantly can significantly encourage the increased performance of educational organizations. To improve the performance of educational organizations, managers can apply motivation variables because motivation variables have been proven to significantly encourage increased performance of educational organizations.

The coconut industry has deep historical and economic importance in Sri Lanka, but coconut palms are vulnerable to water stress exacerbated by environmental challenges. This study explored using Sunn hemp (Crotalaria juncea L.) in major coconut-growing soils in Sri Lanka to improve resilience to water stress. The study was conducted at the Coconut Research Institute of Sri Lanka to evaluate the growth of Sunn hemp in prominent coconut soils—gravel, loamy, and sandy—to determine its cover crop potential. Sunn hemp was planted in pots with the three soil types, arranged in a randomized, complete design with 48 replicates. Growth parameters like plant height, shoot/root dry weight, root length, and leaf area were measured at 2, 4, 6, and 8 weeks after planting. Soil type significantly impacted all growth parameters. After 8 weeks, sandy soil showed the highest plant height and root length, while loamy soil showed the highest shoot/root dry weight and leaf area, followed by sandy and gravel soils. Nitrogen content at 6 and 8 weeks was highest in loamy soil plants. In summary, Sunn hemp produces more biomass in sandy soils, while loamy soils promote greater nutrient accumulation and growth. This suggests the suitability of Sunn hemp as a cover crop across major coconut-growing soils in Sri Lanka, improving resilience.

ZnO nanostructures were obtained by electrodeposition on Ni foam, where graphene was previously grown by chemical vapor deposition (CVD). The resulting heterostructures were characterized by X-ray diffraction and SEM microscopy, and their potential application as a catalyst for the photodegradation of methylene blue (MB) was evaluated. The incorporation of graphene to the Ni substrate increases the amount of deposited ZnO at low potentials in comparison to bare Ni. SEM images show homogeneous growth of ZnO on Ni/G but not on bare Ni foam. A percent removal of almost 60% of MB was achieved by the Ni/G/ZnO sample, which represents a double quantity than the other catalysts proved in this work. The synergistic effects of ZnO-graphene heterojunctions play a key role in achieving better adsorption and photocatalytic performance. The results demonstrate the ease of depositing ZnO on seedless graphene by electrodeposition. The use of the film as a photocatalyst delivers interesting and competitive removal percentages for a potentially scalable degradation process enhanced by a non-toxic compound such as graphene.