This study critically examines the relationship between Total Quality Management (TQM) and Service Quality (SQ) within Dubai’s housing sector, with a specific focus on the moderating influence of blockchain technology (BT) in this relationship. Employing a quantitative approach grounded in a deductive research strategy and positivist epistemology, data were gathered from a sample of industry professionals and subjected to rigorous analysis using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings indicate that the deliberate deployment of TQM methodologies leads to significant improvements in SQ metrics, and the catalytic role of BT further enhances these service quality improvements. The study highlights the transformative potential of BT in recalibrating conventional paradigms of service delivery within the housing sector. Specifically, the analysis reveals that BT plays a pivotal moderating role in the relationship between TQM practices and SQ outcomes, thereby enriching our comprehension of the intricate interplay between these constructs. The study concludes by furnishing nuanced insights into the multifaceted dynamics shaping SQ within the housing sector, while also delineating avenues for future inquiry.

This study aims to explore the evolution of the human resources field in Western academia during the 1970s and 1980s, focusing on the trends in research topics across different decades. The analysis utilizes citation co-citation analysis, multivariate statistical analysis, and social network analysis. The research data were drawn from the Web of Science (WoS) database, comprising 1278 documents. By distinguishing between different time periods, the study identifies shifts in the field across two distinct time frames, visualized through multidimensional scaling maps. The results indicate that the 1970s were dominated by seven major research streams, while the 1980s introduced eight research streams, with “human resources” emerging for the first time as a prominent research frontier. The volume of literature, co-citation frequency, and citation counts all increased over time, reflecting the growing vibrancy and expanding scope of research in the field. Although citation co-citation analysis provides objective quantitative insights, issues such as the purpose of citations, the extent to which cited documents influence citing documents, and the varying layers of citation impact may introduce potential errors in the co-citation analysis results.

Identify and diagnosis of homogenous units and separating them and eventually planning separately for each unit are considered the most principled way to manage units of forests and creating these trustable maps of forest’s types, plays important role in making optimum decisions for managing forest ecosystems in wide areas. Field method of circulation forest and Parcel explore to determine type of forest require to spend cost and much time. In recent years, providing these maps by using digital classification of remote sensing’s data has been noticed. The important tip to create these units is scale of map. To manage more accurate, it needs larger scale and more accurate maps. Purpose of this research is comparing observed classification of methods to recognize and determine type of forest by using data of Land Cover of Modis satellite with 1 kilometer resolution and on images of OLI sensor of LANDSAT satellite with 30 kilometers resolution by using vegetation indicators and also timely PCA and to create larger scale, better and more accurate resolution maps of homogenous units of forest. Eventually by using of verification, the best method was obtained to classify forest in Golestan province’s forest located on north-east of country.

The Nigerian Civil Service faces ongoing challenges in optimizing employee commitment, which is fundamental for efficient service delivery and societal progress. Hence, this paper focuses on the mediating effect of job satisfaction on talent engagement and employee commitment in the Nigerian Civil Service. The study adopted a quantitative approach, which allowed for a survey design to be adopted. A sample of 198 middle- and lower-level managers in the civil service was used. Questionnaires were used for data collection, and SmartPls 3.9 was used for data analysis. The result showed that talent engagement significantly predicts employee commitment and that job satisfaction is a good mediator in the relationship between talent engagement and employee commitment in the Nigerian Civil Service. The findings suggest that creating an engaged workforce through talent engagement can have a positive influence on employee commitment within the public sector, which can result in improved public services and contribute to overall societal development.

Since the reform and opening up, China has continuously pushed forward the administrative system reform, adapted to the national conditions and the requirements of the times, and achieved fruitful results. Generally speaking, the successive administrative system reforms have focused on the government and the adjustment of the dynamic relationship between government-market-society. Due to the special characteristics of local foreign affairs departments in the administrative system, the successive reforms have provided less guidance to them, and related research is also relatively lacking. However, from a practical point of view, local foreign affairs offices have long followed the pace of administrative system reform and carried out a series of adjustments and optimizations. As an important element of administrative system reform, the functional transformation of local foreign affairs offices has been continuously promoted along with institutional reform. This research, which is mainly based on talks and supplemented by document comparisons, aims to study the development results and experiences of the Foreign Affairs Office of Shaanxi Province in the context of administrative system reform, and tries to provide a case study for the administrative system reform of local foreign affairs departments.