This study sought an innovative quality management framework for Chinese Prefabricated Buildings (PB) projects. The framework combines TQM, QSP, Reconstruction Engineering, Six Sigma (6Σ), Quality Cost Management, and Quality Diagnosis Theories. A quantitative assessment of a representative sample of Chinese PB projects and advanced statistical analysis using Structural Equation Modeling supported the framework, indicating an excellent model fit (CFI = 0.92, TLI = 0.90, RMSEA = 0.06). The study significantly advances quality management and industrialized building techniques, but it also emphasizes the necessity for ongoing research, innovation, and information exchange to address the changing problems and opportunities in this dynamic area. In addition, this study’s findings and recommendations can help construction stakeholders improve quality performance, reduce construction workload and cost, minimize defects, boost customer satisfaction, boost productivity and efficiency in PB projects, and boost the Chinese construction industry’s growth and competitiveness.

This study examines the impact of parliamentary thresholds on the Indonesian political system through the lens of the Routine Policy Implementation Model and the Strategic Policy Implementation Model. The main objective is to evaluate the effectiveness of parliamentary thresholds in managing political fragmentation, assess their impact on stability and representation in the legislative system, and understand their implementation’s technical and strategic implications. Using a qualitative approach supported by interview studies and field observations, this research combines analysis of election data in the 2009, 2014, and 2019 elections with a qualitative assessment of policy changes and political dynamics. The Routine Policy Implementation Model focuses on the technical aspects of threshold implementation, including vote counting procedures and seat allocation efficiency. Meanwhile, the Strategic Policy Implementation Model examines the broader implications of these thresholds for political consolidation, government effectiveness, and the representation of minor parties. The results show that the parliamentary threshold has significantly reduced political fragmentation by consolidating the number of parties in Parliament, resulting in a legislative system that is cleaner and easier to administer. However, this consolidation has also marginalized small parties and limited political diversity. The novelty of this study lies in its comprehensive analysis of how parliamentary thresholds affect administrative efficiency and strategic political stability in Indonesia, compared to democratic countries in transition, such as Slovenia and Montenegro. In conclusion, although parliamentary thresholds have increased political stability and government effectiveness, they have also raised concerns about the reduced representation of small and regional parties. The study recommends maintaining balanced thresholds that ensure stability and diversity, implementing mechanisms to review thresholds periodically, and involving diverse stakeholders in adjusting policies to reflect evolving political dynamics. This approach will help balance the need for a stable legislative environment with broad representation.

This study aims to examine whether banks are compliant with adopting sustainability regulations and guidelines, and how they disclose their sustainable finance activities in sustainability reporting by providing case of Indonesian banking. Previous research provided discussions on the role of governance in supporting many variables as quantitative studies, but failed to demonstrate on going practices of how banking industries implement sustainable finance governance. Hence, this study provides originality by analyzing the extend of disclosures in order to evaluate their commitments in responding to sustainability regulations and guidelines, through disclosures of economic, environment, social, and governance (EESG) information in annual and sustainability reports. The samples were undertaken by examining the contents of sustainability and annual reports published for the financial year 2016 to 30 June 2021, for the Indonesian banks listed in business category 4, business category 3, and international banks, with the total of 202 reports. The results indicate that the implementation of sustainable finance in EESG information increases annually with social performances are the highest information disclosed, while the governance and economic information received the lowest level of disclosure. Results of this study will benefit policymakers, banks, and related companies to understand sustainable finance governance, and reveal the importance the role of banking industries to support Sustainable Development Goals (SDGs). Providing the insights of the ongoing discussions are expected to suggest following actions for further policies to support the implementation of sustainable finance, in particular to establish sustainability governance as a foundation of commitments, beyond complying to regulations.

The usage of cybersecurity is growing steadily because it is beneficial to us. When people use cybersecurity, they can easily protect their valuable data. Today, everyone is connected through the internet. It’s much easier for a thief to connect important data through cyber-attacks. Everyone needs cybersecurity to protect their precious personal data and sustainable infrastructure development in data science. However, systems protecting our data using the existing cybersecurity systems is difficult. There are different types of cybersecurity threats. It can be phishing, malware, ransomware, and so on. To prevent these attacks, people need advanced cybersecurity systems. Many software helps to prevent cyber-attacks. However, these are not able to early detect suspicious internet threat exchanges. This research used machine learning models in cybersecurity to enhance threat detection. Reducing cyberattacks internet and enhancing data protection; this system makes it possible to browse anywhere through the internet securely. The Kaggle dataset was collected to build technology to detect untrustworthy online threat exchanges early. To obtain better results and accuracy, a few pre-processing approaches were applied. Feature engineering is applied to the dataset to improve the quality of data. Ultimately, the random forest, gradient boosting, XGBoost, and Light GBM were used to achieve our goal. Random forest obtained 96% accuracy, which is the best and helpful to get a good outcome for the social development in the cybersecurity system.

Air cargo transportation accounts for less than 1% of the global trade volume, yet it represents approximately 35% of the total value of goods transported, highlighting its strategic importance in trade and economic development. This study investigates the relationship between domestic air cargo transport in Brazil and key macroeconomic variables, focusing on how regional economic dynamism, logistical infrastructure, and population density impact the country’s development. Using a panel data regression model covering the period from 2000 to 2020, the study analyzes the evolution of air cargo transportation and its role in redistributing economic growth across Brazil’s regions. The findings emphasize the key factors influencing the air cargo sector and demonstrate how these factors can be leveraged to optimize public policies and business strategies. This research provides valuable insights into the relevance of air cargo transportation for regional and national development, particularly in emerging economies like Brazil, offering guidance for the formulation of strategies that promote balanced economic growth across regions.