Institutional thinking, a concept that underscores the importance of internal perspectives and the enduring purposes of institutions, plays a critical role in maintaining societal stability and ethical governance. This paper explores the dual nature of institutional thinking, highlighting its positive aspects and inherent dangers. Through an examination of economic, political, and philosophical forces, the paper identifies modern challenges that undermine long-term commitments and ethical values within institutions. By drawing on historical and contemporary examples, including slavery, Nazism, and discriminatory practices, the discussion provides a comprehensive understanding of how institutional thinking can both promote human well-being and perpetuate systemic issues. The paper concludes by emphasizing the need to reaffirm institutional values, promote long-term thinking, and balance individual rights with collective responsibilities to harness the positive aspects of institutional thinking while mitigating its risks.

The carbon footprint, which measures greenhouse gas emissions, is a good environmental indicator for choosing the best sustainable mode of transportation. The available emission factors depend heavily on the calculation methodology and are hardly comparable. The minimum and maximum scenarios are one way of making the results comparable. The best sustainable passenger transport modes between Rijeka and Split were investigated and compared by calculating the minimum and maximum available emission factors. The study aims to select the best sustainable mode of transport on the chosen route and to support the decision-making process regarding the electrification of the Lika railroad, which partially connects the two cities. In the minimum scenario, ferry transport without vehicles was the best choice when the transportation time factor was not relevant, and electric rail transport when it was. In the maximum scenario, the electric train and the ferry with vehicles were equally good choices. Road transportation between cities was not competitive at all. The comparison of the carbon footprint based on minimum and maximum scenarios gives a clear insight into the ratio of greenhouse gas emissions from vehicles in passenger transport. It supports the electrification of the Lika railroad as the best sustainable transport solution on the route studied.

The goal of this work was to create and assess machine-learning models for estimating the risk of budget overruns in developed projects. Finding the best model for risk forecasting required evaluating the performance of several models. Using a dataset of 177 projects took into account variables like environmental risks employee skill level safety incidents and project complexity. In our experiments, we analyzed the application of different machine learning models to analyze the risk for the management decision policies of developed organizations. The performance of the chosen model Neural Network (MLP) was improved after applying the tuning process which increased the Test R² from −0.37686 before tuning to 0.195637 after tuning. The Support Vector Machine (SVM), Ridge Regression, Lasso Regression, and Random Forest (Tuned) models did not improve, as seen when Test R² is compared to the experiments. No changes in Test R²’s were observed on GBM and XGBoost, which retained same Test R² across different tuning attempts. Stacking Regressor was used only during the hyperparameter tuning phase and brought a Test R² of 0. 022219.Decision Tree was again the worst model among all throughout the experiments, with no signs of improvement in its Test R²; it was −1.4669 for Decision Tree in all experiments arranged on the basis of Gender. These results indicate that although, models such as the Neural Network (MLP) sees improvements due to hyperparameter tuning, there are minimal improvements for most models. This works does highlight some of the weaknesses in specific types of models, as well as identifies areas where additional work can be expected to deliver incremental benefits to the structured applied process of risk assessment in organizational policies.

Pakistan is a leading emerging market as per the recent classification of the International Monetary Fund (MF), and hedging is used as a considerable apparatus for minimizing a firm’s risk in this market. In these markets, investors are customarily unaware about the hedging activities in firms, due to the occupancy of asymmetric environment prevailing in firms. This research paper adds a new insight and vision to the existing literature in the field of behavioral finance by examining the impact of hedging on investors’ sentiments in the presence of asymmetric information. For organizing this research, 366 non-financial firms are taken up as the size sample; all these firms are registered in the Pakistan Stock Exchange. A two-step system of generalized method of moments (GMM) model is implemented for regulating the study. The findings of empirical evidence exhibit that there is a positive relationship between investors’ sentiments and hedging. Investors’ sentiments are negative in relationship with asymmetric information. Due to the moderate presence of asymmetric information, hedging is positively related to investors’ sentiments although this relation is non-significant.

The research aims to examine East Nusa Tenggara (NTT) bank service digitalization innovations and examine several implications of bank service digitalization innovations. This research uses a qualitative approach with data collection techniques: in-depth interviews, documentation, and focused discussions. The key informants in this research were the board of commissioners, directors, division heads, and NTT bank employees. The findings of this research are, first, the existence of an existing/generic model in the operational, supporting, and monitoring fields of NTT banks. Second, there is an innovation model for digitizing services and efforts to popularize the digitization of NTT bank services to the government-private sector, including micro, small, and medium enterprises (MSMEs), religious institutions, educational institutions, students and students as well as the broader community to provide easy access to sources of financing for the community, Eliminate regional tax leakage, encourage the development of micro, small, and medium enterprises (MSMEs) and assisted village farmers/breeders, provide entrepreneurial opportunities for the community, namely as a digital agent for NTT bank, minimize fraudulent behavior (shirking) in credit distribution. Third, service digitalization innovation uses a contextual sociolinguistic approach because it incorporates local and global vocabulary such as Bpung Mobile, Bpung Farmer, Lopo Dia Bisa, and Bpinjam. Fourth, service digitalization innovation refers to OJK regulations regarding banking digital transformation contained in RP 21 and PBI number 23/26/2021. Fifth, conventional services (hybrid approach) still accompany the digitalization innovation model. Sixth, Bank NTT is in quadrant III, namely growth. Bank NTT continuously optimizes existing resources by taking advantage of opportunities to increase business growth and continues to mitigate threats into opportunities and strengths. The implications of the innovation in digitizing NTT bank services include updating standard operating procedures (SOP), changing corporate culture from Flobamora to Bintang, and accelerating the increase in human capital capacity. The implications of research on bank management refer to the innovation of procurement of new IT systems. Banks can increase their attention to service quality and maintain customer trust to maintain the quality of digital banks among customers. Moreover, with post-COVID-19 conditions that require people to make digital transactions. With the changes in the financial industry towards digitalization, it is necessary to strengthen risk management in financial service institutions. The implications of the research results for policymakers need to be considered in the transformation towards digital banking related to equitable internet access in Indonesia, cybersecurity, and employment. Recommendations for future research are the importance of studying the determinants of digital service innovation in bank services, such as transformational leadership style, good corporate governance, and organizational commitment.

Housing is one of the most significant components of sustainable development; hence, the need to come up with sustainable housing solutions. Nevertheless, the sales of houses are steadily falling due to the unaffordability of houses to many people. Based on the expanded community acceptance model, this research examines the relationships between sustainable housing and quality of life with the moderating factors of knowledge, technology, and innovation in Shenzhen. Additionally, it aims to delineate the principal dimensions influencing quality of life. The study employs purposive sampling and gathers data from residents of Shenzhen via a Tencent-distributed survey. Analysis was conducted using Smart Partial Least Squares (PLS) 4.0. Results indicate a positive correlation between economic sustainability in housing and quality of life. Contrarily, the social and environmental aspects exhibited negligible impacts on quality of life. Knowledge, technology, and innovation were identified as significant moderators in the correlation among all three sustainable housing dimensions and quality of life. The findings are anticipated to enhance understanding of the perceived impacts of sustainable housing on quality of life in Shenzhen and elucidate the role of knowledge, technology, and innovation in fostering this development.