Increasingly, U.S. cities are focusing on transit-oriented development (TOD) policies to expand the stock of higher-density, mixed-use development near public transit stations within the context of a transit corridor and, in most cases, a regional metropolis. A TOD zone relies on a regulatory and institutional environment, public and private participation and investment, and development incentives to create vibrant, people-oriented communities and mobility options and to support business development. TODs provide local governments with more tax revenues due to increased property values (and, as applicable, income and sales tax revenues), but most planning for TODs ignores the non-transit infrastructure costs of increasing development density. This study focused on determining the water and sewer infrastructure costs for TOD zones along a rail line in southeast Florida. The finding was that millions of dollars in funds are needed to meet those water and sewer needs and that few are currently planned as a part of community capital improvement programs.
This research examines three data mining approaches employing cost management datasets from 391 Thai contractor companies to investigate the predictive modeling of construction project failure with nine parameters. Artificial neural networks, naive bayes, and decision trees with attribute selection are some of the algorithms that were explored. In comparison to artificial neural network’s (91.33%) and naive bays’ (70.01%) accuracy rates, the decision trees with attribute selection demonstrated greater classification efficiency, registering an accuracy of 98.14%. Finally, the nine parameters include: 1) planning according to the current situation; 2) the company’s cost management strategy; 3) control and coordination from employees at different levels of the organization to survive on the basis of various uncertainties; 4) the importance of labor management factors; 5) the general status of the company, which has a significant effect on the project success; 6) the cost of procurement of the field office location; 7) the operational constraints and long-term safe work procedures; 8) the implementation of the construction system system piece by piece, using prefabricated parts; 9) dealing with the COVID-19 crisis, which is crucial for preventing project failure. The results show how advanced data mining approaches can improve cost estimation and prevent project failure, as well as how computational methods can enhance sustainability in the building industry. Although the results are encouraging, they also highlight issues including data asymmetry and the potential for overfitting in the decision tree model, necessitating careful consideration.
This study uses dynamic capability theory and a resource-based view to examine whether intellectual capital (human, relational, and structural capital) mediates entrepreneurial leadership and innovation success. Drawing on data from 422 senior-level employees working in Peruvian I.T. companies, the proposed relationships were analyzed using SmartPLS 4. Entrepreneurial leadership was found to foster employees’ innovative performance through the mediating role of human capital, relational capital, and structural capital. Practically, businesses often rely on innovation for survival and growth, so they should consider entrepreneurial leadership to create intellectual capital (human capital, relational capital and structural capital) for innovation performance. Businesses should provide entrepreneurial training that emphasizes role modeling intellectual capital and encourages employees to recognize and pursue entrepreneurial opportunities. With significantly limited research, the study contributes by investigating the interrelationship of entrepreneurial leadership, intellectual capital, and innovation performance. The study contributes to the Resource Based View and Dynamic Capability Theory by demonstrating how entrepreneurial leadership contributes to innovation performance through human capital, relational capital, and structural capital.
Functions are the core of algebra, and the teaching of function concepts is also the main task of high school mathematics Students' learning of functions and their concepts shifts from understanding specific quantitative relationships to understanding abstract quantitative relationships The monotonicity of functions, as the property of the first function that students learn in high school, lays a certain foundation for learning function related knowledge in the future.
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