This financial modelling case study describes the development of the 3-statement financial model for a large-scale transportation infrastructure business dealing with truck (and some rail) modalities. The financial modelling challenges in this area, especially for large-scale transport infrastructure operators, lie in automatically linking the operating activity volumes with the investment volumes. The aim of the paper is to address these challenges: The proposed model has an innovative retirement/reinvestment schedule that automates the estimation of the investment needs for the Business based on the designated age-cohort matrix analysis and controlling for the maximum service ceiling for trucks as well as the possibility of truck retirements due to the reduced scope of tracking operations in the future. The investment schedule thus automated has a few calibrating parameters that help match it to the current stock of trucks/rolling stock in the fleet, making it to be a flexible tool in financial modelling for diverse transport infrastructure enterprises employing truck, bus and/or rail fleets for the carriage of bulk cargo quantifiable by weight (or fare-paying passengers) on a network of set, but modifiable, routes.

The objective of the research is twofold. The study examines the role of public finance in promoting sustainable development in SSA. Secondly, the study investigates the optimal level of public finance beyond which public finance crowds out investment and hinders sustainable development in SSA. The study adopts a battery of econometric techniques such as the traditional ordinary least square (OLS) estimation technique, Driscoll-Kraay covariance matrix estimator, and the dynamic panel threshold model. The study found that an increase in public debts lead to a decline in sustainable development. In contrast, the results show that increase in spending on health and education, and tax can engender sustainable development in SSA. Further, we uncover the optimal levels of public spending on health and education, and public debts that engenders sustainable development in SSA. One main implication of the findings is that governments across SSA needs to reduce public debts levels and increase public spending on health and education to within the threshold levels established in this study to aid sustainable development in SSA.

Cyber-physical Systems (CPS) have revolutionized urban transportation worldwide, but their implementation in developing countries faces significant challenges, including infrastructure modernization, resource constraints, and varying internet accessibility. This paper proposes a methodological framework for optimizing the implementation of Cyber-Physical Urban Mobility Systems (CPUMS) tailored to improve the quality of life in developing countries. Central to this framework is the Dependency Structure Matrix (DSM) approach, augmented with advanced artificial intelligence techniques. The DSM facilitates the visualization and integration of CPUMS components, while statistical and multivariate analysis tool such as Principal Component Analysis (PCA) and artificial intelligence methods such as K-means clustering enhance complex system the analysis and optimization of complex system decisions. These techniques enable engineers and urban planners to design modular and integrated CPUMS components that are crucial for efficient, and sustainable urban mobility solutions. The interdisciplinary approach addresses local challenges and streamlines the design process, fostering economic development and technological innovation. Using DSM and advanced artificial intelligence, this research aims to optimize CPS-based urban mobility solutions, by identifying critical outliers for targeted management and system optimization.

A novel composite material based on polymers (polyvinyl alcohol, polyvinyl butyral) and liquid crystal (4-n-pentyl-4’-cyanobiphenyl) has been developed and studied. Configuration transformations of point defects in nematic droplets under the influence of an electric field, caused by localized changes in the concentration of NLC within the polymer matrix, have been discovered and analyzed. The boundary conditions necessary for achieving a nematic structure with homogeneous alignment of the director both within the droplet and at its surface have been established, optimizing the anisotropy of light transmission in polymer-dispersed liquid crystal (PDLC) films. Additionally, polarization effects inside nematic droplets under the application of an electric field have been identified.

The interest in using project management office (PMO) services in organizations to manage their construction projects is growing in light of rising economic, technological, and social developments based on their ability to achieve organizational goals while avoiding risks. Accordingly, organizations use PMO services to manage their technical and financial project issues to periodically evaluate PMO performance and services in a scientific, practical, and measurable way to ensure successful project path via PMO. Therefore, this research aims to develop a performance evaluation system that enables organizations to follow up and evaluate the PMO performance to ensure that PMO manages the organizations’ expectations and goals successfully according to certain quality, scope, and cost. The study builds on significant findings in PMO competence indexes as evaluation matrix, which includes five basic categories with 136 indexes covering the project life cycle. The matrix was developed based on literature analysis and supplemented with experts’ interviews in construction management. The developed robust competency-based index (RCI) for directive PMO supports the organizations to conduct client satisfaction, correction, or partial/total change of the PMO’s competence flow within five construction project life cycle and process, i.e. governance, portfolio, information, execution, and contract issues.