This research analyses how different leadership styles affect project managers in the telecommunications sector, focusing on transactional and transformational leadership's direct effects on project performance. Ambidextrous Leadership's role as a mediator is explored alongside the influence of Project Management approaches (Waterfall, Agile, Hybrid) and Project Manager Certifications. Data from 224 Project Managers in 77 Indonesian telecom companies was examined using Structural Equation Modelling Partial Least Square (SEM PLS). The findings indicate that Transactional and Transformational Leadership alone don't directly affect Project Performance, but Ambidextrous Leadership significantly enhances it. Different Project Management Approaches (Waterfall, Hybrid, Agile) amplify the impact of leadership styles. Transactional leadership is strongly linked to the waterfall, while transformational and ambidextrous leadership aligns with the agile and hybrid approach. Project Management Certification strengthens Transactional Leadership's effect on Project Performance, with less impact on Transformational Leadership. The research emphasizes the significance of Ambidextrous Leadership in improving project performance and how project management approaches and certifications can enhance or moderate the influence of leadership styles on telecommunication project management. These findings offer industry practitioners and organizations valuable insights, contributing to leadership, project management, and telecommunications research.

The government of India has increased its focus on investment in infrastructure, allocating US$ 130.57 billion in 2022-23 for the sector. Effective project management is crucial for success. However, despite a huge body of knowledge on project success, project delays persist, with 33% of projects delayed by an average of 47 months as of August 2021. This study aims to identify Critical Success Factors for contemporary construction projects in India, offering guidance for project stakeholders. Forty-five attributes of project success were collated from literature and expert discussions and a questionnaire survey was conducted to solicit the views of experts on the critical impact of these attributes on overall project success. The research posits that these attributes have underlying constructs that cause them. Factor analysis was employed to extract the underlying constructs. Six critical success factors (CSF) were extracted. To comprehend the relative importance of the factors, RII was employed on summated factor scores that were then ranked in order of their importance. ANOVA showed consistent assessments of the CSFs across professional roles and geographies. The findings are expected to aid project professionals in prioritizing key factors for optimal project management and successful outcomes.

Considering the acceleration in the development of alternative energy sources due to climate change and the net zero carbon commitments made in this direction, there are different assessments of how the capacity of the refining industry will change in the next two decades. Refinery companies are trying to adapt to altering conditions while also trying to determine their investment strategies. Project portfolio selection problem is one of the relevant issues to be considered in line with these changes. In this article, research has been undertaken to determine which criteria refinery companies take into consideration while selecting their project portfolios. Based on the identified criteria, it is also aimed to carry out a study that will guide sector practitioners in project selection. For this purpose, interviews were conducted with industry experts. The criteria were accredited by applying categorical content analysis to the data obtained and their importance weights were identified accordingly. The most deterministic criteria were abstracted from the findings and applied to a multi-criteria decision-making (MCDM) framework, namely fuzzy MULTIMOORA to suggest a decision support tool that ranks the projects against themselves. Some of the prominent outcomes of the study are also discussed, along with the previous studies and comparative results of the proposed decision support tool.

The adoption of technology in Indonesian construction is still developing at a slower pace than in other sectors, particularly in materials management. Among the automation technologies that can be developed for precast material management, is integrated RFID technology with the Internet of Things (IoT). This study therefore aims to analyze the correlation between factors influencing the implementation of integrated RFID technology with IoT for precast material management in Indonesia and to examine the development model of the integrated RFID technology system with IoT. The research methods include a questionnaire survey with PLS-SEM and the development of technology systems validated by experts. The results demonstrate that factors, such as resource availability, implementation cost, stakeholder involvement, implementation risk, and project conditions have a significant direct and indirect impact on the implementation of integrated RFID technology with IoT for precast material management. Among these factors, the implementation of risk factors has the most significant influence. Furthermore, the development of the integrated RFID technology system with IoT has proven to be beneficial, especially as an automation technology for data recording and visibility in precast material management.

The construction industry faces challenges, such as schedule overruns, cost overruns, poor quality, and safety issues. Lean construction is a valuable concept for waste reduction and improving project performance. This study explored the impact of lean construction principles on contractors' project performance in Ethiopia. Using a quantitative method and simple random sampling technique, 159 respondents from construction companies were selected. This study introduced partial least squares structural equation modeling (PLS-SEM) in the study area. The results showed that process/technology lean principles, people/culture lean principles, and integrated project delivery variables had a direct positive impact on contractor performance. There was also a significant indirect relationship between process/technology-lean construction principles and project performance with a complementary partial mediation effect. However, no significant indirect associations were found between people/culture-lean construction principles and project performance through mediation of onsite construction waste management. The study used FIMIX-PLS to test robustness and detect hidden heterogeneity at non-critical levels. The findings provide researchers and practitioners to identify the influences that are critical for contractors’ projects performance improvement, and that results in the best possible outcome.

Patient punctuality significantly impacts resource utilization and patient waiting times, among other quality indicators, within psychiatry clinics. In pursuit of service improvement, this study endeavors to develop effective appointment scheduling systems that optimally distribute patients' needs during clinical sessions, thereby enhancing resource utilization and patient satisfaction. In developing these scheduling rules, three patient-related uncertainties are considered: preference, availability, and punctuality. Various scheduling rules are evaluated based on their average total cost under different scenarios. The HSBGDM rules have emerged as a balanced approach for clinic operations, effectively managing physician time but occasionally leading to overtime variations. Increased patient delays often exacerbate physician idle times, particularly under IBVST and VBVST rules. Hybrid rules, such as the HSBGDM series, adapt well, improving patient wait times and managing unscheduled patients. However, scheduling systems like REPDM may prolong waits, potentially impacting patient satisfaction. Systems prioritizing new appointments can increase physician idle times due to unpredictability. While accommodating unscheduled patients enhances service quality, it may also cause disruptions. This study provides valuable insights into scheduling dynamics, assisting administrators in balancing efficiency, cost, and patient satisfaction.

The presented article deals with the mathematical modeling of aircraft ground handling on the service apron to utilize ground personnel more efficiently in the case of existing substitutability of workers. This article proposes a supporting decision-making tool for effective planning of the aircraft ground handling. This tool will be used for a selected type of aircraft and using the minimum number of personnel participating in the aircraft ground handling procedure. The optimization is based on the original mathematical programming model and its solution. Computational experiments verifying the functionality of the proposed model were performed on current data from the Ostrava International Regional Airport in the Czech Republic. The originality of the proposed approach (apart from the original model) comes with introducing the substitutability of workers of individual qualifications and the decomposition of workgroups composed of workers of the same qualification down to the level of individual workers. Above-mentioned decomposition of workgroups enables the flexible and separate transfer of individual workers included in the same groups between activities in the event of downtime of the given group and the existence of an activity that is not covered by the required number of workers. The substitutability of workers and the decomposition of individual groups down to the level of individual workers will make it possible to lower the number of workers or verify that the number of workers is optimal and eliminate potential staff downtime.

All organizations and stakeholders would ideally like to see an information technology (IT) project managed successfully. Many researchers have strongly debated the importance of risk management in project management about the size of the project since it gives project managers a forward-looking view of risks and chances to increase the project's success. The main aim of the study is to determine how risk management parameters and their mediated effects impact the effectiveness of IT projects. Data was collected from 261 IT professionals involved in projects through a structured questionnaire and analyzed using regression and SEM to test their statistical significance and prove the hypothesis. The study arrived at some significant results which showed the relationship of Risk Identification and Risk Analysis on Risk Assessment, which impacts Project Success. It also showed that the success of the project depended on Stakeholders Tolerance and Risk Implementation. In addition to this, the study provides evidence that risk management does not influence the success of the project. The study's discovery of the intervening impact of risk management practices clarifies preconceived conceptions in the risk management sector.

Hub networks play a crucial role in optimizing transportation costs in air and road systems. Their main objective is to strategically locate hubs and allocate non-hub nodes within the network. The modular hub location problem is a specific area of hub network design that focuses on accurately calculating transportation costs, considering factors like trip numbers and capacity constraints in network routes. This study proposes a mixed-integer programming model to address the modular hub location problem with multiple allocations. It considers dependent and independent costs associated with vehicles per trip between hub network routes, considering specific vehicle capacities. Two datasets are utilized for validation: the CAB dataset representing 25 nodes of US airports and the TR dataset representing the Turkish transportation system with 81 nodes. To tackle the NP-hard nature of hub location models and the computational complexity of the proposed model, two solutions are developed. Firstly, a novel LP relaxation-based method using GAMS software provides near-optimal solutions for medium-sized instances. Additionally, a Genetic Algorithm (GA) implemented in MATLAB handles larger instances. The GA's efficiency is enhanced by tuning its parameters using the Taguchi method. Results analysis shows that both proposed algorithms yield high-quality solutions within significantly reduced timeframes compared to the CPLEX solver in GAMS software. The LP relaxation-based method performs well for medium-sized instances, while the GA approach is efficient for larger instances after parameter tuning with the Taguchi method.

This study proposes Q-learning-based iterated greedy (IGQ) algorithms to solve the blocking flowshop scheduling problem with the makespan criterion. Q learning is a model-free machine intelligence technique, which is adapted into the traditional iterated greedy (IG) algorithm to determine its parameters, mainly, the destruction size and temperature scale factor, adaptively during the search process. Besides IGQ algorithms, two different mathematical modeling techniques. One of these techniques is the constraint programming (CP) model, which is known to work well with scheduling problems. The other technique is the mixed integer linear programming (MILP) model, which provides the mathematical definition of the problem. The introduction of these mathematical models supports the validation of IGQ algorithms and provides a comparison between different exact solution methodologies. To measure and compare the performance of IGQ algorithms and mathematical models, extensive computational experiments have been performed on both small and large VRF benchmarks available in the literature. Computational results and statistical analyses indicate that IGQ algorithms generate substantially better results when compared to non-learning IG algorithms.