The right selection of implementation system for projects in the construction industry is critical to achieve success. Integrated Project Delivery (IPD), is a comprehensive implementation system which has in recent years been seen to play an effective role in projects improved efficiency. Implementing an IPD system to resolve various problems of traditional systems is very important; however there are several barriers to its implementation. In addition, rooting and classifying the barriers is very significant in being able to resolve them. The aim of this study is the identification of barriers to IPD basically extracted from existing case studies. In this research, the meta-synthesis qualitative method is used for identifying and classifying the IPD barriers. The results are presented in a comprehensive table, and then are illustrated as a pattern by using macro concepts. This pattern is useful for presenting barriers to IPD. Identifying the barriers and resolving them are as important as identifying the benefits of IPD in creating motivation for construction industry owners. They also serve to provide the context for required predictions in implementing this approach in the construction industry.

Construction managers in infrastructure projects in different societies offer and use approaches that can conclude each project's triangle of cost, time, and quality in the most optimal mode, satisfying important needs of the projects. One of these approaches is benefiting from concepts of Constructability, Operability, and Maintainability (the threefold concepts of COM), which can satisfy such need in infrastructure projects. In order to implement each approach, while the desired approach is innovative, as well, there are some barriers. It is significantly required to offer solutions to obtain desired results from that approach. Therefore, the aim of this research is presenting solutions to overcome existing barriers in implementing the threefold concepts of COM in infrastructure projects. For that, the Meta-Synthesis method is applied, which is placed in qualitative research category. In order to analyze collected data, descriptive and pattern coding techniques have been used. As the result of this study, a systematic classification of the solutions to overcome barriers of implementing the threefold concepts of COM in infrastructure projects is presented. The aim of construction managers is successful delivery of projects, for that, it is suggested to use such approaches that result in integration of different project life cycle phases. This facilitates optimization of project time and cost, aiming to provide a better quality of constructions. Therefore, in order to achieve infrastructure projects main objectives, such approaches are to be used, and in order to overcome barriers in implementing them, some solutions are to be identified, classified and presented.

In recent decades, several definitions of competency have been presented by prominent thinkersand scholars of this field, each of them deals with the competency from a certain angle andexpressed different dimensions. Furthermore, the competency approach in human resourcemanagement (HRM) is not a new trend, and the subject of competence is a very old subjectmatter. On the contrary, human resource competence is one of the most important issues of anyorganization, which includes diverse, attractive and, simultaneously, sophisticated topics. Today,due to the dramatic changes in the field of HRM and the trend of managers to meritocracy in theorganization, the planning of an organization based on competency has a special place. Differentstudies in this field show that the necessity to pay attention to the mission perspective, strategy,organizational goals and structure will be an integral part in the successful assignment of humanresources and, without regard to this, the organization's approach cannot be determined. The useof human resource competency models in multiple construction projects requires a majorparadigm, which in HRM literature refers to the competency-based human resource management(CBHRM), and changes the thinking of human resource managers across individuals andorganizations, generally. This competency-based management approach is a coherent approachfor managing human capital in the long term, based on a common set of competency modelsrelated to the macro strategies of each project in this field. In this paper, the researcher initiallyreviewed the diversity of conceptual frameworks and components of competency models inconstruction projects. Then, the competency models of the project manager, civil engineer, andconstruction foreman and worker are identified in project-oriented organizations. At the end ofthe research, a set of competencies of professional, ethical, cultural and social behaviour ispresented in a variety of competency models.

Purpose: This paper develops a conceptual framework that positions startups as systemic enablers of circular economy (CE) strategies within smart city service ecosystems. Addressing a gap in the service quality, service science and sustainability literature, this study aims to conceptually explore how startups operationalise circular principles through service innovation, digital technologies and multi-actor collaboration to support the transition to circular urban service systems. Design/methodology/approach: This study adopts a conceptual research design complemented by an exploratory simulation-based illustration. Secondary literature is synthesised to identify key dimensions, while insights from the IMD (2025) are used as a contextual reference rather than an empirical benchmark. Based on this framework, a ten-item prototype questionnaire was developed and illustrated through a controlled simulation involving 12 artificial intelligence-generated synthetic stakeholder personas representing startup founders, urban planners, corporate innovators and sustainability experts, selected based on recurrent role typologies in the smart city and CE literature. Personas and responses were generated using a large language model (ChatGPT-5) as an instrument-prototyping device and provided Likert-scale evaluations and short qualitative rationales. The simulation is explicitly illustrative and does not constitute empirical data collection. Findings: The illustrative simulation highlights convergent and divergent patterns in stakeholder perspectives. Startups are consistently perceived as strategically relevant for advancing circular transitions through Industry 4.0 technologies and reuse-oriented service models. At the same time, greater variability emerges regarding institutional support, policy adequacy, inclusivity and public–private collaboration. Research limitations/implications: The findings are based on synthetic data and are not generalisable. This study provides a transparent, replicable prototype assessment instrument intended to support hypothesis generation and guide future empirical stakeholder research on smart circular cities. Practical implications: The framework offers a structured lens for policymakers and urban managers to design innovation-friendly and inclusive circular service strategies, and supports startups in strengthening their service-based positioning within urban ecosystems. Originality/value: By integrating service science and CE perspectives, this paper advances a novel conceptual synthesis and demonstrates an illustrative, stakeholder-oriented assessment tool, contributing to theory building at the intersection of service quality, sustainability and smart cities.

Purpose: Create a framework supporting managers in integrating AI into business management decisions. Need for the study: The Artificial Intelligence (AI) discipline is revolutionizing business management via enhanced decision-making procedures, enhanced operational effectiveness, and improved strategic planning. Looking at the openness of their algorithms and data training and handling, AI models are generally categorised into Private and Open-Source models. The aforementioned distinctions significantly affect the functioning of companies in terms of privacy, data security, and competitive standing. Businesses must make a fundamental trade-off between Open-Source AI, that could be limited in data privacy and security, but it presents a lower initial investment, and Private AI, which provides better data control at the expense of increased financial investment. Methodology: Critical analysis of the literature, case studies and practitioner experience. Findings: The research presents limits and opportunities of both Open-Source and private AI, and a framework to support managers in integrating both models in different areas of their operations to optimize benefits. Practical Implications: A structured approach can help managers make informed decisions about adopting AI, balancing cost, security, and scalability