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Transportation infrastructure asset management has long been an active but challenging problem for agencies, which urges to maintain a good state of their assets but faces budgetary limitations. Managing a network of transportation infrastructure assets, especially when the number is large, is a multifaceted challenge. This paper aims to develop a life-cycle cost analysis (LCCA) based transportation infrastructure asset management analytical framework to study the impacts of a few key parameters/factors on deterioration and life-cycle cost. Using the bridge as an example infrastructure type, the framework incorporates an optimization model for optimizing maintenance, repair, rehabilitation (MR&R) and replacement decisions in a finite planning horizon.

The analytical framework is further developed through a series of model variations, scenario and sensitivity analysis, simulation processes and numerical experiments to show the impacts of various parameters/factors and draw managerial insights. One notable analysis is to explicitly model the epistemic uncertainties of infrastructure deterioration models, which have been overlooked in previous research. The proposed methodology can be adapted to different types of assets for solving general asset management and capital planning problems.

The experiments and case studies revealed several findings. First, the authors showed the importance of the deterioration model parameter (i.e. Markov transition probability). Inaccurate information of p will lead to suboptimal solutions and results in excessive total cost. Second, both agency cost and user cost of a single facility will have significant impacts on the system cost and correlation between them also influences the system cost. Third, the optimal budget can be found and the system cost is tolerant to budge variations within a certain range. Four, the model minimizes the total cost by optimizing the allocation of funds to bridges weighing the trade-off between user and agency costs.

On the path forward to develop the next generation of bridge management systems methodologies, the authors make an exploration of incorporating the epistemic uncertainties of the stochastic deterioration models into bridge MR&R capital planning and decision-making. The authors propose an optimization approach that does not only incorporate the inherent stochasticity of bridge deterioration but also considers the epistemic uncertainties and variances of the model parameters of Markovian transition probabilities due to data errors or modeling processes.

In the present article, the authors tackle the problem of IT documentation, which plays an important role in information technology (IT) project management.

They provide a simple tool based on five complementary views, which should be detailed by the project team using a classic source code management platform.

The proposed tool is open source and may be reused by any IT team in various project contexts and heterogeneous development methods.

This research provides an operational framework, which facilitates IT project management and documentation. The framework is open source and may be easily downloaded by any other IT team.

The objectives of this study are twofold: first, to identify the effect of sustainability management on the success of international development projects, and second, to investigate the moderating role of political and social skills on this relationship.

This study adopted a quantitative research methodology based on questionnaire data collected from 43 international development project managers from various fields in Burkina Faso (West Africa). Descriptive statistics and exploratory and confirmatory analyses using principal component analysis were used to assess the quality of the measurement model. A multiple regression analysis based on the partial least squares approach was used to test the hypotheses.

The results show that sustainability management positively contributes to the success of international development projects. However, given the specificities of these projects and their perception of success, the project coordinator's political and social skills do not predict a greater impact of sustainability management on the success of international development projects. The study also found that project coordinators prioritize their technical skills over behavioral ones.

This study fills a gap in the literature, given that little is known about the moderating role of political and social skills in the effect of sustainability management on the success of specific projects such as international development projects.

This paper covers the development of a multidimensional contract administration performance model (CAPM) for construction projects. The proposed CAPM is intended to be used by the industry stakeholders to measure the construction contract administration (CCA) performance and identify the strengths and weaknesses of the CCA system for running or completed projects.

The research design follows a sequential mixed methodology of qualitative and quantitative data collection and analysis. In the first phase, contract administration indicators were collected from relevant literature. In the second phase, an online questionnaire was prepared, and data were collected and analyzed using the crisp value of fuzzy membership function, and structural equation modeling (SEM). The fuzzy set was chosen for this study due to the presence of uncertainty and fuzziness associated with the importance of several key indicators affecting the CCA performance. Finally, SEM was used to test and analyze interrelationships among constructs of CCA performance.

The data collected from 336 construction professionals worldwide through an online survey was utilized to develop the fuzzy structural equation model. The goodness-of-fit and reliability tests validated the model. The study concluded a significant correlation between CCA performance, CCA operational indicators, and the process groups.

The contribution of this paper to the existing knowledge is the development of a fuzzy structural equation model that serves as a measurement tool for the contract administration performance. This is the first quantitative structural equation model to capture contract administration performance. The model consists of 93 Construction Contract Administration(CCA) performance indicators categorized into 11 project management process groups namely: project governance and start-up; team management; communication and relationship management; quality and acceptance management; performance monitoring and reporting management; document and record management; financial management; changes and control management; claims and dispute resolution management; contract risk management and contract closeout management.

Drawing on theories of development economics and sustainable tourism, this research explores the differences between sovereign and nonsovereign small island tourism economies (SITEs) and identifies the antecedents and effects of overtourism in the Caribbean.

The research design is based on a comparative case study of selected Caribbean SITEs. Case study research involves a detailed empirical inquiry that investigates a contemporary phenomenon within its real-life context. The main purpose of a case study is to provide a contextual analysis of the conditions and processes involved in the phenomenon under study. A comparative case study is an appropriate research methodology to explore new multi-faceted concepts with limited empirical evidence.

The results confirm previous studies that nonsovereign SITEs have a distinctive overdrive toward tourism specialization. Moreover, the findings indicate that overtourism is driven by both global and domestic policy factors and generates significant economic volatility, social inequality and ecological stress. The paper discusses the tourism policy implications of the evolving economic disconnectedness, environmental decay and social tensions in SITEs in the Caribbean.

Policy recommendations are presented for transitioning toward a more inclusive development and strengthening the resilience of small island tourism development in the Caribbean.

On shield tunnel construction (STC) site, human error is widely recognized as essential to accident. It is necessary to explain which factors lead to human error and how these factors can influence human performance. Human reliability analysis supports such necessity through modeling the performance shaping factors (PSFs). The purpose of this paper is to establish and validate a PSF taxonomy for the STC context.

The approach taken in this study mainly consists of three steps. First, a description of the STC context is proposed through the analysis of the STC context. Second, the literature which stretch across the PSF methodologies, cognitive psychology and human factors of STC and other construction industries are reviewed to develop an initial set of PSFs. Finally, a final PSF set is modified and validated based on STC task analysis and STC accidents cases.

The PSF taxonomy constituted by 4 main components, 4 hierarchies and 85 PSFs is established for human behavior modeling and simulation under the STC context. Furthermore, by comparing and evaluating the performance of STC PSF and existing PSF studies, the proposed PSF taxonomy meets the requirement for qualitative and quantitative analysis.

The PSF taxonomy can provide a basis and support for human behavior modeling and simulation under the STC context. Integrating PSFs into a behavior simulation model provides a more realistic and integrated assessment of human error by manifesting the influence of each PSFs on the cognitive processes. The simulation results can suggest concrete points for the improvement of STC safety management.

This paper develops a taxonomy of PSFs that addresses the various unique influences of the STC context on human behaviors. The harsh underground working conditions and diverse resources of system information are identified as key characteristics of the STC context. Furthermore, the PSF taxonomy can be integrated into a human cognitive behavior model to predict the worker’s behavior on STC site in future work.

The purpose of this systematic review is to critically analyze pharmaceutical industry case studies on the implementation of Lean 4.0 methodologies to synthesize key lessons, benefits and best practices. The goal is to inform decisions and guide investments in related technologies for enhancing quality, compliance, efficiency and responsiveness across production and supply chain processes.

The article utilized a systematic literature review (SLR) methodology following five phases: formulating research questions, locating relevant articles, selecting and evaluating articles, analyzing and synthesizing findings and reporting results. The SLR aimed to critically analyze pharmaceutical industry case studies on Lean 4.0 implementation to synthesize key lessons, benefits and best practices.

Key findings reveal recurrent efficiency gains, obstacles around legacy system integration and data governance as well as necessary operator training investments alongside technological upgrades. On average, quality assurance reliability improved by over 50%, while inventory waste declined by 57% based on quantified metrics across documented initiatives synthesizing robotics, sensors and analytics.

As a comprehensive literature review, findings depend on available documented implementations within the search period rather than direct case evaluations. Reporting bias may also skew toward more successful accounts.

Synthesized implementation patterns, performance outcomes and concealed pitfalls provide pharmaceutical leaders with an evidence-based reference guide aiding adoption strategy development, resource planning and workforce transitioning crucial for Lean 4.0 assimilation.

This systematic assessment of pharmaceutical Lean 4.0 adoption offers an unprecedented perspective into the real-world issues, dependencies and modifications necessary for successful integration, absent from conceptual projections or isolated case studies alone until now.

Project-driven supply chain risks pose a significant threat to the success of complex development projects, in terms of achieving key performances such as quality, time and efficiency. The purpose of this paper is to adopt a supply chain quality perspective in order to explore and better understand the unique attributes of risks associated with project-driven supply chains for continuously improving the quality of both processes and products.

Theoretically grounded in the framework of Bayesian Belief Networks and Game theory, this paper develops a structured process for assessing and managing risks in project-driven supply chains. The application of the proposed approach is demonstrated through a simulation case study conducted on the development project of Boeing 787 aircraft.

The conflicting incentives amongst stakeholders in a supply chain can jeopardise the success of a project and therefore, assessment of this category of risks classified as “Game theoretic risks” needs special consideration. Project-driven supply chain risks pose a significant threat to the success of complex projects. The results of the study clearly revealed that without mitigating the game theoretic risks, the main objective of timely completion of the Boeing 787 project was not materialised. Further, the lack of management expertise was the major factor contributing to the overall project costs including cost of quality.

The proposed process and analyses present a significant and original insight in terms of capturing the key determinants of both product and service quality such as product performance, convenience and reliability of service, timeliness, ease of maintenance, flexibility, and customer satisfaction and comfort. Propositions are developed for ascertaining the significance of information sharing in a project-driven supply chain, and a fair sharing partnership is introduced to help supply chain managers in managing game theoretic risks in order to achieve the goals of quality, time and efficiency.

Data represents a critical resource that enables construction companies’ success; thus, its management is very important. The purpose of this study is to assess the benefits of construction data risks management (DRM) in the construction industry (CI).

This study adopted a quantitative method and collected data from various South African construction professionals with the aid of an e-questionnaire. These professionals involve electrical engineers, quantity surveyors, architects and mechanical, as well as civil engineers involved under a firm, or organisation within the province of Gauteng, South Africa. Standard deviation, mean item score, non-parametric Kruskal–Wallis H test and exploratory factor analysis were used to analyse the retrieved data.

The findings revealed that DRM enhances project and company data availability, promotes confidentiality and enhances integrity, which are the primary benefits of DRM that enable the success of project delivery.

The research was carried out only in the province of Gauteng due to COVID-19 travel limitations.

The construction companies will have their data permanently in their possession and no interruption will be seen due to data unavailability, which, in turn, will allow long-term and overall pleasant project outcomes.

This study seeks to address the benefits of DRM in the CI to give additional knowledge on risk management within the built environment to promote success in every project.