Given its insular geographic location, Taiwan inherently benefits from a natural advantage in developing its shipping industry, positioning it as a critical sector for the nation’s economic advancement. The shipping industry operates within a highly competitive maritime market, wherein ocean freight forwarders provide services on a global scale, thus classifying them within the international transportation and logistics industry. The global competition from logistics peers renders the services highly substitutable. This study breaks new ground by integrating the SERVQUAL scale with advanced methodologies such as the Analytic Hierarchy Process (AHP) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) to assess and enhance service quality in the shipping industry. By segmenting the five dimensions of SERVQUAL, the study delineates 19 specific evaluation indicators. The expert questionnaires developed and analyzed through AHP and DEMATEL reveal a previously unidentified link between specific service quality dimensions and customer satisfaction. The findings from this analysis offer crucial insights into the critical success factors (CSFs) of service quality and their causal interrelationships, thereby establishing a model for service standards. By leveraging the identified CSFs and understanding the causal relationships among these key factors, ocean freight forwarders can enhance and optimize their value propositions and resources. This proactive approach is expected to significantly improve service quality, fortify core competitiveness, and elevate customer support and satisfaction levels, ultimately leading to an increased market share and ensuring sustainable business operations.

Implementing green retrofitting can save 50–90% of energy use in buildings built worldwide. Government policies in several developed countries have begun to increase the implementation of green retrofitting buildings in those countries, which must rise by up to 2.5% of the lifespan of buildings by 2030. By 2050, it is hoped that more than 85% of all buildings will have been retrofitted. The high costs of implementing green retrofitting amounting to 20% of the total initial construction costs, as well as the uncertainty of costs due to cost overruns are one of the main problems in achieving the implementation target in 2050. Therefore, increasing the accuracy of the costs of implementing green retrofitting is the best solution to overcome this. This research is limited to analyzing the factors that influence increasing the accuracy of green retrofitting costs based on WBS, BIM, and Information Systems. The results show that there are 10 factors affecting the cost accuracy of retrofitting or customizing high-rise office buildings, namely Energy Use Efficiency, Water Use Efficiency, Use of Environmentally Friendly Materials, Maintenance of Green Building Performance during the Use Period, Initial Survey, Project Information Documents, Cost Estimation Process, Resources, Legal, and Quantity Extraction applied. These factors are shown to increase the accuracy of green retrofitting costs.

eGovernment projects are capital intensive and have high probability of failure because of the dynamic and technological laden environment in which they operate. The number of skilled labour and technicalities required are often not available in quantity needed to sustain such project. There is always the need to have in place adequate risk assessment framework to guide the execution and monitoring of eGovernment projects. Several studies have been conducted on the critical success factors relating to risk assessment of eGovernment projects to understand the reasons for the high rate of failure. Therefore, there is need to review these articles and categorize them into different research domain in project risk assessment so as to reveal domain with more or less research and those that need to understand the future research directions in risk assessment for eGovernment projects. Using the positivism paradigm, this study utilized the Systematic Literature Review methodology to collect 147 articles from the following academic databases namely IEEE, Preprints, WorldCat Discovery, ArXiv. Ohio-state University databases, Science Direct, Scopus, ACM, NWU digital library, Usenix, Jise database, Sagepub, MDPI Academia published between 2013 to 2023. Different inclusion and exclusion criteria were applied pruning to 48 articles that were used for the study. The results show the classification of articles in risk assessment for eGovernment projects into those that discusses project analysis, review, framework, maturity and model tools, implementation, and integration, applied methodology and evaluation with the percentage of articles published in each domain with the past 10 years. The various critical success factors that should be considered in the development of a robust risk assessment framework were discussed and future research directions in eGovernment risk assessment were given based on the reviews.

The artificial intelligence (AI)-based architect’s profile’s selection (simply iSelection) uses a polymathic mathematical model and AI-subdomains’ integration for enabling automated and optimized human resources (HR) processes and activities. HR-related processes and activities in the selection, support, problem-solving, and just-in-time evaluation of a transformation manager’s or key team members’ polymathic profile (TPProfile). Where a TPProfile can be a classical business manager, transformation manager, project manager, or an enterprise architect. iSelection-related selection processes use many types of artifacts, like critical success factors (CSF), AI-subdomain’ integration environments, and an enterprise-wide decision-making system (DMS). iSelection focuses on TPProfiles for various kinds of transformation projects, like the case of the transformation of enterprises’ HRs (EHR) processes, activities, and related fields, like enterprise resources planning (ERP) environments, financial systems, human factors (HF) evolution, and AI-subdomains. The iSelection tries to offer a well-defined (or specific) TPProfile, which includes HF’s original-authentic capabilities, education, affinities, and possible polymathical characteristics. Such a profile can also be influenced by educational or training curriculum (ETC), which also takes into account transformation projects’ acquired experiences. Knowing that selected TPProfiles are supported by an internal (or external) transformation framework (TF), which can support standard transformation activities, and solving various types of iSelection’s problems. Enterprise transformation projects (simply projects) face extremely high failure rates (XHFR) of about 95%, which makes EHR selection processes very complex.