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The mega railway infrastructure projects are faced with complex environments and multi-level management challenges. Thus, the mega railway infrastructure project management system not only needs to focus on its composition, but also needs to consider changes and impacts of internal and external environment.

This study attempts to introduce the concept of dissipative structure from the perspective of complexity theory and constructs a positive entropy and negentropy flow index system for mega railway infrastructure project management system in order to analyze the factors of management system more deeply. The Brusselator model is used to construct the structure of the mega railway infrastructure project management system, and the entropy method is used to calculate the positive entropy and negentropy values to verify whether the management system is a dissipative structure.

A plateau railway project in China was used as an example for an empirical study, not only its own characteristics are analyzed, but also the role of constraints and facilitation of the internal and external environment. Based on the research results, several effective suggestions are put forward to improve the stability and work efficiency of mega railway infrastructure project management system.

This study demonstrates that mega railway infrastructure project management system has the characteristics of dissipative structure. It can provide theoretical support for the development of mega railway infrastructure project management system from disorderly state to orderly state.

Recent United Nations Climate Change Conferences recognise extreme climate change of heatwaves, floods and droughts as threatening risks to the resilience and success of public–private partnership (PPP) infrastructure projects. Such conferences together with available project reports and empirical studies recommend project managers and practitioners to adopt smart technologies and develop robust measures to tackle climate risk exposure. Comparatively, artificial intelligence (AI) risk management tools are better to mitigate climate risk, but it has been inadequately explored in the PPP sector. Thus, this study aims to explore the tools and roles of AI in climate risk management of PPP infrastructure projects.

Systematically, this study compiles and analyses 36 peer-reviewed journal articles sourced from Scopus, Web of Science, Google Scholar and PubMed.

The results demonstrate deep learning, building information modelling, robotic automations, remote sensors and fuzzy logic as major key AI-based risk models (tools) for PPP infrastructures. The roles of AI in climate risk management of PPPs include risk detection, analysis, controls and prediction.

For researchers, the findings provide relevant guide for further investigations into AI and climate risks within the PPP research domain.

This article highlights the AI tools in mitigating climate crisis in PPP infrastructure management.

This article provides strong arguments for the utilisation of AI in understanding and managing numerous challenges related to climate change in PPP infrastructure projects.

This study aims to use social media data mining to revitalize and support existing urban infrastructure monitoring strategies by extracting valuable insights from public opinion, as current strategies struggle with issues such as adaptability to changing conditions, public engagement and cost effectiveness.

Twitter messages or “Tweets” about public infrastructure in the Philippines were gathered and analyzed to discover reoccurring concerns in public infrastructure, emerging topics in public debates and the people’s general view of infrastructure services.

This study proposes a topic model for extracting dominating subjects from aggregated social media data, as well as a sentiment analysis model for determining public opinion sentiment toward various urban infrastructure components.

The findings of this study highlight the potential of social media data mining to go beyond the limitations of traditional data collection techniques, as well as the importance of public opinion as a key driver for more user-involved infrastructure management and as an important social aspect that can be used to support planning and response strategies in routine maintenance, preservation and improvement of urban infrastructure systems.

The purpose of this study is to explore how digital construction policy (DCP) drives enterprise green innovation (EGI) from an information processing theory (IPT) perspective, including the mediating mechanisms of market information accessibility and operational risk, the moderating role of intellectual property protection (IPP) and product market competition (PMC) and the heterogeneous effects of ownership, Internet development and managerial ability.

Based on the matched panel data of A-share listed enterprises from 2011 to 2019 and the Broadband China policy as a quasinatural experiment, this study investigates the impact of DCP on EGI by constructing a multi-time point difference-indifferences (DID) model.

Digital construction policies can significantly promote EGI. DCP works in two fundamental ways, namely by increasing market information accessibility and reducing operational risk. IPP and PMC significantly increased the contribution of digital construction policies to EGI. Heterogeneity analysis found that digital technology has a stronger promotion effect for SOEs, high-managerial-ability enterprises and enterprises in regions with low Internet development levels.

The study provides new insights about the antecedents of EGI from a DCP perspective. It also enlightens emerging economies to actualize green innovation under the digital wave.

From the perspective of IPT, this study explains the mechanism of DCP-driven EGI. It enhances understanding of the relationship between DCP and EGI.

Implementing blockchain in sustainable development goals (SDGs) and environmental, social and governance (ESG)-aligned infrastructure development involves intricate strategic factors. Despite technological advancements, a significant research gap persists, particularly in emerging economies. This study aims to address the challenges related to SDGs and ESG objectives during infrastructure delivery remain problematic, identifying and evaluating critical strategic factors for successful blockchain implementation.

This study employs a three-stage methodology. Initially, 13 strategic factors are identified through a literature review and validated by conducting semi-structured interviews with six experts. In the second stage, the data were collected from nine additional experts. In the final stage, the collected data undergoes analysis using interpretive structural modeling (ISM)–cross-impact matrix multiplication applied to classification (MICMAC), aiming to identify and evaluate the independent and dependent powers of strategic factors driving blockchain implementation in infrastructure development for SDGs and ESG objectives.

The study’s findings highlight three significant independent factors crucial for successfully integrating blockchain technology (BT) into infrastructure development for SDGs and ESG goals: data security (F4), identity management (F8) and supply chain management (F7). The study unravels these factors, hierarchical relationships and dependencies by applying the MICMAC and ISM techniques, emphasizing their interconnectedness.

This study highlights critical strategic factors for successful blockchain integration in SDG and ESG-aligned infrastructure development, offering insights for policymakers and practitioners while emphasizing the importance of training and infrastructure support in advancing sustainable practices.

The implementation of smart maintenance (SM) has greatly benefited facility managers, construction project managers and other stakeholders within the built environment. Unfortunately, its actualization for stakeholders in the built environment in the fourth industrial revolution (4IR) era remains a challenge. To reduce the challenge, this study aims at conducting a bibliometric analysis to unearth the critical success factors supporting SM implementation. The future direction and practice of SM in the construction industry were also explored.

A bibliometric approach was adopted for reviewing articles extracted from the Scopus database. Keywords such as (“smart maintenance“) OR (“intelligent maintenance”) OR (“technological maintenance”) OR (“automated maintenance”) OR (“computerized maintenance”) were used to extract articles from the Scopus database. The studies were restricted between 2006 and 2021 to capture the 4IR era. The initial extracted papers were 1,048; however, 288 papers were selected and analysed using VOSviewer software.

The findings revealed that the critical success factors supporting the implementation of SM in the 4IR era are collaboration, digital twin design, energy management system and decentralized data management system. Regarding the future practice of SM in the 4IR era, it was also revealed that SM is possible to evolve into maintenance 4.0. This will support the autonomous maintenance of infrastructures in the built environment.

The use of a single database contributed to the limitation of the findings from this study.

Despite the limitations, the findings of this study contributed to practice and research by providing stakeholders in the built environment with the direction of SM practice.

Stakeholders in the built environment have clamoured to implement SM in the 4IR era. This study provided the critical success factors for adopting SM, guaranteeing the 4IR era. It also provides the research trends and direction of SM practice.

The factors for higher education institutions’ (HEIs) project management failure have been studied for several years. One of the issues is a lack of tools to combine their knowledge infrastructure capabilities (KIC) with project management (PM) to examine these infrastructures and monitor maturity. There are several project management maturity (PMM) models available. However, there are just a few empirical studies that support the three knowledge infrastructure capabilities and PMM integrations. As a result, the current research aims to suggest a new conceptual model, KIC-knowledge management (KM), and assess a research model that includes the three knowledge infrastructure capabilities as a prerequisite to elevate the PMM.

Partial least squares structural equation modeling (PLS-SEM) is used to evaluate the proposed research model. The study’s hypotheses were also examined using a sample of 352 respondents from PM departments at ten Yemeni public universities.

The study found that if the three key knowledge infrastructure capabilities integrate into the PMs, then it will help HEIs to perform project tasks more effectively and efficiently. Also, it will improve the PM maturity level if all the three capabilities positively effect PMM.

The study findings cannot be generalized to other industries because the collected date were with the Yemeni public universities’ context. Also, the new proposed model can be assessed in various sectors to increase the validity of the model. One more thing, future academics can conduct qualitative research study to validate again the proposed model.

Project managers can develop and improve their organization’s effectiveness and performance by focusing on these findings and using the developed model. Also, the findings of this study can be used as a benchmark for evaluating initiatives and knowledge-based governmental entities.

It is an opportunity for knowledge-based governmental entities particularly and other organizations to elevate most of projects to achieve a supreme level of maturity. Also, this study will assist employees to understand the relationship between KICs and projects within HEIs in Yemen.

This paper is among the first to empirically study the impact of the three knowledge infrastructure capabilities toward PMM. It links between two important domains: KM and PM.

The purpose of this study is to develop a decision-support framework that can be used by decision-makers to suspend public infrastructure projects. Additionally, the study also investigates how to select the most convenient infrastructure project for suspension.

The proposed framework includes an extensive set of factors and a novel comparison mechanism that can reveal the most convenient infrastructure project to be suspended. A comprehensible literature review and focus group discussion (FGD) sessions were conducted to identify factors that should be considered for suspension. Then, the neutrosophic analytic hierarchy process (N-AHP) method was used to determine the relative importance of the factors. Finally, the proposed comparison mechanism was demonstrated through a hypothetical case study and Technique for order of preference by similarity to ideal solution (TOPSIS) analysis.

Results showed that suspension decisions cannot be made merely based on “financial” factors. Instead, the other aspects, namely “Technical and managerial” and “Social and Environmental”, should also be taken into consideration. Second, factors related to the initial investment, cost of refinancing, cash flow, permits and approvals, insufficiency of bidders, degradation of the components, reputation, impact on stakeholders and criticality of the infrastructure were particularly elaborated as the most significant, needing the utmost attention of the decision-makers. Lastly, the results demonstrated that the proposed comparison mechanism has considerable potential to identify the most convenient infrastructure project for suspension.

Public infrastructure projects are often under pressure due to the inflationary state and economic stagnation of countries after major crises. The suspension decision for infrastructure projects necessitates comprehensible assessments to consider all consequences. Studies have widely investigated the contractual and legal aspects of project suspension in light of existing literature. However, little effort has been devoted to identifying the factors that decision-makers should consider before suspending a particular infrastructure project. Furthermore, existing literature does not investigate how to select the most convenient infrastructure project for suspension either. Thus, by developing a specific suspension framework for infrastructure projects by considering various factors, this study is the earliest attempt to examine the contract suspension mechanism of public infrastructure projects. In this respect, the study significantly contributes to the theory of contract management domain and has important managerial implications.

The need for infrastructure is growing as urbanization picks up speed, and the infrastructure REITs financing model has been crucial in reviving the vast infrastructure stock, alleviating the pressure on government funds and diversifying investment entities. This study aims to propose a framework to better assess the risks of infrastructure REITs, which can serve for the researchers and the policy makers to propose risk mitigation strategies and policy recommendations more purposively to facilitate successful implementation and long-term development of infrastructure REITs.

The infrastructure REITs risk evaluation index system is established through literature review and factor analysis, and the optimal comprehensive weight of the index is calculated using the combination weight. Then, a risk evaluation cloud model of infrastructure REITs is constructed, and experts quantify the qualitative language of infrastructure REITs risks. This paper verifies the feasibility and effectiveness of the model by taking a basic REITs project in China as an example. This paper takes infrastructure REITs project in China as an example, to verify the feasibility and effectiveness of the cloud evaluation method.

The research outcome shows that infrastructure REITs risks manifest in the risk of policy and legal, underlying asset, market, operational and credit. The main influencing factors in terms of their weights are tax policy risk, operation and management risk, liquidity risk, termination risk and default risk. The financing project is at a higher risk, and the probability of risk is 64.2%.

This research contributes to the existing body of knowledge by supplementing a set of scientific and practical risk evaluation methods to assess the potential risks of infrastructure REITs project, which contributes the infrastructure financing risk management system. Identify key risk factors for infrastructure REITs with underlying assets, which contributes to infrastructure REITs project management. This research can help relevant stakeholders to control risks throughout the infrastructure investment and financing life cycle, provide them with reference for investment and financing decision-making and promote more sustainable and healthy development of infrastructure REITs in developing countries.

The education services sector faces ever-changing global market dynamics with creative disruptions. Building knowledge brands can push the higher education sector beyond its geographical boundaries into the global arena. This study aims to identify key constructs, their theoretical background and dimensions that aid in building a global knowledge brand. The authors' research focuses on adapting and validating scales for global knowledge and education services brands from well-established academic literature.

The authors have adopted a mixed methodology approach and a systematic literature review. Authors interviewed 18 subject matter experts as part of content and face validity to arrive at select constructs, dimensions and items. Quantitative methods with random sampling were adopted as the primary methodology. Initially, the survey was administered to 390 students to test preliminary results. The survey was also administered to 5,112 students at a later part of this study. Valid responses stood at 3,244 with a 63% response rate. Further, the authors conducted confirmatory factor analysis, exploratory factor analysis and structural equation modeling to test the reliability and validity of scales. This study analyzed composite reliability, convergent validity and discriminant validity to finalize items for scales. The authors also validated the hypotheses based on the discriminant validity assessment scores.

Authors' key research findings are that academic stimulus, campus infrastructure and student intent play a significant role in campus culture and events design and experience at campus. Authors were able to bring out 16 key constructs and 55 critical dimensions vital to global education services brand building. This study also adapted and validated 99 items that meet construct validity and composite reliability criteria. This study also highlights that constructs such as student intent, academic stimulus, campus infrastructure scalability, selection mechanism, pedagogical content knowledge, brand identity, events experience and campus culture play a vital role in global brand recognition.

The authors' work is fairly generalizable to education services and the higher education sector. However, this study must be extrapolated and empirically validated in other industry sectors. The research implications of this study are that it aided the authors in building theoretical background for student brand loyalty theory, student expectation theory and study loyalty theory. This study adds to the body of knowledge by contributing to theoretical concepts on students, knowledge culture, events, infrastructure and branding. Researchers can adopt the scales proposed in this study to build research models in higher education branding. This study acts as a catalyst for building theories in education services areas. Researchers can delve deep into proposed research aspects of campus infrastructure, knowledge infrastructure, campus knowledge culture, events design and events experience.

This study aids educators and brand managers to develop global education services and optimize their effort and budget. Administrators in the education services sector must focus on practical aspects of student perception, campus infrastructure, culture and events experience. Practically administrators can reorient their efforts based on this study to achieve global brand recognition.

This study highlights that students are not customers but are co-creators of value in the education sector. This study provides scales and dimensions needed to build co-creation frameworks and models.

Most research in higher education branding has not covered wider aspects of global brand building. Existing theories proposed in higher education and education services articles cover only narrower aspects of campus infrastructure, culture, events design and branding. This study presents a comprehensive list of critical factors that play a vital role in global knowledge brand building. This study highlights the constructs and scales integral to building a global education services brand.