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Insufficient productivity development in the global and Finnish infrastructure sectors indicates that there are challenges in genuinely achieving the goals of resource efficiency and digitalization. This study adapts the approach of capability maturity model integration (CMMI) for examining the capabilities for productivity development that reveal the enablers of improving productivity in the infrastructure sector.

Civil engineering in Finland was selected as the study area, and a qualitative research approach was adopted. A novel maturity model was constructed deductively through a three-step analytical process. Previous research literature was adapted to form a framework with maturity levels and key process areas (KPAs). KPA attributes and their maturity criteria were formed through a thematic analysis of interview data from 12 semi-structured group interviews. Finally, validation and refinement of the model were performed with an expert panel.

This paper provides a novel maturity model for examining and enhancing the infrastructure sector’s maturity in productivity development. The model brings into discussion the current business logics, relevance of lifecycle-thinking, binding targets and outcomes of limited activities in the surrounding infrastructure system.

This paper provides a new approach for pursuing productivity development in the infrastructure sector by constructing a maturity model that adapts the concepts of CMMI and change management. The model and findings benefit all actors in the sector and provide an understanding of the required elements and means to achieve a more sustainable built environment and effective operations.

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.

By adopting the “hard” and “soft” project management (PM) approaches from the PM-literature, this paper aims to problematize the expected role of client organizations in driving innovation in the transport infrastructure sector.

Addressing a large public client in Sweden, a case study design was initially applied to provide in-depth insights and perspectives of client project managers’ views and experiences of managing projects expected to drive innovation. In this paper, the concepts of “hard” and “soft” are used to discuss empirical findings on challenges associated with adopting a PM-approach for driving innovation in projects. The empirical material consists of interview data, complemented with observations and archival data.

Findings reveal challenges associated with combining hard and soft approaches, frequently demonstrating difficulties in balancing short-term project expectations with the promotion of innovation. In line with the literature, project managers note that there is a need for soft approaches to promote development and drive innovation. Yet, findings reflect a situation in which operational success criteria predominate, whereas soft approaches are not sufficiently used to create the grounds required for fostering innovation.

Insights are provided into how PM-approaches may impact construction innovation in the infrastructure sector, demonstrating a need for further research on the challenges and implications of applying and combining hard and soft PM-approaches.

An increase in outsourcing of consultancy services has been observed during procurement and delivery of public-sector infrastructure projects. However, the incidence of project failure has continued unabated despite this shift by public-sector entities. Also, there appears to be limited literature focussed on seeking to provide the rationale governing the decision to outsource or insource consultancy services by public-sector organisations. The purpose of this study was to appraise the performance of public-sector projects in which consultancy services have been outsourced or insourced. These are the gaps which this study was undertaken to fill.

A grounded theory methodology (GTM) research design was adopted based on the nature of evidence sought and gathered from a Provincial Department of Public Works and Infrastructure (PDPWI) in South Africa. Data was obtained from a mixture of semi-structured interviews and project-specific documents spanning a five-year period and was analysed according to the procedures associated with GTM. Accordingly, open coding, axial coding and pattern matching were carried out at several intervals to develop categories and themes.

The findings of the study showed the absence of a structured approach within the PDPWI for facilitating decisions pertaining to outsourcing or insourcing consultancy services within construction projects. Furthermore, the study established that both approaches yielded similar results across all performance facets of cost, time and quality. In addition, a detailed insight into the steps required for the successful application of GTM in built environment research has been provided in the study.

Limited studies have been undertaken to compare the impact of either outsourced or insourced services on the organisational and project performance. This was the gap to which the study reported in this paper was undertaken to contribute.

Urban rail projects are typically large-scale transport infrastructure projects (megaprojects) which have many potential risks that can influence the strategic goals of owners. However, there is a paucity of studies which explore the impact of risks on both “urban rail” project time and cost together considering quantitative assessments. Therefore, this paper focuses on investigating critical risks and quantifying such risk impacts on urban railway project schedule and cost in practice.

A combination of qualitative and quantitative research methods comprising semi-interviews with five experts and a questionnaire survey of 132 professional respondents is used. The data were modeled using Monte Carlo Simulation to predict the probability of project schedule and cost.

The results show that 30 risk variables are categorized into seven main groups which have significant impacts on both project time and cost. Outstanding five risk variables were highlighted as follows: (1) project site clearance and land compensation; (2) design changes; (3) physical project resources; (4) contractors’ competencies and (5) project finance. Such findings were supported by Monte Carlo simulation which predicted in the worst case that the project may suffer 11.03 months’ delays and have cost overrun with a contingency of US$287.68 million.

This study expands our knowledge about time and cost contingency of urban metro railway implementation across developing economies and particularly within the context of Vietnam. Policymakers will not only gain an understanding about risk structure but will also recognize the significant impacts of critical risk through risk impact modeling and simulation. Such an approach provides insights into risk treatment priorities for planners so that they can proactively establish suitable strategies for risk mitigation in practice.

This study collected the bibliographic data of 2034 journal articles published in 2000–2021 from Web of Science (WoS) core collection database and adopted two bibliometric analysis methods, namely historiography and keyword co-occurrence, to identify the evolution trend of construction risk management (CRM) research topics.

CRM has been a key issue in construction management research, producing a big number of publications. This study aims to undertake a review of the global CRM research published from 2000 to 2021 and identify the evolution of the research topics relating to CRM.

This study found that risk analysis methods have shifted from simply ranking risks in terms of their relative importance or significance toward examining the interrelationships among risks, and that the objects of CRM research have shifted from generic construction projects toward specified types of construction projects (e.g. small projects, underground construction projects, green buildings and prefabricated projects). In addition, researchers tend to pay more attention to an individual risk category (e.g. political risk, safety risk and social risk) and integrate CRM into cost, time, quality, safety and environment management functions with the increasing adoption of various information and communication technologies.

This study focused on the journal articles in English in WoS core collection database only, thus excluding the publications in other languages, not indexed by WoS and conference proceedings. In addition, the historiography focused on the top documents in terms of document strength and thus ignored the role of the documents whose strengths were a little lower than the threshold.

This review study is more inclusive than any prior reviews on CRM and overcomes the drawbacks of mere reliance on either bibliometric analysis results or subjective opinions. Revealing the evolution process of the CRM knowledge domain, this study provides an in-depth understanding of the CRM research and benefits industry practitioners and researchers.

Present study aimed to integrate Geographic Information Systems (GIS) and Building Information Modeling (BIM) in conjunction with multicriteria decision-making (MCDM) to enhance infrastructure investment planning.

This analysis combines GIS databases with BIM simulations for a novel highway project. Around 150 potential alternatives were simulated, narrowed to 25 more effective routes and 3 options underwent in-depth analysis using PROMETHEE method for decision-making, based on environmental, cost and safety criteria, allowing for comprehensive cross-perspective comparisons.

A comprehensive framework proposed was validated through a case study. Demonstrating its adaptability with customizable parameters. It aids decision-making, cost estimation, environmental impact analysis and outcome prediction. Considering these critical factors, this study holds the potential to advance new techniques for assessment and planning railways, power lines, gas and water.

The study acknowledges limitations in GIS data quality, particularly in underdeveloped areas or regions with limited technology access. It also overlooks other pertinent variables, like social, economic, political and cultural issues. Thus, conclusions from these simulations may not entirely represent reality or diverse potential scenarios.

The proposed method automates decision-making, reducing subjectivity, aids in selecting effective alternatives and considers environmental criteria to mitigate negative impacts. Additionally, it minimizes costs and risks while demonstrating adaptability for assessing diverse infrastructures.

By integrating GIS and BIM data to support a MCDM workflow, this study proposes to fill the existing research gap in decision-making prioritization and mitigate subjective biases.

This paper aims to propose a new method to derive custom dynamic cyber risk metrics based on the well-known Goal, Question, Metric (GQM) approach. A framework that complements it and makes it much easier to use has been proposed too. Both, the method and the framework, have been validated within two challenging application domains: continuous risk assessment within a smart farm and risk-based adaptive security to reconfigure a Web application firewall.

The authors have identified a problem and provided motivation. They have developed their theory and engineered a new method and a framework to complement it. They have demonstrated the proposed method and framework work, validating them in two real use cases.

The GQM method, often applied within the software quality field, is a good basis for proposing a method to define new tailored cyber risk metrics that meet the requirements of current application domains. A comprehensive framework that formalises possible goals and questions translated to potential measurements can greatly facilitate the use of this method.

The proposed method enables the application of the GQM approach to cyber risk measurement. The proposed framework allows new cyber risk metrics to be inferred by choosing between suggested goals and questions and measuring the relevant elements of probability and impact. The authors’ approach demonstrates to be generic and flexible enough to allow very different organisations with heterogeneous requirements to derive tailored metrics useful for their particular risk management processes.

This study aims to investigate the influence mechanism of expatriates' cultural intelligence (CQ) on expatriate effectiveness (task performance and premature return intention), identifying work engagement as a mediator and cultural distance as a boundary condition.

Drawing on the conservation of resource theory and the person–environment fit (P–E fit) theory, a moderated mediation model is built. Working with a sample of 303 international construction expatriates collected by snowball sampling, the hypotheses are tested by using the structural equation model analysis.

Work engagement partially mediates the relationship between expatriates' CQ and task performance, as well as fully mediates the relationship between expatriates' CQ and premature return intention. Cultural distance moderates the positive relationship between CQ and work engagement, as well as moderates the mediating effects of work engagement.

The impacts of potential moderators (e.g. work–family conflict and organizational culture) on the relationship between CQ and expatriate effectiveness have not been considered in this study.

This study is useful for international construction firms to optimize the allocation of human resources.

This study contributes to the expatriate literature by adding empirical evidence to explain the influence mechanism of expatriates' CQ on expatriate effectiveness.

In comparison to other countries, power generation in Sub-Saharan Africa is poor. The demand for power has surged in recent times and continues to increase at a fast rate. The public–private partnership (PPP) model has been identified as an option to address the challenges in the power sector. The purpose of this research paper is to critically explore the reasons for entering into PPP power projects in Ghana by the public and private parties.

Questionnaires were used to elicit responses from respondents using a two-round Delphi survey. From 60 respondents contacted in round one, 48 responses were obtained, and these 48 respondents further took part in round two. Mean score ranking was used to rank the reasons for entering into PPP power projects, while analysis of variance (ANOVA) was run to test significant difference in perceptions among the respondents.

From round 2 of the Delphi survey, the significant reasons for public sector entering into PPP power projects were as follows: achieving improved value for money, access to additional capital, increased certainty of projects and greater efficiency of project delivery services. For private sector, most significant reasons were as follows: obtaining of investment support, improvement in private sector’s international image and synergy with public sector. From ANOVA analysis, there were significant different perceptions among some of factors on the respondent profile variables and the reasons for entering into PPP power projects, while other factors did not have significant different perception.

Significant reasons for both public and private sectors identified would be incorporated by the government when PPP policy guidelines and laws are reviewed. This will aid in the effective implementation of PPP for power projects.