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Evaluating project success within the construction industry presents challenges due to the unique characteristics of the sector, the complexity of projects, and the involvement of diverse stakeholders. Conducting a bibliometric analysis, this paper aims to unravel the major research themes and methodologies utilised by researchers in studying the critical success criteria for construction projects, as well as extracting these success criteria.

The researchers systematically searched and screened 95 papers from Scopus and Web of Science (WoS) databases. This study conducted research focus parallelship network (RFPN) analysis and keywords co-occurrence network (KCON) analysis using BibExcel and Gephi to cluster the papers, illuminate the relationships among keywords within each cluster, and identify the primary research directions.

Using the RFPN analysis, this study classified the papers into three distinct clusters: infrastructure and public projects success, risk and knowledge management, and contractors and procurement management. Statistical techniques such as structural equation modelling (SEM) and multi-criteria decision-making methods such as analytic hierarchy process (AHP) have been used to analyse project success in the construction industry.

Considering the intensified demand for streamlined digital interactions and the increasing emphasis on sustainability and safety performance, construction companies are recommended to allocate greater investments toward the automation and digitisation of their products and processes. Prioritising modular construction and embracing transformative technologies alongside data science is crucial for enabling well-informed decision-making, and enhancing project success.

This study contributes to the existing body of knowledge by conducting a quantitative and systematic evaluation of the literature on project success criteria in the construction industry and uncovering key research areas. It addresses the pressing need to understand the complexities of construction projects amidst evolving industry dynamics and emerging disruptions. Moreover, by highlighting the implications of digital innovations and modular construction, this study urges deeper exploration into their impact on project performance and stakeholder satisfaction. This research sets a comprehensive framework for investigating the interplay between project complexity, technological advancements, and sustainable practices in the construction sector, paving the way for strategic advancements in the field.

Despite unanimity in the literature that eco-innovation (EI) leads to sustainable development, evidence remains limited on measuring EI efficiency with the Malmquist productivity index (MPI). In conventional data envelopment analysis (DEA) models, decision-making units (DMUs) are inclined to assign more favorable weights, even zero, to the inputs and outputs to maximize their own efficiency. This paper aims to overcome this shortcoming by developing a common set of weights (CSW).

Using goal programming, this study develops a CSW model to evaluate the EI efficiency of the organization for economic co-operation and development (OECD) countries and track their changes with MPI during 2010–2018.

Achieving a complete ranking of DMUs, findings show the higher discrimination power of the proposed CSW compared with the original DEA models. Furthermore, results reveal that Iceland, Latvia and Luxembourg are the only OECD countries that have incessantly improved their EI productivity (MPI > 1) from 2010 to 2018. On the other hand, Japan is the OECD country that has experienced the highest yearly EI efficiency during 2010–2018. This paper also found that Iceland has the highest MPI over 2010–2018.

More investment in environmental research and development (R&D) projects instead of generic R&D enables OECD members to realize more opportunities for sustainable development through minimizing energy use and environmental pollution in any form of waste and greenhouse gas emissions.

In addition to developing a novel common weights model for DEA-MPI to measure and evaluate the EI of OECD countries, this paper develops a CSW model by including the undesirable outputs for EI analysis.

Universities play a central role in scientific development and progress in societies, so, the need for supporting new businesses in universities becomes very important that science and technology park-based incubators can meet it. The purpose of this paper is to prioritize the factors influencing strategic management of university business incubators (UBIs).

Present research prioritizes the factors influencing strategic management of incubators using analytic network process (ANP). The authors gathered data from UBIs affiliated with science and technology park of Guilan, located in city of Rasht (Iran) using the ANP questionnaire during year 2017.

Factors influencing strategic management of incubators comprised of four main criteria and 14 sub-criteria. The criteria and sub-criteria were ranked based on their importance. Results show that “talented managers” has the highest importance for strategic management of UBIs.

This study offers a novel analysis and contribution to the knowledge of ranking UBIs with a multi-criteria decision-making technique. Results of this research show the relative importance of criteria and sub-criteria, which contributes to further improvement of incubator management. University managers and incubator directors can utilize the findings for better resource allocation and aligning the strategies of incubators with macro strategies of the country.

The global construction industry has a history of poor project success, with evident and frequent overruns in cost and schedule. This industry is a highly interconnected and complex system in which the components, i.e. suppliers, contractors, end-users, and stakeholders, are delicately linked to each other, the community, and the environment. Therefore, defining and measuring project success can be challenging for sponsors, contractors, and the public. To address this issue, this study develops and analyzes a more comprehensive set of success criteria for medium and large construction projects.

After reviewing the existing literature, this study identified 19 success criteria for medium and large construction projects, which were categorized into five groups. The fuzzy decision-making trial and evaluation laboratory (fuzzy DEMATEL) method was used to gain further insight into the interrelationships between these categories and explain the cause-and-effect relationships among them. Next, this study applied the modified logarithmic least squares method to determine the importance weight of these criteria using the fuzzy analytic hierarchy process.

28 project managers working in the construction industries in Australia and New Zealand participated in this study. Results suggest that “project efficiency” and “impacts on the project team” are cause criteria that affect “business success,” “impacts on stakeholders,” and “impacts on end-users.” Effective risk management emerged as the most crucial criterion in project efficiency, while customer satisfaction and return on investment are top criteria in “impacts on end-users” and “business success.”

Although numerous studies have been conducted on project success criteria, multicriteria analyses of success criteria are rare. This paper presents a comprehensive set of success criteria tailored to medium and large construction projects. The aim is to analyze their interrelationships and prioritize them thoroughly, which will aid practitioners in focusing on the most important criteria for achieving higher success rates.

This paper systematically evaluates the existing literature of innovations in freight transport, including all modes, to uncover the key research themes and methodologies employed by researchers to study innovations and their implications in this industry. It analyses the role of transport and the impact of innovations during crises, such as COVID-19.

Qualitative and quantitative analysis of the innovations in freight transport unravels the pre-requisites of such endeavours in achieving a resilient and sustainable transport network that effectively and efficiently operates during a crisis. The authors performed keyword co-occurrence network (KCON) analysis and research focus parallelship network (RFPN) analysis using BibExcel and Gephi to determine the major resulting research streams in freight transport.

The RFPN identified five emerging themes: transport operations, technological innovation, transport economics, transport policy and resilience and disaster management. Optimisation and simulation techniques, and more recently, artificial intelligence and machine learning (ML) approaches, have been used to model and solve freight transport problems. Automation innovations have also penetrated freight and supply chains. Information and communication technology (ICT)-based innovations have also been found to be effective in building resilient supply chains.

Given the growth of e-commerce during COVID-19 and the resulting logistics demand, along with the need for transporting food and medical emergency products, the role of automation, optimisation, monitoring systems and risk management in the transport industry has become more salient. Transport companies need to improve their operational efficiency using innovative technologies and data science for informed decision-making.

This paper advises researchers and practitioners involved in freight transport and innovation about main directions and gaps in the field through an integrated approach for evaluating research undertaken in the area. This paper also highlights the role of crisis, e.g. COVID-19, and its impacts on freight transport. Major contributions of this paper are as follows: (1) a qualitative and quantitative, systematic and effective assessment of the literature on freight transport through a network analysis of keywords supplemented by a review of the text of 148 papers; (2) unravelling major research areas; (3) identifying innovations in freight transport and their classification as technological and non-technological and (4) investigating the impact of crises and disruptions in freight transport.