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The purpose of this paper is twofold: first, to develop theoretical underpinnings using TCE, and second, to run the analysis using an advanced tool such as structural equation modeling (SEM).

This study was conducted in the construction industry in Tanzania. A questionnaire-based survey method was used. A total of 308 respondents participated in the study. The relationships between the cause and effect factors were analyzed using SEM.

The important findings are as follows:cost overrun can be explained by consultant-related and material-related factors; disputes can be explained by cost overrun; arbitration can be explained by consultant-related, cost overrun, and dispute factors; litigation can be explained by client-related, disputes, and arbitration factors; and abandonment can be explained by consultant-related, external-related, disputes, arbitration, and litigation factors.

The main contributions of this study are theoretical development and comprehensive analyses of “cause” and “effect” factors of delays in the construction industry.

Analyzing factors of delays in construction projects and determining their impact on project performance is necessary to better manage and control projects. Identification of root factors which may lead to project delay and increased cost is vital at the early or planning stage. Better identification of delay factors at the early stage can help the practitioners to reduce their impacts over the long run. Hence, the purpose of this paper is to propose an intelligent method to analyze causal relationships between delay factors in construction projects. The proposed approach is further validated by a real case study of the construction projects in West Azerbaijan province in Iran.

During the first phase, the fuzzy cognitive map (FCM) is drawn to indicate the causal relationships between the delay factors and the evaluation factors. For this purpose, the causal relationships between 20 delay factors and four evaluation factors are considered. Afterward, the effect of each factor on management goals is evaluated by using a hybrid learning algorithm. Delay factors are further prioritized by applying fuzzy data envelopment analysis (FDEA). In the second phase, an interpretive structural modeling (ISM) is employed to determine the root causes of delay factors.

Results of the first phase show that “supervision technical weaknesses for overcoming technical and executive workshop problems” and “Inaccurate estimation of workload, required equipment and project completion time” are the most significant delay factors. In contrary, “non-use of new engineering contracts” has the lowest impact on the management goals. Meanwhile, the results of the second phase conclude that factors like “Inaccurate estimation of workload, required equipment and project completion time” “weakness of laws and regulations related to job responsibilities” and “lack of foreseen of fines and encouragements in the contracts” are the most significant root factors of delay in construction projects.

This paper integrates three methods including FCM method, FDEA and ISM. In the first phase, FCM is drawn according to the experts’ opinions and concerning management goals and delay factors. Later, these factors are prioritized according to the results of running the algorithm and using the FDEA model. The second phase, the seven-step in the ISM methodology, is done to identify the root factors. To ensure that the root factors of the delay are at a lower level of hierarchical structure, delay factors are partitioned by drawing the ISM model.

The execution of product recovery strategies and the definition of an adequate system to manage its performance are crucial to move toward the employment of a successful circular economy (CE) concept. Defining strategies for the efficient management of product recovery requires product data that is difficult to obtain, making it harder to handle. However, efficient product recovery management can play a key role in shifting companies from a linear economy model to a more sustainable CE model, providing economic benefits and increasing customer satisfaction by recovering and adding value to the discarded product. Therefore, this study aims to provide better models to support decision-making and to evaluate product recovery performance.

The present study highlights a comprehensive two-stage decision approach to identify and examine the relevant key performance indicators (KPIs) for performance improvement of an information facilitated product recovery system (IFPRS) in a CE context. In the first phase, a structural equation modeling (SEM) methodology is adopted to categorize the KPIs by employing exploratory factor analysis and measurement of the model fit is obtained using the confirmatory factor analysis. Further, in the second phase, the KPIs are ranked and prioritized on the basis of expert’s recommendations adopting fuzzy-technique for order of preference by similarity to ideal solution (FTOPSIS).

Empirical investigation is conducted by compiling data from an association of six decision-makers (DMs) and two DMs from a respective prospect. The results highlight that “Technology Capacity” is ranked as the highest and is the most prominent KPI for successful employment of IFPRS practices. The results of the study would benefit policy makers and company directors in the selection of KPIs based on their importance in a context of high competition and greater pressure to adopt sustainable practices in the management of their companies.

As far as the authors know, no study has been performed till date to identify and construct a structural KPIs model for IFPRS performance improvement in the context of CE. The paper, therefore, proposes a two-phase SEM-TOPSIS technique to measure the impact of KPIs which is a new integration in the existing literature. The results of the study would benefit policy makers and company directors in the selection of KPIs based on their importance in a context of high competition and greater pressure to adopt sustainable practices in managing their organizations.

The purpose of this research is to identify the most impactful delay risks in Australian construction projects, including the associations amongst those risks as well as the project phases in which they are most likely present. The correlation between project and organisational characteristics with the impact of delay risks was also studied.

A questionnaire survey was used to collect data from 118 delayed construction projects in Australia. Data were analysed to rank the most impactful delay risks, their correlation to project and organisational characteristics and project phases where those risks are likely to emerge. Association rule learning was used to capture associations between the delay risks.

The top five most impactful delay risks in Australia were changes by the owner, slow decisions by the owner, preparation and approval of design drawings, underestimation of project complexity and unrealistic duration imposed to the project, respectively. There is a set of delay risks that are mutually associated with project complexity. In addition, while delay risks associated with resources most likely arise in the execution phase, stakeholder and process-related risks are more smoothly distributed along all the project phases.

This research for the first time investigated the impact of delay risks, associations amongst them and project phases in which they are likely to happen in the Australian context. Also, this research for the first time sheds light on the project phases for the individual project delay risks which aids the project managers to understand where to focus on during each phase of the project.

The purpose of this paper is to systematically develop a delay risk terminology and taxonomy. This research also explores two external and internal dimensions of the taxonomy to determine how much the taxonomy as a whole or combinations of its elements are generalisable.

Using mixed methods research, this systematic literature review incorporated data from 46 articles to establish delay risk terminology and taxonomy. Qualitative data of the top 10 delay risks identified in each article were coded based on the grounded theory and constant comparative analysis using a three-stage coding approach. Word frequency analysis and cross-tabulation were used to develop the terminology and taxonomy. Association rules within the taxonomy were also explored to define risk paths and to unmask associations among the risks.

In total, 26 delay risks were identified and grouped into ten categories to form the risk breakdown structure. The universal delay risks and other delay risks that are more or less depending on the project location were determined. Also, it is realized that delays connected to equipment, sub-contractors and design drawings are highly connected to project planning, finance and owner slow decision making, respectively.

The established terminology and taxonomy may be used in manual or automated risk management systems as a baseline for delay risk identification, management and communication. In addition, the association rules assist the risk management process by enabling mitigation of a combination of risks together.

This study aims to determine and investigate the main causes of construction project delays. Construction projects are more intricate and associated with significant levels of risk owing to cost overruns. These overruns frequently lead to delays, incomplete work or other related challenges. Building delays are a prevalent problem in the building sector of developing nations. These delays prolong the duration of projects and result in increased costs and conflicts among stakeholders. A conceptual model consisting of the factors causing the delays in heating, ventilation and air conditioning (HVAC) projects was developed and tested in this study.

A comprehensive data collection process was undertaken. A meticulously designed survey was distributed to a diverse cohort of 294 participants, including contractors and sub-contractors from Chennai, Tamil Nadu. The data was collected using stratified sampling, ensuring a representative sample. The data was then analysed using ordinary least squares multiple regression.

The findings of this study have significant implications for the construction industry. They indicate that factors related to sales, clients, design, procurement, finance and labour all contribute to delays in HVAC projects. Understanding these factors can help stakeholders in the industry to better manage and mitigate project delays.

This study is unique because it is a perceptual study of stakeholders. It provides valuable information for analysing and assessing project performance by identifying the primary causes of HVAC project delays. To the best of the authors’ knowledge, the study conducted on HVAC projects is the first of its kind and hence makes a pivotal contribution to the literature on construction projects. Additionally, the study will assist policymakers and consultants in taking necessary steps to minimize delays.

The acknowledged mode of securing work by contractors is through the bidding process. However, the bidding decisions undertaken by some indigenous contractors in developing countries are fraught with challenges that often engender bidding practices (such as collusion through price fixing and intentional lower bidding) and threaten business survival. Therefore, in the quest to better understand these challenges and viable advocate solutions for overcoming them, this paper aims to identify the key challenges impacting the bid decision process by small indigenous building contractors in Dar es Salaam, Tanzania, and establish the strength of their relationship between the pairs of key challenges.

A comprehensive literature review was conducted to identify nine challenges impacting the bid decision of indigenous building contractors in Tanzania, which were used to design a questionnaire survey. Data collected were analysed using descriptive statistics, mean score, inferential statistics (One sample t-tests), Kendall’s concordance and correlation analysis.

Challenges identified from a literature review were empirically tested using survey responses accrued from 33 participating small indigenous building contractors in Dar es Salaam, Tanzania. The findings illustrate that lack of liquidity, profit returns, lack of equipment, lack of experience of several works and procurement procedures are perceived as being the five most critical challenges. Project location, site accessibility and lack of labour were least critical. The major finding from the correlation analysis was the existence of the strong and positive correlation between “project location” and “site accessibility”.

The study is limited by its sample and geographical settings which focussed and confined the results on one country, Tanzania. However, the findings can be considered as important for other developing countries wishing to gain insights into the challenges impacting bid decisions.

Measures for addressing the identified challenges impacting the bidding decisions of the indigenous small building contractors would be undertaken. The findings will enable contractors to not only reconcile the challenges with the industry and in so doing benefit both themselves and the clients but also enable them to be better prepared to deliver contractual obligations and generate socio-economic wealth. Government and policymakers will also be able to appropriately develop macro interventions for managing these challenges, which could be custom-tailored to indigenous small contractors. Finally, improving the ability of local firms to compete in the construction industry has been recognised as having the potential of advancing socio-economic development within the comity of developing countries.

The study enhances government, client and practitioners’ understanding of the challenges affecting the bidding practices among the indigenous building contractors in Tanzania. This area of investigation has previously been under explored particularly sub-Saharan Africa.

Claims are increasingly becoming a norm in construction projects and thus an area that is attracting interventions through researches. This paper aims to establish causes–effects relationship of claims in construction projects.

This is correlation study type of study that attempts to establish causes–effects relationship of claims in construction projects. Significant causes and effects of construction claims were determined using one-sample t-test. To establish the relationship, the significant causes and effects of construction claims were correlated using bivariate correlation analysis.

Among the significant causes, variations, change of scope of the project and delay in completion of works have high level of significant positive relationship with five to six other causes and positive relationship with multiple effects ranging from five to six. Besides, among significant effects, delay in completion and delivering of construction projects, poor contractual relationship among parties and extension of time have significant positive relationship with multiple causes.

The findings of this study are limited to causes-causes relationship and causes–effects relationship of claims in construction projects. This means effects–effects relationship was not covered that could be an important area to investigate as some of causes and effects are at times termed interchangeably.

With reference to previous studies which have focused on determining the causes and effects of construction claims, the findings of the current study have specific contribution on claims management as it divulges the causes of constructions claims that have multiplier effects to the project as a result of their linkage.

The paper unveils causes of claims with multiplier effects to construction projects for project participants to devise strategies to minimize and consequently eliminate them.