Delay Causes and Emerging Digital Tools: A Novel Model of Delay Analysis, Including Integrated Project Delivery and PMBOK

: Delay is one of the main challenges of construction projects, and there is still much to overcome in order to reach near zero delay in all construction projects. This project aims to conduct a systematic critical review including a bibliography analysis on delay literature in construction. The main questions consider what has been learnt from a decade investigating delay causes and e ﬀ ects in the construction literature and what factors have been missed in the literature. This paper also presents a new and challenging question regarding how digital tools and associated technologies may prevent any delay in construction projects, which can change the research direction from delay investigations to identifying prevention factors. The paper identiﬁes the delay dataset, including 493 papers investigating delay in construction, and establishes a speciﬁc dataset of papers focusing on delay e ﬀ ects and causes (DEC), including 94 selected papers covering di ﬀ erent factors examined in over 29 countries such as Iran, India, Turkey, Bangladesh, Saudi Arabia,


Introduction
Disruptive technologies have been increasingly introduced to construction businesses in recent years, even though the industry continues to lag behind all other industries in its adoption of technology.However, there is not enough awareness of the current and best practices in project time management.The applications of these technologies for delay monitoring have not been fully examined regarding, for example, how intelligent or smart contracts can reduce disputes and delays in projects.While there is an urgent need to identify the application of new digital technologies and tools for preventing delay in a project, most papers still try to identify delay analysis techniques using the traditional approaches [1], such as conducting a survey including common factors determined many years ago [2,3].This paper aims to review the literature over the past decade and develop directions for future studies in delay investigations in construction projects.The main objectives of the paper are: to identify the delay effects and causes (DEC) dataset; to identify key critical factors causing delay in construction projects in the previous decade; to identify dominant methods used in the delay literature; to review the current digital technology capacity for preventing delay; and to identify deficiency areas, present a conceptual DEC model, and map the future directions.These objectives are important to project management scholars to base their future investigations on a comprehensive critical analysis of a one-decade endeavour of delay investigations in different countries.
Project managers are able to plan the construction sequence, monitor the status of project activities, and update the project progress to identify the project delays by using project controls software systems, particularly software that is professionally developed for project time and cost management.Specifically, project scheduling software systems are able to manage changes to the schedule baseline to accomplish the planned project completion data.However, site logs in construction projects or periodical progress reports (e.g., daily or weekly) are required to capture the status of the project as an input into the project scheduling software.Applications or platforms developed for project time management are instrumental tools for evaluating the project deviation from the planned baseline.Project scheduling software can be used to compare the actual project progress compared to the planned baseline.The actual start and finish dates for project activities form the basis for actual progress calculations and document the as-built schedule information.Project scheduling software monitors the progress of all the project's activities with the order of the critical path, the near-critical path, and the non-critical path activities to evaluate the impact of delay on project schedule.If critical path activities slip, they immediately cause project delay.The components of a project schedule can be monitored by a variety of techniques such as float dissipation or erosion of float, missed start and finish dates, actual duration analysis, and earned value management using a project controls software system.Project scheduling software predominantly uses the critical path method (CPM) for its scheduling practice.Its use is often the focus of contract claims due to project time impacts and delays to the contract completion date.Schedule progress is measured against the contract planned dates.The baseline is an important reference in all scheduling software if contract and progress delay disputes arise between stakeholders involved in projects.A baseline is a complete copy of a project plan that we can compare to the current schedule to evaluate progress in all scheduling software.As a project progresses, certain types of project data are likely to change.When a project is in progress and data changes, the original baseline created for the project may not accurately measure performance against the current project.Empirical evidence suggests that, during these events, the project schedule needs to be re-baselined to reflect the revised plan to achieve the estimated completion date.Likewise, creating a new baseline may not yield accurate results for measuring performance, because some data change during the life of the project, which should be measured against the original project data [4].
109 senior leaders of public and private organisations from across the globe, 26% from public bodies such as government agencies with the remainder represented by private enterprises [23] (1) Just 25% of construction projects came within 10% of their original deadlines [23] Philippines: 2010-2017; public-private partnership (PPP) projects 92.8% of projects were delayed [24].
Kuwait: 1990-2000; private residential housing projects [39] 56% of projects were delayed, approximately 54% were delayed for four months or more, and 30% were delayed for more than six months [39].
Western Canada: civil, institutional, high rise apartment building, and petrochemical Several cases of 24 projects were delayed more than 100% of contract duration [44].Indonesia 38% of projects were delayed [37].
Projects of 20 nations (Europe, North America, and other); during last 70 years; rail, fixed link (bridges and tunnels), and road Time and cost overruns were, on average, 70% and 28%, respectively [45,46].
Rich democracies (Denmark, Germany, Japan, South Korea, Netherlands, Norway, Spain, Sweden, UK, and US); during last three decades; infrastructure projects Average schedule overrun of projects was 42.7% [47].
This paper first systematically identifies articles investigating delay and time overrun in construction and then conducts a content analysis to review relevant articles in detail and provide a comprehensive understanding of the current literature.Finally, it identifies the gap in the literature and suggests future studies.

Review Method
Based on the initial review of the current practices in the literature, a set of strings was developed to select the final search criteria.The search string was selected as "delay overrun" or "time overrun" and "construction industry" or "construction project" and applied on the Scopus database, which resulted in 493 records using the search criteria, as shown in Appendix A.
The search was limited to articles investigating causes and effects in the past ten years, from 2009 to 2018.Therefore, "cause" and "effect" were also included in the search criteria.Applying the criteria resulted in developing the delay effects/causes (DEC) database in construction with 94 records using the search criteria shown in Appendix A. Different tools and techniques including VOS Viewer and clustering algorithms were used for visualisation and conducting the present systematic review.

Bibliography Analysis
This section reports the results of a quantitative analysis focusing on bibliographic attributes, including co-citations for identifying interconnections of the delay literature within selected articles and their corresponding citations.The systematic analysis alleviates bias during search, article selection, and bibliography analysis.The employed bibliometric method assists in identifying similarities and possible patterns of inquiry based on citation records and cited references [48,49].
Figure 1 shows the result of co-authorship analysis using the full counting method.The minimum number of papers of an author was considered as one, thus 1179 authors and co-authors of 493 selected articles were included and are visualised in Figure 1. Figure 2 shows the co-authorship network for all 259 co-authors using the full counting method based on the DEC dataset including 94 papers.Based on the initial review of the current practices in the literature, a set of strings was developed to select the final search criteria.The search string was selected as "delay overrun" or "time overrun" and "construction industry" or "construction project"' and applied on the Scopus database, which resulted in 493 records using the search criteria, as shown in Appendix A.
The search was limited to articles investigating causes and effects in the past ten years, from 2009 to 2018.Therefore, "cause" and "effect" were also included in the search criteria.Applying the criteria resulted in developing the delay effects/causes (DEC) database in construction with 94 records using the search criteria shown in Appendix A. Different tools and techniques including VOS Viewer and clustering algorithms were used for visualisation and conducting the present systematic review.

Bibliography Analysis
This section reports the results of a quantitative analysis focusing on bibliographic attributes, including co-citations for identifying interconnections of the delay literature within selected articles and their corresponding citations.The systematic analysis alleviates bias during search, article selection, and bibliography analysis.The employed bibliometric method assists in identifying similarities and possible patterns of inquiry based on citation records and cited references [48,49].
Figure 1 shows the result of co-authorship analysis using the full counting method.The minimum number of papers of an author was considered as one, thus 1179 authors and co-authors of 493 selected articles were included and are visualised in Figure 1. Figure 2 shows the co-authorship network for all 259 co-authors using the full counting method based on the DEC dataset including 94 papers.For each of the 1179 authors, the total strength of the co-authorship links with all authors and co-authors were calculated, and the greatest link strength was considered for the visualisation of Figure 1.In addition, different numbers of papers from an author were selected for future investigation.The results show that, for the minimums of two, three, and four papers of an author, 138, 43, and 12 authors met the criteria.This shows that a limited number of authors continuously or frequently contribute to the delay literature, including Lee, H. S. [50][51][52][53], Park, M. [50][51][52][53], Yap, J. B. H. [54][55][56][57][58], Abdul-Rahman, H. [55,57,59,60], and Enshassi, A. [61][62][63][64][65][66][67][68][69].This shows that, among a large set of scholars investigating delay in construction, only a limited number of authors are regularly coauthoring in the delay area.This is also limited in the DEC dataset where the criteria are applied and the focus of the literature is effect and cause.For each of the 1179 authors, the total strength of the co-authorship links with all authors and co-authors were calculated, and the greatest link strength was considered for the visualisation of Figure 1.In addition, different numbers of papers from an author were selected for future investigation.The results show that, for the minimums of two, three, and four papers of an author, 138, 43, and 12 authors met the criteria.This shows that a limited number of authors continuously or frequently contribute to the delay literature, including Lee, H. S. [50][51][52][53], Park, M. [50][51][52][53], Yap, J. B. H. [54][55][56][57][58], Abdul-Rahman, H. [55,57,59,60], and Enshassi, A. [61][62][63][64][65][66][67][68][69].This shows that, among a large set of scholars investigating delay in construction, only a limited number of authors are regularly co-authoring in the delay area.This is also limited in the DEC dataset where the criteria are applied and the focus of the literature is effect and cause.
Figure 3 shows the co-occurrence analytical map of keywords based on the first bibliographic dataset.For this visualisation a minimum number of 2 was selected for co-occurrence visualisation and a total of 713 keywords out of the sample of 2926 keywords are shown in Figure 3.The normalisation method of LinLog was used in VOS Viewer.For each of the 1179 authors, the total strength of the co-authorship links with all authors and co-authors were calculated, and the greatest link strength was considered for the visualisation of Figure 1.In addition, different numbers of papers from an author were selected for future investigation.The results show that, for the minimums of two, three, and four papers of an author, 138, 43, and 12 authors met the criteria.This shows that a limited number of authors continuously or frequently contribute to the delay literature, including Lee, H. S. [50][51][52][53], Park, M. [50][51][52][53], Yap, J. B. H. [54][55][56][57][58], Abdul-Rahman, H. [55,57,59,60], and Enshassi, A. [61][62][63][64][65][66][67][68][69].This shows that, among a large set of scholars investigating delay in construction, only a limited number of authors are regularly coauthoring in the delay area.This is also limited in the DEC dataset where the criteria are applied and the focus of the literature is effect and cause.Figure 3 shows the co-occurrence analytical map of keywords based on the first bibliographic dataset.For this visualisation a minimum number of 2 was selected for co-occurrence visualisation and a total of 713 keywords out of the sample of 2926 keywords are shown in Figure 3.The normalisation method of LinLog was used in VOS Viewer.
Figure 4 also shows the co-occurrence analytical map of keywords based on the first bibliographic dataset, but the minimum number of co-occurrence was selected as five to identify the most frequent concepts.Of the sample of 2926 keywords, 176 keywords are shown in Figure 4. Figure 4 shows that risk management has become more important in recent years.This also shows that the recent publications may tend to offer suggestions to monitor and prevent delay.In addition, it shows that using questionnaire surveys is the traditional method of delay analysis.Figure 4 shows that risk management has become more important in recent years.This also shows that the recent publications may tend to offer suggestions to monitor and prevent delay.In addition, it shows that using questionnaire surveys is the traditional method of delay analysis.Figure 5 also shows the key concepts used in the DEC database (with questionnaire surveys being a dominant method from 2014) and that risk management has become a focus in literature more recently.5 also shows the key concepts used in the DEC database (with questionnaire surveys being a dominant method from 2014) and that risk management has become a focus in literature more recently.

Content Analysis and Data Mining
This section critically reviews the content of the DEC dataset by investigating topics, keywords, and themes.First, the entire DEC dataset was grouped into five main clusters with each cluster against three criteria (the gap identification criteria).Figure 6 shows that there were three clusters within the DEC dataset based on the word similarity of the articles, which were separately analysed using thematic analysis techniques.Based on the results and the similarity of the words, the papers were assigned into five clusters.The DEC dataset could also be classified based on these findings.A careful content analysis showed that there were at least three different types of findings within the DEC dataset: (i) the first group of papers investigating causes of delay [70], effects of delay [71], mitigation strategies, and/or all causes and effects with appropriate mitigation strategies [72,73]; (ii) the second group investigating the effect of one special factor on delay [74]; (iii) the third group proposing and evaluating methods and/or models for identifying, ranking, and estimating delays [75].

Content Analysis and Data Mining
This section critically reviews the content of the DEC dataset by investigating topics, keywords, and themes.First, the entire DEC dataset was grouped into five main clusters with each cluster against three criteria (the gap identification criteria).Figure 6 shows that there were three clusters within the DEC dataset based on the word similarity of the articles, which were separately analysed using thematic analysis techniques.Based on the results and the similarity of the words, the papers were assigned into five clusters.The DEC dataset could also be classified based on these findings.A careful content analysis showed that there were at least three different types of findings within the DEC dataset: (i) the first group of papers investigating causes of delay [70], effects of delay [71], mitigation strategies, and/or all causes and effects with appropriate mitigation strategies [72,73]; (ii) the second group investigating the effect of one special factor on delay [74]; (iii) the third group proposing and evaluating methods and/or models for identifying, ranking, and estimating delays [75].

Current Practices in Delay and Time Overrun Investigations
We first investigated the publications in the past three years to identify the current practices in this field.Tables 3-5 show that most of them used questionnaires and focused on developing countries, and Figure 7 shows word clouds created for different sources based on stemmed words.We first investigated the publications in the past three years to identify the current practices in this field.Tables 3, 4, and 5 show that most of them used questionnaires and focused on developing countries, and Figure 7 shows word clouds created for different sources based on stemmed words.

Number of examined delay factors and list of the selected factors identified
Prioritize delay factors [76]

Method; Sample Size and Participants Number of Factors Measured and Findings
Productivity and delay analysis [125] A new method and a case study This article proposes a method that is a tool for calculating the schedule impacts that happen when there is a problem in lost productivity.
Critical path effect based delay analysis method [126] Hypothetical case studies Analysis effects of delays on the critical path that performs delay analysis accurately and uses a process-based analysis approach to solve simultaneous delays.

Factors influencing delay claims [127], India Arbitration awards, court cases, and professionals
Improper design and owner's neglect, changes in orders, weather and site conditions, delayed delivery, economic conditions, and quantity growth.
Understanding construction delay analysis and the role of preconstruction programming [128], UK In-depth interview; experienced construction planning engineers Complexity, cost, and time.Emphasizes the importance of baseline programs for resolving delay claims.

Method; Sample Size and Participants Number of Factors Measured and Findings
Factors influencing the selection of delay analysis method [129], UAE, a hotel, an international school complex, a highway, sewage treatment plant, and a residential tower Interviews; 8; experts; limited to case studies in the period of 2007-2012 Client's attitude, experience of the delay analyst, reputation and neutrality of the delay analyst, project complexity, and cost and timing of performing the analysis.Time Impact analysis (TIA) and Impacted as Planned (IAP) are two commonly used Delay Analyzing Methods DAMs.The ethnographical approach is suggested, since it provides the opportunity to capture real and live states of knowledge on the selection and the use of DAMs.
Visualisation of delay claim analysis using 4D simulation [130] This article shows that 4D simulation is a reliable method for analyzing delay claim.

Stochastic delay analysis and forecast method [131] Shi's method
This article proposes the Stochastic Delay Analysis and Forecast (SDAF) method, which is an informative analytical method and predicts the effect of a single activity's delay with probability for overall project delay.
Decision-making model for selecting the optimum method of delay analysis [75], UAE, Dubai Semi structured interviews and questionnaire; 74; contactors and consultants This article proposes the Digital Multimeter (DMM) objective tool, which can reduce the potential for disputes and conflicts arising from delays in construction projects.

Key Factors Identified in the Delay Literature
Tables 5-7 show a comprehensive list of factors and the priority of each factor in Asian and African countries.This helps us to understand the importance of current factors in the literature.These two tables are also used for identifying the frequency and the median of each factor.Most of the articles extracted a number of delay factors from the literature.Next, they evaluated each factor or validated them in their context by conducting a survey, and they finally presented the top ranked factors.For example, Al-kharashi and Skitmore [112] identified 112 delay factors from literature.Then, they conducted a survey and presented the 30 important factors from the results.Al-kharashi and Skitmore [112] reported only ten factors out of 30 and reported them in the abstract of their paper.Thus, this paper reported the top ten factors reported by them.Among the DEC dataset, only 63 articles included the causes/main cause of delay.A total of 55 articles were investigated in a certain region or country, which are presented in Tables 5-7.Note: design problems are a general factor that contain items such as errors in drawings and improper/inadequate design documents.Based on the information collected from Tables 6-8, the frequency and the median of each factor were calculated.Table 9 shows that the most frequent factors contributing to project delay are scheduling issues, payment delay, design changes, manpower issues, and financing difficulties.Note: * frequency refers to the number of occurrences that the issue presented by researchers as an important cause of delay in the DEC dataset; the order of issues is based on the frequency values.Source refers to the number of papers mentioned in the selected issue; reference refers to the frequency of the selected issue within the DEC dataset; median refers to the value separating the higher half of the important factors presented as important in the DEC datasets by researchers.

Technology Applications for Time Control and Risk Management
Scheduling issues were identified as one of the most frequent factors causing delay in projects (refer to Table 9).
A good project schedule can serve as a key management tool for making decisions and predicting whether the project will finish on time and within budget.Regular updates to the project schedule are essential to record progress and identify potential problems.
There are various project scheduling software systems, such as Microsoft Project, Oracle Primavera P6, Open Plan Professional (OPP), FastTrack Schedule, ZOHO Projects, @risk, Workfront, eResource Scheduler, ConceptDraw Project, Resource Guru, Smartsheet, and many other software, packages, and platforms.Each of these project schedule software options has different strengths, but they offer the best options for a variety of management needs.
Project scheduling software has been developed to communicate what work needs to be performed, which resources of the organisation will perform the work, and the timeframes in which that work needs to be performed.The project scheduling software should reflect all the work associated with delivering the project on time.However, Microsoft Project, Oracle Primavera P6, and Open Plan by Deltek are the most practical, powerful, and common software in practice.Table 10 compares the strengths and the features of these three.In order to use scheduling software for project delay analysis, the following questions need to be asked before using scheduling software:

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What data need to be assembled as inputs to record the delay events for the update, and what methods will be used to collect the data?

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How often should projects be updated?• Are resources local or offsite?• Which project teams are resources participating in? • Who on each team will be gathering the information used for the project update, and with what frequency are the data updated within the schedule?• Who needs to see the results of the update, and when do they need to see them?

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What types of information need to be generated after each update to communicate progress before the next update?
The answers to these questions help determine how the project management office, the project managers, and the project planning function uses the module to update projects.
Careful details of events are developed in the project schedule to identify delays coupled with an accurate assessment of the source of the delay, thus the responsibility can be assigned.
Activity late finish date is one the main components of each scheduling software to calculate schedule delays.Activity late finish date is the latest possible point in time in which the schedule activity can be completed without violating schedule constraint or delaying the project end date (PMBOK).The late finish date is the point at which the schedule activity contains no float.
Progress curves are used as a basis for comparing the schedule baseline.When the project schedule, the work breakdown structure (WBS), or both are modified through integrated change control, the progress curves are revised to indicate the new progress curve information.Figure 8 shows the float analysis for identifying schedule delays as a basis of S-curve updates in project scheduling software.
(PMBOK).The late finish date is the point at which the schedule activity contains no float.
Progress curves are used as a basis for comparing the schedule baseline.When the project schedule, the work breakdown structure (WBS), or both are modified through integrated change control, the progress curves are revised to indicate the new progress curve information.Figure 8 shows the float analysis for identifying schedule delays as a basis of S-curve updates in project scheduling software.Progress updates are used to calculate delays by using scheduling software.The network schedules are updated on a regular basis, and the agreed timings for updates are generally agreed upon within the special conditions of contract.For example, monthly updates based on the latest schedule baseline are common.Generally, the construction management team updates the schedule with a marking up of the changes from the previous month and provides these details for the project planning function to enter into the scheduling software (e.g., MS Project or Oracle Primavera P6).It is sent to the contractor's project controls team for review until the cut-off date.The project control manager checks and reviews the updated schedule with the project manager.Upon completion of the input work, time calculation and analysis are done within the review process as follows:

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Total float consuming status compared with the previous month schedule.

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Critical path schedule analysis.

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Based on the above analysis, if problem areas are found, these are identified and reported to the project manager.The project control manager implements suggested countermeasures in conjunction with the related managers and under the project managers' instruction.Once the project manager approves the counter measures, they are incorporated in the schedule.Close monitoring is made to meet the corrective action plan.Until a decision on the countermeasures is made, the schedule is not changed.

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The updated schedule is issued to each project management office (PMO), project control department, or project manager as an updated project control for their work and for the next monthly update.

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When compared with the initial estimate, the updated information may indicate some variances in the scheduling basis.On the other hand, along with the project progress, schedule deviations may be detected from the initial scenario caused by various factors.

Progress Measurement Method in Scheduling Software
The progress is calculated based on milestones, which are defined.Each work package is weighed; this physical weight factor is calculated according to supplier contract price.The assessment of planned progress between milestones is obtained by assuming linear progress development between milestones; see Equation ( 1 Each activity weight is calculated based on an activity attribute, such as man-hours, material, or cost applied.For example, the length of time for earthwork is a function of the volume of soil cutting and filling in the specific area of the project site.

Primavera P6 and Delay Analysis
Schedule delay analysis is a method used to determine the extent of impact from potential delay to the agreed milestones.The schedule analysis method in Primavera P6 involves inserting additional activities indicating delays or changes into an updated schedule representing progress up to the point when a delay event occurs to determine the impact of those delay activities.Saving a project baseline plays a crucial role in delay analysis and is a fundamental step in Primavera P6 for schedule delay analysis.Figure 9 shows the baseline in the blue bar and the actual timeline in the yellow bar; as can be seen, a five-day delay in EC160 activity occurred.Primavera P6 is powerful software to analyse project delays, schedule variances, schedule performance index, estimate to completion, and other aspects of earned value management.Figure 10 shows the earned value feature of the Primavera P6 and respective diagrams.In Primavera P6 software, the Progress Spotlight feature is used to highlight the activities that should have started, progressed, or finished between the previous data date and the new data date in the Gantt Chart view.Figure 11 shows the Spotlight feature in Primavera P6 software for identifying the delayed activities.Primavera P6 is powerful software to analyse project delays, schedule variances, schedule performance index, estimate to completion, and other aspects of earned value management.Figure 10 shows the earned value feature of the Primavera P6 and respective diagrams.Primavera P6 is powerful software to analyse project delays, schedule variances, schedule performance index, estimate to completion, and other aspects of earned value management.Figure In Primavera P6 software, the Progress Spotlight feature is used to highlight the activities that should have started, progressed, or finished between the previous data date and the new data date in the Gantt Chart view.Figure 11 shows the Spotlight feature in Primavera P6 software for identifying the delayed activities.In Primavera P6 software, the Progress Spotlight feature is used to highlight the activities that should have started, progressed, or finished the previous data date and the new data date in the Gantt Chart view.Figure 11 shows the Spotlight feature in Primavera P6 software for identifying the delayed activities.In Primavera P6 software, the Progress Spotlight feature is used to highlight the activities that should have started, progressed, or finished between the previous data date and the new data date in the Gantt Chart view.Figure 11 shows the Spotlight feature in Primavera P6 software for

Project Management Body of Knowledge (PMBOK)
Based on the guide to project management body of knowledge [135], project time management encompasses the processes required to manage the project in a timely manner.Project time management has six main processes: (1) plan schedule management; (2) define activities; (3) sequence activities; (4) estimate activity durations; (5) develop schedule; and (6) control schedule.Project Management Body of Knowledge (PBMOK) also emphasises that the schedule baseline is the pillar of delay analysis in projects.A schedule baseline is the approved project timeline upon which any actual dates and changes need to be compared with the schedule baseline for analysing the delays in the schedule model.Updating the project schedule requires maintaining the actual data for project time performance.Any change to the critical path within the schedule baseline leads to delay.In addition, project time management in construction projects needs to focus particularly on other subjects as well as resource definition, allocation and resource levelling, activities to capture contingency allowances, weightage definition, progress curves, monitoring and schedule control procedures, and conditions for owner acceptance approval [136].

Practice Standard for Scheduling
Practice Standard for Scheduling is a Project Management Institute's (PMI's) standard with the detailed focus on project time management processes, project scheduling models, and techniques.This practice standard expands on information contained in the PMBOK guide.The main goal of this standard is to develop schedule models that are appropriate and fit for purposes of projects.This practice standard introduces schedule model creation by selecting a scheduling approach and a scheduling tool.Based on this practice standard, project work breakdown structure and project-specific data are incorporated within the scheduling technique to develop a unique schedule model.Practice Standard for Scheduling has many hints and techniques for managing delays in the project schedule.For example, when the work on an activity is delayed, it is beneficial for the activity to be split into two or more activities at natural break points.In another example, lags and leads also play important roles in managing the impact of delays on the overall project schedule.In addition, assigning a finish date to the end milestone can help the project schedule to better manage delays and changes in the project master schedule [137].

Agile Practice Guide
Agile planning focuses on shorter build cycles and tangible results at frequent and incremental intervals.An important part of agile scheduling is using multiple iterations instead of shifting from one phase to another, which makes the scheduling more complex but more efficient.Scrum and Kanban are two main agile frameworks for planning.Both frameworks are used to break down the work into small and manageable pieces.For controlling the project schedule developed by agile approaches, Burndown charts are typically used.Burndown charts are the most applicable agile tracking and controlling mechanisms used by project teams.The main characteristic of a Burndown chart is tracking the remaining work overtime.Caution should be taken when using agile approach delays because rework is high.Agile planning is a suitable project planning technique for a short-term project such as a software development project but is not recommended for construction projects [135,138].

Discussion and the DEC conceptual model
This paper, unlike other reviews, identified critical common factors and developed the DEC conceptual model for future investigations.The present review contributes to the body of knowledge in two main ways: (i) it identifies the gaps and the deficiency areas in the DEC literature; and (ii) it develops a conceptual model that can be used to design a questionnaire for further investigations in different contexts.These contributions are discussed below and are presented in Table 8 and Figure 12, respectively.In contrast to traditional investigations, the DEC model suggests that future studies should carefully measure the effect of new "digital tools" and technologies in delay.Sepasgozar and Davis [140] discussed different technology types in construction, which can be further detailed and classified based on their application in time management.The effects of new digital tools and technologies on delay have not been evaluated in the literature.Some of the key digital technologies are listed as follows: •  Table 10 shows that four factors were overlooked in the DEC dataset.The data analysis and the interpretations are not always valid or reliable due to small samples of participants, low quality of data, unmatched structure of the research questionnaire with the current DEC literature or the case study context, overlooking the effects of technology adoption by all construction stakeholders, or ignoring jobsite upgraded equipment.The overlooked factor (OF) refers to the data and the lack of evaluating new technologies in delay analysis (Table 11).For example, OF1 is the quality of data collected from questionnaires, which cannot be generalised as a valid finding of critical factors of construction projects all over the world.In fact, a major part of the DEC dataset focuses on developing countries; still, some of them suggested more investigations to understand the project complexity at different strategic, operational, and project levels in these countries [84].This small dataset cannot represent all key practitioners with a real understanding of delay causes and effects.Some studies recruited a limited number of respondents (less than 150), which cannot represent all projects of a country and suffers from lack of validation [27].This leads to bias in the findings of some studies.In some cases, the survey participants were selected carefully, while some cases were supposed to be selected randomly, but in reality, their strategy of randomness was never clarified.Some of the studies used Analytic Hierarchy Process (AHP) or SD-DEMATEL [93] questionnaires to provide a consistency ratio to increase the reliability of the findings, but these studies suffer from a limited number of factors measured and a limited number of participants.The literature also suggests that comparison studies among developing countries [110] and longitudinal studies in delay analysis should be conducted to examine the relationships of factors and stakeholders in an extended period [111].In addition, the future studies should focus on more specific types of construction projects, such as utility, highway construction, and dam construction projects, to find proper strategies to mitigate the effects of environmental issues [111].Figure 12 shows the main constructions of the conceptual DEC model for analysing the causes and the effects of delay in construction projects.The key constructs are resources, project context, and stakeholders.
In contrast to traditional investigations, the DEC model suggests that future studies should carefully measure the effect of new "digital tools" and technologies in delay.Sepasgozar and Davis [140] discussed different technology types in construction, which can be further detailed and classified based on their application in time management.The effects of new digital tools and technologies on delay have not been evaluated in the literature.Some of the key digital technologies are listed as follows:
The literature frequently reports that design mistakes, errors, changing orders and scopes, later approvals, and late technical decision makings were the main causes of delay in different contexts [95,99,104].

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Digital communication systems: cloud-based tools, emails, smart phones, and radio communication systems.Some studies report that the communication and the coordination between different parties were poor [27,95,96,99,109].

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Digital contract management tools: intelligent or smart contracts.The literature shows that many projects suffer from weak administration of contracts [96].

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Digital devices to increase the productivity of heavy equipment: real-time locating systems, Global Positioning System (GPS), and radar.
New questionnaires can be designed based on the factors shown in Figure 12.Future studies also should identify the relationship between different causes and their effects on delay [79].The visibility, the real-time monitoring, and the flexibility of the project using a wider range of digital technologies may mitigate the negative effects of resource and coordination issues.In case of using advanced and digital technologies, vendors have a significant role in successful technology adoption and implementation processes in the project [149][150][151][152][153], which can also mitigate the negative effects of productivity and coordination issues.Appropriate interaction between contractors and vendors (e.g., materials, equipment, or technology suppliers) during both design and construction phases affects delay [27].Additional evidence is required to validate the results of surveys, which will be conducted in the future.Many delay cause factors can be explored using project evidence and digital data generated during the project, and the questionnaires used to collect participant views cannot be considered as accurate and should only be used as tools to explore delay causes and effects.However, the best way (as suggested by this paper) is to adopt a mixed method of big data generated during the project along with the questionnaire developed based on the factors presented in Figure 12.

Conclusions and an Agenda for Future
This paper aimed to identify the most relevant papers of delay causes and effects and to develop the DEC database for future critical analysis.The content of the DEC dataset was systematically analysed using bibliographic, cluster, and thematic analyses.This paper presented the DEC literature, including key findings of delay over the years.This study carefully conducted a systematic content analysis, resulting in four main overlooked factors and deficiency areas, which should be addressed in the future studies.The four factors are faulty data analysis and interpretations due to small samples of participants or low data reliability, unmatched structure of research questionnaires with the current policies or standards, overlooking the effects of technology adoption by construction stakeholders, and ignoring jobsite upgraded equipment.The key deficiencies were identified as faulty of data analysis and interpretations due to small sample of participants or low data reliability, unmatched structure of research questionnaires with the current policies or standards, overlooking the effects of technology adoption by construction stakeholders, and ignoring jobsite upgraded equipment.The overlooked factor refers to the data and the lack of evaluating new technologies in delay analysis.For example, OF1 refers to the quality of data collected from questionnaires, which cannot be generalised as a valid finding of critical factors of construction projects all over the world.In fact, a major part of the DEC dataset focuses on developing countries.This small dataset cannot represent all key practitioners with a real understanding of the delay causes and effects.Some studies recruited a limited number of respondents (less than 150), which cannot represent all projects of a country.This leads to bias in the findings of some studies.In some cases, the survey participants were selected carefully, and in some cases, they were supposed to be selected randomly, but in reality, it is not clear what their strategy of randomness was.Some studies used AHP questionnaires to provide a consistency ratio to increase the reliability of the findings, but these studies suffer from a limited number of factors measured and a limited number of participants.

Figure 1 .
Figure 1.Visualisation of co-authorship network for all 1179 co-authors using the full counting method based on the first bibliographic dataset including 493 papers.

Figure 1 .
Figure 1.Visualisation of co-authorship network for all 1179 co-authors using the full counting method based on the first bibliographic dataset including 493 papers.

Figure 2 .
Figure 2. Visualisation of co-authorship network for all 259 co-authors using the full counting method based on the delay effects and causes (DEC) dataset including 94 papers.

Figure 3 .
Figure 3. Co-occurrence analytical map of keywords created on the first bibliographic dataset.With the minimum number of co-occurrence of 2, a total of 713 keywords out of the sample of 2926 keywords are shown.

Figure 2 .
Figure 2. Visualisation of co-authorship network for all 259 co-authors using the full counting method based on the delay effects and causes (DEC) dataset including 94 papers.

Figure 2 .
Figure 2. Visualisation of co-authorship network for all 259 co-authors using the full counting method based on the delay effects and causes (DEC) dataset including 94 papers.

Figure 3 .
Figure 3. Co-occurrence analytical map of keywords created on the first bibliographic dataset.With the minimum number of co-occurrence of 2, a total of 713 keywords out of the sample of 2926 keywords are shown.

Figure 3 .
Figure 3. Co-occurrence analytical map of keywords created on the first bibliographic dataset.With the minimum number of co-occurrence of 2, a total of 713 keywords out of the sample of 2926 keywords are shown.

Figure 4
Figure 4 also shows the co-occurrence analytical map of keywords based on the first bibliographic dataset, but the minimum number of co-occurrence was selected as five to identify the most frequent concepts.Of the sample of 2926 keywords, 176 keywords are shown in Figure 4.

Figure 4 .
Figure 4. Co-occurrence analytical map of keywords created in the first dataset.With the minimum number of co-occurrence set as five, a total of 176 keywords out of the sample of 2926 keywords are shown.(a) All keywords co-occurrence network map; (b) scheduling co-occurrence network map; (c) risk assessment co-occurrence network map.

Figure
Figure4shows that risk management has become more important in recent years.This also shows that the recent publications may tend to offer suggestions to monitor and prevent delay.In addition, it shows that using questionnaire surveys is the traditional method of delay analysis.Figure

Figure 4 .
Figure 4. Co-occurrence analytical map of keywords created in the first dataset.With the minimum number of co-occurrence set as five, a total of 176 keywords out of the sample of 2926 keywords are shown.(a) All keywords co-occurrence network map; (b) scheduling co-occurrence network map; (c) risk assessment co-occurrence network map.

Figure 5 .
Figure 5. Co-occurrence analytical map of keywords created on the first dataset.With the minimum number of co-occurrence set as five, a total of 25 keywords out of the sample of 550 keywords are shown.

Figure 5 .
Figure 5. Co-occurrence analytical map of keywords created on the first dataset.With the minimum number of co-occurrence set as five, a total of 25 keywords out of the sample of 550 keywords are shown.

Figure 6 .Figure 6 .
Figure 6.Five branches of papers in the DEC, including three clusters of the main relevant articles for the content analysis.

Figure 8 .
Figure 8. Float analysis and progress curves basis for schedule delays [adopted from Management Body of Knowledge (PMBOK)].

Buildings 2019, 8 , 36 Figure 9 .
Figure 9. Baseline in blue bar and actual timeline in yellow bar.

Figure 9 .
Figure 9. Baseline in blue bar and actual timeline in yellow bar.

Buildings 2019, 8 , 36 Figure 9 .
Figure 9. Baseline in blue bar and actual timeline in yellow bar.

36 Figure 12 .
Figure 12.The DEC conceptual model including main constructs of resources, project context, and stakeholders.

Figure 12 .
Figure 12.The DEC conceptual model including main constructs of resources, project context, and stakeholders.

Table 2 .
Delay in different contexts, including the percentages of the delay reported in the literature.

Table 3 .
Summary of selected articles of cluster 1 of delay investigations from 2015 to 2018.

Table 3 .
Summary of selected articles of cluster 1 of delay investigations from 2015 to 2018.

Table 4 .
Summary of selected articles of cluster 2 of delay investigations from 2015 to 2018.

Table 5 .
Summary of selected articles of cluster 3 of delay investigations from 2015 to 2018.

Table 6 .
Priority list of delay factors within DEC literature for Asian countries, mainly Middle Eastern.

Table 7 .
Priority list of delay factors within DEC literature for selected Asian countries.

Table 8 .
Priority list of delay factors within DEC literature for African and other countries.

Table 9 .
Summary of important factors including frequency and median.

Table 10 .
Project delay analysis feature comparison between Microsoft (MS) Project, Primavera P6, and Open Plan by Deltek.
****: The advantage of each software across the selected features.

Table 11 .
Future directions based on deficiencies of the current delay investigations.