Keywords

1 Introduction

Delay/time overrun is a common issue in construction projects worldwide, and the success of construction projects can be considered a measure of the political performance of countries because it is related directly to their economy [1]. Faridi and El-Sayegh state that project delays negatively affect the quality and safety of project work and reflect negatively on the services provided to the community [2]. Therefore, in the present study we performed a literature review focused on identifying and ranking the delay factors, although classification of these factors differs among studies. The relative importance index (RII) analysis was commonly used and many types of construction projects were researched and discussed. The delay factors were classified under different categories, but the most prominent were the contractor and client categories, which relate to financial problems, management, materials and equipment, experience, planning, and methods of construction. In addition, the delay factors in developing countries were greater than in developed countries. The delay factors were many and varied according to the project type, location, and the research method used in the study. Our main focus was to identify the critical categories of delay factors found by previous studies over the past 10 years published in journals ranked under the scientific journal rankings (SJR). The factors identified were classified into categories that were analyzed by Cronbach's alpha for reliability verifying and RII using SPSS software for ranking. The top five categories were: orders and requirements; experiences and productivity; financial problems; planning; and external and management.

2 Literature Review

The research methods used in the studies differed, but usually followed two trends: identifying and analyzing the factors [3]. However, some studies also discussed the effects of delay factors [4]. The delay factors identified were generally classified into categories applicable for each study. For example, Bajjou and Chafi identified the delay factors in African countries and classified them into eight categories [5]. Similarly, Wuala and Rarasati analyzed and classified the factors in Southeast Asia into five categories [6]. In addition, studies discussed the delay factors in different types of projects [7]. For example, tunnels [8], residential projects [9,10,11], roads [12,13,14], railways [15, 16], sport facilities [17], oil projects [18, 19], as well as transport, power, building, and water irrigation projects [20]. These various delay factors were then also variably categorized. For example, financial problems were identified as the contractor category [21,22,23,24], but also as the client category [7, 25,26,27,28]. Management factors were placed in the contractor category [29, 30], but also related to shortages in equipment and material factors [6, 31]. Some studies stated that the contractor category related to experience, planning, and construction method factors [32,33,34], whereas in others the client category was related to decision-making factors [35, 36], or to changes factors [19, 37]. In addition, there were many other categories related to other delay factors, such as the external category related to weather, policy, and security factors [8, 10, 11, 16, 38, 39]. The delay in construction projects affects both developed and developing countries. Rivera et al. studied the delay factors in 25 developing countries and confirmed that 50% of them have similar delay factors [32]. On the other hand, developed countries are also affected by delay factors but less so, according to analysis of three countries: Portugal, the UK, and the USA [40]. In addition, other studies identified global delay factors for both developed and developing countries [17, 23, 41,42,43]. We reviewed all the studies that addressed and identified delay factors to analyze the top-ranked factors, and then identified the developed and developing countries affected by these factors.

3 Research Method

Figure 1 details the stages in our research. We began with the research scope to select relevant studies, which were then refined. The factors (delay/time overrun) were extracted from the selected studies, classified into categories and ranked based on their importance from the researchers’ point of view. Next we analyzed the factor categories by Cronbach’s alpha and the RII. Lastly, the resulting categories were also classified to the relevant developed/developing country.

Fig. 1
A flow diagram starts with the research scope of publications from scopus, leads to the factors identified and classification to categories, and finally leads to the analysis of factors categories. It ends with classified categories of developed and developing states related.

Research flowchart

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3.1 Research Scope and Select Studies

Using the Scopus database, we collected and sorted studies that addressed the relevant factors (i.e., delay/time overrun) in construction projects. Screening was limited to the title of the study. Next we selected studies published in the 10 years of 2012–2021 with the word “delay” in the title and 410 studies were identified. All steps were repeated for studies with “time overrun” in the title and 41 were identified.

The 451 studies were then screened for publication in a high-quality journal or conference ranked by SJR, resulting in 277 studies, which were further reviewed and refined to choose those that clearly identified and ranked the factors of delay/time overrun in different countries. Finally, 71 studies in total were selected: 62 for delay and 9 for time overrun. Microsoft Excel was used in this stage of the research.

3.2 Factors Identified and Classification into Categories

The studies reviewed in this research depended on delay/time overrun factors identified in previous studies that other researchers had performed through interviews, questionnaires, or case studies. The research area included many developing and developed countries. These studies ranked the top essential factors of delay/time overrun, so the top five factors selected from previous studies were included in this research. The delay factors were not all similar in terms of their importance, as they were based on the project type, location, and the method of identifying the factors used in the study. So, some factors were repeated or had a similar description in some studies, and other factors were utterly different in their description in other studies.

The factors extracted from all the studies reviewed had been classified into categories based on the type and description of each factor and thus to any category it most likely belonged. All categories and their factors were coded using NVIVO software, and factors were ranked inside their categories from 1 to 5 based on the rank that each factor had in the original study. Some categories were combined into one category to reduce the number of categories, such as design and work error; experience and productivity; material and equipment; orders and requirements; and tender and contract category. In addition, some studies contained some factors belonging to the same category.

3.3 Analysis of Factor Categories

We applied two types of analysis: Cronbach’s alpha analysis to verify the reliability of data collected regarding delay/time overrun factors and RII analysis to rank the critical categories of the top five factors using SPSS software. The various important factors were identified and ranked based on the project type, location, and research method of the previous studies, which depended on literature reviews to identify the factors, then on questionnaires, surveys or interviews to assess the importance of the factors, and finally, on ranking these factors by analysis. In the questionnaires or interviews, the answers and importance degree of the factors identified in the previous studies were collected from respondents and the answers are ranked to identify the most important using RII analysis. Therefore, we assumed our study was similar to a questionnaire survey of the previous studies that addressed and ranked the top five delay factors, whereby categories classified were questions, studies were respondents, and importance degree of the factors comprised the answers.

We adopted a Likert scale with 5 points to identify the top five essential levels for the top five factors identified in previous studies. The five levels of importance were very high, high, moderate, low, and very low, ranked from 5 to 1 degree of importance. Factors ranked as the first, which was the highest level in the previous studies, took a very high ‘5’ degree of importance, and factors ranked as second, third, fourth, and fifth took a high ‘4’, moderate ‘3’, low ‘2’, and a very low ‘1’ degree of importance respectively. It is good to analyze all factors classified into categories, but the total of factors (i.e., answers) in all categories (i.e., questions) was not equal. Therefore, it was necessary to first reduce the factors for each category to be equal to the category's lowest value of the factors by ignoring the levels of the least important factors. However, the total factors selected after reducing the factors of categories became less than half of the original factors, even with the categories having the lower second, third and fourth values of the total factors. In addition, the total of factors was more than half of the original factors when selecting the following lower fifth and sixth values. However, the sixth lower value of factors had fewer factors and categories than the fifth lower value and there was no point in proceeding with other lower values because the total factors became less, as well as the categories, and it beneficial to analyze the greatest number of factors. So, the best scenario was using the category having the fifth lower value of factors because the total factors selected was more than half the original total. In this process, four categories that had factors with the lowest importance levels were excluded from the analysis. The factors in the remaining categories were analyzed by the two methods stated above using SPSS software.

In addition, the factors extracted from the previous studies included many different countries. Therefore, as the last step in this research, the studies of factor categories resulting from the analysis were classified as developed or developing states. The developing states were identified as per the list of developing countries updated in 2022 on the website of the Australian Government Department of Foreign Affairs and Trade [44]. Finally, the percentage of developed and developing states for each category was calculated and tabulated.

4 Results and Discussion

A total of 360 factors of delay were identified in the 71 studies. The classification of these factors resulted in 14 categories as per the description of each factor and the category to which it belonged. In addition, we found that two or three factors in most studies were mainly classified under the same category. Also, all studies identified 5 factors, except for 5 studies that identified 6 factors due to two factors having the same rank. Each factor’s degree of importance in 14 categories is detailed in Table 1. The total factors ranged from 8 in C1, to 49 in C4. There were 72 factors ranked as the first degree of importance, and 71 factors each for the second and third degrees of importance. Lastly, there were 73 factors each in the fourth and fifth importance degrees.

Table 1 Frequency of degree of importance of factors
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After refining the factors stated in the research method, six scenarios were proposed and selected (Fig. 2). Scenario 5 achieved the highest number of factors, and by getting the factors with the highest degree of importance, the factors for each category was reduced to 19. At the same time, the total of factors was 190, which was more than half of the 360 original factors. Also, the factors in this scenario belonged to 10 categories, because four categories with less than 19 factors were excluded. Table 2 and Fig. 2 detail scenario 5.

Fig. 2
A grouped bar graph of the number of factors versus 6 scenarios. It plots bars for the number of factors for each category, the number of categories, and the total of factors for all categories. The bar for the total of factors for all categories under scenario 5 holds the highest value of 190.

Proposed scenarios for analyzing the categories of factors

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Table 2 Frequency of importance degree of 19 factors for each category in scenario 5
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Cronbach’s alpha analysis was the first analysis applied and the result was 0.974, which indicated an excellent level of reliability (>0.8) and confirmed that the data collected was very acceptable and reliable and can be used for further analysis. Table 3 shows the internal consistency level of Cronbach’s alpha analysis.

Table 3 Internal consistency level of Cronbach’s alpha [7]
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Table 4 shows the results and ranks of the 10 categories analyzed after excluding the categories with the least importance levels of factors (i.e., C1, C2, C12 & C14). The results of the analysis illustrated the categories of the top critical delay factors ranked in previous studies for the 10 year period. The ranking of categories confirmed that the “orders and requirements” (C9) category had the highest level of importance (RII = 0.905), the “experience and productivity” (C4) category was next (RII = 0.842), the third category was “financial problems” (C6) (RI I = 0.832), followed by the “planning” category (C11; RII = 0.789). Lastly, both the “external” (C5) and “management” (C7) categories came fifth (RII = 0.779). Also, it was noted that the importance levels for all 10 categories were between very high and high. The RII of the first three categories (C9, C4 & C6) was > 0.8, so they all had a very high level of importance. In contrast, the fourth (C11), and fifth categories (C5 & C7) had a high importance level with all other remaining categories. Table 5 illustrates the importance levels in the RII analysis.

Table 4 Ranking of categories of factors by RII analysis
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Table 5 Importance levels in the RII analysis [7]
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In addition, the effect of the factors varied according to the different states. Thus, three groups of countries for each category (developed, developing, and global) were classified. In this classification, we considered and calculated all 360 factors, not just those refined and analyzed by RII. Also, some studies discussed global factors and were classified under the global group because they had not specified developed or developing countries. The factors of developed countries were stated in 95 studies, 239 reported factors in developing countries, and 26 studies discussed global factors. Table 6 shows the total factors divided as into those affecting developed and developing countries, as well as global factors.

Table 6 Categories of factors in developed and developing countries
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We also ranked the categories in each group of countries and overall, as shown in Table 7. We excluded global factors in order to identify just those within developed and developing countries groups. The category of “experience and productivity” C4 was the highest rank in terms of the number of factors stated in both developed and developing countries groups and as well as overall rank. Followed by C9 second, C3 & C7 third, C11 & C13 fourth, and C6 as the fifth category in the developed countries group ranking. In the developing countries group, C6, C11, C9, and C8 were ranked one by one. In the overall ranking, the category of “orders and requirements” (C9) was second; “financial problems” (C6) and “planning” (C11) were third, and “management” (C7) and “material and equipment” (C8) were fourth and fifth.

Table 7 Ranking of categories in developed and developing countries
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In total, 334 factors were classified within these groups: 95 for developed countries and 239 for developing countries. Therefore, the percentage of developed countries affected by delay factors was 28%, which was less than the percentage of developing countries affected, which was 72%. Table 7 details the ranks of categories affecting developed and developing countries and the overall rank.

Finally, the results clearly showed that the ranks of categories in terms of the top critical factors in construction projects were very close to the overall ranking of developed and developing countries affected by these factors, where the critical categories were the same in both the important factors ranking, and the overall ranking of countries, although these categories were not same as a ranking from 1 to 5.

However, some categories shared the same rank; for example, category C5 was shared as ranking five in categories of essential factors with C7, whereas C6 and C11 shared in the same rank of three in the overall ranking of countries.

5 Conclusion

Delay remains a contentious issue in construction projects, and it is due to many different factors. We identified 14 critical categories classified from the top five delay factors identified in previous studies. The critical categories with the highest ranking were orders and requirements; experience and productivity; financial problems; planning; and both external and management factors. All categories of essential delay factors identified in this research have affected both developed and developing countries, although the effect was 28% for developed countries and 72% for developing countries.