An impact overview of COVID-19 on the construction industry in Pakistan

The pandemic generated the need wherein companies had to adopt interactive continuous contingency planning. This crisis forced the organisations involved in the CI to adopt long-term strategic goals and develop the best health and safety practices to continue the work and activities on the ongoing projects (Afkhamiaghda et al. 2020). Later on, the representatives of organisations involved in construction projects started interaction online through Zoom and other applications to avoid the risk of COVID-19 (Iqbal et al. 2021). The findings of an analytical study on the CI regarding preventive COVID-19 measures suggested that ensuring workplace safety policies and providing paid sick leave could protect essential workers in high-contact industries and prevent further widening of disparities in COVID-19 morbidity and mortality (Pasco et al. 2020). A study, carried out by Iqbal et al. ( 2021) proposed a crisis management framework for the CI, which is required to be adopted in similar scenarios as of COVID-19.

Conclusively, it can be drawn from the literature review that the CI is diversified, and it includes both services and product components with the involvement of diverse organisations with competing interests on projects. Thus, there is a need to assess the impact of COVID-19 on the CI while taking into account the individuals belonging to these different organisations.

A 5-point Likert scale-based questionnaire was employed in the survey to gather the results from respondents. The respondents indicated their level of agreement using an ordinal scale (Bertram 2007). The respondents were requested to rate the factors from ‘1 to 5’ where ‘1’ indicates no impact or no chance of happening while ‘5’ depicts very high influence/impact or a very high chance of happening, as shown in Tables 5 and 6, respectively. The questionnaire survey based on the Likert scale from ‘1 to 5’ is used twice: once to assess the frequency of occurrence and second, to assess the severity of impact, as shown in Table 3.

Moreover, the questionnaire was designed in such a way that it collected the basic demographic data, like information on the participant, like the participant’s name and experience and current position in the company, and other requisite information like the participant’s organisation type, the scale of project based on several personnel, and COVID identified personnel within the firm and on the project, which were related to the research.

Considering the availability and ease of access, the post-COVID-19 restrictions period, and primarily the availability of funds, the data were collected through a snowball sampling technique considering the respective SMEs (Shafi et al. 2020). Snowball sampling is a type of non-probability sampling technique that is used for the sample population size, that is, the probability that every unit or respondent included in the sample cannot be determined. It is a widely used technique for its time and cost-related benefits (Bo Liu et al. 2014).

An exhaustive list of CI stakeholders, that is, owners, consultants and contractors, was prepared as a first step using mainly the Pakistan Engineering Council’s (PEC) comprehensive list of consultants and contractors. An initial screening was done to identify stakeholders working mainly in the major cities of Pakistan, primarily with public sector buildings and infrastructure-related projects. Certain dominant firms in the industry were particularly included in the sample. The clients selected were mainly decision-makers belonging to executing agencies and ministries that were responsible for delivering large infrastructure projects in road, water, power and railways. There are 41,025 registered companies of consultants, clients and contractors registered with the PEC. Out of these many registered consultants and contractors, some were out of business and some were out of the project domains.

Therefore, to adopt the most accurate sample size for this non-probabilistic approach, a finite population sample check was applied using the equations of well-known researchers (Wiegand 1968; Arain and Pheng 2005): Eq. 1n−n′(1+n′/N)$$\matrix{ {n - n'} \cr {\left( {1 + n'/N} \right)} \cr } $$

Where:

n’ = Sample size from infinite population = S²/V²;

n = Sample size from a finite population;

N = Total population (41,025);

V = Standard error of sample population equal to 0.05 for confidence interval 95%;

S² = Standard error variance of population, S² = P (1 – P); Maximum P = 0.5.

The sample size for the target population was calculated as follows: Eq. 2n′=S2/V2n′=(0.5)2/(0.05)2=100n=100/(1+100/41,025)=100$$\matrix{ {n' = {S^2}/{V^2}} \hfill \cr {n' = (0.5)2/(0.05)2 = 100} \hfill \cr {n = 100/(1 + 100/41,025) = 100} \hfill \cr } $$

Thus, the sample population considering the margin for the client bodies was selected as 125. Therefore, 125 participants from the 3Cs of the CI were selected, and to achieve this desired number, the number of participants per organisation was increased to three.

The designed questionnaires were distributed in the local CI of Pakistan for a detailed survey. Responses to these questionnaires were collected via emails, Facebook, WhatsApp, LinkedIn and hard copies. The complete data collection period took over 02 months in which initially the data were collected electronically, whereas in the later phase the participants were approached for the interviews.

The software analysis and simulations for this research were majorly carried out by importing the data collected from the questionnaires into the Predictive Analysis Software PASW-18.0 version formerly known as statistical package for the social sciences (SPSS-18). It is a statistical software developed by IBM for data management, multivariate analysis and advanced analysis.

The validity and reliability of the research instrument are essential in research data collection. Here in this study, the research instrument was questionnaires. Thus, an application of a validity test was carried out on the data collected from the participants and all the questionnaires were valid for the reliability of the data test. Afterwards, the test regarding the reliability of data was carried out in which 31 items of the FI questionnaire were considered. In the scale of reliability test, the value of Alpha was computed as 0.879, which is considered to be very reliable. It is also important to mention here that only 31 cause factors as established from the pilot studies were included in this FI questionnaire, and not the emerging practices, as it intended to first collect the frequency of occurrence among these points.

To obtain the IMP.I, the data from the first questionnaire, which involved 31 COVID-19 impact factors, were analysed for the authentic values. The N value of valid responses for this survey was 101, which is 80% and considered appropriate. Although the desired number of responses was increased to 125, however, owing to the delayed response and time factor of the research the number of responses was settled at 101 responses for each survey. The result of the FI text is the percentage of FI developed from the score awarded by the participants to each cause factor for assigning ranking, as shown in Table 4.

The 22 factors under the emerging practices and requirements as established from the pilot studies were put under the severity test and made part of the SI questionnaire as a separate section aside from the 31 cause factors of COVID-19, as shown in Table 5.

A major question in the questionnaires was included in the opening section, regarding the number of identified and recognised COVID-19-affected personnel within the participant’s organisation. This question provided the potential numbers as options for the number of participants as >10 but <20, >20 but <50, >50 and <100 and lastly >100. The comprehensive results from a study comparing the percentage of the number of affected persons within the representative organisations, as shown in Figure 8, clearly establish the point of view that 63% of Contractors had the greatest number of COVID-19-affected personnel above the number of 100. This resulted from taking into account the total number of participants with 101 from each survey counting to 202 participants in total. However, as the number of participants from each organisation increased, therefore, only the shortlisted participants from unique organisations accounting for 84 participants from the 3Cs representative of different organisations were taken to present the results in Figures 7 and 8.

Fig. 7

Organisational percentage corresponding to the number of COVID-19 patients.

Fig. 8

COVID-19 affected personnel within the organisation (public vs private sector).

It is also pertinent to mention here that data obtained from survey participants did not account for any mortalities which rendered the mortality figure among the workforce as an insignificant figure. This was primarily because organisations and participants were found to be hesitant to share such data, which was rather a limitation to obtaining direct mortality statistics among the workforce. However, during the interviews, two mortalities during the period were pointed out by the participants and the causes of mortality were associated with COVID-19. Furthermore, during the same period, there was a restriction on the full-strength presence of the workforce owing to which the statistics about absentees were also rendered insignificant and inaccurate as marking attendance like bio-metric and other means were not practiced as a precautionary measure.

This study carried out a comprehensive statistical analysis while taking into account all three stakeholders of the CI of Pakistan. It was found that among all impact factors some factors majorly impacted the operational practices of 3Cs. The ranking of such impact factors was developed based on the IMP.I and the six leading major impact factors are presented for further discussion and relevance concerning the 3Cs, as shown in Table 6.

The increase in planning and overhead costs had been ranked as the most important impact factor by the 3Cs of the CI (Ogunnusi et al. 2021). This is primarily because even during the work suspension, the employees were to be retained and paid, which substantially increased the overhead charges of all the organisations. This resulted in increased overheads of the contractor and reduced the contractor’s profit (Thapa and Priyanka 2020).

Challenges with international manufacturing and shipping were ranked second and the delays in material availability and delivery were ranked sixth. It was assessed that both these factors being related to the supply chain had overlay. The global supply chain had been broken and managing the projects in such cases had been challenging for even global contractors during the pandemic period (Thapa and Priyanka 2020). During the early months of the pandemic, many contractors were unable to source basic materials, such as sand, cement and bricks, while they also suffered from labour shortages. For example, in the United Kingdom, a national shortage of plaster led to significantly increased costs (Marsh 2021). The supply chain crisis had another negative impact on the project costs in the form of abnormal increase in rates and prices of the materials on which the escalation of price adjustment had not been paid. Moreover, the rates quoted by the Contractor before the pandemic were left inappropriate (Hanif and Usman 2021). Other than the permit issuance delays, concerns regarding liquidated damages, cash flow and payment challenges were ranked among the top 6 by the participants as key impact factors of the COVID-19 pandemic. The statistics of each key impact factor in the provinces of Pakistan are shown in Figure 9.

Fig. 9

Province-wise impact contribution of key impact factors.

It is critical to understand that the increase in planning and overhead cost was the first and foremost factor that impacted all three stakeholders of the construction project industry, irrespective of the province. This factor contributed to a maximum of 29% in both Punjab and Sindh Provinces, whereas it was 24% for KPK and the least in AJ&K & GB, at 9%. These statistics are compatible with studies abroad where an average 27% increase in the overall cost of the project was reported due to extended overheads owing to the COVID-19 pandemic (Thapa and Priyanka 2020; Ogunnusi et al. 2021).

Aside from the prime objective of this study, which was to study the COVID-19 pandemic impact across the 3Cs, the secondary objective was to establish a list of emerging practices and the requirements or reliefs sought by the 3Cs to tackle the post-pandemic and future risks and to develop a readiness at the government level. This study ranked the six leading practices among numerous practices, as shown in Table 7. These six leading practices were carried forward to establish the relevance with the 3Cs.

According to AGC, 40% of the contractor firms had to lay off half of their staff due to the COVID-19 outbreak.

Moreover, as a result of the slowing down of construction projects, 27% of the construction companies globally had either furloughed or laid off their project-based employees (Ward and Emily 2020). During this study, the participants greatly favoured and even solicited legislation and regulations regarding the ban on firing or laying off employees during the work suspension period. This was especially required for the private sector in Pakistan as most of the government clients and authorities offer permanent employment, whereas the consultants and contractors are mostly private bodies. According to labour unions, around 75% of Pakistan’s total 65 million labour force is unregistered (Latif and Aamir 2020).

The implementation of social distancing and other safety policies and their enforcement by the client departments was key to continuing safe operation of the construction. It required the development and updating of plans and procedures for both office and job site operations compliant with the most updated standards, regulations and orders, including advice and counsel regarding Occupational Safety and Health Administration (OSHA) standards (Chivilo et al. 2020).

Digitalising construction site monitoring was a major factor and was imperative for economic restart after the shutdown. It was obvious that without the use of advanced technology, the performance gap could not be filled (ECEC 2021). The use of latest engineering communication techniques like 4D and 5D BIM could be used to bridge the gap developed as a result of the pandemic.

Another aspect that may be brought to reduce the exposure of individuals to the site was by limiting the working shift of the construction site workers to 8 h. The average work shift on fast-track mega projects in Pakistan was around 10-12 h, which greatly increased the risk of contracting the pandemic. This limitation in shifts with no overtime can create more jobs with increased productivity, which was otherwise limited due to on-site permit issues and regulations.

There was a dearth of studies providing key impact factors or otherwise nominating specific factors that were to be dealt with by the public and private sectors while tackling the pandemic. In this section, a comparative analysis of the six major impact factors as found out in this study with other studies of the region and the world is shown in Table 8, to highlight the most significant and globally impacting factors.

The critical analysis also considered similar studies carried out globally to find out the most critical factors as (i) permit issuance delayed as a result of remote work and (ii) delays in material availability and delivery. Whereas, other factors had also been found significant from the literature review except for the developed countries like the United States of America and the Gulf Cooperation Council where the CI was much more advanced. However, the study in Pakistan’s neighbouring country Iran being a developing country possessing similar construction traits had similar significant impact factors as a result of COVID-19.

The permit issuance delay as a result of remote work had been highlighted as an important and key factor by many studies, because public sector employees were much more relaxed outside their jobs as compared with the private sector. Moreover, the major number of client departments were public sector organisations from all over the world (Francis et al. 2013). So this was a global issue being faced by the contractors, which should be dealt with by a quick communication and decision-making process. The simplest way to accelerate was that the client and the consultant should avoid delays in approving documents and decision-making by setting out clear rules and regulations while working from home using digitalisation techniques (Eik-Andresen et al. 2016).

The ‘delays in material availability and delivery’ were a key factor primarily because of discontinuation of national and international supply chains due to the pandemic, and even the most efficient contractors were not able to meet the planned progress (Alsharef et al. 2021). A study carried out on 12 tunnel construction projects globally identified a shortage of materials as the third most significant risk impact factor in project delay and failure (Wang et al. 2020). The mitigation plan involved multiple measures that were already being implemented around the globe at both national and provincial levels. These measures included timely communication and planning with suppliers, seeking assistance from the local government and coordinating with the transport department. However, the success of the aforesaid measures would depend on the active interest and radical steps of the concerned departments (Wang et al. 2020).