The purpose of this study was to examine the extent of awareness and adoption of lean construction (LC) in Southwest, Nigeria with a view to enhance project performance.
A convenient sampling method was used to randomly select 165 built environment professionals in Ekiti and Osun State, Nigeria who supplied the research data through a questionnaire survey. This built environment professionals consisted of 40 Engineers, 51 Architects, 44 Quantity Surveyors and 30 Builders. Data analysis was carried out using both descriptive (frequency, percentage and mean score) and inferential (Cronbach’s alpha coefficient and Analysis of Variance (ANOVA) statistics).
The study revealed that the respondents’ general awareness of LC is low (MS = 2.44). Further results showed that the extent of understanding of the built environment professionals about the key concepts of lean philosophy is low (MS = 2.39). It was also revealed that the extent of adoption of LC is very low (MS = 1.88). In the same vein, the extent of adoption of the key concepts of LC is very low (MS = 1.95). More results indicated that the area of work of the respondents accounted for a significant difference (p = 0.002) in the rating of their extent of awareness of LC, as well as its key concepts. On the contrary, the profession of the respondents did not account for a significant difference (p = 0.355) in the rating of their extent of awareness of LC, as well as its key concepts. The final result showed that the area of work of the built environment professionals as well as their profession could not account for a significant difference in their rating of the extent of adoption of LC and its key concepts in the study area
The study correlates low awareness and very low adoption of LC and its key concepts to project performance in the study area. As such, increased awareness and more importantly, extensive adoption of LC would enhance improved project performance in the study area.
The study attempted to expose the extent of awareness and adoption of LC in Southwest, Nigeria. The delineation of the opinions of the respondents on the axes of their profession and area of work affirmed its originality.
Introduction
Countries in many continents of the world have accepted the implementation of lean principles in their manufacturing as well as the construction industries as a major strategy in performance improvement drive. Examples of such nations include but are not limited to the UK, the USA, Germany, Spain, France and South Africa (Singh et al., 2023; Habibi Rad et al., 2022). The adoption of lean construction (LC) is hinged on the need to avert the notoriety of the construction industry for its historically low efficiency, sub-optimum performance, low productivity and lack of pollution control management (Ahmed et al., 2021; Rosenbaum et al., 2012) as well as the demand for improved project performance from stakeholders has been a major push to researchers and professionals to continue to unearth the various ways to navigate the complex project delivery environment of the 21st century (Raja et al., 2020). This is not only to meet expectations but also to exceed them about construction project cost, completion time, quality, safety requirements and total stakeholders’ satisfaction (Li et al., 2017).
One of the answers to the much-desired improvement to the delivery of construction projects in general and specifically in developing countries was found in adapting the lean principles from the manufacturing industry as promulgated by Toyota Company led by engineer Ohmn (Liker, 2005). In the opinion of Basu et al. (2021), the need for the adoption of the lean philosophy was hinged on the ever-increasing tense competitive environment of the 21st-century business atmosphere where companies and industries need to put a very stringent cost and performance improvement in place to have an edge or at least compete favourably with their counterparts as globalization and liberalization of the global market has made business competition a global affair (Pakdil and Leonard, 2014) as such the survival of companies and industries depends on how strong their competitive edge is about their other competitors (Jasti and Kodali, 2015).
Lean production philosophy adopted in the construction sector with LC nomenclature came to the fore in the construction industry with the publication of Koskela (1992). Lukowski (2010) defined LC as the practical adaptation of lean manufacturing principles, or lean thinking, in the built environment. Lean principles from there origin were formulated as the need to reduce waste and improve efficiency became imperative, as such it has been proven over the years that the application of lean principles wherever could be applied to reduce waste, improve delivery time and ultimately enhance efficiency (Shah et al., 2021; Ahmed et al., 2021). All over the world, the quantum of energy that the construction industry is consuming to discharge its function is enormous. For instance, as established by Zhou et al. (2018), the Chinese construction industry consumes about 33% of the country’s raw materials and energy to discharge its functions. This high quantum of raw materials and energy consumption has been attributed to the use of the traditional project management strategy (Singh et al., 2023). In contrast to this, however, several studies in developed economies (Xing et al., 2021; Awad et al., 2021; Hamzeh et al., 2021; Abu Aisheh et al., 2021) have alluded to the fact that the application of lean principles is a game-changer as the industry would benefit in terms of cost saving, enhanced project quality, improved productivity, increased profitability, improved project safety and sustainability.
Another imperative of the adoption of lean philosophy in developing countries is pivotal to the fact that just like when the lean thinking and philosophy was first propounded by the Toyota Company as a solution to the then premium spirit crisis of 1973, it became imperative to cut waste and reduced the production lead time which was characteristics of the then America Traditional production system. The Japanese model led by Toyota was able to convince the world that production profitability could still be achieved despite the economic downturn through lean thinking (Yu &Ye, 2023). The construction industry in developing countries is at a stage where the need to deliver projects at a very stringent cost and time is imperative. This demand is an offshoot of the increase in the cost of construction materials, increased performance objectives, intense competition within organisations and the notoriety of poor project performance which developing economies are noted for (Olatunde and Alao, 2017; Koko et al., 2013)
The construction industry most especially in developing countries is dominated mainly by multinational and medium/small size indigenous contractors. The level of capability and capacity of each of this class of contractors are different (Olatunde et al., 2022), therefore the adoption of the lean principle will help each category of contractor to breach the predisposed factors that make them at a disadvantage when competing for jobs. For example, large multinational foreign contractors have the advantage of high technical know-how with sophisticated mechanical equipment as compared to their local indigenous counterparts but, their overhead is always higher which often places them at a disadvantage when competing for jobs most especially when the construction cost is a major consideration by the client.
Since the pioneering publication of Koskela (1992), researchers and professionals on the international front have devoted substantial time and energy to bringing to the fore the lean philosophy (Li et al., 2020), its theory and application (Zhang and Chen, 2016), lean implementation (Xing et al., 2021; Sarhan et al., 2017; Adamu and Adulhamid, 2016), challenges to lean adoption/implementation (Singh et al., 2023; Evans et al., 2023; Ahmed and Sobuz, 2020); lean awareness and benefits (Ahmed et al., 2021). In the context of the African continent and the Nigerian construction industry specifically, however, much research output is not in the public domain that details the state-of-the-art on LC. Although, Oke et al. (2019) examined the challenges to the implementation of LC practices, Akinradewo et al. (2018) investigated the benefits of adopting LC, both in the South African Construction industry. In the Nigerian Construction Industry (NCI) however, the few studies on LC have left some research gaps in terms of study area and methodology. For instance, Adegbembo et al. (2016) assessed LC practice in the NCI with Ondo State as a study area. The study area for Adamu and Adulhamid (2016) was Yobe State and Northeast Nigeria, and they adopted a case study approach. Oladiran (2017) examined the usage of LC techniques in Nigeria using a qualitative research approach and Lagos as the study area. The respondents for Babalola et al. (2019) were drawn from Lagos, Abuja, Port-Harcourt, Enugu and Kaduna. Musa et al. (2023) examined awareness and barriers of LC in North-west Nigeria. Sholanke et al. (2019) assessed the prospects and challenges of LC practice in Lagos State. It is imperative from these examples that previous research on LC has not exposed the extent of awareness and adoption in Osun and Ekiti states.
Considering the size of Nigeria within the African continent and the world at large, it will be a worthwhile research effort to unravel the extent of awareness and adoption of LC in the country. Furthermore, the need for research efforts on awareness and adoption of lean practice in Nigeria in a time like this is essential as the country is embarking on many mega building and civil engineering projects with their construction cost running to billions of dollars. Examples of such projects included; the construction of the second Niger bridge, Lagos to Calabar Coaster road, construction of the Lagos Ibadan expressway, Eko Atlantic project, Lagos Light Rail, World Trade Centre, Abuja, Lekki Free Trade Zone, Abuja Millennium Tower and Construction of a 1400 MW Gas Turbine Power Station in Delta State. The adoption of the lean principles on these projects would have improved quality, safety, cost, productivity and enhance environmental impact (Ahmed et al., 2021). One of the major LC implementation lessons that the Nigerian construction industry has learned was brought to the fore by Adamu and Adulhamid (2016). The study found that implementation of LC brought about value optimization of construction resources, stable workflows, a drastic reduction in emergency resource requests and enhanced significant increase in productivity. The objectives of the study therefore were to examine the extent of awareness and adoption of LC in the NCI; and examine the relationship between the profession and area of work of the respondents with their extent of awareness and adoption of LC this was to enhance project performance in the study area.
Literature review
The construction industry in Nigeria
The construction industry, known for its potential to drive social and economic growth, holds a unique and complex nature, involving a diverse range of professionals and non-professionals engaged in construction works (Babalola et al., 2019; Akinradewo et al., 2018). Timely project completion and cost control remain persistent challenges, with substantial time and cost overruns observed in construction projects due to their complex nature. Assaf and Al-Hejji (2006) found that 70% of construction projects take longer than expected, and around 14% exceed their budgeted costs with roughly 10% of the materials purchased for these projects ending-up going to waste. Similarly found that 35% of the construction projects in public and 10% of those in private universities were completed at the estimated cost. In contrast, no construction projects were completed within the planned time in public universities, but 20% were completed within the planned time in private universities (Olatunde and Alao, 2017). It is therefore imperative to study the level of awareness and adoption of key concepts and approaches of LC by construction professionals that will help in minimizing the amount of waste produced during the construction process and also enhance project performance and construction process improvement. The Lean approach has gained a strong foothold in the construction sectors of developed countries like the USA and UK, where it is recognized for its contribution to achieving sustainability in building projects (Babalola et al., 2019).
Key concepts of lean construction
LC is a management philosophy and set of principles derived from the lean thinking manufacturing approach pioneered by Toyota Production System (TPS) in the 1950s (Ballard, 2000; Koskela, 2000) and has gained widespread acceptance in the global construction industry but inadequate awareness and adoption of LC techniques presents a significant challenge within the Nigerian construction process (Oladiran, 2017). The LC concept serves as a philosophical approach to management, with its primary emphasis being the identification and elimination of waste throughout the entire journey of a product’s value stream. This approach is not limited solely to the producing organizations but also extends to encompass the broader supply and implementation chain network (Ma et al., 2018). LC seeks to eliminate waste (Alarcón et al., 2011; Amaratunga et al., 2017), reduce non-value-adding activities (Abdelhamid and Everett, 2010), enhance efficiency and improve project outcomes in the construction industry (Sacks et al., 2009). Globally, the LC concept has gained significant recognition and adoption as researchers and practitioners have reported numerous successful lean implementations in various countries.
In recent years, the concept of LC has emerged as a promising approach to enhance project performance through the elimination of waste and the optimization of processes by maximizing value, minimizing waste, improving flow and involving stakeholders (Alarcon et al., 2020). The report on LC implementation in Nigeria is not copious. A literature search of previous studies on the concept of LC implementation in the country has identified Oladiran (2017) and Adamu and Adulhamid (2016) as the only two studies that reported findings about LC implementation in Nigeria. Adamu and Adulhamid (2016) submitted that implementation of LC brought about value optimization of construction resources, stable workflows, a drastic reduction in emergency resource requests and enhanced significant increase in productivity in the twenty housing units that serve as a case study for the research, Oladiran (2017) found that fail-safe quality and safety, daily huddle meetings, increased visualisation and the 5S process were poorly used in Lagos State, their implementation contributed to improved workflow on sites, maintenance of good site organisation and increased job satisfaction among employees. On the contrary, the study further submitted that Last Planner® System (LPS®), first-run studies, just-in-time (JIT), total production maintenance, concurrent design, kaizen, design for buildability and supply chain management techniques were not used at all.
LC techniques: a global perspective
Various studies worldwide have examined the adoption of LC techniques. The study by Aslam et al. (2022) proposed a framework that aids in the selection of suitable lean tools by considering their intended purposes and capabilities. The study introduced a comprehensive list of the following lean tools and techniques: daily huddle meetings; 5S; concurrent engineering; visual management; first run studies; just in time; Six Sigma; fail-safe practices for quality and safety; value stream mapping; last planner system; and kaizen, among others notable techniques.
In a similar vein, Enshassi et al. in their study focused their attention on implementing eight essential LC techniques with the objective of minimizing accidents on construction projects within the Gaza Strip. The study revealed that LC concepts were not optimally implemented on construction projects within the Gaza Strip. Babalola et al. (2018) conducted a study to evaluate the extent to which 32 lean tools and techniques were recognized and implemented within the Nigerian construction sector. The study’s findings underscored that lean techniques are not widely embraced within the NCI. Similar studies conducted by Sarhan et al. (2017) also found comparable results, indicating that the effective implementation of LC techniques in Saudi Arabia was lacking. In addition, the studies conducted by Ogunbiyi et al. (2014) in the UK and Aziz and Hafez (2013) in Egypt identified multiple techniques that facilitate lean implementation and concluded that LC can indeed be realized through the application of these techniques. These studies conducted across different countries have consistently shown challenges in the widespread implementation and adoption of LC techniques, emphasizing the need for further research and efforts to promote lean practices in the construction industry worldwide.
Awareness and adoption of LC in southwest Nigeria
The awareness of LC in Southwest Nigeria is critical for its successful adoption by all professionals in the built environment. According to Oyedele (2018), global awareness of LC has been on the increase, with various countries and regions actively implementing its principles to optimize construction processes. Nevertheless, it is imperative to recognize that awareness levels of LC can vary considerably across different geographical contexts. The extent of familiarity with the concept of LC among construction stakeholders in Southwest Nigeria is an important factor in its adoption because you cannot practice what you do not have adequate knowledge about. The implementation of its principles and practices holds the potential to effectively eradicate any waste generated during the construction process, as highlighted by (Babalola et al., 2018). In the words of Oladiran (2017), implementing lean techniques in the initial phases of construction projects leads to improved environmental sustainability, minimized waste generation, boosted profitability and the promotion of sustainable construction practices, among various other benefits. Research conducted by Nani (2019) opined that awareness levels in developing countries, including Nigeria, lag behind those in more developed counterparts. This aligns with the findings of Babalola et al. (2018) in their study on evaluating the awareness and utilization of 32 lean tools and techniques in the Nigerian construction sector. The study’s conclusion stressed a low level of adoption due to inadequate awareness of lean techniques in the NCI. This inadequacy of awareness in the Southwest region could pose a barrier to the widespread adoption of LC techniques. Evans et al. (2023) noted that the adoption of LC practices in Southwest Nigeria is influenced by economic conditions, economic stability, growth prospects and resource availability. One pivotal factor contributing to the extent of LC adoption in Southwest Nigeria is the economic conditions prevalent in the area. Economic stability, growth prospects and resource availability significantly shape the readiness of construction firms and professionals to integrate lean practices into their operations (Hassan et al., 2016). Moyo and Chigara (2021) undertook a comprehensive analysis of barriers to LC implementation in developing countries, ultimately identifying key hindrances. They concluded that barriers related to integration, performance improvement, human capital management and quality assurance are the most prominent factors impeding the seamless integration of lean practices in construction projects within these regions.
Project performance enhancement through LC
Research (Raja et al., 2020; Adamu and Adulhamid, 2016) consistently confirms that LC principles have a favorable influence on project performance. These principles lead to several advantages, including shorter project durations, reduced costs, improved quality and increased stakeholder satisfaction, as noted by Alashwal et al. (2021). In the context of Nigeria, where project delays and cost overruns have been persistent challenges, these benefits hold particular significance (Olatunde and Alao, 2017). Babalola et al. (2019) grouped the benefits of LC into three primary domains: economic gains, social advantages and environmental benefits. Within the economic realm, the adoption of lean principles yields benefits such as cost savings, time efficiencies and enhanced project quality. Specific benefits in this category encompass reduced project timelines, lowered construction expenses, improved project quality, continuous enhancements in project processes, better inventory management and risk mitigation, among others (Oladiran, 2017; Adamu and Adulhamid, 2016). LC also contributes to various other positive outcomes, as evidenced by multiple studies. Some research carried out by Bajjou et al. (2017), and Sarhan et al. (2018) shows that using LC practices can lead to cost reduction in construction. Other studies (Oakland and Marosszeky, 2017; Bajjou and Chafi, 2018) also found that these practices can improve the quality of construction. According to Sarhan et al. (2018), using lean methods can also make construction projects finish faster, that is a reduction in project duration. Moreover, LC fits well with sustainable development principles (Dixit et al., 2017).
Figure 1 illustrates the flow chart of the research methodological process adopted for this study.
The workflow diagram contains sequential steps connected by arrows. The first box is labelled Literature Review. An arrow points to the next box labelled Design of Questionnaire. Another arrow points to Data Collection. A downward arrow leads to Data Analysis. From Data Analysis, three branches appear. One arrow points to a box labelled Descriptive with items M I S, frequency, and percentage. A second arrow points to a box labelled Reliability Test with Cronbach alpha. A third arrow points to a box labelled Analysis of Variance written as A N O V A. Arrows from these analysis steps converge and point to a final oval labelled Results.Flow chart for research methodological process
The workflow diagram contains sequential steps connected by arrows. The first box is labelled Literature Review. An arrow points to the next box labelled Design of Questionnaire. Another arrow points to Data Collection. A downward arrow leads to Data Analysis. From Data Analysis, three branches appear. One arrow points to a box labelled Descriptive with items M I S, frequency, and percentage. A second arrow points to a box labelled Reliability Test with Cronbach alpha. A third arrow points to a box labelled Analysis of Variance written as A N O V A. Arrows from these analysis steps converge and point to a final oval labelled Results.Flow chart for research methodological process
Research hypothesis
The following null hypotheses were formulated to guide the study:
The profession of the respondents did not account for a significant difference on their opinion in awareness and adoption of LC.
The area of work of the respondents did not account for a significant difference on their opinion in awareness and adoption of LC.
Methodology
The study examined the extent of awareness and adoption of LC in Southwest Nigeria. Two Southwest states Osun and Ekiti were used as the study area. The choice of the two States was due to their similarity in characters (Olatunde, 2019) and proximity to the researchers which aided ease of data collection, as data collection lies at the heart of research. Another motivation for the selection of Osun State as one of the study areas lies in the fact that the state has been recognized by scholars as one of the most urbanized states in Nigeria (Dadamola et al., 2021). Moreover, the noticeable surge in construction activities within the two states in recent times serves as another motivation for their selection.
A quantitative research approach was adopted for data collection with the use of a structured questionnaire. The choice of quantitative research approach was preferred to the qualitative approach for this study because the study intended to quantify the phenomenon being investigated by way of generating numerical data or data that can be transformed into useable statistics, as such the use of qualitative research approach would be inadequate as it is regarded as exploratory and only used to uncover trends in thoughts and opinions (Olatunde and Odeyinka, 2021). The study considered the use of questionnaires the most appropriate for data collection due to the advantage of easy data collection with comparatively large coverage as compared with other methods of data collection. The data collection questionnaire was divided into two sections. Section 1 focused on gathering information about the respondents’ backgrounds. These background-related questions were crucial to confirm that the respondents had the necessary qualifications to provide the required information. The next segment of the questionnaire was designed to ask questions relating to the objectives of the study and questions were asked using a five-point Likert scale (1-very low, 2-low, 3-moderate, 4-high and 5-very high) as adopted in (Pacchini et al., 2019; Olatunde et al., 2021).
The target population for data collection was Architects, Quantity Surveyors, Engineers and Builders. The sampling frame for the target population was 2,949 as obtained from the respective professional associations from each state. A sample size of 300 respondents was selected through a convenient sampling technique. The use of a convenient sampling method was adopted due to its superiority in cost-effectiveness, time-saving and ease of access as compared to other methods of sampling. These advantages were considered important by the researchers to achieve the aim of the study. The distribution of the questionnaire was carried out by the researchers themselves through physical delivery and WhatsAapp medium. Of the 300 questionnaires distributed to the targeted population, 165 were retrieved, this represents a 55% response rate. The decision to proceed with this response rate was justified by the fact that extant literature (Oke and Ogunsemi, 2009; Akintoye, 2000) has established that a response rate of between 20 and 30% is adequate for data analysis. However, after a complete screening and check for completeness, only 156 were found usable with complete responses to all questions asked and were therefore, used for data analysis. For data analysis, frequency, percentage, mean score, Cronbach’s alpha coefficient and analysis of variance (ANOVA) analysis were used. While the Mean score was used to measure the average rating of professionals on the extent of awareness and adoption of LC, the Cronbach’s alpha coefficient was used to measure the internal consistency and reliability of the data. ANOVA was used to test the hypotheses formulated by the study by delineating the opinion of respondents regarding their profession and area of work (academics, industrial practitioners and public works).
Re-Statement of research hypotheses
Two hypotheses were proposed to further quantitatively examine the objectives of the study.
The profession of the respondents did not account for a significant difference in their opinion on awareness and adoption of LC.
The area of work of the respondents did not account for a significant difference in their opinion on awareness and adoption of LC.
Results
Results indicated that the Cronbach’s alpha coefficient of 0.891 and 0.918 respectively were obtained for awareness and adoption of LC. Since the coefficients are both greater than 0.7 value set by DeVellis (2003) this implies that the result is reliable and consistent.
Table 1 indicates the profile of the respondents. The questionnaire administration cut across the targeted respondents as 32.7%, 26.9%, 25.0% and 15.4% were Architects, Quantity Surveyors, Engineers and Builders respectively. The areas of work of the respondents were academics (32.7%), public works (44.2%) and industrial practitioners (23.1%). The respondents could be considered to have adequate on-the-job experience as 55.8% of them have more than 10 years of experience in the NCI. The academic qualification of the respondents shows that they have the required academic qualifications for them to understand and be able to supply the information required of them as 53.9% have Masters and PhD in their various disciplines, while 23.1% were holders of Bachelor of Science/Technology. All the respondents were members of their various professional associations. While 63.5% of the respondents were associate members, 9.6% were fellows of their various professions. This background information shows that the respondents were eminently qualified to supply the information required from them and that their responses could be relied on as they have the requisite academic, professional and on-the-job experience.
Profiles of respondents to questionnaire
| Category | Classification | Frequency | Percentage |
|---|---|---|---|
| Profession of respondent | Architects | 51 | 32.7 |
| Quantity surveyors | 42 | 26.9 | |
| Engineers | 39 | 25.0 | |
| Builders | 24 | 15.4 | |
| Total | 156 | 100.0 | |
| Area of work | Academics | 51 | 32.7 |
| Public works | 69 | 44.2 | |
| Industrial practitioner | 36 | 23.1 | |
| Total | 156 | 100.0 | |
| Years of experience | 1–5 | 21 | 13.5 |
| 6–10 | 48 | 30.7 | |
| 11–15 | 63 | 40.4 | |
| 16–20 | 21 | 13.5 | |
| ≥21 | 3 | 1.9 | |
| Total | 156 | 100.0 | |
| HND | 21 | 13.5 | |
| PGD | 15 | 9.5 | |
| Highest academic qualification | BSc/BTech | 36 | 23.1 |
| MSc/MTech/MBA | 63 | 40.4 | |
| PhD | 21 | 13.5 | |
| Total | 156 | 100.0 | |
| Membership of professional bodies | NIA | 51 | 32.7 |
| NIQS | 42 | 26.9 | |
| NSE | 39 | 25.0 | |
| NIOB | 24 | 15.4 | |
| Total | 156 | 100.0 | |
| Type of membership | Graduate | 15 | 9.6 |
| Probationer | 27 | 17.3 | |
| Associate member | 99 | 63.5 | |
| Fellow | 15 | 9.6 | |
| Total | 156 | 100.0 |
| Category | Classification | Frequency | Percentage |
|---|---|---|---|
| Profession of respondent | Architects | 51 | 32.7 |
| Quantity surveyors | 42 | 26.9 | |
| Engineers | 39 | 25.0 | |
| Builders | 24 | 15.4 | |
| Total | 156 | 100.0 | |
| Area of work | Academics | 51 | 32.7 |
| Public works | 69 | 44.2 | |
| Industrial practitioner | 36 | 23.1 | |
| Total | 156 | 100.0 | |
| Years of experience | 1–5 | 21 | 13.5 |
| 6–10 | 48 | 30.7 | |
| 11–15 | 63 | 40.4 | |
| 16–20 | 21 | 13.5 | |
| ≥21 | 3 | 1.9 | |
| Total | 156 | 100.0 | |
| 21 | 13.5 | ||
| 15 | 9.5 | ||
| Highest academic qualification | BSc/BTech | 36 | 23.1 |
| MSc/MTech/MBA | 63 | 40.4 | |
| PhD | 21 | 13.5 | |
| Total | 156 | 100.0 | |
| Membership of professional bodies | 51 | 32.7 | |
| 42 | 26.9 | ||
| 39 | 25.0 | ||
| 24 | 15.4 | ||
| Total | 156 | 100.0 | |
| Type of membership | Graduate | 15 | 9.6 |
| Probationer | 27 | 17.3 | |
| Associate member | 99 | 63.5 | |
| Fellow | 15 | 9.6 | |
| Total | 156 | 100.0 |
The construction professionals’ level of awareness of LC was measured in two ways. The first method adopted was to ask a direct question about their extent of awareness of LC philosophy, while the second method was to measure their extent of awareness about the key concepts of LC and thereby draw inferences about their extent of awareness of LC. Table 2 shows the result of the extent of the general awareness of the construction professionals about LC philosophy. The result indicated that the extent of awareness of the respondents about LC is low (MS = 2.44). When the result was discriminated based on the profession of the respondents (architecture, quantity surveying, engineering and building technology), the result showed that there was no significant difference on the opinion of the different categories of the respondents (p = 0.335). This implied that the profession of the respondents cannot account for a significant difference in their extent of awareness of LC. The result of further comparison of the opinions of the respondents based on their area of work (academics, industrial practitioner and public works) shows that the area of work of the respondents accounts for a significant difference in their extent of awareness about LC philosophy (p = 0.002). This result implied that, the area of work of the respondents accounted for a significant difference in their extent of awareness about LC.
Extent of awareness of LC
| Based on profession (ARC,QS,ENG&BLR) | Based on area of work (ACA,IP &PW) | ||||
|---|---|---|---|---|---|
| Variable | Mean score | F-stat | p-Value | F-stat | p-Value |
| Extent of awareness of LC | 2.44 | 1.108 | 0.355 | 7.154 | 0.002 |
| Based on profession (ARC,QS,ENG&BLR) | Based on area of work (ACA,IP &PW) | ||||
|---|---|---|---|---|---|
| Variable | Mean score | F-stat | p-Value | F-stat | p-Value |
| Extent of awareness of | 2.44 | 1.108 | 0.355 | 7.154 | 0.002 |
Note(s): ARC = architects, QS = quantity surveyors, ENG = engineers, builders
ACA = academics; IP = industrial practitioners; PW = public works
Therefore, the hypothesis that the profession of the respondents did not account for a significant difference in their extent of awareness of LC was accepted while the hypothesis that the area of work of the respondents did not account for a significant difference in their extent of awareness of LC was rejected.
Table 3 shows the extent of awareness of the respondents to the key concepts of LC. The overall average mean score of the extent of awareness of professionals in the study area shows that their extent of awareness about the key concepts of lean philosophy is low (MS = 2.39). Of the 17 key concepts of LC measured by the study, the respondents’ rating shows that their extent of awareness of key concepts of LC was only moderate on one of the key concepts-“teamwork and value-based management” (MS = 3.23). While the result of the respondents’ opinions on the other key concepts is low (MS ranges from 1.83–2.92). The result of the discrimination of the opinions of the respondents on the key concepts of LC based on their profession indicated that on the overall analysis, there was no significant difference in the opinion of Architects, Quantity Surveyors, Engineers and Builders on their extent of awareness of the key concepts of LC in the study area (p = 0.076). However, analysis of each key concept shows that the respondents’ opinions were divergent on 24% of the key concepts measured by the study.
Extent of awareness of key concepts of LC
| Key concepts | Overall mean | Rank | Based on profession (ARC, QS, ENG & BLR) | Based on area of work (ACA, IP & PW) | ||
|---|---|---|---|---|---|---|
| F-stat | p-Value | F-stat | p-Value | |||
| Teamwork and value based management | 3.23 | 1 | 0.506 | 0.606 | 0.309 | 0.819 |
| Total productive maintenance | 2.92 | 2 | 2.672 | 0.079 | 1.577 | 0.207 |
| Just in time | 2.67 | 3 | 9.226 | 0.000 | 0.966 | 0.416 |
| 5 Whys | 2.58 | 4 | 3.126 | 0.053 | 3.165 | 0.033 |
| Total quality management | 2.46 | 5 | 5.763 | 0.006 | 1.669 | 0.186 |
| Plan, do, check, act | 2.44 | 6 | 0.040 | 0.960 | 2.143 | 0.107 |
| Sort, straighten, shine, standardize, and sustain | 2.44 | 7 | 2.516 | 0.091 | 0.594 | 0.622 |
| Daily huddle meeting | 2.42 | 8 | 3.514 | 0.037 | 7.082 | 0.000 |
| Concurrent engineering | 2.42 | 9 | 1.898 | 0.161 | 2.918 | 0.044 |
| Last planner system | 2.37 | 10 | 2.873 | 0.066 | 4.383 | 0.008 |
| Kaizen | 2.31 | 11 | 2.490 | 0.093 | 8.720 | 0.000 |
| Business process Re-engineering | 2.25 | 12 | 1.018 | 0.369 | 5.810 | 0.002 |
| Six sigma | 2.13 | 13 | 4.304 | 0.019 | 5.531 | 0.002 |
| The kanban system | 2.10 | 14 | 2.097 | 0.134 | 2.364 | 0.083 |
| Pareto analysis | 2.10 | 15 | 2.049 | 0.140 | 2.232 | 0.097 |
| Ishikawa diagram (root cause analysis) | 2.00 | 16 | 0.633 | 0.535 | 3.059 | 0.037 |
| Poka-yoke (error proofing) | 1.83 | 17 | 1.124 | 0.333 | 4.527 | 0.007 |
| Mean average | 2.39 | 2.697 | 0.076 | 3.558 | 0.028 | |
| Key concepts | Overall mean | Rank | Based on profession (ARC, QS, | Based on area of work (ACA, | ||
|---|---|---|---|---|---|---|
| F-stat | p-Value | F-stat | p-Value | |||
| Teamwork and value based management | 3.23 | 1 | 0.506 | 0.606 | 0.309 | 0.819 |
| Total productive maintenance | 2.92 | 2 | 2.672 | 0.079 | 1.577 | 0.207 |
| Just in time | 2.67 | 3 | 9.226 | 0.000 | 0.966 | 0.416 |
| 5 Whys | 2.58 | 4 | 3.126 | 0.053 | 3.165 | 0.033 |
| Total quality management | 2.46 | 5 | 5.763 | 0.006 | 1.669 | 0.186 |
| Plan, do, check, act | 2.44 | 6 | 0.040 | 0.960 | 2.143 | 0.107 |
| Sort, straighten, shine, standardize, and sustain | 2.44 | 7 | 2.516 | 0.091 | 0.594 | 0.622 |
| Daily huddle meeting | 2.42 | 8 | 3.514 | 0.037 | 7.082 | 0.000 |
| Concurrent engineering | 2.42 | 9 | 1.898 | 0.161 | 2.918 | 0.044 |
| Last planner system | 2.37 | 10 | 2.873 | 0.066 | 4.383 | 0.008 |
| Kaizen | 2.31 | 11 | 2.490 | 0.093 | 8.720 | 0.000 |
| Business process Re-engineering | 2.25 | 12 | 1.018 | 0.369 | 5.810 | 0.002 |
| Six sigma | 2.13 | 13 | 4.304 | 0.019 | 5.531 | 0.002 |
| The kanban system | 2.10 | 14 | 2.097 | 0.134 | 2.364 | 0.083 |
| Pareto analysis | 2.10 | 15 | 2.049 | 0.140 | 2.232 | 0.097 |
| Ishikawa diagram (root cause analysis) | 2.00 | 16 | 0.633 | 0.535 | 3.059 | 0.037 |
| Poka-yoke (error proofing) | 1.83 | 17 | 1.124 | 0.333 | 4.527 | 0.007 |
| Mean average | 2.39 | 2.697 | 0.076 | 3.558 | 0.028 | |
Note(s): ARC = architects, QS = quantity surveyors, ENG = engineers, builders
ACA = academics; IP = industrial practitioners; PW = public works
On further discrimination of the opinions of the respondents on their extent of awareness of the key concepts of LC based on their area of work, the result indicated that there was a significant difference in the opinions of built environment professionals working as academics, industrial practitioners and public works (p = 0.028) on the key concepts of LC in the study area. This result showed that the area of work of built environment professionals accounts for a divergence in their extent of awareness of key concepts of LC. The result of the analysis of each concept of LC indicated that their opinions were unanimous on 47% of the key concepts of LC (p value greater than 0.05).
Therefore, the hypothesis that the profession of the respondents did not account for a significant difference in their extent of awareness of the key concept of LC was accepted while the hypothesis that the area of work of the respondents did not account for a significant difference in their extent of awareness of the key concepts of LC was rejected.
Table 4 shows the result of the opinion of the respondents on the extent of adoption of LC in the study area. The extent of adoption of LC in the study area is very low (MS = 1.88). The result of the ANOVA on the basis of the profession (p = 0.093) and the area of work (p = 0.368) indicated that there is no significant difference in the opinions of the respondents on the extent of the adoption of LC in the study area. The result implied that the respondents were unanimous in their opinions on the extent of adoption of LC in the study area.
Extent of adoption of the key concepts of LC
| Variable | Mean score | Based on profession (ARC, QS, ENG & BLR) | Based on area of work work (ACA,IP &PW) | ||
|---|---|---|---|---|---|
| F-stat | p-Value | F-stat | p-Value | ||
| Extent of adoption lean construction | 1.88 | 2.260 | 0.093 | 1.020 | 0.368 |
| Variable | Mean score | Based on profession (ARC, QS, | Based on area of work work (ACA,IP &PW) | ||
|---|---|---|---|---|---|
| F-stat | p-Value | F-stat | p-Value | ||
| Extent of adoption lean construction | 1.88 | 2.260 | 0.093 | 1.020 | 0.368 |
Note(s): ARC = architects, QS = quantity surveyors, ENG = engineers, builders
ACA = academics; IP = industrial practitioners; PW = public works
Therefore, the hypothesis that the profession of the respondents did not account for a significant difference in their extent of adoption of LC was accepted. In the same vein, the hypothesis that the area of work of the respondents did not account for a significant difference in their extent of adoption of LC was accepted.
Table 5 shows the result of the opinions of the respondents on the extent of adoption of the key concepts of LC in the study area. The extent of adoption of the key concepts of LC is very low (MS = 1.95). The result of the test of hypothesis indicated that there is no significant difference in the way respondents rated the extent of adoption of the concepts of LC when their opinions were discriminated along their professional inclination (p = 0.097) as well as their work area (p = 0.063). The unanimity in the opinions of the respondents on the extent of adoption of the key concept of LC implied that their opinion is the true state of affairs on the extent of adoption of the concept of LC in the study area.
Extent of adoption of key concept of LC
| Key concepts | Overall mean | Rank | Based on profession (ARC, QS, ENG & BLR) | Based on area of work (ACA, IP & PW) | ||
|---|---|---|---|---|---|---|
| F-stat | p-Value | F-stat | p-Value | |||
| Teamwork and value based management | 2.46 | 1 | 2.237 | 0.096 | 0.318 | 0.729 |
| Plan, do, check, act | 2.31 | 2 | 1.441 | 0.242 | 0.992 | 0.378 |
| Total quality management | 2.29 | 3 | 3.917 | 0.014 | 3.605 | 0.035 |
| Total productive maintenance | 2.19 | 4 | 1.271 | 0.295 | 1.546 | 0.223 |
| Just in time | 2.08 | 5 | 3.242 | 0.030 | 0.936 | 0.399 |
| Pareto analysis | 2.06 | 6 | 6.385 | 0.001 | 3.834 | 0.028 |
| Daily huddle meeting | 2.00 | 7 | 0.627 | 0.601 | 0.612 | 0.546 |
| Business process Re-engineering | 1.96 | 8 | 4.027 | 0.012 | 7.642 | 0.001 |
| Kaizen | 1.94 | 9 | 2.015 | 0.124 | 0.771 | 0.468 |
| Last planner system | 1.94 | 10 | 3.474 | 0.023 | 5.485 | 0.007 |
| The kanban system | 1.82 | 11 | 2.733 | 0.054 | 3.125 | 0.053 |
| Ishikawa diagram (root cause analysis) | 1.80 | 12 | 2.921 | 0.043 | 2.699 | 0.077 |
| 5 Whys | 1.77 | 13 | 0.704 | 0.555 | 4.897 | 0.012 |
| Concurrent engineering | 1.77 | 14 | 1.012 | 0.395 | 0.119 | 0.888 |
| Sort, straighten, shine, standardize, and sustain | 1.75 | 15 | 0.118 | 0.949 | 0.029 | 0.971 |
| Six sigma | 1.53 | 16 | 0.203 | 0.894 | 1.749 | 0.185 |
| Poka-yoke (error proofing) | 1.50 | 17 | 1.725 | 0.174 | 3.278 | 0.046 |
| Mean average | 1.95 | 2.238 | 0.097 | 2.449 | 0.063 | |
| Key concepts | Overall mean | Rank | Based on profession (ARC, QS, | Based on area of work (ACA, | ||
|---|---|---|---|---|---|---|
| F-stat | p-Value | F-stat | p-Value | |||
| Teamwork and value based management | 2.46 | 1 | 2.237 | 0.096 | 0.318 | 0.729 |
| Plan, do, check, act | 2.31 | 2 | 1.441 | 0.242 | 0.992 | 0.378 |
| Total quality management | 2.29 | 3 | 3.917 | 0.014 | 3.605 | 0.035 |
| Total productive maintenance | 2.19 | 4 | 1.271 | 0.295 | 1.546 | 0.223 |
| Just in time | 2.08 | 5 | 3.242 | 0.030 | 0.936 | 0.399 |
| Pareto analysis | 2.06 | 6 | 6.385 | 0.001 | 3.834 | 0.028 |
| Daily huddle meeting | 2.00 | 7 | 0.627 | 0.601 | 0.612 | 0.546 |
| Business process Re-engineering | 1.96 | 8 | 4.027 | 0.012 | 7.642 | 0.001 |
| Kaizen | 1.94 | 9 | 2.015 | 0.124 | 0.771 | 0.468 |
| Last planner system | 1.94 | 10 | 3.474 | 0.023 | 5.485 | 0.007 |
| The kanban system | 1.82 | 11 | 2.733 | 0.054 | 3.125 | 0.053 |
| Ishikawa diagram (root cause analysis) | 1.80 | 12 | 2.921 | 0.043 | 2.699 | 0.077 |
| 5 Whys | 1.77 | 13 | 0.704 | 0.555 | 4.897 | 0.012 |
| Concurrent engineering | 1.77 | 14 | 1.012 | 0.395 | 0.119 | 0.888 |
| Sort, straighten, shine, standardize, and sustain | 1.75 | 15 | 0.118 | 0.949 | 0.029 | 0.971 |
| Six sigma | 1.53 | 16 | 0.203 | 0.894 | 1.749 | 0.185 |
| Poka-yoke (error proofing) | 1.50 | 17 | 1.725 | 0.174 | 3.278 | 0.046 |
| Mean average | 1.95 | 2.238 | 0.097 | 2.449 | 0.063 | |
Note(s): ARC = architects, QS = quantity surveyors, ENG = engineers, builders
ACA = academics; IP = industrial practitioners; PW = public works
Therefore, the hypothesis that the profession of the respondents did not account for a significant difference on their extent of adoption of the key concepts of LC was accepted, in the same manner, as the hypothesis that the area of work of the respondents did not account for a significant difference in their extent of adoption of the key concept of LC was accepted as well.
Discussion of the result
The low awareness level of LC and its key concepts as found in the study area could be said to align with other previous studies within the African and Asia continents (Olatunji, 2008; Ahmed and Sobuz, 2020; Ahmed et al., 2021; Musa et al., 2023). On the contrary, however, Adegbembo et al. (2016) and Babalola, et al. (2018) found a seemingly high awareness of lean philosophy within their study areas. Similarly, this study could be said to be in contrast with Raja et al. (2020) which found an appreciable awareness level of lean Six Sigma (one of the key concepts of LC) in the manufacturing firms in developing economics. The extent of awareness in the Nigerian construction industry did not translate to adoption; this is evidenced by the difference in the extent of awareness (low) and adoption (very low). The very low extent of adoption of LC and its key concepts in the study area agrees with the findings of Sholanke et al. (2019). The low adoption of LC may be one of the reasons for the low performance of construction projects in the study area as established by previous studies (Memon et al., 2012; Olatunde and Alao, 2017). This assertion was premised on the fact that according to Xing et al. (2021) the adoption and implementation of key lean concepts such as the Last Planner System, kanban system, JIT, prefabrication, internet of things, quality and safety management and continuous improvement, all contributed to the improvement of project performance on projects case studies in Suzhou, China. Adamu and Adulhamid (2016) also validated an improved project performance by the adoption of LC on case study projects in Yobe State Nigeria. Contrary to the low adoption level in the NCI, the adoption of LC in the Kingdom of Saudi Arabia is on the increase (Sarhan et al., 2017).
The result of the comparison of the extent of awareness along the professions that indicated a significant difference could be said to mean that the extent of awareness of construction professionals about LC is influenced by where they work. It appears that those who work in academics are more aware of LC philosophy than the other professionals working in public works and as main industrial practitioners. However, this extent of awareness does not translate to adoption, since the matter of adoption has to do with the construction industry in the study area. This finding implies that there still exists a gap between the theory of LC and its practice in the study area.
Conclusion
The study concluded that construction professionals in Southwest Nigeria have a limited understanding of LC philosophy. This is in addition to a low level of awareness regarding the fundamental concepts of LC. It was further concluded that the profession of the respondents did not account for a significant difference in the extent of awareness of LC nor their extent of awareness about key concepts of LC. However, the areas of work (academics, industrial practitioners and public works) account for a significant difference in the extent of awareness about LC as well as their extent of awareness about the key concepts of LC. It was also concluded that the extent of adoption of LC and its key concepts is very low. The final conclusion is that the profession and the area of work of the professionals in the study area could not account for a significant difference in the extent of adoption of LC or its key concepts. The study contributed to the extant body of knowledge by delineating the extent of awareness and adoption of LC along the profession and area of work of the respondents in the study area. This information will serve as an impetus for improved project performance both in theory and in practice.
Arising from the conclusion of the study, it was recommended that an increase in awareness drive about new technologies and innovative concepts that can enhance project performance improvement from the different professional bodies like the Nigerian Institute of Architects (NIA), Nigerian Society of Engineers (NSE), Nigerian Institute of Quantity Surveyors (NIQS) and the Nigerian Institute of Builders (NIOB). This could be achieved through periodic seminars, workshops and conferences. More recommendations advocated for a deliberate policy direction for an improved project performance drive from the Ministry of Works and Housing this will enhance the adoption of innovative concepts like LC. A deliberate and continuous collaboration between gown (academics) and town (the industry) is recommended so as to foster a closer integration and adaption of academic knowledge into practice.
The study is limited in that the convenient sampling method used for data collection may introduce an element of bias in sampling; hence generalizations might be cautionary. The limitation of data collection to two states in Southwest Nigeria could make generalization to the entire country with caution. The study advocated further study to compare the extent of awareness and adoption in the different regions of Nigeria. Another study could be commissioned to examine the extent of awareness and adoption of LC by selected large construction firms in Nigeria.

