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The Impact of Total Quality Management on Construction
Project Performance in Eti-Osa Local Government Area,
Lagos State, Nigeria.
By
Ernest Chima Osigwe
September 2024
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Table of Contents
Acknowledgement ....................................................................................................... 5
Abstract ....................................................................................................................... 6
List of Figures .............................................................................................................. 7
List of Tables ................................................................................................................ 8
List of Abbreviations ................................................................................................... 9
CHAPTER ONE ........................................................................................................ 10
INTRODUCTION ..................................................................................................... 10
1.1 Background and Context ................................................................................ 10
1.2 Problem Statement .......................................................................................... 12
1.3 Research Rationale .......................................................................................... 14
1.4 Research Aims and Objectives ........................................................................ 15
1.5 Research Questions.......................................................................................... 16
1.6 Structure of the Study ..................................................................................... 16
CHAPTER TWO ....................................................................................................... 18
LITERATURE REVIEW .......................................................................................... 18
2.1 Overview .......................................................................................................... 18
2.2 Construction Project Performance (CPP) ...................................................... 18
2.3 Total Quality Management (TQM) ................................................................. 20
2.4 Malcolm Baldrige National Quality Award (MBNQA) Principles ................. 22
2.5 Conceptual Framework and Hypotheses development .................................. 24
2.6 Total Quality Management (TQM) In Construction Industry ....................... 32
2.7 Research Gap ................................................................................................... 34
CHAPTER THREE ................................................................................................... 35
RESEARCH METHODOLOGY .............................................................................. 35
3.1 Overview .......................................................................................................... 35
3.2 Research Philosophy and Approach ............................................................... 35
3.3 Research Design and Strategy ......................................................................... 36
3.4 The Study Population ...................................................................................... 37
3.5 Sample and Sampling Technique .................................................................... 37
3.5.1 Research Instrument .................................................................................... 38
3.5.2 Validity Test .................................................................................................. 42
3.5.3 Reliability Test .............................................................................................. 42
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3.6 Time Horizon ................................................................................................... 43
3.7 Method of Data Analysis ................................................................................. 43
3.8 Ethical Considerations .................................................................................... 44
CHAPTER FOUR ..................................................................................................... 45
RESULT PRESENTATION AND DISCUSSION..................................................... 45
4.1 Data Preparation ............................................................................................. 45
4.2 Descriptive Presentation .................................................................................. 45
4.2.1 Prequalifying Criteria of Respondents (n=126) .......................................... 46
4.2.2 Demographic Profile of Respondents .......................................................... 46
4.3 Constructs and Associated Factors ................................................................. 48
4.4 Descriptive Statistics........................................................................................ 51
4.5 Research Hypotheses Testing .......................................................................... 52
4.5.1 Research Hypothesis One ............................................................................ 53
4.5.2 Research Hypothesis Two ............................................................................ 54
4.5.3 Research Hypothesis Three ......................................................................... 55
4.5.4 Research Hypothesis Four ........................................................................... 56
4.5.5 Research Hypothesis Five ............................................................................ 57
4.5.6 Research Hypothesis Six .............................................................................. 58
4.6 Multiple Regression Analysis .......................................................................... 59
CHAPTER FIVE ....................................................................................................... 61
DISCUSSION OF FINDINGS .................................................................................. 61
5.1 Summary of Findings ...................................................................................... 61
5.1.1 Leadership (L) and Project Performance ................................................... 61
5.1.2 Strategic Planning (SP) and Project Performance...................................... 62
5.1.3 Customer Focus (CF) and Project Performance ......................................... 63
5.1.4 Workforce Focus (WF) and Project Performance ...................................... 64
5.1.5 Operation Focus (OF) and Project Performance ........................................ 64
5.1.6 Measurement, Analysis and Knowledge Management (MAKM) and
Project Performance.................................................................................................. 65
5.2 Theoretical Contributions and Practical implications ................................... 66
5.3 Recommendations............................................................................................ 68
5.4 Conclusion ....................................................................................................... 70
5.5 Limitations of the Study and Future Research .............................................. 71
CHAPTER SIX .......................................................................................................... 72
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PERSONAL LEARNING AND POTENTIAL IMPACT OF THE STUDY WITHIN
AN ORGANIZATIONAL CONTEXT ..................................................................... 72
6.1 PERSONAL LEARNING AS A RESEARCHER: SELF REFLECTION
...................................................................................... Error! Bookmark not defined.
6.1.1 Description .................................................. Error! Bookmark not defined.
6.1.2 Feelings ........................................................ Error! Bookmark not defined.
6.1.3 Evaluation ................................................... Error! Bookmark not defined.
6.1.4 Analysis ......................................................... Error! Bookmark not defined.
6.1.5 Conclusion .................................................... Error! Bookmark not defined.
6.1.6 Action ............................................................ Error! Bookmark not defined.
6.2 Potential Impact within an Organizational Context ...................................... 72
References .................................................................................................................. 76
Appendix 1: Research Onion .................................................................................. 131
Appendix 2: Questionnaire ..................................................................................... 132
Appendix 3: Consent Form ..................................................................................... 139
Appendix 4: Participant Information Sheet ........................................................... 140
Appendix 5: Histogram of Participant’s Responses MBNQA Questions .............. 143
Appendix 6: Individual Regression Table from SPSS ............................................ 148
Appendix 7: Multiple Regression Table and P-P Plot from SPSS ......................... 154
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Acknowledgement
I wish to convey my gratitude to Arwa Eissa, whose exceptional guidance and support were
invaluable in shaping this dissertation.
I am thankful to the lecturers and colleagues at Worcester Business School for their academic
support and inspiring discussions throughout the course of this MSc program. I extend my
appreciation to the non-academic staff at Worcester Business School and The Hive, whose
daily dedication made learning possible. Furthermore, my gratitude also goes to the
participants and organizations who contributed in making the research possible.
I am profoundly grateful to my family for their infinite support and to my friends for their
steadfast belief in me. Finally, this work is dedicated to God Almighty, who made it all
possible.
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Abstract
This study evaluated the impact of Total Quality Management (TQM) on construction project
performance in Eti-Osa Local Government Area, Lagos State, Nigeria by examining the
impact of six practices from the Malcolm Baldrige National Quality Award (MBNQA)
framework—Leadership (L), Strategic Planning (SP), Customer Focus (CF), Workforce
Focus (WF), Operation Focus (OF), as well as Measurement, Analysis, and Knowledge
Management (MAKM)—on construction project performance. Primary data were gathered
online through a questionnaire with a 5-point Likert scale, disseminated utilising the
Snowball sampling method. A total of 120 practitioners from the public sector of Lagos
State's construction industry, who have been involved in projects within Eti-Osa, participated
in the study. Findings from multiple regression analysis revealed that all six MBNQA
practices impacted project performance positively, indicating that TQM significantly
influenced construction project outcomes. Practical recommendations based on the outcomes
of the study are offered to help construction firms and practitioners in Eti-Osa and across
Nigeria to gain better understanding of the link between TQM and project performance and,
and to effectively implement TQM practices to enhance project outcomes.
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List of Figures
Figure 1: Malcolm Baldrige National Quality (MBNQA) Performance Excellence
Framework………………………………………………………….……………………… 21
Figure 2: Theoretical Model……………………………………………………………… 29
Figure 3: Managerial level of respondents in construction industry….………….……... 45
Figure 4: The Gibbs Reflective Cycle…………………………………………..……… 71
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List of Tables
Table 1: Summary of questionnaire Items………………………………...........................38
Table 2: Prequalifying statistic of respondents………………………………………........43
Table 3: Gender distribution of respondents………………………………………….…..44
Table 4: Distribution of respondent’s years at managerial level...……...…………….…...45
Table 5: Statistical description of MBNQA practices in the construction industry………..46
Table 6: Descriptive statistics………………………………………………………………49
Table 7: Regression analysis of organizational leadership on project performance……….50
Table 8: Regression analysis of strategic planning on project performance……………….51
Table 9: Regression analysis of Customer focus on project performance…………………52
Table 10: Regression analysis of workforce focus on project performance……………..…53
Table 11: Regression analysis of operation focus on project performance…………..……..54
Table 12: Regression analysis of measurement, analysis, and knowledge management
on project performance……………………………………………………………..…….….55
Table 13: Multiple regression analysis of independent variables on project performance... 56
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List of Abbreviations
TQM: Total Quality Management
MBNQA: Malcolm Baldrige National Quality Award
L: Leadership
SP: Strategic Management
CF: Customer Focus
OF: Operation Focus
WF: Workforce Focus
MAKM: Measurement, Analysis and Knowledge Management
PP: Project Performance
CPP: Construction Project Performance
QMS: Quality Management System
NIST: National Institute of Standards and Technology
JUSE: Japanese Union of Scientists and Engineers
ISO: International Organization of Standardization
KMP: Knowledge Management Practices
CRM: Customer Relationship Management
ASEAN: Association of Southeast Asian Nations
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CHAPTER ONE
INTRODUCTION
1.1 Background and Context
The construction industry in Nigeria is expected to record about 3% annual growth rate
between 2023 and 2025, following a 4.8% recovery in early 2022 after the COVID-19
pandemic and other economic downturns (Construct Africa, 2023). The global manufacturing
sector is experiencing accelerated transformations due to climate change, geopolitical shifts,
and the fourth industrial revolution, which is driving technological advances, increased
competitiveness, and market liberalization (Gavin, 2023; Mourtzis et al., 2022). Efficient
resource utilisation is essential for Nigerian enterprises particularly, those involved in
industries with a dynamic nature such as construction, to sustain and improve their
competitiveness.
To effectively compete, construction firms in Nigeria should adopt innovative quality
management standards, shifting from production-focused approaches to competitive,
customer-centric strategies that prioritize client satisfaction (Okolie et al., 2020; Emily,
2023). TQM is broadly acknowledged as a crucial approach for enhancing performance and
competitiveness in many industries globally, encompassing both public and private segments.
The key aim of TQM is to minimize defects, enhance processes, and achieve superior
performance to fulfil and exceed client’s demands (Seetharaman, 2023).
The effectiveness of TQM is substantiated by numerous research as those conducted by Jong,
Sim, and Lew (2019), Wassan et al. (2022), and Dihardjo and Ellitan (2021). These studies
provide evidence that TQM improves organizational performance, with clients increasingly
demanding businesses enhance their products and services, leading to the widespread
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adoption of TQM methodologies (Alanazi, 2020; Lip, 2024). TQM prioritises the attainment
of outstanding quality and effective leadership at every level, placing significant emphasis on
on-going enhancement and the active engagement of employees to achieve customer
satisfaction (Tejaningrum, 2020).
TQM is widely acknowledged for its holistic approach despite the lack of a globally accepted
definition, which aligns with the core principles described by Helmold (2023) and Zainal et
al. (2021) who stressed the importance of on-going enhancement across all aspects of an
enterprise. In the last 20 years, TQM has emerged as a crucial element in acquiring and
sustaining an edge over the competition in many sectors including construction. Its
implementation is crucial for growth, survival, and the achievement of organizational
objectives (Alanazi, 2020; Md. Ashikuzzaman, 2024; Permana, Purba & Rizkiyah, 2021;
Sahney, Banwet & Karunes, 2004).
The successful adoption of TQM and Lean Six Sigma has been instrumental in transforming
companies like Xerox, as highlighted by Kinney (2023). Other organizations like Hewlett-
Packard, Motorola, Harley-Davidson, and Ford also achieved significant improvements in
management strategies and overall performance which they ascribed to the implementation of
TQM (Grant, Shani & Krishnan, 1994; Scheid, 2010). Furthermore, the adoption of TQM has
been linked to enhanced financial results and increased customer satisfaction (Kriemadis,
Sainis & Haritos, 2022; White, 2022). The principles of TQM are evident in modern quality
management practices, including the ISO 9001, MBNQA, Six Sigma and lean production,
which explicitly incorporate TQM’s core principles (ASQ, 2019).
Nigerian construction sector continues to face notable obstacle arising from the insufficient
implementation of TQM, as observed by Egwunatum et al. (2022). According to Ajayi and
Osunsanmi (2018), the adoption of The implementation of TQM in Nigerian construction
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companies is hindered by factors such as insufficient management commitment, lack of
training, limited employee involvement, and poor supplier partnerships. Additional
challenges include inadequate quality documentation, high implementation costs, and poor
planning. These issues result in client dissatisfaction, leading to cost overruns, delays, and
building collapses, preventing global competitiveness. Hence, it becomes imperative to
develop and implement efficient quality management systems, such as TQM, specifically in
regions like the Eti-Osa local government area to enhance productivity and organizational
performance.
1.2 Problem Statement
Despite the significant role of the built-environment sector in a country’s economy, it
continues to encounter obstacles that impede its advancement (Alaloul et al., 2021; Boadu,
Wang & Sunindijo, 2020). These challenges, including stagnant productivity, skill shortages,
and poor quality, are often linked to the industry's highly fragmented nature. This
fragmentation allows those in higher positions to shift the costs and risks down extensive
subcontracting chains to those least capable of managing them, exacerbating these issues
(Sweet, 2024).
Construction companies are under immense pressure to meet client demands for cost-
effective, high-quality products that also comply with environmental regulations, amidst
intense competition (Matters, 2023). In their effort to succeed, companies sometimes resort to
shortcuts or accept lower profit margins, which can compromise quality and other
performance standards (Okuntade, 2015). Given the sector's importance, there is a need for
enhanced efficiency through value-for-money practices, adherence to project timelines, and
cost savings. However, the industry has faced increasing criticism due to the rising number of
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failed or abandoned projects across Nigeria (Daniel, 2019; Atamewan, 2020; Aibinu &
Jagboro, 2002).
The growing complexities and scale of construction projects, coupled with persistent quality
issues, underscore the need for efficient management techniques (Majumder, Majumder &
Biswas, 2022; Jimoh et al., 2016). Furst (2019) and Oyedele, Jaiyeoba & Fadeyi (2012)
highlight that the current challenges in achieving quality standards result in significant
inefficiencies in the utilization of resources such as time, money and others during project
execution. These of factors of budget, duration, and craftsmanship as averred by Oyekunle,
(2024), Tunji-Olayeni et al. (2016) and Aibinu & Jagboro, (2002) critically influence the
performance of construction endeavours.
The construction in Nigeria is currently experiencing heightened demand for improved
performance, which necessitates the adoption of more collaborative approaches and the
implementation of quality management systems (QMS) (Blundell, 2021; Tunji-Olayeni et al.,
2016). Implementing QMS, such as TQM, can minimize the need for rule violations and
rework, while also enhancing overall performance in terms of budget, quality, duration, and
overall fulfilment of client’s expectations (Seetharaman, 2023; Aghimien & Oke, 2016).
Although the advantages of TQM are well acknowledged, significant deficit of evidence
based research on its implementation in many emerging economies such as Nigeria,
specifically in the Eti-Osa local government region still exist. Relevant literature on TQM,
such as studies by Vijayabanu, Karthikeyan & Vijay Surya (2022), Coronel et al. (2021),
Gupta & Khitoliya (2020), Afzal, Hanif & Rafique (2022), Yahya & Alabdullah (2022),
Aghimien et al. (2019), and Salaheldin (2013), stresses the urgent need for further
investigation, with Egwunatum et al. (2021) recommending a comparative analysis across
different regions of Nigeria.
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This present study will explore the influence of TQM techniques on construction endeavours
performance using six MBNQA principles, focusing solely on public sector construction
professionals in managerial positions who have participated in construction endeavours
within Eti-Osa in Lagos State, Nigeria.
1.3 Research Rationale
The construction sector is marked by intense competition coupled with varying levels of
uncertainty, making product quality and customer satisfaction critical. Companies that fail to
meet high-efficiency standards necessary for client satisfaction risk significant revenue
losses. TQM offers a potential solution by emphasizing continuous improvements and
engaging all stakeholders during project execution (Alawag et al., 2020; Ajayi, Akinsiku, and
Salami, 2018; Syed, Ali, and Khatoon, 2016). Despite its potential, the inadequate availability
of evidence-based research on the subject matter in Nigeria’s construction sector, particularly
in Eti-Osa highlights the urgent need for further studies as this present one to fill this void in
knowledge by using six MBNQA practices to assess TQM’s impact on the performance of
construction endeavours in Eti-Osa, Lagos State.
Understanding the significance of TQM's impact on construction project performance in Eti-
Osa cannot be overstated, given the construction sector's significant role in Nigeria's
economic growth (Tunji-Olayeni et al., 2018; Giang and Sui Pheng, 2011; Oxford Business
Group, 2023). Studying the application of TQM in Nigeria might offer important perspectives
for industry stakeholders and regulators alike, leading to evidence-based policies that benefit
the entire sector (Egwunatum et al., 2021; Ayandele and Akpan, 2019). Insights gained from
Eti-Osa could inform interventions across Nigeria, as it mirrors the broader construction
challenges faced in the country. Moreover, comparative evaluations of TQM practices
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globally could foster cross-border knowledge exchange and cooperation toward sustainable
development (Alawag et al., 2023).
An examination of prior research (Abdullahi et al., 2019; Egwunatum et al., 2021; Ahaotu,
2019; Jimoh et al., 2016) emphasises the importance of quality management and shows a
substantial gap in study addressing the influence of TQM principles on project performance.
Consequently, this study will comprehensively evaluate the implications of TQM adoption on
the efficiency of construction projects within Eti-Osa. The findings will be crucial in
establishing knowledge-based guidelines, enhancing industry practices, and promoting
sustainable economic growth in Nigeria's construction sector. Moreover, it will contribute to
the current scope of knowledge on TQM's in relation to construction endeavours in emerging
nations and deepen professional understanding of how TQM practices influence construction
project efficiency.
1.4 Research Aims and Objectives
Research Aim
This present research aims to assess the impact of Total Quality Management (TQM) on the
performance of construction projects (CPF) in Eti-Osa local government area of Lagos state,
Nigeria.
Research Objective
The key study objectives are to;
1. To assess the impact of organizational leadership on the performance of construction
project.
2. To determine the impact of strategic planning on construction project performance.
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3. To ascertain if construction project performance is impacted by customer focus.
4. To determine how workforce focus impacts construction project performance.
5. To find out how construction project performance is impact by operation focus.
6. To determine how measurement, analysis, and knowledge management impact the
performance of construction.
1.5 Research Questions
1. Is construction project performance impacted by organizational leadership?
2. How does strategic planning impact construction project performance?
3. What impact does customer focus have on the performance of construction projects?
4. Does workforce focus impact construction project performance?
5. How is the performance of construction projects impacted by operation focus?
6. Do measurement, analysis and the management of knowledge impact the performance
of construction projects?
1.6 Structure of the Study
This dissertation is structured as follows; the subsequent segment, known as the literature
review, offers an in-depth examination of previous studies of the effect or relationship of
TQM on the general efficiency of construction endeavours, and also introduces the
conceptual model employed. The methodological structure of the study will be discussed in
the third chapter, including the justification for the selected method and how variables are
measured, detailing the research design, technique for collecting data, and the method of data
processing. The fourth chapter delineates the study results, while the fifth chapter scrutinises
the principal findings in relation to the study's objectives and existing literature, emphasising
the study's importance and its academic and professional ramifications. Furthermore, it
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covers recommendations, study limitations, future research suggestions while chapter six
presents the researcher’s personal reflections and the prospective impact of the study within
an organizational paradigm.
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CHAPTER TWO
LITERATURE REVIEW
2.1 Overview
The construction sector, like other production sectors faces challenges that impact efficiency,
with issues in quality and budget management being particularly severe in Nigeria (Bamitale,
Olumide, & Oluwakayode, 2019). Effective project success assessment is vital for identifying
areas for improvement and optimizing future procedures with project managers focus on
measuring success to gauge performance and inform strategic planning, underscoring the
need for clear success criteria (Sastoque-Pinilla et al., 2022; Altuwaim, AlTasan, &
Almohsen, 2023; Homthong, Moungnoi, & Charoenngam, 2024; Beshah et al., 2024). The
global construction sector faces multifaceted challenges, including economic uncertainties,
geopolitical tensions, and environmental concerns, driving a shift towards technological
advancements and sustainability (Buzio, 2023). Effective project outcome management
requires clear success criteria, such as SMART objectives and explicit quality benchmarks, to
enhance project success and stakeholder communication (Alshami, 2018; PMI, 2024). The
next section will explore construction project performance in relation to these objectives.
2.2 Construction Project Performance (CPP)
In today's project-driven economy, projects are central to executing tasks, implementing
changes, and delivering value. This project-centric approach makes performance assessment
critical in evaluating construction projects, as emphasized by the Project Management
Institute (PMI, 2020), as projects generally progress through distinct phases—from initiation
to completion—aimed at producing specific outputs, services, or products within defined
timelines, budgets, and collaborative frameworks. Nevertheless, despite an abundance of
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research, a globally accepted approach in project management for assessing performance
remains yet to be established (Homthong, Moungnoi, and Charoenngam, 2024).
The Iron Triangle, which is a framework that considers time, quality, and cost as important
factors for evaluating construction project performance, has been extensively studied by
researchers (Mellado, Lou, and Becerra, 2019; Caccamese and Bragantini, 2012; Stojcetovic,
2013). These elements, despite criticism, remain vital in construction project performance
assessment since adherence to project timelines is essential for maintaining client trust, while
effective cost management involves balancing various factors such as materials and labour.
Quality assurance, on the other hand, ensures that projects meet stakeholder expectations, and
facilitating the overall safety and efficiency of the project (Eric, 2022). Attaining equilibrium
among these factors is vital for the effective culmination of a project and guaranteeing client
satisfaction.
However, Pink (2021) argues that the construction industry's reliance on the Iron Triangle
often serves as an excuse for the frequent failure to meet project deadlines and budgets, with
delays and cost overruns being commonplace. This perspective emphasises a notable problem
in the industry: the absence of efficient remedies for these enduring issues consequently, this
study seeks to investigate TQM’s role in achieving successful execution of construction
projects that meet client expectations in terms of the Iron-Triangle.
Meng (2012) study further underscores the prevalence of schedule delays, cost overruns, and
quality issues as indicators of poor performance in construction projects. Meng carried out an
exhaustive literature review and concluded that the Iron-Triangle is the primary factor for
assessing the effectiveness of construction endeavours. Through a survey that received a 30%
response rate from 400 construction practitioners in the UK, Meng disclosed that 35.6% of
projects encountered disruptions, 25.2% exceeded their budgets, and 17.7% contained
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substantial flaws. Nevertheless, Meng's study was constrained by a rather low response rate,
which hampers the capacity to apply the findings to a broader population and emphasizes the
necessity for additional studies employing alternative methodologies in other geographical
areas.
Building on Meng’s findings, Mellado, Lou, and Becerra (2019) investigated performance
improvement in the construction industry, with emphasizes on the traditional Iron-Triangle
framework. Their study conducted a comprehensive literature review and employed Kendall's
W test to rank KPIs for evaluating current performance measurement practices, despite the
criticism of the Iron Triangle, their research indicates that it remains a widely used
framework in the industry. However, their conclusions are somewhat constrained by the
vague definitions of performance concepts and the limited scope of the literature reviewed. A
broader examination of performance measurement methods and an expanded literature
review could enhance the knowledge and implementation of performance measures in the
construction sector.
These findings highlight a need for further research, such as this present study, which aims to
assess construction project performance by evaluating the interrelated factors of time, cost,
and quality, which together serve as indicators of project efficiency. By investigating these
elements, this study seeks to offer substantial knowledge for improving project outcomes and
tackling the persistent difficulties encountered in the industry.
2.3 Total Quality Management (TQM)
The theory of TQM was shaped by the seminal work of key figures often referred to as the
Gurus: Deming, Juran, Feigenbaum, and Crosby. Nevertheless, despite its extensive
implementation, there remains a divergence regarding the exact definition of TQM (Pavlović,
2024). Alawag et al. (2020) described TQM as a holistic administrative strategy that
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emphasize the on-going enhancement of the goods, services, and processes of an organization
with the principal aim of understanding and surpassing the needs and expectations of
customers, thereby enhancing client fulfilment and the overall organizational performance.
The American Society for Quality (ASQ, 2023) echoes this perspective, emphasizing that
TQM requires the involvement of every staff within an organization in optimizing operations,
outputs and offerings, together with enhancing the general workplace.
There is much discussion about the origin of TQM, however Jurevicius (2024) pointed out
that it has its roots in the 1950s and 1960s; after the Second World War, the Japanese Union
of Scientists and Engineers (JUSE) established a panel of academics, engineers, and
government representatives to boost production efficiency and improve living conditions in
Japan. TQM gained significant attention in the United States around 1980, as American
companies began to adopt the philosophy to improve their competitiveness (Jurevicius,
2024). The rise of TQM in the global corporate environment is largely attributed to increasing
competition and complexities, which highlight the critical importance of quality management
(Abd-Elwahed & El-Baz, 2018; Aletaiby, Rathnasinghe & Kulatunga, 2021).
ASQ (2024) provides a more detailed definition of TQM as a framework that prioritises the
creation of customer-centric enterprises, seeking to foster continuous staff engagement in
improvement efforts by strategically integrating data-driven processes and effective
communication within the organization's culture and operations. The TQM philosophy is
built on eight core principles: prioritizing customer satisfaction, involving all employees,
focusing on efficient processes, integrating systems, adopting strategic and systemic thinking,
promoting continuous improvement, making decisions based on data, and ensuring effective
communication (ASQ, 2024; Lip, 2024; Barone, 2023).
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Despite the theoretical benefits of TQM, research findings on its practical application have
shown mixed results. An example of such a study is Jong, Sim, and Lew's (2019)
examination of Malaysian construction firms, which looked at how TQM procedures
correlate with project outcomes. The study, which used a cross-sectional and convenience
sampling method, specifically examined ISO 9001 certified firms within the Construction
Industry Development Board’s (CIDB) Grade 7 category, revealed that improving workforce
engagement and operational processes had a notable beneficial effect on the efficiency of
construction endeavours. However, the practice of measurement, analysis and management of
knowledge was found to have a negative effect, suggesting ineffective implementation.
Additionally, the study indicated that customer focus, strategic planning, and leadership did
not show any direct bearing on performance, which challenges traditional TQM models.
Using convenience sampling in this study restricts the capacity to extrapolate the outcomes,
underscoring the need for further research using different methodologies. Policymakers are
advised to incorporate workforce and operational considerations into industry policies to
enhance quality performance.
In summary, while TQM remains a widely recognized and implemented management
approach, its application and effectiveness can vary significantly based on the scenario and
the distinct methodologies employed. The on-going debate and research into TQM highlight
the need for continuous evaluation and adaptation of TQM principles to attain the intended
results across various industries and localities.
2.4 Malcolm Baldrige National Quality Award (MBNQA) Principles
The United State Congress in 1987 instituted the MBNQA as a benchmark for organizational
excellence and a catalyst for performance improvement (Blazey & Grizzell, 2021; ASQ,
2017). Named after Malcolm Baldrige, a former U.S. Commerce Secretary, the award is
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overseen by American Society for Quality (ASQ) in partnership with the National Institute
for Standards and Technology (NIST) (ASQ, 2024; NIST, 2023). The MBNQA aims to
enhance the efficiency of American firms and promote the national economy by providing a
systematic approach to evaluating and improving organizational performance (Setiawan &
Purba, 2021; Lazaros et al., 2017).
Scott (2016) submits that MBNQA Parameters are formulated to assist businesses in
implementing a comprehensive managerial approach to enhance their performance oversight
systems, culminating in;
Enhanced value to customers and stakeholders, hence increasing the sustainability of
the business.
Enhanced overall efficiency and capacity of the enterprise.
Enhanced corporate and individual acquisition of knowledge and skills.
Figure 1: The MBNQA Performance Excellence Framework
Source: (Scott, 2016)
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The MBNQA paradigm consists of seven distinct excellence parameters: workforce focus
strategic planning, operation focus, customer focus, leadership, measurement, analysis and
knowledge management, and finally, results (Setiawan and Purba, 2021; Anastasiadou and
Taraza, 2019). Several notable research (Parast and Safari, 2023; Parast and Golmohammadi,
2019; Prybutok, Zhang, and Peak, 2011; Lazaros, Sofia, and George, 2017; Curkovic et al.,
2000) have confirmed that these criteria are a suitable model for assessing quality
management. For this research, six TQM principles of the MBNQA model: customer focus,
leadership, operation focus, workforce focus, together with strategic planning, and lastly,
measurement, analysis and management of knowledge will be examined.
The rationale for their selection is informed by the research conducted by Jong, Sim, and Lew
(2019) which stated that the model has been;
Adopted in both emerging and industrialized nations (Lee et al., 2012; Lee & Ooi,
2015).
Employed in construction industry endeavours (Jaeger, Adair, and Al‐Qudah, 2013;
Lam, Lam, and Wang, 2008).
Found to include both the intangible and tangible components of TQM (Talib et al.,
2013; Lee & Ooi, 2015; Lee, Ooi, & Choong, 2013).
Extensively embraced by scholars in evidence based studies (Talib et al., 2013; Lee &
Ooi, 2015; Lee et al., 2012).
2.5 Conceptual Framework and Hypotheses development
This study will be led by following assumptions that have been formulated based on the
research questions and examination of relevant literature.
H1: Project performance is substantially impacted by the quality of organizational
leadership (L).
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H2: Strategic planning (SP) has an impact on construction project performance.
H3: Customer focus (CF) impacts project performance.
H4: Focus on the workforce (WF) directly impacts construction project performance.
H5: Construction project performance is significantly impacted by operation focus
(OF).
H6: Measurement, analysis, and knowledge management (MAKM) impacts project
performance significantly.
The theoretical model of this study follows the principles of MBNQA shown in figure 2
below.
Figure 2: Theoretical model
Source: Researcher’s compilation
1. Leadership (L):
The crucial role of leadership in project management, which impacts project tradition,
inspires organisational change, and influencing overall project performance is vastly
26
recognized by numerous authors (Fokina et al., 2023; Bhatti et al., 2021; Ford, Ford,
& Polin, 2021; APM, 2018). Various leadership theories, including emotional
intelligence, contingency, competency, traits, and behaviour, emphasize the
importance of selecting an appropriate leadership approach to enhance project success
and performance (Rehan, Thorpe, & Heravi, 2024; Nauman et al., 2024; Adewuyi,
2023; Fareed et al., 2023; Bui et al., 2021).
The correlation between leadership and project fulfilment is multifaceted, with
differing perspectives across studies. Adewuyi (2023) and Fung and Ramasamy
(2015) argue that while leadership is critical, it may not directly determine project
success. However, it facilitates key factors like teamwork and resource management,
which contribute to overall performance. In contrast, Bui et al. (2021) and Fareed et
al. (2023) assert that transformational leadership directly enhances project success,
organizational innovation and performance, although this effect is significantly
influenced by the level of top management support thus, implying that leadership
effectiveness depends not only on the leadership style but also on the broader
organizational context.
Furthermore, Jiang (2014) adds that leadership can impact project success both
directly and indirectly, particularly by improving teamwork and addressing challenges
posed by specific project types. While Fareed et al. emphasize the transformative
potential of leadership, Jiang and others consider the interaction of various leadership
styles with different organizational factors. Collectively, these studies underscore the
critical role of leadership in project success while suggesting that its effectiveness is
contingent upon contextual and organizational factors. Therefore, this informs the
postulation of the first research hypothesis: H1 - Project performance is substantially
impacted by the quality of organizational leadership (L).
27
2. Strategic Planning (SP):
The literature on strategic and project management both agree that efficient planning
is essential for successful projects (Kerzner, 2019; George, Walker and Monster,
2019; Meredith, 2017). Zwikael and Globerson (2004) emphasize the critical role of
high-quality forethought in enhancing project execution, particularly in construction
and engineering, where it reduces cost and schedule overruns. However, Jayawarna
and Dissanayake (2019) and Zwikael et al. (2014) present mixed findings, suggesting
that the correlation between planning quality and project success is not
straightforward, highlighting the influence of other factors like flexibility and
adaptability. Today Founder, (2023), Edwards, (2023), Mintzberg (1994) and Bart
(1993) further challenged the value of formal planning, arguing that it can stifle
creativity and lead to failure.
These contrasting views suggest that while planning is important, its effectiveness
depends on context, emphasizing the need for a balanced approach that incorporates
both planned actions and responsiveness to unexpected developments. Nevertheless, it
is widely recognized that some level of planning is necessary to mitigate uncertainty
and increase project success likelihood (Serrador, 2012). While planning cannot
ensure success, its absence is likely to lead to failure (Herz and Krezdorn, 2022).
Therefore, suggesting an influence by strategic planning on project performance.
Thus, hypothesis two is proposed: H2 - Strategic planning (SP) has an impact on
construction project performance.
3. Customer Focus (CF):
Customer focus is increasingly vital for organizational success as Chaddock (2024)
highlighted that meeting high customer expectations with personalized experiences
and prompt responses can enhance business performance by driving sales and loyalty,
28
while neglecting these needs often leads to customer churn. A synthesis of multiple
studies underscores the widespread recognition of a customer-centred approach as a
key driver of business performance, positively impacting financial metrics such as
monetary resources, increase in sales, profitability, proportion of the market, and
stock valuation.
Tuominen et al. (2023) and Obafemi, Onyebuchi, and Omoyebagbe (2023) confirm
that understanding and responding to customer needs can significantly enhance these
outcomes, while Eklof, Podkorytova, and Malova (2020) longitudinal study further
supports this by demonstrating that customer satisfaction not only boosts current
profitability but also predicts future financial performance, particularly in
Scandinavian banks. Additionally, Rahman et al. (2021) and Idzikowski et al. (2019)
emphasize the relevance of customer relationship management (CRM) strategies in
improving project performance across different phases, highlighting the evolving
nature of customer relationships.
However, the effectiveness of customer-centric strategies varies by context. For
instance, Talib et al. (2013) found that The Indian service industry did not gain
substantially from customer-centric initiatives, suggesting that regional and industry-
specific factors can indeed influence outcomes of TQM implementation. Furthermore,
Jong, Sim and Lew, (2019) also who discovered that customer focus does not significantly
impact project performance of Malaysian construction firms, a result echoed by Zhao et al.
(2022) who found no positive benefits of customer-oriented activities in the Chinese
manufacturing sector. This discrepancy highlights the need to tailor customer-focused
strategies to specific market dynamics. Furthermore, while some studies broadly link
customer focus to financial performance, others, like Psomas, Vouzas, and
Kafetzopoulos (2014), emphasize its role within TQM in enhancing efficiency of
businesses especially, those providing services.
29
Therefore, it is imperative to examine the correlation between project efficiency and
customer-centred initiatives within the study area in light of these insights.
Consequently, a third hypothesis is proposed: H3 - Customer focus (CF) impacts
project performance.
4. Workforce Focus (WF):
The connection between workforce dynamics and organizational performance is well-
established in management studies, with a strong focus on maximizing employee
potential through practices like training, empowerment, and teamwork. The general
literature (Madgavkar et al., 2022; Kess-Momoh et al., 2024; Lasa et al., 2024; Radu,
2023; Quilliam, 2023; Walters & Rodriguez, 2019; Todd, 2024) highlights the critical
role of a motivated workforce in driving productivity and performance.
Focussing on the importance of dedication and the capacity to produce tangible
results, Zhenjing et al. (2022) examined how work settings affect productivity. Their
analysis of data from 314 academic staff revealed that a positive work environment
enhances performance directly and indirectly by fostering commitment and
achievement. Furthermore, Aman-Ullah et al. (2022) investigated the effect of human
capital—knowledge, skills, and capacity—on the performance of organizations within
Saudi Arabia's hospitality sector; their quantitative study of 356 hotel managers found
that all aspects of human capital positively influence performance, with innovative
leadership further amplifying this effect.
Both studies underscore the importance of workforce-related factors for
organizational success, though from different perspectives. Zhenjing et al. emphasize
psychological processes, while Aman-Ullah focus on leadership's role in leveraging
tangible employee attributes. These findings suggest that a multifaceted approach,
integrating internal motivators and external leadership support, is crucial for
30
translating employee capabilities into organizational success. Further research by
(Akerele, 2023; Krekel, Ward, & De Neve, 2019) reinforces the beneficial association
between workforce focus and organizational efficiency, resulting in the formation of a
fourth hypothesis: H4 - Focus on the workforce (WF) directly impacts construction
project performance.
5. Operation Focus (OP):
Operations strategy is a deliberate plan designed to align operational capabilities with
market demands, thereby contributing to overall organizational strategy
(Chipwatanga, 2019). Achieving organizational excellence, as noted by Geminarqi
and Purnomo (2023) and Handoyo et al. (2023), requires operational excellence
which involves executing business strategies more effectively and reliably than
competitors while managing risks, reducing costs, and increasing revenues. Such
efficiency enhances productivity, product quality, customer satisfaction, and
profitability.
Operation focus comprises two key sectors: work processes and operational
effectiveness. While work processes involve designing, managing, and improving an
organization’s product and workflow (Jaeger, Adair, & Al-Qudah, 2013; Yee, 2018;
Lee & Ooi, 2015). Operational effectiveness on the other hand, as outlined by NIST
(2023) and Lip (2024) aims to enhance customer value and ensure organizational
success and sustainability through activities such as cost control, innovation
management, safety protocols, and supply chain oversight.
Chipwatanga (2019) found that integrating operational excellence with innovation
improves performance at First National Bank – Zambia (FNBZ), consistent with
findings from Mehralian et al. (2017), Jong, Sim, and Lew (2019), Bouranta, Psomas,
and Pantouvakis (2017), Zehir et al. (2012), and Zeng, Phan, and Matsui (2015)
31
across various industries. However, conflicting studies by Shieh and Wu (2002), Talib
et al. (2013), and Sit et al. (2009) revealed that process management's impact on
performance may vary based on context or industry. These discrepancies suggest that
the effectiveness of process management is context-dependent, necessitating further
investigation. Therefore, a fifth hypothesis is proposed: H5 - Construction project
performance is significantly impacted by operation focus (OP).
6. Measurement, Analysis and Knowledge Management (MAKM):
Bailey (2020) emphasizes the critical role of how organizations select and utilize data
in process management to improve effectiveness and efficiency. This process involves
maintaining accurate and accessible knowledge assets, ensuring data reliability, and
supporting quality decision-making. Similarly, Young (2023) and Bouranta, Psomas
and Pantouvakis (2017) stressed that reliable data is essential for enhancing
organizational performance. Additionally, Szukits and Móricz (2023) further
underscore the importance of basing managerial decisions on precise and relevant
data analysis, while Schultz (2024) highlights the necessity of providing high-quality
and timely data to key users to boost performance.
Namdarian, Sajedinejad, and Bahanesteh (2020) found that effective data collection,
analysis, and knowledge management systems directly improve firm performance, a
conclusion supported by Henao-García, Lozada, and Arias-Pérez (2020), who studied
160 firms in developing countries. Zeng et al. (2015) also confirmed that quality
information and knowledge management positively impact performance in their study
of 283 manufacturing plants in ASEAN countries.
Cu et al. (2021), after reviewing 52 research articles from top Information Systems
journals (2010-2021), confirmed the enormous impact of knowledge management
practices (KMP) by organizations on corporate effectiveness. The literature reviewed
32
highlights the necessity for organizations, including those in Eti-Osa's construction
industry, to robustly engage in robust this practice to enhance organizational
efficiency. Therefore, hypothesis six is proposed: H6 - is Measurement, analysis, and
knowledge management (MAKM) impacts project performance significantly.
2.6 Total Quality Management (TQM) In Construction Industry
TQM is an administrative technique employed by organizations to address challenges by
fostering continuous improvement in performance levels. This approach emphasizes the
importance of quality across inputs, processes, and outputs, creating an organizational culture
focused on quality and customer satisfaction (Yahya & Alabdullah, 2022; Seetharaman, 2023;
Barrett, 2000). Quality in the built-environment sector is a pivotal element influencing
various aspects of project success, including timely completion, customer satisfaction, cost
reduction, worker safety, and the well-being of occupants; as such, prioritizing quality is
essential, as it directly impacts the stakeholders involved in construction projects
(Vijayabanu, Karthikeyan & Vijay Surya, 2022). To effectively manage and optimize
construction processes, a robust Quality Management System (QMS) is indispensable as it
not only monitors execution but also assesses the overall excellence and efficiency of projects
(Construction Placements, 2024).
The fulfilment of client’s demands is the cornerstone of this management philosophy whose
importance extends to all sectors, including construction however, despite the critical role of
TQM in enhancing project outcomes; there has been reluctance within the construction
industry to fully embrace TQM practices. Al Jaberi and Naimi (2023) argue that this
hesitancy stems from the industry's reliance on the ISO 9000 series and the perceived lack of
immediate benefits from TQM. The evolving characteristics of construction endeavours and
the inherent complexities of the tasks it entails, further contribute to this reluctance.
Nevertheless, Arditi and Gunaydin (1997) argue that TQM strategies can be effectively
33
applied in the built-environment sector by highlighting the Japanese construction sector as a
pioneer in adopting TQM practices, inspired by the success of TQM in their manufacturing
sector during the 1970s. Thus, underscoring the adaptability of TQM to various industries,
including those characterized by innovative and non-repetitive processes, such as
construction.
Empirical studies by multiple researchers have demonstrated the beneficial effect of TQM on
construction performance. Researchers like Gupta and Khitoliya (2020), Riaz et al. (2023),
Coronel et al. (2021), and Jong, Sim, and Lew (2019) have all linked the adoption of TQM to
improved performance in the built-environment sector. In the Nigerian context, studies by
Alintah-Abel, Iheama, and Emoh (2023), Egwunatum et al. (2021), Olaleye et al. (2019),
Ahaotu (2019), Jimoh et al. (2016), and Okuntade (2015) have similarly found that TQM
significantly influences construction project outcomes. Notwithstanding the extensive
literature, a significant void remains in understanding the impact of TQM on the performance
of construction projects in various regions of emerging economies, particularly in the Eti-Osa
local government area of Lagos State.
This research will fill this void by evaluating the impact of TQM on the efficiency of
construction endeavours in regards to the Iron-Triangle in Eti-Osa. The study will employ six
MBNQA principles: operation focus, leadership, customer focus, strategic planning,
workforce focus, and measurement, analysis, and knowledge management; these practices
were established in relevant research such as those by Lee and Ooi (2015), Jong, Sim and
Lew, (2019) and Alanazi (2020) as vital components of effective TQM adaptation in the built-
environment sector thus, using this paradigm this research will provide insights into how
TQM practices impacts construction project performance in the Nigerian context, particularly
within Eti-Osa local government area.
34
2.7 Research Gap
Eti-Osa local government area has garnered minimal attention in the extensive literature
regarding TQM and the efficiency of construction endeavours. While TQM principles are
widely recognized in construction globally and locally, there exists a noticeable deficit in
empirical studies specifically assessing how these practices influence construction projects in
Eti-Osa. Most prior research (Olaleye et al., 2019; Jimoh et al., 2019; Okuntade, 2015;
Egwunatum et al., 2021; Arditi and Gunaydin, 1997; Agha, 2007) and those by (Yusuf,
Gunasekaran, and Dan, 2007; Pheng and Teo, 2004; Rahman and Bullock, 2005) has
primarily focused on broader national or global contexts, overlooking the unique
characteristics and challenges of specific localities like Eti-Osa local government area.
Despite the global acknowledgment of TQM's relevance in construction, few studies have
assessed its impact on key performance indicators (KPI) such as quality, cost, and time in Eti-
Osa to be specific. This research gap is particularly significant given the area's rapid urban
expansion and substantial economic implications within Lagos State and Nigeria. The
application of the six MBNQA principles mentioned earlier can provide a comprehensive
framework for evaluating TQM effectiveness in this context of Eti-Osa local government
area.
Addressing this gap is essential to understanding how peculiar conditions in Eti-Osa
influence the integration and success of TQM in the built-environment, consequently this
study will fill this void by examining the effect of TQM practices on construction endeavour
efficiency within Eti-Osa, focusing on project time, cost, and quality using the MBNQA
model as a guiding framework.
35
CHAPTER THREE
RESEARCH METHODOLOGY
3.1 Overview
The significance of systematically conducting research in sequential stages is emphasised by
Saunders, Lewis, and Thornhill (2023), thus following Saunder’s Research Onion, chapter
three delineates the technique and design that will be used in this study (Appendix 1). The
discussion will encompass the techniques employed in the study, which will include the
specific parameters of the method, the scales of measurement used for the variables, as well
as the methods implemented for data gathering and analysis. This methodology has been
specifically designed to guarantee both the credibility and accuracy of the outcomes of this
research.
3.2 Research Philosophy and Approach
This research adopts a deductive reasoning technique, as recommended by Bryman, Bell,
and Harley (2022), to develop and test hypotheses grounded in existing theories and
literature. Saunders, Lewis, and Thornhill (2019) argue that this approach aligns with the
positivist worldview, which enables the establishment of cause-effect relationships through
statistical data analysis, ensuring objectivity by reducing emotional bias.
Positivism adopted in this research, is a philosophical stance rooted in realism and supports
theories that reflect observable social realities (Collis and Hussey, 2021). Although
interpretive research offers valuable context, it often faces scrutiny regarding its
trustworthiness, validity, and generalizability as opined by Perry (1998). Contrastingly, Smith
(1998) contends that positivism treats phenomena as indisputable facts, allowing connections
between them to be established as scientific laws, similar to natural sciences.
36
The deductive approach is particularly suitable for this present study as Collis and Hussey
(2021) noted that deductive reasoning facilitates precise measurement and statistical testing
of variables, making it ideal for evaluating TQM practices. However, while deductive
reasoning offers robust hypothesis testing, it also has limitations, including inflexibility, over-
reliance on theories, and potential biases (Fife and Gossner, 2024). To mitigate these issues,
this study incorporated a thorough literature review and advanced statistical methods to
enhance data reliability.
3.3 Research Design and Strategy
This research adopts a descriptive methodology in the assessment of TQM implementation
impacts on construction project efficiency. According to Saunders, Lewis, and Thornhill
(2019), descriptive study involves using surveys in the collection of quantitative data to be
analysed through statistical techniques to describe characteristics or trends. This approach is
particularly valuable for understanding the key issues and serves as an anchor for further
studies by identifying patterns and relationships within the data (Saunders, Lewis, and
Thornhill, 2023). Hair, Page, and Brunsveld (2020) emphasize that a robust theoretical
foundation in research enhances the precision of measurement constructs, validates relational
associations, implies causality, aids in hypothesis formulation, and clarifies variables.
Furthermore, this study will adopt a quantitative mono-method, where a single data collection
instrument, specifically a quantitative survey, will be adopted in answering the questions
associated with this study (Saunders, Lewis, and Thornhill, 2019). The use of quantitative
survey is also supported by Quinlan (2011) who noted that it allows the engagement of study
participants to assess the objective world they encounter collectively. This method is
appropriate for capturing extensive data of a statistically comparable sample, making it ideal
37
for examining the impact of TQM on construction endeavour performance within Eti-Osa
local government area.
3.4 The Study Population
In descriptive studies, defining the study population is crucial, taken criteria such as
geographic area, age, sex, occupation, religion, and ethnicity into consideration (Stratton,
2023; Banerjee & Chaudhury, 2010) thus enhancing sampling decision, data capturing and
analysis which guarantees rigour and the credibility of outcomes (Methodologists, 2023).
Therefore, the study population will consist of construction professionals (Quantity
Surveyors, Builders, Architects, and Structural Engineers) with minimum managerial
experience of 5 years in the public sector of Eti-Osa construction industry. Additionally, the
study will target professionals who have participated in a construction project in Eti-Osa local
government area, located on Lagos Island, spanning 181 square kilometres with a population
density of 1,567.9 individuals per square kilometre (Akin et al., 2022).
3.5 Sample and Sampling Technique
The study will gather data through an anonymous online survey with a structured
questionnaire targeting construction professionals in the public sector who are currently or
have previously worked on construction projects within the Eti-Osa local government area.
The research will use snowball sampling, starting with initial respondents identified through
LinkedIn networking App. Snowball sampling is effective for accessing hard-to-reach groups,
as noted by Bell, Bryman, and Harley (2022) and Easterby-Smith et al. (2008), allowing the
possibility of locating construction experts in the Eti-Osa region who might not be accessible
through traditional sampling methods (Zikmund et al., 2013).
38
The study aims to recruit at least 120 participants, as recommended by Hair et al. (2016) that
15 observations per variable are ideal for robust multiple regression analysis to ensure
generalizability. Initial participants who meet the criteria will be identified and invited
through LinkedIn and consequently, requested to assist in identifying and enlisting other
potential candidates online. The participants will have the opportunity to access a link to
peruse a detailed explanation of the survey, and subsequently, they will encounter inquiries
related to the criteria. Only participants who answered affirmatively to the selection criteria
questions will be eligible to proceed with the completion of the main questionnaire, thus
ensuring the precision and consistency of the outcomes.
To mitigate the limitations of the snowball sampling technique, such as sample bias and non-
representativeness, the study will implement strict eligibility criteria and ensure respondent
anonymity to reduce social desirability bias. The research will prioritize high-quality data
from a diverse sample, following the methodological rigor proposed by Saunders, Lewis, and
Thornhill (2019) ensuring accurate and reliable findings within the study's timeframe.
3.5.1 Research Instrument
The research questions are explored using primary data collected through structured
questionnaires, as recommended by Kuphanga (2024); structured questionnaires are
particularly effective for collecting quantitative data through various survey methods, such as
online surveys. To develop the survey, an extensive review of prior research on the influence
of TQM techniques, specifically the MBNQA principles, on performance was conducted.
The survey is made up of three segments with the first part addressing the respondent’s
demography, while the following section systematically collects data on six MBNQA
practices using a 5-point Likert scale, spanning "strongly agree" (5) to "strongly disagree"
(1). The last segment focuses on assessing the performance of construction organizations
39
using TQM methods, also measured on a Likert scale with 5-points. The measurement scales
utilized in the questionnaire are derived from previously validated research shown in table 1
below, this ensures the precision and dependability of the collected data (Saunders, Lewis,
and Thornhill, 2023).
40
Table 1: Summary of Questionnaire Items
Section
Constructs
Dimensions
Sources
No. of items
Scale
1
Leadership (L)
Top management dedication
to quality practices
Jong, Sim and Lew
(2019), Lee et al. (2012),
Fotopoulos and Psomas
(2010), Lau, Zhao and
Xiao (2004)
4
1 = Strongly disagree
5 = Strongly agree
2
Strategic Planning (SP)
The inclination to formulate
and execute strategic
initiatives within the
organisation.
Nekoueizadeh and
Esmaeili (2013), Jong,
Sim and Lew (2019), Lee
et al., (2012), Fotopoulos
and Psomas (2010), Lau,
Zhao and Xiao (2004)
4
1 = Strongly disagree
5 = Strongly agree
3
Customer Focus (CF)
The capacity to evaluate and
fulfil client expectations
Fotopoulos and Psomas
(2010) Jong, Sim and
Lew (2019), Lee et al.,
(2012), Lau, Zhao and
Xiao (2004),
Nekoueizadeh and
Esmaeili (2013)
4
1 = Strongly disagree
5 = Strongly agree
4
Workforce Focus (WF)
the evaluation of staff
competence and requirements
for development
Babatunde and
Akinfolarin (2018),
Jong, Sim and Lew
(2019), Lee et al., (2012),
Fotopoulos and Psomas
(2010), Lau, Zhao and
Xiao (2004)
4
1 = Strongly disagree
5 = Strongly agree
5
Operation Focus (OF)
Efforts aimed at enhancing
organisational success
Nekoueizadeh and
Esmaeili (2013), Jong,
1 = Strongly disagree
5 = Strongly agree
41
through the improvement of
products, services and work
procedures.
Sim and Lew (2019), Lee
et al., (2012), Fotopoulos
and Psomas (2010), Lau,
Zhao and Xiao (2004)
4
6
Measurement, analysis, and
knowledge management
(MAKM)
The endeavours to collect,
quantify, and evaluate job
performance and
enhancements.
Jong, Sim and Lew
(2019), Lee et al., (2012),
Fotopoulos and Psomas
(2010), Lau, Zhao and
Xiao (2004)
4
1 = Strongly disagree
5 = Strongly agree
7
Project Performance (PP)
The objectives of a
construction endeavours.
Jong, Sim and Lew
(2019), Singh, Kumar
and Singh (2018)
4
1 = Strongly disagree
5 = Strongly agree
Total number of measurement items 28
Researcher’s Compilations
42
3.5.2 Validity Test
Validity in quantitative research pertains to how accurately a concept is measured (Heale &
Twycross, 2015). It involves ensuring that research instruments, like questionnaires, align
with study objectives for precise data collection (Essor et al., 2023). Quinlan et al. (2019)
inferred that validity can be assessed through content validity, which checks if the
questionnaire covers relevant areas; criterion validity, which evaluates correlations with
established standards; and construct validity, which assesses if the questions measure what
they are intended to (Bell, Bryman, & Harley, 2022). For this study, questions were derived
from previous research by Jong, Sim, and Lew (2019), Singh, Kumar and Singh (2018),
Babatunde and Akinfolarin (2018), Nekoueizadeh and Esmaeili (2013) and Lee et al. (2012),
thus ensuring the authenticity of the survey.
3.5.3 Reliability Test
Reliability is described by Bryman, Bell, and Harley (2022) as the consistency of a
measurement tool hence, this study utilized a questionnaire that has been thoroughly tested in
previous research for assessing TQM practices and performance. However, Saunders, Lewis,
and Thornhill (2019) cautioned that while an instrument might be valid, it may not always be
reliable, thus a pilot study as suggested by Quinlan et al. (2019) was carried out to verify the
survey’s reliability, consequently ensuring the validity and overall rigour.
A pilot study, as outlined by Quinlan (2011), involves an initial trial of the data collection tool
to identify any unclear survey items (Aslam et al., 2020). In this case, five participants
completed a test survey via LinkedIn to ascertain if any modifications were required, and to
guarantee accuracy and data reliability. Test-retest reliability for MBNQA practices was
found to be 0.73 and 0.82 for project performance, indicating that the questionnaire is a
reliable and valid research instrument. The pilot study confirmed that respondents could
43
easily interpret the closed-ended questions, allowing for reliable data collection (Saunders,
Lewis, & Thornhill, 2019; Quinlan, 2011).
3.6 Time Horizon
This research will employ a cross-sectional research technique as outlined by Haier et al.
(2007), to collect and analyse data within a four-month timeframe. This approach is fit for the
evaluation of TQM’s impact on project performance, allowing the statistical processing of the
interactions of variables at a single point in time. Essentially, this method provides a snapshot
of current conditions, facilitating effective interpretation of relationships and trends under
time and resource constraints.
3.7 Method of Data Analysis
The data for this present study will be obtained through a structured questionnaire since it is
economical and enables uniform questioning among a big sample (Saunders, Lewis, &
Thornhill, 2019). Statistical techniques, such as multiple regression and descriptive statistics,
will be used to elucidate interactions between variables and manage confounding factors,
ensuring the data is reliable and valid (Denscombe, 2010; Tansu & Naeem, 2022). The data
analysis and recording of result will be achieved using the Statistical Package for Social
Sciences (SPSS)
Furthermore, with respect to time limitation and the academic nature of the study, a cross-
sectional design will be utilized, which is suitable for evaluating the impact of adopting six
MBNQA techniques on construction project efficiency (Hair, Page, & Brunsveld, 2020).
44
3.8 Ethical Considerations
This research will comply with the ethical principles set forth by the University of Worcester,
emphasizing confidentiality to protect participants' interests and enhance research credibility
(Cohen, Manion, & Morrison, 2018; Kang & Hwang, 2023). Respondents will be
comprehensively informed about the intent of the study and will have the option to consent
via a checkbox, as recommended by Bell, Bryman, & Harley (2022), and comprehensive
information will be provided to ensure informed participation. Furthermore, the study will
follow the research proposal guidelines (Saunders, Lewis, & Thornhill, 2019) to maintain
data integrity and prevent breaches, unauthorized use of data, thus ensuring data collected is
only used in fulfilment of the study aim.
Additionally, all data collected for this research shall be deleted in line with the Data
Protection Act 2018 (GDPR) upon study completion and as the research involves data
collection in Nigeria, it will comply with international and Nigerian data protection
regulations, including the Nigeria Data Protection Act of 2023 and the Nigeria Data
Protection Regulation 2019, which was established by the National Information Technology
Development Agency (NITDA).
45
CHAPTER FOUR
RESULT PRESENTATION AND DISCUSSION
4.1 Data Preparation
Data collected through the Survey Monkey platform were downloaded in Excel format and
imported into SPSS for analysis. A frequency distribution check ensured completeness,
consistency, and accuracy, revealing 120 valid entries out of 126 met the selection criteria for
this study set in chapter 3. The data were standardized for ease of analysis, including scoring
sub-constructs of the MBNQA questions. The sample size exceeded the minimum
requirement, adhering to Hair et al. (2016) recommendation of 15 observations per variable
for generalizability in multiple regression analysis thus, ensuring the reliability of this study.
The instrument used to collect data was vetted approved for the study, maintaining alignment
with the research objectives. Additionally, the statistical methods applied in analysing the
study data were carefully selected to address the research questions, making them the most
appropriate for achieving the study’s aims. Sections 3.5.2 and 3.5.3 addressed the reliability
and validity of the survey instrument, respectively.
4.2 Descriptive Presentation
This section presents an elaborate account of the study's outcomes, including an examination
of the demographic features of the participants and analysing important data to emphasise
trends, patterns, and relationships that are pertinent to the research goals.
46
4.2.1 Prequalifying Criteria of Respondents (n=126)
Table 2: Prequalifying Statistic of Respondents (n=126)
Variables
Frequency
Percentage
Professional role in the construction industry
Builder
40
31.7
Structural engineer
30
23.8
Quantity surveyor
Architect
28
28
22.2
22.2
Years of experience at management level in the
construction industry
≥5 years
126
100.0
<years
0
0.0
Involvement in construction project within Eti-Osa local
government area
Yes
120
95.2
No
6
4.8
Researcher's Computation
In Table 2 above, the study's prequalifying data, involving 126 respondents, reveals a diverse
professional representation in the construction industry. The participants included builders
(31.7%), structural engineers (23.8%), quantity surveyors (22.2%), and architects (22.2%),
with over 5 years of management experience. Importantly, the table shows that only 120
respondents (95.2%) have been involved in construction projects within the Eti-Osa local
government area, thus deemed eligible for the study. This is to ensuring that the analysis is
based on insights from those directly engaged in Eti-Osa construction industry hence,
enriching the relevance and applicability of the study’s findings.
4.2.2 Demographic Profile of Respondents
Table 3: Gender Distribution of Respondents (n=126)
Gender
Frequency
Percentage
Male
79
62.7
Female
45
35.7
Prefer not to say
2
1.6
Total
126
100.0
Researcher's Computation
47
The distribution by gender shown in Table 3 indicates that a larger percentage of respondents
at 79(62.7%) are male which might be attributed to a male dominated industry compared to
the 45(35.7%) that are female. However, 2(1.6%) of the participants said they would prefer
not to disclose their gender.
Figure 3: Managerial level in the construction industry
Researcher's Computation
Figure 3 illustrates the distribution of respondents across managerial levels in the
construction industry. The largest group, 55 respondents (43.7%), belongs to middle
management. Bottom management accounts for 38 respondents (30.2%), while 33
respondents (26.2%) occupy top management roles. Notably, 73.9% of the respondents are
positioned in middle or bottom management, reflecting a substantial representation of these
tiers of management in the study’s sample.
48
Table 4: Distribution of Respondent’s Years at Managerial Level
Years
Frequency
Percentage
5-10
45
35.7
11-15
51
40.5
16-20
21
16.7
>20
Total
9
126
7.1
100.0
Researcher's Computation
Table 4 shows the distribution of participants with respect their years of management
experience in the construction industry. A significant proportion of the respondents (40.5%)
have 11-15years experience, reflecting a significant representation of mid-level career
professionals. Notable, 35.7% of the participants have 5-10year experience, while 16.7%
have 16-20years. Only a small portion, 7.1%, has more than 20years of management
experience, representing the least experienced group.
4.3 Constructs and Associated Factors
Table 5 shows the ordinal scale (5-point Likert) response frequencies of respondents
regarding the practices of MBNQA as suggested by Agresti (2018) that for ordinal data, it is
essential to use tables that show the frequencies or proportions of observations in each
category, as using histograms can be misleading by suggesting the data is continuous or
interval-based. However; the histogram for each construct is shown in the appendix 5. The
majority agreed or strongly agreed with these principles, particularly in areas like leadership,
strategic planning, customer focus, and workforce focus, with no strong disagreement
reported. Notably, 71.7% to 78.3% strongly supported top management’s commitment to
quality, while 65.8% to 70.8% endorsed alignment between organizational goals and quality
objectives. Additionally, customer and workforce-focused practices were strongly favoured,
49
reflecting an industry-wide commitment to quality improvement, operational efficiency, and
successful project performance across various dimensions.
Table 5 Statistical description of MBNQA practices in the construction industry (n=120)
MBNQA principles
SD
n(%)
D
n(%)
N
n(%)
A
n(%)
SA
n(%)
Leadership*
Top management establishes and maintains
a clear visible vision, values, and mission
that emphasize customer-focused quality
0(0.0)
0(0.0)
1(0.8)
33(27.5)
86(71.7)
Top management demonstrates active
participation in quality management and
enhancement process.
0(0.0)
0(0.0)
1(0.8)
30(25.0)
89(74.2)
Top management promotes principles and
skills that are associated with quality
0(0.0)
0(0.0)
0(0.0)
26(21.7)
94(78.3)
Top management commits sufficient
resources towards quality enhancement
0(0.0)
1(0.8)
3(2.5)
22(18.3)
94(78.3)
Strategic Planning*
The mission statement of our organization is
effectively communicated throughout the
company and accepted by our personnel
0(0.0)
0(0.0)
0(0.0)
40(33.3)
80(66.7)
Our organization employs a meticulous
planning methodology to consistently
establish and assess both immediate and
long-term objectives
0(0.0)
0(0.0)
0(0.0)
35(29.2)
85(70.8)
Our company's long-term objectives and
short-term tactics are founded on principles
of quality
0(0.0)
1(0.8)
1(0.8)
39(32.5)
79(65.8)
Our organization incorporates on-going
quality enhancements into the planning
process
Customer focus*
Our organization has prioritized client
satisfaction for a prolonged period
Our organization offers channels for
gathering feedback from clients
Our organization views client complaints as
an opportunity for on-going improvement
Our organization administers an annual
client satisfaction evaluation
0(0.0)
0(0.0)
0(0.0)
0(0.0)
0(0.0)
0(0.0)
0(0.0)
0(0.0)
0(0.0)
0(0.0)
1(0.8)
0(0.0)
6(5.0)
0(0.0)
6(5.0)
36(30.0)
33(27.5)
35(29.2)
38(31.7)
34(28.3)
83(69.2)
87(72.5)
79(65.8)
82(68.3)
80(66.7)
Source: Researcher’s Computation, 2024
Note: SD-Strongly disagree D-Disagree N-Neutral A-Agree SA-Strongly agree
* - independent variables ** - dependent variable
50
Table 5 cont’d….: Statistical description of MBNQA practices in construction industry
(n=120)
MBNQA principles
SD
n(%)
D
n(%)
N
n(%)
A
n(%)
SA
n(%)
Workforce focus*
Our organization offers comprehensive
training and improvement programmes for
all staff members
0(0.0)
1(0.8)
6(5.0)
44(36.7)
69(57.5)
Our organization promotes collaboration
and fosters a culture of problem-solving
among its personnel
0(0.0)
0(0.0)
8(6.7)
41(34.2)
71(59.2)
Staff efficiency is consistently assessed and
evaluated
0(0.0)
1(0.8)
5(4.2)
44(36.7)
70(58.3)
Our organization ensures a conducive work
space that promotes the physical and mental
health, safety, and overall welfare of all the
employees
Operation focus*
Our organization creates a series of crucial
work procedures
Our organization sets key metrics or
indicators (KPIs) to assess performance
Our organization consistently supervises
and evaluates the performance of work
procedures
Our organization employs methodologies or
instruments to enhance process efficiency
and minimize variation
Measurement, analysis and knowledge
management*
Our organization employs a system for
measuring organizational performance.
Our organization conducts regular
evaluations and analyses of the data and
knowledge that has been obtained.
Our organization offers essential
performance metrics for analytical and
decision-making purposes.
Our organization uses the findings from
performance reviews to consistently
improve and innovate.
0(0.0)
0(0.0)
0(0.0)
0(0.0)
0(0.0)
0(0.0)
0(0.0)
0(0.0)
0(0.0)
1(0.8)
0(0.0)
0(0.0)
0(0.0)
0(0.0)
0(0.0)
1(0.8)
0.(0.0)
0.(0.0)
14(11.7)
0(0.0)
0(0.0)
3(2.5)
1(0.8)
1(0.8)
3(2.5)
3(2.5)
3(2.5)
33(27.5)
39(32.5)
29(24.2)
32(26.7)
41(34.2)
49(40.8)
40(33.3)
45(37.5)
45(37.5)
72(60.0)
81(67.5)
91(75.8)
85(70.8)
78(65)
70(58.2)
76(63.3)
72(60.0)
72(60.0)
Source: Researcher’s Computation, 2024
51
Table 5 cont’d….: Statistical description of MBNQA practices in construction industry
(n=120)
MBNQA principles
SD
n(%)
D
n(%)
N
n(%)
A
n(%)
SA
n(%)
Project performance**
Typically, our jobs are completed within the
allotted time
0(0.0)
1(0.8)
5(4.2)
48(40.0)
66(55.0)
We consistently excel in completing projects
within the allocated budget
0(0.0)
3(2.5)
7(5.8)
39(32.5)
71(59.2)
Typically, our projects are handed over in
the specified requirements
0(0.0)
0(0.0)
2(1.7)
28(23.3)
90(75.0)
The outcomes of our projects typically
receive positive feedback from stakeholders
0(0.0)
0(0.0)
4(3.3)
30(25.0)
86(71.7)
Source: Researcher’s Computation
Note: SD-Strongly disagree D-Disagree N-Neutral A-Agree SA-Strongly agree
* - independent variables ** - dependent variable
4.4 Descriptive Statistics
Table 6 shows the mean opinion responses for the MBNQA on project performance variables
which is the average of all the included items in each construct. The mean opinion score was
computed by summing the 5-point Likert scale responses of the respondents of the four items
in each of the construct and divided it by 4, and subsequently divided by the total number of
participants. Higher mean value implies stronger level of agreement among the study
participants (Sousa et al., 2019) among the participants. Leadership had the highest score of
4.74 ± 0.36. Workforce focus had the lowest mean score of 4.51 ±0.51. The table also reveals
a negative skew in responses, with most participants indicating "Agree" or "Strongly Agree"
on the Likert scale, while few chose "Disagree" or "Strongly Disagree," resulting in a
distribution favouring higher values (Turney, 2023).
52
Table 6: Descriptive Statistics
Constructs/variables
Mean score
Std. Deviation
Skewness
Project performance**
4.60
0.50
-1.424
Leadership*
4.74
0.36
-1.059
Strategic planning*
4.67
0.33
-1.015
Customer focus*
4.66
0.35
-1.289
Workforce focus*
4.51
0.51
-1.088
Operation focus*
4.69
0.32
-0.869
Management, analysis and
knowledge management*
4.58
0.36
-1.100
Researcher’s Computation
* - independent variables ** - dependent variable
4.5 Research Hypotheses Testing
Six MBNQA practices were examined, forming the basis of the study's proposed hypotheses.
The effect of each practice on project performance was evaluated individually through linear
regression analysis, while multiple regression analysis was used to determine their combined
effect. The original tables from the statistical software used to create this regression analysis
tables are provided in the appendix 6.
53
4.5.1 Research Hypothesis One
H1: Project performance is substantially impacted by the quality of organizational
leadership (L).
Table 7: Regression analysis of organizational leadership on project performance
Independent variable
Coefficients
t-Statistic
p-value
Β
Std. Error
Constant
1.020
0.508
2.007
0.047
Leadership
0.755
0.107
7.066
0.001
Model summary
Observation
120
R
0.545
R2
0.297
Adjusted R2
0.291
Durbin-Watson
1.110
F-Statistic
49.934
F-Statistic (p-value)
0.001
Dependent variable: Project performance
Source: Researcher’s Computations
Simple linear regression analysis was conducted to assess impact of leadership on project
performance in Eti-Osa LGA. The model adopted to assess this is of good fit to the data as
shown by F-statistic = 49.934, p = 0.001. The R2 was .297, indicating that leadership
explained approximately 30% of the variance in project performance.
The regression model showed that leadership quality of the organization had a substantial
(p=001) positive impact on project performance. Also, project performance increased by
0.755 therefore, H1: Project performance is substantially impacted by the quality of
organizational leadership (L) is accepted.
54
4.5.2 Research Hypothesis Two
H2: Strategic planning (SP) has an impact on construction project performance.
Table 8: Regression analysis of strategic planning on project performance
Independent variable
Coefficients
t-Statistic
p-value
Β
Std. Error
Constant
0.877
0.550
1.594
0.114
Strategic planning
0.796
0.117
6.780
0.001
Model summary
Observation
120
R
0.529
R2
0.280
Adjusted R2
0.274
Durbin-Watson
1.151
F-Statistic
45.968
F-Statistic (p-value)
0.001
Dependent variable: Project performance
Source: Researcher’s Computations
Linear regression analysis was conducted to assess strategic planning impact on construction
project performance. The model employed to evaluate this was deemed to be of good fit to
the data as shown by F-statistic value = 45.968, p=0.001. The R2 was .280, indicating that
28% of the variation in project performance was due to strategic planning.
The regression model indicate that strategic planning have a significant (p=0.001) positive
impact on project performance. Also, strategic planning increased project performance by
0.796 thus, H2: Strategic planning (SP) has an impact on construction project performance is
accepted.
55
4.5.3 Research Hypothesis Three
H3: Customer focus (CF) significantly impacts project performance.
Table 9: Regression analysis of customer focus on project performance
Independent variable
Coefficients
t-Statistic
p-value
Β
Std. Error
Constant
1.660
0.555
2.900
0.003
Customer focus
0.631
0.119
5.307
0.001
Model summary
Observation
120
R
0.439
R2
0.193
Adjusted R2
0.186
Durbin-Watson
1.228
F-Statistic
28.167
F-Statistic (p-value)
0.001
Dependent variable: Project performance
Source: Researcher’s Computations
Simple linear regression analysis was conducted to assess impact of customer focus on
project performance. The model employed to evaluate was found to be of good fit to the data
as shown by F-statistic value = 28.167, p=0.001. The R2 was .193, indicating that 19.3% of
the variability in project performance was as a result of customer focus.
The regression model indicate that customer focus have significant (p=0.001) positive impact
on project performance. Also, customer focus increased project performance by 0.631 hence,
H3: Customer focus (CF) significantly impacts project performance is accepted.
56
4.5.4 Research Hypothesis Four
H4: Focus on the workforce (WF) directly impacts construction project performance.
Table 10: Regression analysis of workforce focus on project performance
Independent variable
Coefficients
t-Statistic
p-value
β
Std. Error
Constant
2.224
0.345
6.452
0.001
Workforce focus
0.527
0.076
6.930
0.001
Model summary
Observation
120
R
0.538
R2
0.289
Adjusted R2
0.283
Durbin-Watson
1.069
F-Statistic
48.031
F-Statistic (p-value)
0.001
Dependent variable: Project performance
Source: Researcher’s Computations
Simple linear regression analysis was used to assess impact of workforce focus on project
construction performance. F-statistic value = 48.031 and p=0.001 showed the model
employed to evaluate this was of good fit to the data. The R2 was .289; indicate that 28.9% of
the variance in project performance was attributed to workforce focus.
The regression model indicate that workforce focus significantly/ (p=0.001) impact project
performance positively. Also, it increased project performance by 0.527 therefore, H4: Focus
on the workforce (WF) directly impacts construction project performance is accepted.
57
4.5.5 Research Hypothesis Five
H5: Construction project performance is significantly impacted by operation focus
(OF).
Table 11: Regression analysis of operation focus on project performance
Independent variable
Coefficients
t-Statistic
p-value
β
Std. Error
Constant
0.235
0.543
0.432
0.667
Operation focus
0.930
0.116
8.051
0.001
Model summary
Observation
120
R
0.595
R2
0.355
Adjusted R2
0.349
Durbin-Watson
1.599
F-Statistic
64.811
F-Statistic (p-value)
0.001
Dependent variable: Project performance
Source: Researcher’s Computations
Simple linear regression analysis was conducted to assess operation focus impact on
construction project performance. The model employed to evaluate was found to be of good
fit to the data as shown by F-statistic value = 64.811, p=0.001. The R2 was .355, indicating
that 35.5% of the variation in project performance was due to operation focus.
The regression model indicate that operation focus have significant (p=0.001) positive impact
on project performance, increasing project performance by 0.930. Therefore, H5:
Construction project performance is significantly impacted by operation focus (OF) is
accepted.
58
4.5.6 Research Hypothesis Six
H6: Measurement, analysis, and knowledge management (MAKM) impacts project
performance significantly.
Table 12: Regression analysis of measurement, analysis, and knowledge management on
project performance
Independent variable
Coefficients
t-Statistic
p-value
β
Std. Error
Constant
1.306
0.497
2.627
0.010
Measurement, analysis, and
knowledge management impact
project performance
0.719
0.108
6.640
0.001
Model summary
Observation
120
R
0.522
R2
0.272
Adjusted R2
0.266
Durbin-Watson
1.543
F-Statistic
44.093
F-Statistic (p-value)
0.001
Dependent variable: Project performance
Source: Researcher’s Computations
Simple linear regression analysis was conducted to assess impact of measurement, analysis,
and knowledge management on project performance. The model employed to evaluate this
was found to be of good fit to the data as shown by F-statistic value = 44.093, p=0.001. The
R2 was .272, indicating that 27.2% of the variability in project performance was as a result of
measurement, analysis, and knowledge management.
The regression model indicate that measurement, analysis, and knowledge management have
significant (p=0.001) positive impact on project performance. Also, it increased project
performance by 0.719 thus, H6: Measurement, analysis, and knowledge management
(MAKM) impacts project performance significantly.
59
4.6 Multiple Regression Analysis
Table 13: Multiple Regression Analysis of Independent Variables on Project
Performance
Independent variables
Coefficients
t-Statistic
p-value
VIF
Β
Std. Error
Constant
-1.772
0.591
2.998
0.003
Leadership
0.239
0.114
2.101
0.038
1.653
Strategic planning
0.229
0.123
1.863
0.065
1.630
Customer focus
0.111
0.112
0.993
0.323
1.481
Workforce focus
0.176
0.080
0.2.192
0.030
1.640
Operation focus
0.348
0.134
2.590
0.001
1.815
Management, analysis and
knowledge management
0.268
0.108
2.487
0.014
1.504
Model summary
Observations
120
R
0.734
R2
0.539
Adjusted R2
0.515
Durbin-Watson
1.619
F-Statistic
22.028
F-Statistic (p-value)
0.001
Dependent variable: Project performance
Source: Researcher’s Computations
Table 12 illustrates the outcome of the multiple linear regression analysis conducted to
evaluate the combined effects of the independent variables on project performance. Before
the analysis was done, basic assumptions underlying the model was assessed to affirm the
integrity of the analysis. The Durbin-Watson statistic is used to detect the presence of
autocorrelation in residuals was found to be 1.65, effectively ruling out autocorrelation
among residuals and attesting to the independence of errors (Studenmund, 2001). The
threshold range for this measure is typically between 1.5 and 2.5, with values near 2
indicating the absence of significant autocorrelation (Turner, 2020).
60
The Variance Inflation Factor (VIF) for each predictor was well below the threshold of 5,
dispelling concerns about multicollinearity as the recommended conventional VIF value for
absence of multicollinearity is less than 10 (Tabachnick, Fidell and Ullman, 2019). The
residuals (errors) are normally distributed as shown in the histogram and the P-P plot in the
appendix 7, Homoscedasticity as showed in the appendix is also met as the scatter plot of the
data do not have an obvious pattern (Cohen, 2013). These tests validated the key assumptions
underlying the multiple linear regression models, providing a solid base for subsequent
analysis.
The overall model was found to be of good fit to the data (F=22.028, p=0.001). More than
50% (R2 =.539) of the variability in the dependent variable (project performance) was jointly
explained by the independents variables (Leadership, strategic planning, customer focus,
workforce focus, operation focus and measurement/analysis/knowledge management).
61
CHAPTER FIVE
DISCUSSION OF FINDINGS
5.1 Summary of Findings
This study evaluated the impact of TQM on construction project performance in Eti-Osa,
Lagos. The results from the regression analysis showed a positive relationship between TQM
implementation and project performance, aligning with Gupta and Khitoliya (2020), who
observed reduced rework in Indian construction firms using TQM, and Coronel et al. (2021),
who reiterated the importance of customer focus and continuous improvement in Pampanga.
Six MBNQA practices—leadership, customer focus, strategic planning, and workforce
focus—were found to positively impact performance in Eti-Osa, leading to enhanced
competitiveness and profit margins for construction firms.
5.1.1 Leadership (L) and Project Performance
The study found that leadership significantly impacts construction project performance. This
finding consistent with earlier studies by Bui et al. (2021) and Fareed et al. (2023), which
confirmed that leadership directly enhances project success, innovation, and overall
organizational performance, especially with support from top management. Consequently, the
study achieved its first objective of assessing the impact of leadership on the performance of
projects in the construction sector, confirming the study’s first hypothesis (H1) that project
performance is substantially impacted by the quality of organizational leadership thus,
underscoring the importance of prioritizing leadership development within construction
companies. The study highlighted the significance of context-sensitive leadership, aligning
with theories that emphasize emotional intelligence, contingency, and competency (Rehan,
Thorpe, & Heravi, 2024; Nauman et al., 2024). It supports the view that leadership's
62
influence is multifaceted, directly and indirectly impacting project success by enhancing
teamwork and resource management (Adewuyi, 2023; Fung & Ramasamy, 2015). Moreover,
Jiang's (2014) findings on the interaction between leadership and organizational factors are
validated by the regression analysis outcome, further highlighting the pivotal role of strong,
supportive leadership in navigating complex construction projects and improving overall
performance.
5.1.2 Strategic Planning (SP) and Project Performance
The regression analysis of this study found that strategic planning significantly impacts
construction project performance, aligning with Kerzner (2019) and Meredith (2017), who
emphasized that efficient planning reduces project costs and timelines. This confirms the
study’s second objective and hypothesis (H2), which posits that strategic planning affects
project outcomes. The importance of thorough planning especially, in complex fields like
construction lies in its ability to manage uncertainties and mitigate risks. However, Jayawarna
and Dissanayake (2019) and Zwikael et al. (2014) noted that the relationship between
planning and success is not always linear, with flexibility and adaptability playing crucial
roles. While this study affirms the foundational role of planning, it also acknowledges that
adaptability is key to enhancing performance in dynamic settings. This challenges critiques
by Today Founder (2023), Edwards (2023), Mintzberg (1994), and Bart (1993), who argue
that formal planning can stifle creativity and hinder success in highly complex projects.
Despite these concerns, the study suggests that the structured approach of strategic planning
outweighs its potential drawbacks. These findings reinforce Serrador (2012), who notes that
while planning alone cannot guarantee success, it is crucial for mitigating uncertainty and
increasing the likelihood of achieving project goals. Additionally, Herz and Krezdorn (2022)
argue that the absence of strategic planning often leads to project failure, further underscoring
its positive impact on performance.
63
5.1.3 Customer Focus (CF) and Project Performance
The study found that customer focus impacts construction project performance, aligning with
Chaddock (2024) assertion that meeting customer’s high expectations through personalized
experiences and prompt responses enhances sales, loyalty, and overall business performance.
This outcome aligns with that of Tuominen et al. (2023) and Obafemi, Onyebuchi, and
Omoyebagbe (2023), who noted that understanding and responding to customer needs
positively impacts financial metrics like profitability, market share, and stock valuation.
Similarly, Eklof, Podkorytova, and Malova (2020) longitudinal study showed that customer
satisfaction boosts profitability and predicts future financial performance, an integral issue in
the construction industry where long-term relationships and repeat business are critical for
growth and continuity. Therefore, the hypothesis (H3) of this study; customer focus
significantly impacts project performance is confirmed and the third objective to ascertain if
construction project performance is impacted by customer focus is also accomplished.
Comparable findings from Rahman et al. (2021) and Idzikowski et al. (2019) further
highlight the importance of customer relationship management (CRM) strategies in
improving project performance. However, this result contrasts with Talib et al. (2013) and
Jong, Sim, and Lew (2019), who reported limited benefits of customer-centric strategies in
the Indian service industry and Malaysian construction firms, suggesting that the
effectiveness of these initiatives can vary based on regional and industry-specific dynamics.
Overall, the study reinforces the argument that a customer-centred approach is a critical
driver of project performance in the construction industry, validating the proposed hypothesis
(H3) and highlighting the need to tailor customer-focused strategies to specific market
dynamics.
64
5.1.4 Workforce Focus (WF) and Project Performance
This study also confirms that workforce focus impacts project performance, consistent with
existing studies emphasizing the critical role of employee dynamics in organizational success.
The result from the regression analysis supports the argument that optimizing workforce
potential through training, empowerment, and teamwork directly correlates with improved
performance, aligning with scholars like Madgavkar et al. (2022), Zhenjing et al. (2022) and
Kess-Momoh et al. (2024) that highlighted the impact of a motivated and well-supported
workforce on productivity and organizational outcomes. Similarly, this result aligns with the
findings of Aman-Ullah et al. (2022) in Saudi Arabia’s hospitality industry, echoing the
importance of human capital—knowledge, capacity, and skills—in driving organizational
performance, with innovative leadership amplifying this effect.
Collectively, these findings reinforce the notion that a multifaceted approach, integrating
internal motivators such as a positive work environment and external leadership support, is
essential for translating employee capabilities into successful project outcomes. Through this
analysis, it can then be said that the study has accomplished its fourth objective which is to
determine how workforce focus impacts construction project performance, emphasizing the
importance of strategic workforce management in achieving optimal results. This positive
correlation suggests that investments in workforce development are not only beneficial but
essential for organizational success, particularly in complex project environments.
5.1.5 Operation Focus (OF) and Project Performance
This study also established that a focus on operations generates beneficial effect on project
performance, which aligns with Chipwatanga (2019) assertion that aligning operational skills
with market demands greatly improves an organization's overall strategy
65
The link between operational focus and the efficiency of projects is supported by studies
conducted by Geminarqi and Purnomo (2023) and Handoyo et al. (2023), which emphasised
that achieving operational excellence is crucial for executing corporate strategies more
effectively than competitors. These studies emphasise the significance of risk management,
cost reduction, and revenue increase, which are fundamental aspects of operational focus.
Furthermore, this finding implies that work procedures and operational effectiveness are vital
areas of concentration within operations as Jaeger, Adair, and Al-Qudah (2013), as well as
Yee (2018) and Lee and Ooi (2015) averred that improved project performance can be
archived through the effective work processes which enhances product quality and workflow
management.
However, conflicting results from studies conducted by Shieh and Wu (2002), Talib et al.
(2013), and Sit et al. (2009) indicate that the efficacy of process management may vary
depending on the specific circumstances. Notwithstanding the differences in findings from
previous studies, this current study achieved its fifth objective of finding out how
construction project performance is impacted by operation focus is established thus,
confirming that focussing on operations is a crucial factor in determining project
effectiveness, and emphasising the importance for construction firms to prioritise operational
efficiency and process management as strategic necessities.
5.1.6 Measurement, Analysis and Knowledge Management (MAKM) and
Project Performance
Similarly, this study found that measurement, analysis, and knowledge management
significantly influence project performance by enhancing the efficiency of construction
projects. This finding supports Bailey (2020) focus on the importance of carefully choosing
and using data in process management to improve effectiveness and efficiency. Bailey
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emphasizes the importance of maintaining accurate and accessible knowledge assets,
ensuring data reliability, and supporting informed decision-making. These practices have
been established to have a positive correlation with project performance. The finding is also
validated by Young (2023) and Bouranta, Psomas, and Pantouvakis (2017) who emphasized
the importance of having trustworthy data to enhance organizational performance, this
perspective is reinforced by the result of the study, which demonstrate that effective data
management generates a positive impact on project outcomes.
Furthermore, comparable studies such as those by Szukits and Móricz (2023), Schultz (2024),
Namdarian, Sajedinejad, and Bahanesteh (2020) corroborates this finding in highlighting the
significance of accurate and timely data for managerial decisions hence, affirming the
hypothesis six (H6) that measurement, analysis, and knowledge management impacts project
performance significantly and achieving the study’s sixth objective which is to determine
how measurement, analysis, and knowledge management impact the performance of
construction.
5.2 Theoretical Contributions and Practical implications
This study offers both theoretical contributions and practical implications for the construction
industry, particularly in Eti-Osa, Lagos State, Nigeria. The regression analysis confirms that
the implementation of TQM significantly enhances construction project performance.
Specifically, the study examined six MBNQA practices—leadership, customer focus,
strategic planning, workforce focus, operation focus, and measurement, analysis, and
knowledge management—all of which were found to have a direct, positive impact on
performance. This implies that construction companies aiming to improve productivity
should implement these practices, entrenching them into their organizational culture for
sustained improvement in productivity.
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A key contribution of this research is its emphasis on the role of leadership in improving
project outcomes, aligning with previous research that links strong leadership skills and
commitment to enhanced team morale and project success (Bui et al., 2021; Fareed et al.,
2023). The findings highlight the need for leadership practices and training that focus on
vision-setting, creativity, effective communication, and team-building within a TQM
framework. Additionally, the study underscores the importance of measurement, analysis, and
knowledge management in boosting project and organizational performance. This supports
the conclusions of Marinho and Couto (2022), Szukits and Móricz (2023), and Schultz (2024)
that effective knowledge management systems drive innovation and improve decision-
making.
The study also aligns with other research (Radu, 2023; Madgavkar et al., 2022; Kess-Momoh
et al., 2024) that highlights the critical role of a motivated workforce and operational
excellence in enhancing productivity. By confirming the positive relationship between TQM
practices and construction project performance, the study addresses gaps in the literature
regarding TQM's impact in Eti-Osa. Moreover, individual linear regression analyses of
customer focus and strategic planning underscore their importance in achieving successful
project outcomes and improving organizational performance, as noted by Obafemi,
Onyebuchi, and Omoyebagbe (2023).
For construction managers, these findings suggest that optimizing internal processes is
critical to improving project performance, leading to higher customer satisfaction, increased
profitability, and a more sustainable construction industry. Therefore, Nigerian construction
organizations can apply these insights to enhance project outcomes and contribute to national
growth.
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5.3 Recommendations
These recommendations are offered based on the review of relevant literature and the
findings of this study:
1. Strategic Leadership Development: Construction companies in Eti-Osa should
prioritize leadership development as a strategic initiative to enhance their project
outcomes. Recent studies, including this research alongside those by Nandasinghe
(2020) and Eduzor (2024), underscore the critical role of leadership in boosting team
morale, driving innovation, and improving overall project performance. Given the
unique challenges faced by the Nigerian construction sector, particularly in Eti-Osa,
leadership programs should be tailored to incorporate local realities and international
best practices, focusing on emerging digital innovations in construction leadership,
such as data-driven decision-making, e-documentation processes, remote team
management, and sustainability-driven leadership models (Johari and Hendra, 2023).
To cultivate leadership potential, construction firms should implement structured
mentorship programs and workshops aimed at enhancing both technical and
interpersonal leadership competencies (Bashir, 2023), and also establish a reward
system that promotes innovation and sustainability in leadership that will further
support the development and retention of effective leaders (CIOB, 2008), crucial for
driving performance enhancement initiatives.
2. Innovative Knowledge Management: To improve project performance,
construction firms in Eti-Osa can adopt advanced knowledge management practices,
particularly by leveraging digital tools and innovative technologies. Castaneda and
Cuellar (2020) suggest that robust knowledge-sharing systems facilitate efficient
decision-making and foster innovation. Therefore, this research recommends
developing and implementing continuous knowledge exchange mechanisms, which
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are critical in the construction sector of Eti-Osa, where projects often involve
complexities, evolving trends, and regulatory requirements.
Construction businesses in Eti-Osa seeking to enhance project performance should
also incorporate the latest innovations in Artificial Intelligence (AI) tools to improve
their knowledge management systems. According to Yepes and López (2021), AI can
significantly enhance real-time data collection and analysis across project teams,
accelerating knowledge retrieval, improving decision-making, in addition to
facilitating the application of existing knowledge to new challenges. Furthermore, it
promotes knowledge sharing, ensures robust validation of knowledge gained from
previous projects before integration into future ones, and increases organizational
intellectual capital, as suggested by Anumba and Khallaf (2022).
Additionally, organizations involved in construction projects in Eti-Osa should
implement efficient client feedback loops supported by digital platforms. According
to Wind River (2024), digital platforms such as company websites, mobile
applications, social media channels, emails, surveys, online reviews, and customer
service interactions will enable data-driven decisions through continuous feedback
cycles, helping businesses refine their offerings through innovation, adapting to
changing customer needs, and ultimately improving their project and organization
performance.
3. Lean Construction Methods and Continuous Process Improvement: This study
recommends that construction organizations in Eti-Osa adopt enhanced lean
construction practices fully, to optimize operational efficiency as emphasized by
Pérez, Ávila, and Sánchez (2024). With the increasing global emphasis on
sustainability and cost-effectiveness across various industries, including construction,
it is crucial to minimize waste, reduce delays, and streamline operations. This requires
70
the incorporation of lean processes in construction endeavours, such as Just-In-Time
(JIT), modular construction, BIM, robots, and 3D printing (Davila Delgado et al.,
2019; Babalola, Ibem, and Ezema, 2019). To effectively implement these processes,
construction firms in Eti-Osa should focus on developing robust IT skills among
current employees through targeted training programs and hiring new individuals with
technical expertise. This includes seeking talent from digital-native companies, even
those outside the construction sector, and prioritizing candidates from industries that
have undergone a digital transformation (Blanco et al., 2018). By investing in these
advancements, construction firms in Eti-Osa can significantly improve project
timelines, reduce costs, reduce rework, and ensure high quality outputs that meets and
exceeds client expectations.
5.4 Conclusion
This study aimed to evaluate the impact of TQM on the performance of construction projects
in the Eti-Osa Local Government Area of Lagos state, utilising the MBNQA framework. The
data obtained from the anonymous online survey revealed that six MBNQA practices—
leadership, customer focus, strategic planning, workforce focus, operational focus, and
measurement, analysis, and knowledge management—positively impacted the performance
of construction projects in Eti-Osa. These practices jointly enhanced organizational
processes, ultimately resulting in higher project performance and improved client satisfaction.
The study highlights the critical role of a structured quality management approach in
enhancing project schedules, cost efficiency, and quality standards in the construction sector.
It adds to the growing body of research on TQM and its positive impact in construction
industry, providing valuable insights for industry leaders seeking to improve project
performance.
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5.5 Limitations of the Study and Future Research
This study effectively achieved its primary aim of determining the impact of TQM on
construction project performance in the Eti-Osa local government area. However, several
limitations must be acknowledged. The main limitation stemmed from challenges in
implementing probability sampling techniques, which, as noted by Saunders, Lewis, and
Thornhill (2019), would have allowed for greater generalizability. Simple random sampling
was impractical due to difficulties in accessing a comprehensive list of construction
professionals in Eti-Osa, preventing the generation of a truly random sample. To address this,
a snowball sampling technique was employed, which is effective in reaching hard-to-access
groups (Bell, Bryman, and Harley, 2022). However, snowball sampling can introduce bias
and limit representativeness by relying on initial participants to recruit others, often leading to
homogeneity, selection bias, and social desirability bias (Zikmund et al., 2013).
Additionally, the exclusive use of a structured questionnaire limited insights by restricting
responses to predetermined options, thus hindering the capture of broader qualitative
perspectives (Hair, Page, and Brunsveld, 2020). The reliance on the MBNQA framework also
restricted the study by not considering alternative TQM models. Moreover, the cross-
sectional design provided only a snapshot of current conditions, limiting the ability to assess
changes over time or establish causality (Saunders, Lewis, and Thornhill, 2023).
Future studies should aim for a more representative sample by including practitioners from
the public and private sectors, and also employ alternative sampling techniques to ensure
generalizability. Incorporating other quality standards, as well as qualitative methods like
interviews or focus groups, would provide more comprehensive insights into the impact of
TQM on construction project performance, thereby enhancing empirical evidence and
broadening the applicability of findings.
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CHAPTER SIX
POTENTIAL IMPACT OF THE STUDY WITHIN AN
ORGANIZATIONAL CONTEXT
6.2 Potential Impact within an Organizational Context
The adoption of Total Quality Management (TQM) in the construction sector is a highly
relevant subject, offering substantial benefits in enhancing both organisational efficiency and
industry quality standards. Ojomah (2023) argues that the construction industry is crucial to
Nigeria's economic growth by providing essential infrastructure such as roads, bridges,
airports, housing, and public facilities. In doing this, employment opportunities for skilled
and unskilled workers are created, significantly contributing to the nation's GDP and
improving the quality of life (CIOB, 2023).
Regrettably, the industry as averred by Iroha, Watanabe and Satoshi (2024) has been
characterised by subpar productivity as a result of inadequate project delivery performance,
project delays, exceeding budget limits, scope creep, abandonment, and in the extreme cases,
building collapse (Ekundayo, 2023; Ogunmakinde, 2019). Therefore, ensuring quality in the
construction sector is essential for strategic organisational competitiveness, employee
empowerment, customer satisfaction and loyalty, reduced rework, continuous improvement,
increased productivity, and better budget and schedule performance (Riaz et al., 2023);
various techniques like TQM, Six Sigma, ISO standards, cost of quality analysis, and Kaizen
are used to manage construction project performance and quality.
Findings from this research revealed that the Total Quality Management practices of the
MBNQA impacts project performance in Eti-Osa local government area hence, it is beneficial
for construction firms and the industry to expand their knowledge and adaptation of these
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principles in their operations to improve quality and performance standards, increase
profitability and maximise the economic potential of the industry. The study emphasizes the
pivotal role of leadership, particularly transformational leadership, in enhancing project
performance. Organizations are encouraged to prioritize leadership development programs
that focus on vision-setting, effective communication, and team-building. Bass and Riggio
(2006) argue that transformational leadership not only boosts team morale but also drives
project success. By investing in such training, companies can cultivate leadership styles that
lead to better project outcomes and contribute to overall organizational success.
Another critical factor identified in the study is the significant impact of measurement,
analysis, and knowledge management on project performance. To capitalize on this,
organizations can implement robust knowledge management systems and analytical tools to
enhance decision-making that will foster innovation as suggested by Davenport and Prusak
(1998). By adopting this principle, construction companies can improve their capacity to
monitor project progress, identify potential issues early, and respond more effectively thus,
enhancing project execution and performance outcomes, ultimately strengthening the
organization's capabilities.
Operational focus is also highlighted as a crucial determinant of project success. Slack,
Chambers and Johnston (2010) opine that a streamlined operation results in improved
performance outcomes hence, this study recommends that construction firms refine their
operational processes through lean management techniques, which aim to reduce waste,
delays, and increase efficiency. By regularly auditing processes and providing training on
best practices, organizations can maintain high standards, reduce costs, and deliver higher-
quality projects thereby, ensuring its long-term success. Also workforce focus as identified in
the study plays a significant role in achieving project performance therefore, construction
74
companies can invest in comprehensive employee development programs, include skill
enhancement, career growth plans, and performance evaluations which according to Boxall
and Purcell (2022) will lead to higher organizational productivity and better project outcomes
thus, making investing in workforce development a critical area of focus for companies
aiming to improve their project outcomes.
Additionally, the study found that strategic planning and customer focus significantly impacts
project performance. This finding points to the importance of aligning strategic initiatives and
project goals, while also suggesting that customer-focused strategies should be efficiently
integrated into project development and execution. Kotler and Keller (2016) suggest that
while customer focus is essential, its impact may be limited if not properly aligned with
project management practices therefore, construction firms can adopt this finding in
reassessing their strategic planning frameworks, ensuring greater alignment with project
objectives and effective customer engagement.
In broader context, policymakers and construction industry regulators can leverage this
study’s findings to develop policies and standards that promote best practices across the
industry using insights from this study as a benchmark for construction companies to improve
their leadership, operations, and knowledge management capacities. Additionally, policies
that emphasize continuous professional development can enhance leadership quality
throughout the industry leading to enhanced project performance standards which will in turn
make the industry more competitive and resilient to challenging global economic dynamics.
Porter’s (1985) strategic frameworks could guide the alignment of strategic planning with
project execution, ensuring that construction firms are better positioned to meet their strategic
objectives. The implementation of TQM such as the MBNQA principles can significantly
boost the construction industry’s long-term growth and competitiveness; focusing on
75
continuous improvement, data-driven decision-making, and workforce development,
construction organizations can consistently deliver successful projects that exceed client’s
expectations, attract investment, and foster innovation, ultimately enhancing the industry’s
global standing.
76
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