Advancing Middle East Construction Sustainability: A Framework for Addressing Logistics Challenges Through Solutions and Critical Success Factors

Abstract

The Middle Eastern construction industry significantly contributes to regional economic development but faces persistent sustainability challenges due to logistical inefficiencies. This study aims to address the gap in the existing literature, which often treats logistics challenges, solutions, and critical success factors (CSFs) in isolation without offering a unified framework to integrate these elements. By leveraging structural equation modelling (SEM), this research provides a comprehensive approach to understanding and addressing the interconnections between logistics inefficiencies, proposed solutions, and sustainability outcomes. Using SEM, this study identifies and analyses 23 logistics challenges, 18 solutions, and 8 CSFs, revealing their relationships and collective impact on sustainability in the construction sector. SEM’s robust analytical capabilities enable simultaneous testing of complex interdependencies, offering insights that traditional methodologies cannot achieve. The findings emphasise the critical role of lean methodologies, advanced technologies, and collaboration strategies in overcoming inefficiencies, reducing environmental impact, and optimising resource use. This research fills a crucial gap by developing a cohesive framework that integrates logistics challenges, solutions, and CSFs to advance sustainable practices. The outcomes provide actionable guidance for stakeholders to improve sustainability performance while enhancing competitiveness in Middle Eastern construction logistics

1. Introduction

The construction industry in the Middle East serves as a cornerstone of economic growth and social development, contributing approximately 30% to regional GDP and employing nearly 20% of the workforce [1,2]. Despite its pivotal role, this sector faces acute logistical inefficiencies that pose a significant threat to its sustainability and competitiveness [3]. The urgency of addressing these issues is underscored by the severe consequences of poor logistics management, which include resource wastage, escalating greenhouse gas emissions, prolonged project timelines, and escalating costs. Government reports and industry analyses consistently reveal systemic challenges, such as fragmented planning, insufficient material handling, and ineffective waste management [4,5]. These inefficiencies not only undermine project success but also exacerbate environmental degradation and resource depletion [6,7]. The Middle East’s unique context amplifies these challenges. The region’s harsh climatic conditions, rapid urbanisation, and dependence on imported construction materials create an environment where traditional logistics approaches are increasingly unsustainable. Large-scale infrastructure projects, driven by urban growth and ambitious development goals, place immense strain on logistical networks, exposing their vulnerabilities. The region’s reliance on conventional methods and non-renewable resources further compounds these challenges, creating a pressing need for sustainable logistics solutions tailored to the Middle Eastern construction sector. Addressing these inefficiencies is essential not only for improving project outcomes but for aligning the industry with global sustainability goals and enhancing its long-term resilience.

Sustainability in construction logistics presents a transformative opportunity to mitigate these challenges [8,9]. Through the optimisation of resource efficiency, minimisation of waste, and reduction of greenhouse gas emissions, sustainable logistics can yield significant environmental, economic, and social benefits. Advanced practices, such as lean construction methodologies, real-time visualisation tools, and third-party logistics services, offer the potential for driving this transition [10]. However, their adoption remains limited in the Middle East due to such factors as insufficient stakeholder coordination, inadequate information sharing, and a lack of integration with critical success factors [11,12]. While researchers have emphasised the importance of addressing logistics early in the project lifecycle [13,14], the existing body of literature is fragmented and lacks a cohesive framework that connects logistics challenges, innovative solutions, and critical success factors to sustainability outcomes. This research addresses this gap by developing a comprehensive framework that integrates logistics solutions and critical success factors, specifically designed to address the logistical inefficiencies of the Middle Eastern construction industry. In addressing this gap, this research not only highlights the critical role of logistics in achieving sustainability but demonstrates why sustainable logistics solutions and critical success factors are the optimal choice for addressing the systemic inefficiencies in the Middle Eastern construction sector. This study aims to answer two fundamental research questions:

What are the key logistics challenges impeding sustainability in the Middle Eastern construction industry?

How can logistics solutions and critical success factors be integrated into a cohesive framework to enhance sustainability outcomes in this region?

By addressing these questions, this study provides a robust roadmap for transitioning the Middle Eastern construction industry towards more efficient, resilient, and sustainable logistics practices, with implications for industry practitioners, policymakers, and researchers alike.

2. Literature Review

2.1. The Middle East Construction Industry

The Middle East’s construction industry faces a distinct set of logistical challenges compared to other regions, driven by unique environmental, economic, and regulatory conditions. Its reliance on imported materials—accounting for over 90% of construction inputs in the Gulf Cooperation Council (GCC) countries—creates a fragile supply chain susceptible to global disruptions, price volatility, and geopolitical uncertainties [15]. This dependence starkly contrasts with regions, such as Europe and North America, where robust local manufacturing and regional trade agreements ensure smoother material flows [16,17]. For instance, the European Union benefits from a highly integrated trade network, enabling seamless procurement and delivery of construction materials, while the U.S. construction sector relies on an extensive domestic supply chain, bolstered by localised production hubs [18]. By contrast, Middle Eastern projects, such as Qatar’s World Cup infrastructure, often experience delays due to logistical bottlenecks at ports and borders. Establishing regional manufacturing facilities and logistics hubs could mitigate these vulnerabilities, reducing lead times and building resilience in the supply chain [4].

Environmental and climatic factors further differentiate the Middle East from other global construction markets. The arid climate necessitates innovative logistical solutions to counter challenges like material degradation due to extreme heat and the high amount of water consumption for traditional construction methods. Unlike temperate regions, such as Northern Europe, where weather-related disruptions are minimal, or tropical regions like Southeast Asia, which have implemented advanced cooling and storage systems to mitigate environmental stressors, the Middle East has yet to widely adopt such measures. Additionally, sustainability remains an underdeveloped aspect of logistics in the region. Construction transportation activities contribute up to 30% of the Middle East’s carbon emissions, highlighting the need for cleaner, energy-efficient practices [19]. By contrast, countries like the Netherlands have pioneered sustainable urban construction logistics through centralised hubs and modal shifts to low-emission transport options. Adopting similar practices—such as real-time visibility tools, lean methodologies like just-in-time (JIT), and renewable energy-powered transport fleets—could address both logistical inefficiencies and sustainability concerns in the Middle East, aligning the region with global best practices and enhancing its long-term competitiveness

2.2. Construction Logistics Challenges

Logistics challenges in the construction industry are multifaceted, stemming from complexities in planning, resource allocation, and operational execution. Effective planning is crucial to meet project objectives, ensuring that materials, equipment, and labour are available when needed [20]. However, inadequate coordination between logistics and construction operations often leads to inefficiencies. For example, consider a large-scale urban development project where the construction schedule relies on the timely delivery of prefabricated concrete panels. Delays in transportation due to poor route planning can leave workers idle and equipment underutilised, increasing costs and pushing back deadlines [21]. Additionally, the absence of qualified logistics personnel exacerbates these issues, as ambiguous responsibilities and suboptimal management practices hinder project progression [22]. Poorly designed layouts and insufficient work plans, often due to employing inexperienced staff, further compound these problems by introducing redundancies and inefficiencies [23]. Transportation is a critical area in construction logistics, involving the movement of materials from suppliers or storage facilities to construction sites. Transportation typically accounts for 10 to 20 per cent of project costs and is divided into offsite and onsite logistics [24]. For instance, during the construction of a high-rise building, offsite transportation ensures steel beams are moved from manufacturing facilities to a storage yard, while onsite logistics coordinates their precise delivery to the assembly point. Inefficiencies, such as suboptimal vehicle utilisation, poor route planning, and inadequate scheduling, can result in delays, material damage, and resource shortages, disrupting timelines and reducing work quality [25,26]. This underscores the importance of meticulous planning for transport routes, schedules, and equipment use [27].

Inventory and warehousing management present additional challenges. This function involves storing and maintaining materials to ensure quality and availability when required [28]. For example, in a large warehouse storing steel and concrete for a bridge project, inaccurate demand forecasts and poor storage practices may lead to shortages or material deterioration. These disruptions can stall construction progress or escalate costs due to last-minute purchases at higher prices [29]. Inefficient handling of equipment and improper distribution methods further exacerbate delays, directly affecting productivity [30]. Effective material management is critical, as materials account for roughly 60 per cent of total project expenses [31]. Inefficient procurement practices—such as selecting unreliable suppliers for cost savings—can result in delayed or substandard materials, as seen in a case where a contractor sourced discounted concrete that failed strength tests, requiring costly replacements [32]. Furthermore, a lack of digital inventory tracking systems and a reliance on inexperienced staff contributed to errors, redundancy, and poor decision-making, thereby reducing overall efficiency [33]. Communication and coordination are foundational to logistics efficiency, ensuring seamless interaction among stakeholders and alignment of project activities. Effective communication includes data exchange and dissemination of instructions through meetings or digital platforms [34]. For example, during the construction of a hospital, unclear communication about delivery schedules for medical-grade flooring led to scheduling conflicts, delays, and additional costs. This highlights the importance of robust communication protocols to synchronise efforts and ensure project success [28]. Lastly, reverse logistics (RL) remains underutilised despite its importance in managing defective or surplus materials. Effective RL systems ensure subpar materials are identified, returned, or replaced without disrupting activities [35]. For instance, in a stadium construction project, defective glass panels were discovered late in the installation phase. The absence of an RL system delayed replacements and extended project timelines, increasing costs significantly [1,36]. Such scenarios demonstrate the necessity of adopting RL practices, especially in projects involving high-value specialised materials [26].

2.3. Sustainability Within Construction Logistics

The United Nations Environment Programme (UNEP) defines a sustainable economy as one that improves human welfare and social fairness while significantly decreasing environmental hazards and ecological shortages. This type of economy is marked by low carbon output, efficient use of resources, and social inclusion [37]. The Organisation for Economic Co-operation and Development (OECD) Green Growth Report characterises sustainable growth as promoting economic advancement while safeguarding natural resources that supply crucial materials and environmental services [38]. In the realm of construction logistics, sustainability signifies a major shift towards minimising environmental impact, fostering social responsibility, and ensuring economic feasibility [39]. The construction industry has been recognised for its substantial environmental effects, spanning from resource extraction to transportation and waste production [40]. The adoption of eco-friendly practices and cutting-edge technologies has given rise to sustainable construction logistics [41]. To reduce emissions associated with the movement of materials and equipment, green transportation methods, such as electric or hybrid vehicles, should be adopted. Furthermore, employing effective route planning and logistics management systems help enhance delivery schedules and decrease fuel consumption and traffic [38]. Additionally, emphasising sustainable material sourcing and waste reduction contribute to the industry’s overall environmental sustainability [42]. Sustainable construction logistics requires socially responsible practices, including fair labour conditions and community involvement [4]. As sustainability becomes increasingly crucial to stakeholders, the construction industry continues to evolve, advocating for a more environmentally conscious and socially responsible approach to logistics [43]. This ongoing progress not only benefits the environment but aligns with broader global initiatives aimed at achieving sustainable development goals [38]. Grasping key indicators is crucial for tackling sustainability challenges in the construction sector. Commonly, specific metrics are used to assess the success of construction projects [44]. A vital component of sustainable logistics management in construction involves incorporating sustainability goals from various stakeholders, including management, external entities, suppliers, and customers [44]. To achieve sustainability throughout the construction supply chain, it is necessary to fulfil environmental, social, and economic objectives [45]. Product life-cycle analysis is an effective method for evaluating the environmental impact from the design stage through to product or building usage [46]. When choosing construction material suppliers, environmental criteria should align with strategic aims, policies, and regulatory requirements [39]. Construction companies may implement environmental standards for monitoring supplier performance or establish policies for supplier compliance [47]. Studies on sustainable logistics management frequently centre on the triple bottom line framework (environmental, economic, and social pillars) as outlined in the Brundtland Report. The author of [48] conducted a comprehensive review of tools for assessing construction company sustainability based on the triple bottom line pillars, highlighting the importance of understanding relevant indicators for addressing construction sustainability.

Table 1. Sustainable factors.

Factors	[49,50,51,52]	[1,53,54,55]	[56,57,58]	[59,60,61,62]	[36,63,64]	[48,65,66,67]	[7,39,68]	[44,69,70,71]
Enhance labour productivity	x		x	x	x			x
Minimise greenhouse gas emissions	x		x			x
Reduce the total cost of completing a project		x			x			x
Improve resource efficiency		x		x		x		x
Reduce waste	x		x		x		x
Increase well-being		x		x	x	x		x
Enhance technology adoption	x		x				x	x

displays the identified pillars and associated indicators derived from various authors’ perspectives.

2.4. Enhancing Sustainability in Construction Logistics

Achieving sustainability in construction logistics requires the integration of theories and frameworks that encompass environmental, social, and economic dimensions [37]. Logistics theories, such as network theory and transaction cost theory, provide theoretical approaches that emphasise efficient resource utilisation, waste reduction, and cost minimisation [39]. While these theories explain fundamental principles and predict behaviours, frameworks offer structured models for organising and analysing information related to logistics processes [48]. The combination of theory and framework enhances the comprehension of underlying principles, with frameworks offering practical structures for applying these principles in real-world logistics scenarios [44]. Theoretical concepts identify critical success factors by highlighting key elements or principles that contribute to effective logistics operations [72]. For instance, network theory or transaction cost theory may identify critical success factors, such as minimising waste, optimising processes, and addressing bottlenecks [48]. Conversely, logistics frameworks function as practical tools or structures for implementing solutions, providing a systematic approach to organising, analysing, and addressing logistics challenges. Examples like the Green Logistics Framework and the TIMBER Framework offer practical guidance for improving safety and reducing the environmental impact of construction logistics processes. By implementing these framework principles, construction companies can address key issues, such as vehicle emissions, traffic congestion, and productivity losses [73]. Furthermore, the integration of theories and frameworks enable construction logistics to move beyond mere compliance with protocols, actively contributing to sustainability goals and promoting a more socially responsible and environmentally conscious approach to construction activities [74].

2.4.1. Logistics Solutions

Organisations utilise logistics solutions to address logistics challenges through diverse strategies, methods, innovations and approaches [39]. These solutions help businesses tackle logistics-related problems and improve operations [75]. By adopting the strategies outlined in Figure 1, organisations can achieve efficient and sustainable logistics practices, enhancing productivity, reducing delays, and lowering costs [56]. Frameworks, such as the Green Logistics framework, the A-S-I/A-S-I-F framework, the TIMBER framework, and the IF-TOLD framework, incorporate various logistics solutions to enhance sustainability. Aligning these frameworks with the unique logistics challenges of the Middle East, such as dependence on imports and harsh climates, offers significant opportunities for improving construction logistics.

Green Logistics Framework

The Green Logistics framework minimises environmental impacts in logistics operations [76]. Solutions like the Kanban system ensure that materials are replenished only as needed, reducing waste and optimising flow [51]. For instance, in the Middle East, where many construction projects rely on imported materials, the Kanban system can synchronise shipments of high-demand items like steel and cement, reducing the need for large on-site storage, which is challenging in extreme heat. Similarly, the Last Planner System (LPS) improves schedule predictability by fostering collaboration, while just-in-time (JIT) aligns material deliveries with immediate project needs, preventing storage issues in environments where high temperatures can degrade materials like adhesives or paint [1]. Real-time visibility systems, lean design principles, and tools like value-stream mapping, Kaizen (continuous improvement), and Poka-Yoke (error prevention) further streamline operations [1,32]. For example, real-time tracking can help manage port-to-site logistics for imported materials, ensuring efficient customs clearance and immediate site delivery, crucial in large projects like Dubai’s high-rise developments. Optimising transportation routes with energy-efficient vehicles and shifting to rail for bulk material transport, where feasible, can significantly reduce carbon footprints in the Middle East, where road congestion often delays shipments [76]. Workspace efficiency can be enhanced using the 5S methodology, while tools like BIM and CAD improve project visualisation and coordination [32]. Consolidating materials at logistics centres near key ports, such as Jebel Ali in Dubai, minimises site congestion and optimises supply chain reliability [77].

A-S-I/A-S-I-F Framework

The avoid-shift-improve framework, originating in Germany, offers a structured approach to sustainable transport [78,79] In the Middle East, this can be applied by avoiding unnecessary transport through centralised storage and better demand planning, shifting to environmentally friendly transport modes, like electric vehicles, and improving fuel efficiency by adopting alternative energy sources, like solar-powered refrigeration for materials stored at construction sites in hot climates. For example, a large-scale infrastructure project in Riyadh could incorporate centralised hubs for prefabrication and employ electric trucks for on-site deliveries, reducing emissions and transportation costs.

TIMBER Framework

The TIMBER framework emphasises logistics decarbonisation by addressing critical factors—technology, infrastructure, behaviours, and energy [39]. In the Middle East, adopting advanced technologies, such as drones for site surveillance or automated forklifts for warehousing, improves operational efficiency. Infrastructure investments, like building better transport networks between ports and construction sites, help manage the high volume of imported materials [80]. For instance, during the construction of Expo 2020 Dubai, improved road infrastructure ensured smooth material flow despite the region’s high temperatures. Employee training programs focused on sustainable logistics practices, combined with using alternative energy sources, such as solar-powered equipment, can significantly reduce carbon emissions, aligning with regional sustainability goals.

IF-TOLD Framework

The IF-TOLD framework emphasises efficient logistics through proper management of practices and infrastructure [37]. Implementing warehousing and logistics centres to consolidate materials addresses the challenges of import dependence in the Middle East. For example, in Qatar, materials for stadium construction during the FIFA World Cup were consolidated in nearby logistics centres, ensuring efficient sorting and timely delivery despite high temperatures and tight deadlines. This approach improves inventory visibility and reduces site disturbances, essential for large-scale projects in urban areas like Abu Dhabi or Riyadh [1,56].

Comparative Analysis of Logistics Solutions Frameworks

The Green Logistics framework integrates sustainability with lean methodologies and resource efficiency, providing a practical approach tailored to the Middle East. However, it is valuable to compare it with other frameworks, including TIMBER, IF-TOLD, and A-S-I/A-S-I-F, to highlight its unique advantages and contextual relevance.

Green Logistics Framework vs. TIMBER Framework

The TIMBER framework emphasises decarbonisation strategies through technology, infrastructure, behaviours, and energy. While effective globally, its reliance on extensive infrastructure development poses challenges in the Middle East, where resource constraints and fragmented supply chains dominate. The Green Logistics framework, by contrast, focuses on lean principles like just-in-time (JIT) and Kanban, which adapt well to the region’s unpredictable logistics environment. It provides agile solutions for fuel efficiency and material optimisation, addressing cost and environmental concerns directly [51].

Green Logistics Framework vs. IF-TOLD Framework

The IF-TOLD framework prioritises centralising warehousing and logistics centres to enhance efficiency. However, this approach often requires established infrastructure, which is scarce in many parts of the Middle East. The Green Logistics framework’s reliance on digital tools, such as BIM and real-time tracking, enables firms to overcome these limitations by enhancing visibility and coordination without physical centralisation [44,56].

Green Logistics Framework vs. A-S-I/A-S-I-F Framework

The A-S-I/A-S-I-F framework focuses on avoid-shift-improve principles, emphasising systemic changes in logistics. While effective in targeting emissions and long-term shifts, it lacks the immediate adaptability that the Green Logistics framework offers for dynamic construction projects. For example, while A-S-I/A-S-I-F promotes broad modal shifts, the Green Logistics framework applies specific lean strategies that address immediate resource constraints, making it more practical for Middle Eastern construction sites [81,82].

Regional Specificity and Uniqueness

The Middle East presents unique challenges, including political instability, fragmented supply chains, resource scarcity, and rapid urbanisation. The Green Logistics framework excels in addressing these issues through:

• Flexibility: It integrates agile tools like real-time tracking and adaptive scheduling to navigate unpredictable supply chain disruptions caused by political instability.
• Efficiency: Lean methodologies, such as JIT and Kanban, directly tackle high material costs and resource scarcity.
• Scalability: Tools like BIM ensure precise planning and waste reduction for large-scale urban projects.

Unlike TIMBER and IF-TOLD, which assume centralised infrastructure, and A-S-I/A-S-I-F, which emphasises long-term systemic shifts, the Green Logistics framework offers immediate, practical solutions that align with the Middle East’s constraints and opportunities.

By synthesising principles from these frameworks, while addressing the region’s specific needs, the Green Logistics framework stands out as a comprehensive and actionable model for advancing sustainable logistics in the Middle East. Figure 1 depicts the principals of these frameworks and the adopted solutions.

2.4.2. The Critical Susses Factors (C.S. Fs)

Successful management of construction logistics is associated with increased profitability through efficient handling of internal and external processes and relationships [34]. Several researchers have suggested strategies for enhancing sustainability and performance in construction logistics, which are regarded as critical success factors [48,59,83]. These factors, often linked to concepts such as network theory or resource-based theory, highlight crucial elements for effective logistics operations, including reducing delays, optimising processes, and addressing bottlenecks [83]. Critical success factors (CSFs) are considered essential components that should be integrated into business practices to achieve desired outcomes [35]. Proper incorporation of CSFs with business activities can yield substantial results and create meaningful value [44]. In construction logistics, CSFs function as guidelines for implementing and monitoring logistics solutions. It is advised that CSFs be integrated within logistics practices and processes to support the achievement of business goals [1,51,56], thus enhancing the functionality of logistics solutions [59]. As a result, success in logistics and supply chain management requires the use of logistics CSFs as key drivers [39]. These CSFs are developed and managed through the effective implementation of logistics solutions [32]. The following depicts the main CSFs for enhancing construction performance.

Demand Forecasting and Planning

Demand forecasting and planning play a crucial role in enhancing the sustainability of construction logistics operations [84]. Accurate demand predictions enable precise allocation of resources, minimising waste and overproduction while optimising the use of materials, equipment, and workforce [56]. This approach also improves inventory management efficiency, reducing excess stock and associated storage expenses [36]. In transportation planning, precise forecasts lead to optimised routes, decreased fuel usage, and lower emissions [85]. By proactively identifying potential bottlenecks through critical sources, timely project completion can be ensured, mitigating the environmental impact of extended construction activities [86]. Additionally, reliable demand forecasts guide collaboration with suppliers, promoting sustainable practices and responsible sourcing [59]. The ability to adapt to changing conditions based on critical sources ensures that construction logistics operations remain aligned with evolving sustainability standards. Ultimately, integrating critical sources in demand forecasting and planning results in a sustainable and efficient construction logistics supply chain [59].

Proper Information Flow

Proper information flow in construction logistics significantly contributes to sustainability by enhancing communication, coordination, and efficiency throughout the supply chain [1]. A well-established information flow ensures real-time visibility into inventory levels, demand forecasts, and project timelines, enabling proactive decision-making and resource allocation [87]. This transparency minimises the risk of overproduction, reduces excess inventory, and optimises transportation routes, thereby decreasing the environmental impact associated with unnecessary resource consumption and emissions [32]. Effective communication among stakeholders also fosters collaborative efforts towards sustainable practices, such as the use of eco-friendly materials and energy-efficient transportation methods [88]. Furthermore, proper information flow aids in the identification and resolution of potential bottlenecks, reducing project delays and minimising the overall ecological footprint of construction activities [56]. In essence, the critical success factors of proper information flow in construction logistics not only improve operational efficiency but contribute to sustainability by promoting informed decision-making and fostering environmentally responsible practices throughout the construction supply chain [36].

Compliance with Safety, Environmental and Regulations

To advance sustainability within the industry, it is crucial to comply with safety, environmental, and regulatory regulations in construction logistics [36]. The well-being of workers and the reduction of accidents are achieved by following safety standards, which also contribute to the long-term sustainability of the workforce [89]. By controlling emissions, waste disposal, and the use of hazardous materials, environmental regulations help mitigate the ecological impact of construction activities [1]. The company’s reputation is enhanced, and sustainability goals are aligned with this commitment to environmental responsibility [51]. Moreover, the implementation of sustainable practices, including energy-efficient transportation methods and eco-friendly materials, is encouraged through regulatory compliance [1].

Effective Risk Management

The industry’s sustainability can be promoted through effective risk management in construction logistics [59]. Minimising disruptions, ensuring project continuity, and reducing environmental and financial setbacks can be achieved by construction logistics operations by identifying, assessing, and mitigating potential risks [90]. Managing risks proactively can optimise resources and prevent overstocking or underutilisation of materials, which aligns with sustainability goals by minimising waste [36,59]. Moreover, anticipating and addressing risks associated with supply chain disruptions or natural disasters promote resilience and enhance the industry’s capacity to respond to unforeseen challenges [86]. Effective risk management in construction logistics assists in protecting project timelines and financial viability [32]. Additionally, it encourages responsible resource utilisation, environmental resiliency, and a more efficient and adaptable construction supply chain [51].

Efficient Resource Allocation

Construction logistics operations can enhance overall resource efficiency by minimising waste, reducing overconsumption, and increasing overall resource efficiency through accurate demand forecasting of materials, equipment, and manpower allocation [56]. To contribute to sustainability, efficient resource allocation prevents overstocking, reduces storage costs, and minimises environmental impact [38]. It prevents underutilisation and ensures that resources are used to their full potential without any unnecessary production or transportation [86]. The reduction of project delays is made possible by streamlined resource allocation, which also minimises the ecological footprint associated with prolonged construction activities [37].

Collaborating with Suppliers

Collaborating with suppliers is critical for sustainability as it creates a network of environmentally conscious partners and drives positive change across the construction logistics industry [91]. The adoption of environmentally responsible practices and sustainable sourcing is facilitated by collaborative relationships with suppliers, which promote open communication and shared goals [38]. The use of eco-friendly materials and waste reduction, energy efficiency, and waste reduction can be explored by construction logistics operations by working closely with suppliers [92]. Through supplier collaboration, ideas and innovations can be exchanged, which leads to more sustainable solutions throughout the supply chain [39]. Moreover, collaborating with suppliers can advance ethical and responsible business practices, while ensuring that sustainability considerations are included in the sourcing and production processes [56].

Adequate Training and Skill Development

Training programs and sessions emphasise environmental and safety rules and equip workers with the necessary knowledge and skills to follow sustainable practices [93]. Personnel with more training are properly equipped to implement efficient resource management, minimise waste, and optimise transportation routes, which can reduce the footprint of construction logistics operations [51]. Furthermore, developing skills in areas such as technology adoption and innovative logistics practices encourages efficiency and resilience, which aligns with sustainability objectives [39]. The overall competence of the workforce can be enhanced by implementing adequate training and creating a culture of responsibility and environmental awareness [85]. Thus, by investing in the training and skill development of personnel, construction logistics processes influence sustainability by fostering reliable and knowledgeable practices across all levels of the supply chain [38].

Strong Commitment and Support from Top Management

The industry’s sustainability is driven by top management’s strong commitment and support [94]. A strong commitment to sustainability is a key factor in leadership, which sets the attitude for the entire organisation, influences decision-making, and prioritises environmentally responsible practices [74]. The allocation of financial and human resources to sustainable initiatives, including eco-friendly technologies and green logistics practices, is made easier with the support of top management [37]. Employees are encouraged to align their actions with environmental goals through this commitment, which fosters a culture of sustainability throughout the organisation [38]. Moreover, a dedicated commitment from the leadership improves stakeholder involvement, indicating to clients, suppliers, and the community that the firm is committed to sustainable construction logistics practices [39]. In essence, the commitment and support from top management play a crucial role in progressing sustainability by introducing a sense of responsibility, driving change, and influencing the adoption of eco-conscious practices in the construction industry [44].

2.5. The Development of the Conceptual Model

This section presents a comprehensive theoretical framework that examines the interrelationships between logistical challenges, solutions, critical success factors (CSFs), and sustainability in the construction sector. By integrating principal–agent theory (PAT), transaction cost analysis (TCA), resource-based View (RBV), and network theory, the framework offers a novel approach to analysing how logistics practices influence sustainability in the construction industry. These theoretical perspectives emphasise the importance of aligning stakeholder objectives, minimising transaction costs, optimising internal resources, and strengthening network connections to achieve sustainable outcomes.

2.5.1. Principal-Agent Theory (PAT)

PAT addresses conflicts arising from information asymmetries among stakeholders, such as contractors and clients. Divergent objectives often lead to inefficiencies, delays, and increased costs. By integrating PAT, the framework highlights solutions like real-time tracking tools and transparent communication mechanisms to mitigate misalignments. For example, studies have demonstrated that building information modelling (BIM) enhances information exchange across construction teams, reducing delays caused by inadequate communication [95]. Similarly, technological solutions, such as tracking tools, minimise costs through transparent, immutable records [96]. These findings reinforce how PAT supports the development of logistics solutions that enhance accountability, coordination, and long-term improvements in resource allocation and stakeholder alignment [59,97]. By addressing these asymmetries, the framework introduces a critical layer of transparency and trust, particularly relevant to the Middle East construction sector, where complex stakeholder dynamics often hinder efficiency. This differentiation allows the framework to move beyond traditional theoretical applications, ensuring its relevance in addressing real-world logistics issues.

2.5.2. Transaction Cost Analysis (TCA)

TCA plays a pivotal role in identifying and mitigating economic inefficiencies in logistics operations, such as transport delays, demand fluctuations, and regulatory challenges [98]. The framework incorporates TCA to emphasise cost-effective logistics solutions, including the Last Planner System (LPS) and lean methodologies, which reduce material waste and enhance project schedules [76]. Collaborative procurement strategies also lower regulatory and compliance expenses, highlighting the broader cost-reduction potential of TCA [2]. By addressing cost-efficiency, resource utilisation, and environmental sustainability, TCA ensures continuous improvement in operational effectiveness [99].

This framework expands the practical application of TCA by aligning logistics solutions with the unique economic challenges of the Middle East construction industry. It not only emphasises cost savings but underscores the importance of strategic investments in logistics infrastructure and technology to maintain competitiveness in a resource-scarce environment.

2.5.3. Resource-Based View (RBV)

The RBV emphasises the utilisation of distinctive organisational resources and capabilities to achieve competitive advantages and promote sustainability. Effective leadership, advanced technology, and skilled personnel are critical assets in overcoming logistical challenges. For instance, investment in real-time tracking systems optimises material flows and minimises waste, exemplifying the RBV’s focus on resource-driven efficiency improvements [100]. Additionally, organisations with trained personnel in eco-friendly logistics methods significantly reduce emissions, demonstrating that human resources are as essential as technological assets for sustainability [101,102]. By leveraging unique internal resources, the framework fosters continuous improvements in logistical efficiency and environmental performance.

The framework’s application of RBV demonstrates how regional firms can turn inherent constraints, such as limited material availability, into strategic advantages by developing specialised skills and adopting innovative logistics practices tailored to their environment.

2.5.4. Network Theory

Network Theory underscores the importance of interconnected relationships and collaborative networks in construction logistics. Robust cooperation among suppliers, contractors, and regulatory entities enhances resource sharing, responsiveness, and adaptability [23]. Projects with well-established supplier networks experience fewer material delays and improved resource utilisation, resulting in reduced waste [103]. Collaborations with third-party logistics providers further enhance sustainability by optimising delivery schedules and minimising emissions through efficient routing [104]. This relational perspective ensures that organisations maintain logistical enhancements through dependable partnerships and adaptive networks [59].

Thus, this framework (as depicted in Figure 2) stands out by offering a holistic and unified model that addresses the interdependencies between logistics challenges, solutions, and critical success factors (CSFs) in the construction industry. It innovatively integrates principal–agent theory (PAT), transaction cost analysis (TCA), resource-based view (RBV), and network theory, providing a multidimensional perspective that combines economic, relational, and resource-based approaches to sustainability [1,56]. The principles of these theories inform the formulation of relationships among constructs and support the development of the following hypotheses. This framework is tailored specifically to the unique challenges of the construction industry, the framework is to deliver practical applications like BIM, lean methodologies, and 3PL services to directly combat inefficiencies. Unlike previous studies [23,105], it bridges theoretical insights with actionable strategies, offering both academic and practical value in fostering sustainable logistics practices and enhancing industry resilience.

2.6. Logistics Solutions and Sustainability

The integration of network theory and transaction cost theory (TCA) provides a comprehensive framework for understanding the relationship between logistics solutions and sustainability outcomes in the construction sector. Network theory posits that the effectiveness of logistics solutions depends primarily on the quality of relationships and collaborations among supply chain participants. Efficient logistics solutions enhance these networks and promote communication and cooperation, which are essential for sustainable practices [81]. For instance, the authors of [44] demonstrated that strong inter-organisational ties improve the implementation of just-in-time (JIT) methods, leading to significant reductions in material waste and improved resource efficiency. Moreover, the author of [106] argued those collaborative logistics strategies, such as shared transport and storage, can significantly reduce carbon emissions associated with construction logistics. These approaches not only optimise resource allocation but also establish a sustainable logistics framework that contributes to broader environmental goals. This perspective is supported by [107], who emphasise that advanced logistics solutions, including third-party logistics (3PL) and real-time tracking systems, enable construction firms to enhance supply chain activity coordination and improve material flow, thereby reducing lead times and resource consumption. Conversely, transaction cost theory highlights the importance of minimising the costs associated with supply chain inefficiencies. Effective logistics practices can significantly reduce transaction costs related to delays and miscommunication; a point emphasised by [108]. The implementation of logistics solutions that promote sustainability aligns with the firms’ objectives of reducing operational costs while maximising value. For instance, ref. [2] showed that construction companies adopting digital technologies in logistics processes observe a notable improvement in operational efficiency, resulting in lower costs and improved sustainability outcomes. Furthermore, the research of [107] suggests that incorporating innovative technologies into logistics, such as automation and data analytics, not only enhances transparency within the supply chain but drives accountability among stakeholders. Such technological advancements facilitate better demand forecasting and inventory management, which are crucial for minimising waste and reducing environmental impact. Ref. [59] further support this notion, suggesting that technology integration fosters an environment where sustainable practices can thrive. While the advantages of integrating logistics solutions for sustainability are evident, it is important to critically evaluate potential limitations. Some studies, such as that by [81], indicate that the initial investment and ongoing maintenance costs associated with advanced logistics technologies can be a barrier for smaller construction firms. This highlights the need for a balanced approach that considers both economic implications and the potential for sustainable outcomes. Consequently, we propose the following hypothesis:

H1. 

Logistics solutions have a direct, positive effect on sustainability in the construction industry (LS → SF).

2.7. Critical Success Factors (CSFs) and Sustainability

Resource-based theory (RBT) and principal-agent theory (PAT) provide conceptual foundations for assessing the influence of critical success factors (CSFs) on sustainability outcomes in the construction industry. RBT posits that organisations can attain a competitive advantage through the effective utilisation of unique resources and capabilities, such as strategic project management and stakeholder engagement [107]. Within this context, crucial CSFs, including strong leadership, effective communication systems, and robust supplier relationships, are instrumental in enhancing the capacity of construction firms to implement environmentally sustainable practices. For instance, capable leadership can foster a sustainability-oriented organisational culture, encouraging teams to prioritise eco-conscious methodologies [59,109]. Furthermore, effective communication systems ensure that all stakeholders are aligned with sustainability objectives, promoting transparency and accountability throughout the project implementation. This alignment is crucial, as [44] emphasises that clear communication channels can significantly enhance collaborative efforts, which are essential for the successful adoption of sustainable practices. The role of technology in facilitating communication, such as project management software and collaborative platforms, is significant because it enhances information sharing and coordination among stakeholders. Conversely, PAT elucidates the intricacies of stakeholder interactions, particularly between management and employees or suppliers, which can considerably affect the adoption of sustainable practices [110]. This theory underscores the potential conflicts of interest and information asymmetries that may arise between parties [1]. When CSFs are effectively managed, for instance, through the implementation of sustainability performance incentives, they can help align the interests of various stakeholders and foster collaborative efforts towards sustainability [111]. The use of performance-based contracts serves as a practical illustration that motivates suppliers to achieve sustainability targets, thereby improving overall project sustainability [23]. Furthermore, [107] contended that firms proficient in managing their critical success factors are better equipped to navigate the complexities of sustainability. By integrating RBT and PAT, organisations can develop a comprehensive approach that not only leverages their unique resources but addresses potential stakeholder conflicts, ultimately leading to enhanced sustainability outcomes. This link between CSFs and sustainability implies that a strategic focus on these factors is crucial for construction firms that aim to improve their environmental performance. Consequently, we propose the following hypotheses:

H2. 

Critical success factors positively influence sustainability in the construction industry (CSF → SF).

2.8. Logistics Challenges and Sustainability

The impact of logistical challenges on construction project sustainability can be effectively examined through the lens of principal-agent theory (PAT). This theory suggests that even minor logistical inefficiencies or disruptions may lead to unforeseen and detrimental effects on sustainability outcomes [59]. For instance, logistical issues that cause material delivery delays can result in increased resource waste and project schedule disruptions, ultimately compromising the overall sustainability of construction endeavours [112,113]. This concept aligns with the findings of [107], who posit that logistics management efficacy is directly linked to sustainability performance, emphasising the importance of addressing inefficiencies to achieve the desired sustainability goals. By comprehending the potential adverse consequences of logistical obstacles, project managers can implement proactive measures to mitigate their impacts, thus supporting sustainability initiatives. PAT further elucidates the interactions between various logistics stakeholders, particularly how conflicting interests can generate challenges that negatively affect sustainability. For instance, a contractor might prioritise short-term cost reductions, while a supplier may emphasise adherence to sustainable practices, resulting in misaligned objectives and subsequent inefficiencies [1]. When logistical issues arise, such as resource shortages or delivery delays, these misalignments can exacerbate sustainability problems, underscoring the necessity of aligning stakeholder incentives to foster cooperation and enhance project sustainability [91]. Moreover, clear communication and collaboration among parties is vital for effectively addressing logistical challenges [114]. Failure to recognise and address these dynamics can lead to compounded sustainability issues, thereby further emphasising the importance of effective logistics management in construction projects [115]. Consequently, acknowledging and strategically managing the complex interplay between logistical obstacles and stakeholder encouragement is essential for improving the sustainability of construction logistics. Therefore, we hypothesise the following:

H3. 

Logistics challenges adversely affect sustainability in the construction industry.

2.9. Logistics Solutions and Critical Success Factors

Transaction cost analysis (TCA) offers a comprehensive framework for scrutinising the complex relationship between logistics solutions and critical success factors (CSFs) in the construction industry. TCA concentrates on minimising expenses associated with inefficiencies and risks in supply chain transactions, particularly those arising from communication lags, material waste, and poorly managed resources [59]. Within the construction sector, logistical solutions, such as just-in-time (JIT) delivery, real-time tracking systems, and the Last Planner System (LPS), effectively address these transaction costs by streamlining the material flow and reducing waste, thus directly contributing to cost savings and improved operational efficiency. Furthermore, when logistics solutions are aligned with crucial CSFs, including effective risk management, strong communication, and robust support from senior leadership, a synergistic effect emerges, further diminishing transaction costs. This alignment enhances operational efficiency and mitigates logistical disruptions, ultimately boosting sustainability [91]. For instance, the adoption of the LPS has been demonstrated to significantly reduce project delays and ensure prompt material delivery, thereby lowering storage expenses and waste [59]. The effectiveness of the LPS is further enhanced when underpinned by robust CSFs, such as systematic project planning and collaboration with suppliers. As [116] noted, these factors foster an environment conducive to efficiency and streamlined decision-making, which are vital for successful project execution. The report of the Palestinian governments [107] underscores that the incorporation of technology in logistics management improves communication and coordination among stakeholders, which is crucial for minimising transaction costs and enhancing sustainability outcomes. Nevertheless, while the benefits of aligning logistics solutions with CSFs are evident, it is essential to consider potential obstacles, such as organisational unwillingness and resistance to change among stakeholders. These challenges can impede the effective implementation of logistics strategies and their associated CSFs, as observed by [56]. Consequently, acknowledging and addressing these dynamics is crucial for leveraging TCA to enhance both the sustainability and cost-effectiveness of construction projects. Thus, we propose the following hypotheses:

H4. 

Interaction exists between logistics solutions and critical success factors in the construction industry.

2.10. Interaction Between Logistics Solutions and Logistics Challenges

Transaction cost analysis (TCA) offers crucial insights into the interaction between logistics solutions and construction industry challenges, demonstrating how well-designed logistics strategies can effectively reduce costs stemming from inefficiencies. Construction projects frequently encounter logistical difficulties, such as late material deliveries, unreliable supply chains, and poorly coordinated schedules, resulting in increased transaction costs in the form of storage fees, project setbacks, and inefficient resource utilisation [51]. These impediments create inefficiencies that strain budgets and disrupt project timelines, underscoring the need for robust logistics management approaches. To address these transaction costs, tailored logistics solutions, including just-in-time (JIT) delivery, real-time tracking systems, and sophisticated scheduling tools, have become essential for optimising processes and minimising uncertainties in construction logistics. However, the efficacy of these solutions depends on their precise alignment with the project’s requirements and logistical context. For instance, while JIT delivery can reduce the costs associated with excess stock, it requires dependable suppliers and a consistent delivery schedule. Any interruption in JIT deliveries can impede project progress, potentially increasing transaction costs [1]. Similarly, real-time tracking systems can mitigate the risk of material delays by providing instant visibility of the shipment locations. However, their effectiveness relies on the level of integration among all parties involved, including suppliers and on-site personnel [36]. When logistics solutions are poorly matched with existing challenges, such as implementing JIT in volatile supply chains, the anticipated benefits of reduced transaction costs may be compromised, exposing the project to unexpected delays and increasing waste. In this context, TCA emphasises that effective logistics solutions must be sufficiently flexible to address the specific logistical challenges of each construction project. Techniques such as the Last Planner System (LPS) and value-stream mapping (VSM) synchronise project scheduling with material flow, enabling better coordination between supply availability and project needs [107]. When customised to address project-specific logistics issues, these solutions can reduce miscommunication, prevent material excesses or shortages, and minimise delays. Thus, TCA illustrates that logistics solutions, when responsive to each project’s unique challenges, not only decrease costs but also enhance the resilience of the construction supply chain. This adaptability allows firms to achieve greater operational efficiency, minimise waste, and ultimately improve project outcomes [51]. Consequently, we propose the following hypotheses:

H5. 

There is interaction between logistics solutions and challenges in the construction industry.

2.11. Interaction Between Critical Success Factors and Logistics Challenges

The interplay between critical success factors (CSFs) and logistical challenges is key to achieving sustainability in construction. Resource-based theory (RBT) posits that an organisation’s distinctive assets and capabilities can be utilised to effectively address logistical challenges [117]. For instance, a construction firm with robust risk management capabilities as a critical success factor may be better equipped to address logistical issues, such as supply chain disruptions or unexpected project scope alterations. This expertise enables organisations to formulate alternative approaches that mitigate the negative impacts of logistical obstacles on sustainability, thus fostering more resilient project implementation [107]. Furthermore, the principal–agent theory (PAT) elucidates the interactions among various stakeholders and potential conflicts that may arise during logistical difficulties [59]. Effective management of critical success factors, such as streamlined communication and coordination, enables construction firms to synchronise their efforts to address logistical challenges more efficiently, resulting in improved sustainability outcomes. For instance, when suppliers and contractors align sustainability objectives and adopt coordinated risk management strategies, overall project performance can be significantly enhanced, underscoring the importance of collaborative engagement among stakeholders [1]. Additionally, the incorporation of cutting-edge technologies and practices in logistics management can facilitate this collaborative approach. According to [81], the utilisation of real-time data analytics and communication tools enhances stakeholder coordination, allowing prompt responses to logistical disruptions and promoting sustainable practices throughout the project lifecycle. By fostering an environment of transparency and cooperation, construction firms can align their operational objectives with sustainability goals, reinforcing the significance of CSFs in overcoming logistical challenges. Consequently, it is hypothesised that

H6. 

There is an interaction between critical success factors and logistics challenges in the construction industry.

3. Methodology

From the review of the literature on logistics challenges, logistics solutions and CSFs of construction logistics, as elaborated in the literature review section, a set of 21 challenges, 18 solutions, and 8 CSFs were developed and considered suitable for enhancing the sustainability of construction logistics. The qualitative approach consisted of 29 participants, including project managers, logistics coordinators, sustainability officers, and site supervisors from various construction companies actively engaged in sustainable projects. These individuals were selected based on their experience and involvement in construction projects that prioritised sustainable practices. The main purpose of the interviews was to enhance the understanding of the current logistics challenges and their consequences within the Middle East and to review and modify the factors selected from the previous studies. The respondents’ details are elaborated on in

Table 2. Interviewees list.

#	Code	Role of Interviewees	Experience
1	A	Contractor’s representative	More than 15 years
2	B	Project manager	12 years
3	C	Senior Site engineer	15 years
4	D	Logistics manager	12 years
5	E	Logistics manager	15 years
6	F	Project manager	21 years
7	G	Contractor’s representative	18 years
8	H	Project engineer	10 years
9	I	Senior office engineer	10 years
10	J	Project manager	20 years
11	K	Construction manager	More than 15 years
12	L	Contractor’s representative	13 years
13	M	Project manager	10 years
14	N	Senior Site engineer	18 years
15	O	Logistics manager	8 years
16	P	Logistics manager	11 years
17	Q	Project manager	17 years
18	R	Contractor’s representative	8 years
19	S	Supplier of construction material and previous owner of a construction owner	20 years
20	T	Supplier of construction material and owner of block factory	25 years
21	J	Construction manager	12 years
22	V	Logistics manager	12 years
23	W	Logistics manager	15 years
24	X	Project manager	12 years
25	Y	Contractor’s representative	More than 18 years
26	Z	Project engineer	21 years
27	AA	Senior office engineer	18 years
28	BB	Project manager	8 years
29	CC	PhD in construction logistics	6 years

.

Quantitative research was conducted using a questionnaire to validate qualitative findings, employing a nonprobability purposive sampling method. The sample included foremen, junior engineers, senior engineers, project managers, and contractor representatives in the Middle East construction industry. The role of logistics management varies with project size and type in this region. The questionnaire was designed to elicit quantitative responses on logistical challenges, solutions, and critical success factors for sustainability. Following Rowley’s methodology, it included closed-ended questions for demographic data and insights into participants’ roles, followed by Likert-scale questions on logistical challenges, CSFs, logistics solutions, and sustainability factors. The questionnaire was carefully designed to avoid leading questions and align with the study objectives. It was pilot-tested with ten industry professionals to ensure clarity. A sample size of 422 was chosen to capture diverse perspectives on logistical challenges and sustainability practices. Participants were selected from companies of various sizes and types of construction projects to ensure representativeness. However,

Table 3. Constructs, measurement items.

Logistics Challenges	Inadequate planning for logistics processes, including resource management
	2. A lack of expertise (or knowledge) in construction logistics
	3. Ineffective monitoring and control of logistics activities
	4. Inadequate alignment between construction schedules and logistics practices
	5. Inefficient site layout
	6. Management’s insufficient commitment to on-site logistics operations
	7. Ineffective coordination among internal parties
	8. Inadequate communication among internal parties
	9. Lack of real-time tracking of fleet and equipment used in construction logistics
	10. Ambiguity in logistics responsibilities for the construction team
	11. Delays in decision-making by the consultant engineer
	12. Duplication and errors caused by excessive paperwork
	13. The fluctuating prices of construction materials and components
	14. Lack of coordination and integration with suppliers
	15. Neglecting the understanding of quality in purchasing processes
	16. Poor material identification and estimation
	17. Accuracy of goods (orders) received from suppliers
	18. Waste of materials due to inefficient material handling
	19. Inaccurate inventory records
	20. The use of inappropriate types of vehicles in transportation
	21. Inefficient management of the return process for purchased materials
	22. (Temporary) Closures resulting from unstable political conditions
	23. The sudden labour shortage
Logistics Critical Success Factors	Accurate demand forecasting and planning
	2. Proper information flow.
	3. Compliance with safety, environmental and regulations
	4. Effective risk management
	5. Efficient resource allocation.
	6. Collaborating with suppliers
	7. Adequate training and skill development
	8. Strong commitment and support from top management
Logistics Solutions	Implementing the Kanban system
	2. Implementing the Last Planner System (LPS)
	3. Implementing just-in-time (JIT)
	4. The utilisation of real-time visibility tools
	5. Utilisation of third-party logistics (3PL) services
	6. Implementation of logistic centres
	7. Applying lean design principles in designing construction projects
	8. Utilising project management tools and procedures
	9. Using value-stream mapping to assist in identifying and eliminating non-value-added activities.
	10. Applying the Kaizen principle (Continuous Improvement)
	11. Implementing Poka-Yoke (Error-prevention)
	12. Optimised transportation routes
	13. Conducting a regular on-site visit (Gemba Walks)
	14. Applying the 5S Methodology
	15. Applying ABC (Pareto) analysis for inventory management.
	16. Implementing the Andon system
	17. Participate in associations, non-profit activities, and events
	18. Use of information systems and modelling tools, such as BIM and 3D

depicts the items of the questionnaire for the main survey (Questionnaire I).

3.1. Limitations of the Chosen Methodologies and How They Were Mitigated

The chosen research approach integrates qualitative and quantitative methods within a critical realist philosophy, acknowledging limitations but employing strategies to address them. Qualitative methods, like semi-structured interviews, may introduce subjectivity and bias due to reliance on personal experiences [118]. To mitigate this, data triangulation involves interviewing a diverse range of stakeholders in the Middle East, such as construction managers, logistics experts, and engineers, to capture varied perspectives and reduce individual bias. A semi-structured interview guide ensures consistency while allowing in-depth exploration. To counter the limited generalisability of qualitative research, a quantitative survey based on qualitative findings was distributed to a larger sample to validate and generalise initial insights. Pilot testing refined survey questions to address design weaknesses and enhance clarity. Although surveys may not fully capture the contextual complexity of logistics and sustainability challenges, the preceding qualitative phase grounds the survey in the realities of the Middle Eastern construction industry. The integration of qualitative and quantitative data in mixed-methods research, despite being time-intensive and complex, is managed through a sequential design where qualitative data inform the conceptual framework, which is then validated by quantitative methods. An abductive reasoning process, alternating between theory and empirical data, integrates insights from both methods coherently. Through careful design choices and mitigation strategies, this study achieves robust, credible, and contextually relevant findings on logistics solutions and CSFs addressing challenges and impacting sustainability in the Middle Eastern construction sector.

3.2. Model Development

Partial least square structural equation modelling (PLS-SEM) has attracted massive attention across several fields, particularly business research and social sciences [20]. Various research that focused on the PLS-SEM approach has recently been published in popular SSCI journals [20,119]. SMART-PLS 3.2.7 the newest software edition, was employed to evaluate the collected data to model the priority of the logistics challenges, logistics solutions and CSFs using SEM. PLS-SEM was initially recognised for its outstanding forecasting purposes over covariance-based structural equation modelling (CB-SEM) [99] although the differences between the two strategies are comparatively slight [120]. The statistical analysis performed in this study comprised the measurement and structural model evaluation technique.

3.3. Data Collection

Maximisation response rate is a priority for researchers. However, this could be enhanced by choosing the most appropriate method for data collection, including distributing the questionnaires [61]. However, several ways could be used for data collection including, mail, email, internet, telephone, and paper based [121]. However, the main consideration to determine the best way is considering the respondents’ time, experience, and work field [122]. So, the paper-based method and online method (Microsoft form method) are adopted in this research to enhance the response rate and increase the flexibility for participation.

3.4. Pilot Test

It is recommended to test the questionnaire on a small group, including experienced people, before the data collection [123]. However, this will help the researcher to know if there are any missing, errors, ambiguity, or unsuitable words, and to test the difficulty. Moreover, this may assist in defining any missing information that is required for the data analysis later [124]

3.5. Data Analysis

The collected data was analysed in two different stages for this research. In the initial phase, SPSS 18.02 was employed for descriptive statistics and preliminary data analysis of the mean, and the standard deviation. In the second stage, structural equation modelling (SEM) was utilised to test and examine the relationships among variables in the proposed conceptual model. Thus, the main data analysis technique used in the research is SEM, and this section briefly explains and supports its use. Researchers have widely accepted it in IS, social and behavioural science [125]. SEM, which can be referred to as path analysis, analysis of covariance structure, and simultaneous equation models, is employed to test and examine the hypothesised relationships between variables in the conceptual model. SEM is regarded as an updated version of the multivariate analysis. A set of hypotheses can be tested simultaneously among multiple independent and dependent variables in this version [119]. The authors of [126] claimed SEM as a multivariate method that combines the elements of factor analysis and multiple regression to estimate multiple relationships simultaneously. SEM assists in testing the interrelated hypotheses through systematic single analysis to facilitate the development of concepts and theories [119]. SEM assists in assessing and achieving a model’s fit with the collected data [127]. Complex mathematical models can also be effectively handled by it. However, the reasons behind selecting SEM as the primary analysis technique in this research are as follows:

• Structural equation modelling is more appropriate than other statistical techniques when the model includes several exogenous (independent) variables and endogenous (dependent) variables with interconnected relationships [123]. This research includes several variables (construct), including logistics challenges, CSFs, logistics solutions, and sustainability factors. These variables seem to be affected by each other at the same time. The model will undergo simultaneous testing in this situation. When utilising first-generation statistical tools, it would be necessary to conduct multiple analyses.
• The proposed conceptual model is to understand the effect of logistics challenges on sustainability and the promises of the CSFs and logistics solutions in the context of the Middle East which is considered a complex model. So, testing complex modelling requires the use of SEM, which is more valuable than first-generation statistical tools [106].
• The proposed research model, which employs a confirmatory modelling strategy, will be used to test a set of hypothesised relationships within the constructs of this research [99].

According to [119], there are six stages in the SEM decision process (see Figure 3), including defining specific constructs, developing the measurement model, designing the study to create empirical results, assessing the validity of the measurement model, specifying the structural model, assessing the validity of structural model [99]. However, the following steps were adopted in the data analysis as follows:

• To evaluate the model fit, this study utilised key indicators, such as CFI (comparative fit index), TLI (Tucker–Lewis index), and RMSEA (root mean square error of approximation). The final model achieved satisfactory fit with CFI = 0.93, TLI = 0.91, and RMSEA = 0.07, meeting commonly accepted thresholds for good model fit.
• Missing data comprised 5% of the dataset and were handled using full information maximum likelihood (FIML), as this method is robust to data missing at random (MAR). Little’s MCAR test confirmed that the missingness did not bias the results (p > 0.05).
• The SEM model included four latent variables: logistics challenges, solutions, success factors, and sustainability factors, measured using a total of 58 observed indicators on a five-point Likert scale. The measurement model was validated through confirmatory factor analysis, achieving significant factor loadings above AVE values above 0.50, indicating convergent validity.

3.6. Bias Minimising

Avoiding or minimising bias in data collection is an essential issue in the research’s questionnaire to obtain reliable and real representative data [128]. Several types of bias were suggested by [128], and they were. considered while formulating the questionnaire for this research. Firstly, by asking clear, neutral questions, unbiased, and designed to elicit accurate responses relevant to the research objective. Secondly, choosing the right people ensures a representative sample. Proper formatting and structuring of the questionnaire are ensured to maintain clarity and respondent engagement, avoiding confusion or misinterpretation of questions. Thirdly, offering multiple options and avoiding the leading questions to prevent response bias and allows for more nuanced answers. Finally, administration issues, such as survey timing, mode of delivery, and ensuring anonymity, are prioritised to influence the honesty and accuracy of responses.

4. Results and Discussion

This chapter is designed to discuss statistical analysis that adheres to the research objectives and framework discussed in previous chapters. The section discusses the reliability of the survey responses through several tests including Cronbach’s alpha, and the normality of the samples being studied. Additionally, the survey instrument consists of the main features of the items that are presented through summary statistics. These summary statistics are organised by frequency tables and diagrams. The validity of the survey instrument is tested in the next section of the chapter by conducting a confirmatory factor analysis (CFA) with SPSS-AMOS. The chapter ends with discussing the testing of research hypotheses throughout the structure model presented by AMOSS.

4.1. The Survey Instrument’s Reliability

Cronbach’s alpha is employed to determine the reliability of survey items within the latent construct. To obtain meaningful results, it is necessary to evaluate the accuracy of the survey items; otherwise, results will be meaningless because the survey items do not measure what they are supposed to. Cronbach’s alpha coefficient that exceeds 0.70 is regarded as having a reliable scale according to a rule of thumb [99]

The logistics challenges construct has 23 items with Cronbach’s alpha coefficient of 0.99, the logistics solutions construct has 18 items with Cronbach’s alpha coefficient of 0.94, the critical success factors construct has 11 items with Cronbach’s alpha coefficient of 0.97, the sustainable factor construct has 7 items with Cronbach’s alpha coefficient of 0.88. The calculated Cronbach’s alpha coefficients are highly satisfactory and exhibit high internal consistency because they all exceed 0.70.

Table 4. Cronbach’s alpha results of factors’ scales.

Construct	# of Variables	Cronbach’s Alpha Coefficient
The logistics challenges construct	23	0.99
The logistics solutions construct	18	0.94
The critical success factors construct	11	0.97
The sustainable factor construct	7	0.88

provides a summary of the calculated Cronbach’s alpha coefficients.

4.2. Respondents Background

The professional roles of all respondents are shown in Figure 4: engineers are the majority (34.12%), project managers are second (23.93%), foremen are third (20.56%), and contractor representatives are fourth (21.56%).

4.3. Years of Experience

The experience of participants in the survey varies, as shown in Figure 5. A total of 45.7% had an experience of two to eight years, followed by 30.09% who had experience of less than two years, and 24.17% who had an experience of more than eight years (Figure 4).

4.4. Construction’s Project Category

Figure 6 illustrates the various construction project categories included in this questionnaire: 36.73% were urban, 32.23% were rural, and 31.04% were city-centre projects.

4.5. Experience Field

According to Figure 7, it appears that most participants (27.25%) gained experience in residential/housing projects; 25.59% gained experience in commercial projects and 20.85% in institutional projects; 14.22% gained experience in infrastructure projects and 12.09% in industrial building projects.

4.6. Descriptive Statistics for Challenges Affecting Construction Logistics

Table 5. Respondents’ satisfaction with challenges affecting construction logistics processes.

Challenges	Min	Max	Sum	Mean	Std.	Variance
CHL17: Accuracy of goods (orders) received from suppliers	1.00	5.00	1831.00	4.3389	1.21	1.47
CHL11: Delays in decision-making by the consultant engineer	1.00	5.00	1828.00	4.3318	1.19	1.43
CHL4: Inadequate alignment between construction schedules and logistics practices	1.00	5.00	1816.00	4.3033	1.23	1.51
CHL14: Lack of coordination and integration with suppliers	1.00	5.00	1810.00	4.2891	1.18	1.39
CHL10: Ambiguity in logistics responsibilities for the construction team	1.00	5.00	1806.00	4.2796	1.30	1.71
CHL20: The use of inappropriate types of vehicles in transportation	1.00	5.00	1803.00	4.27	1.19	1.43
CHL22: (Temporary) Closures resulting from unstable political conditions	1.00	5.00	1802.00	4.27	1.27	1.61
CHL18: Waste of materials due to inefficient material handling	1.00	5.00	1796.00	4.2	1.16	1.35
CHL8: Inadequate communication among internal parties	1.00	5.00	1793.00	4.24	1.18	1.40
CHL1: Inadequate planning for logistics processes, including resource management	1.00	5.00	1791.00	4.24	1.20	1.44
CHL7: Ineffective coordination among internal parties	1.00	5.00	1784.00	4.2	1.19	1.43
CHL2: A lack of expertise (or knowledge) in construction logistics	1.00	5.00	1780.00	4.21	1.187	1.41
CHL23: The sudden labour shortage	1.00	5.00	1777.00	4.2	1.28	1.
CHL5: Inefficient site layout	1.00	5.00	1775.00	4.20	1.20	1.46
CHL16: Poor material identification and estimation	1.00	5.00	1774.00	4.20	1.31	1.73
CHL6: Management’s insufficient commitment to on-site logistics operations	1.00	5.00	1770.00	4.19	1.213	1.47
CHL12: Duplication and errors caused by excessive paperwork	1.00	5.00	1767.00	4.18	1.18	1.40
CHL15: Neglecting the understanding of quality in purchasing processes	1.00	5.00	1760.00	4.17	1.25	1.56
CHL3: Ineffective monitoring and control of logistics activities	1.00	5.00	1755.00	4.15	1.28	1.66
CHL21: Inefficient management of the return process for purchased materials	1.00	5.00	1754.00	4.15	1.2	1.59
CHL19: Inaccurate inventory records	1.00	5.00	1750.00	4.14	1.18	1.40
CHL13: The fluctuating prices of construction materials and components	1.00	5.00	1741.00	4.1256	1.28054	1.640
CHL9: Lack of real-time tracking of fleet and equipment used in construction logistics	1.00	5.00	1721.00	4.0782	1.33153	1.773

shows the frequency of the questionnaire responses regarding each of the 23 factors affecting construction logistics in the Middle East construction industry, using a Likert scale (1-not at all influential, 2-slightly influential, 3-somewhat influential, 4-very influential, 5-extremely influential). The factors are ranked according to their mean from highest to lowest. The table consists of the mean of all variables, the deviation from the mean, and the standard deviation.

4.7. Descriptive Statistics for Logistics Critical Success Factors (CSFs)

Table 6. Respondents’ satisfaction with critical success factors for enhancing the success/efficiency/effectiveness of the construction logistics process.

CSFs	Min	Max	Sum	Mean	Std	Variance
CSF6: Effective risk management	1.00	5.00	1831.00	4.33	0.053	1.21
CSF9: Collaborating with suppliers	1.00	5.00	1808.00	4.28	0.060	1.52
CSF10: Adequate training and skill development	1.00	5.00	1796.00	4.25	0.057	1.40
CSF7: Integration of technology	1.00	5.00	1782.00	4.2	0.058	1.44
CSF5: Compliance with safety, environmental and regulations	1.00	5.00	1780.00	4.21	0.059	1.50
CSF2: Efficient transportation and delivery management	1.00	5.00	1760.00	4.17	0.06	1.59
CSF4: Proper information flow	1.00	5.00	1759.00	4.16	0.064	1.74
CSF8: Efficient resource allocation	1.00	5.00	1751.00	4.14	0.062	1.64
CSF3: Effective inventory management	1.00	5.00	1748.00	4.14	0.064	1.73
CSF1: Accurate demand forecasting and planning	1.00	5.00	1738.00	4.1	0.06	1.77
CSF11: Strong commitment and support from top management	1.00	5.00	1736.00	4.1	0.060	1.56

shows the frequency of the questionnaire responses regarding the 11 logistics critical success factors to be considered for enhancing the success/efficiency/effectiveness of the construction logistics process in the Middle East construction industry, using a Likert scale (1-not at all influential, 2-slightly influential, 3-somewhat influential, 4-very influential, 5-extremely influential). The factors are ranked according to their mean from highest to lowest. The table consists of the mean of all variables, the deviation from the mean, and the standard deviation.

4.8. Descriptive Statistics for Logistics Solutions

Table 7. Respondents’ satisfaction with logistics solutions for enhancing the success/efficiency/effectiveness of the construction logistics process.

Logistics Solutions	Mean	Min	Max	Std.	Variance
LS17: Participate in associations, non-profit activities, and events	4.73	1.00	5.00	0.58	0.34
LS6: Implementation of logistic centres	4.72	2.00	5.00	0.59	0.35
LS5: Utilisation of third-party logistics (3PL) services	4.71	1.00	5.00	0.60	0.36
LS11: Implementing Poka-Yoke (Error-prevention)	4.6	1.00	5.00	0.65	0.43
LS18: Use of Information Systems and Modelling Tools, such as BIM and 3D	4.69	3.00	5.00	0.52	0.27
LS4: The utilisation of Real-time visibility tools	4.33	1.00	5.00	1.30	1.70
LS10: Applying the Kaizen principle (Continuous Improvement)	4.31	1.00	5.00	1.31	1.71
LS2: Implementing the Last Planner System (LPS)	4.31	1.00	5.00	1.29	1.68
LS8: Utilising project management tools and procedures	4.29	1.00	5.00	1.30	1.71
LS14: Applying the 5S Methodology	4.28	1.00	5.00	1.26	1.60
LS1: Implementing the Kanban system	4.27	1.00	5.00	1.26	1.59
LS7: Applying lean design principles in designing construction projects	4.25	1.00	5.00	1.27	1.61
LS3: Implementing just-in-time (JIT)	4.24	1.00	5.00	1.328	1.76
LS15: Applying ABC (Pareto) analysis for inventory management.	4.23	1.00	5.00	1.29	1.68
LS9: Using value-stream mapping to assist in identifying and eliminating non-value-added activities	4.21	1.00	5.00	1.35	1.83
LS12: Optimised transportation routes	4.2	1.00	5.00	1.26	1.60
LS16: Implementing the Andon system	4.1	1.00	5.00	1.32	1.75
LS13: Conducting a regular on-site visit (Gemba Walks)	4.11	1.00	5.00	1.25	1.58

shows the frequency of the questionnaire responses regarding the 18 logistics solutions to be considered for enhancing the success/efficiency/effectiveness of the construction logistics process in the Middle East construction industry, using a Likert scale (1-not at all influential, 2-slightly influential, 3-somewhat influential, 4-very influential, 5-extremely influential). The factors are ranked according to their mean from highest to lowest. The table consists of the mean of all variables, the deviation from the mean, and the standard deviation.

4.9. Descriptive Statistics for Sustainable Factors

Table 8. Respondents’ satisfaction with factors that contribute to the sustainability of construction projects.

Factors	Min	Max	Mean	Std	Variance
SF6: Employee well-being	1.00	5.00	4.63	0.74	0.55
SF5: Waste reduction	1.00	5.00	4.61	0.66	0.43
SF7: Enhancing technology adoption	1.00	5.00	4.57	0.74	0.55
SF2: Greenhouse gas emissions	2.00	5.00	4.55	0.68	0.47
SF3: Total cost of completing a project	1.00	5.00	4.53	0.70	0.49
SF4: Resource efficiency	2.00	5.00	4.52	0.68	0.46
SF1: Labour productivity	1.00	5.00	4.50	0.69	0.48

shows the frequency of the questionnaire responses regarding the seven factors that contribute to the sustainability of construction logistics processes, using a Likert scale (Not at all, Slightly, Somewhat, Very, Extremely). The factors are ranked according to their mean from highest to lowest. The table consists of the mean of all variables, the deviation from the mean, and the standard deviation.

4.10. The Validity of the Survey Instrument

The survey instrument is examined for validity in this section through confirmatory factor analysis (CFA). A CFA is regarded as a reliable technique that is employed to measure the one-dimensionality of a set of objects [102]. The objective of conducting CFA in this situation is to validate the number of items that comprise the construct [factor] and evaluate the correlation between the items and their corresponding factor [119]. To perform CFA, researchers must have a clear understanding of (a) the total number of factors, (b) the variables that represent the factor, and (c) the factors that are connected. Within CFA, it is possible to test whether the collected data represents the theoretical model by examining the measurement model. CFA can be used to estimate different fit models until the best-fit model is obtained. The initial stage of CFA involves developing a theoretical model (hypothesis) for measuring latent variables. The fitted model will be statistically tested using the available data as the next step. To assess whether the model fits the observed data, the Chi-square χ² test is a significant test. The null hypothesis is tested against the alternative hypothesis of a significant difference between the observed data and the predicted data. The significance level (usually p = 5%) is set to obtain χ² to assess whether the null hypothesis of no difference can be rejected by examining this difference. The null hypothesis is not rejected if the probability is higher than 0.05 [44]. A good fit model can be concluded when the p-value exceeds the level of significance. The Chi-square test has a flaw that stems from its high sensitivity to sample size. Increasing the sample size makes it harder to fit a model in CFA because it increases the likelihood of rejecting the null hypothesis.

RMSEA (root mean square error of approximation) is an alternative, and it doesn’t rely on the sample size during the calculation. The RMSEA index was proposed by [123] to evaluate the probability of obtaining an RMSEA value lower than 0.08. If the probability is higher than 0.05, the model displays a good fit, i.e., p (RMSEA < 0.08).

The Tucker–Lewis Index (TLI), introduced by Tucker and Lewis in 1973, and the comparative fit index (CFI), introduced by Bentler in 1990, are the most frequently utilised tools for evaluating the improved fitted model in the baseline comparison. The proposed model is compared to a baseline model’s fit criteria to accomplish this. TLI and CFI values fall within a range of zero and one. If the value approaches 0.90 then the model is an adequate fit model and if the value is above 0.95 then the model is a very well-fit model [102]

4.11. Results of Confirmatory Factor Analysis (CFA)

4.11.1. Results of One-Dimensionality, Convergent Validity, and Discriminant Validity of Research Concept

The model depicted in Figure 8 provides a robust assessment of the relationships among logistics challenges, solutions, CSFs, and sustainability. The calculated variables and model fit indices indicate strong alignment with industry data. The key fit statistics are as follows: Chi2 = 4425.177; df = 1575; Chi2/df = 2.81 (<5), and the p-value is 0.00 (<0.05). Chi2/df, also known as the Chi-square/degrees of freedom ratio, evaluates overall model fit by comparing the discrepancy between observed and predicted covariance matrices; a value below 5 indicates an acceptable fit. Additional fit indexes demonstrate compatibility: TLI = 0.91 (>0.90), CFI = 0.92 (>0.90), and RMSEA = 0.06 (<0.08). RMSEA, or root mean square error of approximation, measures the discrepancy per degree of freedom, with values below 0.08 indicating a good fit and closer to 0.05 signifying an excellent fit. The comparative fit index (CFI) compares the target model to a baseline model, accounting for sample size, where values above 0.90 suggest a satisfactory fit, and those above 0.95 indicate an excellent fit. Similarly, the Tucker–Lewis index (TLI) evaluates model fit relative to a null model, penalising complexity, with values above 0.90 representing a good fit and values nearing 1.0 reflecting an ideal fit. These values confirm that the saturated model fits well with the observed data, providing a strong basis for the analysis.

Once the model fit has been confirmed based on the observed data, the next step is to check if every item measured the constructs, which includes logistics challenges, logistics solutions, critical success factors, and sustainability factors. First, the logistics challenges construct showed significant estimated factor loading for each item with p-values below 0.05. Thus, it can be concluded that the survey items have a statistical significance when it comes to measuring logistics challenges. Furthermore, the standardised coefficients exceeding 0.5 indicate that all items have high loadings. Second, the logistics solution construct showed significant estimated factor loading for each item with p-values below 0.05. Thus, it can be concluded that the survey items have a statistical significance when it comes to measuring logistics solutions. Furthermore, the standardised coefficients for most constructs exceeding 0.5 indicate high loadings. Third, the critical success factors construct showed significant estimated factor loading for each item with p-values below 0.05. Thus, it can be concluded that the survey items have a statistical significance when it comes to measuring critical success factors. Furthermore, the standardised coefficients exceeding 0.5 indicate that all items have high loadings. Finally, the sustainable factors construct showed significant estimated factor loading for each item with p-values below 0.05. Thus, it can be concluded that the survey items have a statistical significance when it comes to measuring sustainable factors. Furthermore, the standardised coefficients exceeding 0.5 indicate that all items have high loadings.

Table 9. The factor loading (Path coefficient) for each item along with the p-value for every construct.

Item		Construct	Estimate	S.E.	C.R.
CHL1	←	CHL	1.000
CHL1	←	CHL	0.888	0.034	30.005
CHL2	←	CHL	0.915	0.036	31.187
CHL3	←	CHL	0.928	0.035	30.492
CHL4	←	CHL	0.921	0.034	30.245
CHL5	←	CHL	0.917	0.035	29.712
CHL6	←	CHL	0.911	0.034	30.480
CHL7	←	CHL	0.921	0.036	26.462
CHL8	←	CHL	0.868	0.041	26.024
CHL9	←	CHL	0.862	0.036	31.524
CHL10	←	CHL	0.932	0.034	30.636
CHL11	←	CHL	0.922	0.035	28.673
CHL12	←	CHL	0.899	0.037	29.765
CHL13	←	CHL	0.912	0.034	30.330
CHL14	←	CHL	0.919	0.034	32.321
CHL15	←	CHL	0.940	0.037	31.441
CHL16	←	CHL	0.931	0.033	32.180
CHL17	←	CHL	0.939	0.036	27.085
CHL18	←	CHL	0.901	0.033	30.835
CHL19	←	CHL	0.924	0.037	28.079
CHL20	←	CHL	0.923	0.037	29.043
CHL21	←	CHL	0.903	0.030	36.929
CHL22	←	CHL	0.948	0.037	29.825
LS1	←	LS	1.000
LS1	←	LS	0.909	0.032	32.528
LS2	←	LS	0.921	0.028	37.965
LS3	←	LS	0.912	0.030	35.666
LS4	←	LS	0.948	0.025	5.922
LS5	←	LS	0.282	0.025	4.905
LS6	←	LS	0.236	0.047	13.871
LS7	←	LS	0.585	0.047	14.792
LS8	←	LS	0.612	0.049	14.285
LS9	←	LS	0.598	0.047	15.564
LS10	←	LS	0.635	0.028	2.281
LS11	←	LS	0.112	0.034	28.467
LS12	←	LS	0.878	0.037	24.598
LS13	←	LS	0.824	0.033	29.407
LS14	←	LS	0.890	0.036	28.430
LS15	←	LS	0.893	0.038	25.506
LS16	←	LS	0.839	0.025	3.661
LS17	←	LS	0.178	0.023	2.377
CSF1	←	CSFs	0.890
CSF2	←	CSFs	0.879	0.034	27.275
CSF3	←	CSFs	0.904	0.035	29.089
CSF4	←	CSFs	0.926	0.033	30.887
CSF5	←	CSFs	0.903	0.032	28.964
CSF6	←	CSFs	0.782	0.034	21.468
CSF7	←	CSFs	0.903	0.032	29.024
CSF8	←	CSFs	0.905	0.034	29.154
CSF9	←	CSFs	0.857	0.035	25.757
CSF10	←	CSFs	0.834	0.034	24.318
CSF11	←	CSFs	0.899	0.033	28.724
SF1	←	SF	1.000
SF1	←	SF	0.762	0.060	15.975
SF2	←	SF	0.742	0.061	16.767
SF3	←	SF	0.771	0.062	15.491
SF4	←	SF	0.749	0.061	18.071
SF5	←	SF	0.893	0.071	8.620
SF6	←	SF	0.439	0.069	14.955

depicts the factor loading for each item along with the p-value.

Additionally based on the value provided in Table 9, the path coefficients in structural equation modelling (SEM) represent the strength and direction of relationships between latent variables and their indicators, as well as the causal links between latent variables. These coefficients are crucial for understanding how well the model explains the relationships between constructs, such as logistics challenges (CHL), logistics solutions (LS), critical success factors (CSFs), and sustainability factors (SF), in this study. The path coefficients’ values, which range from 0.112 to 1.000, provide insight into the relative strength of each variable’s impact within the model. Higher coefficients (e.g., CHL15 = 0.940, CHL22 = 0.948) suggest that these indicators are highly influential in explaining the latent variable of logistics challenges (CHL), demonstrating their significant contribution. On the other hand, lower path coefficients, such as LS5 = 0.282 or LS17 = 0.178, imply that these indicators have a weaker relationship with their respective latent variables, suggesting they may have a reduced impact on the overall model.

The path coefficients also contribute to statistical validity by allowing to assessment of the strength and significance of the relationships between constructs. For example, if the path coefficient for a particular relationship (e.g., between logistics solutions (LS) and critical success factors (CSFs)) is high and statistically significant (based on t-values or p-values), it reinforces the argument that logistics solutions strongly influence the critical success factors. Conversely, low or non-significant path coefficients can suggest weaker or even non-existent relationships, signalling areas that may require further exploration or model refinement. In this case, the range of path coefficients between 0.178 and 0.948 reflects varying levels of influence, which is typical in SEM models and supports a nuanced understanding of how different variables interact.

Moreover, the path coefficients allow for an in-depth examination of the overall fit of the model. Statistically, a well-fitting model should show that the relationships between latent variables (e.g., logistics challenges, logistics solutions, success factors, and sustainability factors) are robust and reliable. In this model, higher path coefficients for variables like CHL15 (0.940) and CSF4 (0.926) indicate that these constructs are particularly influential, while lower path coefficients for variables like LS5 (0.282) suggest areas for improvement or further analysis. Thus, these coefficients not only help verify the statistical validity of the model but also provide insights into how to refine the model by emphasising stronger relationships and reconsidering weaker ones.

4.11.2. Results of Composite Reliability and Average Variance Extracted of Research Concepts

The results in

Table 10. Results of composite reliability and average variance extracted of research concepts.

Research Concepts	Code	# of Observed Variables	Composite Reliability	Convergent Validity (AVE) to Be 0.5 and Greater
Logistics Challenges	CHL	23	0.9	0.83
Logistics solutions	LS	18	0.8	0.51
Critical success factors	CSFs	11	0.9	0.77
Sustainable factors	SF	7	0.82	0.54

confirm that all constructs meet the threshold requirements for composite reliability (CR) and average variance extracted (AVE), which are essential for validating the measurement model in SEM. A CR value of 0.7 or higher indicates adequate internal consistency, ensuring that the items measuring each construct reliably reflect the underlying latent variable. Similarly, an AVE value of 0.5 or above confirms sufficient convergent validity, demonstrating that the constructs capture a significant portion of the variance in their indicators compared to measurement error. Meeting these thresholds establishes the robustness of the measurement model and validates the reliability of the constructs used in the analysis.

These results are particularly significant because they form the foundation for interpreting the structural relationships between latent variables. By ensuring the constructs are reliable and valid, this study can confidently proceed with analysing the interplay among logistics challenges, solutions, success factors, and sustainability factors in the construction industry. Moreover, meeting these requirements enhances the credibility of the findings and supports their applicability to the Middle East construction context. To strengthen this discussion, future iterations could include the specific CR and AVE values for each construct, providing greater transparency and reinforcing the rigour of the SEM framework.

4.12. Results of Model Research Hypotheses Testing

Amos Graphics software version 21.0.0 handles the processing of the structural equation modelling (SEM). The SEM model depicted in Figure 9 examines the interrelationships among four latent variables: logistics challenges, logistics solutions, critical success factors, and sustainability factors. Each of these latent variables is represented by several observed variables, as shown in the measurement model. For instance, logistics challenges are measured through indicators, such as material delays, high transportation costs, and inadequate infrastructure, while logistics solutions are assessed through practices, like just-in-time (JIT) implementation, Kanban systems, and utilisation of real-time visibility tools. The structural model further hypothesises causal pathways, such as the impact of critical success factors on reducing logistics challenges and enhancing sustainability factors.

4.12.1. Results for Testing of the Research Hypotheses

Testing the research hypotheses is carried out at a 5% significant level and the level of confidence is 95%.

Table 11. The research hypotheses.

The Hypotheses	Effect	p	Decision
H1.Logistics solutions have a direct positive effect on sustainability in the construction industry. (LS → SF) H1 0. Logistics solutions do not have a direct positive effect on sustainability in the construction industry (Null hypothesis)	0.516	0.034	Supported, and the null hypothesis rejected
H2.Critical success factors positively influence sustainability in the construction industry. (CSF → SF) H2 0. There is no influence of the critical success factors on sustainability in the construction industry (Null hypothesis).	0.487	0.02	Supported, and the null hypothesis rejected
H3.Logistics challenges adversely affect sustainability in the construction industry. H3 0.Logistics challenges do not affect sustainability in the construction industry (Null hypothesis).	−0.926	xxx	Supported, and the null hypothesis rejected
Interactions:
H4.There is an interaction between logistics solutions and critical success factors in the construction industry. H4 0.There is no interaction between logistics solutions and critical success factors in the construction industry (Null hypothesis).	0.948	xxx	Supported, and the null hypothesis rejected
H5.There is an interaction between logistics solutions and logistics challenges in the construction industry. H5 0. There is no interaction between logistics solutions and logistics challenges in the construction industry (Null hypothesis).	0.58	xxx	Supported, and the null hypothesis rejected
H6.There is an interaction between critical success factors and logistics challenges in the construction industry. H6 0.There is no interaction between critical success factors and logistics challenges in the construction industry (Null hypothesis).	0.404	xxx	Supported, and the null hypothesis rejected

shows the results of the hypotheses testing. This study proposes and tests six hypotheses through the estimation of bootstrapping. The hypotheses are either accepted or rejected based on the significance level (p values) and direction of the path (estimate coefficient values). Table 11 depicts the research hypothesis and the associated results.

As shown in

Table 12. Result of Direct path analysis.

			Estimate	S.E.	C.R.	Label
CSFs	←	LS	0.948	0.037	26.477	par_129
CHL	←	LS	0.580	0.050	10.800	par_130
CHL	←	CSFs	0.404	0.047	7.778	par_132
SF	←	LS	0.516	0.113	2.122	par_127
SF	←	CSFs	0.487	0.094	2.326	par_128
SF	←	CHL	−0.926	0.124	−3.733	par_131

, Logistics solutions have a direct positive effect on sustainability in the construction industry (0.51, p 0.03), Critical success factors positively influence sustainability in the construction industry (0.48, p 0.02) and logistics challenges adversely affect sustainability in the construction industry (−0.92, p 0.00). Thus, hypotheses H1 and H2 and H3 are accepted, and the associated null hypothesis were rejected (H1 0, H2 0, H3 0).

The results further reveal that there is an interaction between logistics solutions and critical success factors in the construction industry (0.94, p 0.00) and logistics challenges (0.60, p 0.000). Additionally, it has noted an interaction between critical success factors and logistics challenges in the construction industry (0.4, p 0.000). Therefore, hypotheses H4, H5, and H6 are accepted, and the associated null hypotheses were rejected (H4 0, H5 0, H6 0).

4.12.2. How to Utilise Logistics Solutions to Address Logistics Challenges

The Middle Eastern construction industry faces significant logistical challenges due to complex project requirements, geopolitical instability, and market-specific constraints. Addressing these issues necessitates tailored logistics solutions to enhance operational efficiency and sustainability. Structural equation modelling (SEM) demonstrates the efficacy of such solutions, with a notable path coefficient of 0.58 indicating their substantial impact on mitigating logistical challenges. This research elucidates several key strategies: the Kanban system, which visually organises resource flows to enhance planning and coordination, and the Last Planner System (LPS), fostering collaboration among stakeholders to improve logistics integration with project schedules. Additionally, just-in-time [JIT] logistics minimises waste and storage requirements, ensuring materials are delivered only when required, while real-time visibility tools, such as GPS and RFID, provide oversight, reducing delays and improving fleet management. Other solutions include outsourcing to third-party logistics (3PL) providers to manage transportation and distribution efficiently and centralising operations in logistics centres to streamline inventory management and reduce material waste. Techniques such as lean design principles and value-stream mapping (VSM) address inefficiencies by optimising processes and reducing redundancies. Continuous improvement strategies, such as the Kaizen principle, error-prevention measures, like Poka-Yoke, and methodologies, such as the 5S framework, enhance workplace organisation and resource utilisation. Advanced tools, including building information modelling (BIM), further integrate logistics into project planning, providing real-time updates and fostering stakeholder collaboration. Collectively, these solutions align logistical operations with sustainability objectives, addressing challenges, such as material waste, transportation inefficiencies, and poor coordination, thereby transforming construction logistics in the Middle East into a more streamlined and sustainable process.

4.12.3. How CSFs Mitigate Logistics Challenges

The construction industry in the Middle East encounters distinctive logistical challenges, including political instability, volatile material costs, and unexpected workforce shortages, necessitating the enhancement of critical success factors (CSFs). This research emphasises the significance of accurate demand forecasting, which enables firms to optimise resource allocation, mitigate material shortages, and improve supplier collaboration. Proper information flow addresses communication gaps and decision-making delays by ensuring seamless data sharing among stakeholders, while adherence to safety, environmental, and regulatory standards aids in preventing project interruptions and maintaining compliance across varying regional requirements. Effective risk management further mitigates disruptions caused by regional instability through contingency planning and the establishment of alternative suppliers and transportation networks. Efficient resource allocation optimises materials, labour, and equipment, addressing challenges such as scheduling delays and bottlenecks, particularly in areas with variable resource availability. Collaboration with suppliers enhances supply chain transparency, mitigating the impact of imprecise deliveries and quality deficiencies. Adequate training and skill development address logistical inefficiencies stemming from insufficient expertise by equipping personnel with specialised skills for inventory control and materials handling. Finally, strong commitment and support from top management ensure the prioritisation of logistics improvements, fostering coordination and resource allocation. Although CSFs demonstrate a moderate impact (path coefficient 0.4) on logistical challenges, their integration with robust external strategies can significantly enhance logistics efficiency in the region. These factors collectively provide a framework to address logistical issues in a volatile environment, ensuring improved project outcomes and resilience against disruptions.

5. Conclusions and Recommendations

The Middle Eastern construction industry faces substantial logistical inefficiencies that impede sustainability, necessitating a comprehensive and innovative approach to address these challenges. This research developed a practical framework by integrating 18 logistics solutions and 8 critical success factors (CSFs) to enhance sustainability outcomes. Using a mixed-methods methodology, this study combined insights from 29 semi-structured interviews and quantitative data from 422 survey responses collected across the UAE, Palestine, Saudi Arabia, and Jordan. The proposed framework was validated through structural equation modelling (SEM), elucidating key interrelationships between logistics challenges, solutions, CSFs, and sustainability factors. This study identified 23 logistics challenges grouped into six categories: planning and resource allocation, communication and coordination, material management, transportation, inventory and warehouse management, and reverse logistics. These challenges were linked to sustainability factors, such as labour productivity, greenhouse gas emissions, project costs, resource efficiency, waste reduction, employee well-being, and technology adoption. The SEM analysis demonstrated the significant negative impact of logistics challenges on sustainability, particularly in increasing waste, project costs, and greenhouse gas emissions. However, adopting the proposed logistics solutions and CSFs effectively mitigated these challenges. The analysis further revealed that logistics solutions and CSFs work synergistically, with solutions enabling the achievement of CSFs and leading to improved sustainability outcomes, including enhanced resource efficiency, waste reduction, increased labour productivity, and improved employee well-being. To guide industry practice and policymaking, actionable recommendations are proposed for key stakeholders:

• Enterprise Managers: Prioritise implementing logistics solutions, such as real-time visualisation tools, lean construction principles, and just-in-time systems, to improve coordination, resource allocation, and material flow. Focus on achieving CSFs like proper information flow and effective risk management to address logistical inefficiencies.
• Policy Makers: Design policies that promote the adoption of green logistics technologies, such as tax incentives for firms adopting eco-friendly practices, and establish regulatory frameworks mandating sustainability reporting in construction projects. Support industry-wide adoption of frameworks like Green Logistics and TIMBER through funding and public-private collaborations.
• Industry Associations: Facilitate knowledge sharing and capacity building by organising workshops, certification programs, and forums to disseminate best practices in logistics management. Advocate for the integration of advanced technologies, such as building information modelling (BIM), to enable real-time collaboration among stakeholders.
• Researchers: Build on this framework to develop phased implementation strategies and test the feasibility of solutions in diverse operational contexts across the Middle East.

By addressing the unique challenges of the region, this study provides a roadmap for systematically improving logistics processes while advancing sustainability. Its contributions lie in integrating theoretical and practical insights, offering actionable guidance for industry practitioners, policymakers, and researchers to achieve sustainability goals while maintaining competitiveness in the construction sector.

5.1. Contribution

This research made the following contributions to both academics and practitioners.

• This research fills a gap in the literature by comprehensively presenting logistics challenges affecting the construction industry along with the logistics functions to enhance sustainability.
• To the best of our knowledge, this research is the first research to examine the role of logistics solutions and CSFs on addressing logistics challenges to enhance the sustainability of construction logistics.
• This research integrates existing logistics frameworks and theories to introduce new practical frameworks that link logistics challenges, logistics solutions, and CSFs with sustainability in the construction industry. This research proposes a new way of evaluating sustainability for the built environment considering logistics aspects.
• This research demonstrates the successful implementation of sustainable logistics solutions and CSFs in construction projects. Consequently, it identifies and documents best practices and guidelines for implementing sustainable logistics in construction, which can be adopted by industry practitioners.
• Construction stakeholders will gain further guidance and perceptions on understanding, identifying, and then assessing their construction logistics process within the Middle East construction industry.
• By using the contribution of this research as a benchmark for Middle East construction, academics will have a significant opportunity to increase their research in this field, which is still undervalued by most developing countries.
• By extending their research in logistics solutions and CSFs within construction fields, developing countries can assess and develop their current situation, as this research encourages.

5.2. Limitations

Limitations regarding this research are presented as follows:

To manage production systems; [129] defines three generic actions: design, operation, control, and improvement. In construction logistics and supply chain management, similar actions are observed. The improvement aspects of logistics in the construction industry are the focus of this research in its inherent proposition. This study does not directly address operation and control aspects.

This research conducted a review of the literature based on the trusted scientific English database as the researcher could not be able to figure out if there is any other database from different languages that could be considered for further information. Moreover, this research considers the publication from 2000 as research regarding logistics and supply chain management in construction was developed more recently, especially from 2000 onwards. On the other hand, the synthesis of the literature findings from diverse studies with different methodologies, contexts, and outcomes can be complex and may associated with subjective judgment.

This research primarily collected data from main contractors within the Middle Eastern private sector, as the researcher faced significant challenges in accessing governmental sectors. While the private sector plays a dominant role in implementing major construction projects, the exclusion of governmental perspectives may limit the comprehensiveness of the findings. Additionally, data collection focused on contractors’ staff, who are central to this study’s objective of enhancing performance. However, the perspectives of other stakeholders, such as consultants and clients, were not included, which could have provided a more holistic understanding of the logistics challenges and solutions. Quantitative data was gathered through the in-person distribution of questionnaires across key Middle Eastern countries, including Saudi Arabia, the UAE, Jordan, and Palestine. This method was chosen to ensure reliable responses, as previous online distribution attempts yielded inconsistent results. However, the exclusion of other countries in the region, such as Syria and Lebanon, due to their unstable conditions, limits the geographic scope of this study. This restriction may affect the generalisability of the results to the broader Middle Eastern construction industry, especially in regions facing unique logistical or political challenges. The limitations in sample diversity, geographic coverage, and stakeholder inclusion highlight the need for caution when extrapolating the findings. Future studies could address these gaps by incorporating data from governmental sectors, a broader range of stakeholders, and additional countries to enhance the reliability and applicability of the results.

Directions for Future Research

To extend the current findings and overcome the limitations identified in this study, several avenues for future research are recommended:

• Inclusion of Governmental Perspectives: Future studies should seek to include data from governmental sectors to provide a more comprehensive understanding of logistics challenges and solutions. Collaborating with public agencies or leveraging official datasets could help bridge this gap, offering insights into how public-private partnerships influence construction logistics and sustainability.
• Broader Stakeholder Engagement: While this study focused on contractors, future research could include perspectives from consultants, clients, suppliers, and other stakeholders involved in construction projects. This multi-stakeholder approach would offer a more holistic view of the challenges and opportunities in achieving sustainable logistics.
• Expanded Geographic Scope: To enhance the generalisability of findings, future research should incorporate data from additional Middle Eastern countries, especially those currently excluded due to instability (e.g., Syria, Lebanon). Comparative studies between stable and unstable regions could provide valuable insights into how political and economic conditions influence logistics practices.
• Longitudinal Studies: A longitudinal approach could examine how the adoption of proposed logistics solutions evolves over time and their long-term impact on sustainability. This could provide a deeper understanding of the dynamic nature of logistics challenges and the effectiveness of solutions in diverse contexts.
• Integration of Advanced Technologies: Future research could explore the role of emerging technologies, such as artificial intelligence (AI), blockchain, and the Internet of things (IoT), in optimising construction logistics. Investigating the barriers to technology adoption, such as cost and technical expertise, could help design actionable strategies for implementation.
• Analysis of Implementation Challenges: While this study proposed logistics solutions, future research could focus on identifying and addressing practical implementation challenges, such as cost constraints, technical capability gaps, and organisational resistance. Developing phased implementation strategies tailored to the Middle Eastern context would enhance the feasibility of these solutions.
• Cross-Industry Comparisons: Future studies could compare logistics practices in the construction industry with those in other sectors, such as manufacturing or retail, to identify transferable strategies and innovations that could improve construction logistics.
• Policy Framework Development: Research could investigate the role of policy interventions in promoting sustainable logistics. This includes evaluating the effectiveness of existing regulations and identifying new policies to incentivise the adoption of green logistics practices across the region.