Bridging Generations: Key Determinants of Intergenerational Knowledge Transfer from Older to Younger Employees in Green Building Projects

Abstract

Despite the growing importance of green building projects, limited research has explored the factors influencing intergenerational knowledge transfer (IGKT) in this context. As green building projects are increasingly characterized by high environmental standards, technological complexity, and interdisciplinary collaboration, effective knowledge transfer from older to younger employees becomes crucial for ensuring the success and sustainability of these projects. This study addresses this gap by systematically examining the key factors influencing IGKT in green building projects, applying an integrated Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Interpretive Structural Modeling (ISM) methodology. Firstly, twelve factors were identified across five dimensions: transfer subjects, inter-subject relationships, transfer objects, transfer channels, and transfer context. Based on expert input, a direct influence matrix was constructed, and centrality and cause degrees were calculated to distinguish causal and result factors. Subsequently, the ISM method was employed to classify the key factors hierarchically and develop a multi-level structural model of their interaction paths. Results show that organizational support climate ranked highest in both centrality and influence, while digital transformation capacity emerged as a key driver in green project environments. Surface-level factors (e.g., knowledge absorption and transmission capability) were highly susceptible; intermediate factors (e.g., motivation, knowledge distance) acted as bridges; and deep-level factors (e.g., knowledge complexity and embeddedness), though lower in centrality, posed long-term structural constraints. This study provides valuable insights for enhancing IGKT and fostering effective cross-generational collaboration, which is essential for advancing sustainable practices in the green building sector.

1. Introduction

Knowledge creation and transfer have become essential drivers of competitiveness in the modern construction industry [1,2]. Green building projects, which integrate environmentally responsible, resource-efficient and health-oriented strategies throughout the building life cycle, have gained prominence as the sector responds to increasing expectations for sustainability, energy efficiency and environmental stewardship [3]. These projects typically involve sophisticated design requirements, specialized technologies, and interdisciplinary coordination that span architecture, engineering, environmental science and digital construction [4,5,6]. Such characteristics make accumulated experiential knowledge, particularly tacit knowledge relating to material choices, sustainability trade-offs, environmental certification procedures and long-term performance considerations, indispensable for successful project delivery. Ensuring that this knowledge is effectively transferred within projects is therefore crucial for maintaining organizational capability and achieving high-performance outcomes in green building environments.

Intergenerational knowledge transfer (IGKT) refers to the exchange of knowledge, skills and professional experience between employees of different age groups, and in principle it can occur in both directions [7,8]. In green building projects, the direction of knowledge flow is often more complex than in traditional sectors because younger employees are typically more familiar with emerging digital and sustainability technologies such as BIM, smart energy systems and ecological modeling software. At the same time, older employees tend to possess deeply embedded tacit knowledge such as sustainability-oriented judgment, contextual decision experience and long-cycle project implementation insights acquired through repeated exposure to real-world environmental challenges [9,10,11]. Thus, bidirectional or reciprocal learning is certainly possible and does occur in practice. However, this study deliberately focuses on the downward transfer of sustainability-related tacit knowledge from older to younger employees for two reasons. First, organizations worldwide face an accelerating retirement trend, and the potential loss of accumulated sustainability expertise has been identified as a major risk for maintaining green building quality and long-term capability development [12,13]. Second, tacit sustainability knowledge is significantly harder to codify or replace compared to digital skills, making its effective downward transmission a critical challenge for project teams. By clarifying this analytical boundary, the study does not deny the existence or importance of upward or lateral knowledge flows; rather, it isolates a core mechanism of experience-based sustainability knowledge continuity that is most vulnerable to disruption in green building environments and therefore requires focused analytical attention.

In green building project environments, IGKT is shaped by a combination of individual, knowledge-related and contextual factors that jointly affect its effectiveness. Although project teams often engage in horizontal collaboration and cross-disciplinary learning to integrate architectural, engineering and environmental expertise, the intergenerational transmission of experiential sustainability knowledge forms a distinct process that warrants focused examination. Differences in motivation and capability between generations frequently impede this process. Senior employees may be reluctant to share knowledge due to limited incentives or perceived knowledge loss, while younger employees may lack the experiential grounding needed to interpret such information [14,15]. Green building knowledge adds further complexity because much of it is tacit, context-dependent and difficult to codify, including passive energy strategies, ecological site planning, green material integration and environmental certification procedures. These characteristics increase the risk of distortion or incomplete transmission [16,17,18]. Interpersonal distance, including differences in trust, communication habits and cognitive frames, also influences knowledge absorption and interpretation [19,20]. Project-level cultural conditions further shape IGKT outcomes, as green building projects rely on collaborative climates that encourage knowledge sharing and support long-term learning [21,22,23]. Therefore, to improve the effectiveness of IGKT, green building projects must coordinate and optimize multiple dimensions to achieve efficient knowledge inheritance and application.

Drawing on the theory of psychosocial development, Berk [24] distinguishes early, middle and late adulthood, with guiding younger generations identified as a key developmental task in middle adulthood. Building on this perspective, organizational research commonly categorizes employees into older and younger generational groups, typically treating those above 40 as knowledge holders and those 40 or below as recipients of experience-based knowledge [21,25]. Consequently, IGKT in workplaces is often examined as a process in which senior employees transmit accumulated expertise to colleagues at least a decade younger. Although “generation” can theoretically be defined using multiple dimensions such as career stage or digital cognition (for example, digital natives versus digital immigrants), age remains the most widely used and empirically verifiable criterion in organizational and construction research. In project-based environments, age strongly correlates with accumulated tacit knowledge, years of field exposure, role seniority and experience with long-cycle sustainability decision-making. Therefore, for the purposes of this study, age serves as a practical and conceptually consistent proxy for generational position. At the same time, this study acknowledges that generational differences may also manifest in digital proficiencies and career trajectories, and these characteristics are reflected indirectly through the identified factors (e.g., knowledge distance, digital transformation capability).

Although IGKT has been studied in high-tech, manufacturing and healthcare sectors, research explicitly addressing green building projects remains limited [1,4,26]. The green building sector possesses several distinguishing features, including interdisciplinary integration, performance-driven design, long-term lifecycle evaluation and dependence on tacit sustainability knowledge. These characteristics not only increase the complexity of knowledge creation but also intensify the need for structured intergenerational learning. Existing studies have explored factors such as organizational culture, trust, employee attitudes and technological tools [2,27,28]. However, most rely on qualitative interviews or single-method surveys and provide limited insight into how these factors interact to shape IGKT outcomes in sustainability-oriented project environments. Given these gaps, there is a clear need for a structured analytical approach that not only identifies influential factors but also captures their interaction mechanisms within the unique context of green building projects. Unlike traditional knowledge-transfer models, which focus primarily on individual or organizational dimensions, this study proposes a five-dimensional framework (“subject–relationship–object–channel–context”) that reflects the distinctive characteristics of green, intergenerational and project-based work settings. This framework integrates individual capabilities and motivations, generational relationship dynamics, sustainability knowledge attributes, multi-channel communication pathways and project-specific contextual enablers. Such a holistic structure provides a more comprehensive lens for examining how sustainability-related knowledge flows across generations under conditions of high technical uncertainty, temporary team arrangements and strong performance accountability.

To operationalize this framework, the decision-making trial and evaluation laboratory (DEMATEL) method is adopted to determine the causal influence among factors and distinguish those that act as primary drivers from those that are more dependent [29,30]. Interpretive structural modeling (ISM) is further applied to organize the identified factors into a hierarchical structure, revealing the underlying pathways through which foundational conditions, intermediate mechanisms and surface-level manifestations jointly influence IGKT [31,32]. By integrating these methods, the study moves beyond traditional linear or single-level IGKT models and develops a multi-level analytical structure tailored to the complexities of green construction. The findings contribute theoretically by clarifying how the interplay among five dimensions shapes IGKT in green building contexts, and contribute practically by informing organizations on how to strengthen knowledge continuity and better support the next generation of green building professionals.

The structure is organized as follows. Section 2 introduces the theoretical foundations of intergenerational knowledge transfer and outlines the identification of influencing factors in green building contexts. Section 3 presents the research design and details the integrated DEMATEL-ISM methodology. Section 4 reports the empirical findings, including the causal relationships and hierarchical structure of the identified factors. Section 5 discusses the theoretical and practical implications of the results. Section 6 provides the conclusions, highlights the study’s limitations and suggests avenues for future research.

2. Literature Review

To provide a coherent foundation for the empirical analysis, this section reviews the existing body of knowledge related to IGKT and its relevance to green building project environments. The literature review is structured into three parts: first, an overview of IGKT in organizational settings; second, a synthesis of studies examining knowledge transfer within green building projects; and third, a discussion of the key factor dimensions that influence IGKT based on established communication and knowledge-transfer theories. This structure ensures that the conceptual background of the study is fully articulated before introducing the analytical framework adopted in later sections.

2.1. Intergenerational Knowledge Transfer in Organizations

Knowledge transfer refers to the dual knowledge exchange between knowledge providers and receivers, which covers the provision, acquisition, and application of knowledge [33]. Based on the generational differences between knowledge providers and receivers, knowledge transfer can be divided into intragenerational knowledge transfer (i.e., horizontal knowledge transfer between employees of the same generation) and IGKT (i.e., vertical knowledge transfer between employees of different generations) [34]. The initial research on IGKT was concentrated in the fields of sociology and psychology, focusing on knowledge transfer between different generations. Cumming and Henry [35] pointed out the importance of knowledge and skills transfer in intergenerational relationships, arguing that the older generation can help the younger generation adapt to social changes by guiding and imparting experience. Entering the 21st century, research on IGKT has gradually expanded to the fields of organizational behavior and management, and scholars have begun to pay attention to the sources, concepts, processes, and results of IGKT. For example, Beazley et al. [36] investigated how organizations retain their intellectual assets in the face of knowledge losses caused by personnel turnover such as downsizing, layoffs, and the retirement of baby boomers. Harvey [7] conducted a systematic analysis of IGKT strategies within knowledge-intensive organizations and proposed two models of IGKT: the source-recipient and mutual exchange models. Recently, with the advancement of technology and changes in organizational environments, research on IGKT has further deepened. Scholars have begun to focus on digital tools [37], antecedents and outcomes of knowledge transfer [11,28], and IGKT in different organizational contexts [9,10]. However, existing IGKT research has been developed primarily in non-construction sectors, leaving limited understanding of how IGKT operates within the construction industry, particularly in green building project environments.

2.2. Knowledge Transfer and Intergenerational Knowledge Transfer in Green Building Projects

Green building projects encompass expertise and technologies from diverse disciplines such as building design, energy systems, and ecological science. In recent years, certain researchers have examined how knowledge is disseminated within green building projects. For instance, Ugolini et al. [38] investigated the processes of knowledge exchange among various parties in ecological infrastructure endeavors and assessed the strengths and weaknesses of distinct cooperation approaches. Perkins and Perkins et al. [39] collected experiential knowledge from field experts involved in construction activities and organized it by category to distribute it to builders and planners. Zou and Alam [40] utilized a green building example to formulate an approach for involving stakeholders to address discrepancies in energy efficiency outcomes. Qiang et al. [41] examined how cooperative relationships develop and transform within green building projects, and recommended strategies to strengthen the flow of expertise and information among participants, aiming to boost the effectiveness of sustainable development efforts. Zhou et al. [42] explored the key factors affecting knowledge transfer among stakeholders in green building projects and outlined some combination strategies for different categories by using a configuration analysis approach. As the research deepens, some scholars have begun to pay attention to the impact of generational differences on knowledge transfer in green building projects. Sanaei et al. [43] divided employees in engineering organizations into four generations based on age and proposed that managers need to determine how to cross generational boundaries to increase organizational knowledge transfer. The results showed that the employees’ generational attributes affect the way knowledge is shared among employees (e.g., meetings, personal discussions, emails, instant messaging, etc.). Crespo Sánchez et al. [44] designed an IGKT model to educate students about energy-saving renovations of residential buildings and spread this knowledge to their families.

Despite these contributions, existing studies seldom examine IGKT in green building projects at a system-wide or structural level. Most research discusses knowledge transfer conceptually or through isolated case examples, leaving unclear how the multiple factors influencing IGKT jointly operate in sustainability-oriented project environments. Green building projects involve complex configurations of technological expertise, interdisciplinary collaboration and evolving regulatory requirements, making intergenerational learning particularly reliant on the interplay among individual, relational and contextual conditions. However, prior studies rarely identify such factors comprehensively or analyze their causal relationships. This lack of methodological depth limits current understanding of how experience-based sustainability knowledge is transmitted from older to younger employees and where the most critical leverage points lie. These gaps highlight the need for a structured analytical approach to map the determinants of IGKT in green building projects and to reveal the hierarchical pathways through which they influence knowledge transfer outcomes.

2.3. Factors Affecting Intergenerational Knowledge Transfer in Green Building Projects

As the research on IGKT deepens, scholars begin to focus on the key elements of IGKT. The “5W” model proposed by Lasswell [45] is a classic theoretical framework in the communication field, namely who, what, in which channel, to whom, and with what effect. This model constructs a linear model of the communication process through five basic elements. Under the guidance of communication theory, scholars have proposed the elements that affect knowledge transfer (including subject, object, channel, and context), laying the foundation for subsequent research [46,47]. Whereafter, Joshi et al. [48] incorporated the interaction between the sender and receiver of knowledge as a factor dimension. Combined with earlier research, researchers later categorized the factors impacting knowledge transfer into five main dimensions: subject, relationship, object, channel, and context [49,50]. These five dimensions, while developed in broader knowledge-transfer studies, offer a comprehensive lens through which the determinants of IGKT can be systematically organized.

To ensure that the establishment of the five-dimensional framework is grounded in a rigorous and transparent literature base, a structured review was conducted prior to identifying the influencing factors. Relevant studies were searched in Web of Science, Scopus and Google Scholar using combined keyword groups that captured both the generational and project-based attributes of the research domain. The search strategy was based on two groups of keywords that had to appear simultaneously in each query. The first group captured intergenerational knowledge processes and included terms such as “intergenerational/cross-generational knowledge/expertise/skill/experience transfer/sharing/exchange/transmission/flow/communication”, or “knowledge transfer/sharing/exchange/transmission/flow across generations”. The second group captured the project-based and construction-related context of this study and included terms such as “construction industry”, “building projects”, “project-based organizations”, “sustainable construction”, and “green building projects”. During the literature search, these two categories of keywords were combined using logical AND to ensure that selected studies addressed both intergenerational knowledge processes and construction or green building project environments.

Peer-reviewed studies were included if they satisfied three criteria: (1) they examined knowledge transfer, sharing or exchange involving different generations or age groups; (2) they were situated within project-based, engineering or construction-related organizational settings, including but not limited to green building projects; and (3) they provided conceptual, empirical or contextual insights relevant to the mechanisms, determinants or barriers of generational knowledge flows. Studies not meeting these conditions or lacking clear relevance to intergenerational exchange in construction environments were excluded. Across the screened literature, recurring analytical emphases were identified on individual attributes, relational dynamics, characteristics of the transferred knowledge, communication channels and contextual conditions, echoing the classical “5W” communication logic. These consistent patterns across diverse studies provide theoretical and empirical justification for structuring the analysis around the five dimensions of subject, relationship, object, channel and context. Accordingly, the following subsections elaborate on the core concepts and representative factors within each dimension.

2.3.1. Subject Factors

In the framework of knowledge transfer elements, the characteristics of the subjects involved are central to IGKT, with motivation and ability forming the core determinants. According to Self-Determination Theory (SDT), motivation can be autonomous or controlled, and these forms influence individuals’ willingness to participate in knowledge transfer [51]. Autonomous motivation reflects intrinsic interest, values or self-endorsed goals [52,53]. In IGKT, senior employees may share sustainability-related knowledge because they value mentorship or feel responsible for supporting younger colleagues. Younger employees who show interest in green construction also tend to take the initiative to seek guidance, improving the effectiveness of the transfer process [15,54]. Autonomous motivation enhances persistence and depth in knowledge exchange [55,56]. Controlled motivation, in contrast, arises from external demands or incentives [14]. In green building projects, it may come from certification documentation, managerial requirements or project procedures. While such mechanisms help ensure basic knowledge capture [57,58], they may not be sufficient to elicit the transmission of experience-based sustainability knowledge unless senior staff feel adequately supported or recognized.

Recent studies also emphasize that senior employees’ willingness to transfer knowledge depends on their perceived organizational value, late-career expectations and the availability of appropriate incentives [9,10]. Experienced practitioners are generally more willing to mentor younger colleagues when their expertise in sustainable practices is acknowledged and when mechanisms such as recognition, workload adjustments or dedicated mentoring time are provided [9,10]. Without such support, knowledge providers may hesitate to invest additional effort, particularly when project workloads are high or retirement is approaching. This willingness factor thus represents an important subject-related determinant of IGKT.

Beyond motivation, knowledge transfer also depends on the ability of participants to deliver and absorb knowledge. Knowledge transmission capacity refers to how effectively senior staff can extract, articulate, and share what they know [59]. In green construction, this might involve explaining how to operate high-performance HVAC systems or select low-emission materials. Strong transmission capacity helps ensure that crucial know-how is not lost [60]. On the receiving side, knowledge absorption capacity is about how well junior staff can understand, internalize, and apply new knowledge [61]. Since green projects often involve time-sensitive and technically complex tasks, young professionals with strong absorption capacity, such as the ability to interpret energy simulation data or adapt to new sustainable technologies, are better able to apply knowledge quickly and accurately. This leads to more efficient and effective transfer [11,62].

2.3.2. Relationship Factors

Szulanski [33] emphasized that the relationship between the sender and receiver of knowledge plays a vital role in effective knowledge transfer. The nature of the relationship between senior and junior employees forms a foundational condition for IGKT in project environments. To avoid ambiguity in how relationship factors are conceptualized, this study focuses specifically on professional relationships within project organizations rather than personal ties such as family or friendship. Intergenerational exchanges in green building projects primarily occur through formal or semi-formal workplace interactions, including supervisor-subordinate relationships, cross-disciplinary collaboration and peer exchanges within project teams. These professional ties can be examined through established relational dimensions such as trust, communication frequency, perceived approachability and hierarchical distance, ensuring that the concept of “relationship factors” is analytically grounded rather than broadly or subjectively defined.

In green building projects, both “knowledge distance” and “relational distance” significantly influence IGKT effectiveness. Knowledge distance refers to the differences between senior and junior employees in their knowledge base, practical experience, or awareness of sustainability concepts. This includes both technical knowledge distance (e.g., in renewable energy systems) and managerial knowledge distance (e.g., green construction workflows) [63,64]. In the fast-evolving domain of green buildings, senior employees’ expertise may lie in established energy-saving retrofits, whereas junior employees often possess training in emerging technologies like green certification standards, creating a professional disconnect [8,65]. This disconnect can lead to a “knowledge gap,” where junior employees struggle to fully understand or apply green construction know-how shared by senior staff, thereby diminishing the effectiveness of IGKT [64]. In time- and sustainability-driven project settings, this gap is amplified by the transient nature of project teams, where veteran site managers must quickly pass on key know-how such as sustainable material selection or low-carbon implementation practices to newly assigned engineers. Any miscommunication risks resource waste or compliance issues [66].

Relational distance refers to gaps in organizational hierarchy, social ties, and emotional connection between generations [67,68]. When such distance is large, generational value differences are often more pronounced. Senior employees may question the capabilities or commitment of newcomers to green building values and thus become reluctant to share core environmental insights. At the same time, younger employees may hesitate to ask for guidance due to the authority or perceived complexity of experienced staff, especially concerning sustainable technologies or green compliance processes [69]. This generational disconnect further obstructs the effective transfer and implementation of key sustainability practices within green building projects.

2.3.3. Object Factors

The object dimension concerns the characteristics of knowledge and how they influence IGKT. Among them, knowledge tacitness, complexity, and embeddedness are especially critical. In green building projects, tacit knowledge often takes the form of senior employees’ hands-on experience with sustainable materials, energy-saving technologies, or site-specific environmental strategies, knowledge that cannot be fully captured in manuals or guidelines [16,70]. Tacit knowledge is hard to express through language or text, and must often be conveyed through observation, mentorship, or shared work. Junior staff, lacking field experience, may struggle to grasp these insights if they rely solely on written materials, leading to knowledge gaps in implementing green practices [70,71]. Knowledge complexity refers to the diversity, interdependence, and evolving nature of knowledge. In green building contexts, complex knowledge may involve interdisciplinary integration, such as coordinating structural design with renewable energy systems or achieving LEED certification, which requires holistic understanding and systems thinking. Young employees may find it challenging to quickly comprehend this complexity due to limited exposure or technical depth [17,18]. Knowledge embeddedness highlights how knowledge is tied to specific contexts like team routines, organizational culture, or site workflows. In green building projects, older employees’ knowledge may be deeply embedded in green procurement processes, stakeholder collaboration habits, or regulatory navigation specific to certain regions or clients [69,72]. If young employees cannot understand these contextual elements, it hampers their ability to absorb and apply the transferred knowledge effectively.

2.3.4. Channel Factors

In IGKT within green building projects, transfer channels refer to the methods or media through which knowledge is shared, including both formal and informal channels. Formal channels (e.g., training programs, knowledge systems, documents, and meetings) provide a structured way to transfer knowledge [73,74]. In green building projects, these formal methods, such as training on sustainable design standards, green material specifications, and environmental safety protocols, help junior staff grasp foundational knowledge related to energy efficiency, waste reduction, and eco-certification processes. For instance, during the early phase of green construction, formal training can help young employees systematically understand green technology applications, such as solar integration or rainwater harvesting systems. These tools ensure knowledge consistency across teams and phases. Informal channels include mentoring, daily communication, team collaboration, and social interactions [73,74]. In green building projects, older employees often pass down site-specific strategies for energy-efficient construction or resolving environmental compliance issues through on-the-job coaching and peer learning. Informal communication is especially effective for transferring tacit, experience-based knowledge that is not well documented [20]. Given the dynamic and problem-oriented nature of green construction, informal mentoring, such as guiding a younger colleague through unexpected site-level challenges like waste separation or optimizing HVAC layout for energy savings, helps bridge the theory-practice gap and enhances adaptability.

The effectiveness of IGKT also depends on communication frequency, both online and offline. Online communication, enabled by tools like messaging apps or video calls, is key for fast, wide-area knowledge sharing [21,75]. In green building projects involving dispersed teams or external consultants (e.g., energy analysts or LEED auditors), high-frequency online exchanges support real-time coordination and rapid dissemination of eco-design updates, inspection results, or compliance adjustments [11,20]. For example, senior engineers can upload case-based green construction insights (like how to avoid thermal bridging or manage green material logistics) to a digital platform, helping young professionals quickly retrieve and apply that knowledge. Offline communication, such as site meetings, walkthroughs, and face-to-face coaching, remains irreplaceable for deep knowledge transfer [21,75]. In the context of green building, offline modes like toolbox talks or joint environmental assessments allow experienced workers to guide younger staff in context-specific decisions, such as adjusting construction sequences to minimize environmental impact or verifying green building material use. These interactions help young employees internalize sustainable practices and develop critical thinking skills for site-specific green solutions, which are hard to convey fully through digital means [11,20].

2.3.5. Context Factors

The context of knowledge transfer refers to the environmental and background factors affecting the process, mainly including system, technology, structure, and behavior, which greatly influence IGKT effectiveness. In green building projects, a supportive organizational atmosphere is crucial to encourage sharing of specialized sustainable construction knowledge across generations [21,22]. For example, when senior staff feel that their expertise in green technologies and eco-friendly practices is valued and mentoring is encouraged, they are more motivated to guide younger employees. Likewise, young employees supported by management are more proactive in learning about energy-efficient methods, green certifications, and environmental regulations [23]. Organizational structure also significantly impacts IGKT. In complex green building projects involving multiple contractors and stakeholders, rigid hierarchies can block timely knowledge flow about sustainable innovations, while flatter, networked structures promote cross-team and cross-generational exchange of green expertise [8,65,76]. Leadership style matters too: transformational and supportive leaders foster open communication and a culture of continuous learning focused on sustainability, boosting IGKT, while traditional command styles can suppress knowledge sharing [27,77]. With digital transformation advancing in construction, digital capabilities are becoming vital enablers of IGKT in green projects [78,79]. Digital tools such as mobile BIM viewers, cloud-based platforms, and AR/VR training modules help senior experts capture and share tacit knowledge on sustainable building techniques and green material applications in real time. These technologies allow systematic organization and visualization of green construction experience, making it easier for younger staff to learn and apply eco-friendly practices efficiently [2,80].

3. Methodology

The research employed a combined approach, which is illustrated in Figure 1. The process begins with case collection, where focus group discussions are conducted with knowledge senders and receivers to identify influencing factors. This is followed by key factors identification, utilizing communication theory to build a theoretical model and a three-step screening process (independent scoring, focus group discussions, and Delphi confirmation) to identify the key factors influencing IGKT. The DEMATEL method is then employed to collect data from experts with over 10 years of industry experience and calculate the direct and total influence matrices. Finally, the ISM method is used to generate the adjacency and reachability matrices, followed by hierarchical decomposition to construct the ISM structural model, revealing the interrelationships among the key factors.

3.1. The Identification of Influencing Factors

To explore the core determinants of IGKT in green building projects, this study adopted a two-stage methodological design. Part I focused on case collection, and Part II centered on factor identification. In Part I (case collection), IGKT cases were systematically gathered from completed and ongoing green building projects across diverse contexts. A case was defined as a documented or traceable instance of sustainability-related knowledge transfer between employees of different generations within a real project environment. Cases were identified through project documentation, technical meeting summaries, training archives and referrals from experienced practitioners. Each case had to meet two criteria: (1) it involved knowledge transfer relating to green building technologies, sustainable construction processes or environmental decision-making; and (2) it included at least one senior-junior dyad with a minimum age gap of 10 years. Following these criteria, a total of 37 valid cases were collected, covering a wide range of green building project types, including residential green buildings, commercial and office complexes, industrial and logistics facilities, and public infrastructure projects integrating low-carbon or ecological design principles. These cases provided a rich empirical foundation to examine how intergenerational sustainability knowledge is transferred in practice.

Building on these cases, Part II employed role-based focus group interviews to identify the key factors influencing IGKT. Focus groups were selected because they enable participants to collectively construct meanings, debate interpretations, and reveal shared norms, an approach particularly suitable for knowledge-related and practice-embedded topics such as IGKT [81,82]. Compared with individual interviews, focus groups allow senior and junior practitioners to articulate and refine their views through interaction, thus generating deeper insights into how IGKT operates within real project settings. This methodological choice has also been widely adopted in organizational knowledge and construction management research, where practitioner interaction forms a critical part of experiential knowledge formation.

Drawing from 37 identified IGKT cases, two distinct groups of participants were selected from the collected cases for in-depth interviews: (1) knowledge senders, defined as senior employees (over 40 years old) who regularly transferred sustainability-related knowledge to colleagues at least 10 years younger; and (2) knowledge receivers, identified as junior employees (40 years old or younger) who consistently acquired knowledge from colleagues at least 10 years older in green building practices. All participants possessed substantial professional experience and demonstrated strong communication capabilities. Each group interview lasted 90 to 120 min, with focused discussions examining participants’ perspectives on IGKT in green building projects, particularly emphasizing critical influencing factors and their impacts on transfer effectiveness.

In this study, all interview and questionnaire collection procedures strictly adhered to the principles outlined in the Declaration of Helsinki (1975, revised in 2013), ensuring respect for participants’ autonomy, privacy, and well-being. Prior to participation, each contributor received a clear information statement describing the study purpose, the voluntary nature of involvement, the measures taken to protect confidentiality, and their right to decline or withdraw at any time without consequences. Only participants who explicitly agreed to these conditions proceeded with the interviews. No personally identifiable information was collected during the discussion, and all responses were anonymized during transcription and analysis, ensuring that no individual could be identified from the research data.

Subsequently, systematic classification and coding of the collected data were conducted to establish a transparent and replicable factor system for the DEMATEL-ISM analysis. At this stage, the aim was to document how the study determined what factors would enter the analytical model, rather than to report empirical results. For this reason,

Table 1. Definition and source of the factors.

Category	Factor	Definition	Source References	Source Cases
Subject	Autonomous motivation	Intrinsic drive to engage in knowledge transfer voluntarily.	Osterloh and Frey [52]; Koestner et al. [53]	1, 3, 6, 8, 9, 11, 15, 17, 20, 22, 26, 29, 30, 33, 35
	Controlled motivation	Extrinsic pressure or rewards driving knowledge transfer behavior.	Osterloh and Frey [52]; Koestner et al. [53] Lam and Lambermont-Ford [14]	2, 5, 7, 9, 10, 13, 16, 19, 22, 23, 26, 29, 32, 34, 36
	Green knowledge transmission capability	Ability to effectively share and communicate green knowledge.	Martin and Salomon [59]; Park [61]; Liu et al. [69]	1, 2, 3, 5, 7, 9, 10, 12, 14, 15, 17, 20, 23, 24, 27, 31, 33, 36
	Green knowledge absorption capability	Capacity to understand, integrate, and utilize green knowledge.	Park [61]; Liu et al. [69]; Wang et al. [11]	1, 2, 4, 5, 7, 8, 10, 13, 15, 17, 20, 22, 25, 26, 29, 30, 34, 37
Relationship	Green knowledge distance	Gap between the knowledge levels of the sender and receiver.	Cummings and Teng [63]; Duan et al. [64]	3, 4, 6, 10, 11, 14, 18, 21, 23, 26, 31, 35
	Intergenerational relationship distance	Emotional and social closeness between the sender and receiver.	Ibert [67]; Erskine [68]; Liu et al. [69]	1, 3, 5, 8, 9, 12, 13, 15, 20, 21, 24, 25, 29, 31, 33, 36, 37
Object	Knowledge complexity	Degree of intricacy and difficulty in understanding the knowledge.	Cummings and Teng [63]; Kang et al. [16]; Liu et al. [69]	4, 6, 7, 8, 10, 12, 14, 17, 20, 22, 24, 27, 30, 32, 34, 37
	Knowledge tacitness	Uncodified, experience-based knowledge difficult to articulate.	Cummings and Teng [63]; Kang et al. [16]; Liu et al. [69]	1, 4, 7, 9, 11, 15, 16, 19, 21, 24, 26, 27, 31, 34, 36
	Knowledge embeddedness	Knowledge deeply integrated into organizational routines and contexts.	Cummings and Teng [63]; Liu et al. [69]	2, 4, 6, 7, 10, 12, 14, 15, 18, 20, 21, 24, 26, 30, 32, 35
Channel	Online communication frequency	Rate of digital interactions for knowledge transfer.	Lu et al. [75]; Wang et al. [21]	1, 2, 5, 6, 9, 11, 12, 14, 18, 21, 23, 24, 27, 30, 33, 36
	Offline communication frequency	Rate of face-to-face interactions for knowledge transfer.	Lu et al. [75]; Wang et al. [21]	2, 4, 6, 9, 11, 13, 14, 16, 19, 22, 23, 26, 28, 30, 31, 35
	Formal transfer channel	Structured, official pathways for knowledge transfer.	Chirwa and Boikanyo [73]; Koch and Denner [74]	1, 2, 5, 8, 10, 13, 15, 17, 18, 21, 24, 26, 28, 29, 30, 34, 36
	Informal transfer channel	Unofficial, spontaneous methods of knowledge transfer.	Chirwa and Boikanyo [73]; Liu et al. [20]	1, 3, 4, 7, 8, 9, 12, 13, 16, 20, 22, 24, 25, 29, 31, 33, 35, 37
Context	Digital transformation capability	Organizational ability to leverage digital tools for knowledge.	Yepes et al. [2]; Xu et al. [80]; Zhu et al. [79]	2, 3, 7, 8, 11, 13, 14, 17, 20, 23, 28, 33, 34
	Organizational support atmosphere	Environment fostering encouragement and resources for knowledge transfer.	Harvey [7]; Wang et al. [21]; Rui and Ju [23]	3, 4, 6, 9, 11, 13, 15, 18, 21, 23, 25, 26, 31, 34, 37
	Organizational structure	Framework defining roles and hierarchies affecting knowledge transfer.	Babnik and Trunk Širca [76]; Rupčić [8]	4, 6, 9, 12, 13, 15, 18, 21, 23, 24, 26, 28, 31, 33, 35, 36
	Leadership style	Managerial approach influencing knowledge transfer culture and practices.	Gerpott et al. [83]; Wang et al. [21]; Le and Lei [77]	2, 4, 7, 9, 10, 11, 14, 15, 17, 20, 22, 25, 28, 30, 32, 35, 37

and Figure 2 belong to the methodology section: they present the inputs to the analytical procedures, not the outcomes generated by them. Table 1 summarizes the identified factors together with their definitions, supporting literature and the corresponding case numbers from the 37 IGKT cases. The table demonstrates the methodological rigor behind factor selection by evidencing that each factor is simultaneously grounded in prior scholarly work (Section 2) and traceable to at least 10 real project cases. Presenting Table 1 in the methodology section ensures transparency regarding the origin, justification and reliability of the variables used in subsequent modeling, which is essential for methodological validity and reproducibility. Figure 2 presents the factor framework by displaying the set of identified factors within each of the five dimensions (subject, relationship, object, channel and context). The figure visually organizes the factors that have already been justified in Table 1, showing how the study structures these elements before entering the DEMATEL and ISM analyses. By illustrating the dimensional grouping of the variables, Figure 2 serves as an intermediate methodological product that clarifies the architecture of the analytical model.

A methodological placement of Table 1 and Figure 2 is therefore necessary, as both components serve to document how the analytical framework is constructed prior to model execution. They clarify the linkage between the theoretical foundations established in Section 2 and the variables entered into the DEMATEL-ISM procedures, while also laying the groundwork for the subsequent causal and hierarchical analyses presented in the Results section.

3.2. The DEMATEL-ISM Model

To understand the complex interactions among the factors influencing IGKT, the DEMATEL-ISM model was selected as an appropriate method. DEMATEL is a system analysis method that identifies causal relationships and influence strength among factors in complex systems. It builds a direct impact matrix, quantifies interactions, and calculates each factor’s centrality (importance) and causality (whether it is a “cause” or “effect”) [29,30]. ISM decomposes complex systems into multi-layer hierarchical structures using matrix operations and logic, converting fuzzy factor relationships into clear hierarchies [31,32]. Combining DEMATEL’s causal analysis with ISM’s hierarchical modeling forms the DEMATEL-ISM method, which can uncover both the cause-and-effect links and layered structure of factors in complex systems [84,85]. Specifically, DEMATEL identifies key driving factors by centrality and causality, while ISM builds a multi-level hierarchy to reveal system structure.

IGKT in green building projects is a complex system involving multiple interrelated factors that often influence each other in a cyclical or indirect manner. The DEMATEL-ISM method is well-suited to this complexity, as it simultaneously reveals causal relationships and hierarchical structures among factors impacting IGKT in sustainable construction contexts [86,87]. Compared with methods like structural equation modeling or path analysis, which assume one-way linear relationships, DEMATEL-ISM can model interdependencies and feedback loops critical to understanding knowledge transfer in green building projects [86]. Furthermore, DEMATEL-ISM clarifies key paths and core elements through hierarchical analysis, making it especially effective for tackling the multifaceted challenges of IGKT in green construction [88]. The specific steps of DEMATEL-ISM model are as follows:

Step 1.

Identify system factors and collect data

First, it is necessary to identify the n key factors of the research system, denoted as $X_1$, $X_2$,……, $X_{12}$. Then, an expert evaluation form is designed using a 0–4 scale (0 = no influence, 1 = weak influence, 2 = moderate influence, 3 = strong influence, 4 = extremely strong influence) to assess the direct influence between factors. Finally, the expert evaluations are aggregated to construct the direct influence matrix A, where $A_{ij}$ represents the direct influence of factor $X_i$ on factor $X_j$.

Step 2.

Normalize the direct impact matrix

After constructing the direct influence matrix, it is necessary to eliminate the influence of dimensionality to ensure the convergence of matrix operations. The original matrix A is normalized by dividing each element by the maximum row sum, resulting in the normalized matrix B. After normalization, the elements of the matrix range between 0 and 1, and the sum of each row does not exceed 1, thereby satisfying the conditions for subsequent matrix inversion. The normalized matrix B can be obtained by Equation (1).

$$B={\displaystyle \frac{\mathrm{A}}{\underset{1\le i\le n}{\max }({\sum }_{j=1}^n{A}_{ij})}}$$

(1)

Step 3.

Calculate the total influence matrix

The combined effect of direct and indirect influences is computed through the matrix power series expansion $(C=B+B^2+B^3+\cdots )$. To simplify the computation, matrix inversion is utilized to obtain the total influence matrix C, where the element $C_{ij}$ represents the total influence of $X_i$ on $X_j$ (including all indirect paths), I is the identity matrix. The total influence matrix C can be obtained by Equation (2).

$$C=B{ \left(I-B\right)}^{-1}$$

(2)

Step 4.

Calculate key indicators (influence, centrality, etc.)

By summing the rows of matrix C, the influence degree $D_i$ for each factor is obtained, while summing the columns yields the influenced degree $R_i$. Furthermore, the centrality $M_i$ (importance) and the causality $N_i$ (causal attribute) are calculated. A positive causality value indicates that the factor is a driving factor (cause) in the system, whereas a negative value signifies a dependent factor (effect).

$$D_i=\sum _{j=1}^n{C}_{ij}, R_j=\sum _{i=1}^n{C}_{ij}, M_i=D_i+R_i, N_i=D_i-R_i$$

(3)

Step 5.

Generate the adjacency matrix

A threshold value λ (e.g., mean, median, or empirical value) is established to transform the continuous total influence matrix E into a binary adjacency matrix, retaining only significant influence relationships (where $C_{ij}$ ≥ λ is set to 1, otherwise 0). Additionally, the selection of the threshold λ requires balancing model complexity with information completeness.

Step 6.

Calculate the reachability matrix

Reflexivity is incorporated into the adjacency matrix E, and the reachability matrix F is derived through transitive closure operations (e.g., Warshall’s algorithm or iterative matrix multiplication). An element $F_{ij}=1$ in matrix F indicates the existence of a direct or indirect path from $X_{\mathrm{i}}$ to $X_{\mathrm{j}}$, reflecting global reachability.

$$F={\left(E+I\right)}^k, k\le n-1$$

(4)

Step 7.

Hierarchical decomposition

Based on the reachability matrix, the reachable set $R\left(X_i\right)$, the antecedent set $S\left(X_i\right)$, and the intersection set $T\left(X_i\right)$ are constructed for each factor. The intersection of $R\left(X_i\right)$ and $S\left(X_i\right)$ is calculated, and factors with identical elements in the intersection and the reachable set are assigned to the same hierarchical level. Subsequently, the factors at this level are removed, and the process is repeated to determine the hierarchical levels of the remaining factors until all factors in the matrix are eliminated. At this point, all factors are assigned to distinct hierarchical levels, resulting in a structured system hierarchy.

$$R\left(X_i\right)=\left\{X_i|f_{ij}=1\right\}, S\left(X_i\right)=\left\{X_i|f_{ji}=1\right\}, T\left(X_i\right)=R\left(X_i\right)\cap S\left(X_i\right)$$

(5)

Step 8.

Construct the ISM structural model

The results of the hierarchical decomposition are arranged from the top to the bottom level, and a directed graph is drawn based on the direct influence relationships in the adjacency matrix. In the graph, nodes represent factors, and arrows indicate the direction of influence. This visually illustrates the multi-level hierarchical structure and causal chains of the system, providing decision-makers with intuitive and actionable insights.

3.3. Data Collection Process

The data collection process consisted of two stages: factor screening and expert scoring. The first stage refined the preliminary factor list to ensure conceptual clarity and analytical feasibility, while the second stage quantified the direct influence among the retained factors. Before applying DEMATEL, a controlled reduction in factors is necessary because the number of pairwise causal evaluations increases exponentially with the variable count. Prior methodological studies emphasize that DEMATEL becomes difficult to interpret when too many factors create dense causal networks and overlapping causal diagrams [29,89]. Following this guidance, the present study adopted a structured screening procedure to consolidate the factor list before entering the DEMATEL-ISM analysis. A panel of 15 experts was recruited, including senior practitioners from green building enterprises, scholars specializing in sustainable construction management, and knowledge management experts. The panel was deliberately composed to cover the major segments of the green building sector, including design consulting, construction contracting, project supervision, and facility operation. This ensured that the judgment process reflected multiple stages of the project lifecycle. All experts possessed more than ten years of domain experience and were selected to ensure diversity in roles and generational perspectives. In addition, experts were required to have direct experience with intergenerational collaboration or mentoring in project settings, ensuring that their evaluations were grounded in practical IGKT scenarios. This selection strategy aligns with expert elicitation principles recommending heterogeneous yet domain-relevant panels for qualitative judgment tasks [90]. To further ensure reliability, experts’ initial ratings were checked for response completeness and internal consistency before entering the Delphi round.

Factor screening followed three sequential steps. Factor screening followed three sequential steps. First, experts independently rated the relevance and practical significance of the preliminary factors using a 5-point Likert scale. Second, role-based focus group discussions were conducted. Focus groups are widely recognized for their ability to surface shared interpretations and clarify conceptual ambiguities through interactive dialog [82,91]. This step ensured consistent understanding of factor meanings across participants. Third, a Delphi round was implemented to achieve formal consensus. The Delphi method, characterized by anonymity, iteration and controlled feedback, is particularly suitable for refining factor sets in complex decision-making contexts [90,92]. Its structured process minimizes dominance bias, mitigates conformity pressures and yields more stable expert judgments. In this study, experts anonymously reassessed each factor after receiving aggregated feedback, and explicit criteria were applied to eliminate controversial items. A factor was removed if (1) it failed to reach 80% agreement regarding its necessity or practical relevance, (2) experts consistently reported divergent interpretations even after clarification, or (3) it substantially overlapped with another factor and lacked unique analytical value. For example, “organizational structure” did not obtain sufficient consensus, as experts considered it partly embedded within the broader construct of “organizational support climate”, which better reflected the enabling conditions relevant to IGKT in project environments.

In the second stage, a structured questionnaire survey was administered to quantify the direct influence strengths among the 12 factors. Purposive sampling was used to recruit 20 additional experts with substantial experience in green building projects, consistent with purposive sampling principles emphasizing depth over representativeness for expert-based studies [93]. Expert selection criteria included (1) a minimum of ten years of industry experience, (2) involvement in green building project roles, and (3) familiarity with intergenerational collaboration. To strengthen reliability, the sampling frame covered practitioners, designers, consultants and project managers from different sizes and types of green building organizations, ensuring that the direct influence matrix reflected broad industry practice rather than a single sub-sector.

A 0–4 Likert scale was used to measure causal influence intensity between factor pairs. Two rounds of pretesting were conducted to refine wording and ensure face validity, and standardized scoring instructions were provided to reduce interpretation bias. To further address reliability concerns, two consistency checks were implemented: (1) logical consistency screening to identify contradictory or illogical scoring patterns, and (2) cross-review of extreme ratings by two independent researchers. Responses failing these checks were removed and replaced. Anonymized identifiers (E01–E20) were assigned to all questionnaires to avoid social desirability bias. A mixed collection mode was adopted: some experts completed the survey through face-to-face interviews, while others responded via secure online platforms. Two invalid responses were excluded after logical consistency checks, and replacement experts were invited to maintain the target sample size of 20 valid direct influence matrices. Demographic information of the expert respondents is summarized in

Table 2. The demographic information of experts in the second stage.

Category	Classification	Number
Gender	Female	8
	Male	12
Education level	Bachelor’s Degree	3
	Master’s Degree	12
	Doctoral Degree	5
Age (years)	31–40	7
	41–50	7
	>50	6
Position	Enterprise-level managers	4
	Project manager	6
	On-site execution managers	5
	Other (e.g., technical specialists)	5
Experience in this field (years)	10–15	6
	16–20	7
	>21	7

.

4. Data Analysis and Results

This section presents the empirical results derived from the sequential analytical procedures described in the methodology. It first reports the outcomes of case collection and factor identification, followed by the causal structure revealed through the DEMATEL model, and finally the hierarchical relationships determined by the ISM analysis. Together, these results provide an integrated understanding of how key factors interact to shape IGKT in green building projects.

4.1. Result of Case Collection and Key Factors Identification

A total of 37 valid IGKT cases were obtained, representing documented instances of sustainability-related knowledge transfer between senior and junior employees across multiple types of green building projects. These cases spanned residential, commercial, industrial and public-sector projects, and collectively illustrated a wide spectrum of intergenerational exchanges involving green construction technologies, sustainable material selection, energy-efficiency practices, environmental decision-making and regulatory compliance processes. The cases provide concrete evidence of how IGKT occurs in real project environments, highlighting frequent differences in technical experience, sustainability awareness and problem-solving approaches between generations.

Based on the analyzed cases and expert consensus, twelve key factors were identified as the most substantive determinants of IGKT in green building projects. These factors represent the refined set retained after systematic screening and expert evaluation, and they reflect the recurring patterns observed across the 37 cases. The twelve factors are: green knowledge absorption capacity (X1), green knowledge transmission capability (X2), controlled motivation (X3), autonomous motivation (X4), green knowledge distance (X5), intergenerational relationship distance (X6), knowledge complexity (X7), knowledge embeddedness (X8), formal transfer channels (X9), informal transfer channels (X10), digital transformation capacity (X11), and organizational support climate (X12).

These twelve factors constitute the final analytical variable set for the DEMATEL and ISM procedures. They capture the essential subject-level abilities and motivations, relational conditions, characteristics of sustainability knowledge, communication pathways and contextual enablers that were most consistently observed across the 37 IGKT cases and validated by expert judgment.

4.2. Result of the DEMATEL Model

Through quantitative processing of the initial data, the direct influence matrix A was derived. Subsequently, following the DEMATEL model procedures, the normalized influence matrix B and the total influence matrix C were sequentially determined. Finally, the influence degree, influenced degree, centrality degree, and cause degree of each factor were calculated, with the results summarized in

Table 3. The cause degree and centrality degree of the factors.

Factor		Influencing Degree		Influenced Degree		Centrality Degree		Cause Degree
		Value	Rank	Value	Rank	Value	Rank	Value	Rank
X1	Green knowledge absorption capacity	3.668	12	5.335	2	9.003	4	−1.667	12
X2	Green knowledge transmission capability	3.721	11	5.341	1	9.062	3	−1.621	11
X3	Controlled motivation	3.876	9	4.383	3	8.259	10	−0.507	8
X4	Autonomous motivation	3.950	8	4.936	4	8.886	6	−0.987	10
X5	Green knowledge distance	4.171	10	4.917	5	9.087	2	−0.746	9
X6	Intergenerational relationship distance	4.233	7	4.215	8	8.448	9	0.018	7
X7	Knowledge complexity	4.605	4	3.329	7	7.934	12	1.276	1
X8	Knowledge embeddedness	4.754	5	3.478	9	8.231	11	1.276	2
X9	Formal transfer channels	4.721	1	4.228	6	8.949	5	0.494	5
X10	Informal transfer channels	4.705	6	4.178	12	8.883	7	0.527	6
X11	Digital transformation capacity	4.786	3	3.804	11	8.590	8	0.982	3
X12	Organizational support climate	5.255	2	4.299	10	9.553	1	0.956	4

. The magnitude of centrality degree reflects the relative importance of each factor in facilitating IGKT in green building projects, with higher values indicating greater significance. Table 3 shows the centrality ranking, i.e., organizational support climate (X12) > green knowledge distance (X6) > green knowledge transmission capability (X2) > green knowledge absorption capacity (X1) > formal transfer channels (X9) > autonomous motivation (X4) > informal transfer channels (X10) > digital transformation capacity (X11) > Intergenerational relationship distance (X6) > Controlled motivation (X3) > Knowledge embeddedness (X8) > Knowledge complexity (X7). Specifically, X12 holds the highest centrality, highlighting its pivotal role in both affecting and being affected by other factors.

The influencing degree indicates the extent to which a factor exerts influence on other factors in the system. For example, X12 has the highest influencing degree (5.255), suggesting it plays a key driving role in the knowledge transfer process. Conversely, X1 has a relatively low influencing degree (3.668), meaning it is more of a receiver than a driver in the system. The influence degree reflects how much a factor is affected by others. The top two influential factors are X2 and X1, indicating they are highly susceptible to external influences and thus represent important outcomes of IGKT.

The cause degree is calculated as the difference between influencing and influenced degrees. A positive cause degree implies a net causal influence (i.e., a driving factor), while a negative value indicates a net result of being influenced. For instance, X7 and X8 have the highest positive cause degrees (1.276), signifying they are fundamental causal variables in the system. On the other hand, X1 and X2 exhibit large negative cause degrees (−1.667 and −1.621, respectively), indicating their roles as outcome variables that rely on upstream support and capability factors.

The mean centrality degree of all factors was calculated as 8.75. This value was introduced to partition the coordinate axes into four quadrants, as illustrated in Figure 3. The x-axis represents centrality degree, while the y-axis denotes cause degree. Cause factors (located above the horizontal line y = 0) directly influence IGKT, whereas result factors (below y = 0) are indirectly influenced by cause factors. The larger the absolute value of the causal degree is, the greater the degree to which the factor affects other factors or is affected by other factors. As shown in Figure 3, seven factors including knowledge complexity (X7), knowledge embeddedness (X8), digital transformation capacity (X11), organizational support climate (X12), informal transfer channels (X10), formal transfer channels (X9), and intergenerational relationship distance (X6) exhibited positive cause degrees, signifying their dominant role as causal factors that exert stronger influences on other factors than they receive. Among the causal factors, X8, X7, X11, and X12 ranked in the top four, indicating that knowledge characteristics and organizational environment (including digital transfer capabilities and organizational support atmosphere) have the greatest impact on other factors. Conversely, X1, X2, X3, X4, and X5 displayed negative cause degrees, classifying them as result factors that are more influenced by external drivers than they contribute. Among the result factors, the result degrees of X1 and X2 ranked first and second, indicating that the knowledge absorption and transmission capabilities are most easily affected by other factors.

4.3. Result of the ISM Model

Based on the structural analysis conducted using the ISM approach, the hierarchical relationships among the twelve key IGKT factors were extracted and organized into a multi-level structure. To construct the reachability matrix, a threshold value λ was required to filter out negligible influence values from the total influence matrix. In this study, the threshold λ was set to the mean value of all non-diagonal entries in the total influence matrix, a practice widely adopted in DEMATEL-ISM research because it balances information retention and noise reduction [88,94]. Compared with the median or subjective expert-defined cut-offs, using the mean ensures a more objective and data-driven criterion, allowing weaker and statistically insignificant influence relationships to be removed while preserving the dominant causal structure needed for the ISM hierarchy. This method is particularly suitable for medium-sized factor systems (10–20 variables), where overly strict thresholds may cause excessive information loss, and overly lenient thresholds may produce overly dense networks [89]. After applying this mean-based threshold, the resulting binary adjacency matrix was converted into the final reachability matrix through Boolean operations.

Table 4. The reachable set, antecedent set and collective set of factors.

Factor	Reachable Set R	Antecedent Set S	Collective Set T	Layer
X1	X1, X2	X1, X2, X3, X4, X5, X6, X7, X8, X9, X10, X11, X12	X1, X2	L1
X2	X1, X2, X5	X1, X2, X3, X4, X5, X6, X7, X8, X9, X10, X11, X12	X1, X2, X5	L1
X3	X1, X2, X3, X4, X5	X3, X7, X8, X9, X10, X11, X12	X3	L3
X4	X1, X2, X4, X5	X3, X4, X5, X6, X7, X8, X9, X10, X11, X12	X4, X5	L2
X5	X1, X2, X4, X5	X2, X3, X4, X5, X6, X7, X8, X9, X10, X11, X12	X2, X4, X5	L2
X6	X1, X2, X4, X5, X6	X6, X7, X8, X9, X10, X11, X12	X6	L3
X7	X1, X2, X3, X4, X5, X7, X9, X10, X12	X7	X7	L5
X8	X1, X2, X3, X4, X5, X6, X8, X9, X10, X12	X8	X8	L5
X9	X1, X2, X3, X4, X5, X6, X9, X10, X12	X7, X8, X9, X10, X11, X12	X9, X10, X12	L4
X10	X1, X2, X3, X4, X5, X6, X9, X10, X12	X7, X8, X9, X10, X11, X12	X9, X10, X12	L4
X11	X1, X2, X3, X4, X5, X6, X9, X10, X11, X12	X11, X12	X11, X12	L5
X12	X1, X2, X3, X4, X5, X6, X9, X10, X11, X12	X7, X8, X9, X10, X11, X12	X9, X10, X11, X12	L4

presents the reachable set, antecedent set and intersection set (R, S and T) for each factor, which form the basis for determining hierarchical levels in the ISM procedure. Using these sets, factors were iteratively assigned to different levels. The resulting hierarchical structure is illustrated in Figure 4.

The system is structured into five layers, with varying degrees of influence and complex causal relationships existing between factors at different levels, including interactions that span across layers. The first layer (L1) comprises surface-level factors, which are typically directly observable and superficial, including green knowledge absorption capacity (X1) and green knowledge transmission capability (X2). These factors have broad reachable sets but are contained in the antecedent sets of most other factors, indicating their high dependence and thus positioning them at the top of the hierarchy. Deep-level factors, which have a fundamental impact on the system, are located at the bottom layer (L5) of the hierarchy and include knowledge complexity (X7), knowledge embeddedness (X8), and digital transformation capacity (X11). They exhibit narrow reachable sets and are not influenced by others, meaning they are foundational drivers in the structure. Intermediate-level factors, which connect surface-level and deep-level factors, are found in the intermediate layers, including autonomous motivation (X4) and knowledge distance (X5) in L2; controlled motivation (X3) and intergenerational relationship distance (X6) in L3; formal transfer channels (X9), informal transfer channels (X10), and organizational support climate (X12) in L4. These layers represent transition nodes, with factors in L2 and L3 gradually transmitting influence from foundational elements to outcome factors, while those in L4 integrate and mediate multiple upstream influences.

5. Discussion

This section provides a comprehensive interpretation of the study’s findings and is structured into three subsections to reflect the logical progression from analytical insights to theoretical and practical contributions. First, Section 5.1 presents an in-depth analysis of the 12 key factors, explaining how the DEMATEL-ISM results reveal their roles, interdependencies and hierarchical positions within the IGKT system. This analytical interpretation forms the foundation for broader theoretical reflections. Accordingly, Section 5.2 discusses the theoretical implications by situating the results within existing knowledge-transfer and green construction research, highlighting where the findings align with, extend or diverge from prior studies. Finally, Section 5.3 translates these insights into managerial implications, outlining actionable recommendations for practitioners seeking to strengthen intergenerational sustainability knowledge transfer in green building projects. Together, these three components ensure that the discussion moves beyond reporting results to contextualizing their significance and practical value.

5.1. In-Depth Analysis of the Key Influencing Factors

After the identification of 12 key factors affecting IGKT, this study conducted an in-depth analysis using the DEMATEL-ISM method and categorized them into three hierarchical levels: surface-level, intermediate-level, and deep-level factors. This paper will conduct a layered analysis of the operational mechanisms of these factors.

(1)

Analysis of surface-level influencing factors

Green knowledge transmission (X2) and absorption capacity (X1) appear at the surface level and exhibit the highest susceptibility in the system. This indicates that, although these two factors are the most observable indicators of IGKT performance, their functioning is strongly conditioned by deeper organizational, relational and technological determinants. This finding is generally consistent with existing knowledge-transfer literature, which emphasizes that individual knowledge sharing and learning behavior are highly sensitive to contextual cues [11,62]. Previous studies have treated transmission and absorption capacities largely as individual attributes acquired through experience or expertise [7]. However, our analysis reveals a more dependent pattern: both capacities rank extremely low in driving power, suggesting they cannot independently trigger improvement in IGKT effectiveness. This contradicts the assumption in traditional green construction research that enhancing individuals’ technical abilities alone is a sufficiently strong lever for advancing IGKT [66]. Instead, our results show that surface-level capacities reflect outcomes of deeper conditions, particularly organizational support climate (X12) and digital transformation capability (X11). This offers a more systemic explanation for why in many green projects, knowledge-sharing training programs fail to deliver expected results despite considerable investment in skill-based capacity building.

(2)

Analysis of intermediate-level influencing factors

The intermediate-level factors (L2–L4) act as critical bridges linking surface- and deep-level components within green building projects. The L2-level factors include autonomous motivation and green knowledge distance. Green knowledge distance ranks 2nd in centrality, reinforcing existing findings that intergenerational knowledge gaps in technical, digital and experiential domains are major bottlenecks in transfer effectiveness [13,22]. However, compared with prior studies that treat knowledge distance as a static barrier, this study shows that it is moderately influenced by organizational support and digital transformation capability. This expands previous research by demonstrating that digital-organizational interventions can actively narrow generational knowledge gaps, an insight less explored in knowledge-transfer literature. Autonomous motivation also follows prior findings emphasizing the importance of intrinsic motivation for effective sharing [23]. Yet, our results reveal a new mechanism: knowledge complexity and digital maturity significantly affect autonomous motivation, either heightening burdens or enabling streamlined communication. This complements but extends earlier studies that mainly focus on individual psychological drivers [16], by incorporating green project–specific cognitive load and structural conditions.

The L3-level factors include controlled motivation and intergenerational relationship distance. Controlled motivation ranks relatively low in centrality and influencing degree, echoing prior findings that externally driven knowledge sharing often leads to limited long-term engagement [56,58]. However, our results provide new nuance: in green building contexts, where compliance pressures and sustainability KPIs are common, controlled motivation still contributes, but only when supported by strong transfer channels. Intergenerational relationship distance aligns with previous research showing that relational trust and familiarity strongly influence willingness to share [7]. However, this study additionally indicates that digital collaboration platforms such as sustainability-focused project management systems can reduce relationship distance, a factor rarely discussed in the IGKT literature.

(3)

Analysis of deep-level influencing factors in green building projects

Deep-level factors exhibit relatively low centrality (ranked 8th–12th) but high cause degree, particularly digital transformation capability (3rd) and green knowledge embeddedness (2nd), signifying their critical catalytic roles despite weaker structural connectivity. Green knowledge complexity ranks low in centrality but mid-range in influence, indicating its role as a structural constraint. High complexity directly increases the cognitive burden of interpreting sustainability-related knowledge and indirectly reduces the efficiency of formal and informal transfer channels. This result aligns with previous findings that complex technical or process-related knowledge in sustainable construction is more difficult for younger staff to internalize without additional scaffolding [2]. When task-specific sustainability knowledge becomes overly intricate or tacit, it weakens both autonomous motivation (L2) and the effectiveness of communication channels (L4), thereby restricting IGKT.

Green knowledge complexity ranks low in centrality but mid-range in influence, indicating its role as a structural constraint. High complexity directly increases the cognitive burden of interpreting sustainability-related knowledge and indirectly reduces the efficiency of formal and informal transfer channels. This result aligns with previous findings that complex technical or process-related knowledge in sustainable construction is more difficult for younger staff to internalize without additional scaffolding [2]. When task-specific sustainability knowledge becomes overly intricate or tacit, it weakens both autonomous motivation (L2) and the effectiveness of communication channels (L4), thereby restricting IGKT. Digital transformation capability ranks 2nd in influence, demonstrating the strongest driving effect among all deep-level variables. While existing studies recognize its role in supporting knowledge processes [79,80], this study uncovers a dual mechanism in which technological empowerment reduces knowledge and relational distances, and institutional reconstruction reshapes the climate, expectations and communication patterns within project teams. This dual effect highlights digital transformation as not only a tool-level facilitator but also a deep structural force reshaping IGKT dynamics in green building environments.

5.2. Theoretical Implications

This research offers several key insights into theoretical frameworks. First, this research reconstructs and enriches the multi-dimensional system of IGKT. Previous studies predominantly examine isolated factors such as individual motivation, digital tools or organizational climate [9,10,11,37], often lacking an integrated theoretical model. Consistent with these prior works, our results confirm the importance of individual capability and motivational factors; however, the five-dimensional “subject-relationship-object-channel-context” framework developed in this study offers a more systematic and theoretically grounded lens for understanding IGKT in green building settings. This confirms our expectation that IGKT in sustainability-oriented projects involves multiple interacting layers rather than single-factor influences. By synthesizing literature and empirical case insights, twelve key factors are identified, providing a theoretical structure that captures the multi-level nature of intergenerational sustainability knowledge transfer.

Second, the DEMATEL-ISM results contribute new insights into the hierarchical mechanisms shaping IGKT. It was expected, based on prior research, that organizational support environments would play a substantial role [22,23]. The analysis confirms this expectation: organizational support climate emerges as the most central and influential factor, reinforcing the notion that institutionalized support is essential in intergenerational exchanges. However, an unexpected finding of this study is that surface-level capacities, namely green knowledge transmission and absorption, exert minimal independent influence and instead function primarily as outcomes shaped by deeper contextual and structural drivers. This differs from earlier studies that treat these capacities as primary determinants of IGKT effectiveness [7,11,62]. Our results show that these capacities are highly susceptible to the quality of transfer channels, motivational conditions and digital collaboration tools, suggesting that ability formation is situational rather than static. This finding broadens existing theory by positioning knowledge capacities as adaptive rather than intrinsic attributes.

Third, this research deepens theoretical understanding of digital transformation’s role in IGKT. Prior literature mainly regards digital tools as facilitators that streamline knowledge exchange [78,79,80]. While our results confirm this enabling role, they also reveal an unexpected dual mechanism: digital transformation reshapes not only technological pathways but also the institutional and motivational conditions under which IGKT occurs. Specifically, digital transformation capability simultaneously enhances technological empowerment and contributes to institutional reconstruction by influencing norms, expectations and perceived support within temporary project organizations. This extends the theoretical conversation beyond technological determinism and highlights digital transformation as a deeper systemic catalyst that shapes IGKT behaviors, structures and climates across project-based green building environments.

Overall, the theoretical novelty of this research lies in uncovering multi-level dependencies and revealing that several widely assumed “primary” determinants, such as individual knowledge capacities, are in fact derivative outcomes shaped by deeper organizational and technological forces. These insights refine existing theories of IGKT by demonstrating that sustainable knowledge transfer in green building projects is not merely a behavioral or cognitive process but an embedded, context-dependent system shaped by layered structural conditions.

5.3. Managerial Implications

This research offers a range of managerial implications to facilitate IGKT from older to younger employees within green building projects, which mainly includes four levels: (1) Accurately identifying the core role of the organizational support climate. The findings indicate that the support climate within project teams ranks first in both centrality and impact, highlighting its overarching influence on the knowledge transfer system. On the one hand, project leadership can establish targeted knowledge-sharing incentive mechanisms, integrating IGKT indicators into performance reviews or team evaluations. On the other hand, project teams can foster a more open and collaborative working atmosphere by organizing intergenerational exchange activities related to green building themes (e.g., low-carbon construction mentoring, joint sustainability-focused tasks) to reduce generational barriers and improve cohesion on site; (2) Recognizing the strategic value of digital transformation capability to promote integration between technology and on-site project knowledge. Although digital transformation capability is positioned at a deeper systemic level (L5), its high impact ranking (second place) suggests it plays a strong driving role and exhibits high independence within the system. Project teams can introduce and apply various digital tools (e.g., green BIM systems, smart energy monitoring dashboards, cloud platforms for sustainable material tracking) to externalize and visualize senior employees’ tacit knowledge. These tools can help overcome the spatial and temporal constraints of green building projects, enabling younger staff to access critical insights even outside of direct supervision; (3) Optimizing knowledge transfer channels to enhance the effectiveness of intergenerational project communication. The study reveals that both formal and informal channels significantly mediate IGKT at the project level. This suggests that project managers can further standardize formal knowledge transfer mechanisms such as sustainability design reviews, energy-efficiency report discussions, and digital tracking of green construction processes. Simultaneously, they should support informal interaction channels, including eco-site walkthroughs, hands-on learning during the installation of green systems, and experience sharing during sustainable practice demonstrations, to create multidimensional and fluid IGKT pathways; (4) Developing targeted personnel strategies to strengthen knowledge synergy within project teams. The study finds that while knowledge transmission and absorption capacities are located at the surface level, they exhibit the highest susceptibility to influence (ranking first and second, respectively). This implies that project leaders can adopt targeted talent development strategies, such as assigning senior staff to guide green practice implementation, conducting simulation drills for sustainable construction, and creating structured learning opportunities around low-impact construction methods. Enhancing younger employees’ knowledge absorption skills and strengthening older professionals’ ability to articulate their sustainability expertise can significantly improve IGKT efficiency. In addition, incorporating motivational incentives into green project team management can further bridge generational knowledge gaps and foster seamless collaboration in environmentally driven, time-sensitive building environments.

6. Conclusions

This study systematically analyzed the critical influencing factors of IGKT from older to younger employees in green building projects by integrating the DEMATEL-ISM approach, revealing their hierarchical structure and interaction mechanisms. The findings are summarized as follows:

• 12 key factors affecting IGKT were systematically identified from five dimensions: transfer subjects, inter-subject relationships, transfer objects, transfer channels, and transfer context. These include knowledge absorption capacity, knowledge transmission capability, controlled motivation, autonomous motivation, green knowledge distance, intergenerational relationship distance, knowledge complexity, knowledge embeddedness, formal transfer channels, informal transfer channels, digital transformation capacity, and organizational support climate.
• Organizational support climate ranks first in centrality and second in influence, confirming its role as the core systemic driver of IGKT. Digital transformation capacity ranks third in influence, indicating that although it is not the strongest driver, it remains a critical deep-level factor that substantially shapes transfer channels, reduces knowledge distance and enhances overall knowledge-flow efficiency. Together, these two factors form a complementary “environment–technology” foundation that underpins effective IGKT in green building projects.
• Hierarchically, surface-level factors (i.e., knowledge absorption and transmission capability) exhibited moderate centrality but high susceptibility to influence, suggesting their dependency on deeper-level drivers; intermediate-layer factors (e.g., autonomous motivation and knowledge distance) acted as bridges by mediating inter-subject interactions; deep-layer factors (e.g., knowledge complexity and embeddedness), despite low centrality, emerged as long-term constraints due to their inherent knowledge barriers. By integrating communication theory with hierarchical analysis, this study expands the dynamic framework of IGKT and validates the pivotal roles of the organizational environment and technological capabilities. Practically, it is recommended that green building teams prioritize fostering a supportive organizational culture, accelerate digital transformation, and leverage informal channels to complement formal mechanisms. Additionally, efforts should focus on stimulating senior employees’ autonomous motivation and optimizing knowledge distance to mitigate intergenerational transfer resistance.

There are still certain limitations in this research that warrant further refinement in future work. First the DEMATEL-ISM method primarily explores the interactions and hierarchical relationships among factors but fails to quantify the impact of each factor on the effectiveness of IGKT, making it difficult to provide quantitative optimization recommendations. Future research can integrate methods such as the structural equation modeling (SEM) or Bayesian networks to further quantify the influence of these factors and enhance the precision of the analysis. Furthermore, this study mainly adopts a static analysis approach and does not fully account for the dynamic evolution of the knowledge transfer process. Future research could incorporate system dynamics (SD) or other dynamic simulation methods to develop time-evolution models and explore the long-term evolution of IGKT.