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Article

Learning in MTS of Construction Megaproject: A Conceptual Framework

by
Jinfan Zhang
1,2,*,
Yun Chen
1,
Da Wang
1 and
Yinghui Zhang
1
1
Department of Transportation Engineering, Changsha University of Science & Technology, Changsha 410114, China
2
Department of Civil Engineering, Hunan City University, Yiyang 413000, China
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(5), 4295; https://doi.org/10.3390/su15054295
Submission received: 31 December 2022 / Revised: 22 February 2023 / Accepted: 24 February 2023 / Published: 28 February 2023
(This article belongs to the Section Psychology of Sustainability and Sustainable Development)
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Abstract

:
The construction megaproject team (CMPT) emphasises integration as a megaproject multiteam system (MTS) to facilitate knowledge learning. This paper synthesises the CMPT structure characteristics and team learning processes into a conceptual framework named the CMPT-MTS learning framework to advance future CMPT learning research. The constructs included are identified from published research. A case example is the island and tunnel project of the Hong Kong–Zhuhai–Macao Bridge, which provides practical grounding for framework refinement. The conceptual framework deemed to follow a cyclical pattern identifies the CMPT-MTS structure variables and team learning processes affecting learning outcomes and contextual variables hypothesised to influence the intra- and inter-team interaction. We discuss how the conceptual framework might identify the CMPT learning research gaps for future research. The framework’s contribution to the body of knowledge expands our lens to understand team learning practices in the complex CMPT by considering CMPT as an MTS.

1. Introduction

Today, many megaprojects in the construction field are coupled with the science and technology boom. A megaproject is an ultracomplex project that generally costs over 1 billion dollars [1], such as the Hong Kong–Zhuhai–Macao Bridge. There is no doubt that the construction megaproject team (CMPT) is more complex. The CMPT comprises several individuals and interdisciplinary sub-teams through the project’s lifespan and spatially is distributed across the project sites [2]. The CMPT is initiated to implement megaprojects in a predefined time and budget. Megaprojects often encounter new problems that require the CMPT to grasp new knowledge, techniques, and skills [3]. The importance of knowledge learning for CMPT has frequently been studied.
Regarding team learning, some studies have emphasised the learning process [4,5,6], while others have focused on learning outcomes [7]. Both theory and research have been in the interest of understanding how project teams learn to work, how a project team as an entity learns to adapt and change [6,8,9,10], and how knowledge is shared and transferred between teams [11,12].
The journey towards sustainability is largely limited by practices in the construction industry, which is a significant generator of wastes and other anthropogenic emissions. Additionally, the increasing complexity and dynamics of the construction megaprojects cannot be overlooked. Therefore, it follows that transition to state-of-the-art construction technologies and methods by minimising the use of resources and anthropogenic pollutants. Learning in the construction megaproject will underpin the transition. The challenge in CMPT’s learning is integrating the different levels of learning. Construction megaprojects emphasise teams’ integration as a “team of teams”—or megaproject multiteam system (MTS)—to facilitate knowledge learning [13]. The conceptual framework plays a vital role in exploring how team learning occurs within and between teams in the complex context of construction megaprojects. The frameworks for identifying key variables and developing a shared language help pose testable hypotheses, sustain future study comparisons, improve the replicability of research, and direct practice. However, there is a lack of analysis on a conceptual framework to study the mechanisms of effective and multiple levels of CMPT learning in the domain of construction [14].
This paper aims to portray a conceptual framework indicating the inputs of the MTS structure and the CMPT learning processes, resulting in outcomes that are appropriate to grasp and facilitating CMPT learning. This synthesised framework integrates CMPT learning with the frameworks of team learning and MTS sciences. This paper builds on Shuffler’s summary MTS research framework [15]. It adopts the example of the island and tunnel project of the Hong Kong–Zhuhai–Macao Bridge (ITPHZMB) to describe the elements of the framework and related research questions [16]. This paper’s contribution to knowledge lies in the structure of a relatively new view of team learning in construction megaproject, that of MTS, in terms of a framework for (1) the way it unfolds in construction megaprojects and (2) the establishment of a research agenda and a context for understanding the positioning of and links between individual studies on the subject.

2. Literature Review

2.1. Team Learning Frameworks

In existing theories and research, team learning has concentrated on different levels of learning [17,18]. For example, it has been considered the collective of individual learning [7]. Accordingly, team learning has been viewed as the outcome of learning, embodied as a team’s knowledge, skill, or behaviour changing [17,19]. In addition, team learning has been defined as the learning process embodied as team making changes to adapt or improve [20]. Furthermore, team learning has been viewed as a dynamic process [18].
More specifically, the processes of team learning have been identified as the stages of learning [21], what teams learn during the process [22,23], and the interpersonal behaviours within and between teams [24]. Following this dynamic process view, Sessa defined a team learning framework including three behavioural processes: adaptive learning, generative learning, and transformative learning [6]. Thus, team learning could be viewed as a relatively permanent loop. All these processes of team learning are based on teamwork models in terms of inputs–processes–outputs [25], and their revised versions in terms of inputs–mediators, and/or moderators–outputs–subsequent inputs. Considering team learning in the construction industry, the importance of learning and microlevel learning processes, such as knowledge sharing [26], knowledge transfer [27], knowledge diffusion [28], and knowledge graph [29], have been discussed in existing research.

2.2. MTS Frameworks

Multiteam cooperation is one of the effective ways to deal with a complex environment and complete dynamic tasks [30]. Scholars represented by Mathieu et al. defined multiteam cooperation as a multiteam system from the perspective of system view [31]. The MTS refers to two or more teams interdependently responding to complex and dynamic environments, and all teams sharing at least one goal while pursuing different distal targets. While achieving these goals, a team is involved with at least one other team in terms of inputs, processes, and outcomes. The MTS breaks through the previous research on multiteam cooperation, and emphasises the integrity of multiteam, inter-team, and intra-team associations.
The MTS framework enables team science to further theorise the functionality of MTS. Zaccaro et al. developed an MTS framework differentiating intra-team processes from inter-team processes, identifying the compositional, linking, and developmental attributes that would influence those processes and outcomes [32]. Analogously, Shuffler’s input–mediator–output framework suggested that improving both intra-team and inter-team processes would make for MTS effectiveness [15]. Furthermore, Zaccaro et al. lucubrated how three MTS processes and states varied along three MTS attributes [33]. All these studies lay a good foundation for unfolding how MTS learns.
DeChurch et al. offered a valuable beginning to explore how to conceptually define MTS learning in their conceptual framework about organisational learning in MTS [34]. The learning processes in this framework focus on intra-team knowledge creation, retention, and inter-team knowledge transferring. Sessa et al. provided an integrative framework model focusing on how MTS learns [35,36], and this model was combined with the MTS case study centred on annual musical activities [37]. The framework mode indicates that the MTS learns continuously when constituent teams are ready to learn, and learning is triggered in MTS. The differentiation of learning in MTS is mainly related to the dynamic MTS structure over time.
The MTS science currently appears across a range of domains, including medicine [31], multiagency disaster response [38], business [39], military [40], health care delivery [41], and space exploration [42]. However, the literature on MTS in construction projects is limited. Only a few studies consider construction project teams as MTSs [43]. Therefore, the purpose of this paper is to leverage the existing research on MTS across disciplines to provide a conceptual framework for studying CMPT learning in the domain of construction projects.
In summary, team learning in construction project teams frequently emphasises individual learning and microlearning processes separately, without paying much attention to inter- and intra-team learning systematically. There is a need to develop a framework to further study team learning in CMPTs to achieve the sustainable project goal properly. This study extended the framework and its variables through four phases and, as presented in the following sections, clarified the framework with a case.

3. Methodology

Framework development went through four phases: a literature review phase, two workshop phases, and a case study phase. The first phase involved a literature search and review. Scholarly databases (e.g., Web of Science, Scopus) were searched using the keywords “multiteam systems,” “MTS,” “team learning,” “construction project,” “organization learning,” “megaproject,” and “AEC project.” The search yielded an initial set of over 200 journal articles, dissertations, book chapters, and conference proceedings. From this initial list, sources that did not address MTSs and team learning as per the literature [18,31] were removed, resulting in a final set of 57 sources. Theoretical sources were retained as part of the review, given the rare empirical sources available and the benefit of using theoretical work to help develop a draft framework.
In the second phase, an in-person workshop of over 20 contractors, subcontractors, and owners of construction megaprojects and researchers was held in November 2020. All the participants were over 35 years old. They all had a bachelor’s degree or above. The contractors, subcontractors, and owners all had been team leaders in civil engineering megaprojects for more than 9 years. Researchers were from a research institute and university, respectively, and all of them had more than 8 years of experience in the industry. The participants identified an overarching framework, key structure variables and their preliminary conceptualisations, and learning mechanism taxonomy, which set the tone for future research.
Subsequently, in the third phase, a small group of three management science and engineering researchers, three organisational science researchers, and three contractors attended the second workshop in March 2021. The researchers were from two universities, respectively, and had ample experience working in their fields. Both contractors had more than 5 years of experience as megaproject managers. The participants took a deep dive into the key structure variables and the additional variables from the integration of existing studies and engineering construction practices. All workshops were recorded for later analyses, and all participants agreed to the recording.
In the last phase of research, the case of ITPHZMB was used for further elaborating the framework. The ITPHZMB is a significant component of the Hong Kong–Zhuhai–Macao Bridge in China. It consisted of two 105-square-meter artificial islands and a 6.7 km immersed tube tunnel. The ITPHZMB was used to elaborate the framework because (1) it was a construction megaproject that cost over 13 billion yuan; (2) the design-construction union consisted of seven teams from China, USA, and Denmark, which was MTS as per the literature [43]; and (3) more than 140 experimental studies were carried out, and 540 patents were obtained during the construction period; in other words, team learning was present.
The aim was to highlight the seminal models and frameworks applicable to CMPT learning and not to conduct an exhaustive systematic review. Therefore, additional relevant frameworks or models may exist beyond those cited here. The ITPHZMB case is used to illustrate the concepts included in the framework and discern an MTS conceptual framework centred on CMPT learning in a construction megaproject.

4. CMPT Learning

4.1. MTS: A Perspective on Conceptualising and Facilitating the CMPT Learning

The nature of the CMPT is inter-organisational and temporary [44], which makes the CMPT learning research challenging. Meeting this challenge demands a conceptual consensus and shared understanding of the CMPT structure elements and constructs. The CMPT consists of several individuals and subteams from different parent organisations and/or branches assembled to accomplish a specific construction task as a collaborative “team of teams,” or MTS. The MTS requires collaboration and coordination within and between teams to adapt to changing complex environments and work toward at least a principal common goal [15,32].
In a construction megaproject, participants represent over four primary roles or disciplines, including owner, contractor, subcontractor, consultant, mechanical, electrical, glazing, structural, plumbing, fire protection, lighting, and controls engineers [43]. This paper defines CMPT as a complex entity composed of these participant teams. The relationship between these participant teams varies depending on how the construction project is delivered. The social relation and dynamic environment context of the CMPT are rich in information and ideas that can potentially trigger learning and create negative forces that can impede such learning. Learning often occurs within and between teams, and it is then diffused throughout the CMPT. This paper considers knowledge creation, retention, and transfer related to learning within and between teams [34]. This paper elaborates on the existing theoretical results of team learning and presents an integrated conceptual framework depicting CMPT learning from the MTS perspective.

4.2. An MTS Conceptual Framework for Research on CMPT Learning

At its core, our framework is built on Shuffler’s summary MTS research framework. It adopts parts of Sessa’s MTS learning model [15,36] that can be seen in Figure 1, following an input–mediator–output–input structure by incorporating feedback loops [45]. This framework consists of four different parts: inputs, mediators, outputs, and context.
This cyclical perspective stems from the temporally based phase model of the team process [31], where the outputs of prior performance episodes turn into the inputs of subsequent performance episodes. In Sessa’s MTS learning model [35], there are hiatus periods between performance episodes, during which constituent teams may deal with their business independently. Hiatus periods do not exist in the CMPT because of predefined time. The CMPT-MTS will dissolve, and teams will return to parent organisations and/or branches after completing the megaproject.
In addition, the inputs of this framework apply the MTS theory to depict structure features that directly influence the next processes within and between teams [32]. Next, the outputs of a team and MTS levels are described. Finally, the framework illustrates the synthetic role that environment characteristics, such as the complexity of a megaproject, may have in moderating effects (see Figure 1).
The following sections elaborately describe each of these model elements.

4.2.1. Inputs: Multiteam System Structure

To distinguish the MTS from other constructs and identify different types of MTS, Zaccaro et al. provided a feature typology that highlights the MTS features [32]. These traits have been classified into three types: constitutive attributes, linkage attributes, and developmental attributes.
The constitutive attributes are comprised of holistic demographic features of MTS and their constituent teams, and the linkage attributes comprise different mechanisms for connecting constituent teams. Lastly, the developmental attributes comprise characteristics that portray how the MTS is formed over time. Shuffler deemed that these three features would influence the inter- and intra-team processes within MTS [16].
Analogously, Luciano et al. posited two primary structural dimensions of MTS: differentiation and dynamism [46]. The differentiation refers to the difference and septation between constituent teams that create boundary-enhancing forces in time. The dynamism reflects the degree of stability or change experienced by MTS-constituent teams that may create disruption over time. These two overarching aspects depict structural shape and how structural changes arise over time. The differentiation and dynamism factors are inherent to the MTS and often difficult to directly alter. DeChurch et al. extended the two key structural dimensions of MTS to posit their impact on learning within and between teams [34].
Considering triggers that provoke a learning process response [47], Sessa deemed that they may arise from outside MTS (e.g., change in resources, new information, or directions from stakeholders), and also come from within MTS (e.g., constituent teams, personnel changes) [37]. This paper classifies the factors outside MTS as the context, and takes composition, linking, and developmental attributes of MTS as the inputs of the framework model (see Table 1). Studying in conjunction with compositional, linkage, and developmental characteristics, the attributes of MTS play an important role in unfolding the MTS science [15].
Our framework integrates several structural elements of the MTS model involving the CMPT. For instance, composition elements may include the number and type of teams working collaboratively toward the shared construction goal. Even a construction project involves multiple teams as owner, contractor, and consultant. A construction megaproject is a complex site condition, such as the ITPHZMB, where the White Dolphin National Nature Protecting Area increased the teams (e.g., The Chinese White Dolphin Protecting Administration) that composed the MTS and presented a greater challenge for coordinating teams on the issue of protecting the white dolphins.
It is worth mentioning that the megaproject delivery methods confirm the time of teams’ involvement in a megaproject and the contractual relationship among each team. Hence, the megaproject delivery mode is an important structure variable. The megaproject delivery mode is another MTS structure variable that refers to how constituent teams are linked. The most common methods include construction management at risk (CMR), design–bid–build (DBB), design–build (DB), and integrated project delivery (IPD). For example, IPD, probably the most collaborative approach, facilitates team learning. Conversely, DBB, theoretically the least collaborative approach, controls and limits knowledge transfer interactions between teams.
For instance, the delivery method of the ITPHZMB was engineering procurement construction (EPC). In this method, the contractor team from China Communications Construction Corporation was the leading team (see Figure 2), and the constituent teams were more inclined to share quality requirements and goals. Table 1 presents other aspects of crucial MTS constituent teams’ structures. Overall, the team structure variables in this framework are assumed to influence the learning processes that exist within and among constituent teams.

4.2.2. Mediators: Learning Mechanism of Intra- and Inter-Teams

Since Bandura put forward the Social Learning Theory about the influence of cognitive, behavioural, and environmental factors and their interaction on human behaviours [51], researchers [4,52,53] have applied this theory to the research issues about teams. However, from the limited existing research, affect and cognition are vital for MTS, especially in terms of how they influence and are influenced by behaviours [38,54]. Thus, affective processes and cognition in the MTS should be systematically grasped rather than studied separately, although this can be challenging.
Furthermore, many mediating factors linking inputs and outputs were found not to be behaviour processes, but to include collective affect and cognition [45]. Thus, the term learning mechanism has replaced the term process in the IMO framework models. The learning mechanism consists of affect, cognition, and learning process, as shown in Table 2 and Figure 1, and there is an interactive relationship between them. Most of the constructs originate from team-level searches.
Although learning often occurs within and between teams, existing research on learning in the MTS is limited. From the cognitive and social perspective, learning in groups consists of three processes: construction, co-construction of meaning, and constructive conflict [23]. On the contrary, Sessa proposed three learning processes: adaptive, generative, and transformative learning occurred considering how the MTS developed over time [37]. However, this paper leverages a meso-level lens through what is considered knowledge creation, retention, and transfer as they relate to learning within and between teams [34].
The positive affect, such as trust, cohesion, and efficacy, can promote knowledge learning [34] and psychological safety [4] in the MTS. Therefore, additional attention to affective states is necessary, which may be particularly critical for the CMPT-MTS. For example, how constituent teams and MTS perceive and respond to time, safety, and cost pressure that may impact learning and other affective states such as collective efficacy [12,62]. For example, the ITPHZMB teams built a “people-oriented” team culture to stimulate collective efficacy and cohesion that had the incentive to learn and work for the expertise teams [16].
When the CMPT-MTS exerts efforts on learning, using learning resources effectively is very important, especially under the pressure of time. Thus, when the constituent teams do not have a shared cognition basis, such as the shared mental models and the transactive memory, learning may be ineffective and time-consuming, which hampers the MTS implementing goals. The MTS shared mental model (SMM) refers to the similar cognitive structures or schemas of tasks and procedures, teams and people, and schedules and plans that are comprehended and held by constituent teams [60]. In addition, according to the transactive memory system (TMS) theory [63], CMPT-MTS has a shared cognitive division of labour for encoding, storing, and retrieving information and knowledge based on a shared understanding of one another’s expertise among constituent teams.
The highly expert MTS, such as the CMPT, possesses the SMM and the TMS that help decrease the cognitive burden on any individual team and enable constituent teams to work as one system. The constituent teams can perfectly mesh without requesting superfluous information and explanation. These cognitive states are also invaluable for learning [38,64].

4.2.3. Outputs: Multilevel Outcomes of CMPT Learning

The inputs and learning processes of the CMPT-MTS emerge as multilevel phenomena and they subsequently have multilevel outputs within and between teams. Although many existing studies regard team performance as a benefit from team learning, it does not always mean that the more learning occurs in a team, the better the team will perform [65]. It requires analysis within and between teams to unfold different outcomes at a team and MTS level (see Table 3).
These learning processes within and between teams aim to achieve the MTS overarching goals: project performance as well as teams’ task performance. Apart from that, learning in the CMPT may promote health, safety, and environment (HSE) performance at the MTS level and safety performance at the team level [12]. However, the maladaptive learning may hurt teams; therefore, at which stage the project team exists in its life cycle should be considered when determining whether the team should focus on one specific type of learning [65]. Similarly, Sessa deemed that the learning process should be in line with MTS development [35]. Extrapolating further upon these ideas, it may even be the case that the CMPT learning not only affects the development of teams but also their function in CMPT-MTS development.

4.2.4. Learning Loops

The inputs, mediators, and outputs discussed show how the CMPT-MTS learns. Furthermore, the CMPT is not only MTS; it also follows a cyclic mode, that is, the outputs of learning become the inputs of subsequent MTS learning over time [68].
Learning evolves over time, which means that at some point in time, the outcomes of the CMPT-MTS learning will influence inputs and define processes of how the constituent teams will learn and work in the future. For instance, at the end of a project task milestone, the CMPT should receive feedback from all constituent teams to advance their learning processes and improve future outcomes [31]. This feedback can be submitted both formally and informally at the team level or the MTS level.

4.2.5. Moderator Context

Finally, the contextual factors presented at the top of Figure 1 refer to all the factors outside the CMPT-MTS that may affect the relationship among inputs, mediators, and outputs. Modern construction megaprojects are complex projects operating in dynamic environments, meaning the context is complex and dynamic.
Depending on whether the context factors are time-dependent, they can be divided into two categories [69]. Specifically, the time-independent context is mainly related to structural features of a project that does not change over time (e.g., project size, goals, relationships between different components of the structures or facilities, and project site). Thus, the time-dependent context deals with the implementation behaviours of the project that has the potential to evolve over time (e.g., human behaviours, organisation culture, development in requirement and scope, social, political and economic, and weather conditions). The contextual factors may all influence the direction or intensity of interrelationships among inputs, processes, and outputs.

5. Discussion

This paper integrates MTS and team learning, which provides a practical understanding and analysis framework for the sustainable goals realisation in a construction megaproject. On the one hand, The MTS theory provides a comprehensive description of project teams and their collaboration goal scenarios. The MTS theory extends team learning to appropriately depict the learning process within and among project teams in a construction megaproject context. It also implies the prospect of the proposed framework being applied to other phases of megaproject, such as the design phase [70]. On the other hand, there are few context and performance variables. The complexity and resilience context of a construction megaproject have a double-edged influence on team learning [71]. The more details to portray the complexity and resilience of construction megaproject, the more truth the framework may explain [72]. More than that, the team learning process interlaces other team processes (e.g., work process [71]), which may make team learning process and team learning performance more complex. Bringing in other learning performance (e.g., task safety risks [73], customer value [74]) for this framework is feasible and needful.
This paper makes several contributions to the MTS and CMPT learning literature.
First, this paper has theoretical implications for expanding the application scenario of MTS. Through this paper, a better understanding of different theoretical elements related to CMPT learning (e.g., composition, linkage, and development) was obtained. Second, it is expected that the framework proves valuable for identifying key variables that affect the CMPT learning outcomes, which can inform testable hypotheses. By understanding how project teams form MTS and the MTS’s features that influence the learning processes emerging within and between teams to influence the project performance, the science and practice of CMPT learning can be advanced. Third, this paper facilitated a paradigm shift toward the meso-level learning process in the CMPT. Despite an abundance of studies on team learning process in construction projects, most of the previous studies provide a microlevel learning process or macrolevel learning outcomes [26,27,28,29]. CMPTs coming from multiple organisations form a system in pursuit of a common goal. In particular, many interorganisational rather than interpersonal collaborations fit the definition of MTS.
Furthermore, this paper offers several practical implications. The framework suggests a perspective to diagnose a CMPT’s learning potential for team leaders (e.g., project managers), which can be used to formulate learning interventions or how to structure the MTS context for learning to emerge more easily, in other words, how to recognise that learning is a process. The CMPT-MTS needs adaptive learners, collaborating component teams to follow regulation policies and agree to project procedures. It also needs generative and transformative learners, trying new methods, experimenting with and incorporating new technologies, and integrating new teams and individuals because severe pressures often emerge. In other words, it aims to help teams see the bigger picture and better understand their goals (e.g., sustainability, cost performance, schedule performance, etc.) in the megaproject. MTSs are open to ideas and information beyond the boundaries of the component teams, and the MTS itself is likely to revise routines and build new and more effective mental models in the complex environment.
There are some limitations in this research which should be addressed in future studies. Given that learning spans multiple phases of the CMPT-MTS, the CMPT-MTS requires differential inter- and intra-team learning processes at different points in time. For instance, the knowledge creation process, such as transactive memory system formation, is important for the early phase of the CMPT-MTS. However, this process is less important once the CMPT-MTS encounters the difficulty of a project task. At that point, knowledge transfer among teams and the boundary-spanning process would be more important to enable the CMPT-MTS to tackle the difficulty [71], which confirms that CMPT-MTS learning is dynamic and the genuine need for better understanding how the inputs, mediators, and contextual factors of the CMPT-MTS interact to affect the outputs. Some recent research on MTS employed social network analysis to explore the relationship between constituent teams [75,76], and we approve that it is necessary to leverage the network to better understand the interaction of constructs in this conceptual framework in the future. In addition, a qualitative comprehension of specific features of a megaproject and the CMPT-MTS may be preferable before embarking on the quantitative study.
In summary, the CMPT-MTS learning framework defines inputs, mediators, and outcomes in favour of comprehending and enhancing the learning performance of the CMPT. The innovation of the framework is that the MTS theory is applied, and the CMPT learning is unfolded with the MTS lens.

6. Conclusions

This paper aims to present a conceptual framework model of CMPT learning from the perspective of considering the CMPT as an MTS. An existing learning model is expanded from the individual and team levels to the MTS level, thus providing a systematic framework for enriching the knowledge of learning in the CMPT and the MTS. Future research can clarify that the inter- and intra-team learning processes are important at any phase of the CMPT via this framework. The key variables influencing CMPT-MTS learning can be identified. Subsequently, the testable hypotheses can be informed through this framework. The theory and practice of CMPT-MTS learning can be facilitated by comprehending how different teams form an MTS, how structural features affect learning processes within and among teams, and how learning processes affect team performance, a team’s development, and sustainability. Uncertainties are not captured well, and a holistic approach to capture uncertainty should be designed in the future [77].

Author Contributions

Conceptualisation, J.Z. and Y.C.; methodology, J.Z., Y.C., D.W. and Y.Z.; validation, J.Z. and Y.C.; formal analysis, J.Z., Y.C. and D.W.; investigation, J.Z., Y.C. and Y.Z.; resources, D.W. and Y.Z.; data curation, J.Z. and Y.C.; writing—original draft preparation, J.Z.; writing—review and editing, J.Z.; visualisation, J.Z. and Y.Z.; supervision, Y.C.; project administration, J.Z. and Y.C.; funding acquisition, Y.C. All authors have read and agreed to the published version of the manuscript.

Funding

The presented work has been funded by the National Natural Science Foundation of China (NSFC) under Grant No. 71371036, Hunan Provincial Natural Science Foundation of China (Grant No. 2021JJ40025), and Scientific Research Foundation of Hunan Provincial Education Department (Grant No. 20A093).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. CMPT-MTS Learning Conceptual Model.
Figure 1. CMPT-MTS Learning Conceptual Model.
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Figure 2. Composition of the contractor MTS in ITPHZMB [16].
Figure 2. Composition of the contractor MTS in ITPHZMB [16].
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Table
Table 1. Key Conceptual Model Variables, Definitions, and Examples of Inputs.
Table 1. Key Conceptual Model Variables, Definitions, and Examples of Inputs.
VariablesDefinitionsExamples (or Types)
CMPT-MTS compositionType and number of teams that symbiotically work together toward common goals [32].Case study: seven different expert teams from different organisations were mainly involved in the ITPHZMB-CMPT-MTS for 85 months (see Figure 2). The overarching goal was completing the island and tunnel project under predefined time and cost.
Boundary statusThe percentage of constituent teams that work in the same organisation and work context [32].Case study: teams comprising the ITPHZMB-CMPT-MTS all from different organisations, especially two foreign teams, makes coordinating across teams challenging.
Geographic dispersionDegree to which constituent teams are centralised vs. decentralised [32].Case study: teams were dispersed across construction segments and departments; however, the project management teams were collocated.
CMPT-MTS linkage
InterdependenceWays that inputs, processes, and outcomes among different constituent teams are correlative [48].Serial: some of the constituent teams formulate and complete their tasks, and then pass the work on to the next team.
Parallel: constituent teams work on different parts of the task parallelly in a non-interfering way.
Embedded: task requirements require the unanimous action of multiple constituent teams adjusting in real-time. The case study follows a closer form of collaboration, with interaction among construction teams and design teams.
HierarchyOrdering of constituent teams according to an arrangement of responsibility [32].Case study: China communications construction corporation was the initiator and leader of the ITPHZMB-CMPT-MTS; the CCPD was the leader of the design team (see Figure 2).
EmpowermentThe influence of constituent teams within the MTS [32].Case study: China communications construction corporation played a key role in the ITPHZMB-CMPT-MTS power distribution because they had the final say in all decision making. From an owner perspective, the owner team possesses financial power over project plans.
Experience or tenurePrevious project experience or expected duration within MTS of constituent teams [32].Case study: the project management team has established protocol and system for a long-term MTS across the project construction period, but peripheral teams (e.g., institute team, white dolphin conservation team) continually change according to the dynamic context.
Collaboration mechanismThe process of synchronising or aligning the constituent teams’ actions [49].Decentralised coordination structure: all constituent teams communicate freely with one another.
Centralised coordination structure: free communication is restricted.
Collaboration modalityThe modes in that constituent teams share information and resources within MTS [15].In-person, phone, virtual, BIM, etc.
CMPT-MTS development
Genesis and direction of developmentThe means with which MTS is started up, and the direction of MTS developing [15].Appointed MTS: specific structures in mind, in terms of leadership, workflow, linkages, and goal hierarchies, is typically designed. The case study was an appointed MTS.
Emergent MTS:
self-structuring and self-managing.
Membership and linkage constancyThe transformation of MTS composition [32].Case study: project management team was constant. Peripheral teams were fluid.
Delivery methodA method not only defines the roles and responsibilities of parties engaged in a project, but also defines the project implementation framework in terms of the sequence of activities, such as design, procurement, and construction [50]. The engineering procurement construction (EPC) method means that the owner entrusts an organisation to carry out the whole process or several stages of contracting for design, procurement, construction, and trial operation of a construction project in accordance with the contract. Generally, an organisation is responsible for the quality, safety, cost, and progress of construction projects in terms of the total price contract. The case study used an EPC method.
Table
Table 2. Key Conceptual Variables, Definitions, and Examples of Mediators.
Table 2. Key Conceptual Variables, Definitions, and Examples of Mediators.
VariablesDefinitionsExamples (or Types)
Intra- and inter-teams
Learning process
Knowledge creationGenerate new knowledge in organisations [55].Case study: The CMPT-MTS defines problems and then actively develops new knowledge to solve them.
Knowledge retentionEmbed knowledge in a repository so that it persists over a period of time [55].Case study: The archives kept in the CMPT-MTS and the work procedure embedded in the CMPT-MTS.
Knowledge transferProcess through which one unit (e.g., team, department, or division) is affected by the experience of another [56].Case study: Interaction between design teams and construction teams that can be divided as formal (e.g., meeting) and informal knowledge transfer (e.g., chatting with WeChat).
Affect
TrustA prerequisite in all endeavours concerning uncertainty and interdependencies [44].Members believe that other members and teams will fulfil their tasks well.
EfficacyPerceived speculation and judgment on particular performance [57].Collective efficacy is emergent motivational states at the teams and/or MTS.
Self-efficacy is perceived by individuals.
CohesionCommitment of each component team to each other and task [58].Within MTS, team members form interpersonal relationships that strengthen their commitment to each other and to constituent teams.
Perceived stressIndividuals’ and teams’ negative perceptions of tasks, conditions, and the situation [59].Case study: The CMPT-MTS is motivated due to clear goals, but they are also often time pressured.
Psychological safetyBelief that the team is safe for personal relationship risk [4].Team members would like to speak up about their thought within their team and to other teams without fear of being denounced.
Cognition
Shared mental modelsSharing and accuracy of mental models among teams [60].Case study: Teams hold a clear understanding of the project plan and procedure in common between teams.
Transactive memoryCooperative division of labour for learning, remembering, and communicating relevant team knowledge [61].Members understand who is responsible for each task within MTS and when each task should be accomplished during the construction period.
Table
Table 3. Key Conceptual Model Variables, Definitions, and Examples of Outputs.
Table 3. Key Conceptual Model Variables, Definitions, and Examples of Outputs.
VariablesDefinitionsExamples (or Types)
Project performanceMeasures outcomes during actual events and during training both within teams and across teams [35].Cost performance;
Schedule performance;
Quality performance.
Health, safety, environment (HSE)Measures performance of health and safety with due respect for the environment [66].Case study: The ITPHZMB-CMPT-MTS specified an HSE management system named “all staffs, full coverage, whole process,” that aimed to protect health, safety, and the environment.
Team development stageAssessment MTS and teams being at which stage [67].MTS and teams may develop at formation stage, shock stage, mature stage, and dissolution stage.
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Zhang, J.; Chen, Y.; Wang, D.; Zhang, Y. Learning in MTS of Construction Megaproject: A Conceptual Framework. Sustainability 2023, 15, 4295. https://doi.org/10.3390/su15054295

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Zhang J, Chen Y, Wang D, Zhang Y. Learning in MTS of Construction Megaproject: A Conceptual Framework. Sustainability. 2023; 15(5):4295. https://doi.org/10.3390/su15054295

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Zhang, Jinfan, Yun Chen, Da Wang, and Yinghui Zhang. 2023. "Learning in MTS of Construction Megaproject: A Conceptual Framework" Sustainability 15, no. 5: 4295. https://doi.org/10.3390/su15054295

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