Content area
Project management maturity models (PMMMs) provide structured approaches to evaluate and enhance project alignment with strategic and sustainability goals. We conducted a PRISMA-aligned systematic review of project management (PM) maturity in project-based organizations (PBOs) from 2010 to 2023, utilizing Scopus as the primary database, with supplementary searches in ProQuest and Google Scholar. PBOs play a key role in delivering infrastructure, energy, environmental initiatives that impact natural and socio-economic systems. Across the literature, sustainability emerges as a critical driver of maturity, with models like SPM3, PSM3, and the Sustainable Project Management Cube integrating economic, environmental, social indicators. Unlike traditional PMMMs, which focus on cost, time, and scope, these models integrate sustainability throughout the project lifecycle and provide prescriptive tools to support long-term resilience. Our findings indicate that while PM maturity models are crucial for performance in PBOs, their unique operational context necessitates models tailored to six key drivers: sustainability, structured frameworks, benchmarking, strategy formulation, continuous improvement, and technological advancement. Additionally, the maturation pathways differ between enterprise and intelligent PBOs, highlighting the need for adaptive, context-sensitive maturity assessments.
Introduction
Project success, attributed to project management (PM) success, is conceptualized and assessed in a multidimensional, dynamic, and holistic approach. As projects grow more complex, appraisal techniques must be continually reviewed and adapted [1, 2]. Over time, the concept of PM success is contingent on a multiplicity of perspectives, including considerations of the people involved in the assessment, the timing of the assessment, the criteria applied in the appraisal, the characteristics of the project, and the context in which the project is carried out [1]. Similarly, the success of PM outcomes is no longer judged solely by the traditional components (cost, time, scope, and quality) [3]. However, it is assessed based on the resultant benefits, commercial success, sustainability, efficiency in resource utilization, and satisfaction of different stakeholder categories [1]. In this context, the integration of sustainability into project management has gained significant relevance, reflecting a paradigm shift in how project success is defined and delivered. The literature widely considers sustainability as integral to project performance and recommends applying a triple-bottom-line lens, People, Planet, and Profit, to planning and execution, thereby aligning economic value creation with environmental stewardship and positive social outcomes [4]. Furthermore, sustainable project management requires embedding sustainability principles into project processes and decision-making frameworks, enabling organizations to make meaningful contributions to the Sustainable Development Goals (SDGs) while enhancing their strategic resilience [5].
At the policy level, sustainability in project management is increasingly policy-driven. Global frameworks, such as the UN 2030 Agenda for Sustainable Development and the Paris Agreement, are operationalized through national rules and policies, including climate transition and biodiversity strategies, as well as sustainability disclosures [6, 7–8]. National industrial and infrastructure policies, together with public procurement “social value” requirements, further embed sustainability into business cases, funding conditions, and stage-gate controls [9, 10].
Translating these frameworks into practice, policies, and corporate commitments are often executed through projects, temporary, and organizations used to deliver new products/systems and manage change [11, 12–13]. In project-based organizations, the project becomes the primary mechanism for coordinating core functions, placing PBOs where strategic intent is translated into delivery [12]. Work on strategy–project portfolio management and public-sector “projectification” further demonstrates this strategy-to-execution linkage [14, 15, 16–17]. Project-based organizing is characteristic of construction and infrastructure and other complex products and systems (CoPS) sectors (e.g., aerospace/defense/telecom), and is also used in pharmaceutical and biotech Research and Development (R&D) portfolios [12, 18].
The categorization proposed by [2] expands on the PM success criteria outlined by Pinto et al. [1], grouping them into short-term outcomes, such as cost and time efficiency, effectiveness, relevance, stakeholder satisfaction, project visibility, and long-term outcomes, including overall impact and sustainability. Despite the specificity of the PM body of knowledge (PMBOK) and other standardized guides for best practices and process guidelines under PM [19, 20] revealed that globally, 11.4% of the project costs go to waste, with the global failure rate estimated at 9.9% [21]. These wastes, which represent inefficiencies, are partly linked to the inability of the project managers to establish proper PM methodologies. One overlooked approach is the application of the tenets of PM maturity. PM maturity is an organization’s capacity to deliver the desired strategic outcomes from a project in a predictable, controllable, and reliable manner [22, 23]. PM maturity describes how and whether an organization can consistently and successfully deliver project performance goals within the PM success outcomes, as defined by the PM success criteria outlined in [1] and further supported by [24, 25]. PM maturity is defined using models that describe the best practices an organization should aim to adopt. As a reflection of the current state of the organization’s performance and achievements in terms of PM, the maturity models indicate the strengths and weaknesses of predetermined criteria [26]. The models can thus be used as benchmarks for PM within the organization.
Project-based organizations (PBOs) are businesses that use projects as their primary means of achieving organizational objectives and conducting operations [27] through a business model that integrates intelligent systems into PM practices and processes [28]. For PBOs, project success, PM success, and organizational performance are more correlated than for other organizations, since PBOs organize and implement their operations, tactics, and strategies around projects [29, 30–31]. PBOs operate under challenging conditions characterized by high complexity, intense global competition, demanding customers, and resource scarcity [30, 32]. Thus, robust PM maturity frameworks provide structured pathways enabling PBOs to systematically enhance their capabilities and performance, aligning project delivery with strategic objectives [30, 32, 33].
Numerous project management maturity models have emerged to help organizations assess and improve their project capabilities. These include the Organizational Project Management Maturity Model (OPM3) by the Project Management Institute (PMI), IPMA Delta by the International Project Management Association (IPMA), Axelos’s Portfolio, Programme, and Project Management Maturity Model (P3M3), and the Capability Maturity Model Integration (CMMI) by the Software Engineering Institute (SEI) [33, 34]. However, these models exhibit inherent limitations. OPM3, for instance, faces criticism due to subjective assessments at higher maturity levels [24]. IPMA Delta emphasizes individual competencies, potentially overlooking systematic process enhancements [34]. P3M3 simplifies multidimensional maturity into a single numeric level, masking nuances in different PM areas [35]. CMMI, originating from software engineering, requires substantial adaptation for broader PM contexts [24, 34].
Despite the extensive literature on PM maturity models, comprehensive reviews that explicitly target their applications and development within the unique operational context of PBOs are limited. Existing studies broadly categorize maturity models or evaluate their general applicability without focusing on project-based contexts [36, 37]. Therefore, a clear research gap exists regarding PM maturity model assessment and utility explicitly tailored for PBOs.
This systematic review aims to: (1) synthesize recent research on project management maturity in project-based organizations (PBOs); (2) compare leading PM maturity models, assessing their structure, applicability, and limitations in PBO contexts; (3) identify and evaluate key drivers of PM maturity in PBOs: sustainability, stakeholder engagement, continuous improvement, and technological advancement; and (4) clarify gaps and propose PBO-specific directions for future research. Collectively, the review advances theory and practice for aligning organizational PM capabilities with current industry standards and global policy frameworks.
Theoretical background
Project management (PM) maturity generally refers to an organization’s capability to consistently deliver project outcomes successfully by systematically improving its processes, practices, and competencies over time [38]. PM maturity models (PMMMs) are structured frameworks designed to evaluate, guide, and enhance this capability by defining maturity levels and assessing organizational practices against predefined benchmarks or standards [24]. Project-based organizations (PBOs) execute most of their strategic and operational tasks through projects, making adopting robust PM maturity frameworks critical for sustained competitive advantage and efficiency [23, 31].
In project-based settings, sustainability functions as a core design dimension of maturity. Integrating sustainability into project management practices requires structured frameworks that enable organizations to measure, manage, and improve their capabilities systematically. PMMMs provide structured assessments that help organizations effectively align their project management processes with sustainability principles [39, 40]. The adoption of sustainable practices within project management not only reduces costs but also increases opportunities and profits, thereby facilitating organizational success. However, organizations should recognize that sustainability entails additional investments in natural resources and finances to ensure project success [41]. The Sustainable Project Management Maturity Model (SPM3) is a dual-purpose tool, both descriptive and prescriptive, that assesses the extent to which sustainability is integrated into project processes and outcomes. It utilizes four maturity levels, Compliant, Reactive, Proactive, and Purpose, across economic, environmental, and social indicators, guiding organizations from basic compliance toward sustainability-driven project strategies [42].
Several researchers have attempted to classify PM maturity models. Kostalova and Tetrevova [35] classified PM maturity based on the assessment method used. Out of 29 models, 14 were found to be process-oriented, four were classified as organization-oriented, and the remaining 11 were categorized as competence-oriented. The classification focuses on the structure of the PM maturity models without delving into the substance of the elements that influence maturity.
Another classification by Fabbro and Tonchia [24] employs a multidimensional approach, dividing PM maturity models into three distinct categories. The first category includes models developed by prominent PM institutions and bodies, characterized by established theoretical foundations and unique structures [29]. Examples include the Organizational Project Management Maturity Model (OPM3), developed by the Project Management Institute (PMI), which assesses an organization’s capability to align strategic planning and achieve predictable outcomes through project, program, and portfolio management [43]. While OPM3 provides robust guidance grounded in best practices [34, 44], studies have noted difficulties in objectively determining whether an organization has truly achieved certain Key Performance Areas (KPA) outcomes (e.g., “standardized” or “controlled” processes), leading to elements of subjective judgment in OPM3 assessments [45, 46, 47–48]. From a systems theory perspective, OPM3 integrates multiple layers, aligning tactical and strategic dimensions, thus fostering comprehensive maturity [38]. Another Category 1 model is the International Project Management Association’s IPMA Delta [38, 49], which emphasizes certification and individual competence through training and mentoring. Under this model, PM maturity extends beyond processes that are insufficient in delivering the targeted results and outcomes under the PM [49, 50]. The recognition of individual competence has enabled maturity under the IPMA Delta model to consider the organization’s resource-based view, while also acknowledging its dynamic capabilities [38]. The maturity assessment under IPMA Delta focuses on maturity within each module, namely, Individuals (I), Projects (P), and Organizations (O), as these constituents are integral to achieving PM success and determining the aggregate maturity across the three domains [24].
A third prominent model in Category 1 is (P3M3) by Axelos [50]. The P3M3 enables organizations to focus on the maturity of their projects, which are sometimes designed to fulfill a particular program or classified into a portfolio [27]. The maturity framework is thus integral for public-sector institutions, which rely on programs, projects, and portfolios to achieve their institutional goals [45]. Despite its uniqueness, the P3M3 utilizes maturity levels similar to Capability Maturity Model Integration (CMMI), although it has a 5-phase maturity trajectory [34]. However, a noted drawback of P3M3 is its reduction of organizational maturity to a single overall score, which can oversimplify the diagnosis. Nevertheless, by offering sub-models for projects, programs, and portfolios (PjM3, PgM3, and PfM3), P3M3 provides a more systemic view of organizational project management capability than models focusing only on individual projects [47, 51, 52]. These Category 1 models have gained wide adoption, particularly in organizations already aligned with PMI, IPMA, or Axelos standards. Their popularity stems from their institutional support and the credibility of well-established PM bodies of knowledge. By contrast, outside these standards, many researchers and companies have proposed alternative PM maturity models tailored to specific needs or contexts.
Category 2 of Fabbro and Tonchia’s classification includes the most historically prominent and extensively validated models [24]. Examples are the Berkeley PM process maturity model (PM2) [53], CMMI [54], Kerzner’s project management maturity model (PMMM) [55], PM maturity models by PM Solutions [56], and Prado’s PM maturity model [22]. Due to extensive application and empirical testing, these models have been evaluated in various contexts, both theoretically and practically, leading to their refinement and appraisal. For example, a study found that among nine evaluated models, only Prado’s project management maturity model was positively rated for use in construction firms, as it required no contingencies during implementation and utilized a survey-based assessment approach suitable for most organizations [57]. Maturity is assessed across seven key areas. Similarly, the CMMI, was developed in 1999 based on the Capability Maturity Management (CMM) model from 1986 [24, 34]. Over time, the CMMI has been enhanced to feature two representations: one based on the CMM, which has a 5-phase maturation pathway, and the other offers a continuous maturation pathway for each maturity level [34].
Category three as defined by Fabbro and Tonchia [24] encompasses the most recent maturity models, including the Sustainable PM maturity model [36], the Management Maturity Model (MMM) [27], and the National Project Management Maturity Model (NPM3). These maturity models are designed using knowledge and techniques for PM maturity modeling that have been developed over time. This shift to a shorter maturation path emphasizes adaptability and efficiency, recognizing that not all organizations require a five-tier structure, while maintaining rigor in evaluation. In contrast, the earliest model, the CMM, was first conceptualized in 1989, and later improved into the CMMI [47].
Overall, Fabbro and Tonchia’s classifications offer a more insightful perspective on the characteristics of PM maturity models. Over time, the existing PM models have been refined, with changes to their structure and underlying PM theoretical bases. However, despite these advancements, researchers have identified several persistent challenges with existing PM maturity models.
Key limitations noted in the literature include: First, the PM maturity models are inflexible in their structure and levers, which limits their applicability to the dynamic environment in which they are applied [23, 58]. The structured assessment methodologies account for the inflexibility, considering that they do not leave room for customization based on the characteristics of the project or organization. The inflexibility of the model constrained the ability of management teams to adapt it to the specific requirements and contextual nuances of the projects they were undertaking. Second, PM maturity models are designed to identify problems and raise awareness about the issue’s existence but do not offer solutions other than the generic propositions that can be inferred from the maturation path [24, 59]. Since they are based on assessing how successful an organization is in relation to particular criteria, they indicate the areas where the institution has fallen short; however, no models to highlight how an organization can match PM maturity and performance [59]. Although a study finds a direct link between PM maturity and organizational performance, the benefits appear temporary [60]. Third, the models fail to account for the rapid pace of transformation driven by technology, as well as other processes, management systems, policies, and practices [61, 62]. Technological changes play a key role since they influence all PM knowledge areas, as well as the capabilities of the project personnel [63]. Considering that PM maturity models are focused on creating an efficient and effective function system rather than controlling the results, considerations of how technology influences this outcome are integral to appreciating the entirety of the role of maturity models [57, 64].
Fourth, the maturation pathway, comprising five levels, does not accommodate the depth of detail required for measuring progress in every type of organization and for every type of project in which the organization is involved, in terms of time and space [36]. Essentially, this implicates the need for changes to the preferred PM maturity model, or the use of multiple models [64]. While the most recent maturity models, classified by Fabbro and Tonchia, feature a maturation pathway with four levels, they are still based on the same principle that the change representing maturation should be a quantitative standard across all levels [24, 65].
Fifth, the models focus on work processes, while overlooking certain organizational aspects, such as the contribution of human resources [25]. Unlike other categories of resources, human resources contribute to PM in a highly flexible manner [25, 47]. The capabilities of project personnel can be repurposed and re-tasked based on the circumstances. Furthermore, human resources are creative and intelligent, thus allowing them to amplify their contribution to PM. The oversight explains why most PM maturity models overlook the role of culture, as well as how it can play a direct or mediating role in influencing PM outcomes [60, 66]. The two studies concur that a hierarchical cultural orientation, which revolves around the control and formalization of processes to ensure efficiency and schedule adherence, affects PM performance the most.
Finally, PM maturity models are theoretically limited since they are based on software maturity models derived from CMM, which lacks a theoretical basis [35, 55]. The lack of a theoretical basis arises from the limited details on process dynamics, which makes it obscure as a basis for the discussion on the link between practices and maturity levels [45]. The available empirical support can be easily construed as support for other models [24]. However, the success of CMM in practice and its theoretical viability have contributed to the development of over 30 models based on its core principles [48]. Although some of the more recent PM maturity models have been customized to feature extensive and specific theories and principles of PM, they still contain legacy elements from the original model.
Methods
Following a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-guided protocol, we ran a systematic literature review. By combining content analysis and systematic literature review, critical contributions are provided from the most recent and impactful publications on the research topic. The methodologies are integral in eliminating biases while eliciting transparency in how the articles are selected and analyzed. The analytical approach is outlined in Table 1.
Table 1. Summary of review methods, purpose, and key parameters
Stage/title | Purpose | Key parameters |
|---|---|---|
Study design (PRISMA) | Frame scope and ensure replicability | PRISMA flow and documented protocol |
Eligibility criteria | Define inclusion/exclusion | Peer-reviewed journals; PM maturity focus; validity screens (content, construct, descriptive, external, statistical-conclusion) |
Data sources | Select literature bases | Primary: Scopus; supplemental manual: ProQuest, Google Scholar |
Search and initial screening | Map the field for taxonomy/overview | Query: “project management maturity model” AND “project-based organization/firm”; apply eligibility consistently |
Risk of bias and reliability | Reduce selection/interpretation bias | Selective reporting checks; multi-author cross-checking |
Extraction and Analysis of Data | Build evidence for analysis | Combine literature and content analysis to derive MM traits, a PBO-specific framework, and key development challenges |
Study design
The review is conducted using the PRISMA approach. The process entails standardized approaches to reviewing existing literature, focusing on the identification, screening, and assessment of the eligibility of the articles to be included in the review [67]. The PRISMA approach is preferred over other alternatives since it demonstrates the quality of the review, highlights the strengths and weaknesses of the review to the readers, and can be replicated for subsequent reviews [68]. Additionally, the PRISMA method facilitates systematic documentation, thus enhancing the transparency and reproducibility of the review process [69]. In line with the proposed structure for reviews developed through PRISMA by [70], the review identifies the research problem and the research aims to be fulfilled.
Criteria for eligibility
The articles included in this review are based on the criteria included hereunder. All publications included are English-language journals published between 2010 and 2023, with a focus on PM maturity. The publications that did not meet the inclusion criteria, including those published before the cutoff date, as well as books, conference proceedings, lectures, and those published in a language other than English, were excluded. The selection of publications was also based on certain aspects of validity, including the following. To ensure robustness, additional validity criteria were applied to rigorously screen articles. These criteria are summarized in Table 2 and include content validity, construct validity, descriptive validity, external validity, and statistical conclusive validity.
Table 2. Validity criteria for screening articles
Criteria | Definition |
|---|---|
Content validity | Matching test items and variables with the objectives of the study |
Construct validity | The extent to which the test measures the theoretical construct or variable |
Descriptive validity | The degree to which the information gathered in the study is objective and accurate |
External validity | The degree to which the findings from the study can be generalized to other institutions |
Statistical conclusive validity | The extent to which the conclusions regarding the maturity models are logical and sequential |
Data sources
The researchers used Scopus to identify the targeted studies. The database was the preferred source of information since it offers a robust and broad coverage of publications in different research fields [71]. Additionally, a manual search was performed on ProQuest and Google Scholar for articles that provide additional context to the analysis. These additional searches ensured comprehensive literature coverage and minimized database-specific biases. The articles were then screened through the criteria provided by [68, 70, 71] for systematic analysis.
Information search
A search string was developed, encompassing ‘PM maturity models’ and ‘project-based organizations, which are derived from the main topic of the review. Variations such as ‘project-based firms’ were also included for terminological diversity within the existing literature. Three hundred fifty-seven publications were collected during the review’s ‘Collection of Literature Phase.’ A review of the publications revealed several common terms, all of which reference the development, application, and review of maturity models for various industries. After applying the inclusion and exclusion criteria, 101 publications were included in the analysis. During the ‘Extraction and Synthesis of the Data,’ the guidelines on testing for validity outlined by [72, 73] were applied, the three types of validity culminated in selecting studies presenting accurate results from diverse standpoints.
Addressing the risk of bias
The three types of validity culminated in the selection of studies presenting accurate results from diverse standpoints [74]. To address potential biases, careful consideration was given to selecting studies that were free from conflicts of interest and selective reporting. Since the articles were extracted primarily from reliable sources, none of the studies were excluded due to biased rationales. Additionally, cross-checking and peer-review among multiple authors were performed to minimize selection bias and ensure objectivity in the selection and analysis of the articles [75, 76].
Extraction and analysis of data
The data analysis process involved additional review and screening of the selected articles. An additional full-text review was conducted on the 357 articles, resulting in a total of 64 articles in the final analysis.
The data was analyzed through qualitative content analysis, whereby the synthesis of the qualitative and survey studies was aggregated through quantitative means [74]. The bases of convergence in the codes were then classified and reported as sub-themes [76]. The sub-themes were further aggregated into themes to fulfill the two objectives of the review. All the authors reviewed the appropriateness of the identified sub-themes and themes, with the selection and description based on consensus to eliminate disagreements [47]. All authors reviewed the coding and thematic aggregation to achieve consensus and minimize interpretative bias. This collaborative approach ensured the high reliability and validity of the identified themes [77, 78].
Results
A taxonomy of generic PM maturity models
Distribution based on maturity models
An analysis of the selected publications highlights that multiple studies apply different PM maturity models. The most frequently utilized model is the generic PMMM, confirming its foundational role in maturity model research. The distribution of models across selected studies is shown in Fig. 1 and Table 3.
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Fig. 1
Frequency of maturity model usage in reviewed studies
Table 3. Distribution of reviewed studies by maturity model
Maturity model | References |
|---|---|
PMMM | [3, 21, 23, 38, 44, 55, 79, 80, 81–82] |
CMM | [24, 83] |
OPM3 | [43, 45, 84, 85] |
P3M3 | [52, 86] |
Kerzner Project Management Maturity Model (KPM3) | [87] |
PM2TOM2 | [53] |
PRMM | [32] |
IP3M | [33, 49] |
Different methods | [22, 24, 27, 28–29, 34, 47, 50, 53, 62, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99–100] |
Distribution based on methodologies
Quantitative methodologies dominate the research on PM maturity, primarily to investigate the effects of maturity on project success and performance. Qualitative methods, including case studies and conceptual analyses, are also extensively applied, particularly where knowledge of maturity models remains exploratory. Figure 2 and Table 4 summarize the methodological distribution.
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Fig. 2
Classification of reviewed studies based on research methodology
Table 4. Classification based on methodology
Methodology | References |
|---|---|
Quantitative | [3, 32, 43, 45, 52, 55, 62, 79, 81, 84, 87, 88, 89–90, 94, 96, 99, 101, 102–103] |
Qualitative | [21, 33, 44, 46, 86, 89, 104, 105, 106, 107, 108, 109, 110, 111–112] |
Systematic review | [1, 5, 22, 29, 34, 36, 38, 41, 48, 92, 95, 113, 114–115] |
Conceptual papers | [2, 23, 24–25, 49, 63, 91, 93, 98, 116, 117, 118–119] |
Multi-methods | [97, 100] |
Framework for optimal maturity model for PBOs
A structured approach was identified, comprising five phases crucial for designing maturity models tailored for PBOs. However, the literature lacks clarity on the prioritization or relative importance of these phases. Table 5 presents a structured framework that outlines key categories and subcategories for developing maturity models in PBOs, highlighting objectives, outcomes, maturation paths, and phases.
Table 5. Design process for project management maturity models
Category | Subcategory | Explanation |
|---|---|---|
Objectives of maturity model | Descriptive | Backward-looking analysis |
Prescriptive | Forward-looking analysis | |
Comparative | Benchmark against an industry | |
Outcomes | PM Success | Time, Cost, Scope, and Quality |
Project Success | Achieve business goals | |
PM Performance | Strategy, governance, technology, people, culture, customers, leadership, and operations | |
Maturation Path | Staged | Different goals and outcomes in each phase |
Continuous | Similar goals and outcomes in each phase | |
Recognition of Maturity | Absolute | – |
Partial | – | |
Maturation Phases | Four phases | Nascent, Developing, Adolescent, and Mature |
Five phases | Initial, Managed, Defined, Quantitative Managed, and Optimizing |
In the first phase, the design process involves determining the objectives of the maturity model, whether descriptive (a backward-looking model to indicate what the organization has achieved), prescriptive (a forward-looking model to propose what the organization seeks to achieve), or comparative (comparing two entities or circumstances). The phase involves determining what data to use and how to analyze it.
In the second step, the goals of the maturity model are identified, including whether the institution seeks to use the maturity model to achieve PM success, project success, or project performance [3, 19]. The selected goals influence the levers of maturity for the PBO and whether they can be applied for descriptive, prescriptive, and comparative purposes.
In the third phase, the PBO selects the maturation path, depending on whether it seeks a staged or continuous maturation approach. Unlike continuous paths, staged maturation paths recognize that each phase has distinct goals and outcomes [27, 47, 62]. Under the continuous paths to maturation, the PBO relies on similar resources, capabilities, and goals throughout [30, 31]. Homogeneity contributes to the possibility of a steep learning curve, unlike in the case of staged maturation paths, where each phase presents novel challenges and opportunities.
In the fourth phase, the PBO must determine whether maturity in each phase is recognized absolutely or partially. Partial maturation occurs when the PBO transitions the firm from the current maturity level to a higher level after it has achieved a significant part of the requirements for maturation [34, 52]. On the contrary, under the ‘absolute’ models, the PBO only recognizes change once all the dimensions have been attained.
In the fifth phase, the PBO adopts a maturity model featuring three, five, or six phases. While contemporary maturity models feature five phases [45, 47], PBOs have identified custom maturation trajectories featuring different phases to accommodate the unique projects in which they are involved. The number of phases the PBO adopts indicates how intricate the institution perceives the maturation process.
By aligning these categories with the unique structure of PBOs, particularly their temporary governance and outcome-driven focus, this framework can guide the development of customized maturity models that are both adaptable and sustainable.
Discussion
This section synthesizes the literature on PM maturity models tailored explicitly to project-based organizations (PBOs). It begins by examining available maturity models and progresses toward methods of assessing maturity, ultimately identifying the key drivers that influence the implementation of these models. The discussion also highlights critical gaps and future directions for enhancing the effectiveness of maturity modeling in PBO contexts.
PM maturity models for PBOs
The scarcity of research interest in this area can be attributed to the presumption that all perspectives of PM maturity relevant to PBOs have been covered in past studies that relate to PM maturity models for contemporary organizations. PBOs can rely on the existing PM maturity models since these maturity models are designed for use in an environment where decisions and operations are guided by theories on PM [22]. Early research by Yazici [65] utilized the OP3M framework to demonstrate how PM maturity and organizational culture impact perceived performance among PBOs. On the contrary, [31, 65] argue that PBOs are involved in interdisciplinary work that involves complex problem-solving scenarios. The differences in the successive projects, programs, or portfolios they are involved in lead to ‘projectification’, which has implications for the operative and strategic management mechanisms of the institutions [98]. The complexities of ‘projectification’ have led to the development of customized maturity models tailored to the complex functions undertaken by PBOs. For instance, Pereira [105] designed a knowledge management (KM) maturity model for PBOs. The model is based on the KM cycle phases for European PBOs, with the primary goal of establishing an effective approach for PBOs to achieve organizational learning. The study reveals that while most organizations have achieved half of what is necessary to implement KM systems, they lack the prerequisite infrastructure needed to support the entire process within the context of PBOs [105]. While the technological changes have solved a number of the challenges in KM as identified by [90, 105], they serve as stopgap measures, which fail to fulfill the criteria for PM success (multidimensional, dynamic, and holistic) as outlined by [1].
Enterprise/strategic PBOs
While most emergent maturity models are designed using unique methodologies, Tahri and Drissi-Kaitouni conceptualized maturity sequentially [98]. The design facilitated the assessment of maturity levels while providing a trajectory for improvement in maturity in line with the prevailing market and environmental demands [94]. The specificity of the attributes under each phase of maturation facilitated comparative analysis among institutions while also enabling those institutions to respond to industry benchmarks promptly. The approach recognized the integral nature of the PDCA cycle as a tool for continuous improvement among strategic PBOs, while accounting for variations in attributes at each level of maturity, as shown in Table 6 [98].
Table 6. Strategic PBO maturity models [98]
Dimension | N1: Reactive | N2: Disciplined | N3: Adjusted | N4: Effective | N5: Optimized |
|---|---|---|---|---|---|
D1: Methodology | C111 | C121 | C131 | C141 | C151 |
C112 | C122 | C132 | C142 | C152 | |
C113 | C123 | C133 | C143 | C153 | |
C114 | C124 | C134 | C144 | C154 | |
C145 | C155 | ||||
D2: IT Resources | C211 | C221 | C231 | C241 | C251 |
C232 | C242 | C252 | |||
C233 | |||||
D3: Managerial Skills | C311 | C321 | C331 | C341 | C351 |
C312 | C322 | C332 | C342 | C352 | |
C323 | C333 | C343 | C353 | ||
C334 | |||||
D4: Relationship | C411 | C421 | C431 | C441 | C451 |
D5: Communication | C511 | C521 | C531 | C541 | C551 |
The framework reveals that organizations at lower maturity levels (NI) have a qualitatively and quantitatively lower load in terms of attributes compared to those at higher maturity levels (N5). These levers are related to the non-process factors, such as relationships and communication. However, a critical limitation could be the reduced emphasis on process-oriented elements, which may lead to an imbalance at the initial stages of maturity development.
The intelligent PM maturity model (IP3M)
The IP3M, which is developed for intelligent PBOs, is a system-based model that balances stability and rigidity [33]. This aligns with the findings by [92, 96], who indicated that most emergent PM maturity models are derived from the principles used to develop past models, with the early models being derived from the CMM [55]. In designing these maturity models for intelligent PBO, a study [33] identifies the new business model dimensions that are integral in the maturation path, including project management (PM), competitive intelligence (CI), business intelligence (BI), KM, and governance. Although the IP3M features five levels, like other PM maturity models discussed earlier, the uniqueness in its design arises from the structure and sub-dimensions under each level and how they are applied to various processes and functions within the organization, as shown in Table 6. First, it is also the only model that utilizes the partial recognition of maturity, albeit at the lowest and highest maturity levels. As a result, organizations classified at the same level of maturity can be perceived as having different PM capabilities. Second, the model incorporates a broader range of categories among the levers of maturity, including non-process factors such as input from human thought and workgroup practices, which are integral to real-life organizational processes. Third, PM maturity is separated from other categories of levers under maturity levels 1 to 3, ensuring that the PBO does not overlook other aspects of management, such as KM, BI, CI, and Governance. The separation of these factors enhances the firm’s ability to identify problem areas affecting PBO maturity and design the right interventions based on the specific challenge. The framework is shown in Table 7.
Table 7. Maturity levels of IP3M [33]
Maturity level | Definition | PM | KM, BI, CI, and Governance |
|---|---|---|---|
Level 0 | Unawareness | No data governance No Business intelligence No PM processes—Ad hoc Dispersion of data sources No documentation of required information No initiatives for knowledge capitation | |
Level 1 | Asset identification | 100% defined PM processes 60% application of PM processes | 100% at BI 100% at CI 100% Governance 100% of the definition of KM processes and 60% apply to most projects |
Level 2 | Intelligence awareness | The generalization for all projects | BI, CI, KM, and governance processes are 100% applied |
Level 3 | Intelligence utilization | Decision-making and problem-solving | Fully generalized to all PM activities Applied to the key projects |
Level 4 | Competitive leverage | Optimization and adaptability | |
The strategies applied in developing PM maturity models for contemporary organizations inform the methodologies used to improve the maturity models for enterprise/strategic PBOs, creating intelligent PM maturity models for PBOs. The design presented herein addresses several of the challenges identified in the theoretical background. First, the lack of specificity in the time it takes to transition from Level 0 to Level 4 challenges strategists interested in marking success on a period basis and matching those benefits (some of which are financial) with the associated costs [22, 49, 81]. Second, while the blending of qualitative and quantitative levers of maturity in some phases increases the clarity of what the maturation path entails (Phases 1, 2, and 3), it still does not simplify the work of project managers who seek to utilize the tool for strategy formulation and implementation [33, 63]. For instance, the requirement for the 60% application of PM processes under Level 1 leads to obscurity and disparity in interpretation by management teams within different contexts or organizations. Finally, the structure of the maturation path, which converges to ‘Optimization and adaptability’, is perceived as capable of turning the organization into risk intolerance [33, 63]. At this level, the organization risks missing out on the benefits of taking certain risks, which have the potential for huge payoffs, as they would lose their maturity rating.
The utility of custom PBO maturity models discussed in section “A taxonomy of generic PM maturity models” reveals that it is possible for project managers to further calibrate the maturation pathways and the levers of maturity to fit the project-based environment in which the organization operates. Past studies have outlined how to measure PM maturity [2, 62] with a specific focus on what data is collected, how and from whom, as well as the philosophical foundations for the analytical processes [21, 86, 88]. While most studies rely on quantitative methodologies, it is apparent that qualitative approaches have led to a shift from the generic 5-phase maturity model featuring a continuous maturation trajectory derived from the traditional CMM. The methodology of assessing PM maturity is closely linked to the assessment outcomes [1, 89, 99, 120]. Whether generic or PBO-specific, PM maturity models exhibit considerable variability dependent on context, as identified by [79], and further supported by [1]. Furthermore, while there are similarities in the characteristics of PM outcomes at low levels of maturity, the characteristics differ significantly at higher maturity levels, commensurate with the PM performance outcomes that can be achieved in those levels [1, 19].
Assessment of PM maturity for PBOs
Assessment of PM maturity involves several underlying assumptions regarding methodologies and practical considerations. First, PM competencies can be accurately estimated, leading to the objective quantification of the determinants [2]. The premise originates from the capability perspective in quality management, whereby changes in outcomes across the 10 PMBOK areas can be controlled based on preset parameters [80]. While this assumption is correct for PM in some sectors, such as manufacturing and construction [107], it is not applicable in information technology (IT) or information systems (IS) PM areas where interactions between/among humans are integral to success [93]. This is why the assessment of maturity under such circumstances has to rely on subjectively determined constructs. The process combines objective and subjective assessment methodologies for PBOs involved in multifaceted projects.
Moreover, PBOs often operate in dynamic environments where external variables, such as stakeholder demands, regulatory shifts, or environmental constraints, can disrupt standardized assessments [121]. This further requires adaptive maturity assessment tools that capture non-linear and emergent progress. Second, it is presumed that project managers agree on the universality of PM practices, hence the convergence in the characteristics of the quantitative methodologies applied in past studies. However, research on PM practices, starting with the PMBOK and the multiplicity of theoretical bases for PM reveals that these practices are contextual rather than universal [33, 100]. Different sectors emphasize different KPAs, for example, stakeholder engagement is more critical in non-governmental organizations (NGOs) and development sectors, while risk control may dominate in aerospace or defense projects. The findings explain why there are over 30 primary PM maturity models, with additional models designed to target specific industry-specific or organizational contexts based on the particular PM context. Finally, PM maturity models have a preset path of maturation, based on a unidirectional change in the determinants of change [33, 97]. However, alternative patterns for the evolution of the firm’s maturation accommodate the variations in the change within the institution. This is why most PM maturity models provided hereunder have flexible maturation paths, enabling firms to improve their PM practices from their status quo.
In addition, the growing role of digital transformation and data analytics has opened up possibilities for real-time, adaptive PM maturity assessments using AI-supported dashboards and feedback loops. These innovations enable organizations to track maturity evolution more responsively, supporting continuous improvement beyond linear models [122, 123].
Drivers of applying PM maturity models for PBOs
Since PBOs are unique in their reliance on projects within their tactical, operational, and strategic norms, it becomes evident that existing maturity models often overlook critical drivers such as risk management and stakeholder management. Typically, these areas are fulfilled as standalone managerial functions in contemporary organizations, and thus, maturity models frequently omit them. However, for PBOs, such functions must be integrated explicitly into each project’s lifecycle, emphasizing the necessity of including these capabilities as inherent maturity drivers. This limitation highlights a significant gap in existing frameworks, underscoring the importance of comprehensively examining all drivers.
The effectiveness and practical application of maturity models discussed previously (sections “PM maturity models for PBOs” and “Assessment of PM maturity for PBOs”) depend significantly on several drivers. These drivers, described below, underline why PBOs actively adopt and customize maturity modeling frameworks to suit their strategic, tactical, and operational needs.
Sustainability integration in PBOs
The PMMMs examined in the manuscript primarily focus on improving processes and capabilities, with only limited explicit integration of sustainability. Classic models were not designed initially around the triple bottom line; their primary concern is strengthening project execution and alignment with strategic goals such as time, cost, and quality [36]. As a result, economic aspects are implicitly addressed through efficiency and the realization of benefits. However, dedicated environmental stewardship or social impact criteria are generally absent [36, 124]. While project managers increasingly acknowledge the relevance of sustainability, its application in practice remains uneven, often concentrated on economic gains such as cost-efficiency and competitive advantage. Social and environmental dimensions, although recognized as important, are frequently treated as secondary considerations or addressed only when aligned with immediate business goals. This imbalance reflects a gap in current maturity models, which rarely embed sustainability holistically across all dimensions of project performance [125].
Recent peer-reviewed literature has begun to fill this gap by proposing dedicated maturity models integrating sustainability principles into project management. A recent review reported that, among more than 70 PM maturity models, only three explicitly address sustainability [126]. Silvius and Schipper’s Sustainable Project Management Maturity Model (SPM3) is a prominent example. SPM3 assesses project processes and outputs for their sustainability integration, evaluating to what extent project management practices and deliverables align with the triple bottom line of People, Planet, and Profit. This model defines four incremental maturity levels in the way sustainability is embedded, ranging from Level 1: Compliant (where sustainability is only minimally and implicitly considered, primarily to meet regulatory requirements) to Level 4: Purpose (where sustainability is a core driver and justification for the project). At higher levels, organizations transition from reactive risk mitigation (reducing negative impacts) to proactive value creation (delivering positive social and environmental benefits alongside economic gains) [126]. The SPM3 thus incorporates explicit economic, environmental, and social indicators at each stage, reflecting principles such as balancing these three dimensions, considering both short- and long-term impacts, and upholding transparency and ethics in decision-making.
Another model that embraces sustainability is the GPM P5 Standard/PSM3 Maturity Model, developed by the Green Project Management (GPM) organization. This model—formally known as the Portfolio, Program, and Project Sustainability Model (PSM3™)—evaluates an organization’s project management maturity through a sustainability lens, with assessments across over 40 criteria spanning environmental, social, and governance performance in projects. It builds on six principles of sustainable project management (such as stakeholder accountability, ethical decision-making, and intergenerational impact) and defines six maturity levels for integrating these principles. A PSM3 assessment yields a multidimensional sustainability maturity profile, indicating how well sustainability practices are institutionalized in project portfolios. This goes beyond measuring project efficiency—it examines how projects incorporate eco-efficiency, social responsibility, and value creation for stakeholders [127, 128].
Additionally, the Sustainable Project Management Cube Model provides a multidimensional framework to guide project managers toward integrating sustainability [129]. Unlike earlier models that serve mainly as assessment tools, the “SPM Cube” model is conceived as a practical guide or tool for comprehensive and systematic integration of sustainability into project management practices. It encourages project managers to “think twice”—embedding ecological sustainability considerations alongside traditional project parameters—and adds a third dimension (a “cube”) to typical dual constraints, effectively ensuring that environmental and social facets are weighed equally with time, cost, and scope. By design, this model directly targets the economic, environmental, and social pillars, providing structured prompts or criteria at each project phase to consider the impacts on the planet, people, and economic outcomes. Notably, the model positions the project manager as a central driver of sustainable transformation and outlines guidelines for adopting sustainability-aligned practices throughout the project life cycle. These practices address sustainability across three vectors, people, processes, and solutions (including both digital and non-digital approaches) and aim to build the competencies of project managers as key agents in delivering sustainable project outcomes.
The concept of sustainability has gained prominence in PM [83, 117], specifically the transfer of knowledge, the organizational culture, organizational commitment, competence of management, and the potential value of sustainability to the organization [113]. Using the example of the biotechnology sector, organizations must adopt certain principles, including ethical decision-making, integration, and transparency, to ensure ecological and social equity in their goals, focus on critical stakeholders, and demonstrate accountability and commitment, while also prioritizing economic outcomes [87].
Sustainability is integral to project success, PM success, and PM performance, since it enhances the organization’s value by mitigating risks, improving project outcomes, and ultimately, the competitive advantage of the firm [1, 36, 41, 87]. The outcomes are achieved through appreciation of the two perspectives on sustainability in PM: sustainability through the project (whereby the project deliverables lead to sustainability), and sustainability of the project (which relates to the achievement of project goals in a manner that leads to the fulfillment of the social, economic, and ecological criteria) [5, 118]. However, the definition of project success is a dynamic construct that changes in line with the knowledge base in the PM field. Consequently, the adoption of sustainability in PM has led to the evolution from the Iron Triangle dimensions of quality (cost, scope, and time) and to a different set of outcomes under the triple-bottom-line (TBL) model (economic, social, and ecological dimensions) [5, 109].
The concept of sustainability introduces inherent tensions in the PM context for PBOs, such as loss of control over the project, the temporary nature of the goals, and institutional barriers [111]. Similarly, project managers tend to prioritize the economic dimension of sustainability over the social and ecological domains [106]. In such cases, project managers face paradoxical circumstances that can only be solved through the capabilities achieved at higher maturation levels. At higher maturity levels, where economic goals have been addressed, project managers can focus on additional goals, such as those classified under the social and ecological domains.
Furthermore, maturity models must go beyond static assessments to include prescriptive pathways for improvement, such as feedback loops and sustainability roadmaps. These features enable PBOs to implement actionable changes, such as sustainability training, stakeholder mapping, or lifecycle assessment methods, thereby progressing toward higher maturity levels [36, 126].
These models are particularly relevant to PBOs, which often operate across infrastructure, environmental, and social impact domains. As these organizations become increasingly accountable for delivering sustainable value, not just outputs, maturity models like SPM3 and the sustainable PM cube provide clear frameworks for embedding sustainability at each phase, enabling PBOs to align project delivery with broader ESG mandates. Despite the growing theoretical consensus, empirical adoption of sustainability-aligned PMMMs remains limited, especially among mid-tier or non-technical PBOs. This highlights the need for future research and policy incentives to support the integration of these practices into organizational settings.
Structured and systematic frameworks for PM
PM maturity is a systematic and sequential process that enables an organization to quantify its PM processes and how they contribute to the project’s success [91, 110]. The models provide a structured and systematic framework for identifying the strengths and weaknesses of the organization, as well as its capabilities to manage projects, programs, or portfolios [38]. While the PMBOK offers a framework comprised 10 domains, its utility has become overshadowed by the changes in the current PM environment, specifically under PBOs. PBOs constantly seek novel frameworks to solve emergent and extant problems, which is where PM maturity models come in. The frameworks facilitate the planning and prioritization of initiatives aimed at improving project performance and success within PBOs.
Comparison and benchmarking
PBOs operate in an environment where they constantly have to prove themselves better than their competition at PM, to a diverse set of stakeholders to get market opportunities [27, 119]. The PM maturity models provide an accurate snapshot of the organization’s proficiency in PM outcomes. This leads to a systematic and disciplined approach for organizations to benchmark and improve their processes [32, 53]. The snapshot reveals the current conditions of the organization, in comparison with the ‘best-in-class’ status, thereby facilitating the identification of relative performance gaps. The identified gaps can thus be deployed as systematic guidance for organizational improvement.
Through the maturity models, a PBO can compare its performance and outcomes with those of other PBOs across a range of benchmarks [28, 112], including best-in-industry entities [3], against a particular set of best practices [87], or particular competitors in the industry. For instance, a study [84] revealed that only a third of the firms with a PM maturity level higher than 50% qualified for international tenders. The findings highlight that PM maturity can be used to classify firms based on their delivery capabilities, as classification as an entity that qualifies for international tenders places the organization in a unique position relative to its competitors.
Strategy formulation
The competitiveness of PBOs in managing projects, programs, and portfolios depends on the suitability of their organizational strategies [112]. PBOs utilize available knowledge and capabilities when formulating strategies, which inform the direction to be adopted by the firm, as well as the actions required to achieve its goals [104]. PM maturity models provide a predefined path for developing strategies with various outcomes, including continuous improvement, innovation along a specific path, and capability enhancement [61, 96]. Other PM maturity models offer maturation paths focusing on capacity developed along an unbounded range of KPAs while ensuring progressive improvement in outcomes.
Continuous improvement (CI)
The concept of maturity originates from quality management, whereby organizations oversee the accomplishment of all tasks and activities to preferred levels of excellence [101, 108]. These preferred levels of excellence are subject to change, due to the effects of temporal and spatial factors. CI entails improving PM outcomes through incremental or breakthrough improvements, effective planning, and implementing and controlling changes to organizational processes, aiming to achieve specific outcomes [93, 114, 130]. The process is oriented toward gradual evolutionary change rather than significant and revolutionary innovations [34]. For PBOs, CI is an integral consideration, yet it remains problematic, due to the uniqueness in the characteristics of each project. The association persists since most processes of assessing maturity involve determining whether the PM processes are defined, established, applied, controlled, and continuous improvement are framed around the Plan, Do, Check, and Act (PDCA) approach [108].
PM maturity models contribute to CI by proposing a systematic process through which the capabilities of an organization can evolve in a stage-by-stage approach along a predictable, logical, or preferred trajectory, commonly referred to as the maturation path [33]. Based on existing frameworks, a discernible trajectory exists through which project managers can improve performance, productivity, and success in PM-related activities by applying maturity modeling [79]. These improvements originate from the increased capability to achieve the project goals and access to information and knowledge on achieving better PM outcomes.
The maturation path represents how the institution can achieve incremental improvement since each phase comprises individual KPAs that, when fulfilled, lead to betterment in the processes and capabilities of the institution. Furthermore, each of these phases is a collection of actions and goals that must be fulfilled for the organization to progress to a higher level of maturity [30]. However, PBOs encounter challenges in achieving these outcomes related to CI [38]. Essentially, individual project performance supersedes the overall performance of the PBO, a scenario that is contrary to the foundation of CI [31, 104]. Similarly, project managers are more focused on upholding project focus, thereby complicating the implementation of initiatives for improvement from a PBO perspective. Project managers have to identify the points of intersection between successive projects.
The role of technology in the maturation path
One key element of PM in the twenty-first century is the increased reliance on intellectual abilities and intelligence through advanced technologies, as opposed to natural and physical resources [33]. The change accelerates technological and scientific progress linked to digital and smart systems under the Industrial Revolution 4.0 (IR 4.0) ecosystem [115]. In turn, these technologies facilitate the implementation of technological innovations that improve the working systems under PM and the productivity of all resources [97, 102]. IR 4.0 technologies facilitate digitization, leading to clean technology solutions that directly enhance PM maturity by reducing material and carbon footprints across project activities in PBOs [95]. The changes alter how PM processes are carried out by introducing horizontal integration [33], including initiating smart business strategies and the prominence of innovation as a driver of continual improvement in PM in general and for particular project success outcomes. Project managers have thus had to adopt novel roles and capabilities as a result of integrating PM processes to achieve sustainability in business. IR 4.0 technologies are integral in introducing real-time solutions to various PM-related challenges facing managers and project personnel in PBOs [64], thereby facilitating improvements in quality management outcomes and maturity within the PM areas [103].
These drivers collectively represent critical factors determining PM maturity among PBOs. The framework for optimal maturity modeling identified in section “Criteria for eligibility” highlights multiple pathways through which a PBO can develop its maturity model. As explained in the theoretical background, the organizational context has a significant influence on the effectiveness of the applied maturity model. Future research should explicitly address existing gaps, particularly by integrating overlooked areas such as risk management and stakeholder management. This review calls for standardized sustainability assessment protocols that can be integrated into PM certification schemes and government-funded project frameworks, encouraging PBOs to align internal practices with national sustainability goals. This review calls for standardized sustainability assessment protocols that can be integrated into PM certification schemes and government-funded project frameworks, encouraging PBOs to align internal practices with national sustainability goals. This integration will foster the development of more holistic, contextually relevant, and practically effective maturity models, ultimately enhancing PM practices within PBO environments. Figure 3 summarizes the key drivers that reflect the strategic, operational, and technological needs that shape maturity model adoption and customization in PBOs.
[See PDF for image]
Fig. 3
Key drivers supporting the application of PM maturity models in PBOs
Implications
Theoretical implications
This review clarifies project management maturity for project-based organizations (PBOs) by making explicit the design choices embedded in a structured framework for PBO maturity models, including objectives, outcomes, maturation paths, recognition of maturity, and phases. In the framework, a staged path assumes different goals and outcomes in each phase, whereas a continuous path pursues similar goals across phases. Likewise, absolute recognition requires all criteria to be met before advancement, whereas partial recognition allows advancement once a significant subset of the criteria is achieved. These elements are presented as integral parts of model design for PBOs, not incidental implementation details, and the framework is explicitly positioned to guide customized models aligned to PBOs’ temporary governance and outcome-driven focus.
In parallel, the review consolidates sustainability-oriented maturity approaches (e.g., SPM3, PSM3, and SPM Cube) that embed economic, environmental, and social indicators across maturity levels, while also noting that many traditional models still treat sustainability as an add-on in practice. Together, the framework and these sustainability models support a contingent, context-sensitive view of maturity in PBOs and justify adapting enterprise-generic models to the specific conditions of PBOs.
Practical implications
For managers and policymakers, the review translates into concrete choices about how maturity is built and governed in PBOs. Operationally, PBOs can use maturity models as structured diagnostic systems to identify strengths/weaknesses, plan improvements, and benchmark against comparable organizations in their sector. Furthermore, embedding sustainability throughout the lifecycle is made tractable by models that provide stage-based ESG indicators (SPM3/PSM3) and integration prompts (SPM Cube), enabling measurable checkpoints across projects and portfolios.
Furthermore, technology emerges as a driver that can accelerate maturity improvements, complementing structured frameworks, benchmarking, strategic alignment, and continuous improvement as levers for sequencing a realistic, auditable roadmap. Collectively, these implications operationalize PBO-tailored assessment and sustainability-integrated maturity in practice.
Future research
The review leads to two directions for future research in fulfilling the third objective. First, the review shows the absence of empirical research on how PBOs can utilize maturity models to achieve or enhance PM efficiency. The tactical, operational, and strategic elements in PBOs are all organized around specific projects, underscoring the need to account for contextual variation in maturity modeling. Future work may translate the identified contextual and driving factors into a measurable instrument and validate their relationships across organizations and sectors, complemented by mixed-methods case studies. In parallel, practice-oriented implementation studies may co-design and pilot a sustainability-integrated PM transformation model.
Second, the high failure rates in some projects can be attributed to failures in PM capabilities among contemporary organizations. Since PBOs rely exclusively on projects in their operational, tactical, and strategic activities, they are placed in an advantageous position where they can achieve a steep learning curve in PM capabilities and attain PM maturity more efficiently and effectively compared to contemporary organizations. Researchers must perform a comparative analysis of PM maturity among PBOs to test this hypothesis using matched samples and, where possible, longitudinal or multi-sector designs to examine boundary conditions and generalizability.
Conclusions
This review consolidates current knowledge on how project-based organizations (PBOs) approach project management (PM) maturity, emphasizing the distinctiveness of their operational models. The findings highlight that PBOs adopt fundamentally different maturity frameworks than other organizational types, differences driven by their inherent project orientation. These distinctions are reflected in the development of maturity models tailored to the specific dynamics of enterprise versus intelligent PBOs, suggesting that a one-size-fits-all approach to PM maturity is inadequate.
Six core drivers of PM maturity in PBOs have been identified: sustainability, structured PM frameworks, benchmarking practices, strategic alignment, continuous improvement, and technological advancement. However, the review also exposes notable omissions in existing research, particularly the lack of attention to risk management and stakeholder engagement, two critical elements in project-based operations. These significant gaps influence how PBOs manage complexity, variability, and stakeholder expectations across diverse projects.
Overall, the review underscores the need for more integrated and context-sensitive maturity models that reflect the realities of PBOs. Future research should explore overlooked maturity drivers and examine how these factors interact within specific institutional or cultural contexts. By advancing this understanding, researchers and practitioners can contribute to the development of more effective and adaptable PM maturity frameworks that support organizational growth and resilience.
Acknowledgements
Not applicable.
Author contributions
R.A.-M., G.A., and E.M. contributed to conceptualization and validation; R.A.-M. and E.M. helped in methodology; R.A.-M. helped in formal analysis and investigation; G.A. and E.M. helped in writing—original draft preparation; writing—review and editing. All authors have read and agreed to the published version of the manuscript. Acknowledgement: Not applicable Funding: Not applicable.
Funding
Not applicable.
Data availability
The original contributions presented in this study are included in the article.
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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