Exploring Different Patterns of Perceived Barriers to Sustainable Project Management

Abstract

This study explores the subjective perceptions of project managers regarding barriers to implementing sustainable project management (SPM). Using Q-methodology and grounded in the theory of planned behavior (TPB), 28 project managers across diverse industries sorted and ranked statements about sustainability-related constraints. The analysis revealed three distinct belief patterns: “motivated yet confined”, characterized by structural and organizational limitations; “motivated yet lacking competency”, reflecting personal skill gaps and limited training; and “motivated yet unsupported”, highlighting weak normative support from peers and leadership. Despite differing barriers, all participants expressed positive attitudes toward sustainability, underscoring a common intention–behavior gap shaped by varying perceptions of behavioral control and normative reinforcement. The findings suggest that generic interventions are insufficient; instead, belief-sensitive strategies are needed to enable SPM adoption. Implications include reforming performance measurement systems, integrating sustainability into professional training, and cultivating supportive organizational cultures. The study contributes to both behavioral theory and project management practice by reframing sustainability barriers as belief-dependent phenomena and offers a foundation for more tailored, psychologically grounded interventions. These insights are relevant for educators, policymakers, and organizational leaders seeking to enhance sustainability outcomes through empowered and context-aware project management practices.

1. Introduction

The imperative of sustainability has interpenetrated virtually all domains of contemporary business and governance, including project management (PM). Sustainable project management (SPM) integrates environmental, social, and economic concerns into project planning, execution, and closure [1]. While numerous studies have focused on how project managers (PMs) can or should embed sustainability principles in the management of a project (e.g., [2,3]), less attention has been paid to the barriers they encounter in this. This gap is critical because PMs are pivotal agents in implementing sustainability goals and strategy [4].

Within this study, sustainable project management (SPM) is conceptualized as the integration of environmental, social, and economic dimensions into all phases of a project’s lifecycle—from initiation and planning to execution, monitoring, and closure [1,5]. This threefold framework, often referred to as the ‘triple bottom line’ (TBL) moves beyond a narrow focus on environmental ‘greenness’ to encompass social equity and long-term economic viability. For project managers, this translates into practices such as conducting lifecycle assessments, engaging diverse stakeholders, ensuring worker well-being, optimizing resource efficiency, and considering the long-term societal impact of project deliverables.

As stakeholder expectations evolve, the PM’s role shifts from a technical executor of plans, to a strategic enabler of sustainable development [6,7]. In this capacity, PMs must internalize and advocate sustainability values, yet face significant complexity in implementation due to institutional constraints, resource limitations, and behavioral factors [5]. These hard barriers are well-documented and include, but are not limited to: perceived and actual increases in project costs and timelines [8,9]; a lack of clear and standardized sustainability metrics and tools [10]; regulatory uncertainty and a lack of stringent enforcement [8,11]; and technical challenges related to new materials and processes [12]. At the same time, subjective belief-based barriers—such as perceived competency deficits or misalignment with organizational norms—remain underexplored [13]. This gap is problematic because behavioral science underscores that personal beliefs fundamentally shape decision-making and intentions [14].

To address this gap, we ground our study in the theory of planned behavior (TPB) [14,15], which posits that behavioral intentions are driven by three belief types: behavioral beliefs (attitudes toward the behavior), normative beliefs (perceived social pressures), and control beliefs (perceived ability to execute the behavior). The TPB offers a structured lens to analyze how PMs subjectively interpret SPM barriers, moving beyond organizational-level analyses that dominate extant literature [16,17]. Specifically, we address calls for a deeper examination of “soft” barriers—e.g., emotional dissonance or stakeholder misalignment—which subtly influence decisions but have received less empirical attention compared to technical or financial constraints [18,19]. Using Q-methodology [20], this study aimed to identify different subjective patterns of perceived barriers among PMs.

To frame our investigation, we addressed the following research questions: What subjective patterns of barriers to SPM adoption do PMs experience? How can these patterns be typified and labeled? How do the patterns align with the TPB’s behavioral, normative, and control beliefs? These questions bridge the gap between organizational and personal barrier to SPM.

The paper proceeds as follows. First, we review the TPB framework and its application to SPM. Next, we detail our Q-methodology design. We then present the different patterns of barriers the study revealed. Finally, we discuss theoretical and practical implications, limitations, and future research directions.

2. Theoretical Framework

The implementation of SPM requires a robust understanding of the subjective barriers perceived by project managers. This study employs the TPB [14,15] as its foundational theoretical framework, which provides a structured approach to analyzing human behavior by identifying three core belief systems that influence behavioral intentions. Behavioral beliefs encompass an individual’s attitudes toward a specific behavior, such as their perception of the value of SPM. Normative beliefs reflect perceived social pressures, including stakeholder expectations regarding sustainability practices. Control beliefs involve an individual’s perceived ability to adopt the behavior, accounting for factors like resource availability and personal competencies. Each of these belief categories informs a corresponding determinant of intention—attitude, subjective norm, and perceived behavioral control—thereby producing a predictive model of whether an individual is likely to undertake a particular behavior (see Figure 1). Together, they make the TPB particularly valuable for examining the intention–behavior gap commonly observed in sustainability adoption [21]. The two dashed arrows act as a reality check on the model, accounting for the gap between perception and reality.

A strength of the TPB in the context of SPM is its emphasis on perceived behavioral control. Project managers frequently operate within environments where organizational policies constrain their authority, client demands, and resource limitations [1,13]. These constraints directly influence their ability to implement sustainable practices, even when they possess strong personal motivation. Ajzen [22] highlights that perceived control acts as a key moderator between intention and action, explaining why many project managers struggle to translate their sustainability goals into practice.

A critical insight for applying the TPB to SPM is that objective, hard barriers in the project environment are cognitively processed by project managers through these belief systems. Specifically, normative and control beliefs act as the subjective lens through which structural obstacles are perceived and internalized. For instance, the well-documented hard barrier of “lack of standardized sustainability tools” [10] manifests as the control belief, “I lack the tools to apply sustainability”. Similarly, the hard barrier of “absence of client demand or regulatory pressure” [8,11] is experienced as the normative belief, “Clients do not prioritize sustainability”. This theoretical mapping clarifies that the TPB does not ignore external barriers but rather explains the psychological mechanism by which they translate into personal impediments to action, thus bridging the macro-level organizational constraints with the micro-level individual decision-making of the PM.

The relevance of the TPB to SPM barrier research is further underscored by three project-specific dynamics. First, project managers often face structural constraints beyond their immediate control, such as rigid organizational procedures or conflicting stakeholder priorities [8]. Second, their access to essential resources—such as training, tools, and team expertise—varies significantly across projects, directly impacting their perceived ability to adopt SPM [19]. Third, the ambiguous nature of authority in project environments complicates efforts to align sustainability objectives with broader organizational or client expectations [3]. By applying the TPB’s tripartite framework, this study moves beyond merely cataloging organizational barriers to instead explore how project managers cognitively interpret and respond to these constraints—a critical gap in existing research [17].

While other behavioral theories were considered during the design of this study, the TPB emerged as the most suitable framework due to its diagnostic precision and adaptability. PRIME theory [23], for example, focuses primarily on addiction mechanisms and impulse control, making it less applicable to professional decision-making contexts. Similarly, the multilevel goal conflict theory [24] examines tensions between competing objectives. Still, it lacks empirical validation in project management settings and does not adequately address the role of belief systems in shaping perceived control. The health action process approach (HAPA) [25] offers insights into behavior change processes but is inherently prescriptive and better suited to health-related behaviors than to organizational or project-specific challenges.

Furthermore, while macro-level theories like institutional theory [26,27] could explain the isomorphic pressures (coercive, mimetic, normative) that create the organizational constraints PMs face, and practice theory [28] could focus on the routines that constitute ‘business-as-usual’, the TPB was selected for its meso-level focus because it effectively captures how individual PMs cognitively process and respond to these very external pressures and ingrained routines, aligning with our research aim of understanding subjective perceptions.

TPB’s flexibility in accounting for perceived—rather than solely objective—control makes it uniquely valuable for this research. For instance, a project manager may believe they lack the necessary training to implement SPM, even if training programs are theoretically available. This perception alone can hinder action, regardless of actual circumstances. By focusing on subjective interpretations of barriers, the TPB enables a nuanced analysis of why sustainability initiatives often stall despite strong organizational commitments.

Critics of the TPB argue that it overlooks emotional, habitual, and unconscious influences on behavior [29]. However, Ajzen [22] clarifies that the TPB was designed as a flexible framework rather than an exhaustive model, and its predictive power can be enhanced by incorporating context-specific variables such as self-identity or past behavior. In this study, the TPB served primarily as a diagnostic tool rather than a predictive model, allowing for the systematic categorization of barriers into behavioral, normative, and control dimensions while revealing patterns in how these beliefs interact to impede SPM adoption.

To operationalize the TPB, the study mapped the full set of 45 barrier statements from the Q-sample to the three belief categories. Behavioral beliefs included statements such as “Sustainability adds long-term value”, reflecting positive attitudes, and “Implementing sustainability increases project complexity”, indicating negative perceptions. Normative beliefs were represented by items like “Clients do not prioritize sustainability”, highlighting weak social pressure, and “Colleagues expect environmental compliance”, suggesting stronger normative expectations. Control beliefs were captured through statements such as “I lack the tools to apply sustainability”, signaling low perceived agency, and “There is insufficient training”, pointing to skill gaps. This structured categorization enabled a theory-guided analysis of barrier patterns while ensuring empirical findings remained grounded in the TPB’s conceptual framework.

The TPB provides a validated and parsimonious model for dissecting SPM barriers. Its focus on perceived control directly addresses the complexities of project environments, where managers must navigate competing priorities with limited authority. By distinguishing between attitudinal, social, and structural barriers, the TPB enables the development of targeted interventions tailored to the specific challenges faced by project managers. This study advances the call by Silvius [1] to treat sustainability adoption as a psychological phenomenon deeply intertwined with organizational systems, offering both theoretical and practical insights into the belief systems that shape SPM implementation.

3. Methods

This study employed a mixed-methods approach to explore the different subjective patterns of barriers perceived by PMs when engaging in SPM. Specifically, Q-methodology was chosen for its ability to reveal and categorize shared viewpoints among individuals through both qualitative and quantitative lenses. The following sections detail the study’s design, participants, data collection procedures, and analytic strategy.

3.1. Research Design: An Embedded Mixed-Methods Approach

A convergent embedded design was adopted (Figure 2), combining an initial qualitative data phase with a subsequent quantitative analysis, in line with Creswell and Plano Clark’s [30] model of mixed-methods integration. The research began by developing a concourse—a structured set of statements—sourced from sustainability and project management literature. These statements were then subjected to Q-sorting by participants, and the resulting data underwent factor analysis to identify clusters of shared subjective perspectives.

The decision to use Q-methodology rested on its unique strength: enabling researchers to examine and quantify subjectivity systematically [31]. Unlike traditional surveys that aggregate responses to infer trends, Q-methodology seeks to understand different patterns of meaning across individuals, making it ideal for examining varied perceptions of sustainability barriers among PMs.

3.2. Q-Methodology Overview

Q-methodology is a structured approach to studying subjective perspectives. In simple terms, participants ranked statements about SPM barriers (e.g., “Sustainability increases project complexity”) on a scale from “Most agree” to “Most disagree”. Statistical analysis then grouped participants with similar rankings into distinct patterns, revealing shared viewpoints. This mixed-method approach combines qualitative insights (participants’ reasoning during sorting) with quantitative rigor (factor analysis) [20]. The process followed five stages:

• Q-Sample Construction: We developed 45 statements capturing SPM barriers from the literature.
• P-Set Selection: 28 project managers from diverse industries were recruited.
• Q-Sorting: Participants sorted statements using a forced-distribution grid (Figure 3).
• Factor Analysis: Statistical clustering identified shared perspectives.
• Interpretation: Each cluster was analyzed to define barrier typologies.

3.3. Development of the Q-Sample

A total of 45 statements were included in the Q-sample. These were derived from a systematic review of academic literature on sustainable project management, individual behavioral barriers, and organizational change. Sources included peer-reviewed journals such as the International Journal of Project Management, Journal of Cleaner Production, and Ecological Economics.

Statements were constructed to reflect the three types of beliefs from the theory of planned behavior (TPB): behavioral, normative, and control [14]. Each statement was carefully phrased to express a potential barrier or constraint, either internal (e.g., lack of skill or motivation) or external (e.g., organizational or stakeholder pressure). The final statement pool was tested with two project management professionals to ensure clarity and interpretability before full deployment (

Table 1. Barriers to sustainability identified in literature: Q-set statements by TPB category.

No.	Category	Sub-Classification	Sub-Statements (Identified Barriers)	Sources
1	Behavior	Motivation	Sustainability does not stimulate me	[21]
2	Behavior	Motivation	I do not feel motivated to address the topic of sustainability	[32]
3	Behavior	Motivation	I do not experience a moral or ethical obligation to do so	[33]
4	Behavior	Motivation	I perceive implementing sustainability in projects as inconvenient	[21]
5	Behavior	Knowledge and Skills	I feel overwhelmed by the complexity of SPM practices	[34]
6	Behavior	Policy	I am not aware of any sustainability-related legislation for my project	[35]
7	Behavior	Priority and Risk	I am not aware of any environmental risks or impact of my project	[9]
8	Behavior	Priority and Risk	I think that sustainability increases the risk and uncertainty in the project	[12]
9	Behavior	Priority and Risk	I favor traditional PM over new, sustainable practices	[12,17,36]
10	Behavior	Priority and Risk	I regard SPM practices as low priority	[10,17]
11	Behavior	Priority and Risk	I am satisfied with the current PM practices in my project	[36,37]
12	Behavior	Project’s Nature	I believe that SPM is only aimed at large(r), impactful projects	[1,34]
13	Behavior	Project’s Nature	I believe that for the types of projects I manage, considering sustainability unnecessarily increases the cost	[38]
14	Behavior	Influence and Awareness	I do not see a connection between the project’s objectives and sustainability	[39]
15	Behavior	Influence and Awareness	I do not feel responsible for the sustainability of my projects	[40]
16	Normative	Motivation	My project owner or client is not giving me additional incentives/compensation for the extra effort of sustainable practices	[41]
17	Normative	Motivation	Addressing sustainability will not give me a better status as a project manager	[21]
18	Normative	Motivation	The project team prefers to stick to already-established PM routines	[18]
19	Normative	Policy	I believe it is the project owner’s or client’s responsibility to drive sustainability	[40]
20	Normative	Policy	My company does not adopt environmentally friendly PM practices	[40]
21	Normative	Priority and Risk	Sustainability is not the project’s performance priority	[34]
22	Normative	Priority and Risk	Implementing sustainability practices may hurt my relationship with the project owner/client	[42]
23	Normative	Priority and Risk	When integrating SPM practices, my reputation as a project manager could be at risk	[42]
24	Normative	Project’s Nature	According to the project owner/client, sustainability is not relevant for this project	[34]
25	Normative	Project’s Nature	Company procedures limit the consideration of sustainability in the project	[43]
26	Normative	Influence and Awareness	End users are not interested in sustainability	[19]
27	Normative	Influence and Awareness	Stakeholders are not interested in sustainability	[40]
28	Normative	Influence and Awareness	I expect to be confronted with negative reactions or feedback about SPM practices	[40]
29	Normative	Influence and Awareness	I feel there is a lack of interest amongst project team members	[9]
30	Normative	Influence and Awareness	The market does not value SPM practices	[44]
31	Control	Knowledge and Skills	Sustainability is too complex and not practical enough to apply in the project	[40]
32	Control	Knowledge and Skills	Methods for SPM practices are missing	[10]
33	Control	Knowledge and Skills	The project team lacks the knowledge to understand how sustainability can be implemented in the project	[10]
34	Control	Knowledge and Skills	The team does not have the competences to integrate sustainability in the project	[10]
35	Control	Knowledge and Skills	I do not have experience with SPM practices	[45]
36	Control	Policy	For my projects, no clear environmental issues or impacts have been identified	[46]
37	Control	Policy	I do not understand the methods or practices of sustainable PM	[10]
38	Control	Policy	Regulations hinder the adoption of SPM practices in my project	[11]
39	Control	Policy	I believe that sustainability is difficult to integrate in the project	[47]
40	Control	Priority and Risk	Considering sustainability does not make my projects more successful	[47]
41	Control	Project’s Nature	I do not believe that sustainability can be addressed by all project managers in every project	[32]
42	Control	Project’s Nature	It is too difficult to align the project with sustainability goals or objectives	[48]
43	Control	Project’s Nature	My project is not suitable for green project management practices	[10]
44	Control	Project’s Nature	I believe my project is too small to reap the benefits of implementing sustainability	[49]
45	Control	Influence and Awareness	A proactive involvement and engagement of stakeholders requires too much effort	[17]

).

3.4. Participant Selection (P-Set)

A non-probabilistic purposive sampling strategy was employed to select 28 project managers from diverse industries, including construction, IT, finance, public infrastructure, and consulting. Participants were primarily based in Vienna, Austria, but not restricted to this geographic area. The criteria for inclusion included at least two years of project management experience, involvement in sustainability-related decisions or projects, and the willingness to participate in an interactive sorting exercise. Diversity was intentionally maximized across dimensions such as industry, age, gender, and organization type to enhance the representativeness of viewpoints.

Table 2. Description of the P-set.

Question	Answer Categories	Total Sample
		Frequency	Percentage
Age	18–27	9	32.14
	28–37	10	35.71
	38–47	8	28.57
	48+	1	3.57
Gender	Male	14	50.00
	Female	14	50.00
Project Type (multiple answers allowed)	Building and Construction Public Infrastructure	3	6.38
	Building and Construction Real Estate	8	17.02
	Building and Construction Development	2	4.26
	Organizational Change	7	14.89
	Information Technology	12	25.53
	Research and Development	7	14.89
	Other *	8	17.02
Industry Type (multiple answers allowed)	Agriculture	1	1.54
	Energy	3	4.62
	Healthcare	5	7.69
	Logistics Services	2	3.08
	Facility and Real Estate	5	7.69
	HR Services	1	1.54
	Consulting	5	7.69
	Education and Training	2	3.08
	Industry	7	10.77
	Building and Construction	8	12.31
	Wholesale and Retail	3	4.62
	Financial Services	5	7.69
	Legal Services	1	1.54
	ICT and Communication	7	10.77
	Public Administration	3	4.62
	Other **	7	10.77
Years of Experience in Project Management	1–5	16	57.14
	5–10	5	17.86
	10–20	6	21.43
	20+	1	3.57
Project Size	<1 million €	9	32.14
	1–10 million €	10	35.71
	>10 million €	9	32.14
Sustainability Integrated in Company Strategy (1—not at all, 5—to the full extent)	1	1	3.57
	2	6	21.43
	3	12	42.86
	4	7	25.00
	5	2	7.14

Notes: * Procurement, Development of Activities, Education Program, IFRS 17 (Insurance), Manufacturing, Healthcare, Literature Content, Medical Technology; ** Insurance, Manufacturing, Research and Technology, Electrical and Electronics, Media, Social Sector, Sports Betting.

documents the final P-set.

3.5. Q-Sorting Procedure

Each participant was asked to complete a Q-sort, ranking the 45 statements along an 11-point quasi-normal distribution grid ranging from “Most agree” to “Most disagree”. A participant placing a statement in the +5 column indicates it is a barrier they perceive as most salient, while a statement placed in the −5 column is one they strongly reject as a barrier. The sorting was completed in-person or online via video conferencing (using Microsoft Teams), supported by the Miro collaborative whiteboard platform.

Participants were encouraged to “think aloud” while sorting, allowing for the capture of qualitative notes and rationale behind their rankings. These post-sort commentaries were transcribed and later used to assist with factor interpretation. For instance, while placing Statement #44 (“I believe my project is too small to reap the benefits…”) in the +4 column, one participant commented: “My projects are under six months and EUR 200k. The overhead of a full sustainability assessment just isn’t justified. I need a lightweight checklist, not a full-scale framework”. This qualitative data was crucial for interpreting the quantitative ranking.

3.6. Data Analysis Using PQMethod©

Q-sorts were entered into the PQMethod© software, release 2.35, a specialized program designed for the statistical analysis of Q-sort data. This software is widely used for conducting Q-methodology studies, combining qualitative and quantitative techniques to explore subjective viewpoints [50], and facilitating the entire Q-process, including data entry, correlation of Q-sorts, factor extraction (e.g., centroid or principal components), factor rotation (e.g., varimax, manual), and the generation of factor scores and interpretation aids. Its user-friendly interface and methodological rigor make PQMethod© the standard tool for researchers applying Q-methodology in fields such as psychology, political science, education, and organizational studies [50]. In this study, we used centroid extraction and varimax rotation, while the criteria for factor retention included eigenvalues greater than 1.0, at least two significantly loading participants per factor, and theoretical coherence with TPB constructs.

4. Results

4.1. Analysis of Factors

The analysis of 28 project managers’ Q-sorts revealed three distinct patterns of perceived barriers to SPM, each with unique characteristics and demographic correlates (

Table 3. Characteristics and correlations of the three factors.

Metric	Factor 1	Factor 2	Factor 3
Eigenvalues	4.938	2.5463	1.7148
Explained Variance (%)	18	9	6
Number of Defining Variables (Q-Sorts)	12	4	5
Average Reliability Coefficient	0.8	0.8	0.8
Composite Reliability	0.98	0.941	0.952
Standard Error of Factor Z-Scores	0.143	0.243	0.218
Correlation with Factor 1	1.000	0.051	0.244
Correlation with Factor 2	0.051	1.000	−0.100
Correlation with Factor 3	0.244	−0.100	1.000

).

Table 4. Factor loadings table.

Participant Number	Factor 1	Factor 2	Factor 3
1	0.2502	0.127	0.1002
2	0.0346	0.0516	0.3793X
3	−0.0004	−0.5469X	0.1104
4	0.5636X	−0.0283	0.2554
5	0.5278X	0.0646	−0.4292
6	0.7905X	−0.1052	0.0945
7	0.094	−0.4335X	0.3857
8	0.0335	−0.1571	0.4910X
9	0.4016	0.1119	0.4933X
10	0.3933	−0.1562	0.0859
11	0.4808	0.3932	−0.3557
12	0.6176X	−0.0312	−0.2428
13	0.0344	0.4347X	−0.2982
14	0.6413X	−0.0401	−0.0473
15	0.4392X	−0.1599	0.0037
16	0.199	0.5634X	−0.072
17	0.3156	0.1268	−0.1263
18	0.4525X	−0.3813	0.1064
19	0.4313	0.1309	0.4785X
20	0.4143X	0.1251	−0.2815
21	−0.0373	0.0676	0.2512
22	0.5502X	0.0617	−0.1152
23	0.6237X	−0.2244	−0.1569
24	0.3185	−0.2671	0.0097
25	0.0766	0.1551	0.6011X
26	0.5370X	0.4108	0.1365
27	0.5640X	0.0449	0.2429
28	0.2997	0.3825	0.1088

Note: Participants’ loadings on the three factors.

displays the factor loadings, showing how participants clustered based on their barrier perceptions, with significant loadings onto a single factor (loading ≥ ±0.40, p < 0.01).

As Table 4 illustrates, twelve participants loaded significantly on Factor 1 (“motivated yet confined”), while four and five aligned with Factors 2 and 3, respectively. These groupings reflect fundamentally different patterns in how project managers perceive barriers to SPM.

4.2. Factor Interpretation

The three extracted factors were labeled:

• Factor 1: “motivated yet confined”—PMs who are committed to sustainability but perceive organizational policies or rigid systems as barriers.
• Factor 2: “motivated yet lacking competency”—PMs who support sustainability but feel unprepared due to insufficient training or knowledge.
• Factor 3: “motivated yet unsupported”—PMs who feel enthusiastic but experience a lack of peer or leadership encouragement.

These factors were analyzed through a dual-lens approach combining statistical and qualitative insights. First, each factor’s defining array—comprising statement rankings with Z-scores ≥ |1.0|—was examined to identify consensus and distinguishing items. For example, Factor 1 (“motivated yet confined”) was marked by strong agreement (+1.39) with “Company procedures limit sustainability consideration”, contrasting sharply with Factor 3’s neutrality (–0.12). Second, post-sort interview transcripts were thematically coded to contextualize quantitative patterns. Participants loading on Factor 2 (“motivated yet lacking competency”) frequently cited “no training on sustainability metrics” in open-ended remarks, aligning with high rankings (+2.13) for control-belief statements like “I lack tools to apply sustainability”.

To ensure theoretical coherence, factors were mapped to TPB constructs. Control beliefs dominated all three factors (average Z-score range: 0.14–0.49), but their manifestations differed: Factor 1 emphasized policy constraints (e.g., “client responsibility” norms), while Factor 3 highlighted unsupportive infrastructures (e.g., “no clear environmental guidelines”). This granularity echoes Ajzen’s [14] assertion that perceived control varies by context. Finally, demographic cross-tabulations (

Table 5. Participant Demographics and Factor Loadings.

Demographic	Categories	Total P-Set (%)	Factor 1 (%)	Factor 2 (%)	Factor 3 (%)	No Factor Loading (%)
Age	18–27	32.14	55.56	22.22	11.11	11.11
	28–37	35.71	40.00	10.00	30.00	20.00
	38–47	28.57	37.50	12.50	12.50	37.50
	48+	3.57	0.00	0.00	0.00	100.00
Gender	Male	50.00	35.71	21.43	21.43	21.43
	Female	50.00	50.00	7.14	14.29	28.57
Project Type	Building and Construction	27.66	50.00	0.00	12.50	37.50
	Organizational Change	14.89	42.86	14.29	28.57	14.29
	Information Technology	25.53	41.67	16.67	25.00	16.67
	Research and Development	14.89	42.86	14.29	0.00	42.86
Industry Type	Building and Construction	12.31	62.50	0.00	12.50	25.00
	Healthcare	7.69	20.00	0.00	40.00	40.00
	ICT and Communication	10.77	42.86	14.29	0.00	42.86
Years of Experience	1–5	57.14	43.75	25.00	18.75	12.50
	5–10	17.86	40.00	0.00	20.00	40.00
	10+	25.00	40.00	0.00	20.00	40.00
Project Size	<€1M	32.14	33.33	11.11	44.44	11.11
	€1M–€10M	35.71	40.00	30.00	0.00	30.00
	>€10M	32.14	55.56	11.11	11.11	22.22

) revealed practical nuances—e.g., construction PMs disproportionately loaded on Factor 1 (62.5%), underscoring industry-specific policy barriers.

Factor 1, labeled “motivated yet confined”, showed project managers who were personally committed to sustainability but constrained by organizational structures. This group exhibited strong disagreement with behavioral belief statements (average Z-score: −0.59), particularly rejecting notions of personal reluctance such as “Sustainability does not stimulate me” (Z: −2.02). However, they faced significant normative barriers (Z: 0.44), strongly agreeing that “Company procedures limit the consideration of sustainability in the project” (Z: 1.39). Demographically, this factor was particularly prevalent among younger project managers (55.6% of 18–27 year olds) and those in the construction industry (62.5%) (Table 4). As one participant noted, “We want to implement sustainable practices, but client contracts and company policies make it nearly impossible” (P12, construction). This aligns with Silvius et al.’s [42] findings about structural barriers in regulated industries.

Factor 2, “motivated yet lacking competency”, presented a different challenge. While these project managers maintained generally positive attitudes (behavioral belief Z: −0.21), they struggled primarily with control beliefs (Z: 0.26), particularly in terms of project feasibility. Statements like “I believe my project is too small to reap the benefits of implementing sustainability” received strong agreement (Z: 2.13). This factor was most common among mid-career professionals (28–47 years) managing smaller projects (<€1M) in IT and organizational change sectors. The qualitative comments revealed frustration with the lack of scalable solutions, as one IT project manager explained: “The sustainability frameworks we see are designed for massive infrastructure projects, not for our agile software development cycles” (P16).

The third pattern, “motivated yet unsupported” (Factor 3), showed project managers who faced systemic implementation barriers despite their motivation and competency. They reported the strongest control belief challenges (Z: 0.49), particularly regarding institutional support, as evidenced by high agreement with “For my projects, no clear environmental issues or impacts have been identified” (Z: 2.56). Healthcare professionals (40%) and those managing small projects (44.4%) were disproportionately represented in this factor. Their comments often highlighted policy–practice gaps: “Leadership talks about sustainability but provides no concrete guidance or resources” (P22, healthcare).

4.3. Analysis of Sub-Categories Scores

Delving deeper into sub-categories revealed more nuanced patterns.

Table 6. Count of subclassifications of barriers in Q-sample and means per factor.

Subclassification	Count in Q-Sample	Factor 1 (Z-Score)	Factor 2 (Z-Score)	Factor 3 (Z-Score)
Motivation	7	−0.5636	−0.1561	0.1056
Knowledge and Skills	6	0.1978	0.2307	−0.0122
Policy	7	0.6274	−0.1473	0.3937
Priority and Risk	9	−0.1926	−0.1086	−0.0902
Project’s Nature	8	−0.0309	0.4025	0.4138
Influence and Awareness	8	0.0431	−0.1879	−0.7401
Total	45	−	−	−

provides granular insight into how specific barrier types manifested across factors.

For Factor 1, policy-related barriers dominated (Z: 0.63), while motivation scored lowest (Z: −0.56), confirming that these project managers were personally willing but institutionally constrained. The construction industry’s strong representation here suggests sector-specific challenges with rigid procurement processes and client expectations [41].

Factor 2’s challenges centered on the nature of projects (Z: 0.40) and knowledge gaps (Z: 0.23). The prevalence of IT professionals in this group points to a mismatch between available sustainability tools and the realities of technology projects. As Marnewick et al. [32] and Magano et al. [6] found, traditional sustainability metrics often fail to accommodate the rapid iteration cycles of software development.

Factor 3’s most severe barriers involved institutional support (policy Z: 0.39) and project alignment (Z: 0.41). The healthcare sector’s strong presence here reflects the unique challenges of applying environmental sustainability frameworks in patient care contexts [10]. One hospital project manager noted, “Patient safety always trumps environmental concerns in our decision-making” (P25).

4.4. Consensus Statements: The Common Ground in SPM Barriers

Eight statements showed no significant differences across factors (p > 0.01), revealing universal perspectives (

Table 7. Consensus statements per factor.

Number	Statement	Category/Subclassification	Avg. Z-Score	Factor 1	Factor 2	Factor 3
10	I regard SPM practices as low priority	Behavior/Priority and Risk	−0.67	0	−1	−1
15	I do not feel responsible for the sustainability of my projects	Behavior/Influence and Awareness	−0.33	0	−1	0
17	Addressing sustainability will not give me better status	Normative/Motivation	−1.33	−1	−2	−1
20	My company does not adopt environmentally friendly PM practices	Normative/Policy	−0.33	1	−1	−1
32	Methods for SPM practices are missing	Control/Knowledge and Skills	0.67	1	0	1
37	I do not understand the methods/practices of SPM	Control/Policy	0.67	1	0	1
42	It is too difficult to align projects with sustainability goals	Control/Project’s Nature	−1.00	0	−2	−1
45	Stakeholder engagement requires too much effort	Control/Influence and Awareness	1.33	1	2	1

).

As Table 7 demonstrates, all project managers strongly rejected the idea that sustainability was someone else’s responsibility (“I do not feel responsible for the sustainability of my projects”, Z: −0.33). This finding robustly confirms that motivation is not the primary barrier to SPM implementation.

Similarly, statements about methodological gaps received moderate consensus agreement (average Z: 0.67), suggesting widespread recognition of the need for better SPM tools across all sectors. However, views on organizational adoption were more mixed (“My company does not adopt environmentally friendly PM practices”, Z: −0.33), indicating that while most organizations have begun sustainability efforts, implementation remains inconsistent.

The most striking consensus emerged around stakeholder engagement challenges (“A proactive involvement of stakeholders requires too much effort”, Z: 1.33). This suggests that even motivated, competent project managers in supportive environments still struggle with the practical realities of sustainability-focused stakeholder management.

5. Discussion and Conclusions

The study’s methodological rigor is rooted in the structured and systematic application of Q-methodology, enabling the exploration of PMs’ subjective perceptions in a way that is both quantitative and qualitative. By combining literature-informed statement construction with theory-guided interpretation, the study delivers robust insights into the individual belief structures that shape SPM behavior. The selected methodology also aligns with the study’s core epistemological stance: that sustainability integration is a function not only of external frameworks and systems but also of how individuals perceive and interact with these structures. Q-methodology proved especially powerful for operationalizing this dual focus, illuminating not just what barriers exist, but how they are interpreted differently depending on the PM’s internal belief framework.

A fundamental finding that frames all subsequent interpretations is that participants across all three factors expressed positive attitudes towards sustainability, firmly rejecting statements suggesting personal reluctance (e.g., “Sustainability does not stimulate me”, Z = −2.02). This robust baseline motivation indicates that resistance to sustainable project management (SPM) is less about personal aversion and more a function of structural, competency-based, and normative barriers. However, this finding also highlights a key consideration for the interpretation of our results: the recruitment criteria, which required ‘involvement in sustainability-related decisions or projects’, may have unintentionally selected for a cohort already positively predisposed to sustainability [13]. Consequently, while the identified patterns provide a subtle understanding of the barriers faced by motivated practitioners, they may not fully capture the perspectives of truly resistant or disengaged project managers. Future research should actively seek to include these voices to provide a more complete range of barrier perceptions.

Beyond the statistical clustering of Q-sorts, the “think-aloud” commentaries provided by participants during the sorting process offered valuable interpretive insights. Several participants explicitly described the mismatch between sustainability frameworks and project scale, with IT project managers, for instance, noting that “full sustainability assessments do not fit agile cycles, where lighter checklists would be more appropriate”. Similarly, construction professionals repeatedly pointed to contractual and regulatory rigidity as barriers, emphasizing that “client contracts and company procedures leave no space for flexibility”. In the healthcare sector, project managers stressed the ethical tension between patient safety and environmental priorities, remarking that “sustainability cannot override immediate clinical concerns”. These observations reinforce the quantitative factors: they contextualize Factor 1’s structural confinement, Factor 2’s competency deficits, and Factor 3’s lack of organizational support. They also confirm Ajzen’s [14,15] argument that perceived behavioral control is context-dependent, shaped by concrete organizational and sectoral realities rather than abstract attitudes alone. By integrating these participant voices, the discussion underscores that SPM adoption is not only a matter of individual intention but also of systemic fit and contextual translation [5,13].

5.1. Factors Interpretation

The three identified barrier patterns—motivated yet confined, motivated yet lacking competency, and motivated yet unsupported—reveal critical insights about sustainability adoption in project management when examined through the lens of established literature.

5.1.1. Control Belief Dominance and Organizational Enablers

The prevalence of control beliefs across all factors (Z-scores 0.14–0.49) strongly supports Ajzen’s [15] contention that perceived behavioral control is the most potent predictor of behavior adoption in professional contexts. This finding aligns with Silvius and de Graaf’s [42] organizational enablers theory, which posits that individual motivation becomes operational only when structural supports exist. Our Factor 1 participants’ struggles with policy constraints (e.g., “Company procedures limit sustainability consideration”, Z = 1.39) mirror precisely the “ostensible support” phenomenon described by Borg et al. [41], where organizations profess sustainability commitments but maintain incompatible operational systems.

5.1.2. Sector-Specific Barrier Manifestations

The demographic concentrations in each factor reveal important sectoral dynamics. The overrepresentation of construction PMs in Factor 1 (62.5%) validates Caldera et al.’s [8] identification of “regulated industry paralysis”—where compliance-focused sectors develop rigid procedures that ironically inhibit innovation. Conversely, IT professionals’ predominance in Factor 2 reflects what Marnewick et al. [32] term the “agile sustainability gap”, as rapid-iteration methodologies struggle to incorporate longitudinal sustainability metrics. Healthcare PMs in Factor 3 embodied the “values-action disconnect” noted by Sinxadi and Awuzie [19], where clinical operational constraints thwart strong ethical motivations for sustainability.

5.1.3. The Motivation-Action Paradox

While all factors rejected behavioral belief barriers (e.g., “Sustainability does not stimulate me”, Z = −2.02), this apparent motivation failed to translate to action—a phenomenon Barneveld and Silvius [21] attribute to “intention erosion” in matrix organizations. Our findings extend their work by demonstrating how erosion mechanisms differ: Factor 1—Intention erosion through policy misalignment; Factor 2—Erosion through competency gaps; and Factor 3—Erosion through support system voids. This tripartite model of intention erosion provides a more nuanced framework than previous unidimensional conceptualizations (e.g., [13]).

5.2. Perspectives and Participant Demographics: A Nuanced Intersection

The demographic patterns across factors reveal critical context for interpreting barrier perceptions, extending beyond simple descriptive statistics to illuminate how professional environments shape sustainability implementation.

5.2.1. Age and Career Stage Dynamics

Younger PMs (18–27 years) disproportionately loaded on motivated yet confined (55.6%), corroborating Magano et al.’s [51] finding that early-career professionals perceive organizational structures as immutable constraints. This contrasts with mid-career PMs (28–47 years) in motivated yet lacking competency, who—consistent with Presseau et al.’s [24] goal conflict theory—balanced sustainability aspirations against delivery pressures. The absence of older PMs (48+) in any factor suggests either greater adaptability or entrenched resistance to change [52], warranting further study.

5.2.2. Industry-Specific Constraint Archetypes

The construction sector’s dominance in motivated yet confined (62.5%) exemplifies what Caldera et al. [8] term “regulated industry paralysis”, where compliance-focused cultures inhibit innovation. Conversely, healthcare PMs’ alignment with motivated yet unsupported (40%) reflects the “ethical dissonance” phenomenon identified by Sinxadi and Awuzie [19]—professionals morally committed to sustainability but lacking operational pathways. IT professionals’ presence in motivated yet lacking competency (16.7%) mirrors the “tool gap” for agile methodologies noted by Toriola-Coker et al. [10].

5.2.3. Project Scale as a Moderator

Small-project managers (<€1M) predominated in motivated yet unsupported (44.4%), supporting Armenia et al.’s [17] contention that sustainability is often “systematically undersupported” in lower-budget initiatives. Large-project PMs (>EUR 10M) in motivated yet confined (55.6%) echoed Sabini and Alderman’s [53] finding that increased resources paradoxically reveal deeper policy constraints.

5.2.4. Gender Implications

The underrepresentation of female PMs in Factor 2 (“motivated yet lacking competency”) is a notable finding that merits further investigation. Rather than indicating higher confidence, this pattern may reflect systemic gendered dynamics in STEM and project management fields [13]. Women may be less likely to attribute challenges to personal competency gaps due to well-documented phenomena like the confidence gap [6] or, conversely, may be more adept at identifying external, systemic obstacles as the root cause of implementation failures. This finding underscores the need for future research to employ a gendered lens to explore how socialization, access to training, and workplace dynamics differentially shape male and female PMs’ perceptions of sustainability barriers.

5.3. Theoretical Implications

5.3.1. Extending the TPB in Professional Contexts

Our results necessitate two refinements to the TPB application in project environments. First, the theory’s behavioral control dimension should be bifurcated into personal agency (skills, knowledge) and organizational enablement (policies, resources), as their impacts differ markedly. Factor 2 PMs lacked primarily personal agency (“I lack tools”, Z = 1.21), while Factor 3 faced organizational enablement deficits (“No clear guidelines”, Z = 2.56). This distinction was obscured in prior studies (e.g., [3]).

Second, normative beliefs exhibited context-dependent potency. In Factor 1, they were constraining (“Client responsibility”, Z = 2.08), while in Factor 3, they were neutralized (“Market doesn’t value SPM”, Z = −1.94). This supports Magano et al.’s [6] contingency model of normative influence but adds the critical moderator of organizational support systems.

5.3.2. Extending the TPB in SPM

This study yields three significant theoretical contributions that refine and extend the TPB within professional sustainability contexts. These contributions emerge from the intersection of our empirical findings with established behavioral literature.

The Conditional Efficacy of Behavioral Beliefs

While the TPB posits behavioral beliefs as foundational to intention formation [15], our results demonstrate their limited operational power in organizational settings. Across all factors, project managers exhibited strong positive attitudes toward sustainability (e.g., unanimous rejection of “Sustainability does not stimulate me”, Z = −2.02), yet these beliefs failed to translate into consistent implementation. This supports and extends Sniehotta et al.’s [29] critique by revealing how organizational contexts neutralize attitude–behavior relationships. Specifically, we identified three distinct neutralization mechanisms: policy constraints in Factor 1 (“motivated yet confined”), competency gaps in Factor 2 (“Lacking Competency”), and system voids in Factor 3 (“Unsupported”). This tripartite model of attitude neutralization provides a more nuanced framework than previous unidimensional conceptualizations [13], particularly for professional environments where institutional forces routinely override individual motivations.

Context-Dependent Activation of Normative Beliefs

Our findings challenge TPB’s traditional treatment of subjective norms as uniformly influential. Instead, we observed what might be termed “selective normative activation”—where referent group salience [15] varies dramatically by professional context. Construction project managers (Factor 1) demonstrated high sensitivity to client and organizational norms (“Company procedures limit sustainability”, Z = 1.39), while healthcare professionals (Factor 3) actively dismissed market pressures (“The market doesn’t value SPM”, Z = −1.94). This sector-specific pattern of normative belief influence aligns with Magano et al.’s [6] contingency model but adds the crucial dimension of organizational support systems as moderators. The practical implication is profound: normative belief interventions must be tailored to industry-specific reference groups rather than applied generically.

The Dual Pathways of Control Belief Influence

Most significantly, our analysis reveals that perceived behavioral control operates through two distinct pathways in project environments, necessitating a bifurcation of Ajzen’s [14] original construct. Personal agency deficits (Factor 2’s “I lack tools”, Z = 1.21) reflect individual-level control limitations, while organizational enablement failures (Factor 3’s “No clear guidelines”, Z = 2.56) represent system-level constraints. This distinction empirically validates Barneveld and Silvius’s [21] proposition about “layered behavioral control” in project contexts, while addressing a critical gap in Armenia et al.’s [17] implementation framework. The practical consequence is that interventions targeting personal agency (e.g., skills training) will prove ineffective for organizational enablement deficits (e.g., policy gaps), and vice versa.

Demographic Moderators of TPB Relationships

Beyond these core contributions, our demographic findings reveal important boundary conditions for TPB application. The age-related patterns (younger PMs’ greater normative susceptibility in Factor 1) suggest career stage moderates belief hierarchies, supporting but refining Presseau et al.’s [24] life course hypotheses. Industry concentrations demonstrate how sectoral logics reshape belief activation sequences—construction’s procedural focus versus healthcare’s ethical priorities. Perhaps most critically, project scale emerged as a novel moderator, with small-project constraints revealing scale-dependent control belief activation patterns not previously identified in the literature [10].

Collectively, these contributions move beyond merely applying the TPB to project environments, instead offering a refined theoretical model that accounts for the complex interplay between individual beliefs and organizational systems in sustainability implementation. They provide a framework for future research to investigate behavioral change mechanisms in professional contexts while offering practitioners a more nuanced diagnostic tool for barrier analysis.

As a final note, the TPB framework is not merely diagnostic but also prescriptive. By identifying which specific belief type (behavioral, normative, control) is the primary barrier for a given group, organizations can design precise interventions to foster SPM adoption. For instance, our findings suggest that improving attitudes (behavioral beliefs) is less urgent than building competency (control beliefs) and reforming policies (which influence both control and normative beliefs).

5.4. Practical Recommendations: From Barrier Diagnosis to Tailored Implementation

The identified barrier patterns necessitate a move beyond generic sustainability mandates to tailored, belief-sensitive interventions. The following recommendations provide organizations with a strategic roadmap to enable their project managers, categorized by the primary barrier profile they aim to address.

For organizations with “motivated yet confined” PMs, who are constrained by structural barriers, the primary strategy involves embedding Sustainable Project Management (SPM) directly into governance artifacts; that is, revising core project governance documents to mandate sustainable practices. This requires a cross-functional team—comprising strategy, legal, and PMO representatives—to audit and revise core project documents such as procurement templates, project charters, and contracts to mandate sustainability criteria. The implementation roadmap begins with co-creating standardized, project-type-specific requirements, piloting these revised artifacts on volunteer projects to measure added effort versus value, and culminating in company-wide mandates complemented by mandatory training for all PMs and sponsors to ensure adoption and clarity. Concurrently, equipping these PMs with client engagement toolkits is essential; this involves developing sector-specific business cases that articulate the value of SPM and providing templates for proposals and meetings that integrate sustainability options, thereby empowering PMs to proactively manage client expectations and advocate for sustainable practices with formal authority.

For “motivated yet lacking competency” PMs, who struggle with skill and knowledge gaps, intervention should focus on developing scalable, sector-specific SPM toolkits that move beyond one-size-fits-all frameworks. The implementation process starts with auditing and curating existing resources into a modular digital library tagged by project type, size, and phase, which is especially crucial for agile environments where micro-tools like a “sustainability sprint checklist” are needed. This must be paired with a shift to just-in-time micro-training, where learning modules are directly linked to project phase gates; for instance, a short module on stakeholder sustainability analysis becomes a prerequisite for planning sign-off. To ensure effectiveness, organizations should launch a digital portal to host these resources and foster peer learning through mentorship programs that pair less experienced PMs with proven SPM champions, thereby building practical self-efficacy through accessible tools and supported application.

Addressing the systemic gaps faced by “motivated yet unsupported” PMs requires interventions that provide clarity and dedicated support. A critical step is establishing “sustainability translator” roles to operationalize high-level policies into practical project guidance. The roadmap for this involves formally defining this new role, piloting it as a funded position in a high-volume division like IT or facilities for 6–12 months to measure the impact on project outcomes and PM satisfaction, and—based on proven success—integrating it as a permanent function within the PMO or sustainability office. Furthermore, eliminating ambiguity through clear accountability structures is paramount; this entails explicitly incorporating sustainability performance into the terms of reference for project owners and sponsors, linking the achievement of sustainability KPIs to performance reviews and incentives, and establishing formal escalation pathways for PMs to request resources when they encounter sustainability risks beyond their authority. By implementing these tailored, roadmap-driven strategies, organizations can systematically dismantle the specific barriers their project managers face, thereby transforming underlying motivation and emerging competency into practical and sustainable project outcomes.

5.5. Limitations and Future Research

The geographic concentration of participants in Austria (and primarily Vienna), a region with a strong regulatory environment and high sustainability awareness, likely influenced the results. The overrepresentation of the construction sector further amplifies this context, as this industry is often subject to stringent regulations. This may have led to an overemphasis on structural and policy barriers (Factor 1) compared to what might be found in a more geographically and industrially diverse sample from regions with weaker sustainability governance. Future cross-cultural comparative studies are essential to disentangle the effects of national policy environments from individual and organizational barriers. Moreover, as noted in the discussion, the generalizability of our findings may be influenced by a potential sampling bias towards project managers who are already engaged with or positively inclined towards sustainability concepts. Consequently, while the identified patterns provide a nuanced understanding of the barriers faced by motivated practitioners, they do not capture the perspectives of truly resistant or disengaged project managers. Investigating the belief systems of these individuals represents a vital avenue for future research to provide a complete spectrum of barrier perceptions. While the Q-methodology captured rich subjective data, longitudinal designs could track how interventions alter belief systems over time. Also, the sample’s demographic composition, which skewed towards younger project managers, may influence the generalizability of the findings. Younger professionals might experience barriers differently than their more experienced counterparts; for instance, they may perceive stronger organizational constraints due to less established influence or navigational capital within their organizations [54]. Future research should deliberately oversample older and more senior project managers to explore whether career stage and tenure alter barrier perceptions. Additionally, the gender dynamics observed (female PMs underrepresented in Factor 2) warrant targeted investigation given potential gendered socialization in STEM fields [13]. Such work will further contribute to our understanding of how to make sustainability an integral and achievable aspect of project management practice across diverse contexts.

Concluding, this study advances the TPB by revealing how organizational ecosystems filter individual sustainability intentions. The control belief bifurcation, normative paradox, and demographic moderators collectively provide a diagnostic framework for barrier analysis. Practitioners must recognize that motivation, while necessary, is insufficient without tailored structural supports. Future efforts should develop context-sensitive implementation tools that account for sector, career stage, and project scale—moving beyond one-size-fits-all sustainability mandates.