The Paradox of Trust: How Leadership, Commitment, and Inertia Shape Sustainability Behavior in the Workplace

Abstract

This study explores the factors driving employees’ sustainability-switching behaviors (SSBs) by integrating the Push, Pull, and Mooring (PPM) model with the Theory of Reasoned Action (TRA). A quantitative, cross-sectional survey was conducted with a convenience sample of 132 professionals actively involved in organizational sustainability initiatives across diverse industries and global regions. The findings reveal that leadership commitment significantly fosters both affective and normative employee commitments, with normative commitment positively influencing SSB. Surprisingly, organizational trust showed a negative impact on SSB, suggesting that employees may delegate responsibility for sustainability to the organization when trust is high. Inertia emerged as a strong barrier to behavioral change, independently inhibiting sustainability efforts. The study highlights the complex dynamics among leadership, trust, and inertia, offering practical insights for organizations aiming to foster sustainability. Addressing inertia directly and promoting shared responsibility for sustainability are critical for successful organizational transitions. Future research should explore the psychological mechanisms behind inertia and further investigate the paradoxical role of trust in sustainability initiatives.

1. Introduction

Sustainability transitions at both organizational and individual levels have become imperative in addressing the growing global challenges posed by environmental degradation, socioeconomic inequalities, and unsustainable patterns of production and consumption. While corporate sustainability strategies have traditionally focused on macro-level initiatives, such as technological innovation, regulatory compliance, and strategic environmental management (George & Schillebeeckx, 2022), there is a growing consensus that the effectiveness of these initiatives increasingly depends on micro-level, employee-driven behaviors (Chaudhary, 2019).

Despite this growing recognition, important gaps remain in our understanding of the mechanisms that foster sustainable workplace behaviors. Employee engagement in sustainability initiatives is a complex and dynamic process, shaped by the interplay of cognitive, emotional, and contextual factors embedded within organizational environments. While established frameworks, such as the Theory of Reasoned Action (TRA) (Ajzen, 2011), have contributed valuable insights by linking attitudes, subjective norms, and behavioral intentions, their focus on individual will often underestimates the influences of external constraints, organizational culture, and structural barriers that may inhibit sustainable behaviors, even when intentions are favorable.

To address these limitations, this study proposes an integrative framework by combining the Push, Pull, and Mooring (PPM) model with TRA. Originally developed to explain migratory decisions (Moon, 1995), the PPM model offers a useful lens to conceptualize how employees move from unsustainable to sustainable behaviors within organizational contexts. In this adapted framework, Push factors refer to internal motivations that drive behavioral change, such as leadership commitment to sustainability; Pull factors represent external organizational influences that attract employees toward sustainable behaviors, such as organizational trust; and Mooring factors capture personal and contextual obstacles that hinder behavioral change, notably behavioral inertia.

Integrating these models allows for a more comprehensive analysis of the interdependent psychological, social, and contextual factors influencing sustainability-related behaviors at work. Prior applications of the PPM framework in sustainability contexts have been limited and often overlook the mediating roles of affective and normative commitments or the moderating effects of personal inertia in sustaining or obstructing behavioral change (Bravo & Ostos, 2021; Khan et al., 2020).

Given the increasing pressure on organizations to foster sustainable business models, understanding the factors that facilitate or impede employee engagement in sustainability initiatives is critical. To address this concern, this study seeks to answer the following research question: What are the key constructs and factors that contribute to enhancing employees’ sustainability attitudes and behaviors, thereby promoting a transition toward corporate sustainability?

This study seeks to fill these gaps by addressing the following research objectives (ROs): RO1—How does leadership commitment influence affective and normative employee commitments in the context of sustainability transitions?; RO2—What is the role of organizational trust in predicting employees’ sustainability-switching behaviors?; and RO3—How does behavioral inertia function as a barrier to employees’ sustainability behaviors, and does it moderate the influences of leadership commitment, employee commitment, and trust?

By achieving these objectives, the study contributes to the sustainability management literature in three main ways: (1) refining the TRA by integrating contextual and organizational dimensions through the PPM framework, thereby surfacing paradoxical dynamics, such as overconfidence and behavioral inertia; (2) adapting and applying the PPM model to employee behavior in sustainability initiatives; and (3) offering practical recommendations for managers and policymakers to strengthen employee engagement in organizational sustainability transitions.

The remainder of this paper is structured as follows: the next section provides a detailed review of the theoretical foundations, including the TRA and the PPM model, followed by the development of the hypotheses. The methodological framework is then outlined, including research design, data collection, and analysis methods. The results are subsequently presented, discussed, and interpreted, considering the research hypotheses, followed by conclusions, practical implications, and suggestions for future research.

2. Theoretical Development and Hypotheses

In the present study, a conceptual model is developed using the Theory of Reasoned Action and migration theory. An explanation will be given, in the next subsections, about the insights found in the literature and their rationale, which support the hypotheses that were formulated.

2.1. Theory of Reasoned Action (TRA)

The Theory of Reasoned Action (TRA), developed by Fishbein and Ajzen (2009), proposes that behavior is directly determined by behavioral intentions, which are themselves influenced by two primary factors: attitudes toward the behavior and subjective norms (Ajzen, 2011). Attitudes reflect an individual’s evaluation of whether performing a given behavior is favorable or unfavorable, while subjective norms capture the perceived social pressures to perform or avoid the behavior.

Although TRA has been widely applied in organizational contexts, it presents certain limitations and specific boundaries of applicability. By design, TRA is a cross-sectional model, which constrains its ability to explain behavioral changes over time—a significant limitation in dynamic organizational environments, where relationships among variables evolve continually (Boster et al., 2014). Furthermore, in some organizational settings, intention alone may not sufficiently predict behavior. For example, within the domain of continuous improvement capabilities or complex workplace processes, contingency factors, such as the organizational climate, extrinsic incentives, or operational constraints, often influence whether intentions materialize into action (Chitraranjan & Botenne, 2024; Yen-Tsang et al., 2012). This limitation becomes particularly evident in technology-intensive environments, where TRA’s linear assumption of intention leading directly to behavior may oversimplify the complex, reciprocal dynamics of human–technology interactions (Almahri & Saleh, 2024).

An additional critique involves the expectancy-value framework used in TRA analyses, which can produce statistically ambiguous or uninterpretable results, a concern sometimes referred to as the ‘expectancy-value muddle’ (La Barbera & Ajzen, 2020). Moreover, while TRA emphasizes intention as the nearby predictor of behavior, intention alone does not guarantee action. This intention–behavior gap is particularly salient in organizational settings, where social-psychological forces, organizational priorities, or structural barriers can intervene between intention and behavioral execution (La Barbera & Ajzen, 2020). In this sense, the model assumes that behavior follows linearly from motivation, often underestimating the role of external and contextual factors that may inhibit action, even in the presence of strong positive intentions (Mishra et al., 2014).

Despite these limitations, TRA remains a well-established and frequently applied framework in organizational research (Boustani & Chammaa, 2023; López & Costa, 2024; Mishra et al., 2014). It has been employed to examine factors influencing training transfer, where attitudes toward training and perceived relevance significantly affect the intention to apply acquired skills (Mohammed Turab & Casimir, 2015). Additionally, TRA has been widely used to explore knowledge-sharing behaviors in organizations, identifying factors such as extrinsic motivators, organizational climate, self-efficacy, and reciprocity as significant predictors of employees’ intentions to share knowledge (Curado et al., 2025; Olan et al., 2022).

TRA has also been extended in ethical decision-making studies, incorporating constructs like ethical judgment and behavioral norms to better explain how individuals integrate multiple cognitive and normative elements when making ethical choices (Lim et al., 2023). In the field of climate change communication, the model has been instrumental in designing strategies to influence behavioral intentions regarding pro-environmental actions (Han, 2021; Nguyen et al., 2018).

While TRA asserts that intention precedes behavior, in practice, intention functions as a necessary but not sufficient condition for behavioral enactment. For example, even if an employee intends to adopt sustainable practices, such behaviors are unlikely to occur if the organization does not actively promote and support sustainability. The greater an organization’s commitment to sustainability, the more likely employees are to engage in sustainable behaviors driven both by internalized standards and social pressures from their workplace environment (Han, 2021; Untaru et al., 2016).

While this study integrates the TRA with the PPM model to address contextual and structural constraints, it is important to clarify how this framework relates to adjacent models commonly applied in sustainability behavior research. The Norm Activation Model (NAM) (Schwartz, 1977), the Theory of Planned Behavior (TPB) (Ajzen, 1991), and the Value–Belief–Norm (VBN) theory (Stern et al., 1999) each offer complementary perspectives by incorporating personal norms, perceived behavioral control, and value-based moral obligations, respectively. However, these frameworks typically emphasize psychological determinants without explicitly modeling organizational or institutional constraints. By incorporating mooring factors, such as behavioral inertia and paradoxical trust dynamics, the integrated TRA–PPM framework captures both individual-level intentions and the structural forces that enable or inhibit behavioral switching. This dual focus provides explanatory gains by identifying why intention-rich but action-poor contexts persist, and how leadership and contextual clues interact with these constraints, offering a more comprehensive account of sustainability transitions within organizational environments.

2.2. Push, Pull, and Mooring (PPM) Model

Frameworks describing push and pull factors have been widely applied in migration research across various scientific disciplines (Bravo & Ostos, 2021; Fang & Li, 2022; Sajjad et al., 2020). Among these, the Push–Pull–Mooring (PPM) model stands out for its ability to conceptualize and model the factors influencing an individual’s movement from one point to another whether that movement is voluntary or involuntary, temporary or permanent (Moon, 1995).

In change processes, push factors represent negative conditions or pressures at the point of origin that drive individuals away, while pull factors reflect positive attributes or opportunities at the destination that attract them (Bansal et al., 2005). However, due to the complexity of decision-making processes underlying change behaviors, push and pull factors alone are insufficient to fully capture the nuances of migration decisions. As Hou et al. (2011) argue, individuals sometimes feel compelled to move for reasons not easily explained by these categories. This necessitates the inclusion of a third category—intervening variables, or mooring factors—as originally proposed by Moon (1995).

Mooring factors refer to personal, social, cultural, and contextual conditions that can either facilitate or hinder the decision to stay or leave a given situation. These factors serve as anchors or constraints in the decision-making process, influencing whether individuals act on push and pull pressures. Recognizing this, the PPM model functions as an integrated framework for analyzing how positive, negative, and restrictive forces jointly shape intentions to change (Tang & Chen, 2020).

In this framework, attitudes toward change, whether favorable, unfavorable, or indifferent, play a crucial role, as they interact with economic, social, environmental, and psychological factors to influence individual decisions (Sajjad et al., 2020). For sustainable transitions to occur, it is therefore essential to understand how various micro- and macro-level factors interact to support or impede behavioral change.

A consistent theme in studies using the PPM model is that it does not prescribe a fixed set of variables. Instead, it acknowledges that the specific factors driving movement between points are context dependent, varying across situations, individuals, and environments (Bansal et al., 2005; Wang et al., 2020). The literature highlights that both positive and negative forces, whether individual or institutional, micro or macro in nature, contribute to shaping intentions and behaviors, increasing or decreasing the likelihood of change (Bravo & Ostos, 2021; Fang & Li, 2022; Sajjad et al., 2020).

Moreover, identifying the consistency and intensity of these impacts on attitudes, intentions, and behaviors is critical for understanding and managing behavioral change processes (Del Giudice et al., 2017; Xu et al., 2021). This underscores the importance of determining which factors are the most decisive for success or failure in each context, thereby enabling organizations or policymakers to act strategically to promote the desired transitions.

The aim of this research is to explore the factors influencing individual attitudes and behaviors toward sustainability transitions, using the PPM model as an analytical lens. By identifying and examining key push, pull, and mooring factors, this study seeks to uncover promising drivers for promoting organizational and individual sustainability behaviors. The following sections present the rationale for selecting the PPM factors used in this study, along with the hypotheses to be assessed. The conceptual framework supporting this research is illustrated in Figure 1.

2.2.1. Push Factors

Push factors are understood as the motivational drivers that promote behavioral change, grounded in attributes or conditions that encourage individuals to leave an undesirable situation in pursuit of a more favorable one (Haldorai et al., 2019). For instance, social inequalities, poor working conditions, or organizational injustices can negatively impact an individual’s quality of life and job satisfaction, creating a tension between their current state and an ideal, desired situation. In this study, commitment is conceptualized as a push factor capable of shaping employees’ intentions to migrate toward sustainable behaviors within organizations.

Organizational commitment should be viewed strategically, encompassing both the organization’s capacity and willingness to foster multiple forms of commitment with its diverse stakeholders (Ferro-Soto et al., 2018) and employees’ alignment with the organization’s objectives and sustainability values (Yan et al., 2019). In this sense, commitment operates as a motivational force that binds or fails to bind individuals to actions that support organizational goals (Bakker, 2013). A lack of clearly articulated commitments and transparent action plans on sustainability inevitably undermines individual engagement, increasing perceptions of irresponsibility, dissatisfaction, and behavioral inertia (Bravo & Ostos, 2021; Fonseca et al., 2021).

Employee commitment itself is a multidimensional construct, traditionally comprising three dimensions, as defined by Meyer and Allen (1991): affective commitment (a desire to remain), continuance commitment (a need to remain), and normative commitment (a sense of obligation to remain). This study focuses on the affective and normative dimensions. Affective commitment reflects the emotional attachment employees feel when they perceive alignment between their personal values and the organization’s sustainability goals. Research demonstrates that organizations actively engaged in sustainability initiatives can strengthen employees’ affective commitments by fostering shared values (Lee & Ha-Brookshire, 2020; Taştan & Davoudi, 2019). Employees are more likely to feel emotionally invested in their organization when its sustainable practices identify with their own beliefs (Brickson, 2007).

Normative commitment, in contrast, relates to employees’ internalized senses of moral obligation to support organizational initiatives (Meyer & Parfyonova, 2010). This moral duty often arises when employees identify with the company’s social and environmental responsibility efforts. Peterson (2004), for example, found that when employees perceive their organization’s corporate social responsibility initiatives as being meaningful, their normative commitment increases.

Furthermore, there is broad agreement that an organization’s commitment to sustainability is conveyed through the conduct of its leaders, who model and communicate expectations for sustainable behavior to their teams (Wesselink et al., 2017; Yucel et al., 2014). Employees observe and respond to leaders’ behaviors, gradually adopting and identifying with the sustainability practices their leaders champion (Nicholson & Kurucz, 2019). Empirical evidence confirms that increasing awareness of green initiatives and socially responsible practices fosters employees’ willingness to adopt sustainable behaviors, including social protection and ethical conduct (Asadi et al., 2019). This reinforces both affective and normative commitments within the workplace.

In this context, the organization’s commitment to integrating sustainability begins with ethical leadership. Drawing on Brown et al.’s (2005, p. 120) definition, ethical leadership involves “the demonstration of normatively appropriate conduct through personal actions and interpersonal relationships and the promotion of such conduct to followers through two-way communication, reinforcement, and decision making.” This suggests that commitment is intricately linked to leadership conduct, as employees interpret leaders’ ethical behaviors as signals that inform their own attitudes, emotional attachment, and sense of moral duty in a climate of trust and transparency.

Ultimately, commitment is perceived and measured through the value and benefits it generates for employees and stakeholders. Its authenticity can be evaluated by assessing the consistency of leaders’ actions in promoting sustainability, the relationships of trust they build with stakeholders, and the reputation they establish within and beyond the organization. Based on these considerations, and as illustrated in Figure 1 (the research model), the following hypotheses are proposed:

Hypothesis 1a (H1a):

Leadership commitment to sustainability positively influences employees’ affective commitments.

Hypothesis 1b (H1b):

Leadership commitment to sustainability positively influences employees’ normative commitments.

Hypothesis 2 (H2):

Employees’ affective commitments are positively related to sustainability-switching behavior.

Hypothesis 3 (H3):

Employees’ normative commitments are positively related to sustainability-switching behavior.

2.2.2. Pull Factors

In migration theory, decisions about whether to move are influenced not only by the conditions at the current location but also by the perceived attractiveness of the destination. In this context, pull factors refer to the attributes of the destination that positively attract individuals (Bansal et al., 2005). Within organizational settings, such pull factors might include talent retention practices, environmental stewardship, responsiveness to stakeholder expectations, and employees’ perceptions of how well their organization cares for their well-being.

In this study, organizational trust (OT) is conceptualized as a key pull factor, influencing employees’ attitudes and behaviors toward sustainability. Trust, in this sense, reflects the identity the organization projects through its policies, values, principles, and behaviors in favor of sustainable development. It also signals how organizational leaders acknowledge, address, and value the needs and contributions of their employees and other stakeholders (Kidron & Vinarski-Peretz, 2022). Increasingly, research recognizes that meaningful progress toward sustainability requires not only top-down policies but also collaborative involvement across all organizational levels and stakeholders (Silvestre & Fonseca, 2020).

Trust is a gradual, cumulative process, continuously built and reinforced through interpersonal and organizational interactions (Brower et al., 2000). It is embedded in the daily relationships formed between organizations and their stakeholders. In this regard, organizational trust manifests as a dual construct: it encompasses both employees’ trust in the organization’s values and systems and their trust in its leadership (Bai et al., 2024; Ilyas et al., 2020). Employees assess qualities such as ethical conduct, competence, fairness, integrity, and relational care demonstrated by their leaders, and these perceptions shape the overall trust within the organization.

Empirical studies indicate that organizations committed to sustainability and social responsibility are more attractive to employees (Backhaus et al., 2002). When employees perceive that their organization actively promotes sustainability practices and social impact initiatives, they are more likely to align with those values, strengthening their trust in the organization. This, in turn, fosters the development of positive attitudes and behaviors, encouraging employees to see themselves as contributors to organizational sustainability efforts rather than as passive observers. Accordingly, and as illustrated in Figure 1 (the research model), the following hypothesis is proposed:

Hypothesis 4 (H4):

Organizational trust positively influences sustainability-switching behavior.

2.2.3. Mooring Factors

Mooring factors are intervening variables associated with favorable or unfavorable aspects of the migration process itself, shaped by personal, social, psychological, and cultural values. These factors have the potential to moderate the influences of both push and pull factors on migration-related decisions (Bansal et al., 2005).

Migratory processes and, by extension, behavioral change processes are often grounded in change models that weigh the costs and benefits of moving from one state to another. These models consider both monetary and non-monetary sacrifices, including time, effort, uncertainty, and emotional investment (Han et al., 2011). A central element in this equation is the individual’s attitude toward change, which significantly shapes switching behavior (Bansal et al., 2005). In this context, attitudes reflect a person’s predisposition to respond positively or negatively to a behavior (Ajzen, 2005) and have been widely applied in migration and change behavior studies (Bravo & Ostos, 2021; Sajjad et al., 2020).

Research has shown that attitudes encompassing cognitive, affective, and behavioral components can generate positive or negative evaluations depending on the anticipated outcomes of a given behavior (Ajzen, 2011). This suggests that behavioral change processes, including those related to sustainability, depend heavily on individual awareness, the perceived value of the change, and personal decision making. Frameworks such as the TRA affirm that the decision to maintain the status quo or move toward change is influenced by the perceived cost of the change, the expected benefits, and the presence of behavioral inertia (Ashby & Teodorescu, 2019; Bravo & Ostos, 2021; Kornilaki & Font, 2019).

Behavioral change toward sustainability, in particular, can be triggered by multiple factors, including economic, cognitive, emotional, and belief-based drivers (Kornilaki & Font, 2019). Yet this change is also contingent upon the time, effort, and commitment an individual is willing to invest in adopting new sustainable behaviors. The perception of benefit, or its absence, relates to one’s adaptability to new realities and the perceived value of making such efforts (Bravo & Ostos, 2021).

When individuals lack sufficient motivation to engage in sustainability-oriented actions, they tend to maintain existing behavioral patterns, reinforcing the status quo (Kornilaki & Font, 2019; Polites & Karahanna, 2012). This entrenched state is known as behavioral inertia, defined as the persistence of existing attitudes and practices despite the availability of more advantageous alternatives (Lai et al., 2017; Polites & Karahanna, 2012). Studies consistently show that inertia acts as a barrier to change, negatively affecting the formation of positive attitudes toward new behaviors (Bravo & Ostos, 2021; Lai et al., 2017).

It is widely recognized that overcoming behavioral inertia requires the intervention of external forces or organizational mechanisms capable of disrupting established patterns and reconfiguring attitudes toward change (Polites & Karahanna, 2012). Given this, and as illustrated in Figure 1 (the research model), the following hypotheses are proposed:

Hypothesis 5 (H5):

Inertia negatively influences employees’ sustainability-switching behaviors.

Hypothesis 6 (H6a):

Inertia negatively moderates the relationship between employees’ affective commitments and sustainability-switching behaviors.

Hypothesis 6 (H6b):

Inertia negatively moderates the relationship between employees’ normative commitments and sustainability-switching behaviors.

Hypothesis 7 (H7):

Inertia negatively moderates the relationship between organizational trust and sustainability-switching behavior.

3. Methodology

This study employs a structured quantitative research design to investigate the factors influencing employees’ sustainability-switching behaviors (SSBs) within organizations. The methodology encompasses several key components, including the research instrument, data collection procedures, sample characteristics, and statistical analyses employed to assess the proposed hypotheses.

3.1. Research Instrument

The development of a valid and reliable research instrument was essential for capturing the multidimensional factors influencing sustainability-switching behaviors (SSBs) among employees. To this end, the study designed a structured questionnaire, integrating constructs drawn from the PPM model and the TRA. The instrument was structured around six key constructs identified in the literature as primary drivers of sustainability-related behavior: leadership commitment (LC), affective employee commitment (AEC), normative employee commitment (NEC), organizational trust (OT), inertia (I), and sustainability-switching behavior (SSB).

To ensure both content validity and reliability, each construct was measured using established scales adapted from prior validated studies, selected for their proven applicability in assessing organizational and employee behaviors within sustainability contexts:

• Leadership Commitment (LC): Assessed with a five-item scale adapted from Brown et al. (2005) and Liden et al. (2015), focusing on leaders’ ethical conduct and sustainability-oriented actions.
• Affective Employee Commitment (AEC): Measured with a five-item scale adapted from Allen and Meyer (1990) and Gyensare et al. (2016), capturing employees’ emotional attachments to and identification with their organization.
• Normative Employee Commitment (NEC): Evaluated using a four-item scale adapted from Allen and Meyer (1990), reflecting employees’ senses of moral obligation to support their organization’s sustainability goals.
• Organizational Trust (OT): Measured with a four-item scale adapted from Robinson and Rousseau (1994), assessing trust in the organization’s ethical integrity and its commitment to sustainability.
• Inertia (I): Assessed using a four-item scale adapted from Polites and Karahanna (2012), capturing employees’ resistances to behavioral change, even when confronted with sustainability initiatives.
• Sustainability-Switching Behavior (SSB): Measured with a three-item scale specifically designed for this study, evaluating employees’ willingness to adopt sustainable behaviors in response to organizational initiatives.

All the items were rated on a five-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree), allowing participants to express the degree of their agreement, perception, or intention toward each item.

For clarity and transparency,

Table 1. Adapted instrument and scale.

Construct	Adapted From	Measurement Items
Leadership commitment (LC)	Brown et al. (2005); Liden et al. (2015)	(LC1) My manager emphasizes the importance of giving back to the community. (LC2) My manager considers my opinions and values about the environment, economy, and society. (LC3) My manager encourages employees to attend environmental and social initiatives. (LC4) My manager openly engages in discussions around sustainability topics. (LC5) I feel quite confident that my manager will try to follow the sustainable development goals.
Affective employee commitment (AEC)	Allen and Meyer (1990); Gyensare et al. (2016)	(AEC1) I do not feel ‘emotionally attached’ to the sustainability programs of this organization. (R) (AEC2) This organization has a great deal of personal meaning for me. (AEC3) I really feel as if this organization’s environmental problems are my own. (AEC4) I do not feel a strong sense of belonging to my organization. (R) (AEC5) Right now, staying with my organization is a matter of necessity as much as desire.
Normative employee commitment (NEC)	Allen and Meyer (1990)	(NEC1) I do not feel any obligation to remain with my current employer. (R) (NEC2) The social and environmental reputation of the organization is of great importance to me. (NEC3) This organization deserves my loyalty. (NEC4) I would not leave my organization right now because I have a sense of obligation to the people in it.
Organizational trust (OT)	Robinson and Rousseau (1994)	(OT1) I believe my organization has a high degree of ethical integrity. (OT2) My organization is not always honest and truthful in sustainable practices. (R) (OT3) I am not sure I fully trust the organization’s sustainability approaches. (R) (OT4) My organization’s management is sincere in its attempts to address the points of view of its employees and stakeholders.
Inertia (I)	Polites and Karahanna (2012)	(I1) Overall, I am not sure my contribution will help my organization’s sustainability practices. (I2) I am not ready to make the extra effort needed to change my habits for the reason of the environment. (I3) I will continue to do my routines even though I know it is not the most efficient way to do things. (I4) Overall, I do not identify with the sustainable practices of my organization.
Sustainability-switching behavior (SSB)		(SSB1) I am determined to switch to increased environmental and social behavior. (SSB2) I will be more consistent in my attitude toward sustainability. (SSB3) The likelihood of my switching to increase sustainable behavior is high.

Scale: Responses ranged from 1—‘strongly disagree’ to 2—“disagree”; 3—“undecided”; 4—“agree”; 5—“strongly agree”. Note: (R) indicates a reverse-keyed item. Scores on these items should be reflected (i.e., 1 = 5, 2 = 4, 3 = 3, 4 = 2, and 5 = 1) before computing scale scores. Source: Authors’ own.

presents a detailed breakdown of the items included in each construct, providing a comprehensive overview of the research instrument’s design and operationalization.

3.2. Validity and Reliability

Ensuring the validity and reliability of the research instrument was a critical step in the study’s methodological process. The initial version of the questionnaire underwent a content validation process by a panel of five experts specializing in organizational psychology, management, communication, and sustainability. These specialists were invited to assess the questionnaire for the appropriateness of its terminology, the clarity of the items, and the objectivity of its measurement scales. Based on their feedback, minor revisions were made to enhance the phrasing of certain items and to refine the overall structure of the instrument for greater clarity and contextual alignment.

To assess the internal consistency reliability of the scales, Cronbach’s alpha coefficients were calculated for each construct (McDonald, 1970). A threshold of 0.70 was established as the minimum acceptable value, with values above this indicating satisfactory internal consistency. In addition to the reliability assessment, the content validity of the instrument was reinforced both by the expert evaluations and through the careful selection of established, previously validated scales drawn from the existing literature.

This validation process confirmed that the instrument was contextually appropriate and relevant to employees across different organizational sectors, strengthening the overall robustness of the study’s empirical measurements.

3.3. Sampling Strategy

This study used a non-probabilistic convenience sampling approach (Forza, 2002). This strategy was chosen due to the exploratory nature of the research and the practical challenges associated with accessing a geographically dispersed and industry-diverse population of employees engaged in sustainability-related activities. The professional networking platform LinkedIn provided an efficient channel for reaching individuals across multiple sectors and global regions. To ensure relevance to the study objectives, clear inclusion criteria were communicated within the survey introduction.

The authors acknowledge that the use of convenience sampling and self-reported eligibility introduces potential limitations. The voluntary nature of participation and reliance on a self-selected, digitally networked sample may have resulted in a response bias toward individuals with a heightened interest or predisposition toward sustainability issues. In this study, involvement was determined through a self-reported screening question asking whether respondents were directly or indirectly engaged in sustainability-related initiatives, programs, or responsibilities within their organization. For the purposes of this study, active involvement was operationalized as participation in roles such as contributing to organizational sustainability reports, leading, or supporting environmental initiatives, participating in corporate social responsibility (CSR) teams, or holding responsibilities directly related to sustainability program implementation. Additionally, the operational definition of involvement may vary between industries and organizational contexts, affecting the uniformity of the respondents’ experiences.

While efforts were made to maximize the diversity of the sample sectors, geographies, and professional roles, the findings should be interpreted within the context of this sampling approach, and caution is advised when generalizing the results to the broader employee population.

3.4. Data Collection

The research employed a structured, quantitative survey method, with data collected through a self-administered electronic questionnaire. The survey was distributed to employees occupying middle and senior leadership positions across different sectors via the professional networking platform LinkedIn. This distribution method ensured broad access to professionals with experience in corporate sustainability initiatives, capturing insights from employees directly involved in or impacted by organizational sustainability efforts.

The questionnaire was administered in English and accompanied by a detailed introduction that outlined the study’s objectives and ensured participants of the confidentiality of their responses. Ethical considerations were paramount throughout the research process. The anonymity and confidentiality of the participants were prioritized, with all the data collected securely stored and accessible only to the research team. Participation was voluntary, with respondents informed of their right to withdraw at any time without any consequences. The study protocol adhered to ethical guidelines, ensuring that the research was conducted with integrity and respect for the participants’ rights.

To further increase the response rates, a follow-up reminder was sent two weeks after the initial invitation. Data collection took place in the first semester of 2024. Data collection followed a non-probabilistic convenience sampling methodology used in other studies (Fonseca et al., 2021).

The link to the survey was shared by 32 of those groups, yielding 157 responses. After data cleaning to remove incomplete or incorrectly completed questionnaires, a final sample of 132 valid responses was retained, resulting in a response rate of 22%; this response rate is consistent with similar studies employing digital surveys (Martens & Carvalho, 2017).

3.5. Sample Characteristics

To ensure that the results are generalizable across different demographic and organizational contexts, the study captured various characteristics of the respondents. The demographic section of the questionnaire included questions about age, gender, education level, professional experience, organizational role, and geographic location.

The demographic profile provides a contextual understanding of the sample. In this study, 53% of the respondents were female, and 73% of the participants fell between the ages of 21 and 50. Additionally, 46% held senior management positions, and 38% had more than 21 years of professional experience. Most respondents were highly educated, with only 4% holding a basic level of education. Geographically, the respondents represented five continents, ensuring a diverse sample that enhances the external validity of the findings.

Table 2. Socio-psychographic profile of the respondents.

Demographic Profile		By Count (N = 132)	By Percentage (%)
Gender	Male Female	62 70	47.0 53.0
Age (years)	<20 21–30 31–40 41–50 51–60 >61	- 34 30 33 20 15	- 25.7 22.7 25.0 15.2 11.4
Academic qualification	High school (or equivalent) College graduation Post-graduation or specialization Master’s degree PhD degree	5 13 30 63 21	3.7 9.8 22.8 47.8 15.9
Professional experience (years)	From 1 to 5 From 6 to 10 From 11 to 20 21 or more	35 19 28 50	26.6 14.4 21.2 37.8
Current professional position	Entry level Intermediate level/Experience level Line management Middle management Senior management	12 27 15 17 61	9.0 20.4 11.4 12.9 46.3
Organizational dimension (employees)	Small (<50) Medium (from 51 to 250) Large (>251) Multinational	63 15 25 29	47.8 11.4 18.9 21.9
Activity sector (*)	Extraction (1) Transformation (2) Services (3) Knowledge-based activities (4)	11 21 53 47	8.3 15.9 40.1 35.7
Geographic participation	Africa America Asia Europa Oceania	4 20 23 77 8	3.0 15.2 17.5 58.3 6.0

^(*) (1) such as natural resources and agriculture; (2) such as manufacturing, construction, and processing and producing goods; (3) such as entertainment, finance, retailers, consultancy, and tourism; (4) such as information technology, research, and education. Source: Authors’ own.

provides a socio-psychographic profile of the respondents.

The sample size was validated using a power analysis conducted via G*Power 3.1.9.2 software (Faul et al., 2007). Based on an effect size of 0.15 (medium effect), a test power level of 95%, and a significance level of 5%, the minimum sample size required for the study was calculated at 89 participants (Cohen, 1988). With a final sample of 132 valid responses, the study exceeds the minimum requirements, ensuring sufficient statistical power to detect meaningful relationships between variables.

To address the potential for non-response bias, the procedure recommended by Armstrong and Overton (1977) was applied. This involved comparing the first 10% of the responses with the last 10% to check for significant differences in response patterns. The independent sample t-test results indicated no significant differences between early and late respondents, confirming that non-response bias is not a significant issue in this study.

This section outlines the rigorous process followed to ensure the reliability and validity of the research instrument and the robustness of the sample and data collection process. The sample is diverse and sufficiently large, and the research instrument has been validated to ensure that the constructs measured align with established theoretical frameworks. The integration of expert feedback and thorough statistical validation ensures that the data collected can provide meaningful insights into the factors driving sustainability-switching behaviors among employees.

4. Data Analysis and Results

The data analysis aimed to assess the proposed hypotheses by examining the relationships among the key constructs: leadership commitment (LC), affective employee commitment (AEC), normative employee commitment (NEC), organizational trust (OT), inertia (I), and sustainability-switching behavior (SSB). The analysis was conducted in two stages: (1) the evaluation of the measurement model and (2) the assessment of the structural model.

Descriptive statistics, reliability tests, and hypothesis testing were performed using the Statistical Package for the Social Sciences (SPSS) for the preliminary analysis and SmartPLS 4.0 for the structural equation modeling (SEM), allowing for the examination of both direct and moderating effects.

4.1. Measurement Model Evaluation

The evaluation of the measurement model focused on ensuring the reliability and validity of the constructs using composite reliability, convergent validity, indicator reliability, and discriminant validity. The Mahalanobis distance was calculated for 132 observations with no missing data, and 4 observations were identified as multivariate outliers. After the analysis, it was decided to exclude these observations. The final database consisted of 128 observations. These assessments are crucial for verifying that the questionnaire accurately captures the underlying theoretical constructs.

Reliability and Internal Consistency: The composite reliability (CR) was calculated for each construct, with the results confirming acceptable levels of reliability for all the constructs, as the values exceeded the minimum threshold of 0.70 but remained below the upper limit of 0.95 (Hair et al., 2021). This indicates that the measurement items consistently capture the underlying constructs.

Table 3. Measurement model for all the constructs and items.

Variable	N	Min.	Max.	Mean	Std. Deviation	Variance	Skewness	Std. Error	Kurtosis	Std. Error	VIF
AEC1	128	1	5	3.73	1.207	1.456	−0.593	0.214	−0.875	0.425	1.286
AEC2	128	1	5	3.55	1.260	1.588	−0.545	0.214	−0.861	0.425	1.705
AEC3	128	1	5	3.55	1.071	1.147	−0.516	0.214	−0.537	0.425	1.307
AEC4	128	1	5	3.75	1.223	1.496	−0.767	0.214	−0.421	0.425	1.660
AEC5	128	1	5	3.07	1.323	1.751	−0.193	0.214	−1.187	0.425	1.110
I1	128	1	5	2.12	0.993	0.986	0.790	0.214	0.080	0.425	1.403
I2	128	1	5	1.78	0.869	0.755	1.320	0.214	2.155	0.425	1.276
I3	128	1	5	2.11	1.052	1.106	1.057	0.214	0.684	0.425	1.168
I4	128	1	5	2.01	1.016	1.031	0.946	0.214	0.428	0.425	1.551
LC1	128	1	5	3.66	1.213	1.471	−0.547	0.214	−0.892	0.425	3.114
LC2	128	1	5	3.94	1.070	1.146	−0.970	0.214	0.308	0.425	4.182
LC3	128	1	5	3.74	1.131	1.279	−0.736	0.214	−0.206	0.425	3.626
LC4	128	1	5	3.73	1.200	1.441	−0.721	0.214	−0.462	0.425	3.210
LC5	128	1	5	3.80	1.206	1.454	−0.804	0.214	−0.353	0.425	3.437
NEC1	128	1	5	2.98	1.286	1.653	0.097	0.214	−1.166	0.425	1.250
NEC2	128	1	5	4.30	0.797	0.636	−1.346	0.214	2.436	0.425	1.114
NEC3	128	1	5	3.70	1.159	1.344	−0.783	0.214	−0.142	0.425	1.568
NEC4	128	1	5	3.42	1.195	1.427	−0.333	0.214	−0.858	0.425	1.596
OT1	128	1	5	3.81	1.018	1.035	−0.707	0.214	−0.006	0.425	2.308
OT2	128	1	5	3.73	1.112	1.236	−0.539	0.214	−0.670	0.425	2.199
OT3	128	1	5	3.50	1.065	1.134	−0.398	0.214	−0.607	0.425	2.243
OT4	128	1	5	3.70	1.075	1.155	−0.734	0.214	0.070	0.425	2.095
SSB1	128	2	5	4.37	0.697	0.486	−1.070	0.214	1.445	0.425	3.209
SSB2	128	2	5	4.40	0.632	0.399	−0.751	0.214	0.517	0.425	3.520
SSB3	128	2	5	4.37	0.626	0.392	−0.657	0.214	0.479	0.425	2.643

AEC: affective employee commitment; I: inertia; LC: leadership commitment; NEC: normative employee commitment; OT: organizational trust; SSB: sustainability-switching behavior; VIF: variance inflation factor. Source: Authors’ own.

shows that all the CR values are within the acceptable range, confirming the internal consistency.

Convergent Validity: The convergent validity was assessed using the Average Variance Extracted (AVE), where values should exceed 0.50 to indicate that the constructs explain more than half of the variance in their items. Two constructs initially fell below this threshold: affective employee commitment (AEC) and normative employee commitment (NEC). After examining the factor loadings, the items AEC5 and NEC1 were removed due to low loadings, resulting in AVE values that surpassed 0.50 for all the constructs.

Discriminant Validity: The discriminant validity was tested using the Fornell–Larcker criterion, which ensures that a construct is more strongly related to its own items than to other constructs. The square root of the AVE for each construct was higher than its correlation with other constructs, confirming the discriminant validity. Additionally, cross-loadings were examined to ensure that each item was loaded higher on its intended construct than on any other. Two items, AEC3 and OT1, were excluded due to cross-loadings with other constructs.

Table 4. Discriminant validity of the constructs.

Construct	AEC	I	LC	NEC	OT	SSB	AVE	CR
AEC (Affective Employee Commitment)	0.789						0.622	0.831
I (Inertia)	−0.439	0.720					0.518	0.810
LC (Leadership Commitment)	0.548	−0.441	0.888				0.788	0.949
NEC (Normative Employee Commitment)	0.684	−0.414	0.516	0.743			0.553	0.785
OT (Organizational Trust)	0.631	−0.529	0.649	0.676	0.813		0.660	0.853
SSB (Sustainability-Switching Behavior)	0.203	−0.398	0.113	0.350	0.165	0.920	0.846	0.943

AVE: average variance extracted; CR: composite reliability; bold values: square root of the AVE. Source: Authors’ own.

shows the discriminant validity at the construct level, and

Table 5. Results of the factor analysis (cross-loadings).

Variable	AEC	I	LC	NEC	OT	SSB
AEC1	0.738	−0.387	0.405	0.517	0.493	0.191
AEC2	0.798	−0.293	0.470	0.574	0.491	0.137
AEC4	0.828	−0.363	0.418	0.523	0.508	0.154
I1	−0.395	0.753	−0.353	−0.428	−0.421	−0.305
I2	−0.302	0.636	−0.218	−0.224	−0.407	−0.198
I3	−0.095	0.677	−0.187	−0.066	−0.102	−0.314
I4	−0.481	0.801	−0.489	−0.460	−0.619	−0.304
LC1	0.545	−0.442	0.880	0.543	0.656	0.090
LC2	0.530	−0.397	0.915	0.470	0.575	0.205
LC3	0.426	−0.287	0.892	0.433	0.506	0.075
LC4	0.411	−0.412	0.860	0.373	0.520	0.094
LC5	0.494	−0.407	0.890	0.440	0.598	0.031
NEC2	0.421	−0.376	0.355	0.704	0.407	0.341
NEC3	0.631	−0.345	0.509	0.863	0.672	0.249
NEC4	0.465	−0.139	0.212	0.647	0.374	0.164
OT2	0.494	−0.465	0.419	0.492	0.787	0.109
OT3	0.501	−0.463	0.523	0.528	0.802	0.085
OT4	0.539	−0.399	0.606	0.605	0.848	0.176
SSB1	0.163	−0.426	0.097	0.324	0.168	0.931
SSB2	0.171	−0.300	0.060	0.314	0.108	0.928
SSB3	0.230	−0.362	0.156	0.326	0.177	0.900

AEC: affective employee commitment; I: inertia; LC: leadership commitment; NEC: normative employee commitment; OT: organizational trust; SSB: sustainability-switching behavior; bold values: highest loads. Source: Authors’ own.

shows the results of the factor analysis (cross-loadings).

Overall, the refined measurement model exhibited good psychometric properties, ensuring the robustness of the constructs for further analysis.

Justification for Item Reduction and Measurement Decisions

In line with the best practices in Partial Least Squares Structural Equation Modeling, item retention decisions were based on a combination of factor loadings, content validity, and their contributions to construct reliability and convergent validity.

Specifically, items AEC5, NEC1, and OT1 were removed post hoc during the measurement model evaluation phase due to low outer loadings (below the recommended threshold of 0.60) and problematic cross-loadings with other constructs. The pre-removal loadings for these items were as follows: AEC5: 0.412; NEC1: 0.475; and OT1: 0.519.

These values fell below Hair et al.’s (2021) recommended minimum acceptable thresholds of 0.60 for exploratory models and 0.70 for confirmatory models. Their removal was further supported by incremental improvements in the Average Variance Extracted (AVE) and Composite Reliability (CR) values across the affected constructs after the exclusion, contributing to the overall model validity.

We acknowledge that several AVE and CR values remained near the minimal thresholds (AVE > 0.50; CR > 0.70) after the adjustments. However, decisions to retain the remaining constructs and their items were theoretically driven, given the foundational roles of affective and normative commitments, organizational trust, and inertia within the integrated TRA-PPM framework employed in this study. The constructs are not interchangeable, and their exclusion would undermine the theoretical integrity of the proposed model (Khan et al., 2020; Peterson, 2004).

Moreover, Hair et al. (2021) and Fornell and Larcker (1981) suggest that AVE values slightly above 0.50 and CR values above 0.70 are acceptable for exploratory models or early-stage theory adaptation studies, particularly when constructs are theoretically indispensable and when their exclusion would omit conceptually meaningful dimensions of the framework.

To further support the model’s robustness, the multicollinearity diagnostics (VIF values) were all below recommended thresholds, and the discriminant validity was confirmed via both Fornell–Larcker criteria (Fornell & Larcker, 1981) and cross-loading inspection, reinforcing the adequacy of the final measurement model.

Nonetheless, we recognize that some constructs demonstrated empirical fragility. Future studies should aim to refine these scales, possibly through item redevelopment, larger sample validation, or multi-method assessments combining attitudinal and behavioral indicators to enhance measurement precision and structural reliability.

4.2. Structural Model Evaluation

Following the validation of the measurement model, the structural model was analyzed to test the proposed hypotheses. The evaluation involved examining the path coefficients, coefficients of determination (R²), effect sizes (f²), and variance inflation factors (VIFs) to assess the relationships between the constructs.

Path Coefficients and Hypothesis Testing: The SmartPLS 4.0 bootstrapping routine (with 5000 subsamples) was used to calculate the path coefficients and their significance levels. The results are summarized in

Table 6. Hypothesis testing and path analysis.

Hypothesis	Relation	Struc. Coeff.	St. Dev.	t Statistic	p-Value	r2	f2	VIF	Result
H1a	LC → AEC	0.548	0.070	7.823	0.000	0.301	0.430	1.000	Supported
H1b	LC → NEC	0.516	0.072	7.183	0.000	0.266	0.362	1.000	Supported
H2	AEC → SSB	−0.113	0.123	0.912	0.362		0.008	2.149	Not supported
H3	NEC → SSB	0.410	0.121	3.387	0.001		0.098	2.362	Supported
H4	OT → SSB	−0.281	0.130	2.167	0.030	0.274	0.048	2.282	Supported
H5	I → SSB	−0.463	0.104	4.431	0.000		0.188	1.569	Supported
H6a	I × AEC → SSB	−0.128	0.155	0.827	0.408		0.008	2.160	Not supported
H6b	I × NEC → SSB	0.121	0.150	0.809	0.418		0.006	2.551	Not supported
H7	I × OT → SSB	−0.148	0.123	1.207	0.228		0.016	1.843	Not supported

AEC: affective employee commitment; I: inertia; LC: leadership commitment; NEC: normative employee commitment; OT: organizational trust; SSB: sustainability-switching behavior; r²: coefficient of determination; f²: effect size; VIF: variance inflation factor. Source: Authors’ own.

and Figure 2, providing evidence for several of the hypotheses.

H1a (leadership commitment positively influences affective commitment) was supported, with a significant positive relationship (p < 0.001, β = 0.431). H1b (leadership commitment positively influences normative commitment) was supported, with a significant positive relationship (p < 0.001, β = 0.378). H2 (affective commitment positively influences sustainability-switching behavior) was not supported, as the relationship was non-significant (p = 0.324, β = 0.112). H3 (normative commitment positively influences sustainability-switching behavior) was supported, with a significant positive relationship (p < 0.01, β = 0.245). H4 (organizational trust positively influences sustainability-switching behavior) was not supported, as the relationship was significant but negative (p = 0.030, β = −0.281). This result was unexpected and suggests that higher levels of trust might lead to reduced personal responsibility for sustainability behaviors. H5 (inertia negatively influences sustainability-switching behavior) was supported, with a significant negative effect (p < 0.001, β = −0.432).

Moderation Analysis: The hypothesized moderating effects of the inertia were tested by examining its interactions with affective commitment (H6a), normative commitment (H6b), and organizational trust (H7). The results revealed no significant moderation effects:

H6a (inertia negatively moderates the relationship between affective commitment and sustainability-switching behavior) was not supported (p = 0.634, β = −0.023). H6b (inertia negatively moderates the relationship between normative commitment and sustainability-switching behavior) was not supported (p = 0.521, β = −0.034). H7 (inertia negatively moderates the relationship between organizational trust and sustainability-switching behavior) was not supported (p = 0.419, β = −0.029).

Coefficients of Determination (R²): The R² values indicate the explanatory power of the model. For the key dependent variable, the sustainability-switching behavior (SSB), the R² value was 0.284, meaning that the model explains 28.4% of the variance in the sustainability behavior. This is considered as moderate (Cohen, 1988) and suggests that other factors not included in the model also play roles in influencing sustainability behaviors. For the affective commitment and normative commitment constructs, the R² values were 0.301 and 0.266, respectively, indicating that leadership commitment has a substantial impact on both types of commitment.

Effect Sizes (f²): The effect size (f²) measures the practical significance of each path in the model. Cohen’s (1988) guidelines suggest that an f² value of 0.02 is small, 0.15 is medium, and 0.35 is large. The effect sizes of the leadership commitment on the affective (f² = 0.430) and normative (f² = 0.362) commitments were both from medium to large, indicating strong practical significance. In contrast, the effect sizes of the normative commitment on SSB (f² = 0.098), organizational trust on SSB (f² = 0.048), and inertia on SSB (f² = 0.188) were from small to moderate, suggesting that these factors, while significant, have limited practical impact on behavioral change.

Variance Inflation Factors (VIFs): VIF values were calculated to assess multicollinearity. All the VIF values were below 3, indicating that multicollinearity is not a concern in this model (Hair et al., 2021).

4.3. Summary of the Results

The analysis supports several key relationships among leadership commitment, employee commitment, organizational trust, inertia, and sustainability-switching behavior. Leadership commitment significantly influences both affective and normative commitments, with normative commitment showing a stronger impact on sustainability-switching behavior. Inertia exerts a strong negative effect on behavioral change, acting as a barrier to the adoption of sustainable practices.

Unexpectedly, organizational trust was found to negatively impact sustainability-switching behavior, suggesting that high levels of trust may reduce employees’ perceived responsibility to engage in sustainability initiatives, possibly due to an over-reliance on the organization to manage sustainability efforts. This finding highlights the complexity of trust dynamics and warrants further investigation.

While the moderating effects of the inertia were not supported, its direct negative effect on behavioral change emphasizes the importance of addressing behavioral inertia when fostering sustainability within organizations.

5. Result Discussion

The results of this study offer a comprehensive understanding of the factors that shape employees’ sustainability-switching behaviors (SSBs), as examined through the integrated lens of the Push, Pull, and Mooring (PPM) model and the Theory of Reasoned Action (TRA). The findings provide both anticipated and unexpected insights into how leadership, trust, employees’ commitments, and behavioral inertia interact to either promote or hinder sustainability-related behaviors within organizational settings.

5.1. Critical Reflection and Theoretical Positioning

While this study offers empirical support for several of the hypothesized relationships, it is essential to critically reflect upon these results, considering the existing literature and potential alternative explanations. Notably, the finding that affective commitment did not significantly influence the sustainability-switching behavior (SSB) contrasts with earlier work (e.g., Erdurmazli, 2025), which suggests that emotional attachment typically fosters pro-organizational behaviors. One possible explanation is that affective commitment alone may lack the normative or instrumental imperative required for employees to actively engage in challenging or disruptive practices, such as sustainability transitions, particularly when such behaviors imply effortful habit change or potential role conflicts (Han et al., 2011).

Equally, the negative relationship between organizational trust and SSB warrants further conceptual reflection. While trust is often positioned as a relational enabler of organizational citizenship behaviors (Bai et al., 2024), recent studies caution against its complacency effects (De Roeck & Farooq, 2018). High levels of trust may reduce personal accountability, as employees assume that sustainability responsibilities are sufficiently managed by organizational leadership or systems. This aligns with the paradox of trust discussed in organizational change literature (Egeland & Stensaker, 2017), where over-reliance on institutional mechanisms can diminish individual initiative.

Furthermore, the expectation that inertia would moderate the relationships among leadership, commitment, trust, and SSB was not supported. A plausible interpretation is that inertia may operate as a contextual barrier independent of interpersonal factors. Recent work by Moradi et al. (2021) and Faraj and Leonardi (2022) indicates that organizational routines, the absence of feedback loops, or a lack of enabling infrastructure are potent sources of behavioral inertia that act structurally, beyond individual psychological reluctance. This reinforces the need to conceptualize inertia not only as an attitudinal construct but as an institutional and operational phenomenon embedded in organizational systems (Ashby & Teodorescu, 2019).

5.2. Differentiating Affective and Normative Commitments in Sustainability Behavior

An important aspect arising from our findings concerns the distinct roles of affective and normative commitments in shaping employees’ sustainability-switching behaviors (SSBs). Although both constructs originate from the seminal (Allen & Meyer, 1990) framework, our results suggest divergent behavioral outcomes that warrant closer examination.

While normative commitment significantly predicted SSB (supporting H3), affective commitment did not (H2 not supported). This result highlights a conceptual nuance that deserves deeper reflection. In sustainability transitions, emotional attachment to the organization may be insufficient to motivate employees toward proactive, and often effortful, behavioral change. Unlike general organizational citizenship behaviors, sustainability behaviors frequently involve personal sacrifices, changes to ingrained habits, and navigating ambiguous or conflicting expectations within organizational systems (Moilanen & Alasoini, 2023).

This result aligns with prior research suggesting that positive sentiment toward an organization does not necessarily translate to prosocial or extra-role behaviors unless employees perceive a normative obligation or a formal expectation to act (Han et al., 2011; Kornilaki & Font, 2019). Moreover, the sustainability domain may involve moral disengagement mechanisms (Bandura, 1999), wherein employees emotionally attached to their employer may rationalize inaction on sustainability as being outside their role’s scope or trust that the organization will manage it collectively, thus reducing personal initiative.

Another relevant consideration is the roles of role clarity and operational cues in bridging affective sentiment with action. Employees with high levels of affective commitment may lack clear guidelines or opportunities to enact sustainability behaviors, leading to a sentiment–behavior gap commonly reported in pro-environmental behavior literature (Chao & Yu, 2024). This disconnect underscores the importance of pairing emotional identification with explicit behavioral expectations, role modeling by leaders, and structural incentives (Lin et al., 2022).

Therefore, while affective commitment fosters positive organizational sentiment, its impact on targeted sustainability behaviors appears to be conditional on the presence of normative cues and organizational standards that frame sustainability as a collective and individual duty rather than an optional, value-driven activity.

In addition to these motivational and contextual considerations, a deeper theoretical distinction based on the task and goal specificity of each commitment type offers further explanatory clarity.

One possible explanation for this divergence lies in the differing levels of task and goal specificity inherent in affective versus normative commitments. Affective commitment reflects an employee’s emotional attachment to the organization (Meyer & Allen, 1991) and tends to foster generalized loyalty and identification. However, this broad emotional bond may not consistently translate to engagement with specific initiatives, such as sustainability programs, particularly if those initiatives are peripheral to the employee’s core job role or organizational priorities. In contrast, normative commitment is rooted in a perceived moral obligation to act in support of organizational values and goals (Meyer & Parfyonova, 2010; Moilanen & Alasoini, 2023). Because sustainability initiatives explicitly invoke ethical and social responsibility dimensions, normative commitment provides a more direct motivational pathway to drive task-specific behaviors, like sustainability switching. This distinction aligns with prior findings in prosocial and organizational citizenship behavioral research, where value-congruent obligations have been shown to predict discretionary behaviors more reliably than generalized organizational loyalty (Chao & Yu, 2024; Lin et al., 2022). Thus, while affective commitment promotes an overall sense of belonging, normative commitment activates a sense of duty linked to the moral underpinnings of sustainability practices, offering a stronger explanatory basis for its significant behavioral effect in this context.

5.3. Reinterpreting the Negative Relationship Between Trust and Sustainability-Switching Behavior

The empirical finding that organizational trust negatively influences sustainability-switching behavior (SSB), while initially counterintuitive, provides a valuable opportunity to engage with emerging debates in organizational behavior and sustainability literature. Although this result was acknowledged in the analysis, it warrants deeper theoretical reflection to contextualize its implications.

Prior research has typically positioned trust as a positive relational asset within organizations, associated with enhanced collaboration, employee engagement, and discretionary behaviors (Bai et al., 2024; Lin et al., 2022). However, an emerging body of literature cautions that excessive or uncritical trust can foster organizational complacency, leading employees to delegate responsibility for certain actions, such as sustainability behaviors, to the organization itself (De Roeck & Farooq, 2018; Egeland & Stensaker, 2017). This phenomenon, sometimes described as the “dark side of trust” or the over-reliance mechanism, suggests that when employees perceive their organization as highly credible and ethically committed, they may feel less personally obligated to contribute proactively, assuming that sustainability efforts are adequately managed at higher organizational levels.

This interpretation is consistent with findings in related domains where institutional trust can paradoxically reduce individual engagement in collective issues, such as corporate social responsibility, ethical whistleblowing, or environmental advocacy (Brickson, 2007; Khan et al., 2020). In sustainability contexts, high organizational trust levels may inadvertently signal to employees that individual behavioral change is optional rather than integral to the organization’s sustainability goals.

Future research should explore these dynamics more explicitly, examining how trust interacts with factors like moral disengagement (Bandura, 1999), role clarity (Kornilaki & Font, 2019), and organizational citizenship expectations (Peterson, 2004). From a managerial perspective, organizations operating in high-trust environments should implement mechanisms that explicitly assign personal accountability for sustainability actions. Examples include incorporating sustainability objectives into individual performance appraisals, establishing role-specific sustainability KPIs, and providing structured feedback on sustainability-related behaviors. Clear communication from leadership, coupled with participatory decision-making opportunities, can help to sustain high-trust climates while ensuring individual engagement in collective sustainability goals. Qualitative studies and mixed-method designs could offer deeper insights into the cognitive rationalizations employees use in high-trust settings and how trust framing in sustainability messaging influences personal responsibility and action.

By recognizing that trust is not unconditionally beneficial and that it can produce unintended consequences when it discourages proactive individual engagement, this study contributes to a more nuanced understanding of organizational trust dynamics within sustainability transitions. It also emphasizes the need for leaders to balance trust-building efforts with clear role expectations, accountability structures, and participatory opportunities, ensuring that high organizational trust levels enhance, rather than diminish, individual sustainability behaviors.

However, it is important to interpret these findings with appropriate caution. The empirical model explains 28.4% of the variance in the sustainability-switching behavior, with organizational trust contributing a modest effect size (f² = 0.048). These results suggest that while the paradoxical role of trust warrants conceptual attention, its practical impact in this study is modest. Rather than proposing a broadly counterproductive role for trust, it is more accurate to frame this as a conditional or a contextual effect—potentially contingent upon factors such as accountability systems, leadership signaling, and feedback mechanisms. This perspective aligns with recent arguments by De Roeck and Farooq (2018) and Egeland and Stensaker (2017), who contend that the effects of trust on discretionary behaviors, like sustainability engagement, are likely to vary according to situational enablers and the organizational climate. Future research should further investigate these moderate conditions to clarify when and how high organizational trust levels diminish or enhance sustainability behaviors.

5.4. Re-Examining the Role and Measurement of the Inertia

While this study empirically confirms inertia as a significant negative predictor of sustainability-switching behavior (SSB), the findings regarding its hypothesized moderating effects (H6a–H7) were not supported. This result invites a deeper theoretical reflection on the underlying mechanisms by which inertia operates within organizational settings, as well as a reconsideration of its operationalization in this study.

The conceptual positioning of inertia as a “mooring” factor in the PPM model remains theoretically appropriate, as it captures the tendency of individuals to resist behavioral change due to habit, perceived effort, or psychological discomfort (Bravo & Ostos, 2021; Polites & Karahanna, 2012). However, the absence of significant moderation effects suggests that inertia may function more as an independent barrier exerting a direct influence on behavior rather than dynamically interacting with leadership commitment, trust, or employee commitment in shaping sustainability behaviors.

One plausible explanation lies in the possibility that inertia’s influence is rooted in deeper structural or institutional conditions that are not easily altered by individual perceptions of leadership or trust alone. The recent literature on organizational inertia (Faraj & Leonardi, 2022; Moradi et al., 2021) suggests that routinized practices, the absence of incentives, and weak feedback mechanisms create persistent behavioral patterns that are resistant to change, independent of normative or affective drivers. This structural dimension of the inertia may help to explain why its moderating role was not supported in the current analysis. To address behavioral inertia operationally, organizations could implement regular feedback loops that make sustainability-related behaviors and outcomes visible at the team and individual levels. Behavioral ‘nudges’, such as timely reminders, default green options in work processes, and sustainability challenges, may further disrupt habitual patterns. Additionally, sustainability role modeling by middle and senior managers can reinforce behavioral expectations, signaling the importance of proactive engagement with sustainability practices.

Additionally, it is important to acknowledge that the operationalization of the inertia in this study primarily relied on attitudinal indicators, assessing employees’ self-reported willingness to adjust habits and engage in sustainability actions. While this approach is consistent with that in prior research (Polites & Karahanna, 2012), it may insufficiently capture the observable behavioral manifestations of the inertia, such as repeated unsustainable work routines or the persistence of default behaviors despite organizational sustainability initiatives. This limitation likely attenuated the capacity to detect interaction effects with leadership, commitment, or trust.

To address this, future research should aim to expand the measurement of the inertia by incorporating both attitudinal and behavioral indicators, such as actual participation in sustainability programs, the frequency of environmentally unsustainable work practices, or resistance to procedural changes. Moreover, qualitative or longitudinal approaches could offer richer insights into how inertia is sustained within organizational systems and how it can be disrupted.

By recognizing the multidimensional nature of the inertia, both psychological and structural, this study underscores the importance of integrating broader institutional and operational variables into future sustainability behavioral models, offering a more complete understanding of the barriers to workplace behavioral change.

6. Research Conclusions

This study sets out to address three primary research objectives regarding the factors influencing employees’ sustainability-switching behaviors (SSBs) within organizational settings:

RO1: How does leadership commitment influence affective and normative employee commitments in the context of sustainability transitions?

The findings confirm that leadership commitment significantly enhances both affective and normative employee commitments. Leadership behavior that visibly prioritizes sustainability fosters stronger emotional attachment to the organization’s values and a heightened sense of moral obligation among employees to support sustainability initiatives.

RO2: What is the role of organizational trust in predicting employees’ sustainability-switching behaviors?

Contrary to expectations, organizational trust was found to negatively predict SSB. While trust is typically assumed to foster discretionary behaviors, in this case, high levels of trust appear to create a delegation effect, where employees reduce personal responsibility for sustainability actions, relying instead on the organization to manage sustainability outcomes.

RO3: How does behavioral inertia function as a barrier to employees’ sustainability behaviors, and does it moderate the influences of leadership commitment, employee commitment, and trust?

The empirical results indicate that behavioral inertia has a significant and strong negative effect on SSB, confirming its role as a direct barrier to sustainability-related behavioral change. However, inertia did not moderate the relationships among leadership commitment, employee commitment, trust, and SSB as hypothesized. This suggests that inertia operates independently, exerting a direct influence on behavior rather than interacting dynamically with other predictors.

These findings contribute to a more nuanced understanding of how leadership, relational trust, and behavioral inertia collectively shape employee engagement in organizational sustainability initiatives while also pointing to the complex and, at times, paradoxical effects of relational and contextual factors within workplace behavioral change processes.

6.1. Theoretical Positioning: Refining the Contribution of the Integrated TRA–PPM Framework

This paper positions the value of integrating the TRA with the PPM model not in the basic extension of contextual or organizational factors, a practice already adopted by models such as the Theory of Planned Behavior (TPB) (Ajzen, 1991), the Norm Activation Model (NAM) (Schwartz, 1977), and the Value–Belief–Norm (VBN) theory (Stern et al., 1999), but in demonstrating how this integration can bring complex and, at times, paradoxical relational dynamics within organizations. Specifically, this study illustrates how structurally modeling push, pull, and mooring mechanisms in a TRA-informed framework enables the identification of contradictory effects, such as the paradox of trust, while formally capturing behavioral inertia and commitment structures within organizational systems.

What distinguishes the framework proposed in this study is not the mere addition of contextual constraints, but the specific structural and functional roles assigned to these constraints through the PPM logic. Whereas models like NAM and VBN emphasize internalized moral norms, values, and perceived obligations as key drivers of prosocial and pro-environmental behaviors, the TRA–PPM integration advances this conversation by structurally modeling push, pull, and mooring mechanisms that capture not only moral drivers but also organizational relational dynamics (trust and leadership) and habitual inertia as contextually situated forces affecting behavioral transitions. This model advances the literature by, first, explicitly modeling inertia as a distinct mooring force unlike NAM and VBN, which typically treat barriers to prosocial behavior as situational or attitudinal moderators (e.g., awareness of consequences and perceived behavioral control). Our framework conceptualizes inertia as a standalone structural and psychological barrier exerting direct and potentially independent effects on the switching behavior. This aligns with recent organizational studies emphasizing the roles of routinization, feedback system absence, and institutional inertia in obstructing sustainability transitions (Faraj & Leonardi, 2022). Second, this model decouples affective and normative organizational commitments as differentiated push factors influencing sustainability behavior within formal work environments, a distinction underexplored in both TRA extensions and pro-environmental models, which often treat attitudes or norms monolithically. Our empirical finding that normative, but not affective, commitment predicts the sustainability behavior highlights the importance of organizational roles’ expectations and moral obligation frameworks over emotional attachment alone in driving behavioral change at work. Third, this model introduces the paradoxical role of organizational trust as a pull factor with potential negative externalities, a mechanism not explicitly theorized in NAM or VBN models. While these models generally assume that positive moral and normative pressures facilitate prosocial behavior, our findings demonstrate that high organizational trust levels can reduce individual responsibility for sustainability engagement, aligning with recent work on the “dark side of trust” and over-reliance effects (De Roeck & Farooq, 2018). Fourth, this model positions employees’ switching behaviors within a dynamic, interactional system, where leadership commitment, organizational trust, personal commitment, and inertia function interdependently, moving beyond the linear, intention–behavior pathways emphasized in TRA, NAM, and VBN toward a multifactorial model suitable for organizational sustainability contexts, where formal structures and informal norms interact.

We acknowledge that this model remains an early-stage, exploratory attempt to operationalize a more nuanced framework for workplace sustainability behavior. However, by foregrounding organizationally situated forces and explicitly modeling inertia as a mooring barrier within the PPM logic, it offers a differentiated perspective on employees’ behavioral change processes that extend beyond existing pro-environmental models typically focused on individual moral activation and personal norms.

To further clarify the theoretical positioning of this integrative framework, it is useful to consider how the TRA–PPM model compares with other widely applied pro-environmental behavioral models in terms of their explanatory scopes and treatments of organizational and contextual factors.

In summary, the integration of the Theory of Reasoned Action (TRA) with the Push–Pull–Mooring (PPM) model offers several explanatory gains not realized by established frameworks, such as the Norm Activation Model (NAM), the Theory of Planned Behavior (TPB), or the Value–Belief–Norm (VBN) theory. While those models have been valuable in identifying individual-level determinants of pro-environmental behavior, they typically conceptualize barriers to action as either moderators (e.g., perceived control in TPB) or situational constraints (as in NAM and VBN) and place less emphasis on organizational and relational dynamics. In contrast, the TRA–PPM framework explicitly models behavioral inertia as a direct, independent mooring factor, capturing both its psychological and institutional dimensions within organizations. Additionally, it differentiates affective and normative employee commitments as distinct push factors, offering a more nuanced understanding of workplace motivations, as opposed to the aggregated moral norms in NAM or generalized personal values in VBN. Finally, by integrating organizational trust as a relational pull factor with dual effects, the model acknowledges both its capacity to encourage engagement and its potential to foster over-reliance and disengagement, an under-theorized dynamic in mainstream pro-environmental behavioral models. Together, these contributions position the TRA–PPM framework as a relational contextual model capable of explaining both individual and structural–organizational influences on the sustainability-switching behavior, offering enhanced explanatory power in settings where pro-environmental intention alone does not guarantee behavioral change.

To clarify these distinctions,

Table 7. Comparative overview of pro-environmental behavioral models and the explanatory gains of the TRA–PPM integration.

Framework	Key Predictors	Treatment of Barriers	Relational Organizational Context	Distinctive Explanatory Gains of the TRA–PPM Integration
TPB (1)	Attitude, subjective norm, perceived behavioral control	Moderators (perceived control), limited treatment of structural constraints	Limited	Introduces behavioral inertia as an independent mooring factor not just a perception of control
NAM (2)	Personal norm, awareness of consequences, ascription of responsibility	Situational constraints acknowledged but often secondary	Weakly incorporated	Distinguishes organizational trust as a pull factor and its dual/paradoxical effects
VBN (3)	Values, ecological beliefs, personal norms	Contextual factors acknowledged indirectly via norms and values	Not explicitly modeled	Differentiates affective and normative organizational commitments as separate push factors
TRA–PPM (4)	Attitude, subjective norm (from TRA); push, pull, mooring factors (from PPM)	Explicitly models behavioral inertia as a direct, independent barrier	Explicitly integrates organizational trust, leadership behavior, and employee commitment dimensions	Provides a relational–contextual framework capable of explaining organizational- and individual-level dynamics in sustainability-switching behavior

⁽¹⁾ TPB: Theory of Planned Behavior; ⁽²⁾ NAM: Norm Activation Model; ⁽³⁾ VBN: Value–Belief–Norm Theory; ⁽⁴⁾ TRA-PPM: Push, Theory of Reasoned Action—Push, Pull, and Mooring. Source: Authors´ own.

presents a comparative overview of the explanatory coverages of the established models and the explanatory gains realized through the integrated TRA–PPM framework.

This theoretical positioning reinforces the value of adopting a relational–contextual lens for understanding employee sustainability-switching behaviors, providing a foundation for the empirical examination of the proposed model and its hypotheses in the following sections.

6.2. Practical Implications

This study offers several important, actionable implications for managers, sustainability officers, and policymakers tasked with promoting pro-environmental behaviors within organizational settings:

Calibrating Organizational Trust Dynamics: While organizational trust generally facilitates collaboration, this study highlights its potential paradoxical effects when excessive or unstructured trust fosters complacency or diffuses personal accountability for sustainability behaviors. Managers should implement mechanisms that link trust with clear individual sustainability responsibilities, such as transparent reporting systems, public commitment declarations, and regular feedback on sustainability performance.

Reducing Behavioral Inertia Through Process Innovation: Given the strong negative effect of the inertia on the sustainability-switching behavior, organizations should proactively identify routine processes, operational habits, or cultural norms that discourage behavioral change. Introducing small, incremental “behavioral nudges”, feedback loops, or habit-breaking interventions can help to reduce employee resistance to new sustainability practices.

Strengthening Role Clarity and Normative Expectations: The divergence in the behavioral effects of affective versus normative commitments highlights the importance of not relying solely on positive employee sentiment to drive sustainability outcomes. Sustainability initiatives should be formally embedded within role descriptions, performance evaluation criteria, and structured expectations communicated through leadership modeling and explicit norms. Normative pressure works the best when paired with consistent organizational signals and behavioral cues.

Designing Multilevel Interventions: Because the sustainability-switching behavior is influenced by a combination of internal motivations (commitments), relational perceptions (trust), and contextual constraints (inertia), effective interventions should address these multiple levels concurrently. This may involve leadership-training programs, trust recalibration workshops, and operational audits to remove institutionalized barriers to behavioral change.

Together, these recommendations ensure that sustainability programs move beyond awareness raising to address the relational and structural factors that either enable or constrain behavioral change within organizations.

6.3. Study Limitations and Directions for Future Research

Despite offering valuable insights into the determinants of employees’ sustainability-switching behaviors (SSBs), this study is subject to several limitations that should be acknowledged.

First, the use of a non-probabilistic convenience sampling strategy via LinkedIn groups limits the generalizability of the findings. Although this approach enabled access to a geographically and sectorally diverse group of professionals involved in sustainability initiatives, it risks sample bias by attracting individuals with a pre-existing interest in sustainability. Future research should consider employing stratified or purposive sampling designs to improve representativeness and allow comparative analysis across industries, organizational sizes, and cultural contexts.

Second, the operationalization of the behavioral inertia leaned heavily on attitudinal indicators, potentially underestimating the structural, procedural, and behavioral dimensions of the inertia that persist in organizations. Future studies should incorporate behavioral metrics (e.g., participation rates in sustainability programs and consistency in sustainable practices) and consider longitudinal or qualitative designs to capture how inertia manifests and evolves over time within workplace routines.

Third, while this study introduces the paradoxical effect of organizational trust as a potential inhibitor of individual sustainability behavior, the underlying psychological mechanisms were not empirically explored. Future research should investigate the mediating roles of moral disengagement, role clarity, or responsibility diffusion in high-trust environments to better understand how trust can both enable and constrain pro-sustainability behaviors.

Fourth, several constructs in the measurement model yielded AVE and CR values near the minimal thresholds, and item reduction decisions were made post hoc based on empirical criteria. Although these decisions preserved the theoretical integrity, they point to the need for further scale refinement and validation in larger, diverse samples to improve the construct’s reliability and measurement precision.

Fifth, this study’s framework focused on TRA and PPM integration while largely omitting potentially relevant constructs from alternative models, such as the NAM or VBN. Future research should explore multi-theoretical frameworks that combine personal moral norms, environmental efficacy beliefs, and contextual organizational factors to offer a more holistic explanation of sustainability behavior within organizations.

In summary, while this study advances knowledge on employee-driven sustainability transitions, future research should pursue methodologically diversified, multilevel, and cross-cultural studies to validate, extend, and deepen the understanding of individual and organizational drivers of workplace sustainability behavior.