The objective of this research is to assess the association between proactive personality and project success by examining the mediating role of affective commitment, the moderating impact of transformational leadership between proactive personality and affective commitment and the moderating role of project complexity between affective commitment and project success.
Data analysis and hypothesis testing were conducted using smartPLS 4, a partial least squares (PLS)-structural equation modeling tool. The data were collected through a questionnaire using convenience sampling from 288 employees of the informational technological sectors of Pakistan.
The findings of this study revealed that proactive personality has a positive and significant impact on project success directly and indirectly through the mediating mechanism of affective commitment. The moderating influence of transformational leadership between proactive personality and affective commitment is examined in such a way that high transformational leadership behavior will strengthen the relationship, and the moderating role of project complexity between affective commitment and project success will strengthen the relationship.
In this study, three unanswered research questions from the literature have been addressed. The first research question is how proactive personality can enhance project success? This research addressed the fact that proactive personality behavior can increase a project’s success. The second research question is: what are the suggested mechanisms for a proactive personality to increase project success? The current study proves that a proactive personality increases project success through a mediating mechanism of affective commitment. Finally, the third research question that is addressed by this study is: does the relationship between affective commitment and proactive personality get moderated by transformational leadership style? And does project complexity moderate the relationship between affective commitment and project success? This study reveals that both moderators strengthen their respective relationships.
1. Introduction
The survival of an organization depends on the proactive measures it takes to address disruptive and global technological challenges. The only way to survive in the current competitive market is to react rapidly to the environmental changes (Nesterkin, 2013; Paulsen et al., 2013). According to Fuller and Marler (2009), proactive employees are not only inclined to adapt but also actively shape their work environment to fit the dynamic demands of competitive contexts. They tend to exhibit behaviors that go beyond job requirements, such as taking initiative, engaging in problem-solving and demonstrating agility in facing unanticipated challenges. While past academic research concentrated on proactive personality impact in individual job performance (Crant, 2000), there has been limited research on how proactive personality influences project success, particularly through the mediating role of affective commitment and the moderating roles of leadership and project complexity. Proactive behavior as a social behavior impacts project and organizational effectiveness (Bindl and Parker, 2011). In a competitive market, it can be challenging for organizations to deal with complicated changes (Fraj et al., 2015). Therefore, researchers are interested in identifying proactive behavior because proactive behavior allows employees to take initiative, take advantage of opportunities and impact the environment (Yang et al., 2019) and this proactive behavior is always positively correlated with work outcomes like project performance and success (Chan, 2006). Since the proactive personality was introduced, researchers have been provoked to look into how people behave in various work environments (Roopak et al., 2018). According to Rodrigues and Rebelo (2019) proactive people are more likely to take initiative and have a social impact on project performance. Employees must be efficient and effective due to the short-term and novel nature of the projects, which requires creativity and innovation to ensure performance, so employees' proactive personality can positively enhance the project’s success (Chan, 2006), as proactivity is an essential trait that enables employees to foresee and mitigate potential disruptions in their work environment (Bindl and Parker, 2011). Numerous researchers have found that project success is based on many factors (Rehan et al., 2024), including leadership styles (Gehring, 2007), internal and external environments, personality traits and employee behavior (Belassi and Tukel, 1996). Hence, this study will assess the effect of employees' proactive personalities on project success. The following research questions have been addressed by this study: How does proactive personality influence project success? Does affective commitment mediate this relationship? Does transformational leadership and project complexity moderate the effects of proactive personality and affective commitment on project success? According to Zhou and George (2001), a proactive personality is an important dispositional antecedent that fosters creativity or “the development of new and potentially valuable ideas” in the workplace. According to Sagha et al. (2017), every individual is unique and possesses unique personality qualities that significantly impact an organization’s effectiveness. Thus, the impact of personal resources on organizational performance demonstrates the significance of personality in human composition according to Xanthopoulou et al. (2007).
Organizations operate in situations that are complex, ambiguous and change quickly. Organizations must foster proactive behavior in their workforce to boost competitiveness in order to manage such a complex and unpredictable environment (Fuller and Marler, 2009). The concept of “the relatively stable tendency to affect environmental change” describes the proactive personality (Bateman and Crant, 1993, p. 103). Employees with proactive personalities often adapt their circumstances to meet their needs. Proactive people think critically by investigating their surroundings, thus they are not restricted to reacting to a particular circumstance. Future success would be attainable for these proactive employees (Bateman and Crant, 1993; Crant, 2000; Thomas et al., 2010). Accordingly, researchers are interested in identifying proactive behavior in employees because it allows them to take advantage of opportunities and initiatives and affect the environment (Yang et al., 2019). Additionally, proactive behavior is always positively correlated with work outcomes, such as project performance (Chan, 2006). Employee efficiency and effectiveness are required due to the short-term and innovative nature of the projects, which necessitates originality and innovativeness to ensure performance. The proactive attitude of the employees can also contribute to the success of the project (Chan, 2006). Several studies demonstrated that employees perform well when they are committed, especially in project-based organizations, while completing the projects successfully (Dwivedula et al., 2016). Moreover, employee commitment enables organizations to succeed; thus the achievement of employee commitment is necessary during project completion and management (Bakker et al., 2008). Furthermore, according to researchers, employee commitment leads to employee loyalty and this loyalty leads to better performance and project success (Dwivedula et al., 2016). Bass (1990) describes transformational leadership as a style that motivates employees to exceed expectations, providing them with autonomy, a sense of purpose and the support necessary to excel. Affective commitment or the emotional attachment an employee feels toward their organization, is particularly important because it increases motivation and engagement, which are key drivers of successful project outcomes (Meyer and Allen, 1991). Employees who are emotionally committed are more likely to go above and beyond to ensure the success of a project, this commitment is enhanced through transformational leadership and is particularly effective in project contexts. To the best of our knowledge, the evaluation of transformational leadership’s moderation on the proactive personality-affective commitment relationship has not been tested. According to the research, transformational leadership has a significant effect on individuals who are highly determined and committed and it also fosters a positive interaction with proactive personalities (Den Hartog and Belschak, 2012) and particularly during uncertain times, followers of transformative leaders exhibit high levels of commitment and motivation (House and Aditya, 1997).
Furthermore, according to Camps and Rodríguez (2011), transformational leadership raises employees' self-perceived employability, commitment and performance. Collaborating with transformational leaders enhances employees' self-perception of their employability and strengthens their commitment to their employers who have placed their trust and confidence in them. Employee performance rises as a result of this increased commitment (Camps and Rodríguez, 2011). In addition, it is also described by researchers that transformational leadership can increase employee proactive behavior (Strauss et al., 2009) by enhancing employees' affective commitment to the organization and profession (Zhang and Inness, 2019; Zhang et al., 2019). The current study proposes that proactive behavior by employees and transformational leadership support can enhance the impact of a proactive personality on affective commitment, which in turn improves project success, furthermore, empirical studies demonstrate that transformational leadership enhances affective commitment and job satisfaction, which in turn mediates project success (Fareed et al., 2022; Ayaz and Awaıs, 2023). The literature shows a gap between proactive personality and project performance through the mediating and moderating roles of affective commitment and transformational leadership, respectively, thus this study examined how organizations can boost project success rates, which is definitely achievable through affective employee commitment and transformational leadership. (see Figure 1). The objective of this study is, therefore, firstly, to investigate the connection between project success and a proactive personality. Secondly, the mediating role of employees' affective commitment between proactive personality and project success. Finally, this research demonstrates how transformational leadership can function as a moderator between proactive personality and project success, as well as how project complexity can influence the relationship between affective commitment and project success. The hypothesis of this study build upon attribution theory and person organization fit theory, Figure 1 presents the hypothesized framework. Drawing on attribution theory (Heider, 1958), this study posits that employees attribute organizational outcomes to both internal factors (e.g. their own proactive personality) and external conditions (e.g. leadership style). Additionally, the person-organization fit theory supports the assumption that alignment between individual traits and organizational climate enhances affective commitment and ultimately, project success.
The diagram has the heading “Hypothesized Model” written at the top left. The diagram contains three labeled rectangular boxes arranged horizontally. From left to right, the first box is labeled “Proactive Personality,” the second box is labeled “Affective Commitment,” and the third box is labeled “Project Success.” At the top center, between the first and second boxes, there is a box labeled “Transformational Leadership.” At the top center, between the second and third boxes, there is a box labeled “Project Complexity.” Arrows connect the boxes as follows: A rightward arrow labeled “H 2” points from “Proactive Personality” to “Affective Commitment.” A rightward arrow labeled “H 3” points from “Affective Commitment” to “Project Success.” An arrow with two 90-degree bends, labeled “H 1,” points from “Proactive Personality” to “Project Success.” A line labeled “H 4” is drawn horizontally below “Affective Commitment.” An arrow labeled “H 5” points from “Transformational Leadership” to the arrow connecting “Proactive Personality” and “Affective Commitment.” An arrow labeled “H 6” points from “Project Complexity” to the arrow connecting “Affective Commitment” and “Project Success.”Proposed hypothesized model. Source: Created by authors
The diagram has the heading “Hypothesized Model” written at the top left. The diagram contains three labeled rectangular boxes arranged horizontally. From left to right, the first box is labeled “Proactive Personality,” the second box is labeled “Affective Commitment,” and the third box is labeled “Project Success.” At the top center, between the first and second boxes, there is a box labeled “Transformational Leadership.” At the top center, between the second and third boxes, there is a box labeled “Project Complexity.” Arrows connect the boxes as follows: A rightward arrow labeled “H 2” points from “Proactive Personality” to “Affective Commitment.” A rightward arrow labeled “H 3” points from “Affective Commitment” to “Project Success.” An arrow with two 90-degree bends, labeled “H 1,” points from “Proactive Personality” to “Project Success.” A line labeled “H 4” is drawn horizontally below “Affective Commitment.” An arrow labeled “H 5” points from “Transformational Leadership” to the arrow connecting “Proactive Personality” and “Affective Commitment.” An arrow labeled “H 6” points from “Project Complexity” to the arrow connecting “Affective Commitment” and “Project Success.”Proposed hypothesized model. Source: Created by authors
2. Theoretical background and hypothesis development
2.1 Attribution theory
According to Heider’s (1958) attribution theory offers a foundation to understand how proactive personalities attribute their successes and failures, which ultimately affects their level of engagement and commitment to projects. They proposed that how people attribute events, situations and other individuals to their proximity changes the whole perspective (Heider’s, 1958). Scholars have concentrated on the networking cycle, employee attitudes and actions at work and psychological health. Attribution theory supports this study. Attribution theory offers a framework for understanding proactive individuals’ motivation, especially in dynamic project-based environments where their actions significantly impact outcomes. The researchers (Zhang et al., 2022) conducted a meta-analysis revealing that proactive personality positively correlates with success factors, including behavior and task performance. These people, who consider themselves proactive, act to shape the environment in ways that satisfy them in their personal and professional lives and may result in favorable consequences. This tendency stems from their internal attributions, which reinforce a sense of control over external circumstances. Consequently, their attribution style serves as a motivational factor that propels them to take charge in ambiguous situations. Proactive individuals are likely to attribute their successes to stable, internal factors, which in turn fosters resilience in the face of future project challenges. When proactive employees perceive their successful outcomes as a result of stable traits, they are more likely to persist in high-effort activities, as they believe future success is within their control (Bateman and Crant, 1993). also hint that proactive personalities put more effort into delivering exceptional performance. Similarly, the findings of (Ma et al., 2024) underscore the significance of proactive personality in driving career development outcomes.
2.2 Person-organization fit theory
The person-organization (P-O) fit theory supports this study. P-O fit is central to aligning individual motivations with organizational objectives, which is crucial for achieving successful outcomes in dynamic project environments. Kristofs (1996) integrative review defines P-O fit as the compatibility between individuals and organizations, emphasizing that when personal and organizational values align, employees are more likely to demonstrate commitment, engagement and job satisfaction. This alignment is critical for proactive individuals because they seek environments that encourage initiative and innovation. Unlike employees who may be passive or reactive, proactive individuals actively seek alignment with organizational values and goals that resonate with their own aspirations for impact and creativity furthermore, new studies suggests proactive individuals experience stronger person–environment fit, leading to enhanced job satisfaction and commitment, supporting our application of P–O fit theory (Soares et al., 2024). Schneider (2001) developed a model based on this theory and claimed that people are drawn to jobs that are similar to or in line with their personalities or traits; this is known as person-organization fit. A meta-analysis by (Kristof, 1996), based on the person-organization fit theory, revealed a substantial and high correlation between person-organization fit and employee commitment to their organization and profession. Proactive employees often embody complementary fit, as they bring new ideas, problem-solving abilities and adaptability, which enhance the organization’s capacity to handle complex projects (Dvir et al., 2006). that in concern to PM, it is possible to find a controlled study that aims to understand the personality of managers and employees and how it affects a project’s success. This study attempted to link the experiences of management personnel with their psychosomatic acts. He focused on this area by using the person-organization fit theory to align the manager’s and employees' personality traits with the project’s success. They think project employees are more attracted to the work according to their personalities. The explanation above demonstrates that the relationship between personality, employee commitment and project performance is supported by the person-organization fit theory. So, suppose that if the work is in line with the personalities of the managers or employees, in that scenario, individuals display a stronger sense of commitment to their work and organization, which improves organizational results and facilitates project completion.
2.3 Proactive personality and project success
The idea of a proactive personality has gained popularity in recent years. According to (Jiang, 2017), a proactive mentality is a relatively significant tendency that gives people the confidence to build agility to impact the environment. All proactive personalities take the initiative and maintain an openness to new ideas and inventiveness, people with proactive personalities are inspired to take on extra obligations and are able to go above and beyond their job duties, their foresight allows them to plan ahead, reducing the likelihood of project delays or conflicts (Xiong and King, 2018). Proactive personality, as defined by (Crant, 2000), encompasses a range of traits, including adaptability, foresight, initiative, and resilience that align with the demands of project-based work. Proactive employees are better equipped to respond to shifting project demands and deadlines, enabling them to support the team’s goals even in times of uncertainty (Parker and Collins, 2010). Fuller and Marler (2009) argue that adaptability is a critical factor in proactive individuals’ success, as it allows them to contribute effectively even when projects encounter unforeseen challenges. This adaptability aligns with the goals of project success by ensuring that proactive employees can continuously add value throughout the project lifecycle and increases project success (Li et al., 2020).
According to Zhang et al. (2012), task performance at work has benefited from employees with proactive personalities, people who show proactive personality traits achieve better results since they are content with both work and personal aspects. Fuller and Marler (2009) discovered that proactive personality demonstrates positive effects on job performance in various workplace environments. Similarly, Parker and Collins (2010) highlighted that proactive behaviors such as anticipating challenges and taking initiative are critical for achieving positive outcomes in complex work environments.
Proactive behavior is said to be enabled by a proactive personality. Individuals with proactive behavior encourage change and consciously create resources to choose better possibilities in the future and the cycle continues (Yildiz et al., 2017). Everyone having this quality can contribute to an organization’s improvement. As a result, we can conclude that being proactive affects a person’s personal and professional life because proactive people have a clear sense of what they want to accomplish, know how to get there and are constantly looking for new methods to do so.
Projects include a new component that requires innovation to handle unpredictability (Khan et al., 2024). Projects are associated with high risk and the project’s outcome can determine whether or not the end aim is realized (Yip et al., 2006). According to (Kim et al., 2010), a proactive personality increases employee innovation at work. A project can be distinguished by its creativity in addition to its reasoning, accomplishment, content, or outcome (Valverde et al., 2020). Proactivity has been identified by (Farooq et al., 2020) as the element for motivation, together with control at the individual and group level (Parker et al., 2010). Each aspect of motivation provides a foundation for accomplishing that goal; it can be utilized as an individual’s desire; Project life begins with intra-motivation, which serves as the starting point (Valverde et al., 2020). According to researchers, a proactive personality has a beneficial effect on employee performance, it enables achieving desired results (Greguras and Diefendorff, 2010; Yang and Chau, 2016).
According to a recent study by Zhang et al. (2021), proactive people promote an environment that demands achieving the desired performance. A proactive individual can handle ambiguity, work toward goal completion and exhibit creative behavior at work, which may improve project success and performance (Li et al., 2020). According to (Hsiao and Wang, 2020), proactive personalities perform better than other personalities by taking different paths to success (Jaffery and Abid, 2020). Researchers have become interested in the idea since proactive people impact the environment (Tisu et al., 2020). According to literature (Crant, 2000; Zhou and George, 2001), a high level of personal performance results from having a proactive personality. So, based on the above discussion we propose:
A proactive personality has a positive association with project success
2.4 Proactive personality and affective commitment
People vary in their ability to respond in ways that affect their surroundings. To account for these variations among people, a proactive personality has been proposed as an attribute of personality (Bateman and Crant, 1993; Crant, 1995, 2000). According to Bateman and Crant (1993), the individual characteristic of proactive personality describes someone who strives to maintain full control of personal initiative to create beneficial results while minimizing external limitations in their environment.
Proactive personality has gained prominence since it emerged as a reliable concepts and a predictor of important results, such as organizational performance, in the early 1990s (Crant, 1995) and the ability to handle professional constraints (Parker and Sprigg, 1999).
We anticipate that proactive people will create occurrences consistent with pursuing their goals due to their intrinsic talents to shape work settings in their favor, due to their problem-solving abilities (Weiss and Cropanzano, 1996). It has been demonstrated that proactive people actively monitor their surroundings, stay attentive and take actions that will result in the outcomes they want. Proactive people constantly search for new knowledge and techniques to help them perform better (Bateman and Crant, 1993; Crant, 2000). These characteristics point to proactive people’s capacities to shape their working circumstances and environment as they see appropriate.
According to Yousaf et al. (2013), the development of positive work environments as a result of people’s proactive efforts appears likely to arouse positive emotional states, which will raise affective commitment. Researchers suggest that employees with proactive personalities are better able to regulate their surroundings and influence them in ways that they find desirable and this develops employees attachment and feeling of being at home (Yousaf et al., 2013). Individuals with proactive personality traits tend to improve their affective commitment (Ullah et al., 2020; Sridadi et al., 2024) as proactive individuals engage in work tasks with enthusiasm, Proactive employees tend to find greater meaning in their work by taking initiative and shaping their work environment to suit their strengths (Weiss and Cropanzano, 1996). This sense of ownership and control over their tasks enhances their emotional attachment to the organization (Yousaf et al., 2013). The Self- Determination theory SDT indicates that people with proactive attitudes exhibit strong intrinsic motivation, as they actively seek opportunities to realize their potential. Self-determination theory posits that autonomy is a fundamental psychological need; when fulfilled, it leads to greater job satisfaction and emotional attachment. Proactive individuals naturally seek environments that grant them autonomy, as it allows them to take initiative and pursue projects aligned with their interests (Deci and Ryan, 2000). This empowerment increases the emotional attachment that proactive employees feel toward the organization, thus strengthening their affective commitment (Bass, 1990). Researchers said that this attachment consequently affects their satisfaction with their work and ultimately translates into higher affective commitment (Bowling et al., 2005), so based on the above discussion we propose:
Proactive personality is positively related to affective commitment
2.5 Affective commitment and project success
According to McShane and Glinow (2008), employees who feel strongly committed to the organization they value their membership since it allows them to connect with that organization. Therefore, the best measure of an employee’s willingness to support a company is affective commitment (Meyer and Herscovitch, 2001). Researchers Steyrer et al., (2008) have discovered a connection between this commitment and organizational performance.
Researchers claim that affective commitment shows a person’s desire to support the goal of their commitment (Meyer and Herscovitch, 2001). Affective commitment encourages active involvement from participants in transformational change; this commitment leads to increased effort, greater persistence in the face of challenges and a willingness to collaborate with team members (Herold et al., 2007). Emotionally committed employees are more likely to engage in proactive problem-solving, contribute innovative ideas and support their colleagues, all of which are critical for achieving project success (Gendron et al., 2006). Affective commitment drives employees to expend additional effort and resources on projects, ensuring higher-quality outcomes and a stronger alignment with project goals (Meyer and Allen, 1991). Project work often involves encountering obstacles, adjusting to shifting requirements and managing tight deadlines. Employees who are effectively committed are more likely to remain resilient in the face of these challenges, as their emotional attachment to the organization drives them to persevere rather than disengage (Pierce et al., 2001). More recent research supports previous findings, according to (Andersen et al., 2006; Ameer et al., 2021; Waseem et al., 2024), who also claimed that “commitment to the project which subscribes to the affective commitment of employees ensures project success.” Moreover, according to researchers, employee commitment leads to employee loyalty and this loyalty leads to better performance and project success (Dwivedula et al., 2016). Meyer and Allen (1991) found that affective commitment enhances work performance, while Bakker et al. (2008) highlighted that employees who are emotionally engaged with their work are more likely to contribute to successful outcomes in project-based environments. Based on the above discussion, we thus propose the following hypothesis:
Affective commitment of the followers has a positive impact on project success
2.6 The mediating role of affective commitment between proactive personality and project success
Workers who demonstrate strong affective commitment toward their organization show appreciation toward membership since they describe themselves through this institution (McShane and Glinow, 2008). Affective commitment provides the optimal method for evaluating employee support for organizations (Meyer and Herscovitch, 2001), researchers installed a connection between this commitment and project performance in organizations (Steyrer et al., 2008). This commitment can be displayed toward different organizational levels and goals. Moreover, Nyhan (1999) recognized affective commitment as a component of organizational performance and employee adoption as an organizational aim and value, referred to as a success project. It is also stated by (Ghafoor et al., 2016) that affective commitment leads to the success of a project.
Researchers suggested that proactive personality is a personality feature that explains individual differences (Bateman and Crant, 1993; Crant, 1995, 2000). According to the researchers, Project performance demonstrates a positive correlation with proactive personality (Yang et al., 2020). According to a recent study by Zhang et al. (2021), proactive people promote an environment demanding to achieve the desired performance. A proactive individual can handle ambiguity, work toward goal completion and exhibit creative behavior at work, which may improve project success and performance (Li et al., 2020).
According to researchers, employees with a proactive mentality can alter their environment in positive ways and feel more in control of their circumstances, as a result, they feel emotionally attached and at home (Yousaf et al., 2013). Researchers said that this attachment to proactive personality consequently affects their satisfaction with their work (Bowling et al., 2005) and ultimately translates into higher affective commitment and higher affective commitment leads towards project success as researchers state that the success of the project is increased if the employees show more commitment towards their profession and work (Ghafoor et al., 2016).
Proactive individuals are known to generate and manage resources effectively, especially when they perceive their work as meaningful. The Job Demands-Resources (JD-R) Model argues that such resource accumulation, motivated by affective commitment, helps mitigate job demands and enhances job engagement, especially in challenging environments like project-based work (Bakker and Demerouti, 2007). Proactive individuals not only bring their resources into the project context but also rely on affective commitment to sustain these resources, which is vital for long-term engagement and success (Bakker and Demerouti, 2007). Proactive individuals who feel emotionally committed to a project perceive it as their own, leading them to take greater responsibility and exhibit resilience in the face of project challenges (Pierce et al., 2001), proactive individuals tend to take initiative, seek out meaningful work and align their personal goals with organizational objectives. This proactive behavior leads to a stronger emotional attachment to their work (affective commitment), which motivates them to invest more effort in ensuring the success of the project. So, we are proposing the hypothesis:
Affective commitment mediates the relationship between proactive personality and project success.
2.7 Moderating the role of project complexity between affective commitment and project success
According to Ekstedt et al. (2003), dynamic situations frequently lead to the formation of temporary organizations, organizations may create projects when they realize that the permanent organization’s structure will not allow them to achieve their goals. As a result, when we evaluate temporary organizations, we must take the context into account (Gundersen et al., 2012). The distinctiveness of a project frequently necessitates the introduction of Novel tasks that are notably different from regular ones performed by an organization (Brockhoff, 2006). Each member also possesses the specialized skills necessary to complete the project responsibilities. Former relationships between the participants are frequently absent because these experts come from various organizational units (Sydow et al., 2004). The novelty of the challenge, as well as the diversity of the participants, adds to the complexity of the tasks. To compensate for the lack of regularities and the mission’s overall complexity, there is neither a well-established hierarchy nor a long-standing feeling of coherence (Ratcheva, 2009). The participants may feel a sense of risk and uncertainty when all of these elements are taken into account (Tatikonda and Rosenthal, 2000). Because temporary organizations frequently generate disruptions; as a result, these companies are more likely to perceive change and uncertainty (Sydow et al., 2004). Thus, we propose that the complexity of a project and uncertainty feelings significantly influence the effectiveness of followers and employees in these projects. Researchers said that employee impact on commitment grows stronger when projects become more complex, according to (Liu, 1999; Locke and Latham, 1990). As the difficulty of the project affects a person’s expectations of their performance capacity, the person becomes more committed to their work and projects and will change their behavior for the project to be successful (Tyssen et al., 2013). Project complexity refers to the aggregation of multiple dimensions, including planning challenges, resource constraints, cost management, technical and technological requirements and social issues within the project itself (Nassar and Hegab, 2008). While complex environments, on the other hand, describe the external dynamic conditions that projects operate within, such as market volatility, technological innovation and organizational restructuring (Ekstedt et al., 2003; Sydow et al., 2004). Project complexity influences internal project dynamics, while a complex environment introduces external uncertainties that projects must navigate. Social cognitive theory suggests that individuals are influenced by their environment and when projects are highly complex, employees with affective commitment are more likely to believe in their ability to manage the complexities and remain focused on project success (Bandura, 1986). According to Evans (2008), complex projects trigger more reflective processing, requiring employees to think critically and make deliberate decisions. Affective commitment aids in this reflective processing by providing the motivation necessary to stay engaged with the project’s complexities (Hobfoll, 1989). According to the conservation of resources COR theory, people work hard to acquire, hold onto and protect their precious resources, which include psychological resources such as commitment and resilience. When project complexity is high, affectively committed employees may draw on their internal resources to withstand the increased demands, thereby fostering project success. This alignment explains that project complexity can magnify the effects of affective commitment, as committed employees are more capable of managing and even thriving in complex project environments by relying on their psychological resources (Hobfoll, 1989). In complex projects, employees must deal with greater uncertainty, ambiguity and interdependencies. These challenges demand higher levels of engagement, emotional resilience and collaborative problem-solving, making affective commitment a key driver of project success in such environments (Maylor et al., 2013). High levels of commitment are predicted to provide higher achievements when faced with challenging goals (Liu, 1999). Thus, we proposed:
The project complexity increases the positive impact of commitment on project success
2.8 Moderating role of transformational leadership between proactive personality and affective commitment
Studies have recently given more attention to transformational leadership Ribeiro et al. (2018) and over the past two decades, transformational leadership has emerged as the most significant leadership theory (Judge and Piccolo, 2004; Avolio et al., 2009; Sosik and Jung, 2010). Goleman (1995) asserts that today’s firms require leaders who can motivate their employees to attain their objectives. Transformational leadership represents a complete change as a whole new standard of leadership because it focuses on fulfilling the requirements and wants of individuals (Medley and Larochelle, 1995). Transformational leadership is a unique leadership style that resonates particularly well with proactive employees, who are naturally inclined toward initiative and self-driven change (Den Hartog and Belschak, 2012). Transformational leaders promote autonomy, competence and relatedness through their emphasis on empowerment and recognition. Proactive employees, who naturally seek autonomy and growth, are more likely to experience heightened affective commitment when they perceive transformational leaders as facilitating these psychological needs (Deci and Ryan, 2000).
Previous research has demonstrated that transformational leadership significantly influences employees' personal behavior, work satisfaction and behavior innovation (Nielsen et al., 2008). In addition to providing inspiration and motivation, transformational leaders offer practical support, such as setting clear goals, providing feedback and allocating resources (Nielsen et al., 2008). These leadership behaviors help proactive employees focus their energy and maximize their impact, which in turn strengthens their emotional commitment to the organization (Judge and Piccolo, 2004). According to empirical evidence, transformational leadership significantly affects individuals with high levels of self-determination and commitment at work and strengthens the relationship between proactive personality and transformational leadership (Den Hartog and Belschak, 2012). Moreover, transformational leadership possesses superior potential to influence others as compared to transactional leadership. According to Bass and Avolio (1996), transformational leadership, for example, has been linked to the highest levels of motivation and job satisfaction as well as the lowest levels of burnout inside the organization. Additionally, the research shows that transformative leadership enhanced commitment and motivation from followers especially when facing uncertain situations (House and Aditya, 1997). Transformational leadership is a unique leadership style that resonates particularly well with proactive employees, who are naturally inclined toward initiative and self-driven change, transformational leaders cultivate an environment of trust, support and mutual respect (Judge and Piccolo, 2004). Proactive employees, who thrive in environments where they can influence their surroundings, are likely to feel a stronger sense of affective commitment when they perceive transformational leaders as invested in their growth and well-being (Avolio et al., 2004). The study of (McCormick et al., 2019) evidenced that we can improve proactive behavior through an encouraging, inspiring and supportive leadership style. Furthermore, researchers suggest that employees with a proactive personality can manipulate their environment in desirable ways and feel better control over their environments. This leads to feelings of emotional attachment and being at home (Yousaf et al., 2013). Researchers said that this attachment consequently affects their satisfaction with their work (Bowling et al., 2005) and ultimately translates into higher affective commitment. Furthermore, the research also proves that this satisfaction and commitment in employee behavior is greatly influenced by transformational leadership (Nielsen et al., 2008). Researchers said that transformational leaders are known for developing proactiveness among followers (Steinmann et al., 2018), they can help employees address challenges linked to creativity and innovation (Ali et al., 2021; Nauman et al., 2021) and proactiveness in the workplace (Jauhari et al., 2017), which could be vital for project success (Guo et al., 2019). Researchers (Ali et al., 2021; Abbas and Ali, 2023) also suggested that transformational leadership significantly enhances project success, so, according to researchers, proactive employees can increase project success if they are working under transformational leaders (Khattak et al., 2024).
Transformational leaders foster an environment where proactive employees feel valued and supported by offering them opportunities for personal growth, recognizing their contributions and encouraging them to take initiative, this sense of empowerment and recognition strengthens employees’ emotional commitment to the organization (Avolio et al., 2004). Additionally, researchers have described that transformational leadership can increase proactive employee behavior (Strauss et al., 2009) through Strengthening employees' organizational and professional affective commitment (Avolio et al., 2004; Zhang and Inness, 2019).
From the above discussion, we can assume that an employee demonstrates higher commitment when they possess proactive personality characteristics under transformational leadership conditions (Strauss et al., 2009). Empirical studies support this moderation effect. For example, Den Hartog and Belschak (2012) found that transformational leadership enhances the relationship between proactive personality and organizational commitment, as transformational leaders provide vision and support that motivates proactive employees to become more emotionally invested in their work. We are proposing the hypothesis.
Transformational leadership strengthens the relationship between a proactive personality and affective commitment.
3. Research methodology
3.1 Data collection
The population of this study included the employees of the IT industry of Pakistan. Data were collected using convenience sampling. Convenience sampling was chosen due to time and resource constraints, making it difficult to access a random sample. To reduce potential biases, diversity in age, gender and job roles was considered (Etikan et al., 2016). Initially, the organization’s top management was contacted to discuss the study’s goals and determine the best way to gather data. The study targeted employees involved in ongoing or recently completed projects. The data was collected at a single time by using cross cross-sectional approach. The unit of analysis was individual. The responders were informed that the study results were available upon request and that their involvement in the study was entirely voluntary throughout the research process. Confidentiality was assured and the study’s purpose was explained during workplace visits. The researchers used a self-administered questionnaire to obtain information from participants. In order to mitigate social desirability bias, participants were guaranteed anonymity for their answers. Harman’s single-factor test was conducted as well for common method bias. Respondents were comprised of the project teams, including the project managers and the project employees, the project management literature has employed this method Stuckenbruck (1986). Professionals working in this field provided the data for this study from January 2024 to April 2024. A total of five hundred questionnaires were distributed to the respondents. The distribution of 500 questionnaires was guided by methodological considerations associated with Partial Least Squares Structural Equation Modeling (PLS-SEM). Following guidelines, the 10-times rule (Hair et al., 2017), which is also supported by recent studies (Kock and Hadaya, 2018). The minimum sample size should be ten times the maximum number of arrowheads pointing toward any latent variable in the model. Our achieved sample size exceeds these stricter thresholds, thereby ensuring the overall reliability of the model results. Out of five hundred, 329 questionnaires were returned to us and the remaining respondents did not respond, for a response rate of 65%, which is considered high for the Asian context, such as Pakistan. Similarly (Javed et al., 2019), reported 72% response rate. While analyzing the received questionnaires, 41 questionnaires were discarded which were incomplete. The response rate was considered adequate for organizational research and steps were taken to minimize non-response bias by comparing the demographic characteristics of respondents and non-respondents. Follow-up reminders were sent to participants to encourage response, the researchers implemented strategies to reduce non-response bias by analyzing early and late respondents to verify equality in essential study variables (Dillman et al., 2014). So, finally, 288 questionnaires were considered for final analysis. This sample size was deemed adequate for PLS-SEM analysis, following guidelines that recommend a minimum of 10 respondents per path in the structural model (Hair et al., 2019).
3.2 Measurements
The research data collection relied on a five-point Likert scale spanning from 1 for strongly disagree to 5 for strongly agree to evaluate the variables. The research used a six-item proactive personality measurement, which originated from (Bateman and Crant, 1993). The 6-item version of the scale appeared in the research of (Wang et al., 2019; Bertolino et al., 2011). A sample of items: “I am always looking for better ways to do things.” For measuring affective commitment as the intervening variable, a measure by (Porter et al., 1974) was adapted that contains a (15-item) questionnaire on affective commitment. The sample question is, “I find that my values and the profession’s values are very similar.” The 14-item scale was employed in this study to measure project success. This study adapted a composite multi-dimensional measure to measure project success holistically. This method is consistent with past studies (Khan et al., 2020; Ameer et al., 2021; Mubarak et al., 2022) and this methodology is compatible with the preceding research (Pinto and Pinto, 1990; Bryde, 2008; Khang and Moe, 2008; Mir and Pinnington, 2014; Suprapto et al., 2015; Raziq et al., 2018). This measurement of the project success is also used by (Aga et al., 2016), covering the duration, budget, end-user satisfaction, performance and effectiveness. We adapted this scale from past studies. The sample of an item is “The project was completed according to the budget allocated.” For measuring transformational leadership that is an intervening variable, a measure was adapted from (Aga et al., 2016), that contains (13 items) questionnaire on leadership, which are based on the basic instrument presented by (Vinger and Cilliers, 2006; Mehmood and Arif, 2011), a sample item was “Project manager provides team members with new ways of looking at puzzling things”. We measure project complexity using a 4-item scale adapted by (Geraldi et al., 2011). Herman’s single-factor test of common method bias was implied to rule out the assumption of biases in the data. According to the criteria of this test, the single factor must not account for 50% of the total Variance (Aguirre-Urreta and Hu, 2019). As per the results the single factor accounts for 36.15% of the Variance, which means that the data does not contain common method bias.
3.3 Test of reliability and validity
For the analysis of data, we used Partial Least Squares structural equation modeling (SEM) through SmartPLS 4.1.0.2. PLS-SEM is deemed as variance-based SEM because it uses the total variance to estimate the model. Also, it is a widely used method to analyze complex models (Kaufmann and Gaeckler, 2015; Qazi et al., 2022). The present study employed PLS-SEM because it does not make distributional assumptions and performs a high degree of statistical power with small samples of data (Hayes, 2017), unlike covariance-based SEM (CB-SEM).
All the assumptions and robustness checks were applied. We assessed the measurement model before the structural model. Since the constructs were reflective, assessing each indicator’s loading is required, along with the construct’s convergent and discriminant validity and internal consistency reliability. The following parameters were used to assess statistics quality: firstly, Average Variance extracted (AVE) > 0.5; secondly, Composite reliability (CR) > 0.7; thirdly Loading >0.7; and lastly Number of items per construct >3 (Fornell and Larcker, 1981; Chin, 1998; Shah and Goldstein, 2006; Peng and Lai, 2012; Hair et al., 2014; Henseler et al., 2015). CR measures internal consistency reliability, while AVE measures convergent validity that quantifies how well a construct accounts for the Variance in its measures. Fornell and Larker measure is used for discriminant validity. Table 1 represents the results. The factor loading value of one item of transformational leadership is < 0.5, so one item of transformational leadership is dropped due to lower factor loading (Hair et al., 2010); other than that, the factor loading values of all the items were greater than 0.7 (Hair et al., 2010), this suggests that the items are well-correlated with the constructs see Figure 2.
Reliability and validity of the constructs
| Constructs | Cronbach’s alpha | Composite reliability | Average variance extracted (AVE) |
|---|---|---|---|
| AC | 0.975 | 0.978 | 0.744 |
| PC | 0.929 | 0.950 | 0.825 |
| PP | 0.851 | 0.888 | 0.569 |
| PS | 0.969 | 0.972 | 0.713 |
| TL | 0.980 | 0.982 | 0.819 |
| Constructs | Cronbach’s alpha | Composite reliability | Average variance extracted (AVE) |
|---|---|---|---|
| AC | 0.975 | 0.978 | 0.744 |
| PC | 0.929 | 0.950 | 0.825 |
| PP | 0.851 | 0.888 | 0.569 |
| PS | 0.969 | 0.972 | 0.713 |
| TL | 0.980 | 0.982 | 0.819 |
Note(s): AC = Affective Commitment, PC= Project Complexity, PP= Proactive Personality, PS= Project Success, TL = Transformational Leadership
The path diagram starts on the left with two circles arranged in a vertical series. From top to bottom, they are labeled as follows: “T L” and “P P.” From “T L,” twelve individual leftward arrows connect to twelve vertically arranged rectangles labeled from top to bottom as follows: The first arrow, with a path coefficient of 0.866, points to the first rectangle labeled “T L 1.” The second arrow, with a path coefficient of 0.983, points to the second rectangle labeled “T L 10.” The third arrow, with a path coefficient of 0.950, points to the third rectangle labeled “T L 11.” The fourth arrow, with a path coefficient of 0.746, points to the fourth rectangle labeled “T L 12.” The fifth arrow, with a path coefficient of 0.938, points to the first rectangle labeled “T L 2.” The sixth arrow, with a path coefficient of 0.781, points to the second rectangle labeled “T L 3.” The seventh arrow, with a path coefficient of 0.857, points to the third rectangle labeled “T L 4.” The eighth arrow, with a path coefficient of 0.806, points to the fourth rectangle labeled “T L 5.” The ninth arrow, with a path coefficient of 0.966, points to the fifth rectangle labeled “T L 6.” The tenth arrow, with a path coefficient of 0.988, points to the sixth rectangle labeled “T L 7.” The eleventh arrow, with a path coefficient of 0.984, points to the fifth rectangle labeled “T L 8.” The twelfth arrow, with a path coefficient of 0.951, points to the sixth rectangle labeled “T L 9.” From “P P,” six individual rightward arrows connect to six vertically arranged rectangles labeled from top to bottom as follows: The first arrow, with a path coefficient of 0.796, points to the third rectangle labeled “P P 1.” The second arrow, with a path coefficient of 0.736, points to the fourth rectangle labeled “P P 2.” The third arrow, with a path coefficient of 0.790, points to the fifth rectangle labeled “P P 3.” The fourth arrow, with a path coefficient of 0.704, points to the sixth rectangle labeled “P P 4.” The fifth arrow, with a path coefficient of 0.727, points to the first rectangle labeled “P P 5.” The sixth arrow, with a path coefficient of 0.769, points to the second rectangle labeled “P P 6.” In the center, the circle labeled “A C” has fifteen individual rightward arrows connecting to fifteen vertically arranged rectangles labeled from top to bottom as follows: The first arrow, with a path coefficient of 0.859, points to the first rectangle labeled “A C 1.” The second arrow, with a path coefficient of 0.854, points to the second rectangle labeled “A C 10.” The third arrow, with a path coefficient of 0.915, points to the third rectangle labeled “A C 11.” The fourth arrow, with a path coefficient of 0.916, points to the fourth rectangle labeled “A C 12.” The fifth arrow, with a path coefficient of 0.832, points to the fifth rectangle labeled “A C 13.” The sixth arrow, with a path coefficient of 0.790, points to the sixth rectangle labeled “A C 14.” The seventh arrow, with a path coefficient of 0.845, points to the seventh rectangle labeled “A C 15.” The eighth arrow, with a path coefficient of 0.916, points to the eighth rectangle labeled “A C 2.” The ninth arrow, with a path coefficient of 0.919, points to the ninth rectangle labeled “A C 3.” The tenth arrow, with a path coefficient of 0.834, points to the tenth rectangle labeled “A C 4.” The eleventh arrow, with a path coefficient of 0.793, points to the eleventh rectangle labeled “A C 5.” The twelfth arrow, with a path coefficient of 0.846, points to the twelfth rectangle labeled “A C 6.” The thirteenth arrow, with a path coefficient of 0.869, points to the thirteenth rectangle labeled “A C 7.” The fourteenth arrow, with a path coefficient of 0.895, points to the fourteenth rectangle labeled “A C 8.” The fifteenth arrow, with a path coefficient of 0.843, points to the fifteenth rectangle labeled “A C 9.” The value 0.138 is written inside the “A C” oval. To the top right of “A C,” the circle labeled “P C” has four rightward arrows connecting to four vertically arranged rectangles labeled from top to bottom as follows: The first arrow, with a path coefficient of 0.880, points to the first rectangle labeled “P C 1.” The second arrow, with a path coefficient of 0.937, points to the second rectangle labeled “P C 2.” The third arrow, with a path coefficient of 0.944, points to the third rectangle labeled “P C 3.” The fourth arrow, with a path coefficient of 0.870, points to the fourth rectangle labeled “P C 4.” On the far right, the circle labeled “P S” has fourteen rightward arrows connecting to fourteen vertically arranged rectangles labeled from top to bottom as follows: The first arrow, with a path coefficient of 0.855, points to the first rectangle labeled “P S 1.” The second arrow, with a path coefficient of 0.883, points to the second rectangle labeled “P S 10.” The third arrow, with a path coefficient of 0.876, points to the third rectangle labeled “P S 11.” The fourth arrow, with a path coefficient of 0.799, points to the fourth rectangle labeled “P S 12.” The fifth arrow, with a path coefficient of 0.807, points to the fifth rectangle labeled “P S 13.” The sixth arrow, with a path coefficient of 0.865, points to the sixth rectangle labeled “P S 14.” The seventh arrow, with a path coefficient of 0.825, points to the seventh rectangle labeled “P S 2.” The eighth arrow, with a path coefficient of 0.856, points to the eighth rectangle labeled “P S 3.” The ninth arrow, with a path coefficient of 0.821, points to the ninth rectangle labeled “P S 4.” The tenth arrow, with a path coefficient of 0.826, points to the tenth rectangle labeled “P S 5.” The eleventh arrow, with a path coefficient of 0.875, points to the eleventh rectangle labeled “P S 6.” The twelfth arrow, with a path coefficient of 0.848, points to the twelfth rectangle labeled “P S 7.” The thirteenth arrow, with a path coefficient of 0.864, points to the thirteenth rectangle labeled “P S 8.” The fourteenth arrow, with a path coefficient of 0.810, points to the fourteenth rectangle labeled “P S 9.” The value 0.584 is written inside the “P S” oval. The interconnections between circles are as follows: A rightward arrow from “T L” to “A C” has a path coefficient of 0.089. A rightward arrow from “P P” to “A C” has a path coefficient of 0.317. A dotted downward arrow from “T L” connects to the arrow between “P P” and “A C” with a path coefficient of 0.157. A rightward arrow from “P P” to “P S” has a path coefficient of 0.330. An arrow from “A C” to “P S” has a path coefficient of 0.518. An arrow from “P C” to “P S” has a path coefficient of negative 0.133. A dotted downward arrow from “P C” connects to the arrow between “A C” and “P S” with a path coefficient of 0.131.Statistical model. Source: Created by authors
The path diagram starts on the left with two circles arranged in a vertical series. From top to bottom, they are labeled as follows: “T L” and “P P.” From “T L,” twelve individual leftward arrows connect to twelve vertically arranged rectangles labeled from top to bottom as follows: The first arrow, with a path coefficient of 0.866, points to the first rectangle labeled “T L 1.” The second arrow, with a path coefficient of 0.983, points to the second rectangle labeled “T L 10.” The third arrow, with a path coefficient of 0.950, points to the third rectangle labeled “T L 11.” The fourth arrow, with a path coefficient of 0.746, points to the fourth rectangle labeled “T L 12.” The fifth arrow, with a path coefficient of 0.938, points to the first rectangle labeled “T L 2.” The sixth arrow, with a path coefficient of 0.781, points to the second rectangle labeled “T L 3.” The seventh arrow, with a path coefficient of 0.857, points to the third rectangle labeled “T L 4.” The eighth arrow, with a path coefficient of 0.806, points to the fourth rectangle labeled “T L 5.” The ninth arrow, with a path coefficient of 0.966, points to the fifth rectangle labeled “T L 6.” The tenth arrow, with a path coefficient of 0.988, points to the sixth rectangle labeled “T L 7.” The eleventh arrow, with a path coefficient of 0.984, points to the fifth rectangle labeled “T L 8.” The twelfth arrow, with a path coefficient of 0.951, points to the sixth rectangle labeled “T L 9.” From “P P,” six individual rightward arrows connect to six vertically arranged rectangles labeled from top to bottom as follows: The first arrow, with a path coefficient of 0.796, points to the third rectangle labeled “P P 1.” The second arrow, with a path coefficient of 0.736, points to the fourth rectangle labeled “P P 2.” The third arrow, with a path coefficient of 0.790, points to the fifth rectangle labeled “P P 3.” The fourth arrow, with a path coefficient of 0.704, points to the sixth rectangle labeled “P P 4.” The fifth arrow, with a path coefficient of 0.727, points to the first rectangle labeled “P P 5.” The sixth arrow, with a path coefficient of 0.769, points to the second rectangle labeled “P P 6.” In the center, the circle labeled “A C” has fifteen individual rightward arrows connecting to fifteen vertically arranged rectangles labeled from top to bottom as follows: The first arrow, with a path coefficient of 0.859, points to the first rectangle labeled “A C 1.” The second arrow, with a path coefficient of 0.854, points to the second rectangle labeled “A C 10.” The third arrow, with a path coefficient of 0.915, points to the third rectangle labeled “A C 11.” The fourth arrow, with a path coefficient of 0.916, points to the fourth rectangle labeled “A C 12.” The fifth arrow, with a path coefficient of 0.832, points to the fifth rectangle labeled “A C 13.” The sixth arrow, with a path coefficient of 0.790, points to the sixth rectangle labeled “A C 14.” The seventh arrow, with a path coefficient of 0.845, points to the seventh rectangle labeled “A C 15.” The eighth arrow, with a path coefficient of 0.916, points to the eighth rectangle labeled “A C 2.” The ninth arrow, with a path coefficient of 0.919, points to the ninth rectangle labeled “A C 3.” The tenth arrow, with a path coefficient of 0.834, points to the tenth rectangle labeled “A C 4.” The eleventh arrow, with a path coefficient of 0.793, points to the eleventh rectangle labeled “A C 5.” The twelfth arrow, with a path coefficient of 0.846, points to the twelfth rectangle labeled “A C 6.” The thirteenth arrow, with a path coefficient of 0.869, points to the thirteenth rectangle labeled “A C 7.” The fourteenth arrow, with a path coefficient of 0.895, points to the fourteenth rectangle labeled “A C 8.” The fifteenth arrow, with a path coefficient of 0.843, points to the fifteenth rectangle labeled “A C 9.” The value 0.138 is written inside the “A C” oval. To the top right of “A C,” the circle labeled “P C” has four rightward arrows connecting to four vertically arranged rectangles labeled from top to bottom as follows: The first arrow, with a path coefficient of 0.880, points to the first rectangle labeled “P C 1.” The second arrow, with a path coefficient of 0.937, points to the second rectangle labeled “P C 2.” The third arrow, with a path coefficient of 0.944, points to the third rectangle labeled “P C 3.” The fourth arrow, with a path coefficient of 0.870, points to the fourth rectangle labeled “P C 4.” On the far right, the circle labeled “P S” has fourteen rightward arrows connecting to fourteen vertically arranged rectangles labeled from top to bottom as follows: The first arrow, with a path coefficient of 0.855, points to the first rectangle labeled “P S 1.” The second arrow, with a path coefficient of 0.883, points to the second rectangle labeled “P S 10.” The third arrow, with a path coefficient of 0.876, points to the third rectangle labeled “P S 11.” The fourth arrow, with a path coefficient of 0.799, points to the fourth rectangle labeled “P S 12.” The fifth arrow, with a path coefficient of 0.807, points to the fifth rectangle labeled “P S 13.” The sixth arrow, with a path coefficient of 0.865, points to the sixth rectangle labeled “P S 14.” The seventh arrow, with a path coefficient of 0.825, points to the seventh rectangle labeled “P S 2.” The eighth arrow, with a path coefficient of 0.856, points to the eighth rectangle labeled “P S 3.” The ninth arrow, with a path coefficient of 0.821, points to the ninth rectangle labeled “P S 4.” The tenth arrow, with a path coefficient of 0.826, points to the tenth rectangle labeled “P S 5.” The eleventh arrow, with a path coefficient of 0.875, points to the eleventh rectangle labeled “P S 6.” The twelfth arrow, with a path coefficient of 0.848, points to the twelfth rectangle labeled “P S 7.” The thirteenth arrow, with a path coefficient of 0.864, points to the thirteenth rectangle labeled “P S 8.” The fourteenth arrow, with a path coefficient of 0.810, points to the fourteenth rectangle labeled “P S 9.” The value 0.584 is written inside the “P S” oval. The interconnections between circles are as follows: A rightward arrow from “T L” to “A C” has a path coefficient of 0.089. A rightward arrow from “P P” to “A C” has a path coefficient of 0.317. A dotted downward arrow from “T L” connects to the arrow between “P P” and “A C” with a path coefficient of 0.157. A rightward arrow from “P P” to “P S” has a path coefficient of 0.330. An arrow from “A C” to “P S” has a path coefficient of 0.518. An arrow from “P C” to “P S” has a path coefficient of negative 0.133. A dotted downward arrow from “P C” connects to the arrow between “A C” and “P S” with a path coefficient of 0.131.Statistical model. Source: Created by authors
Table 1 represents that all variables meet the benchmark for composite reliability and Cronbach’s alpha values at 0.7 or higher, so there is no issue of internal consistency. Furthermore, the average variance extracted (AVE) value for all the variables is above 0.5 (Hair, 2016). Thus, all of the variables are observed to have an acceptable convergent validity. Good internal consistency between constructs was indicated by Cronbach’s alpha values, which varied from 0.72 to 0.89. Composite reliability values were all above 0.70 and AVE values ranged from 0.55 to 0.72, confirming adequate convergent validity. We check the discriminant validity by using Fornell-Larker criteria because it is widely recommended in PLS-SEM research and provides a clear measure of whether constructs are sufficiently distinct from one another. Table 2 shows that square root values of AVEs exceed the off-diagonal correlations between variables, so discriminant validity is confirmed here through the Fornell-Larker Criterion.
Discriminant validity – Fornell Larcker criterion
| Constructs | AC | PC | PP | PS | TL |
|---|---|---|---|---|---|
| AC | 0.863 | ||||
| PC | −0.242 | 0.908 | |||
| PP | 0.323 | 0.139 | 0.754 | ||
| PS | 0.695 | −0.267 | 0.450 | 0.844 | |
| TL | 0.130 | 0.340 | 0.033 | 0.038 | 0.905 |
| Constructs | AC | PC | PP | PS | TL |
|---|---|---|---|---|---|
| AC | 0.863 | ||||
| PC | −0.242 | 0.908 | |||
| PP | 0.323 | 0.139 | 0.754 | ||
| PS | 0.695 | −0.267 | 0.450 | 0.844 | |
| TL | 0.130 | 0.340 | 0.033 | 0.038 | 0.905 |
Note(s): AC = Affective Commitment, PC= Project Complexity, PP= Proactive Personality, PS= Project Success, TL = Transformational Leadership
3.4 Results
The structural model is accessed to evaluate the hypothesis between dependent and independent variables by PLS-SEM by using the same smartPLS 4.1.0.2. Path coefficients of all the variables are represented in Table 3. The results output proved that there is a positive and significant impact of Proactive personality on project success with (β = 0.330, t-value = 6.559), which is greater than the threshold t > 1.96 and (p-value<0.001), which is why H1 is accepted. The significant positive impact of proactive personality on project success suggests that employees who exhibit initiative and adaptability are better equipped to manage dynamic project demands. Following hypothesis 2 states that Proactive personality is positively related to affective commitment, the results confirmed this relationship with a path coefficient (β = 0.317, t-value = 6.559, p < 0.001). The statement of hypothesis 3 that the affective commitment of the followers positively impact project success is also accepted by the results with (β = 0.518, t-value = 8.957, p < 0.001), this indicates that emotional attachment to project goals enhances employees’ perseverance and problem-solving abilities, which are critical in complex, temporary organizational settings. The R-square value of project success is 0.584, which is significant as it lies within the threshold of 0–1 (Rigdon, 2012); see Figure 2. The variance inflation factor (VIF) values of all the constructs were less than <3, which verifies multi-collinearity (Hair et al., 2019). The absence of collinearity in the structural model was validated by VIF values see Table 4. It could also be seen that the beta value of the direct relationship of project complexity with project success is (−0.133) and the beta value of the interaction term of project complexity and affective commitment is (0.131), which shows the violating effect of moderation in the strengthening case as the beta coefficient of affective commitment and project success is (0.581) see Figure 2.
Path coefficients
| Hypothesis | Path | Coefficients | t value | p-value |
|---|---|---|---|---|
| H1 | PP → PS | 0.330 | 6.559 | 0.000 |
| H2 | PP → AC | 0.317 | 5.538 | 0.000 |
| H3 | AC→PS | 0.518 | 8.957 | 0.000 |
| Hypothesis | Path | Coefficients | t value | p-value |
|---|---|---|---|---|
| PP → PS | 0.330 | 6.559 | 0.000 | |
| PP → AC | 0.317 | 5.538 | 0.000 | |
| AC→PS | 0.518 | 8.957 | 0.000 |
Note(s): AC = Affective Commitment, PC= Project Complexity, PP= Proactive Personality, PS= Project Success, TL = Transformational Leadership
Multi-collinearity statistics
| Constructs | VIF |
|---|---|
| AC→PS | 1.334 |
| PC→PS | 1.221 |
| PP→AC | 1.002 |
| PP→PS | 1.263 |
| TL→AC | 1.059 |
| PC×AC | 1.291 |
| TL×PP | 1.058 |
| Constructs | VIF |
|---|---|
| AC→PS | 1.334 |
| PC→PS | 1.221 |
| PP→AC | 1.002 |
| PP→PS | 1.263 |
| TL→AC | 1.059 |
| PC×AC | 1.291 |
| TL×PP | 1.058 |
Note(s): AC = Affective Commitment, PC= Project Complexity, PP= Proactive Personality, PS= Project Success, TL = Transformational Leadership
3.5 Specific indirect mediation analysis
The mediation investigation evaluates affective commitment as a mediating factor that connects proactive personality to project success outcomes. A bootstrapping approach was used to evaluate mediation with 5,000 resamples. Bootstrapping is particularly suitable as it does not assume normality in the sampling distribution of the indirect effect and provides more robust and accurate estimates of mediation (Hayes, 2017). It can be seen from the results that the beta values of proactive personality’s direct impact on project success are positive and significant. The indirect effect of proactive personality on project success through affective commitment was significant, with a path coefficient of 0.164 and a p-value of <0.01, indicating a mediation effect. At the same time, the relationship is also significant, with the inclusion of a mediator between a proactive personality and project success through affective commitment. Hence, the results confirm the acceptance of hypothesis 5. The results indicate a partially mediated relationship between the independent and dependent variables through affective commitment, as both the direct and indirect effects are significant see Table 5. These results suggest that affective commitment is a key mechanism through which proactive employees contribute to project success. Proactive individuals may engage more deeply with their work, fostering an emotional attachment that motivates them to go above and beyond in their efforts, leading to successful project outcomes.
Mediation analysis
| Mediation analysis | Coefficients | Standard deviation | t value | p Value |
|---|---|---|---|---|
| Direct effect | ||||
| PP → PS | 0.330 | 0.050 | 6.559 | 0.000 |
| Indirect effect | ||||
| PP→AC→PS | 0.164 | 0.038 | 4.293 | 0.000 |
| Mediation analysis | Coefficients | Standard deviation | t value | p Value |
|---|---|---|---|---|
| Direct effect | ||||
| PP → PS | 0.330 | 0.050 | 6.559 | 0.000 |
| Indirect effect | ||||
| PP→AC→PS | 0.164 | 0.038 | 4.293 | 0.000 |
Note(s): AC = Affective Commitment, PC= Project Complexity, PP= Proactive Personality, PS= Project Success, TL = Transformational Leadership
3.6 Moderation analysis
We performed the moderation analysis to analyze the moderating effects of transformational leadership and project complexity. Table 6 shows the moderating effects of the proposed relationships. The values of the moderating effects of the transformational relationship between proactive personality and affective commitment show that the moderating effect is significant and strengthens the relationship, which means proactive employees are more committed if they are working in the presence of transformational leadership. The moderating impact of project complexity on the relationship between affective commitment and project success is examined next. We analyze the moderation effect of project complexity on the relationship between affective commitment and project success. The values show the interaction term is significant, which means that if employees face higher project complexity, they will show higher commitment to provide higher achievements when faced with challenges.
Moderation analysis
| Moderation Analysis | Coefficient | Standard deviation | t value | p Value |
|---|---|---|---|---|
| TL×PP→AC | 0.157 | 0.062 | 2.511 | 0.012 |
| PC×AC→PS | 0.131 | 0.059 | 2.224 | 0.026 |
| Moderation | Coefficient | Standard deviation | t value | p Value |
|---|---|---|---|---|
| TL×PP→AC | 0.157 | 0.062 | 2.511 | 0.012 |
| PC×AC→PS | 0.131 | 0.059 | 2.224 | 0.026 |
Note(s): AC = Affective Commitment, PC= Project Complexity, PP= Proactive Personality, PS= Project Success, TL = Transformational Leadership
4. Discussion
Our research has addressed a significant gap in the literature by analyzing the effects of proactive personality on project success in Pakistan as well as evaluates the mediation of affective commitment between these variables and the moderation effects of transformational leadership between proactive personality and affective commitment and also how project complexity moderates between affective commitment and project success. Results between proactive personality and project success portray the positive link. The findings of this study align with attribution theory, where proactive individuals interpret and respond to organizational stimuli (e.g. leadership and project conditions) in ways that amplify their commitment and performance (Martinko et al., 2007; Di Maddaloni and Derakhshan, 2024). Furthermore, the role of affective commitment as a mediator is underpinned by person-organization fit theory, which suggests that congruence between an individual’s proactive disposition and supportive environments (such as transformational leadership) fosters stronger emotional ties and improved outcomes. The mediation effect of affective commitment supports the person-organization fit (P-O fit) theory, which posits that individuals whose personal values align with organizational values develop stronger emotional bonds and perform better (Kristof, 1996).
This study aligns with the previous studies (Bindl and Parker, 2011), in which they presented the proactive personality as a social behavior that impacts project success and organizational effectiveness. Expanding upon these results, our research shows that the association between proactive personality and project success, especially in complex project environments, is mediated by affective commitment echoing the work of (Thomas et al., 2010). As proactive behavior gives employees the potential to take initiative and opportunities to influence the environment, it is important to adopt proactive behavior in this competitive market by quickly responding to the changing environment.
In a competitive market, it can be difficult for organizations to deal with complicated changes (Fraj et al., 2015). Thus, the current study recommends that in this competitive market, firms need to pick candidates with proactivity or create conditions that help employees develop their proactive traits. Organizations should keep these skilled and committed workers after employing such proactive individuals. These workers assist a company in accomplishing its objectives because they have the ability to take initiative, take advantage of opportunities and affect the environment (Yang et al., 2019) and this proactive behavior is always positively correlated with work outcomes, such as project performance and success (Chan, 2006). These results align with the person-organization fit theory, who suggested that individuals are more likely to succeed when their values and behaviors are congruent with those of the organization, therefore in the IT-Project based organization the employees with proactive personalities feel a stronger organizational fit, thereby enhancing their emotional attachment and, consequently, their contribution to project success. Building on these findings, the mediation impact of affective commitment between proactive personality and project success is further examined in the current study. The current findings are consistent with the findings of (McShane and Glinow, 2008; Meyer and Herscovitch, 2001), who proposed that an employee’s affective commitment is the strongest indicator of their efforts to support the success of their projects and the performance of organizations. As proactive behavior gives employees the potential to take the initiative and opportunities to influence the environment, employees can feel control over the environment, which leads to emotional attachment. This attachment of the proactive employees will consistently increase their satisfaction with their work and organization (Bowling et al., 2005) and ultimately transfer into higher affective commitment, leading to project success (Ghafoor et al., 2016). Therefore, project performance directly relates to proactive personality through employees who exhibit high commitment levels. The study suggests improving the employees' personalities to gain commitment, as this loyalty and commitment can increase the project’s success. The present study additionally investigates the relationship between affective commitment and proactive personality by analyzing transformational leadership as a moderating influence. The findings suggest a higher correlation exists between affective commitment and proactive personality when adopting transformational leadership behavior. Transformational leadership and followers' behavior have been found to be positively correlated in the past few decades (Zwingmann et al., 2014). It is evident from the literature that transformational leadership styles significantly influence proactive individuals with high commitment and determination (Avolio et al., 2004). So, the results of this study align with the study of (Strauss et al., 2009), that transformational leadership can increase proactive employee behavior by enhancing employees' affective commitment to the organization and profession (Avolio et al., 2004; Zhang and Inness, 2019). Thus, a crucial role is played by transformational leadership between affective commitment and a proactive personality. Lastly, this study investigates the moderating role of project complexity between affective commitment and project success. In this present competitive market, it can be difficult for organizations to deal with complicated changes (Fraj et al., 2015). So, the results of this study align with the research (Liu, 1999; Locke and Latham, 1990), who suggested that when the complexity of a project increases due to the competitive environment, the project’s employees show more committed behavior toward their projects. As the difficulty of the project affects a person’s expectations of their performance capacity, the person becomes more committed to their work and projects and will change their behavior to ensure the project’s success. High levels of commitment are predicted to provide higher achievements when faced with challenging goals (Liu, 1999). So, project complexity is an important variable between the affective commitment and project success.
5. Theoretical and practical implications
This research presents multiple theoretical and practical implications. From a theoretical perspective, the study confirms that affective commitment serves as a mediator between proactive personality and project success outcomes by offering a novel mechanism for understanding employee behavior (Seibert et al., 2001; Rehan et al., 2024). This mechanism illustrates a new pathway through which proactive traits lead to improved organizational outcomes, offering insight into the dynamics of motivation and personality in project-based contexts (Grant et al., 2009). From a practical perspective, organizations can use these findings to develop strategies that foster specific proactive behaviors among employees, such as taking initiative, anticipating and preventing potential problems and seeking out opportunities for improvement. By encouraging these behaviors, organizations can strengthen employees' affective commitment, which in turn contributes to greater project success. The two research questions that have received less attention in the field of project management have been addressed in the current study. The first research question is looking into the link between employees' proactive personality and project success. The results of this study confirm that the success of the projects can be increased by the proactive behavior of employees, which is a new contribution to the literature. The positive influence of proactive personality on project success aligns with recent findings by (Rehan et al., 2024), who emphasized the role of proactive traits in complex projects. The second research question looks into the mediating mechanism of affective commitment between proactive personality and project success. The results of this study revealed that affective commitment can mediate the relationship between proactive personality and project success; this mechanism provides the literature with a new way of thinking about how proactive behavior can enhance employees' affective commitment, which ultimately results in the higher success of the projects.
Moreover, this study also confirms that transformational behavior is a moderator between proactive personality and affective commitment; therefore, organizations should focus on employees' personalities and their leadership styles while hiring them as it, directly and indirectly, relates to the success rate of the projects. The moderating effect of transformational leadership is in line with findings by (Newman et al., 2018), confirming that such leaders enhance employee commitment, particularly in dynamic environments.” Transformational leaders also play a key role in fostering affective commitment by building trust and emotional connections with their teams. Organization should organize transformational leadership trainings for managers, especially for those leading high-complexity projects as leaders who adopt transformational approaches can empower proactive employees by providing vision and recognition, thereby enhancing affective commitment. It is suggested by the current study that organizations should prioritize proactive personnel or help them to improve through different trainings. Organizations should prioritize recruiting candidates with a demonstrated ability to adapt and self-initiate and they should include personality assessments as part of their hiring processes. Additionally, from a practical standpoint, organizations can use these insights to strengthen employee proactive behaviors and affective commitment by revising recruitment practices to assess proactive traits, designing transformational leadership development programs and fostering supportive, innovation-driven workplace cultures. In complex project environments, particularly within the IT sector, these strategies can enhance project success rates by empowering employees to navigate uncertainty and complexity effectively. These findings of this study also have societal implications, suggesting that investments in leadership and employee development can contribute to greater organizational resilience, innovation and overall project performance (Bakker and Oerlemans, 2019; Ahmad et al., 2021; Blake et al., 2022). Organizations should propose initiatives for fostering a supportive environment that encourages proactive behaviors and affective commitment and they can encourage innovation through flexible policies, cross-functional collaboration and task autonomy, which are particularly valuable in IT project-based environments. Furthermore, the current study also suggests focusing on employees' affective commitment, as committed employees can handle complex projects better by facing challenging goals. The results of this study reinforce recent findings in project management literature, where the interplay of personality traits and leadership behaviors is seen as vital to success (Bakker and Oerlemans, 2019; Ahmad et al., 2021).
6. Limitations and future directions
This study has limitations which can be improved through future investigations by researchers. The present study used the cross-sectional approach to collect the data, thus our capacity to infer causality is limited by the cross-sectional design. The longitudinal research design allows future investigators to examine time-based changes in proactive personality as well as affective commitment and project outcomes (Ployhart and Vandenberg, 2010).
Secondly, the sample size is small due to the limited number of project-based organizations in Pakistan: The sample was limited to IT employees in a single geographic region, which may not be representative of other industries or global contexts. Future research should aim to replicate this study in diverse industries and cultural settings to examine whether the relationships between proactive personality, affective commitment and project success hold across different organizational environments (Hofstede, 2001). Moreover, the data for this study was collected only from Pakistan, which may cause the generalizability issue to arise. Furthermore, the present study only employed affective commitment as a mediator between proactive personality and project success; future studies should consider other mediating mechanisms, such as work engagement, job satisfaction or organizational identification (Bakker et al., 2008). Moreover, in the current study, we analyze transformational leadership as a moderating mechanism to link proactive personality and affective commitment; future studies can introduce other leadership styles.
7. Conclusion
This study highlights several important findings. The current study adds to the body of literature on the impact of employees' proactive personalities on project success by providing experimental evidence of the mediation role of affective commitment and a moderating element of transformational leadership between proactive personality and affective commitment. Affective commitment functions as an essential factor which connects proactive personality to project success achievements, consistent with earlier findings (Kristof, 1996; Meyer and Herscovitch, 2001), this finding highlights the importance of emotional attachment in translating proactive behaviors into organizational outcomes. By fostering affective commitment, organizations can ensure that proactive employees remain engaged and motivated, leading to better project outcomes. The findings of this study help in a deeper understanding of attribution theory which posits that proactive individuals who attribute project success to their actions and the organizational support they receive higher levels of affective commitment. Therefore, the current study’s findings demonstrate that in order to improve organizational effectiveness and ensure project success, it is necessary to understand the personalities of individuals working in organizations, particularly in complex environments and in the project-based IT sectors (Seibert et al., 2001; Grant et al., 2009), where positions are contract-based, temporary or specialized to a single project. Furthermore, it seems that an employee’s personality is a reliable predictor of how an individual is faithful to his work; this faithfulness alternatively results in offering a successful project. Thus, achieving employees' commitments is necessary while completing the projects successfully. This study contributes in person-organization fit theory by showing that proactive personality aligns well with the needs of project-based organizations and proactive personality significantly drives career development outcomes (Zhang et al., 2022) where task complexity and leadership support play critical roles as proactive employees feel a stronger organizational fit in environments where they have the freedom to take initiative and influence project outcomes. This sense of fit, in turn, enhances their commitment and performance, aligning well with project-based environments like the IT sector. Managers should provide employees with opportunities for development and greater autonomy to encourage proactive behaviors. Additionally, creating a supportive work environment that fosters emotional commitment will help ensure that employees are fully engaged, motivated and capable of driving successful project outcomes.

