Personality profiles and innovation success: insights from micro-entrepreneurial ventures

Human personality is a complex and multidimensional set of traits, behaviors, preferences, and tendencies that shape how an individual thinks, acts, and responds to various life situations (Subha Rani, 2014; Strachan, 2017; Zare & Flinchbaugh, 2019; Bhullar, Schutte, & Wall, 2020; Park & Kim, 2021; De Haro & Vena, 2025). It is a psychological “signature” that defines people’s uniqueness and distinguishes them from others (Hao, Seibert, & Lumpkin, 2010). In other words, personality is a dynamic and organized set of characteristics that influences an individual’s cognitions, emotions, motivations, and behaviors in various situations (Bhullar et al., 2020; Subha Rani, 2014).

In psychology, scholars studied personality through several theoretical approaches, among which the most notable are the psychodynamic (Freud, 1904), cognitive-behavioral (Dollard & Miller, 1950), humanistic (Rogers, 1961), and trait-based (Cattell, 1950) perspectives. The latter approach appears particularly compelling from the standpoint of human innovation. Given that we understand a trait as a coherent and enduring pattern of thinking, feeling, and behaving (Cattell, 1990), trait theories seek to describe personality based on an individual’s distinctive characteristics to predict their future behavior. One of the most widely recognized and utilized trait theories is the Five-Factor Model (FFM) of personality (McCrae & Costa, 1987; Goldberg, 1990). This model identifies five fundamental personality dimensions, i.e. openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism (OCEAN), which science regards as universal and which account for the majority of individual personality differences (John & Srivastava, 1999). Notably, this framework not only facilitates the analysis of these five broad dimensions but also enables a more fine-grained exploration of personality by examining the facets (Soto & John, 2009; Matz, Chan, & Kosinski, 2016; Jirásek & Sudzina, 2020) or mini-markers (Saucier, 1994; Ali, 2019) that underlie them, thereby offering deeper insights into individual differences (Zare & Flinchbaugh, 2019). The examination of these facets allows researchers to identify subtle individual differences that may be particularly relevant for distinct behavioral patterns, such as creativity, problem-solving, leadership, and adaptability (Matz et al., 2016; Li, Huang, & Gao, 2022). For example, openness to experience is not a monolithic trait but rather a constellation of interrelated characteristics, including intellectual curiosity, aesthetic sensitivity, and a proclivity for novelty (Jirásek & Sudzina, 2020). Similarly, extraversion extends beyond sociability to encompass attributes such as assertiveness and enthusiasm, which influence interpersonal dynamics and professional success (Ali, 2019; Park & Kim, 2021).

Incorporating facets into personality research provides a more granular understanding of how personality shapes human behavior, enhancing its explanatory power beyond the FFM’s broad categories (Jirásek & Sudzina, 2020). Recognizing the influence of specific facets allows for a more precise assessment of individual differences, particularly in domains where personality traits are linked to performance, well-being, or innovation (Soto & John, 2009; Matz et al., 2016). This level of specificity is especially relevant in fields such as entrepreneurship and organizational psychology, where distinguishing between overarching traits and their constituent facets can refine predictive models of professional success and personal development (Saucier, 1994). Consequently, an approach that considers both the principal dimensions of personality and their underlying facets yields a richer and more nuanced depiction of the ways in which personality informs various life outcomes.

Considering the aspiration to predict future human behavior, it is worth emphasizing that innovativeness represents precisely such a desirable trait, irrespective of the perspective – whether micro, meso, or macro. But how do we cultivate innovativeness? This question has preoccupied humanity for centuries. As early as the beginning of the Common Era, Roman philosophers such as Seneca suggested that “finesse is born from hunger” (Latin: artificia docuit fames) (Seneca, 1969). This perspective remains relevant today, as highlighted by Taleb in his concept of antifragility (Taleb, 2012).

In contemporary research, scholars examine the construct of innovation capability to address this question (Forsman, 2011; Martínez-Román, Gamero, & Tamayo, 2011; Mendoza-Silva, 2021; Zastempowski, 2022). Scholars typically understand this as the organization’s ability to manage and generate innovations over the long term (Smith, Busi, Ball, & van der Meer, 2008; Mendoza-Silva, 2021). However, despite extensive research, significant ambiguities persist regarding its precise definition (Calantone, Cavusgil, & Zhao, 2002; Martínez-Román et al., 2011; Sulistyo & Siyamtinah, 2016; Dziallas & Blind, 2019; Mendoza-Silva, 2021).

From the Resource-Based View (Prahalad & Hamel, 1990; Barney, 1991), scholars often conceptualize innovation capability as a combination of diverse resources that facilitate innovation, encompassing both tangible assets, such as financial and technological resources, and intangible elements, including knowledge, skills, and organizational culture (Guan & Ma, 2003; Guan, Yam, Mok, & Ma, 2006; Smith et al., 2008; Forsman, 2011). Some studies suggest that innovation capability not only serves as a driver of innovation but also enhances an organization’s capacity to adapt to competitive pressures, market fluctuations, and shifts in the external environment (Guan & Ma, 2003; Elmquist & Le Masson, 2009).

Smith et al. (2008) define a firm’s innovation capability as a set of specific organizational capabilities designed to manage and create innovation over time, whereas Forsman (2011) contends that innovation capability comprises both internal resources and capabilities, along with external inputs obtained through networking and collaboration. This dual perspective underscores the interconnected nature of innovation capability, highlighting the critical interplay between internal competencies and external relationships in sustaining long-term innovation potential.

There appears to be a distinct group of entrepreneurs in whom both these dimensions — personality and innovation capability — uniquely intertwine, namely, self-employed micro-entrepreneurs. Notably, although Schumpeter (1912) already identified them as a key force driving the development of “the capitalist machine,” micro-entrepreneurs remain on the periphery of innovation research (Roper & Hewitt-Dundas, 2017; Audretsch, Kritikos, & Schiersch, 2020; Crespo, Curado, Oliveira, & Muñoz-Pascual, 2021; Farè, 2022; Nafizah, Roper, & Mole, 2024; Zastempowski, 2024), with studies on the self-employed being even scarcer (Romero & Martínez-Román, 2012; Faherty & Stephens, 2016; Plotnikova, Romero, & Martínez-Román, 2016; Lange, Hüsig, & Albert, 2023). This oversight is particularly striking given statistical data indicating that this group of entrepreneurs constitutes a substantial share of modern economies (e.g. 16.8% in the European Union). Furthermore, some studies highlight their significant contribution to job creation, economic growth (Margolis, 2014; Sharp, Torp, Van Hoof, & de Boer, 2017; Burke & Cowling, 2020; Portes & Bagwell, 2023), innovation, and entrepreneurship (Roper & Hewitt-Dundas, 2017; Sharp et al., 2017; Švarcová, Kramoliš, Dobeš, Urbánek, & Horáková, 2022).

While extensive research has explored the relationship between personality traits and innovative behavior across various contexts, including established organizations and entrepreneurial ventures (De Jong & Den Hartog, 2010; Hao et al., 2010; Zare & Flinchbaugh, 2019), studies specifically focusing on the self-employed micro-entrepreneurs remain limited. Existing meta-analyses provide insights into how personality influences entrepreneurship and innovation (Hao et al., 2010), but they often overlook the unique challenges and dynamics of micro-entrepreneurs who operate independently and with fewer organizational resources. Moreover, while prior studies have examined broad personality traits, the role of specific personality facets in shaping innovation capability within this group remains underexplored (Leutner, Ahmetoglu, Akhtar, & Chamorro-Premuzic, 2014; Ogurlu & Özbey, 2022). This article aims to fill this gap by investigating the link between personality facets and innovation capability among self-employed micro-entrepreneurs. Building on previous studies that have established links between personality traits and innovation capability in broader entrepreneurial contexts (De Jong & Den Hartog, 2010; Hao et al., 2010), I sought to extend this knowledge by focusing specifically on self-employed micro-entrepreneurs. While prior research has explored general personality traits, the role of personality facets in shaping innovation capability in this distinct group has received limited attention.

Therefore, I formulated the following research question: Is there a relationship between the personality facets of self-employed micro-entrepreneurs and their innovation capabilities?

The article is structured as follows. In the theoretical background, constituting part of the literature review, I delve into the FFM of personality, innovation capability, and the relationship between them. Subsequent sections respectively outline the research methodology and the findings, while the discussion and concluding sections deliberate on the outcomes and their theoretical and practical recommendations.

Based on the achievements of psychology, we can assume that personality is a distinctive and relatively stable set of mental traits that underlie a person’s characteristic ways of thinking, feeling, and behaving (Neuman, 2014; Strachan, 2017; Bhullar et al., 2020), which encompasses traits, dispositions, character, motivation, temperament, will, self-assessment, and skills (Scripcaru, Scripcaru, Iliescu, & Iacob, 2022).

Drawing from the above-mentioned trait theory, we can infer that the FFM is among the predominant and extensively employed personality models, alternatively referred to as the Big Five. Formulated by multiple investigative teams (McCrae & Costa, 1987; Botwin & Buss, 1989; Goldberg, 1990; Jang, McCrae, Angleitner, Riemann, & Livesley, 1998), this framework asserts the presence of five primary personality trait dimensions – OCEAN. Renowned for its widespread acceptance, cross-cultural relevance, and pragmatic value in personality exploration (Costa & McCrae, 2008; Marcati, Guido, & Peluso, 2008; Abdullah, Omar, & Panatik, 2016; Stock, Von Hippel, & Gillert, 2016; Ali, 2019), the model has garnered recognition. Below, I briefly summarize the key characteristics and facets encompassed by the FFM.

Openness to experience reflects an individual’s inclination toward exploring new ideas, creativity, and interest in culture, art, and knowledge (De Haro & Vena, 2025; Stock et al., 2016). The literature typically assesses openness in comparison to experiences that relate to openness to fantasy, aesthetics, feelings, actions, ideas, and values (Costa & McCrae, 1992; George & Zhou, 2001). People with high openness to experience are typically curious about the world and open to diversity and new perspectives (George & Zhou, 2001; De Haro & Vena, 2025). They enjoy experimenting, are flexible, and are tolerant of change (Zhou & George, 2001). On the other hand, individuals with low openness to experience may be more conventional, inclined to stick to familiar paths, and avoid the risks associated with new ideas or situations (McCrae & Costa, 1987).

Openness to experience also encompasses various facets, including aesthetics and ideas (Soto & John, 2009; Matz et al., 2016). Noteworthy, great interest in aesthetics and art is a feature usually demonstrated by people with a high level of openness to experience (Swami & Furnham, 2019; Zare & Flinchbaugh, 2019; Babcock & Wilson, 2020). They are inclined to explore various forms of artistic expression, from painting and music to literature and theatre (Matz et al., 2016; Afhami & Mohammadi-Zarghan, 2018). Their open-mindedness makes them more receptive to perceiving and appreciating different aspects of beauty in the surrounding world. Moreover, they may be more inclined to experiment with their own forms of artistic expression, which are not necessarily bound by traditional norms or conventions (Cleridou & Furnham, 2014).

Similarly, individuals with high openness to experience often have rich inner lives and imagination – they have ideas (Babcock & Wilson, 2020). They are usually more prone to generating original ideas and taking innovative approaches to problem-solving. Their ability for abstract thinking and cognitive flexibility allows them to combine diverse concepts and perspectives creatively (Kaufman et al., 2016).

Conscientiousness refers to the degree to which an individual is organized, systematic, and meticulous in their approach to life (Roberts, Lejuez, Krueger, Richards, & Hill, 2014; Park & Kim, 2021). People with high conscientiousness exhibit attention to detail, discipline, self-discipline, and a tendency to set ambitious goals and strive to achieve them (George & Zhou, 2001; Zhao & Seibert, 2006; De Haro & Vena, 2025). They are typically responsible, punctual, and diligent in their actions. On the other hand, individuals with low conscientiousness may tend to be impulsive and chaotic and struggle to maintain order in their personal and professional lives (McCrae & Costa, 1987).

Moreover, in the field of conscientiousness, scholars indicate two important facets, namely self-discipline and order (Soto & John, 2009; Matz et al., 2016). Individuals characterized by high levels of conscientiousness typically exhibit strong self-discipline (Babcock & Wilson, 2020). They possess the ability to control their behaviors, consistently pursue set goals, and adhere to specific norms or values (Nudelman & Otto, 2021). These are individuals who meticulously plan their actions, establish priorities, and engage in regular routines to achieve success in their professional, personal, or educational lives (Pilarska, 2018). Self-discipline is crucial for them as it helps them stay on track toward achieving long-term goals.

Individuals characterized by high levels of conscientiousness typically emphasize maintaining order and organization in their lives (Babcock & Wilson, 2020). Their environment is usually tidy, and things are arranged in their proper places. They value cleanliness, regularity, and systematicity in their daily duties and time management (Xu, Karinen, Chapman, Peterson, & Plaks, 2020). For them, order is crucial for effectiveness, efficiency, and a sense of control over their lives (McCrae & Costa, 1987).

Extraversion refers to the degree to which an individual is inclined to open up to the external environment, engage in social interactions, and derive energy from contact with other people (Saatci & Ovaci, 2020; De Haro & Vena, 2025). Individuals with high levels of Extraversion are typically outgoing and communicative and enjoy being the center of attention (McCrae & Costa, 1987; Zare & Flinchbaugh, 2019; Runst & Thomä, 2022). They often actively participate in social life, easily make new acquaintances, and derive pleasure from group activities (Reilly, Lynn, & Aronson, 2002). On the other hand, individuals with low levels of extraversion may be more prone to solitude, avoid large gatherings, and prefer quiet, intimate gatherings with close friends (Rashid, Alzafari, & Kratzer, 2020).

In the dimension of extroversion, Soto and John point to two interesting facets of personality: assertiveness and activity (Soto & John, 2009). Individuals with high levels of extraversion typically exhibit strong, assertive traits (Babcock & Wilson, 2020). They are self-assured, open in social interactions, and inclined to express their opinions and needs directly and decisively (Steel, Rinne, & Fairweather, 2011; Goel, Padickaparambil, Sreelakshmi, & Pothiyil, 2024). Their assertiveness allows them to effectively communicate with others, express their emotions, and resolutely pursue goals (Rashid et al., 2020; Ceccarini & Andreani, 2022). Moreover, extroverted individuals often derive energy and motivation from interacting with other people, which can further support their assertiveness in various social situations.

Another significant aspect of extraversion is activity. Extraverted individuals are typically energetic, lively, and prone to engaging in various activities (Berenbaum, Chow, Schoenleber, & Flores, 2016; Babcock & Wilson, 2020). They enjoy being in the spotlight, participating in social events, and being part of various groups or projects. Their enthusiasm and positive outlook on life often attract others and facilitate the establishment of new social connections and relationships (Sun, Kaufman, & Smillie, 2018; Rashid et al., 2020). Moreover, the activity of an extroverted individual can lead to a wide range of life experiences and the acquisition of new skills through exploring different fields and interests (Wilson & Dishman, 2015).

Agreeableness refers to an individual’s tendency toward kindness, cooperation, and avoidance of conflicts in interpersonal relationships (Matz et al., 2016). Individuals with high agreeableness are typically empathetic, friendly, and willing to compromise (Zare & Flinchbaugh, 2019; De Haro & Vena, 2025). They tend to avoid confrontation and strive to maintain harmony in their relationships with others (Rashid et al., 2020). On the other hand, individuals with low agreeableness may be more assertive, prone to confrontation, and less willing to make concessions to avoid conflicts (Stock et al., 2016).

Furthermore, according to the concept of Soto and John, agreeableness includes two facets of personality, i.e. altruism and compliance (Soto & John, 2009; Zare & Flinchbaugh, 2019). Individuals characterized by high levels of agreeableness typically exhibit strong altruistic tendencies. They are inclined to sacrifice their time, energy, and resources for the sake of others (Tobin & Graziano, 2020). Altruism is a natural attitude for them, motivating them to provide assistance, support others, and care for their well-being. Agreeable individuals often engage in charitable actions and volunteering or are ready to provide emotional support to their loved ones and those in need (Zhao, Ferguson, & Smillie, 2017). Their ability to show empathy and concern for others makes them valued in communities and interpersonal relationships (Zhao & Smillie, 2015).

In terms of compliance, we should emphasize that individuals with high levels of this trait typically avoid conflicts and strive for harmony in their relationships with others. They are inclined towards compromise and avoiding confrontation to maintain peace and good relations with their surroundings (Tobin & Graziano, 2020). Their priority often lies in avoiding disputes and seeking to resolve conflicts peacefully and diplomatically (Babcock & Wilson, 2020). However, excessive agreeableness can sometimes lead to sacrificing their own needs and desires for others, which can result in frustration or not expressing their views and desires.

Neuroticism is the final key trait in the FFM of personality. It refers to the degree to which an individual experiences negative emotions such as anxiety, worry, depression, or insecurity (Matz et al., 2016; Anwar, Shah, & Khan, 2018). Individuals high in neuroticism may be prone to experiencing intense emotions, overreacting to stressful situations, and have a tendency to experience low self-esteem (Zare & Flinchbaugh, 2019; Rashid et al., 2020). They often exhibit mood swings and struggle to cope with emotional challenges (De Haro & Vena, 2025). In contrast, individuals low in neuroticism are typically more emotionally stable, less susceptible to negative emotional reactions, and have better coping abilities with stress and life difficulties.

Like the earlier FFM traits, neuroticism has two key facets. These are anxiety and depression (Soto & John, 2009). Individuals characterized by high levels of neuroticism often experience intense feelings of anxiety (Zhang, 2020). They may be prone to bouts of worry, fear of the unknown, or excessive stress in response to life’s difficulties. Anxiety can lead to excessive concern about the future and avoidance of situations that trigger distress (Saviola et al., 2020). Individuals with high neuroticism may tend to overestimate risks and interpret situations as more dangerous or threatening than they actually are.

Another significant facet of neuroticism is a tendency toward depression. Individuals with high levels of this trait may experience feelings of sadness, hopelessness, and loss of interest in life (Zhang, 2020). Depression can lead to a decrease in energy, difficulties in concentration, as well as changes in appetite or weight. Individuals with high neuroticism are more vulnerable to depressive disorders, especially in stressful situations or in response to difficult life events (Montag, Sanwald, Widenhorn-Müller, & Kiefer, 2022).

While prior research has primarily examined the FFM traits in relation to innovation as broad constructs, this study adopts a facet-level approach to provide a more detailed perspective on the personality-innovation link. Moreover, by focusing on micro-enterprises, it extends the discussion beyond traditional organizational settings where multiple stakeholders shape innovation.

Numerous studies have extensively explored innovation capability within the innovation management field. However, as Mendoza-Silva (2021) suggests, the multitude of conceptualizations surrounding its definition has led to significant research gaps. Similarly, El et al. (2020) argue that innovation capability remains difficult to delineate as a distinct construct, while Kiron and Kannan (2015) highlight the ongoing challenges in its measurement. The following section presents the most frequently cited definitions in the literature.

According to Lawson and Samson (2001), innovation capability refers to the continuous transformation of knowledge and ideas into new products, processes, and systems that benefit a firm and its stakeholders. Drawing on the Resource-Based View theory (Penrose, 1959; Teece, 1980; Prahalad & Hamel, 1990; Barney, 1991), Guan and Ma (2003) describe innovation capability as a combination of various resources that foster innovation. Other studies suggest that innovation capability enables an organization to adapt to competition, market conditions, and environmental changes (Guan & Ma, 2003; Elmquist & Le Masson, 2009).

Forsman (2011) proposed that innovation capability comprises internal resources, organizational capabilities, and external input gained through networking. Martínez-Román et al. (2011) define innovation capability more broadly as an internal competence that influences the entire organization. Similarly, drawing on the theory of dynamic capabilities (Teece, Pisano, & Shuen, 1997), Cheng and Lin (2012) argue that innovation capability constitutes a dynamic capability – namely, a learned and stable pattern of collective activity through which an organization systematically develops and modifies its operating routines to enhance effectiveness.

Mendoza-Silva (2021) further contends that, due to its intangible nature, we can analyze and measure innovation capability from various perspectives, including its dimensions, input or output measurements, and determinants. Zastempowski (2022) synthesizes these perspectives, emphasizing that we should perceive innovation capability as a tacit and non-modifiable strategic asset (Guan & Ma, 2003), grounded in organizational learning (Calantone et al., 2002) or knowledge transformation (Lawson & Samson, 2001), as well as in the ability to absorb, master, and improve existing technologies (Romijn & Albaladejo, 2002) to successfully adopt or implement new ideas, processes, or products.

Considering the above, this article adopts Zastempowski’s (2022) definition of innovation capability, as it synthesizes multiple perspectives on the concept and offers a holistic approach to understanding its components. This definition is particularly valuable because it integrates both theoretical and empirical insights, making it well-suited for assessing innovation capability in diverse organizational contexts. It is important to note that this study utilizes Zastempowski’s definition rather than a specific innovation capability model, distinguishing it from frameworks focused on individual innovative behaviors. While models such as the Innovator’s DNA (Dyer, Gregersen, & Christensen, 2008, 2011) and Innovative Work Behavior (Scott & Bruce, 1998; Janssen, 2000; De Jong & Den Hartog, 2010) offer valuable insights into individual-level innovation processes, they primarily address the behavioral and cognitive mechanisms underlying innovation rather than the broader organizational capability to foster and sustain innovation. Moreover, recent approaches integrating personality traits with configurational methodologies, such as fsQCA (De Haro & Vena, 2025), emphasize micro-level determinants rather than the structural and systemic aspects of innovation capability that are central to this study.

Given that most scholars concur that innovation capability comprises multiple distinct elements primarily related to the internal characteristics of organizations – including (1) absorptive capacity and external knowledge, (2) organizational structures and culture, (3) leadership and communication, (4) individual creativity and innovativeness, and (5) organizational learning culture (Cohen & Levinthal, 1990; Guan & Ma, 2003; Yam, Guan, Pun, & Tang, 2004, 2010; Kianto, 2008; Martínez-Román et al., 2011; Konsti-Laakso, Pihkala, & Kraus, 2012) – this study employs Forsman (2011) framework, which comprises seven dimensions. I chose this categorization because it offers a comprehensive representation of the key aspects of innovation capability at the organizational level, while still allowing for the examination of how individual-level characteristics, such as entrepreneurial personality traits, influence a firm’s innovation potential.

Prior research across various fields has indicated that stable personality characteristics can serve as indicators for individuals who exhibit creative (Feist, 1998; Abdullah et al., 2016; Faullant, Holzmann, & Schwarz, 2016; Waheed & Dastgeer, 2019; Jirásek & Sudzina, 2020) and innovative behaviors (Ahmed, 1998; Abdullah et al., 2019; Waheed & Dastgeer, 2019; Ali, 2019; Saatci & Ovaci, 2020; Mustafa, Coetzer, Ramos, & Fuhrer, 2021). However, findings remain inconclusive (Jirásek & Sudzina, 2020), prompting Mendoza-Silva (2021) to call for further investigation into the influence of personality traits on innovation capability, emphasizing a significant research gap in this area.

Building on this, I extended the inquiry one step further by examining whether a relationship exists between personality facets and innovation capability. A review of the existing literature revealed a lack of studies addressing this specific relationship. Therefore, the subsequent discussion explores potential associations at a broader level of analysis, focusing on personality traits rather than facets. Building upon this analysis, I endeavored to formulate hypotheses concerning the potential relationship between the specific facets of personality traits and innovation capacity.

Concerning the first personality trait, i.e. openness to experience, prior research suggests its positive influence on various dimensions of innovativeness. Empirical evidence supports its beneficial impact on the innovativeness of engineers (Azami & Kaikhavani, 2017), students (Ali, 2019), and employees (Saatci & Ovaci, 2020), as well as on innovative work behavior (George & Zhou, 2001; Munir & Beh, 2016; Abdullah et al., 2019; Som & Suradi, 2019) and entrepreneurial intention (Li et al., 2022). Furthermore, scholars have associated openness to experience with heightened creativity (Zare & Flinchbaugh, 2019; Li et al., 2022), individual exploratory activities (Park & Kim, 2021), and the adoption of innovative problem-solving strategies (Javed, Khan, Arjoon, Mashkoor, & Haque, 2020; Jirásek & Sudzina, 2020; Abu Raya et al., 2023). Moreover, the literature links it to improved innovation performance (Hsieh, Hsieh, & Wang, 2011; Vo et al., 2024) and self-selection into Doing-Using-Interacting-based innovation within less R&D-intensive small and medium-sized enterprises (Runst & Thomä, 2022). At a macro level, scholars have also associated it with national innovation levels.

Consequently, I proposed the first two hypotheses regarding the specific facets of openness to experience:

The existing literature further substantiates the notion that conscientiousness positively correlates with various dimensions of innovation. Empirical studies highlight its beneficial impact on engineers’ innovativeness (Azami & Kaikhavani, 2017), as well as creativity (Zare & Flinchbaugh, 2019; Jirásek & Sudzina, 2020; Li et al., 2022). Moreover, scholars have linked conscientiousness to individual innovativeness among students (Ali, 2019), employees (Saatci & Ovaci, 2020), and professionals working in health organizations (Thajil & AL-Abrrow, 2024).

Moreover, research suggests that conscientiousness positively influences innovative work behavior (George & Zhou, 2001; Munir & Beh, 2016; Lee, 2017; Som & Suradi, 2019), contributes to the success of teams in radically new products (Aronson, Reilly, & Lynn, 2008), and supports the longevity of entrepreneurial ventures (Ciavarella, Buchholtz, Riordan, Gatewood, & Stokes, 2004). Furthermore, the literature associates it with enhanced innovation performance (Hsieh et al., 2011), greater entrepreneurial intention (Li et al., 2022), and engagement in high-level exploitation activities (Park & Kim, 2021). However, some studies suggest that conscientiousness may exhibit negative associations with creativity and originality (Abdullah et al., 2016; Patterson & Zibarras, 2017; Jirásek & Sudzina, 2020).

Despite these mixed findings, the prevailing body of research predominantly highlights the positive relationship between conscientiousness and innovation. Accordingly, the present study aligns with the perspective that conscientiousness, particularly its facets of discipline and order, provides a stable foundation for enhancing innovation capability. Consequently, I proposed the following hypotheses regarding the specific facets of conscientiousness:

Furthermore, the literature provides substantial evidence of the relationship between extraversion and individual innovativeness. Empirical research suggests that extroversion is positively associated with creativity (Abdullah et al., 2016; Zare & Flinchbaugh, 2019; Jirásek & Sudzina, 2020; Li et al., 2022), the innovativeness of engineers (Azami & Kaikhavani, 2017), and individual innovativeness among students (Ali, 2019). Moreover, the literature links extraversion to innovation competencies (Saatci & Ovaci, 2020), individual work behavior (Duradoni & Di Fabio, 2019; De Haro & Vena, 2025), and innovation performance (Hsieh et al., 2011; Vo et al., 2024). Scholars have identified further associations with self-selection into Doing-Using-Interacting-based innovation (Runst & Thomä, 2022), the development of innovative knowledge assets in organizations (Yovav & Harpaz, 2021), and entrepreneurial intentions (Li et al., 2022).

Considering the above, I proposed two additional hypotheses related to facets of extraversion:

In the case of the fourth FFM trait – agreeableness – existing research has provided mixed evidence regarding its relationship with innovation. Several studies suggest a positive connection between agreeableness and workplace behaviors conducive to innovation (Munir & Beh, 2016; Rahman, Rosidah, Faizah, & Hamidah, 2023; Vo et al., 2024), individual innovativeness among students (Ali, 2019), technological innovation (Hsieh et al., 2011), and innovation at the national level. Furthermore, the literature associates agreeableness with increased innovativeness through knowledge sharing (Vo et al., 2024). However, conflicting evidence exists regarding its impact on innovative work behavior, with some studies reporting no significant relationship (Munir & Beh, 2016).

A more nuanced perspective suggests that agreeableness may exert both positive and negative influences on innovation. While high levels of agreeableness can facilitate cooperative behaviors and knowledge exchange, they may simultaneously reduce the propensity for independent creative thinking and risk-taking, which are critical components of innovation. Abdullah et al. (2016) argue that heightened Agreeableness is linked to decreased creativity, possibly due to a tendency to conform to group norms rather than challenge existing ideas. Similarly, Patterson, Kerrin, and Gatto-Roissard (2009) highlight the ambiguous role of agreeableness in innovative behavior, suggesting that while it can foster collaboration, it may also discourage individuals from engaging in disruptive innovation or challenging the status quo.

The association between agreeableness and entrepreneurship also remains inconclusive. Some meta-analytical studies indicate that entrepreneurs tend to score lower on agreeableness than managers (Hao et al., 2010), which may be attributed to the competitive and risk-oriented nature of entrepreneurial environments. Highly agreeable individuals might struggle with assertiveness, negotiation, and strategic decision-making, all of which are crucial for entrepreneurial success. Leutner et al. (2014) further reinforce this perspective, finding that lower agreeableness correlates with greater entrepreneurial success, likely because it reduces tendencies toward conflict avoidance and excessive deference to others.

These conflicting findings suggest that different facets of agreeableness may play distinct roles in innovation. Altruism, a prosocial aspect of agreeableness, may enhance innovation capability by fostering collaboration and collective problem-solving. Conversely, compliance, which reflects a tendency to adhere to norms and avoid conflict, may have a more complex relationship with innovation, potentially encouraging cooperation while simultaneously inhibiting risk-taking and unconventional thinking.

Based on these insights, I formulated the following hypotheses related to the specific facets of agreeableness:

In turn, in the case of neuroticism, prior research has consistently demonstrated an inverse relationship with various dimensions of innovation. Empirical studies indicate that neuroticism is negatively associated with innovation skills (Li et al., 2022; Rahman et al., 2023), user innovation engagement (Zhou & Tang, 2023), the innovativeness of engineers (Azami & Kaikhavani, 2017), and individual innovativeness among students (Ali, 2019). Furthermore, scholars linked neuroticism to reduced creativity (Abdullah et al., 2016), lower effectiveness in radical and incremental new product development teams (Aronson et al., 2008), and diminished innovative performance (Rodrigues & Rebelo, 2019; Rahman et al., 2023). Moreover, research suggests that neuroticism decreases the likelihood of self-selection into Doing-Using-Interacting-based innovation (Runst & Thomä, 2022) and negatively correlates with entrepreneurial intentions (Li et al., 2022).

Building upon these findings, I formulated the following hypotheses related to the specific facets of neuroticism:

I collected the microdata underlying the presented analyses during the third and fourth quarters of 2022. The target population comprised self-employed individuals in Poland who were officially registered in the National Official Register of Economic Entities (NOREE). As of the fourth quarter of 2022, this population totaled 3,134,000. I drew a representative sample using stratified sampling, wherein I delineated strata based on the type of activity, administrative region, and legal form, as classified by Statistics Poland.

The initial sample consisted of 550 observations, ensuring a 98% confidence level with a maximum margin of error of ±3%, assuming a fraction size of 0.1. Moreover, I generated a reserve sample from the same sampling frame, maintaining an identical stratification scheme. This reserve sample was 19 times larger than the original sample, meaning that for each randomly selected primary record that met the inclusion criteria, I secured 19 additional corresponding records in the reserve sample. If a respondent from the primary sample declined to participate, I interviewed one of the corresponding entities from the reserve sample.

In total, I randomly drew 11,000 records, encompassing both primary and reserve samples. I collected data using the Computer-Assisted Telephone Interviewing (CATI) method. To mitigate the effect of socially desirable responses, I implemented the anonymity and confidentiality method, ensuring that respondents’ answers remained anonymous. This approach intended to minimize the pressure to align responses with prevailing social norms. The final dataset comprised 524 valid responses from self-employed individuals, enabling statistical inference with a maximum margin of error of ±3% at a 98% confidence level, assuming a fraction size of 0.1. Table 1 presents the characteristics of the surveyed self-employed micro-entrepreneurs.

I measured the dependent variable, i.e. innovation capability, on Forsman’s (2011) framework, which conceptualizes this construct as comprising the following seven dimensions: (1) knowledge exploitation, (2) entrepreneurial capabilities, (3) risk management capabilities, (4) networking capabilities, (5) development capabilities, (6) change management capabilities, and (7) market and customer knowledge. Following established recommendations, I evaluated the degree of innovation capability using a three-point ordinal scale: 1 = low, 2 = moderate, and 3 = high. I subsequently computed the mean value to derive the final measurement of the innovation capability variable. Notably, the original variable was ordinal and discrete. However, we may regard the newly derived variable – the mean calculated across a large number of observations – as continuous, as it assumes a wide range of values and its distribution may approximate that of a continuous variable. In applied research, scholars typically consider such a variable quasi-continuous (Johnson & Wichern, 2018).

In terms of independent variables, the assessment of personality traits among the self-employed was based on the Big Five Inventory, developed by John and Srivastava (1999), which comprises 44 items rated on a five-point Likert scale. To capture more specific personality facets, I adopted the framework proposed by Soto and John (2009), utilizing 35 of the 44 statements from John and Srivastava’s (1999) original inventory.

While more comprehensive instruments such as the Revised NEO Personality Inventory (NEO-PI-R; Costa & McCrae, 2008) or the Big Five Aspect Scales (BFAS; DeYoung, Quilty, & Peterson, 2007) are available, I decided to employ the BFI-44 because of several key considerations. First, the BFI-44 is a well-validated and extensively utilized instrument in personality research. It offers robust psychometric properties while maintaining a pragmatic length for survey-based studies. This was particularly pertinent given the constraints of our study design, which necessitated a careful balance between comprehensiveness and respondent burden.

Second, although the BFI-44 does not afford the same degree of granularity as the NEO-PI-R or BFAS, prior research (Soto & John, 2009) has demonstrated that it effectively captures meaningful distinctions at the facet level when appropriately analyzed. The adoption of facet-level measures derived from the BFI-44 aligns with the overarching objective of this study, which prioritizes the examination of specific personality aspects rather than merely the broad five-factor framework.

To facilitate a more nuanced assessment of personality traits, I categorized the selected items into ten distinct facets, each reflecting a finer-grained aspect of the FFM dimensions. I coded these facets as follows (with “R” denoting reverse-scored items):

1. Aesthetics within openness to experience – items 30, 41R, 44

2. Ideas within openness to experience – items 10, 15, 25, 35R, 40

3. Order within conscientiousness – items 8R, 18R

4. Self-discipline within conscientiousness – items 13, 23R, 28, 38, 43R

5. Assertiveness within extroversion – items 1, 6R, 21R, 26, 31R

6. Activity within extroversion – items 11, 16

7. Altruism within agreeableness – items 7, 22, 27R, 32

8. Compliance within agreeableness – items 2R, 12R, 17

9. Anxiety within neuroticism – items 9R, 19, 34R, 39

10. Depression within neuroticism – items 4, 29

Furthermore, I incorporated one control variable, namely Age, measured by the number of years since the establishment of the enterprise. This variable was numerical and I applied logarithmic transformations for analytical purposes.

I employed an ordinary least squares (OLS) regression model (Wiśniewski, 2015) to examine the impact of personality facets on innovation capability. I performed all the computations using Stata 16.1.

Table 2 presents descriptive statistics for the studied variables.

To evaluate the potential occurrence of common method bias (CMB), I utilized Harman’s single-factor examination (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003), encompassing the OCEAN personality traits and innovation capability variables examined in this study. The findings indicated that the exploratory single-factor model accounted for 23.615% of the variance, suggesting that CMB was not a concern.

Subsequently, I assessed the adequacy of the sample using the Kaiser–Meyer–Olkin (KMO) measure and Bartlett’s test of sphericity (Cureton & D’Agostino, 2013). The KMO returned a value of 0.811, while Bartlett’s test of sphericity (χ² = 38,033.764; df = 1953) demonstrated statistical significance at p < 0.001, confirming the reliability of the measurement scale. Cronbach’s alpha coefficients provided further validation as presented in Table 2.

The insights derived from the correlation coefficients in Table 3 highlight several key findings. First, I observed significant statistical relationships between the dependent and independent variables. However, the coefficients for the components of the OCEAN personality traits consistently remained below 0.323, indicating a weak degree of interconnection. Second, certain correlation coefficients among the facets of self-employed micro-entrepreneurs' personality traits exceed 0.5. This is unsurprising, as they represent different facets of the same FFM trait, thereby exhibiting expected correlation. Nevertheless, an examination of variance inflation factors (VIF) revealed values below 5 (mean VIF = 3.61), suggesting moderate correlation among the variables and a low probability of multicollinearity.

To examine the presence of heteroskedasticity, I conducted the Breusch-Pagan/Cook-Weisberg test, which assesses the assumption of homoskedasticity in ordinary least squares (OLS) regression models (Breusch & Pagan, 1979; Cook & Weisberg, 1983). The test yielded a chi-square statistic of 8.83 with one degree of freedom, and a corresponding p-value of 0.0030, indicating statistical significance at the 1% level. Consequently, I rejected the null hypothesis of homoskedasticity, confirming the presence of heteroskedasticity in the model residuals. Given that heteroskedasticity violates a key assumption of OLS, potentially leading to inefficient estimates and biased inference, I implemented heteroskedasticity-robust standard errors (HC3 covariance matrix estimation) to mitigate its effects (MacKinnon & White, 1985). This approach ensures that statistical inferences remain valid despite the detected variance irregularities, enhancing the robustness of the estimated coefficients.

The results of the OLS model with heteroskedasticity-robust standard errors, presented in Table 4, indicate that only three personality facets were significantly related to innovation capability. These are aesthetics and ideas associated with openness to experiences, and assertiveness related to extroversion. All three facets exerted a positive impact on the innovation capability of the self-employed micro-entrepreneurs. These findings support hypotheses H1 and H2 (p ≤ 0.01) as well as H5 (p ≤ 0.05). In contrast, the remaining hypotheses – H3, H4, and H6, H7, H8, H9, H10 – were not supported, and I consequently rejected them.

To further validate the robustness of our findings, I employed a bootstrapping approach with 1,000 replications as a means of assessing the stability of our regression estimates. Bootstrapping provides a non-parametric resampling method that enhances inference reliability, particularly in the presence of heteroskedasticity or potential model misspecifications (Efron & Tibshirani, 1994). This technique allows for the estimation of standard errors and confidence intervals without relying on traditional parametric assumptions. As presented in Table 5, the bootstrapped estimates closely align with those obtained from the heteroskedasticity-robust OLS model (Table 3), indicating that the key relationships identified remain statistically robust. The significance levels of the relevant predictors – aesthetics, ideas, and assertiveness – were consistent across both estimation methods, reinforcing the validity of hypotheses H1, H2, and H5. These results confirmed that my primary conclusions were not driven by idiosyncratic sample variations, thus strengthening the overall findings’ reliability.

Referring to the research question and hypotheses, the obtained results present intriguing insights and provoke further reflection.

The findings indicate that, for self-employed micro-entrepreneurs, two examined facets of the openness to experience trait—namely, aesthetics and ideas— positively influence their innovation capability. When assessing the impact of primary personality dimensions, represented by the OCEAN model, on various aspects of innovation, these outcomes align with and reinforce previous studies (Ahmed, 1998; Abdullah et al., 2019; Ali, 2019; Waheed & Dastgeer, 2019; Saatci & Ovaci, 2020; Mustafa et al., 2021).

However, my research advances this understanding by specifically examining detailed personality facets (Soto & John, 2009) alongside a clearly defined concept of innovation capability (Forsman, 2011). From this viewpoint, the presented results contribute more granular empirical evidence.

First, the data robustly supports the significant and positive role of aesthetics in fostering innovation capabilities among self-employed micro-entrepreneurs. Noteworthy, the aesthetics facet pertains to the human relationship with art, culture, and beauty, as well as openness to new experiences involving creative and artistic endeavors (Soto & John, 2009; Jirásek & Sudzina, 2020). Scholars frequently link openness to imagination, creativity, and an eagerness to explore novel ideas and experiences (Stock et al., 2016; Zhao & Seibert, 2006). Specifically, the aesthetic aspect of openness captures an individual’s engagement with artistic and creative expression across various media, such as visual arts, music, literature, and other forms of creativity.

In the context of the innovation capabilities of self-employed micro-entrepreneurs, the aesthetic aspect of openness may yield multiple benefits. Micro-entrepreneurs who highly value aesthetics often excel at generating innovative ideas, as their acute sensitivity to beauty and artistic expression facilitates the development of distinctive products and services that distinguish themselves in a competitive market. These individuals may demonstrate greater effectiveness in brand creation, translating into visually appealing products and strong brand identities, thereby attracting customers and enhancing memorable customer experiences. Moreover, heightened aesthetic awareness can result in a greater emphasis on user-centric product design. Micro-entrepreneurs attuned to Aesthetics prioritize the overall user experience and strive to offer products that are not merely functional but aesthetically appealing and emotionally resonant. Furthermore, Aesthetic sensitivity can encourage interdisciplinary cooperation involving artists, cultural professionals, designers, and other creatives, leading to the emergence of innovative and visually compelling products.

Second, the findings demonstrate that as a facet of openness to experience, ideas positively influence the innovation capability of self-employed micro-entrepreneurs. Aligning with Kaufman et al.’s (2016) perspective, it is noteworthy that individuals with high ingenuity typically exhibit a greater propensity for generating original ideas and adopting innovative approaches to solving problems. Their ability to think abstractly and their cognitive flexibility also allow them to combine diverse concepts and perspectives creatively. Regarding the innovation capabilities of self-employed micro-entrepreneurs, pronounced ideas may manifest in various attitudes or abilities. Foremost among these is the capability to generate innovative concepts. Micro-entrepreneurs exhibiting high levels of ingenuity are more likely to conceive novel product or service ideas. Their aptitude for integrating diverse ideas and engaging in unconventional thinking — “outside the box” – can facilitate the development of unique solutions that can differentiate them within a competitive market. Moreover, ideas foster adaptability to change. Highly imaginative individuals typically demonstrate greater flexibility and openness to change. In a dynamic business environment where change is inevitable, micro-entrepreneurs can leverage their inventive capabilities to swiftly adapt and respond to evolving market demands, thus producing innovative outcomes. Third, a creative approach to problem-solving is essential. Elevated ingenuity empowers micro-entrepreneurs to approach challenges with unconventional perspectives and explore innovative solutions. Rather than adhering strictly to traditional methodologies, these entrepreneurs may experiment with diverse strategies, discovering novel solutions capable of achieving market success. Finally, innovative ideas can significantly enhance a micro-entrepreneur’s ability to establish a distinctive brand identity and effectively differentiate themselves within a competitive market. Products or services resulting from creative ideas are likely to attract customer attention and cultivate enduring brand loyalty.

Third, let me highlight an additional conclusion from the presented research. Assertiveness – one facet of the extroversion trait – has been demonstrated to positively influence the innovation capability of self-employed micro-entrepreneurs. We may contextualize this finding within the existing literature (Abdullah et al., 2019; Ahmed, 1998; Ali, 2019; Waheed & Dastgeer, 2019; Saatci & Ovaci, 2020; Mustafa et al., 2021), which suggests that, akin to openness, extroversion generally positively influences various dimensions of innovation. Nonetheless, the study revealed that only the Assertiveness facet significantly contributes to innovation capability, whereas the other examined facet, activity, did not yield statistically significant results.

Assertiveness refers to the tendency of individuals with extroverted personalities to communicate and interact confidently, directly, and proactively, demonstrating enthusiasm and energy in social interactions (Soto & John, 2009; Jirásek & Sudzina, 2020). Within the context of self-employed micro-entrepreneurs, we may identify several activities where assertiveness positively influences innovation capability. First, assertiveness significantly facilitates ideas’ promotion and presentation. Assertive micro-entrepreneurs are likely more proactive in promoting and articulating their innovative concepts to diverse stakeholders, including potential investors, customers, and collaborators (Babcock & Wilson, 2020). Second, assertiveness enhances collaborative engagement. Micro-entrepreneurs exhibiting assertive traits tend to initiate and actively participate in partnerships and collaborations, promoting the exchange of ideas – or “cross-pollination of ideas” – a critical element in fostering innovation (Dyer, Gregersen, & Christensen, 2011). Third, assertiveness is advantageous in overcoming challenges. Individuals with assertive personalities generally confront challenges directly (Rashid et al., 2020; Ceccarini & Andreani, 2022), which for micro-entrepreneurs translates into effectively managing and resolving obstacles encountered during the development and implementation of innovative solutions. Finally, assertiveness equips micro-entrepreneurs to manage rejection effectively. Assertive individuals typically demonstrate greater resilience in coping with rejection and failure, both inherent aspects of the innovation process.

Fourth, the present study did not confirm a significant impact of either examined facet of conscientiousness – order or self-discipline – on the innovation capability of self-employed micro-entrepreneurs. This finding stands in contrast to prior research, which has frequently highlighted a positive association between conscientiousness and various forms of innovativeness, including creativity (Zare & Flinchbaugh, 2019; Li et al., 2022) and innovative work behavior (George & Zhou, 2001; Munir & Beh, 2016).

Several interpretations may account for this discrepancy. First, conscientiousness – particularly in the context of micro-entrepreneurship – may support operational efficiency and stability, but does not necessarily foster risk-taking, exploratory thinking, or deviation from established routines, all of which are essential for innovation development. Second, these facets may exert a more substantial influence in more complex organizational settings, where structure and planning contribute directly to innovation implementation. In contrast, self-employed micro-entrepreneurs often operate in highly uncertain environments that require adaptability and improvisation, where excessive emphasis on order and discipline may, paradoxically, hinder innovative responses to dynamic market conditions.

Moreover, these findings may suggest that for self-employed individuals, it is not meticulous planning or procedural rigor, but rather cognitive flexibility, imaginative thinking, and the confident articulation of novel ideas – traits more closely associated with openness to experience and extraversion – that are more instrumental in enhancing innovation capability. Thus, while conscientiousness may be beneficial for long-term task execution and organizational control, it does not appear to play a decisive role in fostering innovation within the inherently fluid and informal context of solo entrepreneurship.

Fifth, an additional unexpected result of the present study lies in the lack of a statistically significant relationship between either of the two investigated facets of agreeableness – altruism and compliance – and the innovation capability of self-employed micro-entrepreneurs. This outcome stands in contrast to prior findings in the literature, which suggest a nuanced, bidirectional influence of these facets on innovative behaviors. Specifically, scholars often link altruism with enhanced collaboration and knowledge sharing – factors believed to support innovation – and consider compliance potentially detrimental due to its association with conformity and risk aversion (Patterson et al., 2009; Zhao & Smillie, 2015; Vo et al., 2024).

We may interpret the absence of such effects in the current study in light of the specific characteristics of micro-entrepreneurship. In solo business settings, where innovation processes are often individualized and driven by personal initiative rather than group dynamics, the interpersonal benefits associated with altruistic behavior may be less central to innovation outcomes. Unlike in larger organizational environments, where team-based collaboration and empathy-driven leadership can significantly affect knowledge flows and idea generation, self-employed entrepreneurs may rely more heavily on individual resourcefulness and creativity than on prosocial orientation.

Similarly, the non-significant influence of compliance suggests that, within the context of self-employment, a tendency to avoid conflict or adhere to social norms may neither facilitate nor inhibit innovation in a meaningful way. While prior research hypothesized that high compliance may limit disruptive thinking or challenge the status quo (Abdullah et al., 2016; Patterson & Zibarras, 2017), it is possible that in micro-enterprises, the absence of hierarchical structures and peer conformity pressures that typically characterize larger organizations neutralize such tendencies. Moreover, micro-entrepreneurs are frequently required to adapt to a wide range of external conditions, and innovation may be driven more by necessity and flexibility than by personality-based predispositions toward social harmony or deference.

These findings underscore the importance of contextualizing personality–innovation relationships within specific entrepreneurial environments. They suggest that in the case of solo ventures, innovation capability may depend less on interpersonal or cooperative tendencies and more on traits directly connected with cognitive exploration and expressive assertiveness, such as those identified under openness to experience and extraversion.

Finally, another noteworthy finding emerging from this study is the lack of a statistically significant relationship between either facet of neuroticism – anxiety and depression – and the innovation capability of self-employed micro-entrepreneurs. This result contrasts with the prevailing consensus in prior literature, where scholars typically identified neuroticism as a negative predictor of innovation-related outcomes, including creativity, individual innovativeness, and innovation performance (Rodrigues & Rebelo, 2019; Li et al., 2022; Rahman et al., 2023). Scholars view both anxiety, associated with heightened worry and stress sensitivity, and depression, linked to low energy and reduced motivation, as inhibitors of innovative behaviors, particularly in dynamic or high-pressure environments (Zhang, 2020; Montag et al., 2022).

The absence of such effects in the present study may suggest that the mechanisms through which neurotic tendencies impair innovation are less salient in the context of solo entrepreneurship. By definition, micro-entrepreneurs operate outside conventional organizational structures and are often responsible for setting their own pace, objectives, and working conditions. This autonomy may buffer the potential negative effects of emotional instability by allowing individuals to manage stressors more flexibly, avoid triggering environments, or adopt coping strategies suited to their psychological disposition.

Moreover, the nature of innovation among self-employed individuals may differ substantially from that in corporate or team-based settings. While elevated neuroticism may undermine performance in collaborative innovation processes – due to communication difficulties, fear of evaluation, or emotional volatility – it may have less impact when innovation efforts are self-directed and intrinsically motivated. In such cases, even individuals with high levels of anxiety or depressive tendencies may develop creative or adaptive solutions, particularly if they are motivated by necessity or have cultivated resilience through entrepreneurial experience.

These findings suggest that the influence of neurotic traits on innovation may be context-dependent and moderated by factors such as autonomy, perceived control, and coping resources. Consequently, we should not assume personality–innovation relationships to operate uniformly across all entrepreneurial environments. Instead, they require careful interpretation with regard to the structure, demands, and psychological climate of the business context in which innovation takes place.

Summarizing the considerations presented, let us revisit the research question: Is there a relationship between the personality facets of self-employed micro-entrepreneurs and their innovation capabilities? The answer is not entirely straightforward.

First, the personality of self-employed micro-entrepreneurs, perceived from the perspective of their facets, plays a significant role in building their innovation capabilities. Second, only three aspects of personality traits, namely aesthetics and ideas associated with openness to experience, as well as assertiveness, a facet of extraversion, positively influence innovation capability. Third, the remaining analyzed facets did not prove to be statistically significant.

Noteworthy, the presented research results have both theoretical and practical implications.

From a theoretical perspective, by identifying that specific personality facets – such as aesthetics, ideas, and assertiveness – can influence the innovation capability of self-employed micro-entrepreneurs, the findings enrich our understanding of innovativeness in the context of individual traits. These results are grounded in trait theory, particularly the FFM (McCrae & Costa, 1987), which posits that stable personality characteristics have a predictive effect on individual behavior across various situations. However, this study went a step further by focusing not on the broad dimensions but rather on personality facets (Soto & John, 2009), allowing for a more nuanced grasp of the psychological mechanisms that underlie innovative potential.

The positive impact of facets such as aesthetics (reflecting sensitivity to art and beauty) and ideas (linked to intellectual openness and creative thinking) highlights the close association between openness to experience and the capacity to generate and implement novel solutions – consistent with prior research (George & Zhou, 2001; Kaufman et al., 2016). At the same time, these findings align with theories conceptualizing innovativeness as a cognitive and emotional disposition, echoing the notion of the innovative personality (Feist, 1998), which integrates traits like creativity, openness, and independent thinking.

We may also interpret the confirmation of assertiveness – a facet of extraversion – as a contributor to innovation capability through the lens of the Resource-Based View (Barney, 1991), which treats personal traits such as communication skills, proactiveness, and self-confidence as intangible assets that contribute to competitive advantage. As a marker of interpersonal strength and a willingness to express one’s ideas, assertiveness may support innovation not only by enhancing collaboration but also by facilitating the implementation of change and convincing others to embrace new solutions (Ceccarini & Andreani, 2022).

As such, this study not only fills an empirical gap regarding micro-entrepreneurs – a group often overlooked in innovation research (Roper & Hewitt-Dundas, 2017; Audretsch et al., 2020) – but also expands theoretical frameworks of innovation by introducing a micro-psychological level of analysis. Simultaneously, it opens new avenues for future research by highlighting the need to further explore the role of personality facets across different stages of the innovation process (e.g. idea generation, implementation, scaling) and within alternative personality models (e.g. HEXACO – Ashton, Lee, & de Vries, 2014). This can lead to a more refined understanding of how psychological predispositions shape individuals’ capacity to adapt and create value in dynamic market environments.

In practical terms, the obtained results can help improve various activities in micro-enterprises. Let me mention some socio-economic recommendations.

In terms of developing aesthetics, it is worth (1) stimulating artistic and cultural education through courses, workshops, reading books, and visiting art galleries, or participating in structured training modules on visual storytelling, product design, or branding aesthetics designed for entrepreneurs, (2) actively seeking inspiration by studying other projects, styles, and trends in various fields, and (3) deepening visual practice, e.g. by developing drawing, painting, photography, or other forms of visual art. Entrepreneurial incubators or accelerators may also consider including “creative mindset” labs as part of their development offerings.

In the area of ideas, we should pay attention to (1) developing creative thinking, e.g. through exercises such as freewriting, mind mapping, or attempts to solve problems from unusual perspectives; (2) continuously expanding horizons, i.e. various sources of inspiration – e.g. through travel, reading various books, exploring different fields of art and culture, and (3) experimenting. Dedicated innovation bootcamps, interdisciplinary hackathons, and ideation workshops tailored for solo entrepreneurs may significantly support this dimension. Coaching programs focused on cultivating divergent thinking and “design sprints” can also be effective.

Finally, regarding assertiveness, suggestions include (1) developing communication skills, (2) assertiveness training, e.g. by participating in workshops or training sessions where you can practice assertive communication techniques, and (3) building self-confidence, including celebrating successes, positive thinking, and constructively dealing with criticism. Mentorship programs pairing entrepreneurs with experienced business leaders can reinforce assertive behaviors in real business contexts. Moreover, role-playing sessions and entrepreneurial leadership simulations may enhance both verbal and non-verbal assertiveness in pitching and negotiation scenarios.

All of the suggested practical implications are strongly related to the development of neuroplasticity and cognitive skills (Draganski et al., 2004; Diamond, 2013).

Finally, the conducted research has certain limitations. First, I analyzed the personality aspects of self-employed micro-entrepreneurs based on the FFM concept, which is not the only one. Therefore, regarding the possible directions for future research, scholars may indicate whether personality aspects of micro-entrepreneurs analyzed using, for example, the Myers-Briggs Type Indicator (MBTI) (Myers, McCaulley, & Most, 1985) or the HEXACO model (Ashton et al., 2014), will also point to the importance of similar personality aspects. Second, the research results are also geographically limited, and the formulated conclusions may only concern self-employed micro-entrepreneurs in Poland. Therefore, it is worth expanding the research to other countries with different cultures and levels of economic development. Third, as with all cross-sectional studies, the design limits the ability to draw causal conclusions from the observed associations. Future research using longitudinal or experimental designs may help establish more definitive causal links between personality traits and innovation capability. Fourthly, I measured all variables using self-report instruments. While I employed validated tools and took steps to reduce common method bias (e.g. Harman’s single-factor test indicated no serious threat), such methods inherently carry the risk of response biases. Lastly, although the reliability of most scales used was acceptable to high (Cronbach’s α between 0.717 and 0.925), one subscale (Order, α = 0.690) approached the lower threshold of internal consistency. Readers should consider this aspect when interpreting results related to this dimension.

In this research, I examined a group of micro-entrepreneurs. Since the survey questions were addressed to managers, the study involved human participants. They were informed that the survey was anonymous, and I analysed the data anonymously without collecting any personal information. Therefore, in accordance with the recommendations of the National Science Centre (https://www.ncn.gov.pl/sites/default/files/pliki/2016_zalecenia_Rady_NCN_dot_etyki_badan.pdf), which form the basis for research guidelines at my University (https://www.wf.cm.umk.pl/panel/wp-content/uploads/1_UCHW-SENAT-2017-179-za%C5%82.pdf), this study did not require ethics committee approval.