This study examines entrepreneurs' subjective well-being (SWB) in the form of life satisfaction. It presents a multilevel analysis approach explaining the relationship between individual-level variables (demographics and developed personal characteristics), country-level institutional variables (political stability, corruption perception index, paying tax regulations, and business freedom), and entrepreneurs' SWB. The multilevel mixed-effects logistic regression analysis is used to test the econometric model with data from the Life in Transition Survey III for 34 countries. Findings show that both individual and governing factors play a significant role in shaping entrepreneurs' SWB. The individual-level variables such as job satisfaction, financial situation, generalized trust, optimism, and social standing are the most critical factors driving self-employed life satisfaction. On the institutional level, business freedom and political stability are the most instrumental, followed by the corruption perception index and paying tax regulatory. Overall, this research enhances comprehension regarding SWB within the entrepreneurship domain, yielding significant implications for entrepreneurship theory and practice within the well-being framework, along with providing pertinent recommendations for policymakers.
Entrepreneurship is the key driving force to societal wealth, job creation, innovation, and economic growth.1 Beyond contribution to economic development, entrepreneurship has the potential to tackle some of the most critical global sustainability concerns, such as social injustice, environmental pollution, and climate change (Global Entrepreneurship Monitor, 2018). Entrepreneurship is described as an individual's ability to put ideas into actual activities (Sánchez-García, Vargas-Morúa, & Hernández-Sánchez, 2018), and is held in high esteem by individuals for the fact of self-determination and autonomy it provides. People's motivation to enter entrepreneurship is known to be fueled by both extrinsic (such as financial aspect, power, and social standing) and intrinsic rewards (such as job satisfaction, self-fulfillment, and life meaning) (Sherman, Randall, & Kauanui, 2016). In particular, "being your own boss" is highly appealing and offers a fulfilling experience (Stephan et al., 2020). However, the path to entrepreneurial success is not a straight line. Entrepreneurs frequently face stressful situations in the course of their business endeavors, characterized by uncertainties, rapid developments, and excessive workload (Baron, Franklin, & Hmieleski, 2013), all while simultaneously balancing their psychological well-being (Sherman et al., 2016). Consequently, it is widely presumed that entrepreneurs often experience profound negative emotions, which can adversely affect their overall well-being.
The integral role of well-being in entrepreneurship holds such significance that its absence can precipitate burnout (decision to end entrepreneurial pursuit due to emotional distress) and affect business existence. Due to the significance of entrepreneurial well-being, researchers have become increasingly interested in the "economics of happiness," as evidenced by the growing number of scientific articles that consider SWB (e.g. Binder & Coad, 2013; Brieger et al., 2021; Kara & Petrescu, 2018; Stephan, 2018). Although research on SWB and its determinants has received substantial attention in recent years, it has, however, received comparatively less attention in the context of entrepreneurs than that of society at large (Johansson Sevä et al., 2016; Kara & Petrescu, 2018). In particular, there has been a rise in interest in studying the variations in SWB between salaried workers and the self-employed (e.g. Korankye & Lartey, 2022; Mahadea & Ramroop, 2015; Millán, Hessels, Thurik, & Aguado, 2013), however, research has only marginally delved into a more in-depth examination of SWB among entrepreneurs. Hence, further study is required in this regard, as suggested by Weis et al. (2008), indicating that the understanding of the origins of this significant construct is just in its infancy. Given this context, using the latest data from the Life in Transition Survey (LiTS III) for 34 Eurasian countries, this research intends to evaluate the factors exerting potential influence on the SWB of the self-employed in the form of life satisfaction. While many factors can influence entrepreneurial well-being, the present study focuses mainly on investigating how individual-level variables such as perceived own financial satisfaction, perceived economic situation, job satisfaction, perceived social standing, generalized trust, optimism, self-assessed health, number of workers and demographic characteristics (age, gender, marital status, education), impact the entrepreneurs’ SWB.
Additionally, drawing on Institutional Theory (Frey & Stutzer, 2000), we expand the analysis of self-employed in the happiness literature and examine the role of institutional variables such as political stability, corruption, business freedom, and paying tax regulatory in determining self-employed SWB. We develop a multilevel model for data analysis to examine the relationships between individual and institutional factors and SWB. Combining individual and country-level variables, we explore which elements are more instrumental to SWB.
Despite the growing importance of entrepreneurial well-being, there is still a research gap examining the complex dynamics of this phenomenon. Our selection of variables is motivated by their fundamental importance in research on well-being and entrepreneurial experiences. As we recognize that individual-level factors greatly influence SWB among entrepreneurs, we also acknowledge that national-level institutions critically affect the entrepreneurial ecosystem and the welfare of entrepreneurs operating in various institutional contexts.
In addition, this study is guided by the imperative to address entrepreneur burnout by comprehending the factors that influence SWB. Given that burnout is a crucial factor that extinguishes the drive to persist and persevere, we stand by the rationale that recognizing and understanding its prevalence and impact on individual well-being can inform strategies for sustainable entrepreneurship. Since the analysis of SWB among entrepreneurs as a specific isolated topic has received less attention and the examination of institutional heterogeneity as a potential explanation for cross-country variations in SWB is also notably underrepresented, this would constitute the main contribution of the present study. The study uses an extensive data set on institutional-level variables, which presents its primary strength, ensuring the scientific soundness and relevance of our research. The diverse data set from multiple sources of country-level data allows for a more holistic rather than simplistic understanding of entrepreneurial settings and facilitates cross-country comparisons. It also lays the foundation for determining significant policy implications.
Furthermore, many existing studies have primarily focused on the objective dimension of well-being, denoted by GDP per capita or income level, or have used narrower measures for SWB. Therefore, when referring to SWB, we address this gap by measuring the overall quality of an individual's life. Additionally, this study involves a wide range of individual-level factors in its analysis. We consider that finding the main SWB drivers is the first step towards maximizing the SWB of entrepreneurs. Thereby, the anticipated outcome of this study is to significantly contribute towards providing pertinent parties, including entrepreneurial practice and institutional bodies, with effective entrepreneur well-being predictors.
LiteratureSubjective well-beingSWB (also regarded as happiness) is widely acknowledged as a critical aspect that plays a pivotal role in an individual's life. People from many cultures regard SWB as the most significant aspect of their lives and prioritize it over material achievement (Diener, 2000). In addition to promoting positive affect, well-being holds considerable value due to its manifold positive implications. For instance, higher income, enhanced work performance, organizational success, physical and mental health, and improved social interactions are all related to the higher well-being of individuals (see review by Diener, Oishi, & Tay, 2018; Diener & Seligman, 2004). Similarly, Lyubomirsky et al. (2005) suggest positive associations between happiness and success-producing behaviors. Happier people also exhibit greater resilience than unhappy individuals, who recover more rapidly from stress and bounce back faster from adverse events (Tugade & Fredrickson, 2004).
In many scientific fields, including economic study, SWB has been used to measure the evaluation of living conditions and pinpoint concerns, including variations in the quality of life, prosperity, and life satisfaction. In essence, SWB is a person's perception of and assessment of their life (Diener, 1984, 2009). Rath and Harter (2010) proposed that, in a broad sense, everything that is significant to our experiences and ways of thinking in life is included in our state of well-being.
For a long time, researchers have evaluated ways of predicting SWB. Numerous viewpoints have been used to approach well-being research, including the economic perspective (Amorós, Cristi, & Naudé, 2021; Brown, Gardner, Oswald, & Qian, 2008; Deci et al., 2001; Diener & Seligman, 2004). Although various ways to define well-being are often linked to the measurement tools employed, the most frequent explanations come from the hedonic and eudaimonic standpoint, representing a clash of opposing paradigms. The hedonic account of well-being is understood as well-being in terms of the presence of pleasure or pain avoidance or happiness; it holds the idea that subjective happiness is what constitutes well-being, incorporating all judgments about the positive and negative facets of life (Ryan & Deci, 2001). On the other hand, within the eudaimonic account discussed by Ryan & Deci (2001), subjective happiness is not deemed a fundamental component of well-being. Rather, guided by self-determination theory, this viewpoint emphasizes self-realization as central to well-being. It aims at distinguishing subjective feelings with objective valid needs, where the latter is being given credit for constituting the true human nature and resulting in human development and full functioning.
According to the most widely accepted definition, SWB is a construct comprised of three components: (1) it involves positive affect, which is the presence of pleasant feelings; (2) it presents the absence of negative affect; and (3) it is an overall cognitive assessment of a person's life that can be referred to as life satisfaction (Diener, 1984). For this study, the last cognitive component of SWB, or evaluative well-being—measured by life satisfaction—will be the outcome variable. The evaluative model of well-being assumes that the ability to evaluate one's life by giving different hedonic experiences relative weights throughout time makes people the finest judges of their lives (Kahneman & Krueger, 2006).
In the entrepreneurial context, there has been a growing academic interest in comprehending the relationship between entrepreneurship and well-being (e.g. Brieger et al., 2021; Larsson & Thulin, 2019; Nikolaev et al., 2019). Many studies have evidenced positive associations between SWB and self-employment (Andersson, 2008; Bradley & Roberts, 2004; Johansson Sevä et al., 2016). Nikolaev et al. (2019), found an association between entrepreneurship and significant enhancements in psychological functioning on a personal and social level. Similarly, Binder & Coad (2013) suggest that increased life satisfaction is a possible outcome of entrepreneurial engagement. The primary reasons why greater well-being has been recognized as an essential outcome of entrepreneurship participation include higher levels of autonomy, job control, and flexibility it provides (Hessels, Arampatzi, van der Zwan, & Burger, 2018; Stephan, 2018). Despite entrepreneurs’ reported well-being, there are trade-offs between the costs and benefits of self-employment. The findings show that it is also true that self-employed can experience lower levels of life satisfaction (Bencsik & Chuluun, 2021). For example, entrepreneurs face different challenges than employees due to long working hours, increased work stress, and the risk of losing their investments (Hessels, Rietveld, & van der Zwan, 2017; Hetschko, 2016). They also experience higher levels of work-family conflict and lower family satisfaction compared to employees of organizations (Schjoedt, 2013). There is evidence, too, that self-employment leads to more mental health problems (Andersson, 2008), and lower physical well-being (Bencsik & Chuluun, 2021).
While the direct effects of entrepreneurship participation on well-being are evident, many personal and contextual factors impact an entrepreneur's well-being. While previous research has effectively examined factors influencing entrepreneurs’ SWB, it has, however, introduced factors not encompassed in the proposed model of this study, including but not limited to personality traits (Berglund, Johansson Sevä and Strandh, 2016), entrepreneur's definition of personal success (e.g. Sherman et al., 2016), the role of physiological functioning (Nikolaev et al., 2019), dynamics between work and family (Powell & Eddleston, 2017), company characteristics (e.g. Millán et al., 2013), the presence of social capital in the form of family support (Nguyen & Sawang, 2016; Xu, He, & Yang, 2021), political connections in the form of social capital (Xu, Yang, & He, 2022), societal engagement and prosocial behaviors (Stephan et al., 2021), social value creation beliefs (Brieger et al., 2021), urban-rural dimension (Abreu, Oner, Brouwer, & van Leeuwen, 2019), and macroeconomy and immigrant status (Johansson Sevä et al., 2016).
Notably, a significant body of research on SWB has concentrated on comparing entrepreneurs and paid employees (Berglund et al., 2016), aiming to discern differences in SWB between the two groups. These investigations have shown that self-employed people frequently report higher levels of job satisfaction (Andersson, 2008; Binder & Blankenberg, 2020). Much research on SWB has historically focused on the general public (Diener et al., 2018; Lambert, Karabchuk, & Joshanloo, 2022; Ngamaba & Soni, 2018). For instance, studies on the impact of institutional quality on general society's SWB demonstrate the positive effect of institutional effectiveness on individual SWB levels (Cárcaba, Arrondo, & González, 2022; Shiroka-Pula, Bartlett, & Krasniqi, 2023). Research has also compared the well-being of employees and self-employed in various institutional contexts and countries. The findings indicate that the quality of entrepreneurial institutions raises the well-being of paid workers, but the effect is stronger for self-employed (Fritsch, Sorgner, & Wyrwich, 2019).
While there is a wealth of research on SWB (Millán et al., 2013), specifically on entrepreneurship and SWB (Abreu et al., 2019; Brieger et al., 2021; Jiang, Lu, & Lu, 2017), these studies frequently employ more limited metrics, such as job satisfaction, as their outcome variable to reflect SWB. Additionally, entrepreneurial research examining variables concurrently at the individual and national levels within a cohesive model is relatively underrepresented.
This comprehensive review lays the groundwork for a more holistic perspective on the well-being of entrepreneurs. The objective of this study is to provide specific perspectives on SWB by redirecting attention toward entrepreneurs, generating new insights, and expanding the existing literature. Therefore, this study proposes an extended model with twelve individual and four country-level variables, examining their influence on entrepreneurs' SWB. The aim is to identify the most impactful factors using a comprehensive measure—life satisfaction—as the dependent variable for measuring SWB. The following section presents the conceptual model.
Conceptual ModelThis study presents a multilevel model consisting of twelve individual-level variables, including demographic characteristics, perceived own financial satisfaction, perceived economic situation, job satisfaction, perceived social standing, generalized trust, optimism, self-assessed health, number of workers, and four country-level variables — political stability, corruption, business freedom, paying tax regulatory — as independent variables to assess their impact on entrepreneur's SWB, which is the outcome variable of this study. Many other factors are theorized to impact SWB; nevertheless, it is plainly outside the scope of this work to consider every potential research domain. The following segment provides a literature review of the proposed research model.
Individual-level variablesExtant literature offers compelling evidence on SWB and life satisfaction determinants, encompassing many individual-level factors. SWB is contingent upon various personal and socially acquired characteristics, such as educational attainment, ethnic identity, gender, and family structure (Mahadea & Ramroop, 2015). Other research gives genetics a relatively significant role in SWB, suggesting to account for 30 to 40 % of the variance in individual differences in SWB, while environmental factors are responsible for about 60 to 70 % of SWB (Diener et al., 2018; Nes & Røysamb, 2015). Cárcaba et al. (2022) argue that although genes influence a person's potential for well-being, they do not entirely control their success. Rather, other factors also play a role in determining an individual's SWB.
Job satisfaction is among the most widely studied factors, particularly in entrepreneurship. Job satisfaction is the degree to which people are happy with their job situation and their work (Morrow & McElroy, 1987). Despite the literature's extensive documentation of the link between job satisfaction and well-being, the way these two factors interact has always been controversial due to endogeneity (Cannas, Bruno, Sironi, & Mentel, 2019). Job satisfaction can be conceptualized as a sub-dimension within the broader construct of SWB (Sironi, 2019), offering insights consistent with the "part-whole" theory or the "spillover" hypothesis (Cannas et al., 2019). Work is an essential facet of human life, and findings suggest strong effects on individuals’ satisfaction with life or SWB (Calaguas, 2017). Without denying the possible impact of SWB on job satisfaction, this paper considers job satisfaction as a component contributing to an individual's overall SWB and, therefore, focuses on investigating the effect that job satisfaction has on SWB.
Health is another critical factor that has been extensively examined in the context of SWB. Given its indispensable role in human life, a plethora of research has been devoted to investigating the enduring relationship between SWB and health/longevity (Diener, Pressman, Hunter, & Delgadillo-Chase, 2017). Even though SWB can affect health, the substantial impact that health has on SWB suggests a reciprocal relationship; health continues to affect SWB, even when the effect of SWB on health is considered (Dolan, Peasgood, & White, 2008). Similarly, Diener et al. (2018) suggest that the relationship between high SWB and health is unclear as causality could flow in both directions, meaning health and illness can impact SWB and vice versa. However, research has theorized findings of health contributing to increased life satisfaction. For example, self-rated health contributes to life satisfaction in individuals and across nations (Cho, 2015; Ngamaba & Soni, 2018), while poorer perceived health is negatively associated with SWB (Dolan et al., 2008).
The construct of economic well-being is a crucial factor in determining one's SWB. Financial satisfaction, perceived economic situation, and social standing in relation to income ranking are commonly studied variables in this regard. Fulfilling basic and psychological needs can increase SWB, and one's financial state has been extensively investigated in this context as it affects the fulfillment of these needs, including shelter, food, and autonomy (Diener et al., 2018). Income is a fundamental predictor of economic well-being as it measures the purchasing power of individuals (Voukelatou et al., 2021). Research conducted across various countries with different cultures indicates that financial satisfaction, among other factors, is positively associated with SWB (see review by Diener et al., 2018; Haller & Hadler, 2006; Johnson & Krueger, 2006). As might be presumed, people who feel unsatisfied with their financial situation frequently have lower levels of life satisfaction (Hayo & Seifert, 2003). Perceived social standing refers to an individual's perception of their socioeconomic ranking relative to others, and it plays a significant role in shaping one's SWB. The prevailing consensus is that while absolute income holds significance, the relative income ranking in comparison to others substantially impacts SWB (Posel & Casale, 2011). Research has shown that individuals who perceive themselves as having a higher income and status ranking tend to experience higher levels of SWB (Guven & Sørensen, 2012). Conversely, individuals belonging to lower-income groups often exhibit a negative correlation with happiness (Ngamaba & Soni, 2018). Analogous to these economic well-being metrics, a country's economic situation greatly influences residents' overall well-being and quality of life. Findings show that an improved economic state within a nation enhances well-being and has a substantial impact on happiness (Youssef & Diab, 2021). Certain research findings suggest that economic health is of great importance for the level of life satisfaction among the self-employed (Johansson Sevä et al., 2016).
In the realm of entrepreneurship and well-being, optimism is another contributing factor. Optimism is a cognitive construct mainly characterized by positive anticipation for the future (Carver & Scheier, 2014). According to Scheier & Carver (1993), different behavioral patterns and expectations regarding accomplishing goals exist between optimists and pessimists. They also claim that optimists report higher SWB because they are better at handling difficult life circumstances than pessimists. An optimistic outlook promotes SWB by fostering feelings of self-worth, harmonious relationships, and positive financial perceptions (Leung, Moneta, & McBride-Chang, 2005). Recent findings also show that dispositional optimism is associated with entrepreneurial success (Lindblom, Lindblom, & Wechtler, 2020).
Social trust is also an important part of well-being. Social trust can be referred to as the belief that most individuals in society are trustworthy, and it shows a person's reliance on the kindness of other people ( Bai, Gong, & Feng, 2019). The impact of social trust on well-being is rather significant. Several studies argue that there is a strong association between social capital measures, including general trust, and one's well-being ( Helliwell, 2006; Helliwell & Wang, 2011). Similarly, Hamamura et al. (2017) found that generalized trust positively correlated with respondents' life satisfaction and physical health. Within the domain of entrepreneurship, research indicates that individuals are more inclined to share their expertise with people they can trust and rely on, thereby emphasizing the critical role of trust (Rezaei, Sadraei, Jafari-Sadeghi, & Vrontis, 2023).
Adding to the discussion of factors influencing SWB, it is crucial to recognize the role of workers in entrepreneurial endeavors and their impact on the entrepreneur's well-being. Solo self-employed face numerous challenges, such as reduced security, a lack of social support, and limited career resources, thus bearing complete responsibility for their work (Engel, van Burg, Kleijn, & Khapova, 2017). Evidence shows that when a higher number of workers are employed, it can lead to higher job security and satisfaction for employer entrepreneurs compared to those with no or fewer employees (Millán et al., 2013). Conversely, an alternative perspective posits that having no employees involved allows entrepreneurs to enjoy the freedom to shape their career path and purpose independently (Van Den Groenendaal, Rossetti, Van Den Bergh, Kooij, & Poell, 2021).
Country-level variables: Institutional quality variablesInstitutions play a critical role in determining individual behavior and economic performance. Within the entrepreneurship domain, institutions encompass regulations that govern and structure the economic, social, and political interplays among individuals and social collectives, influencing business activities and fostering economic advancement. Institutional contexts that support entrepreneurial behavior have a significant impact on the development and expansion of new businesses (Ge, Stanley, Eddleston, & Kellermanns, 2017; Onjewu, Jafari-Sadeghi, Kock, Haddoud, & Sakka, 2023; Jafari-Sadeghi, Nkongolo-Bakenda, Anderson, & Dana, 2019), whereas entrepreneurial circumstances play an important role in determining entrepreneurs’ level of SWB (Fritsch et al., 2019). When there is institutional uncertainty, entrepreneurs may face managerial difficulties and limitations in their ventures due to perceived incongruence between their entrepreneurial actions and institutional order (Bylund & McCaffrey, 2017).
For a long time, measures of governance quality have included perceived corruption and political stability. For example, Samanni and Holmberg (2010) argue that happiness and government quality are strongly correlated, using corruption as one of the metrics to assess government quality. Higher political freedom and lower levels of corruption are linked to higher SWB (Diener et al., 2018). People are happier and more satisfied with their lives when government institutions are more efficient, impartial, and free of corruption (Bjørnskov, Dreher, & Fischer, 2010; Helliwell & Huang, 2008). On the other hand, higher levels of perceived corruption are strongly linked to lower rates of well-being (Dolan et al., 2008).
Political stability is a governance quality variable. A country is politically stable with a low likelihood of government collapse due to conflicts or fierce competition between political parties (Friedman, 2011). Political stability can attract investments that are advantageous for a country and create wealth ( Bai & Jia, 2016). Lv et al. (2021) found that the determinants of entrepreneurial success encompass a synergistic blend of various factors related to institutional quality, including political stability.
Two other additional domains that hold importance in entrepreneurship are Doing Business and Regulatory Efficiency. We take Business Freedom and Paying Tax Regulations as proxies for environmental uncertainty and regulatory efficiency. Business Freedom is a component of Economic Freedom regarded as a representation of a business-friendly climate. According to Heritage2, Business Freedom measures Regulatory Efficiency and assesses how much the regulatory and infrastructure environment impedes enterprises from operating effectively. Miller & Kim (2013) refer to business freedom as the ability of an individual to establish and operate a business free from government interference. They also argue that the most frequent obstacles to the unhindered practice of entrepreneurship are complex and ineffective regulatory laws. Through exerting control over businesses, governments can determine how they are affected by the environment and, consequently, their level of environmental uncertainty (Hatak, Fink, & Frank, 2015).
Another institutional quality metric is Paying Tax Regulatory. Taxes exemplify ongoing costs that have a diminishing effect on the gains from innovation and entrepreneurship activity, and at the same time, they exhibit strong associations with entrepreneurship rates (Darnihamedani, Block, Hessels, & Simonyan, 2018). Paying taxes is burdensome to entrepreneurs because they typically consider it as a share of their earnings, which is why it is perceived as lowering their income. This may also influence their decisions by limiting innovative ideas and products (Darnihamedani et al., 2018). Findings also show that the opportunity cost of entrepreneurship rises with higher tax progressivity because people are less inclined to choose self-employment when compared to paid employment (Wen & Gordon, 2014).
Collectively, these findings point to the significance of desired or supportive institutional contexts towards higher SWB. Thus, we propose that institutional context is particularly relevant to SWB.
Methodology and plan of analysisSample and data collectionThis study adopts a quantitative analysis approach and relies on a reliable dataset sourced from the LiTS III survey, which represents the latest survey wave conducted among private households in 34 countries, spanning from the end of 2015 to early 20163. It contains information on respondents' socioeconomic status, including perception-based questions on various economic, political, and social topics and questions on general life satisfaction, providing specific insights into SWB. The survey was developed in two stages, stratified by geographical region and the level of urbanity (urban or rural area), and administered face-to-face through the Computer-Assisted Personal Interviewing method (CAPI). The selection of respondents was made automatically by the software. In each country, approximately 1,500 interviews were conducted. Upon removing a few missing observations, our analysis included a sample of 50,333 individual-level observations.
Considering that entrepreneurship is characterized by a new entry or existing business establishment (Gartner, 1990), and self-employment represents the most direct type of entrepreneurship (Blanchflower & Oswald, 1998), our focus will be investigating respondents who report being self-employed. Following Nikolaev (2019), we include entrepreneur-employer cases (businesses employing other people). This is in line with previous research on entrepreneurship (Dvouletý, Mühlböck, Warmuth, & Kittel, 2018; Krasniqi, 2009), and specifically on the SWB of entrepreneurs (Brieger et al., 2021; Johansson Sevä et al., 2016; Kara & Petrescu, 2018; Nikolaev et al., 2019), which have used the terms '' entrepreneur '' and '' self-employed ''interchangeably. A variety of job conditions are detailed in the LiTS, including unemployed, employed, self-employed, and employers, so our analysis will be built upon entrepreneur cases (self-employed and entrepreneur-employer with employees including self). To build our variable, we extracted responses from the question ‘’What type of job do you have in your primary occupation’. After further data classification, this variable, determined by the declared number of workers, yielded 2,335 cases (4.64 % of the sample) following the exclusion of missing values.
Study variables and measuresDependent variable: subjective well-beingThe dependent variable of this study is SWB. We use the LiTS's life satisfaction scale to measure self-employed SWB. The term "subjective well-being" relates to how individuals view and evaluate their own lives (Diener, 1984, 2009; Diener et al., 2018). It is a self-reported evaluation of an individual with a demonstrated reliability in empirical research on well-being (Diener et al., 2018). Building upon the understanding that SWB is a broad measure (Binder, 2014), and goes beyond a material or health perspective, this study will focus on investigating entrepreneurs' SWB in the form of life satisfaction. Life satisfaction is the most frequently used and best-validated concept for measuring well‐being (Pavot & Diener, 2008).
Following previous literature (Fritsch et al., 2019; Johansson Sevä et al., 2016; Shiroka-Pula et al., 2023), we assess SWB on a one-item measure: "All things considered, I am satisfied with my life now" (available in LiTS III). Respondents answered the items on a five-point Likert scale, ranging from 1 = strongly disagree to 5 = strongly agree. A dummy variable for life satisfaction was created to facilitate the analysis, taking the value of 1 if the respondent stated agreement or strong agreement with life satisfaction and 0 if expressed disagreement or lesser agreement.
Independent variablesThe independent variables of this study are grouped into individual-level variables and institutional variables measuring institutional quality, as detailed in the following.
Individual-level variables- •
Socio-demographic factors: gender (male = 1, female = 2); respondents age (continuous variable); marital status (married, single, divorced, widowed, separated), a dummy variable was created (married = 1 otherwise = 0); education (no degree, primary education, lower secondary and (upper) secondary = 0, post-secondary, tertiary education, bachelor's degree and master's degree = 1).
- •
Job satisfaction is measured with ‘’All things considered; I am satisfied with my job now’’ (Likert scale 1 = strongly disagree to 5 = strongly agree).
- •
Perceived personal financial situation is measured with ‘’All things considered; I am satisfied with my financial situation as a whole’’ (Likert scale: 1 = strongly disagree to 5 = strongly agree).
- •
Perceived social standing/self-assessed income bracket/group is measured by the question ‘’Imagine a 10-step ladder where on the bottom, the first step, stand the poorest 10 percent of people in [your country] and on the highest step, the tenth, stand the richest 10 percent of people in [your country]." Respondents were then asked to state which step of the 10-step ladder they believe their household currently rests.
- •
Self-assessed health is measured with the question ‘’How would you assess your health?’’ (very good = 1, good = 2, medium = 3, bad = 4, very bad = 5). To align with the scaling of other variables for analytical consistency, this variable was reverse-coded (very good = 5, good = 4, medium = 3, bad = 2, very bad = 1).
- •
The number of workers is measured with the question ‘'How many people in total work in the business company, institution, or organization where you work in your primary occupation (including yourself)?’’, 1 person (self) = 1, 2-5 people = 2, 6-10 people = 3, 11-20 people = 4, 21-100 people = 5, 101 or more = 6. We created a dummy (1 person/self = 0, otherwise = 1).
- •
Generalized social trust refers to trust in people in general and inside a group—among family, neighbors, or other individuals. Generalized social trust is measured with the question ‘’Generally speaking, would you say that most people can be trusted or that you cannot be too careful in dealing with people? Responses were recorded on a five-point scale, ranging from ‘’complete distrust = 1’’ to ‘’complete trust = 5’’. Subsequently, a dummy was created (no trust = 0, trust = 1).
- •
Optimism: Based on Carver & Scheier (2014) suggesting that optimism is known as one's anticipation that future circumstances will generally be favorable, we therefore measure optimism with the statement ‘’Children born now will have a better life than current generation’’, (Likert scale: 1 = strongly disagree to 5 = strongly agree).
To analyze the relationship between institutional factors and SWB, this study presents the following variables:
- •
Political Stability and Absence of Violence/Terrorism is a Worldwide Governance Indicator published by the World Bank and measures the perception regarding the chances of encountering political instability and acts of politically motivated violence, including terrorism. The rank represents the country's position relative to all the countries included in the aggregate indicator, where a rank of 0 indicates the lowest position and 100 represents the highest.
- •
Paying Tax Regulatory is a sub-index of The Doing Business published by the World Bank Group. It captures economies based on the tax regulatory best practices measured by the indicator. The rating is given on a scale from 0 to 100, with 100 being the best regulatory performance and 0 the worst.
- •
Business Freedom is a pillar of the Economic Freedom Index published by the Heritage Foundation. The Business Freedom component measures how much the infrastructure and regulatory framework impede enterprises' ability to operate efficiently. Each country's score for Business Freedom ranges from 0 to 100, with 100 representing the most liberal business environment.
- •
The Corruption Perception Index (CPI) is published by Transparency International. It measures the perceived level of public sector corruption in each nation on a scale of 0 to 100, where 0 means highly corrupt and 100 means very clean.
The summary statistics of this study's variables are presented in Table I. Also, a more detailed summary of country-level indicators is provided in Table A.1 in the Appendix.
Summary statistics
Considering the nature of the data and the aim of the present study, we conducted a multilevel regression for data analysis. Given that the data in this study have a nested or hierarchical structure, with individuals nested within countries, multilevel modeling is appropriate as it allows for data analysis with such hierarchical structures, accounting for the potential correlation and dependence of observations within the same country. Other studies (Ferrer-i-Carbonell and Frijters, 2004; Shiroka-Pula et al., 2023) have employed comparable research approaches to assess well-being. These researchers have shown that treating the life satisfaction scale as a quantitative variable (continuous) or binary yields the same results as using a complicated model, such as an ordered probit model. Therefore, recent research has started to employ simple OLS or binary choice models instead of more complex ordered probit models. In line with this literature, we adopt the binary choice model for this study. Since the dependent variable of this study is binary, where a value of 1 indicates agreement or strong agreement with life satisfaction and 0 otherwise, we employ mixed effects logistic regression (Snijders & Bosker, 2011). The model examines the relationship between various individual and country-level predictor variables and life satisfaction while accounting for both fixed and random effects at the country level.
The inclusion of fixed effects allows for controlling the influence of specific predictor variables on the outcome variable, and the robust option used in the analysis adjusts the standard errors for clustering at the country level, which helps address potential heteroscedasticity or correlation within countries (Shiroka-Pula et al., 2023). Furthermore, to mitigate the problem of multi-collinearity (see Table A.2 in the Appendix), we systematically introduce country-level variables into the model one by one.
In the first stage of the analysis, a baseline random model with no explanatory variables is estimated to determine the appropriateness of the proposed model (Krasniqi & Williams, 2017; Williams & Krasniqi, 2017). The results of the Inter-Cluster Correlation (ICC) analysis show that 8.9 percent of the variance in SWB is explained at the country level, indicating significant variation in SWB between countries.
Results and discussionThe findings from the regression analysis concerning individual-level variables, as evidenced by Model 1 (see Table II), show that several variables are associated with life satisfaction. Regarding socio-demographic variables, gender, education, and age in this study do not exhibit a significant association with the reported life satisfaction of entrepreneurs. Research on SWB has reported similar but fewer results (Dolan et al., 2008). For example, Millán et al. (2013) found no gender effect on the degree of well-being at work for either paid employees or self-employed individuals. As per Suhail & Chaudhry (2004), gender was found to have no significant impact on well-being, and there was no statistically significant association between life satisfaction and age. Concerning education, while literature indicates its pivotal role in fostering entrepreneurial readiness (Jafari-Sadeghi, Nkongolo-Bakenda, Dana, Anderson, & Biancone, 2020), other research shows that education does not affect happiness (Youssef & Diab, 2021).
Multilevel Mixed-effects Logistic Regression analysis results (n=2,043)
| VARIABLES | Model 1 | Model 2 | Model 3 | Model 4 | Model 5 |
|---|---|---|---|---|---|
| Individual-level variables | |||||
| Gender (0=man; 1=woman) | -0.006 (0.020) | -0.007 (0.020) | -0.007 (0.020) | -0.007 (0.020) | -0.006 (0.020) |
| Age | -0.000 (0.001) | -0.001 (0.001) | -0.000 (0.001) | -0.000 (0.001) | -0.000 (0.001) |
| Marital status | 0.040⁎⁎ (0.018) | 0.044⁎⁎⁎ (0.017) | 0.043⁎⁎ (0.018) | 0.043⁎⁎ (0.017) | 0.042⁎⁎ (0.018) |
| Education | -0.010 (0.026) | -0.005 (0.025) | -0.007 (0.025) | -0.010 (0.025) | -0.013 (0.025) |
| Optimism | 0.036⁎⁎⁎ (0.010) | 0.038⁎⁎⁎ (0.010) | 0.038⁎⁎⁎ (0.010) | 0.036⁎⁎⁎ (0.010) | 0.036⁎⁎⁎ (0.010) |
| Satisfaction with economic situation | 0.028⁎⁎ (0.012) | 0.029⁎⁎ (0.012) | 0.028⁎⁎ (0.012) | 0.028⁎⁎ (0.012) | 0.026⁎⁎ (0.012) |
| Job satisfaction | 0.106⁎⁎⁎ (0.012) | 0.104⁎⁎⁎ (0.012) | 0.105⁎⁎⁎ (0.012) | 0.105⁎⁎⁎ (0.012) | 0.106⁎⁎⁎ (0.012) |
| No. of workers | 0.047* (0.025) | 0.048* (0.026) | 0.047* (0.025) | 0.048* (0.025) | 0.050⁎⁎ (0.025) |
| Satisfaction with own financial situation | 0.111⁎⁎⁎ (0.011) | 0.111⁎⁎⁎ (0.011) | 0.111⁎⁎⁎ (0.011) | 0.112⁎⁎⁎ (0.011) | 0.113⁎⁎⁎ (0.011) |
| Generalized trust | 0.063⁎⁎⁎ (0.017) | 0.063⁎⁎⁎ (0.017) | 0.063⁎⁎⁎ (0.017) | 0.063⁎⁎⁎ (0.017) | 0.064⁎⁎⁎ (0.017) |
| Social standing | 0.014⁎⁎⁎ (0.005) | 0.013⁎⁎⁎ (0.005) | 0.013⁎⁎⁎ (0.005) | 0.014⁎⁎⁎ (0.005) | 0.014⁎⁎⁎ (0.005) |
| Health assessment | 0.024⁎⁎ (0.012) | 0.022* (0.012) | 0.022* (0.012) | 0.024⁎⁎ (0.012) | 0.024⁎⁎ (0.012) |
| Country-level variables | |||||
| Political Stability | 0.002⁎⁎⁎ (0.001) | ||||
| CPI score | 0.002⁎⁎ (0.001) | ||||
| Paying Tax Regulatory | 0.001* (0.001) | ||||
| Business Freedom | 0.004⁎⁎⁎ (0.002) | ||||
| Constant | -0.507⁎⁎⁎ (0.095) | -0.577⁎⁎⁎ (0.100) | -0.585⁎⁎⁎ (0.111) | -0.609⁎⁎⁎ (0.116) | -0.813⁎⁎⁎ (0.153) |
| Observations | 2,043 | 2,043 | 2,043 | 2,043 | 2,043 |
| Number of groups | 34 | 34 | 34 | 34 | 34 |
| Identity: country | .072 | .062 | .065 | .066 | .062 |
| ICC | .034 | .025 | .029 | .029 | .026 |
Robust standard errors in parentheses.
The findings from the regression analysis concerning individual-level variables, as evidenced by Model 1 (see Table II), show that several variables are associated with life satisfaction. Regarding socio-demographic variables, gender, education, and age in this study do not exhibit a significant association with the reported life satisfaction of entrepreneurs. Research on SWB has reported similar but fewer results (Dolan et al., 2008). For example, Millán et al. (2013) found no gender effect on the degree of well-being at work for either paid employees or self-employed individuals. As per Suhail & Chaudhry (2004), gender was found to have no significant impact on well-being, and there was no statistically significant association between life satisfaction and age. Concerning education, while literature indicates its pivotal role in fostering entrepreneurial readiness (Jafari-Sadeghi, Nkongolo-Bakenda, Dana, Anderson, & Biancone, 2020), other research shows that education does not affect happiness (Youssef & Diab, 2021).
On the contrary, our findings reveal a statistically significant positive relationship between marital status and entrepreneurs' reported life satisfaction. This implies that being married may, in this context, lead to higher levels of life satisfaction. This finding aligns with established literature, which consistently demonstrates that married or partnered individuals report higher life satisfaction than their non-married peers (Dolan et al., 2008; Næss, Blekesaune, & Jakobsson, 2015). This can be attributed to a wide range of benefits that the institution of marriage can provide to individuals, including a sense of belonging and connection, emotional support, shared financial resources and responsibilities, and the fulfilling of intimate needs that ultimately lead to enhanced life satisfaction (Wadsworth, 2016).
As evidenced by the statistically significant coefficient in the regression analysis (β = .11, p < 0.01), job satisfaction shows a statistically significant relationship with life satisfaction. The direction of the relationship between job satisfaction and SWB has long been debatable due to endogeneity. Yet, within scholarly discourse, the causal relationship between job satisfaction and SWB shows that job satisfaction fosters an increase in SWB (Bowling, Eschleman, & Wang, 2010; Cannas et al., 2019). The positive relationship between the two variables can be mainly attributed to autonomy and non-pecuniary rewards that entrepreneurs experience from their entrepreneurial endeavors (Carter, 2011). Additionally, task variety and flexibility at work tend to make entrepreneurs consider their work meaningful, which may result in higher levels of well-being (Hessels et al., 2018). This empirical finding suggests a close interconnection between work-related satisfaction and overall self-employed well-being. It further expands the discussion regarding theories on workplace satisfaction and adds to the body of literature examining the intersectionality of work and life satisfaction in non-traditional workplaces. Taking into account the dynamics of happiness in non-traditional work environments, as well as integrating entrepreneurial contexts, allows us to approach workplace theories and practices more comprehensively.
Optimism is strongly correlated to entrepreneurs’ well-being and is statistically significant. Previous studies on the connection between optimism and well-being suggest that having more optimism is linked to having higher emotional well-being. For example, Yu & Luo (2018) found a significant positive correlation between dispositional optimism and well-being. Furthermore, optimists tend to have better health than pessimists due to the increased likelihood of engaging in health-promoting behaviors (Bouchard, Carver, Mens, & Scheier, 2017). The present study reaffirms the established relationship between optimism and well-being and, at the same time, has practical implications for practitioners who aim to improve overall well-being by creating interventions that support and nurture optimism. This would lead to both psychological well-being on an individual level and societal well-being on a broader scale.
Our findings suggest a positive relationship between health and SWB. The positive correlation between health status and SWB is well-established in the literature, where good health is consistently linked to higher levels of happiness and life satisfaction (Korankye & Lartey, 2022; Ngamaba, 2017). Individuals with major disabilities or those managing chronic diseases typically experience sustained lower levels of SWB compared to individuals without such conditions (Ngamaba & Soni, 2018). Therefore, governments can promote citizens’ SWB by prioritizing initiatives aimed at improving health outcomes.
Concerning the economic well-being of participants, we have used perception-based measures. Our findings show that perceived social standing measured with income evaluation strongly predicts entrepreneurs’ life satisfaction (Ngamaba & Soni, 2018). Posel and Casale (2011) also found that individuals perceiving themselves in the middle- and richest-income thirds of national income report higher SWB than the ones in the poorest. They further suggest that a person's perception of their relative position has more impact on SWB than actual assessments of status based on reported income.
Financial satisfaction is positively correlated with SWB. This finding parallels previous research suggesting that income does more than just enable people to buy goods and services (Howell & Howell, 2008). Findings show that income and financial satisfaction are strongly associated with higher happiness and life satisfaction (Diener, Ng, Harter, & Arora, 2010; Ng & Diener, 2014; Ngamaba, 2017; Ngamaba & Soni, 2018).
The association between economic satisfaction and SWB is statistically significant and positive. This implies that for the self-employed, economic growth may result in more potential for business expansion, larger profits, and generally better financial prospects, affecting their well-being. According to prior research, the degree of life satisfaction for self-employed is significantly impacted by economic growth, as opposed to that of workers (Johansson Sevä et al., 2016). The association between entrepreneurs' economic well-being constructs and SWB is consistent with needs theory (Tay & Diener, 2011), and well-established positive psychology theories (Ryan & Deci, 2001). Even in the particular setting of entrepreneurship, it emphasizes the crucial role that financial health plays in determining overall life satisfaction. Financial well-being helps people meet their basic requirements, ranging from merely surviving to achieving greater goals. This, in turn, makes it easier to feel fulfilled and to be happy in both personal and work life. The results also highlight the belief held by entrepreneurs that their level of life satisfaction is directly related to the status of the economy. This observation may also imply that when entrepreneurs find the economic environment conducive to their well-being, they may demonstrate greater readiness to create innovation and generate jobs. Consequently, to maximize the benefits associated with self-employment, countries must prioritize economic growth.
Findings reveal that the number of workers plays a role in an entrepreneur's life satisfaction. For example, in their study with self-employed, Johansson Sevä et al. (2016) found that self-employed with employees report higher life satisfaction than solo self-employed. Given that entrepreneurs are subject to various stressors, it stands to reason that sharing the burden of the tasks with others may give them a sense of security and support, increasing life satisfaction.
Our findings show a positive and statistically significant relationship between generalized trust and well-being which is also confirmed by earlier research (Hamamura et al., 2017; Helliwell & Wang, 2011). This implies that positive and uplifting social relationships are necessary for the well-being of entrepreneurs. Like a rollercoaster ride, entrepreneurship is full of failures and setbacks, mixed in with moments of innovation simultaneously. Social support is one of the most valuable resources for helping entrepreneurs deal with challenging situations in this sense. As a result, acknowledging trust's critical role in fostering SWB recommends incorporating trust-building practices into the entrepreneurship context and beyond, such as open communication and moral business conduct.
Models 2-5 in Table II present the relationship between SWB and institutional variables. The present study demonstrates that greater political stability leads to elevated life satisfaction for entrepreneurs, which is highly significant. CPI, Paying Tax Regulatory, and Business Freedom are also significant and positively related to the life satisfaction of entrepreneurs. This implies that a stable and effective institutional environment can act as a significant determinant of enhanced overall well-being. Previous research suggests similar findings. For instance, Ngamaba (2017) reports that political stability positively improves SWB; while political instability within countries decreases levels of well-being (Diener & Seligman, 2004). In terms of political governance and control of corruption, well-functioning societies experience greater SWB (Youssef & Diab, 2021), even compared to those in the wealthiest countries ( Helliwell, 2003). Additional research has also reported a positive correlation between control of corruption and life satisfaction (Fritsch, Sorgner, & Wyrwich, 2021; Satrovic, Cetiner, & Muslija, 2018). For example, Helliwell (2003, 2006) demonstrates the significant effects of good governance on wellbeing. Similarly, Diener & Seligman (2018) suggest that living in a democratic environment and a sustainable society positively impacts well-being. Drawing on Baumol's theory, corruption is regarded as a well-established instance of an informal institution that may harm a company's ability to expand by diverting resources away from strategic investments and growth-oriented initiatives (Krasniqi & Desai, 2016), and since more corrupt environments result in greater transaction costs for businesses, it can be seen as a tax that discourages economic activity, particularly high ambition entrepreneurship (Anokhin & Schulze, 2009). Our findings imply that building anti-corruption initiatives leads to a climate conducive to cooperation, trust, and ultimately higher well-being. Under politically stable conditions, on the other hand, entrepreneurs may focus entirely on the creative aspects of their projects, strategize, and achieve business goals without interference and concerns. Consequently, political stability encourages investment confidence and draws in both local and international investment.
Paying Tax Regulatory and Business Freedom are the other two policy-related variables of interest to explain SWB. Current studies suggest that the consequences of taxes likely impact the well-being of entrepreneurs in ways more than just financial outcomes (Bruce & Mohsin, 2006). Fritsch et al. (2021) found that ‘’paying tax’’ as one of the pillars of the Doing Business index has the most significant positive link with individual life satisfaction. This relationship is more significant for self-employed than salaried employees. Elevated tax rates reduce start-up prospects and make business management less enjoyable, consequently lowering the well-being of the self-employed. Therefore, institutions aiming to promote business operations should establish a less complex and easily administrable tax system as well as low perceived tax rates. To support this, Nyström (2008) provides evidence that a one-unit improvement in the regulatory measure produces a rise in the self-employment rate of just over 1 %.
Regarding Business Freedom, earlier literature has found positive relationships between a friendly business environment and job-and-life satisfaction, which was more robust for self-employed (Fritsch et al., 2021). Chambers & Munemo (2019) provide strong evidence that nations with high entry barriers, inadequate institutions, or both have much-reduced rates of new business development. Unnecessary bureaucratic procedures can give enough possibilities for corruption and bribery, too—and further encourage the employment of third parties early in the start-up process—even in situations where it is not expressly mandated, thus increasing the cost of operation. Costly and bureaucratic entrance requirements discourage new businesses from entering the market and speed up the departure of established businesses, which impedes domestic investment. Consequently, a more friendly business environment would free entrepreneurs to concentrate on expanding their companies, increasing productivity, and engaging in creative endeavors rather than dealing with complicated business-related procedures. This would also lead to a rise in the number of new formal businesses; in turn, higher business formalization broadens the tax base and provides the government with more funds for social and economic programs (Chambers & Munemo, 2019).
Collectively, the findings from Models 2-5 lend credence to the notion that institutional governance plays a pivotal role in both the general well-being of entrepreneurs and their entrepreneurial behavior, supporting happiness literature (Diener & Ryan, 2009; Ryan & Deci, 2001), and institutional theory (Frey & Stutzer, 2000).
Conclusion and implicationsThis study maps out the impact of different individual-level and country-level institutional factors on entrepreneurs’ SWB, offering significant insights for the theoretical understanding, practical applications, and policy formulation within the domain of entrepreneurship and SWB. The results indicate that the well-being of entrepreneurs is significantly influenced by both, individual and institutional variables, with the exception of gender, age, and educational attainment, which display no impact within the scope of this study. This implies that the notion of well-being extends beyond individual dimensions for entrepreneurs, emphasizing the substantial influence exerted by institutional quality on their SWB. Therefore, understanding its determinants is essential when designing sustainable and sound economic policies, while also identifying strategies for addressing potential negative factors related to well-being. When it comes to creating a politically stable environment, using qualitative regulatory tools, and building institutional trust regarding corruption, more awareness should be directed to implicit parties on the significant effect these aspects might have. Strong anti-corruption laws that are established and upheld can improve the business climate for entrepreneurs by encouraging trust and cooperation, which raises contentment with life and commercial success. Entrepreneurs operating in healthy institutional environments experience higher life satisfaction and, in return, less burnout due to the benefits of reduced concerns. Political stability, on the other hand, fosters an environment that is favorable for long-term business planning and strategic decision-making in the entrepreneurial context due to the reduced risk and uncertainty about political turmoil, policy shifts, and societal tensions, which has a positive impact on the entrepreneurs' overall quality of life.
The influence of regulatory efficiency on entrepreneurs' life satisfaction in terms of taxes and doing business highlights the need for policies to simplify the processes that impede businesses from operating efficiently, including tax-paying regulations and ease of starting, running, and closing a business. Reducing bureaucratic processes might help entrepreneurs feel more satisfied with their work and increase compliance.
Our findings strongly suggest that supporting and encouraging entrepreneurs in their financial pursuits is essential to a healthy entrepreneurial community. Policymakers must comprehend the significance of economic prosperity to promote a robust business environment. Therefore, facilitating access to financial resources and tailored programs for supporting entrepreneurial endeavors, along with creating avenues for financial education would create an environment where entrepreneurs are more likely to experience financial satisfaction. Working towards economic growth, as well, can contribute to an ecosystem where entrepreneurs are more likely to experience life satisfaction. On this note, we strongly suggest that well-being-related factors be given more weight when making institutional-level policy decisions.
At the individual level, this study contributes by providing practical suggestions for entrepreneurs, which they can leverage to their benefit. For instance, they can recognize and exploit factors that are positively related to their well-being and be aware of factors that have diminishing effects. On a personal level, entrepreneurs may react to stresses as they arise by utilizing a range of coping methods, which is made possible by the autonomy they enjoy as a result of being self-employed. Researchers have suggested several techniques in addition to coping mechanisms to help in the management and recovery from business demands. For example, family involvement and support, engaging in mindfulness exercises, and building business networks boost an entrepreneur's sense of self-efficacy, health, and general well-being (see review by White & Gupta, 2020). Social support (meaning trust and support from their family, friends, and others around them in their profession) is a critical tool to assist with managing difficult circumstances. This concept captures the notion that a person feels appreciated, cherished, and surrounded by people they can currently relate to and trust. Positive main effects of social support for both psychological well-being and SWB were observed in earlier literature (Nguyen & Sawang, 2016). Shen et al. (2018) argue that while relaxation alone cannot provide true well-being, engaging in social and recreational activities centered around hobbies is essential to achieving higher levels of productivity and well-being. Since social support functions are a strong pillar, business owners should take the initiative to establish a strong, trusting network that will support them in overcoming obstacles and setbacks in their endeavors.
Researchers have also used self-care as a mediator to adverse outcomes. Dolan et al. (2008), in their review, suggest that exercise appears to have significant policy potential since it may serve to both promote and lessen a variety of beneficial and adverse outcomes, such as weight gain and depressive symptoms, as well as greater levels of enjoyment and life satisfaction. Entrepreneurs may improve their well-being by promoting a culture that values their health and engaging in personal self-care activities without waiting for any policy to take effect. On the other side, institutions could enhance entrepreneurs' SWB by incorporating well-being schemes such as encouraging work-life balance, access to healthcare, and providing resources for preventive health measures. Such endeavors would contribute to individual and societal well-being, thereby fostering sustainable business practices and economic development.
Coming from the well-being theories, it is evident that individuals are searching for what gives their lives meaning and fulfillment. The right actions that are purposeful and goal-oriented, help them reach their most significant potential and ultimately enhance their well-being. A considerable portion of what makes people feel fulfilled and have a purpose in life is influenced by what happens in the workplace. It seems that engaging in meaningful and valuable jobs is just as vital as building a prosperous life for themselves. This may also help explain why some business owners stick with their companies during challenging times and even with lower initial income than their salaried counterparts. Thus, it makes sense to advise entrepreneurs to assess and engage in activities that provide meaning to them. Of course, this is easier done for voluntary entrepreneurs than for necessity-driven ones; however, if they are already engaged in entrepreneurship that is not satisfying, they can either consider the possibility of adding meaningful innovation to complement it, approach it from a different angle by finding value and significance in their current venture, or eventually move to a more fulfilling entrepreneurial endeavor. Ultimately, one's job should exert positive feelings for them.
Our findings also imply that entrepreneurs should consider growing their staff and delegating effectively, as these strategies enable them to make the most of their time and resources, improve job security, and foster a positive work environment that ultimately enhances the quality of their lives.
Studying entrepreneur well-being is crucial, as achieving higher well-being has significant implications for entrepreneurs. Research shows that low well-being is linked to entrepreneurial burnout and potential business closure (Sherman et al., 2016). Conversely, high life satisfaction makes entrepreneurs more resilient to future challenges (Hahn, Frese, Binnewies, & Schmitt, 2012), increasing their success and impact on the community. Findings suggest that interventions based on positive psychology might successfully improve life satisfaction. Building resilience and experiencing satisfaction can be facilitated by integrating positive psychology into entrepreneurial endeavors. As a result, it provides stakeholders with a special viewpoint and set of resources for enhancing general well-being. It is therefore important that entrepreneurs attend to their well-being, and nations take steps to improve it on the institutional level.
Despite its contribution, the study has several limitations. This study is mainly based on data from transitional nations; therefore, we invite future researchers to investigate the possibility of confirming our findings in different contexts. We rely on answers to subjective questions to measure life satisfaction, which people in other countries may perceive and scale differently. Future research may examine cross-cultural differences to comprehend and analyze how cultural elements influence SWB, which could provide additional insights in this direction. Lastly, due to the unavailability of data, the study does not account for heterogeneous traits that constitute entrepreneurship, such as enterprise size, necessity and opportunity entrepreneurs, and innovative vs imitative entrepreneurs. Further study in this area is thus required, and it should be expanded to include more explanatory variables on the SWB of the self-employed.
FundingThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
CRediT authorship contribution statementAlbanë Gashi: Conceptualization, Methodology, Software, Writing – original draft, Writing – review & editing. Besnik Krasniqi: Conceptualization, Formal analysis, Methodology, Validation, Writing – review & editing, Supervision, Writing – original draft. Veland Ramadani: Conceptualization, Writing – review & editing. Gentrit Berisha: Methodology, Supervision, Writing – review & editing.
The author(s) extend their sincere appreciation to the anonymous referees who offered their expertise and insights during the review process, which greatly enriched the quality and significance of this research.
Country-level institutional indicators
Note: The data are from 2015, except for Paying Tax Regulatory, which is from 2016 due to data unavailability.
Following literature (Brieger, De Clercq, & Meynhardt, 2021; Johansson et al., 2016; Kara & Petrescu, 2018; Nikolaev, Boudreaux, & Wood, 2019), the terms "entrepreneur" and "self-employed" are used interchangeably. In our sample, the entrepreneur includes both self-employed and employers.