Does fairness matter? How perceived stakeholder treatment shapes solo entrepreneurs’ well-being and performance Open Access

Solo entrepreneurs work on their own yet operate in a complex landscape of different relationships with key external stakeholders—clients, financiers, government agencies, and unions. While previous research has focused on how stakeholders can be managed (Mitchell et al., 2021; Alvarez and Sachs, 2021; Suddaby et al., 2021; Pedrini and Ferri, 2019), in this paper, we study how entrepreneurs perceive the fairness of the treatment they get from their external stakeholders and what consequences these perceptions may have for entrepreneurial well-being and performance. We build on the long tradition of organizational justice and fairness at work (Colquitt et al., 2022), which refer to subjective judgements of whether individuals feel treated appropriately by others (Eib and Cropanzano, 2023; Byrne and Cropanzano, 2001). Individuals judge decisions, processes and interpersonal treatment, and come to a holistic judgement – fairness perceptions – that drive attitudes and behaviours (Ambrose et al., 2015). Although fairness at work is a well-established concept in organizational behaviour research (Bobocel, 2021), most studies focus on within-organizational relationships, typically studying employees’ fairness perceptions towards their supervisors. Some studies have extended the lens to interactions with outside-organizational stakeholders like customers (Wo et al., 2019), yet employees still exercise limited agency because of their subordinate role. In contrast, entrepreneurs, control their venture and decide how to engage each stakeholder. This autonomy is most pronounced for solo entrepreneurs, who, as sole owner, manager, and frontline worker personally manage every stakeholder interaction. Lacking an internal hierarchy, all their fairness experiences originate from outside the organization. Because solo entrepreneurs represent most businesses in OECD and European countries (van der Zwan and Hessels, 2019; Eurostat, 2022), understanding how external stakeholder treatment affects solo entrepreneurs is a key but overlooked dimension of the entrepreneurial work environment. Our study addresses this gap and provides some first empirical evidence regarding the role of stakeholder treatment for solo entrepreneurs’ well-being and performance.

Experiences of interpersonal treatment by others, such as fairness perceptions, can be understood through social exchange theory (SET; Cropanzano and Mitchell, 2005) to explain exchange relationships that entrepreneurs have with their stakeholders (Dutta and Khurana, 2023). Exchange relationships characterized by fairness perceptions increase engagement and commitment, particularly in uncertain circumstances (Colquitt et al., 2013; Rupp et al., 2014). All people, entrepreneurs included, want to be fairly treated, feel respected, and rewarded for their efforts (Cropanzano et al., 2001). Soenen et al. (2019) have shown that feeling fairly treated as entrepreneur was associated with less burnout and better firm performance. Xu et al. (2021) found that entrepreneurs’ fairness perceptions in relation to the governmental institutions were related to higher job and life satisfaction. Likewise, tax compliance was higher when entrepreneurs felt that the tax authority treated them fairly (Kogler et al., 2015). This demonstrates that stakeholder relationships are relevant for entrepreneurs’ fairness perceptions and their health and performance. However, this limited evidence does not disentangle potential differences in fair treatment across various stakeholders.

Our overall aim is to understand the sources of fairness perceptions of entrepreneurs and their associations to well-being and performance. Focussing on solo entrepreneurs and their perceptions of fairness in relation to external stakeholders, we contribute to the psychology of entrepreneurship and entrepreneurial well-being and health literature in at least three ways. First, we highlight the relevance of fairness perceptions from stakeholders as a key but underexplored predictor of well-being and performance. Specifically, we relate fairness perceptions of solo entrepreneurs with overall fairness, career satisfaction, self-rated health, and self-rated job performance both concurrently and prospectively across six months. Within the psychology of entrepreneurship literature, several factors of the entrepreneurial work environment and their effect on performance and well-being have been studied (Gielnik et al., 2020; Stephan, 2018). Despite these advances, the quality of interactions with stakeholders has been overlooked so far, leaving a blind spot for an important aspect of entrepreneurs’ working life. Complementing this literature, we suggest that fairness perceptions are an important work environment factor for entrepreneurs and demonstrate the relevance of fairness perceptions for career satisfaction, job performance and self-rated health, indicators of contentment and functioning.

Secondly, drawing upon social exchange theory (Cropanzano and Mitchell, 2005) and the fairness at work literature (Cropanzano and Ambrose, 2015), we position fairness as a fundamental concept to understand exchange relationships of entrepreneurs with their stakeholders. Specifically, we study four sources of fairness perceptions of solo entrepreneurs: governmental agencies, clients, banks and unions. We explore whether and in what way solo entrepreneurs differ in their fairness perceptions to these external stakeholders. This offers a nuanced understanding of how distinct external stakeholders shape entrepreneurial experiences, and responds to the call for more in-depth analyses of the role that various sources together play in shaping fairness perceptions (Bobocel, 2021). Despite ample evidence that individuals form fairness perceptions in relation to different sources (Lavelle et al., 2015), the idea of considering these different sources simultaneously has novelty and provides a more realistic view of how individuals judge their environment.

Lastly, our novel approach of considering the joint contribution of fairness from multiple stakeholders through a person-oriented approach complements more traditional variable-oriented approaches (Morin et al., 2018; Bergman et al., 2003). Person-oriented approaches have been sparsely adopted in the entrepreneurial literature (for two exceptions, Bujacz et al., 2020; Kleine et al., 2024) but provide exciting possibilities next to clustering approaches (Crum et al., 2022). Specifically, this method allows exploring subgroups of entrepreneurs (so-called profiles) and describe these subgroups with individual (e.g. age, gender, education) and business characteristics (e.g. type of business, sector), disclosing aspects that may constitute risk factors for poor work environment perceptions and long-term negative outcomes.

Contrasting the prescriptive approach of law or philosophy, organizational behaviour conceptualizes fairness at work as a subjective individual perception that drives attitudes and behaviours (Bobocel, 2021; Cropanzano and Ambrose, 2015). At work, individuals form fairness perceptions towards entities, like an organization, or specific individuals, like a supervisor or client. Individuals form these fairness judgements overall, across transactions, exchanges, events and time, judging whether cost-reward ratios and interpersonal behaviour are fair from said entity (Ambrose and Schminke, 2009; Cropanzano et al., 2001). We follow the distinction between fairness and justice by Goldman and Cropanzano (2015), where fairness refers to an evaluative assessment of whether an event is perceived as more or less fair and justice refers to adherence to specific justice rules.

Fairness perceptions have been related to positive attitudes and behaviours, such as commitment, engagement, performance, and inversely to deviant behaviours, burnout, and ill-health (for meta-analyses, see Colquitt et al., 2013; Rupp et al., 2014). Fairness perceptions can be considered a work environment aspect that is separate – theoretically and empirically – from other work environment aspects, such as job demands or control (Ndjaboué et al., 2012). Fairness matters to individuals for economic or instrumental reasons but also communicates being valued and respected as interaction partners. When individuals feel unfairly treated, not adequately rewarded for their efforts or disrespected, they are more likely to terminate any future engagement with that exchange partner, limiting efforts to the minimum or reciprocating with deviant behaviours, like lying, cheating, sabotaging. Individuals can also go against their own self-interest to harm others in order to remedy unfair treatment (Cropanzano et al., 2001).

Social exchange theory (SET; Cropanzano and Mitchell, 2005) is often used to explain the consequences of fairness perceptions. SET is a paradigm of different conceptualizations but the basis is transactions between two or more parties. Social exchange is defined as the “exchange of activity, tangible or intangible, and more or less rewarding or costly, between at least two parties” (Cook et al., 2013, p. 61). Exchange relationships can be mutually beneficial and evolve into committed and trusting relations of mutual obligations when exchange partners follow the rule of reciprocity–meaning that fair exchanges exist when rewards match investments or when profits of the exchange partners match. Exchange relationships can also turn sour in the case of an asymmetry between rewards and costs or when anticipations do not meet reality. SET applies to relationships on an individual, micro-level but also extends to macro-level structures, like exchange relationships between groups, organizations and inter-organizational settings (Dutta and Khurana, 2023). SET theorists have incorporated issues of power, such that some parties control more highly valued resources, and affect, such that individuals react with anger when they do not receive what they anticipated. Thus, SET suggests that individuals can view their exchange relationships as more or less fair and react emotionally in response to these fairness perceptions (Cropanzano and Ambrose, 2015).

The multi-foci model (Lavelle et al., 2015) posits that individuals differentiate between different sources when making judgements of fair treatment. This emphasizes the incorporation of various sources, meaning that an individual can hold multiple, unique social exchange relationships with different sources. When an individual feels fairly treated by a certain social exchange partner, they are more likely to reciprocate the beneficial treatment towards that source. While the multi-foci model was put forth with an organizational context in mind, it can be applied to entrepreneurs, suggesting that entrepreneurs form different fairness perceptions in relation to their social exchange partners.

Definitions of stakeholders are manifold, but commonly describe stakeholders as anyone that affects or is affected by a business reaching its goals (Freeman, 1984). Stakeholder networks are complex, including a range of internal organizational (such as employees) or external organizational (such as clients, governmental agencies, financial institutions) stakeholders (Parmar et al., 2010). Given our focus on solo entrepreneurs, we study four external stakeholders: governmental agencies, financiers, clients, and unions. The first three stakeholders are generally relevant for many solo entrepreneurs, whereas the focus on unions may be of particular interest in a European setting where unions play a strong institutional role.

Governmental institutions as stakeholders have an interest in a company’s success in generating taxes, innovation, employment, and economic growth, and decide on policies and regulations surrounding entrepreneurial activities (Bosma et al., 2018). Extensive regulations by governments can constitute obstacles for entrepreneurs (Alvarez et al., 2021), and thus, providing assistance or information to entrepreneurs may facilitate entrepreneurial action (Aparicio et al., 2016). Interactions of entrepreneurs with governmental institutions take place via government officials and studies on tax paying have shown that these interactions may be relevant sources for entrepreneurs’ fairness perceptions (Verboon and Goslinga, 2009; Kogler et al., 2015). In other words, entrepreneurs judge the fairness of government officials’ communication, decisions, and information, and over time, form a fairness perception around the government as an institution.

Financiers are also crucial for fairness perceptions of entrepreneurs. Evidence suggests that decisions of financial investments can be biased, for instance, favouring male over female business owners (Johnson et al., 2018). Banks are the most common route to get a loan and a study found that bank loan officials did not use predetermined rules for decision-making or received adequate training, and instead judged loan proposals on personal impressions (Wilson, 2016). Emerging evidence suggests that loan decisions based on algorithms may reproduce prejudices and biases as algorithms are trained on past decisions (Garcia et al., 2024). This mean that fairness perceptions of entrepreneurs regarding financiers may vary.

Clients are another important stakeholder that might shape fairness perceptions (Parmar et al., 2010). The importance of fair exchanges between entrepreneurs and clients has mainly been studied from the clients’ point of view (see for example, Gokmenoglu and Amir, 2021; Mayser and von Wangenheim, 2012). In contrast, fairness perceptions by entrepreneurs concerning relationships with their clients have been scarcely studied but may matter just as much. De Clercq and Rangarajan (2008) found that entrepreneurs’ fairness perceptions from clients correlated positively with their commitment to clients. Most entrepreneurs have several clients and thus it may seem counterintuitive that an entrepreneur can form a cohesive overall fairness perception of their clients. However, it parallels the judgement of fair treatment by colleagues (i.e. several different individuals), for which empirical evidence suggests that individuals form such overall fairness perceptions (Naumann and Bennett, 2000).

Lastly, we include unions as another relevant stakeholder for fairness perceptions of entrepreneurs. A predominant view is that unions and labour unionization are threats to business success (LeCounte, 2024; Wagar and Wilkins, 1996). In Europe, however, unions can take a different role, since solo entrepreneurs can join unions themselves, for instance, to access unemployment insurance and certain income protection (Fulton, 2018). Solo entrepreneurs in the Netherlands joined unions to receive assistance with taxes, legal issues, workshops and network meetings (Jansen, 2020). In Sweden, union density has decreased but was still around 70% in 2023 (Kjellberg, 2023). We propose that entrepreneurs judge whether they feel fairly treated by unions based on their experiences with union officials when asking for assistance or information.

Person-oriented approaches aim to discover the configurations of factors that characterize different types of individuals, i.e. to discover subpopulations in which individuals are similar to one another and in what respects they differ from others (Bergman et al., 2003). Latent profile analyses provide categorizations of qualitatively and quantitatively distinct profiles of experiences within a heterogenous population (Morin et al., 2018). A key advantage is the ability to assess how the configuration of multiple factors (that is typical for each of the subpopulations and differentiates them from one another) relates to external variables.

Within the entrepreneurship literature, person-oriented approaches have been scarcely used although they are particularly useful to study new phenomena (Crum et al., 2022). Based on person-oriented approaches, scholars have studied configurations of entrepreneurs’ personality (Korunka et al., 2003), well-being profiles (Bujacz et al., 2020), and profiles of challenge and threat appraisals (Kleine et al., 2024). Given that fairness perceptions from multiple stakeholders have not been studied before, that their configurations and combined effects are unknown, the use of latent profile analysis offers a suitable exploratory approach. Entrepreneurs are a heterogeneous population, some entrepreneurs likely have high fairness perceptions to all stakeholders, whereas others have not. There may also be those with varying profiles, with high fairness perceptions to clients or financiers, but low fairness perceptions to governments or unions. Since the most typical configurations and their prevalences are unknown, we formulate a research question rather than a hypothesis:

In addition to identifying distinct profiles of stakeholder fairness, we also aim to better understand the profiles by studying differences between profiles in individual and business characteristics. Differences in individual and business characteristics may exist, for instance, given that gender affects the likelihood of getting bank loans (Malmström et al., 2023). It may also be that sector matters for fairness perceptions. We furthermore investigate well-being (career satisfaction, self-rated health) and self-rated job performance as potential consequences of fairness perceptions. SET suggests that fairness perceptions enhance predictability, facilitate securing valued resources and help turn relationships into high-quality social exchanges, and meta-analyses show that employees’ fairness perceptions relate to performance, well-being and health (Colquitt et al., 2013; Robbins et al., 2012). We sample solo entrepreneurs across two time points to explore the relevance of fairness perceptions for outcomes concurrently and prospectively. Our second research question is:

We sampled solo entrepreneurs who own their own business and have no employees, following the occupational definition of entrepreneurs as those who work for themselves at their own risk (Stephan, 2018). Data were collected through postings on webpages of incubators, unions, professional networks, through social media campaigns and postal letters sent to registered businesses. Participants received individualized feedback about their psychological resources after survey completion. The data collection was approved by the ethics committee (blinded for review).

Data collection at T1 lasted from winter 2021 to summer 2022. Inclusion criteria were to have an active registered business in Sweden without employees. Those who answered the survey at T1 and indicated their interest in participating longitudinally were invited to a shorter follow-up questionnaire at T2 around six months later. Informed consent was obtained from all participants. The data collection was approved by the responsible ethics committee (Dnr 2021–03852, Dnr 2022–00626–02, Dnr 2022–01742–02).

At T1, N = 485 eligible solo entrepreneurs participated. Of these, N = 343 were interested in the follow-up, and of these, N = 194 participated at T2 (longitudinal response rate = 40%). Non-response analyses revealed that those who participated at both times indicated higher job performance (M = 3.93 vs. M = 3.67, p < 0.05), higher turnover in the past year (p < 0.05), and were more likely to be entrepreneurs as their main activity (83% vs. 70%, p < 0.001) than those who only participated at T1. No other differences in individual and business characteristics, fairness measures or outcomes were significant.

Because of missing data on all study variables, our analytical sample at T1 was N = 453. Respondents were on average 53 years old (range: 22–87, SD = 12), 63% were women, 56% had a university degree, 70% of all participants lived in the major cities in Sweden, and around 90% of all participants were born in Sweden. For around 75% of participants their business was their main activity, the remainders combined entrepreneurship with organizational employment, retirement, and, in very few cases, studies, sick leave or parental leave. Sixty-three percent of participants had a registered sole proprietorship company, the remaining 37% had a limited company. The average experience as entrepreneur was 12 years (range: 0–55, SD = 10, median: 10 years).

If not stated otherwise, answer scales went from 1 (strongly disagree) to 5 (strongly agree). Original scales in English were translated to Swedish and back-translated to English to check for accuracy of wordings (Brislin, 1970).

We adapted the direct measure of overall fairness from an employee-organizational setting (Ambrose and Schminke, 2009) and phrased the items on stakeholder fairness by starting every item with: “To what extent do you feel fairly treated … ?”, and then adding the stakeholders “By governmental agencies and municipalities”, “By clients”, “By banks or financiers”, “By unions”, and “As entrepreneur”. The first four items were used in the latent profile analysis; the latter item was used as validating variable.

We measured gender (0 = male, 1 = female), age in years, education (0 = below Bachelor level, 1 = Bachelor level or above), child at home (“Do you have children under the age of 18 living at home?”, 0 = no, 1 = yes), having a partner (0 = single, 1 = married, cohabiting, in a relationship). Household contribution was assessed with “How much does your income contribute to the overall household income?”, with the scale 1 (all income, 100%), 2 (more than 50% but less than 100%), 3 (about 50%), 4 (less than 50%). Entrepreneurial experience in years was assessed by “In total, how long have you worked as entrepreneur?” Main work activity was assessed by “Is your work as entrepreneur your main activity?” (0 = no, 1 = yes). Necessity entrepreneurship was measured with one question adapted from the scale on extrinsic contract motivation by Gagné et al. (2010) “I work as entrepreneur because I had no better alternatives for employment” on a scale from 1 (strongly disagree) to 5 (strongly agree).

We measured type of business (0 = sole proprietorship, 1 = limited company) and capital needed with the question “When you started or took over your business, how much capital did you invest?” (answer scale ranging from 1 (very little) to 5 (a lot)). The variable was very skewed (60% answering “very little”) and thus re-coded (0 = very little, little, 1 = above answer options 1 and 2). Turnover was assessed with the question “What is the approximate turnover of your business in the last financial year?”, ranging from 1 (less than 250.000 SEK) to 10 (100.000.000 SEK or more). The options were recoded to 1 (less 250.000 SEK), 2 (250–500.000 SEK), 3 (500–999.000 SEK) and 4 (anything above). Because the question reflected the last financial year, turnover is no outcome variable. Sector was assessed with the Swedish Standard Industrial Classification (SNI), which is based on the European NACE codes. To categorize the 21 codes, we formed four categories, taking into consideration the gender composition on the Swedish labour market (Cerdas et al., 2019): 1 (goods, energy production and machinery, male dominated), 2 (public administration, education, health and social work, female dominated), 3 (knowledge-intensive work, gender-balanced, slightly more men), and 4 (labour-intensive work, gender-balanced, slightly more women).

Overall fairness was asked as summative perception of feeling fairly treated as entrepreneur. Career satisfaction was assessed with the item “I am satisfied with the success I have achieved in my career so far as entrepreneur” from a scale by Greenhaus et al. (1990). Although these concepts were only assessed with one item each, there is extensive evidence on the high validity of one-item measures for such organizational concepts (Matthews et al., 2022). Self-rated job performance was measured with three items (Koopmans et al., 2014), capturing whether entrepreneurs during the previous three months had felt that they had planned optimal, been able to focus on main work assignments and perform their work well within the shortest possible time. Cronbach’s alpha was 0.796 (T1) and 0.806 (T2). Lastly, self-rated health was measured with one item (“How would you rate your general state of health?”) and answered on a 5-point scale ranging from very good to very bad. Scores were reversed so that higher values reflect better health. The validity and reliability of this item has been shown in previous studies (Idler and Benyamini, 1997).

A latent profile analysis (LPA) was conducted in Mplus 8.3. As recommended (Jung and Wickrama, 2008), various statistical criteria and interpretability of the solution were considered to decide the number of latent profiles. We report Akaike information criteria (AIC), Bayesian Information Criteria (BIC), Sample Size Adjusted Bayesian Information Criteria (SABIC), where decreases indicate better fit of model to the data. We also considered the Parametric Bootstrapped Likelihood Ratio Test (BLRT) and the Vuong-Lo-Mendell-Rubin adjusted likelihood ratio test (VLMR-LRT), which indicate whether adding a further profile fits the data better (Jung and Wickrama, 2008). We report entropy values, which is an index of classification accuracy, with values closer to 1 or above 0.80 indicating better precision. We also considered the percentages of individuals in the different profiles, which should include at least 1% (in small samples 5%) of the total sample (Jung and Wickrama, 2008).

Differences between profiles in individual and business characteristics and outcomes were tested with the BCH procedure in Mplus (Asparouhov and Muthén, 2021). For binary and continuous variables, the automatic BCH procedure was used. A significant overall chi-square value indicates overall profile differences, which are followed up by pairwise comparisons between profiles. For multi-categorical variables, the manual BCH procedure was used and odds ratios are provided. Pairwise comparisons are carried out to test profile differences in threshold crossing, e.g. whether the crossing from category 1 to 2 or 2 to 3 is significant.

Table 1 presents model fit indices of the LPA. The BIC value was the lowest with five profiles and increased slightly with six profiles. In the three-profile solution, the entropy value was rather low and the class count rather high. In the five-profile solution, the entropy value decreased compared to the four-profile solution and the class count involved a 2% profile, which is very small. For these reasons, the four-profile solution was retained for the next phase of the analyses.

Figure 1 visualizes the four-profile solution. The profile “Unfair” (N = 128, 28%) was a common profile, characterized by lower-than-average fairness perceptions, particularly regarding financiers. The profile “Fair” (N = 77, 17%) was the least common profile, characterized by above-average fairness perceptions, particularly regarding financiers. The profile “Financiers & Government Agencies Fair” (N = 95, 21%, “Fin & Gov Fair” in short) was characterized by slightly above-average fairness perceptions, particularly regarding governmental agencies and financiers. The most common profile “Average Fair” (N = 153, 34%) revolved around the mean on all stakeholders.

To test the stability of the profile solutions, we randomly split the sample in half and ran the LPA with sample 1 (see Table A1). The four-profile solution in this reduced sample was reasonable to select, given that the entropy value was high, and the class count of the 5-profile solution involved a 1% profile. We then ran another LPA series with subsample 2 (see Table A2) and the visualized four-profile solution with this subsample (see Figure A1) remained very similar to the profile solution from the entire sample. We therefore decided to validate the profiles using the entire sample to have more statistical power.

Table 2 provides the analysis results for differences in profile membership in individual and business characteristics.

For individual characteristics regarding age, members of the “Fair” profile were older (M = 55.95, SD = 13.06) than members of the “Unfair” profile (M = 51.74, SD = 10.52). Regarding years of experience as entrepreneur, members of the profile “Unfair” had longer experience (M = 14.09, SD = 9.75) than members of the profile “Average Fair” (M = 10.61, SD = 10.17). Regarding household contribution, members of the profile “Unfair” had a significantly larger proportion of contributing all household income (33%) compared to the “Fin & Gov Fair” profile (20%). Members of the “Fin & Gov Fair” profile had a higher proportion of contributing around 50% or less to the household than in both profiles “Unfair” and “Fair”.

Regarding business characteristics, differences between profiles were found for capital needed when starting the business. Members of the “Unfair” profile needed more capital compared to the profiles “Fair” and “Average Fair”. In turn, members of the “Fair” profile needed the least amount of capital, less so than “Fin & Gov Fair” and “Average Fair”. Regarding necessity entrepreneurship, members of the “Unfair” profile were more likely than all other profiles to say they started their business due to lack of better alternatives. Members of the profile “Fin & Gov Fair” had a higher proportion of turnover of above 1 mSEK (27%) than the profile “Average fair” (18%). Regarding sector, members of the “Fair” profile operated to a larger extent in knowledge-intensive sectors (business services, IT, finance, insurance operations, real estate businesses), as well as education, health care, social work than the “Unfair” profile. Members of the “Fair” profile worked comparatively less in labour-intensive sectors (travel, support services, culture, entertainment, arts) than the “Unfair” profile and the “Average fair” profile. Members of the “Unfair” profile worked more in labour-intensive sectors compared to members of the “Average fair” profile.

Results regarding differences between profiles in terms of outcome variables are reported in Table 3. Perceptions of overall fairness as entrepreneur at T1 differed between profiles, such that the “Unfair” profile had lowest and the “Fair” profile highest overall fairness perceptions. At T2, the difference descriptively persisted, but only the “Unfair” profile differed significantly from all other profiles. For career satisfaction at T1, members of the profiles “Fair” and “Fin and Gov Fair” had higher values than the two profiles “Unfair” and “Average Fair”. This pattern was very similar even for career satisfaction at T2, with the exception that “Fin & Gov Fair” did not differ significantly from “Average Fair”. Self-rated health at T1 was lowest among the “Unfair” and “Average Fair” profiles and significantly higher for the “Fair” and “Fin & Gov Fair” profile, at T2 the “Unfair” profile maintained the lowest score on health. Regarding job performance at T1, the “Fair” profile had higher scores than the other profiles and the profile “Unfair” had lower scores than the “Fair” and “Fin & Gov Fair” profiles. The “Fair” profile had the highest job performance means even at T2.

To highlight the value of the person-oriented approach, we explored regression approaches with interactions between the stakeholder fairness perceptions (see Table A3 for correlation matrix). This approximates the latent profile approach, that stakeholder fairness perceptions have combined effects. Predicting T1 or T2 work and health outcomes, respectively, by the four stakeholder fairness variables, including all six two-way interactions, three three-way interactions and one four-way interaction resulted in no significant interactions (when using Bonferroni correction for number of interactions included). Predicting T2 work and health outcomes with only the six two-way interactions between all T1 stakeholder fairness revealed one significant interaction (from banks/financiers × clients onto career satisfaction, b = 0.26, p = 0.018). Doing the same for T1 work and health outcomes, we found two significant interactions (governmental agencies × unions, b = 0.07, p = 0.038, and banks/financiers × unions, b = −0.09, p = 0.009), neither of which would be counted as significant with a Bonferroni correction. None of the two-way interactions were significant when predicting T2 work and health outcomes, controlling for T1 work and health outcomes. Secondly, we tested a path model with observed variables only, in which stakeholder fairness perceptions predict overall fairness as entrepreneur, and, in turn, the T2 variables career satisfaction, job performance, and self-rated health, controlled for their T1 scores, mirroring the idea of overall fairness as proximal mediator (Ambrose and Schminke, 2009). Stakeholder fairness perceptions were positively associated with overall fairness as entrepreneur, which, in turn, was positively associated with the outcomes over time (see Figure A2 and Table A4). There were two exceptions: fairness perceptions from unions were not significantly associated with T2 performance, although correlations with T2 performance were significant (r = 0.23, p < 0.01). The association between overall fairness as entrepreneur and performance at T2 was only marginally significant (p = 0.078), despite significant correlation (r = 0.26, p < 0.001). Our chosen latent profile approach extends these variable-oriented analyses in revealing how common different stakeholder fairness configurations are and highlighting the joint contribution of fairness from different sources.

In this article, we studied how solo entrepreneurs feel treated by governmental agencies, clients, banks and unions. Our findings indicate that solo entrepreneurs differ in their fairness perceptions towards these stakeholders, form subgroups with different profiles, and individuals with distinct fairness perceptions profiles differ in their career satisfaction, self-rated health, and self-rated job performance. This is, to our knowledge, the first study to look at fairness perceptions of entrepreneurs in relation to different stakeholders, revealing that fairness from stakeholders matters for entrepreneurs. Thus, this paper provides some first evidence for the relevance to add fairness in stakeholder relations as an important yet overlooked work environment factor. As entrepreneurs are embedded in stakeholder relationships, we emphasize that different stakeholder profiles play distinct roles in entrepreneurs’ work environment. Understanding which entrepreneurs perceive which stakeholder to treat them fairly or unfairly can provide new insights for entrepreneurship and fairness theory.

One aim of the study was to explore entrepreneurs’ fairness perceptions in relation to well-being and performance outcomes. Results showed large differences between profiles in career satisfaction, self-rated health and job performance. The findings extend efforts of studying psychological aspects for predicting well-being and health of entrepreneurs (Wiklund et al., 2019; Frese and Gielnik, 2023; Stephan, 2018). The psychology of entrepreneurs’ literature has outlined multiple entrepreneurial work environment factors and their effects on business performance, well-being and health (Davidsson, 2016; Gielnik et al., 2020; Stephan, 2018). Despite these advances, the quality of interactions with stakeholders has been overlooked so far, leaving a blind spot of an important aspect of entrepreneurs’ daily working life. Complementing this stream of literature, we suggest that fairness perceptions from stakeholders are an ingredient of the work environment with importance for entrepreneurs’ satisfaction and health, which are critical ingredients for business success and survival. Further, we add to the growing evidence that social and interpersonal relations between entrepreneurs and their social exchange partners matter in the wider entrepreneurial local ecosystem (Cunningham et al., 2019; Roundy and Burke-Smalley, 2022), since we illuminate on the role of building high-qualitative exchange relationships. For better understanding the local ecosystem of entrepreneurs, it may be relevant to consider fairness aspects. This may also help better understand loneliness, as it is often assumed that solo entrepreneurs work in isolation (Stephan, 2018). Our results highlight that solo entrepreneurs have social interactions and relationships with various stakeholders, and the quality of these may matter for well-being and performance. More research into these stakeholder relations might provide more insights into how entrepreneurs manage loneliness. It would also be valuable to study fairness perceptions of entrepreneurs vis-à-vis other work environment factors.

Importantly, we asked participants to indicate whether they feel fairly treated, which is in line with the tradition to view fairness as descriptive concept (Eib and Cropanzano, 2023). While other scholars have suggested to look at entrepreneurs as actors of justice, or that entrepreneurs should treat their stakeholders responsibly (Bosse et al., 2022), we argue that entrepreneurs’ own fairness perceptions from different stakeholders also matters. Entrepreneurs are typically ascribed high psychological resources and high agency (Baron et al., 2016). One could therefore assume that entrepreneurs would not perceive unfairness or would use their agency and take action to circumvent unfair treatment. Our results, although limited in that the data do not allow causal inferences, challenge this assumption, as there was a large variety in the solo entrepreneurs’ fairness perceptions. Of particular interest are further studies on mixed profiles’ (combination of higher and lower fairness perceptions from different stakeholders) association with well-being and venture success over time. The subjective nature of the fairness concept opens a variety of future research directions: we do not know what entrepreneurs regard as fair, what expectations they have, and how their fairness perceptions are formed. The results do underline the heterogeneity of solo entrepreneurs, an aspect that scholars have emphasized as warranting further research (Pahnke and Welter, 2019).

The found profiles varied quantitatively and qualitatively, each displaying a unique configuration of fairness perceptions. This is important for theory development since it reveals that entrepreneurs form unique exchanges with their different stakeholders, and these relations can differ and combine in various ways. With this, we offer a novel approach of considering the joint contribution of fairness from multiple stakeholders and examine different configurations of fairness perceptions through a person-oriented approach, complementing traditional variable-oriented approaches (Bergman et al., 2003; Bobocel, 2021). This responds to the call for more in-depth analyses of the role that various sources together play in shaping fairness perceptions (Bobocel, 2021). Despite ample evidence that individuals form fairness perceptions in relation to different sources (Lavelle et al., 2015), the idea of considering these different sources simultaneously has novelty and also provides a more realistic view of how individuals judge their environment, i.e. making judgements of the quality of multiple stakeholder relationships.

The differences in fairness perceptions regarding different institutions were also notable. The results suggest that fairness perceptions from governments and financiers are relevant for well-being and performance. This aligns with stakeholder theory, suggesting entrepreneurs are more vulnerable to some stakeholders than others (Pinelli et al., 2021). While it may be possible to replace clients, avoiding contact with a specific governmental agency is often impossible. Future research should explore how entrepreneurs form fairness perceptions of institutions, and what role institutional representatives play. The different justice dimensions, like procedural or interactional justice, may provide suitable guidelines to capture how interactions with institutions develop (Colquitt et al., 2022). It remains unclear whether logics of formal procedures, decisions, speed of decisions or language use matters most. It is possible that fairness perceptions with institutions are formed based on limited information and stay stable unless disrupted by major events (Jones and Skarlicki, 2013). Entrepreneurs with formed opinions about institutions (Wagar and Wilkins, 1996) may avoid interactions, limiting opportunities to change fairness perceptions. This raises questions about how malleable fairness perceptions of entrepreneurs are towards institutions, and what drives changes in fairness perceptions.

The studied solo entrepreneurs generally perceived clients as fairer than the other stakeholders. Future research could examine how factors like number of clients, dependency and relationship length shape these perceptions. Based on SET (Cropanzano and Mitchell, 2005), resources affect power differentials, such that greater dependency on a major client may result in entrepreneurs accepting unfair treatment. Dependency on particular clients can be higher for newly started businesses (Yli-Renko et al., 2020), but the “Unfair” profile in this study had an average of 14 years of entrepreneurial experience, meaning that it may be difficult for some businesses to exit less rewarding client relationship Studying why interactions with social exchange partners, who are perceived as unfair are ongoing may be warranted, given the toll this can take on health and well-being (Eib and Cropanzano, 2023).

Given the benefits of belonging to the “Fair” profile, it is relevant to discuss what differentiates this profile. Members of the “Fair” profile were slightly older, experienced, in the knowledge-intensive sector, and required little startup capital. Only 68% had their business as main activity (compared to the “Average Fair” profile with 79%). Hybrid entrepreneurs are often viewed as less entrepreneurial (Frese and Gielnik, 2023), combining employment with a business before becoming entrepreneurs full-time once their business is profitable (Raffiee and Feng, 2014). However, many of the entrepreneurs in the “Fair” profile had other commitments and a long entrepreneurial experience, showing that hybrid entrepreneurship may not be as fleeting as the literature suggests. It may even enhance fairness perceptions by reducing dependency on stakeholders and venture success.

The results regarding needed capital highlight an interesting aspect. While the importance of capital is well-known in the literature, particularly for small businesses (Wiklund and Shepherd, 2005), capital needed when starting is a concept that may have more downhill effects than currently suggested in the literature. Although a retrospective perception, the concept better distinguished between stakeholder fairness profiles than turnover. This suggests that the starting phase may be a pivotal moment for forming fairness perceptions with stakeholders. Early interactions with financial institutions may inform long-term decisions, like avoiding faster growth to sidestep further loan negotiations. From the perspective of SET (Cropanzano and Mitchell, 2005), while bank officials make decisions regarding multiple entrepreneurs using a certain frame of reference (Wilson, 2016), entrepreneurs engage only with few bank officials, having only one house to put up as collateral. Future research should explore how different reference frames and expectations of bank officials and entrepreneurs form, collide or accord, and what consequences these perspectives have on decisions.

Our study has limitations that are important to discuss, which provide further research opportunities. Data were based on subjective measures, but as fairness is a subjective perception, this approach is reasonable. It would have been a good addition to also assess outcomes with other means than subjective ratings. While we have related profiles to outcomes over time, we cannot assess the stability of profiles, and it cannot be ruled out that profile membership fluctuates or changes with time. It would be of great value to measure fairness perceptions in relation to stakeholders multiple times to test how social exchange relationships between entrepreneurs and stakeholders develop in different stages of their relationship (Huang and Knight, 2017). An advantage of person-oriented analyses is that common method variance is very unlikely to have played a role (Meyer and Morin, 2016). We followed common strategies of survey design to minimize biases, ensuring participant anonymity, varying response formats and separating measurements in the survey (Podsakoff et al., 2012). Data are limited in that causal conclusions cannot be drawn, nor can we exclude the possibility that third variables explain some of these relationships. Our sample included 63% women, whereas in Sweden only around 33% of solo entrepreneurs were women in 2022 (Eurostat, 2022). Our sample was highly educated (56% had a university degree); compared to the national average where about 50% of female solo entrepreneurs and 37% of male solo entrepreneurs in Sweden have a tertiary education (Eurostat, 2022). However there is also evidence that solo entrepreneurs have higher educational attainment (van der Zwan and Hessels, 2019).

Furthermore, all participants were solo entrepreneurs, which was a deliberate choice for the purpose of this study. Among all businesses in Sweden in 2022, about 74% were run alone without employees (Statistics Sweden, 2025), thus solo entrepreneurs is a relevant group of entrepreneurs in Sweden. Most businesses in OECD countries are run by solo entrepreneurs (Eurostat, 2022; van der Zwan and Hessels, 2019). Future research is warranted on employer-entrepreneurs, to also consider internal stakeholders like employees, which enables studying how entrepreneurs enact fairness towards their employees. Investigating how entrepreneurs impact employees through enactment of justice-related principles would follow the call by Wiklund et al. (2019) to study how entrepreneurs impact their stakeholders. Future studies should consider the dependency status of solo entrepreneurs in shaping fairness perceptions (Millán et al., 2020). It would also be interesting to study how algorithmic decision-making from banks or financial institutions are perceived by entrepreneurs. The idea is that loan decisions based on machine learning is less subjective (Garcia et al., 2024) but empirical research is needed to understand how such loan decisions are received, and how notifications can be made that allow explanations and justifications to be perceived as fair.

Members of the relatively large “Unfair” profile indicated lower career satisfaction, self-rated health and job performance even after six months. While some may question whether fairness is even expected, the results of the current study indicate that, just like all other individuals (Cropanzano et al., 2001), entrepreneurs want to feel fairly treated. Policymakers and practitioners interested in fostering sustainable entrepreneurship should consider entrepreneurs’ fairness perceptions, particularly fair treatment from financiers and governmental agencies might be relevant to create a positive work environment for entrepreneurs. These stakeholders could oversee their procedures to communicate with entrepreneurs, considering that fairness is shaped by decisions but also by information and interpersonal treatment. Results revealed that capital needed when starting their business was important for fairness perceptions of entrepreneurs. Thus, funding availability at the start of the business may be important, likely more so for young individuals, those with no prior entrepreneurial experience, or with less savings. Furthermore, fairness perceptions were unequally distributed across sectors, and entrepreneurs in labour-intensive sectors, here mostly culture, entertainment, and art – all services much needed for society, may be at risk of developing health problems. Practically, this may signal that rule transparency and regulatory clarity of governmental agencies and financiers need improvement for businesses in these sectors. Unfairness perceptions are often linked to unmet expectations. In a country like Sweden, where rule of law governs, the fact that entrepreneurs did not perceive fair treatment from institutions is striking and begs for remedies, be it in the form of more education to potential business owners or clearer guidelines for institutions. From an individual entrepreneurs’ perspective, our results show that certain circumstances are more common in the “Fair” profile: being older, not having children at home, combining entrepreneurship with something else, low entry capital need, and being an opportunity entrepreneur. Changing unfavourable circumstances may be impossible, so that interventions to cope with unfairness are needed (see Barclay and Saldanha, 2015). Individuals could also seek collective voice (e.g. via unions) to address unfair practices. However, the most effective approach may be to combine individual-level strategies (coping, resilience) with systemic changes (transparent institutions, fair procurement).

This study highlights the importance of the perceptions of fair conduct by stakeholders for entrepreneurs. Entrepreneurs interact with individuals and institutions in multiple transactions, and whether they feel these transactions are fair or not provides an important ingredient to their psychosocial work environment shaping their satisfaction, health, and performance.