Abstract
Purpose
This research aims to investigate whether, in a principal–agent relationship, personal characteristics of the agent (seniority, locus of control (LOC), self-efficacy (SE), risk appetite (RA)) have an impact on their performance, on costs for the principal and on organizational justice (distributive justice (DJ) especially) in a sample of insurance brokers.
Design/methodology/approach
The adopted structural equation modeling (SEM) analysis highlights the different role that personal characteristics play in affecting or moderating the agent’s performance. Moreover, the mediation analysis highlights the role played by gender and tenure in moderating the relationship between personal characteristics and work outcomes.
Findings
The findings of this study suggest that an agency relationship is not based only on rational choices made by the principal and agent in their own self-interest, but also by other idiosyncratic factors that influence the outcome of the relationship.
Research limitations/implications
In order to better understand the agent’s behaviour, agency relationship investigation should consider other psychological variables in addition to the traditionally considered risk orientation, uncertainty and information asymmetry.
Practical implications
This study gives specific insights into preventing undesired behaviours, e.g. organizational withdrawal, opportunism, high staff/employee turnover, as advocated by current literature.
Originality/value
By systemically investigating and analysing personal characteristics of the agent such as LOC, agent’s SE and RA, this study provides an original contribution to the knowledge on the determinants of costs and effectiveness in the agency relationship.
Keywords
Citation
Ferrari, F. (2024), "Balancing efficiency and fairness in an output-based agency relationship: an empirical investigation of the cognitive factors favouring a win–win situation", Evidence-based HRM, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/EBHRM-03-2024-0060
Publisher
:Emerald Publishing Limited
Copyright © 2024, Filippo Ferrari
License
Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at http://creativecommons.org/licences/by/4.0/legalcode
Introduction
Agency theory (AT) traditionally examines company–worker relationships through economic and contractual lenses, emphasizing mechanisms like output-based and performance-based pay. Efficiency in these relationships is typically dictated by situational factors, with the assumption that agency costs rise alongside uncertainty and the risk aversion of both the principal and agent (Eisenhardt, 1989; Chung et al., 2020). In output-based contracts, aligning agent goals with the principal’s objectives occurs by tying compensation to measurable outcomes, thus transferring risk to the agent. However, perceived unfairness in such contracts can lead to undesirable behaviors, such as increased turnover and opportunism, which elevate agency costs (Gläser et al., 2022).
Recent literature suggests a socially embedded model of AT, integrating cognitive and social factors, including fairness, to align principal–agent goals, thereby reducing cooperation barriers and agency costs (Larkin et al., 2012; Cuevas-Rodríguez et al., 2012). Balancing efficiency requirements with fairness remains challenging; while efficiency for the principal is tied to reducing losses and boosting revenue, fairness (distributive justice (DJ) for the agent hinges on the equitable distribution of rewards and responsibilities (Colquitt et al., 2001). Establishing a win–win equilibrium—benefiting both parties economically and psychologically—is essential for supporting cooperation, reducing risk and enhancing organizational performance (Bosse and Phillips, 2016; Casadesus-Masanell, 2004).
Fairness, especially DJ, is instrumental in mitigating agency issues. For instance, perceived unfairness in CEO compensation can foster excessive risk-taking (Jain et al., 2024), while unfair equity incentives might drive unethical practices like underfunding pensions (Martin et al., 2020). Khandelwal et al. (2023) further highlight that unresolved agency issues negatively impact corporate performance, emphasizing that addressing fairness can improve outcomes. While fairness is increasingly acknowledged in AT literature, cognitive and psychological factors influencing agents' perceptions of fairness remain underexplored (Graso et al., 2020).
Research suggests dispositional traits—locus of control (LOC), self-efficacy (SE) and risk appetite (RA)—might moderate fairness perceptions, shaping motivation and performance in AT dynamics (Chung et al., 2020; Ma and Wang, 2022). Including such traits in AT would create a more nuanced framework, moving beyond traditional economic models centered solely on quantifiable variables like risk and reward (Bosse and Phillips, 2016; Klein and Colauto, 2020). However, incorporating these cognitive elements requires interdisciplinary collaboration due to methodological complexities (Perrow, 1986).
With organizations increasingly adopting performance-driven environments, understanding the impact of cognitive factors on agent behavior is essential (Larkin et al., 2012). DJ is shaped not only by reward fairness but also by individual traits like LOC, SE and RA, which influence agents' responses to performance-based systems (Bosse and Phillips, 2016; Locke and Latham, 1990; Rauh and Seccia, 2010). This study seeks to examine the interaction between cognitive factors and economic incentives in output-based agency relationships, expanding AT to incorporate cognitive psychology and economic models for a comprehensive framework on agent behavior. The hypotheses explore LOC, SE and RA’s impact on balancing efficiency and fairness in the principal–agent dynamic, in line with Ferrari’s (2014) seminal work on achieving a win–win agency relationship.
Theoretical background
Traditional AT describes the principal–agent relationship where the agent acts in the principal’s interest in exchange for a reward (Jensen and Meckling, 1976). While AT traditionally centers on economic incentives, recent literature highlights the psychological impact of reward structures, particularly in pay-for-performance systems. Studies show that perceptions of unfair compensation can intensify risk-taking behavior, complicating the principal–agent dynamic. For instance, Jain et al. (2024) demonstrate that unfair compensation amplifies risk, while Martin et al. (2020) point out ethical concerns, such as the link between unfair CEO incentives and pension underfunding, highlighting the need for fairness to mitigate risk and opportunism. Khandelwal et al. (2023) further argue that agency issues significantly affect corporate performance, underscoring the importance of incorporating cognitive factors to address justice and motivation.
In addition to economic incentives, studies increasingly recognize intrinsic factors like LOC, SE and RA as influential on goal-performance relationships, impacting perceived justice levels (Bosse and Phillips, 2016; Locke and Latham, 1990; Rauh and Seccia, 2010). In output-based agency relationships, an agent’s RA is anticipated to correlate with their perception of DJ. Agents with a high RA are drawn to performance-based incentives, aligning with their risk-taking tendencies and perceiving rewards as fair, unlike risk-averse agents who may view such systems as unjust (Allen et al., 2010).
Despite these insights, research on the RA–DJ relationship remains limited, with fragmented findings. For instance, risk-seeking agents may not value procedural fairness in the same way as risk-averse agents (Van Koten et al., 2013), while fair treatment lowers uncertainty for risk-averse agents but has less impact on risk seekers (Richards et al., 2016). Additionally, high-income-focused agents often prefer output-based contracts for potential earnings. Overall, more research is needed to clarify the RA–DJ link in output-based agency relationships. To address these theoretical and empirical limitations, this paper aims to test the following hypothesis:
In an output-based agency relationship, the agent’s RA level is positively correlated with their Distributive Justice (DJ) level.
Recent research highlights the significance of LOC—an individual’s belief in controlling outcomes either through their own actions (internal LOC) or due to external factors like luck (external LOC) (Robbins and Judge, 2013)—in influencing job roles within pay-for-performance frameworks. Individuals with an internal LOC tend to have a lower perception of risk (Adams, 2024) and are likely to excel in output-based contracts, attributing successes and failures to their efforts, which strengthens their perception of DJ (Adams, 2024; Lewin and Sager, 2010). Conversely, those with an external LOC often feel less in control, perceive situations as unfair, and overestimate risks, resulting in reluctance toward output-based contracts and greater performance anxiety (Robbins and Judge, 2013).
Despite its relevance, LOC has been largely neglected in AT literature, which traditionally focuses on economic and contractual factors (Klein and Colauto, 2020; Bahadır and Levent, 2022). The current understanding of the LOC-DJ relationship is limited, with mixed findings influenced by variations in measurement methods, organizational culture, and industry contexts (Beuren et al., 2015). These complexities highlight the need for further research to clarify how LOC impacts DJ perceptions within agency relationships, expanding knowledge on AT and providing a more nuanced understanding of agent behavior. To address these theoretical and empirical limitations and provide deeper insights into how individual traits affect perceptions of fairness, this paper aims to test the following hypothesis:
In an output-based agency relationship, the agent’s internal LOC level is positively correlated with their DJ level.
SE, defined as the belief in one’s capability to achieve desired outcomes (Bandura, 1997), significantly influences motivation, persistence, and performance, particularly in challenging roles like management and sales (Lewin and Sager, 2010). In output-based contracts, where compensation is performance-tied, agents with high SE perceive themselves as capable of meeting expectations, impacting their risk assessment and task evaluation positively (Porter et al., 2008). High SE enables agents to view challenges as growth opportunities rather than threats, often leading to fairer task evaluations and underestimated task difficulty (Gist and Mitchell, 1992).
Despite its importance, SE is underexplored in AT, which tends to focus on economic factors (Ferrari, 2023). While some studies examine the Principal’s SE, few focus on the Agent’s SE. Research indicates that SE may negatively correlate with pay satisfaction (Kim et al., 2008) and that organizational justice moderates the SE-performance link, especially at lower SE levels (Kim et al., 2022). Conflicting results on SE’s relationship with DJ suggest that individual and situational factors impact this link, underscoring the need for further empirical exploration.
In an output-based agency relationship, the agent’s SE level is positively correlated with their DJ level
In output-based agency relationships, SE is generally linked to improved performance due to heightened motivation and persistence (Bandura, 1997). However, high SE can also lead to overconfidence, which poses risks in performance-tied contracts (Ferrari, 2023; Singh, 2020). Overconfident agents often underestimate risks and resources, overlook their limitations in controlling outcomes, and may make poor decisions (Hayward et al., 2006; Simon et al., 2000). Research by Larkin et al. (2012) shows that overconfidence diminishes the effectiveness of performance-based compensation by increasing psychological costs, logical errors, and potential financial losses (Vancouver et al., 2002).
Despite the implications, the SE-overconfidence-financial loss relationship remains underexplored in AT, which predominantly focuses on economic and contractual elements (Singh, 2020; Ferrari, 2023). This gap highlights an opportunity to blend cognitive psychology with economic theories, investigating how SE impacts financial outcomes through overconfidence (Simon et al., 2000). Such integration could refine AT models and improve risk management strategies, though further empirical research is needed to validate these findings across various organizational contexts. Given the available empirical literature and its limitations, it is possible to formulate the following hypothesis:
In an output-based agency relationship, the agent’s SE level is positively correlated with financial losses.
In output-based agency relationships, SE is generally expected to positively correlate with work performance (WP), as it drives agents to persist in their goals, viewing setbacks as challenges rather than failures (Bandura, 1997; Markman et al., 2002). High-SE agents exhibit resilience and a strong sense of control, leading to increased motivation and effort, particularly in contracts where rewards are tied to specific targets (Yagil et al., 2023; Stajkovic and Luthans, 1998).
However, the relationship between SE and performance is complex. Excessively high SE can lead to overconfidence, unrealistic goal-setting, and ultimately poorer outcomes (Vancouver et al., 2002; Vancouver and Purl, 2017). The literature presents mixed results on this relationship, suggesting that factors such as task complexity and environmental demands may moderate the SE-WP link (Iroegbu, 2015).
SE’s impact on WP is underexplored in AT, which typically emphasizes economic incentives. Investigating SE’s influence, including how overconfidence affects performance, could deepen AT by integrating cognitive psychology, thus offering new insights into agent decision-making and behavior (Yeo and Neal, 2006; Simon et al., 2000). Considering this theoretical scenario (and its limitations), the following hypothesis can be formulated:
In an output-based agency relationship, the agent’s SE level is positively correlated with WP level.
Figure 1 shows the hypothesis system.
Methodology
Independent variables
According to the above mentioned literature, three characteristics were considered:
- (1)
LOC measured with the Italian version of the LOC scale of Farma and Cortinovis (2001) (12 items, Cronbach’s alpha = 0.79). An example of an item is “I believe my future is determined by luck or chance [Credo che il mio futuro sia determinato dalla fortuna o dal caso]”
- (2)
RA measured with the Italian version of the Financial Risk assessment instrument (Grable and Lytton, 2003; 12 items, Cronbach’s alpha = 0.74). An example of an item is “Based on your experience, how much are you investing in stocks or mutual funds? [In base alla tua esperienza, quanto investi in azioni o fondi comuni di investimento?]”
- (3)
SE measured with the Italian version of the SE scale of Sibilia et al. (1995) (10 items, Cronbach’s alpha = 0.79). An example of an item is “When I am faced with a problem, I usually find several solutions” [Quando mi trovo di fronte an un problema, di solito trovo diverse soluzioni].
Dependent variables
Three factors of interest to the Agent and/or the Principal were considered:
- (1)
DJ measured with the sub-scale of Colquitt’s Organizational Justice scale, Italian version (4 items, Cronbach’s Alpha = 0.86); An example of an item is “Are the resources you received justified, considering your performance?” [Le risorse che hai ricevuto rispecchiano gli sforzi da te sostenuti?]
- (2)
Individual performance measured considering the ratio of premiums collected/claims settled (Income/Claims ratio)
- (3)
Costs for the company measured by considering the financial losses resulting from unpaid policies (in Euros).
Control variables: gender and tenure
A key research question is whether, and how, an Agent’s gender affects motivation, behaviors, and outcomes within the Principal-Agent framework, though empirical findings remain inconclusive (Lewin and Sager, 2010; Paltseva, 2019). Studies indicate women generally display higher risk aversion than men (Parrotta and Smith, 2013), yet lab-based research may underestimate women’s risk tolerance (Roszkowski and Grable, 2005). Consequently, gender is treated as a control variable in this study.
The study also considers Agent tenure as a control variable, categorizing tenure into up to 5 years, 6–15 years, and over 15 years. Experienced agents tend to be valuable assets, as maturity in sales often correlates with confidence in variable compensation earnings (Onyemah and Anderson, 2009). Research also links increased tenure with both higher motivation and a potential rise in overconfidence, particularly as expertise develops (Chen et al., 2020; Ma and Wang, 2022; Lee et al., 2022).
Findings
The survey was carried out on a sample (N = 173) of Italian brokers in the insurance sector. A power analysis was carried out to identify the sample size required to detect a given difference in a single mean with specified power (99) and significance (0.05): the sample dimension (n = 173) satisfied these methodological needs.
A structural equation modeling (SEM) analysis was conducted to verify the hypotheses. Figure 1 shows the path diagram of the SEM analysis. All hypotheses are supported by findings.
The model shows a good fit (AIC = 724.677; BIC = 767.174 with n = 173), confirmed by additional fit measures: Comparative Fit Index = 0.998; Tucker-Lewis Index = 0.971. Table 1 shows the parameter estimates of the model.
Given the large correlations and number of variables in the analysis, multicollinearity among variables is possible. Therefore, a test for multicollinearity has been carried out, and the variance inflation factors (VIF) has been reported. The results of the test are as follows: WP: R2 = 0.213; VIF = 1.270; DJ: R2 = 0.327; VIF = 1.485; and Los: R2 = 0.092; VIF = 1.100). Therefore, common method bias – CMB due to multicollinearity among variables can be excluded (Kock, 2017).
To explore the differences among participants for the gender control variable, a series of univariate ANOVAs were conducted. After checking homoscedasticity with an F-test: DJ (F(1, 172) = 0.800, p = 0.373) was found not to be related to gender. Financial losses (Los F(1, 173) = 4.284, p = 0.041) and WP (WP= (F(1, 173) = 15.391, p < 0.01), significantly differ between males and females. The average WP of male agents is significantly greater, but the financial losses they generate are also on average greater. Considering personal characteristics, only the SE was significantly higher in males: (F(1, 172) = 10.080, p = 0.002).
To further explore the differences among participants for the tenure control variable, a series of univariate ANOVAs were conducted. After checking homoscedasticity with an F-test: WP (F(1, 173) = 9.331, p < 0.01) and DJ (F(1, 173)) = 6.889, p = 0.002) were found to be related to seniority. Financial losses (F(1, 173) = 0.606, p = 0.548) were not found to be related to seniority. The seniority range with the highest performance levels is the intermediate one (from 6 to 15 years of tenure); that showing the lowest levels of DJ is up to 5 years. Considering personal characteristics, only the LOC was found to be related to seniority (F(2, 172) = 23.344, p = 0.001)). Once again, the range with the highest internal LOC levels is the intermediate one (6–15 years of tenure).
Discussion
Personal characteristics create a “cognitive framework” that shapes behavior within Agency Relationships (Wiseman et al., 2012). This framework should incorporate both organizational justice and Agent performance efficiency to optimize outcomes (Ferrari, 2014). While literature addresses pay-for-performance impacts, it often neglects balancing the Principal’s efficiency needs with the agent’s fairness concerns (Alavi et al., 2024; Gupta et al., 2024). This study investigates cognitive factors influencing efficiency, performance, and DJ to achieve a balanced principal–agent relationship. The findings are discussed below in light of these objectives and the available theoretical evidence.
Recent studies (Arnold et al., 2024; Prigge et al., 2024) highlight the psychological impacts of pay-for-performance, aligning with this research’s examination of how the agent’s RA influences their perception of DJ in output-based contracts. Findings confirm H1, supporting agents with high RA tend to perceive DJ positively in such contracts, suggesting that leveraging high RA can reduce turnover and opportunism, thus promoting organizational justice and efficiency. The study also shows that agents view reward systems as fair when aligned with their motivations (Allen et al., 2010; Kashyap et al., 2007). This highlights the importance of considering RA in fairness perceptions, supporting the integration of psychological dimensions, like fairness, motivation, and trust, into AT (Dughera and Marciano, 2022). By demonstrating RA’s positive influence on DJ, the study advocates for output-based contracts to balance efficiency and fairness (Eisenhardt, 1989; Van Koten et al., 2013).
The study supports H2, showing that agents with an internal LOC—those who believe they influence their own outcomes—perceive output-based contracts as fair, as rewards align with their performance. This aligns with findings that internal LOC agents fit well within performance-based systems, attributing success and failure to personal effort (Adams, 2024; Bahadır and Levent, 2022; Robbins and Judge, 2013). The research also notes a curvilinear relationship between internal LOC and tenure, peaking at intermediate experience levels (6–15 years), which correlates with higher performance and perceptions of DJ (Robbins and Judge, 2013; Lewin and Sager, 2010). By highlighting internal LOC’s role in fostering accountability and performance, the study suggests incorporating LOC into cognitive frameworks to balance efficiency and justice in Agency Relationships, addressing research gaps on LOC and DJ (Klein and Colauto, 2020; Beuren et al., 2015).
The study supports H3, demonstrating that SE plays a significant role in enhancing perceptions of DJ within agency relationships. It shows that agents with high SE levels are more likely to perceive outcomes as fair, aligning SE with the AT cognitive framework for its positive effects on DJ. High SE correlates with increased motivation, persistence, and performance, particularly in output-based contracts (Porter et al., 2008). This aligns with findings by Kim et al. (2022), indicating that organizational justice moderates the SE-performance link, especially when fairness is emphasized. The study supports Ferrari’s (2023) view that SE impacts agent behavior and evaluations. Despite varying findings due to measurement differences (Stajkovic and Luthans, 1998), the study advocates integrating SE into AT models systematically, enhancing understanding of SE’s role in DJ across organizational contexts (Cuevas-Rodríguez et al., 2012).
The study, supporting H4, explores the nuanced role of SE in agency relationships, addressing gaps in the literature where SE’s relationship with overconfidence and performance outcomes remains inconclusive (Ferrari, 2023; Singh, 2020). Findings show that while high SE often correlates with better performance, it can also foster overconfidence, especially in output-based contracts under high performance pressure (Singh, 2020). This overconfidence may lead agents to underestimate risks and engage in risky behaviors, resulting in financial losses (Ferrari, 2023; Hayward et al., 2006). Additionally, high-SE agents may make resource allocation errors due to inflated confidence, as noted by Shane and Stuart (2002), further impacting financial outcomes. This aligns with Larkin et al.’s (2012) claim that overconfidence can reduce performance-based compensation effectiveness. The study underscores SE’s dual effects on performance and financial risk, recommending cautious interpretation of income-based measures within certain contexts (Wiseman et al., 2012).
The study supports H5, affirming the complex relationship between SE and WP. While SE is widely recognized to drive motivation and persistence (Bandura, 1997; Stajkovic and Luthans, 1998), prior studies have shown mixed results, with some finding positive, negative, or no correlations (Iroegbu, 2015). This study expands on the theoretical framework by showing that high SE can boost agents' confidence in controlling outcomes, enhancing motivation (Yagil et al., 2023). However, the findings also align with Vancouver and colleagues’ (2002, 2017) caution about the risks of excessive SE, including overconfidence and unrealistic goals. These results highlight the need for a balanced approach when incorporating SE into output-based contracts, ensuring alignment with realistic performance goals and supportive organizational structures to maximize effectiveness and prevent negative outcomes.
Given the complexity of the scenario and the numerous relationships between the variables, the SEM analysis was supplemented with a mediation analysis to measure both direct and indirect relationships between the variables. Interestingly, the mediation analysis shows that in this sample SE does not have a direct effect on WP (r = 0.256, p = 0.067). The findings instead show a mediating effect of LOC, and the results confirm the total effect of SE on WP (r = 0.367, p = 0.015) becomes significant only when LOC moderates the relationship. While high SE generally predicts better performance by enhancing motivation and persistence (Stajkovic and Luthans, 1998), findings introduce the crucial role of LOC as a mediator, influencing how SE translates into actual performance within specific agency contexts. Table 2 shows the parameter estimates of the mediation analysis.
The analysis reveals that SE is significantly higher in males, who exhibit better WP but also greater financial losses. SE alone does not directly affect WP or financial losses in males; its impact becomes significant only when mediated by high levels of internal LOC. For females, LOC significantly mediates the negative relationship between SE and WP, which is otherwise not significant. SE does not have a significant impact on financial losses in females, contrary to hypothesis H4. Table 3 summarizes the parameter estimates of the mediation analysis by gender.
The study suggests that SE can lead to overconfidence, especially in male agents, resulting in potentially negative outcomes. Although both genders initially exhibit similar RA, the overconfidence observed in males likely arises from factors beyond the current model. Psychological research indicates that high SE, particularly under performance pressure, can lead agents to overestimate their abilities and underestimate risks (Singh, 2020). This tendency is pronounced in output-based contracts, where high SE agents may view tasks as less challenging and overlook obstacles, reinforcing a distorted sense of control (Bandura, 1997). This overconfidence, fueled by outcome pressure, often leads agents to take excessive risks, ignore market changes or resource constraints, and selectively focus on favorable information (Hayward et al., 2006; Shane and Stuart, 2002; Simon et al., 2000). Men are also culturally predisposed to greater risk-taking and competitiveness (Harris and Jenkins, 2006).
LOC further influences this dynamic. While LOC positively impacts WP and DJ perceptions across genders, combining high SE and LOC in males can increase overconfidence, particularly in financial decisions. Conversely, females with high LOC make more cautious choices, which reduces ambiguity but may limit WP (Roszkowski and Grable, 2005). Since RA is similar across genders and unrelated to WP or financial losses, these LOC differences are likely tied to known gender distinctions: men focus on potential gains, while women consider potential costs (Niederle and Vesterlund, 2007). This study contributes to existing research by examining the gendered effects of SE, RA and LOC, highlighting the need to consider gender differences in pay-for-performance systems and addressing gaps in prior research (Arnold et al., 2024; Paltseva, 2019).
Conclusions
This study suggests that agency relationships are influenced not only by rational self-interest but also by complex, idiosyncratic factors that shape outcomes. The findings emphasize a need for systemic analysis of the antecedents, consequences and moderating factors within a “cognitive framework.” SEM reveals that personal characteristics significantly impact the Agent’s performance with variations based on gender and tenure. DJ also plays a key role in these dynamics; for example, Jain et al. (2024) indicate that perceived unfairness can increase risk-taking, while Khandelwal et al. (2023) highlight how fairness issues can harm corporate performance.
To achieve a balanced, economically profitable agency relationship, as suggested by Bosse and Phillips (2016) and Perrow (1986), the study recommends developing dispositional variables such as LOC, RA and SE. Fair compensation structures, as emphasized by Martin et al. (2020), help align agents’ risk preferences with organizational goals, reducing opportunism and promoting responsible risk-taking. Extending Wiseman and Gomez-Mejia’s (1998) behavioral agency model, the study suggests that agency relationships should account for factors beyond risk and uncertainty, with LOC being key to predicting performance and moderating outcomes by gender and career stage. Schijven et al. (2024) add that governance mechanisms enhance learning and improve long-term results.
Overall, this research highlights the importance of balancing fairness, cognitive factors and risk management in agency relationships to achieve sustainable outcomes. A win–win equilibrium that balances the agent’s DJ with the principal’s profitability relies on optimizing levels of LOC, RA and SE, as Ferrari (2014) notes, fostering a mutually beneficial agency relationship. Figure 2 illustrates this equilibrium, formalizing the study’s findings.
This research also highlights the need for a tailored, systemic and contextualized approach in each agency relationship to prevent opportunistic agent behavior and ensure fairness in outcomes. In doing so, it offers valuable contributions to the HRM literature, which are discussed in the following section.
Implications for theory/research
By empirically investigating the impact of personal characteristics of the agent such as LOC, SE and RA on DJ, this study supplements and clarifies what is already known in the literature but has not yet been adequately developed, as called elsewhere (Rouziès et al., 2017).
Moreover, by showing the effects of RA, LOC and SE on WP, DJ and financial losses, this study introduces important variables in an agency relationship context that have been previously neglected. In doing so, the validity of adopting a cognitive framework is again demonstrated, but at the same time the psycho-social bases of the agency relationship are highlighted, as elsewhere suggested (Wiseman et al., 2012) and the assumption of an agent’s rational behaviour is challenged.
Furthermore, the empirical literature investigating the role played by gender in agency relationships is largely inconclusive (Paltseva, 2019). By highlighting the different effects that LOC has on male agents compared to female agents, this research makes a new contribution to the study of gender differences in the workforce within the agency relationship, a topic previously neglected by empirical research.
Finally, research on gender differences in risk orientation to date has mainly taken place in the laboratory (Bertrand, 2011), and it has been suggested that women have greater risk aversion (Parrotta and Smith, 2013). This study expands our knowledge by suggesting that, in an agency relationship in a real context, the scenario is more complex, and that the gender variable interacts with other variables, moderating them.
Implications for practices
This study provides valuable insights for recruitment, training, and managerial practices in organizations with output-based agency relationships, emphasizing the importance of incorporating agents' personal characteristics to enhance outcomes. By examining traits such as LOC, SE and RA, the study highlights ways to prevent undesired behaviors, including organizational withdrawal, opportunism and turnover (Lewin and Sager, 2010; Sunder et al., 2017).
During recruitment, assessing candidates' dispositional factors, particularly internal LOC and high SE, can ensure a better fit for performance-based roles, reducing turnover risks. Systematically analyzing these traits provides an original contribution to understanding cost and effectiveness determinants in agency relationships, supporting Graso et al.’s (2020) view of agents as active participants rather than passive recipients of treatment.
In training, organizations should enhance SE while managing overconfidence risks, focusing on programs for risk management, self-regulation and realistic goal-setting. Such training helps agents navigate performance-based challenges effectively.
Finally, managerial practices should create transparent reward systems that align with agents' motivations and address individual differences, including gender and tenure, to foster fairness and motivation, ultimately boosting organizational efficiency and agent satisfaction.
Limitations and relevant future research directions
While this study provides valuable insights, several limitations suggest directions for future research. First, the sample size, though statistically valid, limits the generalizability of the findings. Expanding the sample or examining specific industries could identify unique dynamics.
Additionally, this study did not consider factors like selling orientation (Wessels, 2011), so integrating more personal characteristics into the principal–agent model would enhance the cognitive framework. Future research could explore attributes such as professional background, educational background and cultural factors, which may impact the relationship between risk orientation and DJ.
This study also focuses on a single financial year, lacking a diachronic perspective. Future studies could adopt a longitudinal approach to examine changes over time, with variables like agent age or tenure potentially influencing results (Martin and Réveillac, 2019).
Figures
Regression coefficients
95% confidence interval | |||||||
---|---|---|---|---|---|---|---|
Predictor | Outcome | Estimate | Std. Error | z-value | p | Lower | Upper |
SE | WP | 0.367 | 0.150 | 2.443 | 0.015* | 0.073 | 0.662 |
SE | Los | 0.387 | 0.150 | 2.583 | 0.01*** | 0.093 | 0.680 |
SE | DJ | 0.708 | 0.132 | 5.351 | <0.001*** | 0.449 | 0.968 |
LOC | DJ | 0.229 | 0.109 | 2.104 | 0.039* | 0.016 | 0.442 |
RA | DJ | 0.563 | 0.175 | 3.209 | 0.015* | 0.219 | 0.907 |
Note(s): *significant for 0.05; *** significant for 0.01
Source(s): Author’s own work
Parameter estimates of the mediation analysis
95% confidence interval | ||||||
---|---|---|---|---|---|---|
Estimate | Std. Error | z-value | p | Lower | Upper | |
Direct effects | ||||||
SE → WP | 0.256 | 0.139 | 1.833 | 0.067 | −0.018 | 0.529 |
Indirect effects | ||||||
SE → LOC → WP | 0.112 | 0.067 | 1.661 | 0.097 | −0.020 | 0.243 |
Total effects | ||||||
SE → WP | 0.367 | 0.150 | 2.443 | 0.015 | 0.073 | 0.662 |
Path coefficients | ||||||
LOC → WP | 0.407 | 0.095 | 4.295 | <0.001 | 0.221 | 0.592 |
SE → WP | 0.256 | 0.139 | 1.833 | 0.067 | −0.018 | 0.529 |
SE → LOC | 0.275 | 0.152 | 1.801 | 0.072 | −0.024 | 0.573 |
Note(s): Delta method standard errors, normal theory confidence intervals, ML estimator
Source(s): Author’s own work
Synopsis by gender (M, F) of the parameter estimates of the mediation analysis
Estimate (M) | p | Estimate (F) | p | |
---|---|---|---|---|
Direct effects | ||||
SE → WP | 0.325 | 0.116 | −0.399 | 0.125 |
SE → Los | 0.393 | 0.090 | 0.114 | 0.677 |
Indirect effects | ||||
SE → LOC → WP | 0.295 | 0.018* | −0.153 | 0.200 |
SE → LOC → Los | 0.021 | 0.858 | −0.202 | 0.136 |
Total effects | ||||
SE → WP | 0.620 | 0.001*** | −0.552 | 0.026* |
SE → Los | 0.414 | 0.037* | −0.088 | 0.741 |
Residual covariances | ||||
WP → Los | 0.062 | 0.570 | 0.189 | 0.202 |
Note(s): Delta method standard errors, normal theory confidence intervals, ML estimator
*p < 0.05, **p < 0.01, ***p < 0.001
Source(s): Author’s own work
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Further reading
Ambrose, M.L. and Schminke, M. (2009), “The role of overall justice judgments in organizational justice research: a test of mediation”, Journal of Applied Psychology, Vol. 94 No. 2, pp. 491-500, doi: 10.1037/a0013203.
Gabler, C.B. and Hill, R.P. (2015), “Abusive supervision, distributive justice, and work-life balance: perspectives from salespeople and managers”, Journal of Personal Selling and Sales Management, Vol. 35 No. 3, pp. 247-261, doi: 10.1080/08853134.2015.1058167, available at: https://www.jstor.org/stable/26762795
Lubatkin, M.H., Ling, Y. and Schulze, W.S. (2007), “An organizational justice-based view of self-control and agency costs in family firms”, Journal of Management Studies, Vol. 44 No. 6, pp. 955-971, doi: 10.1111/j.1467-6486.2006.00673.x.
Rafatnia, A.A., Ramakrishnan, S.A.L., Abdullah, D.F.B., Nodeh, F.M. and Farajnezhad, M. (2020), “Financial distress prediction across firms”, Journal of Environmental Treat Technology, Vol. 8 No. 2, pp. 646-651.
Sweeney, P.D. and McFarlin, D.B. (1993), “Workers' evaluations of the ‘ends’ and the ‘means’: an examination of four models of distributive and procedural justice”, Organizational Behavior and Human Decision Processes, Vol. 55 No. 1, pp. 23-40, doi: 10.1006/obhd.1993.1022.
Vancouver, J.B. and Kendall, L. (2006), “When self-efficacy negatively relates to motivation and performance in a learning context”, Journal of Applied Psychology, Vol. 91 No. 5, pp. 1146-1153, doi: 10.1037/0021-9010.91.5.1146.
Verbeke, W., Dietz, B. and Verwaal, E. (2011), “Drivers of sales performance: a contemporary meta-analysis. Have salespeople become knowledge brokers?”, Journal of the Academy of Marketing Science, Vol. 39 No. 3, pp. 407-428, doi: 10.1007/s11747-010-0211-8.