Dieser Artikel untersucht das komplexe Wechselspiel zwischen Motivation und Zusammenarbeit im Bereich der Unternehmensforschung und konzentriert sich darauf, wie intrinsische und extrinsische Faktoren die Leistung von Wissenschaftlern beeinflussen. Die Studie zeigt, dass extrinsische Motivationen wie finanzielle Belohnungen und berufliche Anerkennung die Forschungsergebnisse und Erwartungen an den gesellschaftlichen Austausch erheblich beeinflussen. Intrinsische Motivationen sind zwar wertvoll, weisen aber keinen direkten Zusammenhang mit der Forschungsleistung auf, was die gängige Meinung in Frage stellt. Die Forschung verwendet einen gemischten Methodenansatz, der die Modellierung von Strukturgleichungen (PLS-SEM) mit der qualitativen Vergleichsanalyse (fsQCA) kombiniert, um sowohl lineare als auch konfigurative Effekte zu erfassen. Die Ergebnisse unterstreichen die Bedeutung extrinsischer Bestrebungen bei der Förderung einer Denkweise, die Vernetzung und sozialen Austausch wertschätzt und letztlich eine höhere Produktivität in der Forschung fördert. Der Artikel untersucht auch die vermittelnde Rolle sozialer Austauscherwartungen und bietet einen umfassenden Rahmen für das Verständnis, wie sowohl interne Treiber als auch externe Belohnungen das akademische Verhalten innerhalb von Forschungsnetzwerken beeinflussen. Der einzigartige Beitrag der Studie besteht in der Integration theoretischer Modelle und empirischer Daten, die Wissenschaftlern, akademischen Führungspersönlichkeiten und politischen Entscheidungsträgern umsetzbare Einsichten bieten, die darauf abzielen, die Forschungsleistung im Bereich des Unternehmertums zu steigern.
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Abstract
Research generating novel insights into entrepreneurship can contribute to entrepreneurial success and socioeconomic growth. This paper explores the influence of intrinsic and extrinsic motivations on the research performance of entrepreneurship scholars, with a particular focus on research collaborations. Grounded in Self-Determination Theory (SDT) and Social Exchange Theory (SET), the study aims to fill a gap in the entrepreneurship research literature by examining how different types of motivations impact research productivity. Using a mixed-methods approach, the research employs Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze the linear relationships between variables and fuzzy-set Qualitative Comparative Analysis (fsQCA) to identify configurations of conditions leading to high research performance. The findings suggest that, while extrinsic motivations, such as recognition and financial rewards, significantly enhance research output, no support was found for the role of intrinsic motivations. Social exchange expectations mediate to a shallow extent the relationship between extrinsic motivation and research performance. These findings underscore the importance of external rewards and collaborative dynamics in cultivating impactful entrepreneurship research, informing academic leaders, researchers, and policy-makers on how to foster more productive research environments in this rapidly expanding field.
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1 Introduction
Entrepreneurship researchers (or entrepreneurship scholars interchangably) play a crucial role in advancing knowledge that spurs entrepreneurial activities, innovation, the creation of new jobs, and social or socioeconomic growth (Acs and Szerb 2007; Cervelló-Royo et al. 2024; Daumiller and Dresel 2020; Ferreira et al. 2019; Galindo and Méndez 2014; Keilbach and Sanders 2009; Ribeiro-Soriano 2017; Scatozzi et al. 2025; Van Praag and Versloot 2007; Wennekers and Thurik 1999). Despite the high relevance of scholarly knowledge in entrepreneurship, little is known about how to systematically foster the growth of such knowledge. Much of the prior literature attributes variance in research productivity to demographic or institutional factors, such as gender (van den Besselaar and Sandström, 2016), research time (Bentley and Kyvik 2013), or work environment (Sheridan et al. 2017). However, while these factors are undoubtedly important, they offer only a partial explanation of what propels scientific output. By comparison, less attention has been paid to the specific intrinsic and extrinsic motivational factors driving scholars to publish impactful work (Blind et al. 2018; Horodnic and Zaiţ, 2015; Peng and Gao 2019; Stupnisky et al. 2019a). This gap poses a challenge for research institutions aiming to cultivate high-performance research teams and, thus, to accelerate progress in entrepreneurship research. The findings are relevant for entrepreneurship scholars striving for career advancement, academic leaders aiming to advance their institutions’ research output and reputation, and policy-makers allocating resources.
A further missing piece in the literature concerns how such motivations play out in collaborative, reciprocal relationships among researchers (Lenart-Gansiniec et al. 2025). Collaboration—through co-authorships, network ties, and mutual support—has been frequently linked to higher publication counts, increased citations, and broader visibility within a field (Katoh et al. 2021; Lam 2011). Yet, it remains unclear whether a scholar’s intrinsic enjoyment of the subject matter (e.g., intellectual curiosity, personal growth) or their extrinsic goals (e.g., financial rewards, professional standing) spark a heightened expectation of collaboration, or if collaboration simply emerges as an afterthought. Addressing how motivation and expectations of collaboration intersect is central to understanding research performance in entrepreneurship, where academics often rely on cross-disciplinary teams and varied institutional partnerships to investigate complex phenomena (Obschonka et al. 2017), comparable to entrepreneurial teams (Horvatinovic et al. 2023). Consequently, clarifying this relationship may yield actionable insights for entrepreneurship scholars seeking career advancement, academic leaders seeking to improve institutional research output, and policy-makers determining how to allocate resources.
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Given these gaps, the main problem this study addresses is the lack of clarity about how different motivations—particularly intrinsic vs. extrinsic—drive entrepreneurship scholars’ research productivity, especially within collaborative settings. To bridge this gap, the purpose is twofold: (1) to examine how distinct types of motivation influence research performance among entrepreneurship scholars, and (2) to determine whether social exchange expectations, rooted in collaborative reciprocity, mediate the motivation–performance relationship. The following research questions guide the inquiry:
RQ1 How do intrinsic and extrinsic aspirations individually affect entrepreneurship scholars’ research performance?
RQ2 How do these aspirations translate into social exchange expectations of reciprocal academic collaboration?
RQ3 Do these social exchange expectations mediate the relationship between the motivational factors and research performance?
These questions are tackled by drawing on Self-Determination Theory (SDT) and Social Exchange Theory (SET). While SDT explains how intrinsic and extrinsic motivations drive individual behavior (Ryan and Deci 2000a, b), SET highlights the social, reciprocal exchanges through which researchers co-create knowledge (Cropanzano et al. 2017; Emerson 1976). SDT illuminates why scholars might be driven by personal enjoyment (intrinsic) or by career advancement and recognition (extrinsic), whereas SET clarifies how reciprocal collaboration among researchers reinforces or modifies those motivations. This additional focus on mutual support and collaboration is especially relevant in entrepreneurship research, where researchers frequently build large, cross-disciplinary networks to publish at higher rates and increase visibility (Katoh et al. 2021; Lam 2011). Integrating SDT and SET thus provides a more complete framework for understanding how both internal drivers and external rewards channel researchers’ behavior within research networks. By conceptualizing motivation and social exchange expectations as mutually reinforcing, this perspective offers a more nuanced explanation of when and why scholars engage in collaborative knowledge creation—thereby clarifying how motivation and social exchanges jointly shape research performance in the field of entrepreneurship.
The productive convergence of SDT and SET was also demonstrated by prior research. For example, Aryee et al. (2015) show how perceptions of overall justice—framed by employees’ psychological needs (via SDT) and reciprocal relationships (via SET)—lead to enhanced job performance. Their findings underscore that satisfaction of fundamental needs operates in tandem with fair exchanges, ultimately elevating performance. Similarly, Henderson and Jeong (2024) highlight how leader-member exchange (LMX), which also represents reciprocal relationships, fosters self-determined motivations, which then translate into higher performance. These studies thus reinforce the notion that both intrinsic drivers and social exchange mechanisms are vital to understanding how motivation unfolds in professional contexts—an insight that informs the focus on entrepreneurship scholars’ research productivity. The focus on entrepreneurship research rather than business and management research (or even research in general) is due to the fact that it stands out from other management subfields due to its quite young age and exponential growth, strong interdisciplinary focus (including economics, psychology, sociology, and organizational behavior, etc.), practical orientation, and high relevance to innovation and socioeconomic development. This boundary-spanning nature also reflects the dual imperative to advance academic theory and address real-world challenges, making entrepreneurship scholars particularly conscious of translational impact (Keilbach and Sanders 2009). Therefore, understanding the motivations that drive entrepreneurship scholars and how they collaborate is especially pertinent, as the field continues to expand in breadth and global influence. All subfields of entrepreneurship research are included.
This study contributes to entrepreneurship research by offering a nuanced understanding of the role that both intrinsic and extrinsic motivations play in influencing research performance, specifically within the context of entrepreneurship research. It expands on existing literature by integrating SDT and SET to examine how social exchange expectations mediate the relationship between motivation and performance. One of the key contributions is the novel finding that extrinsic aspirations, such as financial rewards and professional recognition, have a significant positive impact on research performance, as well as on the expectations of social exchanges.
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The application of the results can lead to a higher research performance at the individual and university level. The findings are relevant for individual scholars striving for career advancement, academic leaders, such as deans and department heads, and policy-makers allocating financial and other research resources.
2 Literature review and hypotheses development
2.1 Research performance
In this study, research performance refers to the quality and impact of scholarly outputs, typically measured through indicators such as the number of publications (research productivity) in reputable journals and the citation rates those publications accumulate (research impact) (Horodnic and Zaiţ 2015; Ryan 2021; Stupnisky et al. 2019a). The accumulated research performance of individual influence the performance of universities (Ryan 2016).
Much research has been devoted to this important topic, taking two different perspectives in the investigation of research productivity. Some of the literature addresses the requirements for publications and the environment in which researchers work and how this influences their performance (Bentley and Kyvik 2013; Cargile and Bublitz 1986; Sheridan et al. 2017). Another part looked at the researchers’ individual characteristics and explored the influence that these factors can have. For example, past research has linked scholarly productivity to the influence of gender (Kelchtermans and Veugelers 2011; Long 1992) or age (Bonaccorsi and Daraio 2003; Inceoglu et al. 2012; Simonton 1988). In addition, the influence of the motivation underlying the researchers’ work and the impact of this on their research productivity was also examined (Chen et al. 2006; Sauermann and Cohen 2010; Stupnisky et al. 2019a; Tien 2000, 2008). As there are different practices in research fields that can affect research performance, it can be difficult to compare different disciplines (Nederhof 2006; Zuckerman and Merton 1971). Consequently, it is appropriate to examine scholars from a specific research area (Bouwma-Gearhart 2012; Horodnic and Zaiţ, 2015; Rodriguez Miramontes and Gonzalez-Brambila 2016; Stupnisky et al. 2023). Here the focus is on entrepreneurship research.
2.2 Motivation for research
The motivation behind an action, such as publishing or research in general, can influence its outcome (Gagné and Deci 2005). Motivation describes the impulse to act (Ryan and Deci 2000a). The different factors that motivate researchers and how they influence their work have been subject of research. For example, the effects of intrinsic motivation on research behavior were investigated and found to have a negative impact on burnout (Singh et al. 1998). In another study by Colbeck (1992), the influence of intrinsic motivation and extrinsic rewards on the interests of researchers was explored. It was found that the degree of interest in a task was linked to the belief that completing that task would lead to further rewards (Colbeck 1992).
In more recent research, various theories have been used to explain the motivation of researchers, such as Achievement Goal Theory (Daumiller and Dresel 2020), Control-Value Theory (Stupnisky et al. 2019b), or Self-Determination Theory (SDT) (Blind et al. 2018; Lam 2011; Stupnisky et al. 2019a). Due to the clear reference to the research object (Deci et al. 2017), the theoretical model for this work was developed on the basis of SDT. According to this theory, different types of motivation exist, namely intrinsic and extrinsic motivation, which can have a varying influence on behavior and ultimately performance (Deci and Ryan 2008a; Ryan and Deci 2020). Intrinsic motivation is present when the reward lies in the action itself, whereas extrinsic motivation is stimulated by external rewards. Past literature has identified intrinsic motivation as an important influence on performance (Horodnic and Zaiţ, 2015; Sauermann and Cohen 2010) and the career satisfaction of researchers (Lounsbury et al. 2012). Chen et al. (2006) observed that researchers were motivated by both extrinsic and intrinsic factors and that this increased the number of their publications. Recent research conducted by Stupnisky et al. (2017) supports this by showing a positive correlation between intrinsic motivation and research behavior. In addition, Stupnisky et al. (2019a) concluded that autonomous motivation, which includes intrinsic motivation, leads to higher research performance, while extrinsic motivation had a slightly positive effect. In contrast, Horodnic and Zaiţ (2015) found that extrinsic motivation had a negative effect on research performance.
2.3 Motivating factors
Personality studies have shown that researchers differ from the general population regarding their traits (Feist and Gorman 1998; Lounsbury et al. 2012). The different motivators are part of such an individual characteristic and can influence a person’s attitude to a particular action (Ryan 2014). The motivational research performance literature has identified three motivators for researchers (Blind et al. 2018; Lam 2011; Levin and Stephan 1991; Shinn and Lamy 2006)—“ribbon,” “gold,” and “puzzle.”
The goal in science is to make a discovery and publish this knowledge (Merton 1957), and the reward is recognition from peers (Merton 1973). This form of extrinsic motivation can be considered as striving for the “ribbon” and can manifest itself in publishing, receiving research awards, and career promotions (Blind et al. 2018; Lam 2011). This is supported by Tien (2000, 2008) who concluded that promotions have a considerable influence on the number of publications. The second motivator, “gold,” is seen because of the first and refers to the financial benefits gained through scholarly achievements (Stephan 1996). Studies have come to mixed results regarding the extent to which money is a motivating factor. According to Herzberg’s theory, money is seen as a hygiene factor that only needs to be satisfied but has no additional motivating effect (Herzberg 1966). However, Tien (2008) came to the result that a higher salary was a decisive motivator for academics behind conducting research. The last factor concerns the intrinsic motivator to solve the “puzzle” (Blind et al. 2018; Lam 2011). While some academics conduct research with the aim of publication, others perform research for its own sake (Hangel and Schmidt-Pfister 2017). This motivator expresses the enjoyment that scholars get from research and their work itself (Stephan 1996). The three factors can individually or simultaneously motivate researchers in their pursuits (Lam 2011).
2.4 Collaboration in research
Another typical characteristic among researchers is their collaboration (Beaver and Rosen 1979). Studies have shown that collaboration, particularly at the international level, correlates positively with research productivity (Abramo et al. 2017; Kwiek 2016; Lee and Bozeman 2005; McFadyen and Cannella 2004) and the number of citations (He et al. 2009; Rodriguez Miramontes and Gonzalez-Brambila 2016; Wuchty et al. 2007). According to Social Exchange Theory (SET), transactions are based on rules of reciprocity (Emerson 1976). The research explores how different types of motivation could affect these social exchange expectations and how they relate to performance.
2.5 Self-determination theory
Motivation explores the drivers behind people’s behavior. Figure 2 shows the research model, based on SDT, which states that people act depending on their inner needs and external influences (Deci and Ryan 1985a, 2000).
Autonomous actions are characterized by voluntariness, i.e. people do something because they want to, in contrast to controlled actions, when people do something because they have to (Gagné and Deci 2005). Autonomous motivation is associated with better performance (Deci et al. 2017).
Intrinsic motivation is a form of autonomous motivation, which arises from the enjoyment of the action itself and is not triggered by external influences, such as a reward or pressure (Good et al. 2022). Researchers have tried to identify the characteristics of a task that promote intrinsic motivation. Initial studies focused on psychological needs, such as the desire for independence and control (Deci and Ryan 1985b). According to SDT, intrinsic motivation is influenced by independence, perceived competence in implementation, and the degree of affiliation to a task, whereas extrinsic motivation is a version of controlled motivation and is present when an action is undertaken to achieve a specific result (Deci and Ryan 1985b; Ryan and Deci 2000b). Research shows that intrinsic motivation is positively related to performance (Cerasoli et al. 2014; Good et al. 2022). In this case, people feel controlled by others because they are given a reward or an equivalent depending on their perceived performance (Deci et al. 2017). The results on the relationship between extrinsic motivation and performance are mixed. For less complex tasks, research has shown a positive effect of extrinsic motivation on performance (Bareket-Bojmel et al. 2017). Other research indicates that extrinsic motivation can have a negative impact on creativity and performance, while intrinsic motivation performs better in comparison (Gerhart and Fang 2015).
2.6 Intrinsic aspirations
SDT also explains the motivation behind long-term goals (Deci and Ryan 2008b). These goals are categorized into intrinsic aspirations and extrinsic aspirations (Kasser and Ryan 1996). Life goals of intrinsic aspirations include rewarding relationships, contributing to the community, health, and personal growth. Studies have shown that, when academics are strongly intrinsically motivated, this is also reflected in their work (Beigi et al. 2017; Kraimer et al. 2019). Intrinsic motivation is seen as a basic requirement for research (Baruch and Hall 2004) and thus as a necessity for academic achievements (Pudelko and Tenzer 2019). Studies have shown that it is a key factor in initial career success (Mueller et al. 2015; Seibert et al. 2013) and career satisfaction (Lounsbury et al. 2012), and that it has an important influence on research performance (Horodnic and Zaiţ, 2015; Sauermann and Cohen 2010; Stupnisky et al. 2019a). Researchers who are intrinsically motivated perform better in their studies and show higher publication rates (Chen et al. 2006; Stupnisky et al. 2017). Accordingly, intrinsically motivated researchers are more involved in research and specifically look for new research opportunities (Hangel and Schmidt-Pfister 2017; Stupnisky et al. 2023). For researchers, intrinsic aspirations can include belonging to the scientific community (rewarding relationships), the desire to develop in one’s field (personal development), and contributing to science (contribution to the community) (Kasser and Ryan 1996). Against this background, the following hypothesis is proposed:
Hypothesis 1
Entrepreneurship scholars with stronger intrinsic aspirations—encompassing community contributions, meaningful relationships, personal growth, and independent self-construal—will report higher research performance (i.e., more publications in reputable journals and greater citation impact).
2.7 Extrinsic aspirations
However, actions are not only intrinsically but also extrinsically motivated as not all tasks have an intrinsic value (Hardré and Kollmann 2012). Intrinsically motivated researchers perform better than extrinsically motivated colleagues (Gagné and Deci 2005). Extrinsic motivation might even have a negative influence (Gerhart and Fang 2015; Horodnic and Zaiţ 2015). However, there is evidence that supports the positive impact of extrinsic rewards on researchers’ performance, such as a higher publishing rate (Chen et al. 2006; Stupnisky et al. 2019a; Tien 2000). Extrinsic aspirations include goals, such as wealth, reputation, and popularity (Kasser and Ryan 1996). In this case, the researchers strive to be recognized by their peers (Sauermann and Cohen 2010) and to profit from the resulting financial success (Blind et al. 2018; Lam 2011). The prospect of gaining recognition for one’s achievements, such as a promotion, was found to have a significant influence on the research performance of scholars (Tien 2000, 2008). For researchers, extrinsic aspirations can include gaining additional income through their publications (wealth) and the desire to be recognized as a respected and influential part of the community (reputation and popularity) (Lam 2011). Awareness of one’s extrinsic goals can lead to an increased level of voluntariness to act (Ryan and Deci 2020). If there is additional will and commitment, this can have a positive effect on performance (Duckworth et al. 2007). Since recognition in the field of research is a particularly important asset that goes hand in hand with further financial opportunities, it can be assumed that these reasons motivate researchers to publish high-quality papers. Therefore, the following hypothesis is proposed:
Hypothesis 2
Entrepreneurship scholars with stronger extrinsic aspirations—which include additional income, self-image, and interdependent self-construal—will report higher research performance.
2.8 Social exchange expectations
Researchers strive for success in the context of social relationships and want to build sustainable relationships (Granovetter 1985). Existing relationships can be seen as a source of benefit for the respective partner (Nahapiet and Ghoshal 1998). Within relationships, it is expected that a favor will be returned over time (Blau 1964). In other words, transactions are based on rules of reciprocity, as stated by social exchange theory (Emerson 1976). In their social structure, people act in such a way that they want to promote positive and prevent negative experiences (Cropanzano et al. 2017). Research indicates that such collaboration, especially at the international level, is positively linked to both research productivity (Abramo et al. 2017; Kwiek 2016; Lee and Bozeman 2005; McFadyen and Cannella 2004) and the number of citations (He et al. 2009; Rodriguez Miramontes and Gonzalez-Brambila 2016; Wuchty et al. 2007). Consequently, collaboration is seen as beneficial (Butz et al. 2024; Gonzalez-Brambila et al. 2013). Researchers generating attention share it with their collaborators (Klamer and Dalen 2002). By working together, researchers can participate in several projects simultaneously and investigate issues from different perspectives (Ryazanova and McNamara 2016). In addition, a positive relationship between intrinsic motivation and research collaboration was found (Katoh et al. 2021). Therefore, a positive relationship between the intrinsic ambitions of researchers and their social exchange expectations can be predicted and the following hypothesis is proposed:
Hypothesis 3
Entrepreneurship scholars with stronger intrinsic aspirations will exhibit greater expectations of social exchange (e.g., mutual citation, reciprocal co-authorship invitations, collaborative support).
Networks consisting of various relationships are considered helpful for a successful career (Baruch and Hall 2004; Kraimer et al. 2019). Building relationships is associated with obtaining research resources and more prestige (Lam 2011) and repeated collaboration with the same researcher with more publications and citations (Ryazanova and McNamara 2016). A study by Katoh et al. (2021) found that extrinsic motivation had a positive effect on research collaboration, especially in the absence of intrinsic motivation. It is hypothesized that researchers with extrinsic ambitions are aware that networking and collaboration are important to achieve their goals. Consequently, they are presumed to support their colleagues and invite them to joint research while also expecting reciprocal support. This leads to the following hypothesis:
Hypothesis 4
Entrepreneurship scholars with stronger extrinsic aspirations will exhibit greater expectations of social exchange.
2.9 Mediating influence of social exchange expectations
As argued above, both types of aspirations are related to social exchange expectations as well as to research performance. An increased social exchange expectation will lead to more mutual help, support, and collaboration between researchers and thus to more research. Collaboration between researchers not only increases the number of publications and citations, but can also improve quality through different knowledge sources, mutual review, and inspiration (Ryazanova and McNamara 2016). Building trust through increased collaboration is associated with better performance (Colquitt et al. 2007). Therefore, social exchange expectations can be expected to mediate the aspirations–research performance relationship. The following hypothesis is proposed:
Hypothesis 5
Social exchange expectations will mediate the links between (a) intrinsic aspirations and research performance and (b) extrinsic aspirations and research performance. Specifically, higher social exchange expectations will strengthen the positive effects of both intrinsic and extrinsic aspirations on research performance.
3 Methodology
We decided to use a mixed-method approach, consisting of Partial Least Squares Structural Equation Modeling (PLS-SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA), as each method captures a different dimension of how motivation and social exchange link to research performance. First, PLS-SEM can test linear relationships in a comprehensive theoretical model, accommodating multiple latent constructs and potential mediating pathways (Hair et al. 2022). It is suitable for smaller-to-moderate sample sizes and offers robust insights into the direct and indirect effects among the constructs of interest. Second, fsQCA analyzes configurations of antecedent conditions—including nonlinear and combinatorial effects—to reveal multiple paths that can lead to different levels of research performance (Kraus et al. 2018; Kumar et al. 2022; Ragin 2000). Therefore, this method goes beyond detecting additive, symmetric relationships, rather recognizing that certain variables may interact differently depending on which other conditions are present.
By combining both methodologies, the symmetric main and mediating effects are captured, as well as the asymmetric (i.e., nonlinear or combinational) ways in which motivations and social exchange expectations produce varying outcomes. This dual approach aligns with the research objective of explaining not just whether but also how distinct motivational factors and collaborative dynamics jointly foster higher research productivity among entrepreneurship scholars.
The research model designed for the PLS-SEM approach is depicted in Fig. 1.
Fig. 1
Conceptual model considering symmetric relationships between constructs.
PLS-SEM provides statistical validation for both the measurement and structural models, exploring the reliability of constructs and relationships initially presumed to exist. This aspect of PLS-SEM is instrumental in assessing impacts of the independent variables on the dependent variables. Conversely, fsQCA presents a configuration of various antecedent conditions that influence the outcome and outlines combinations of conditions that result in the presence or absence of an outcome.
The constructs presented in Table 1 outline satisfactory reliability and convergent validity based on the internal consistency measures (Cronbach’s alpha), composite reliability (CR), and average variance extracted (AVE).
Table 1
Description of constructs and items from the measurement model
I am considering creating a consultancy agency to turn my knowledge into an additional source of revenue
I am motivated to accept a temporary affiliation to another academic institution that is willing to offer me a higher compensation than my current employer
INTSC: Interdependent self-construal
0.705
I feel fulfilled when I cooperate with researchers with complementary skills and knowledge
It is important for me to develop long-term professional relationships with my peers
I consider collaborations with “research giants” in my field to be highly valuable in developing my research skills
SI: Self-image
0.838
I feel that I am a researcher of worth, at least on an equal plane with others with significant contributions to the body of knowledge in entrepreneurship
Due to my research, I got a position(s) as a Visiting Scholar/Professor or similar at prestigious business schools
Source authors
The latent variable Intrinsic Aspirations demonstrates acceptable reliability with a Cronbach’s alpha of 0.709. The items associated with Meaningful Relationships (MR) have the highest contribution to Intrinsic Aspirations (outer loading = 0.759), while the items related to Independent self-construal (INDSC) have the lowest contribution to Intrinsic Aspirations (outer loading = 0.692).
The latent variable Extrinsic Aspirations has a Cronbach’s alpha of 0.685, slightly below the preferred threshold of 0.70, but the composite reliability (CR) and average variance explained (AVE) values suggest that this construct still captures the variance in its indicators adequately. The items associated with Self-image (SI) have the highest contribution to Extrinsic Aspirations (outer loading = 0.838), while the items related to Additional income (AI) have the lowest contribution to Extrinsic Aspirations (outer loading = 0.663).
The latent variable Social Exchange Expectations reveals high reliability with a Cronbach’s alpha of 0.844. All items within this construct have strong outer loadings, particularly reciprocal research recommendation—SEE2 (0.881) and reciprocal citation expectation—SEE3 (0.891), suggesting that these indicators are strong measures of social exchange expectations.
The latent variable Research Performance has a strong internal consistency, given by Cronbach’s alpha of 0.807. The construct’s items display high outer loadings, with rigor at 0.919 and relevance at 0.846, indicating a robust measure of research performance.
Overall, these constructs demonstrate adequate reliability and convergent validity, with most items having outer loadings exceeding the acceptable threshold of 0.70.
FsQCA possesses numerous unique advantages. It is particularly appropriate for studies utilizing medium-sized samples. In this study, the sample size was 210. This feature makes fsQCA ideal for in-depth investigations. It is based on the principles of set theory, facilitating a detailed examination of interactions among various conditions. Importantly, fsQCA acknowledges the intricacies of multiple causation. In fsQCA, multiple factor combinations can affect a specific outcome. This aspect is especially relevant to the study of research performance for scholars involved in entrepreneurial research, in which individual and demographic differences shape preferences. Likewise, the principle of equifinality in fsQCA allows for the possibility of multiple paths leading to the same outcome. This feature means that fsQCA can provide a comprehensive understanding of the factors that drive sustainable cryptocurrency adoption.
The first step of fsQCA is the calibration of variables into sets. Dependent variables in statistical methods are referred to as outcomes in fsQCA. Likewise, independent variables are known as conditions. Calibration can convert variables into fuzzy sets or crisp sets. Fuzzy sets represent a continuum, where values range from 0 (no membership in the set) to 1 (full set membership). This spectrum allows for gradations in the data. In contrast, crisp sets are binary. Conditions are either fully present (1) or fully absent (0). This binary approach is effective for inherently dichotomous conditions. The choice between fuzzy and crisp sets depends on the nature of the underlying variables and the specific requirements of the research.
FsQCA provides an adequate framework for uncovering probable behavioral patterns among perceptions of research performance of entrepreneurship scholars. FsQCA employs an inductive approach that is well-suited to the complexities of this research area. It focuses on three key principles: conjunction, equifinality, and causal asymmetry. Conjunction refers to the interplay of multiple conditions leading to an outcome. In this study, it is reflected by how different factors interact to influence research performance. Equifinality refers to the possibility of multiple, distinct paths resulting in the perception of research performance. This study is reflected by the diverse motivations of scholars to better perform on the academic campus. Causal asymmetry refers to the idea that the causes of high research performance may differ fundamentally from those leading to low research performance.
The proposed configurational model was conceptualized by choosing the variables that could best be regarded as causes: meaningful relationships (MR), personal growth (PG), community contributions (CC), additional income (AI), self-image (SI), independent self-construal (INDSC), interdependent self-construal (INTSC), and social exchange expectations (SEE). These conditions were assumed to be sufficient to achieve entrepreneurial research performance (RP) (Fig. 2). FS/QCA 4.0 was used for the fuzzy-set analysis (Ragin 2000). The software detects potential pathways that lead to an outcome of interest.
Fig. 2
Conceptual model considering asymmetric relationships between constructs.
The data were calibrated using external criteria (Table 2). The raw data were calibrated using the direct method and the fsQCA method. The values of an interval scale were set to match the three qualitative breakpoints of a fuzzy set: 5 for full membership, 1 for full non-membership, and 3 for the crossover point (Ragin 2000). The original interval scale values were then converted into fuzzy-set membership scores with the help of these three breakpoints. This method provided the fine-grained calibration of case membership in sets. Scores ranged from 0.05 to 0.95 (with a possible error of 0.05).
An online questionnaire-based survey was used to collect data from researchers in the field of entrepreneurship on specific items assigned to four constructs of the conceptual model (intrinsic aspirations, extrinsic aspirations, social exchange expectations, and research performance).
Since the literature does not offer well-established scales for measuring the items in the conceptual model, scales were adapted from relevant research grounded in SDT and SET that influence researchers ‘performance (Table 1). In this regard, a key challenge is that existing scales are often designed for different contexts or narrower scopes. To capture the entrepreneurship scholars’ unique environment, well-established measures from SDT (Ryan and Deci 2000a; Gagné and Deci 2005) and SET (Cropanzano et al. 2017; Emerson 1976) were adapted, selecting and rewording items to reflect academic motivations and collaborative behaviors typical of entrepreneurship research. To ensure clarity of the measurement instrument, a pretest of the items assigned to the four latent variables was conducted. A pilot study was carried out with a focus group of ten researchers to evaluate the comprehensibility of the items, using a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree).
The entrepreneurship researchers invited to participate in the study were recruited from the editorial boards of the entrepreneurship journals assigned to the first and second quartile of the 2021 Journal Citation Reports (JCR), namely (in alphabetical order): Entrepreneurship and Regional Development, Entrepreneurship Theory and Practice, International Entrepreneurship and Management Journal, International Journal of Entrepreneurial Behavior & Research, International Small Business Journal, Journal of Business Venturing, Journal of Small Business Management, Small Business Economics, and Strategic Entrepreneurship Journal. As no worldwide directory of all entrepreneurship researchers exists, the editorial boards of entrepreneurship journals make many of them visible. Additionally, the focus on editorial boards is also a quality filter, as there is a high correlation between a board membership and the researcher’s own research performance; usually only well-established researchers get invitations to joint editorial boards. The focus on Q1 and Q2 journals serves an additional quality filter in regards to the journals’ impact. Whereas entrepreneurship research also gets published in other journals (e.g., journals with a broader business and/or management scope), most of their editorial boards do not have sections, which makes it difficult to identify the board members responsible for entrepreneurship. Besides, it is very likely that these are also member of the editorial board of at least one of the entrepreneurship journals mentioned above.
The email addresses of 1013 of the enlisted entrepreneurship scholars were identified. The answers were collected in February 2023.
The control variables considered participants’ publication records on entrepreneurship, as well as their impact and recognition of their research contributions.
3.2 Sample demographics
In the final sample of 210 entrepreneurship researchers, 118 individuals (56%) identified as men, 90 (43%) as women, and 2 individuals (1%) preferred not to disclose their gender. This distribution provides a balancd representation of gender within this study.
The age distribution of the participants in this study shows a diverse range. A total of 22 individuals (10%) are under 30 years old, while 31 (16%) fall between 30 and 40 years. The largest age group comprises 70 participants (33%) aged between 41 and 50 years. Additionally, 49 participants (23%) are between 51 and 60 years old, and 38 (18%) are over 60 years, indicating a broad spectrum of ages among the research sample.
The respondents in this study have their main affiliations spread across 29 countries, illustrating a diverse and global sample. The majority of participants are affiliated with institutions in the United States of America (29%), United Kingdom (14%), Spain (7%), Germany (6%) and Italy (5%). The sample includes respondents from various regions, including Europe (48%), North America (32%), Asia (11%), South America (4%), Australia (3%), and Africa (2%). This broad distribution of affiliations provides a comprehensive perspective on the research landscape in entrepreneurship worldwide.
The timeline of respondents’ first research on entrepreneurship varies significantly. Thirteen respondents (7%) began their research less than 5 years ago, 42 (20%) started 5 to 10 years ago, 45 (21%) initiated their research 10 to 15 years ago, and 38 (18%) began 15 to 20 years ago. Notably, the largest group, comprising 72 individuals (34%), started their research more than 20 years ago, indicating a considerable range of experience within the sample.
The participants’ publication records on entrepreneurship reveal a wide range of research productivity. A total of 54 individuals (26%) have published fewer than 10 articles, while 111 (53%) have published between 10 and 49 articles. Additionally, 28 individuals (13%) have published between 50 and 99 articles, and 17 (8%) have an extensive publication record with more than 100 articles. This distribution highlights varying levels of engagement and expertise in entrepreneurship research within the sample.
The participants in this study have an average of 4,941 citations in the Web of Science (WoS), reflecting the impact and recognition of their research contributions. Additionally, the average H-index among the participants is 20, indicating a substantial level of scholarly influence and productivity in the field of entrepreneurship.
Respondents were also asked to outline the main topics covered by their teaching and research on entrepreneurship. Key themes they have been involved in and are working on include crowdfunding, entrepreneurial finance and venture capital, entrepreneurial leadership, opportunity recognition and formation, entrepreneurial mindset and cognition, intrapreneurship, social entrepreneurship, business model innovation, entrepreneurial ecosystems, networking, digital entrepreneurship, and entrepreneurial identity.
4 Results
4.1 PLS-SEM results
The path coefficients on the arrows that connect the latent variables from the conceptual model are illustrated in Fig. 3.
Fig. 3
Path coefficients associated to the relationships from the measurement model. SmartPLS 4 software output
The very small but positive path coefficient on the relationship between Intrinsic Aspirations and Social Exchange Expectations (0.056) suggests a weak positive association between intrinsic aspirations (e.g., the desire to contribute to the entrepreneurship field) and social exchange expectations. Respondents with intrinsic motivations might slightly expect reciprocal social interactions, while the minimal strength of this path indicates that intrinsic aspirations do not significantly drive expectations for social exchanges in an academic context.
The negative path coefficient on the link between Intrinsic Aspirations to Research Performance (− 0.155) highlights an inverse relationship between intrinsic aspirations and research performance. While intrinsic motivations like personal growth and contributions to the entrepreneurship field are valuable, they might not directly translate into measurable research outputs such as publication relevance and impact. This negative relationship could also suggest that a focus on intrinsic motivations might sometimes divert attention away from conventional metrics of entrepreneurship research success.
The positive and moderate path coefficient on the relationship between Extrinsic Aspirations and Social Exchange Expectations (0.363) suggests that researchers driven by extrinsic aspirations (such as income, recognition, or professional status) are more likely to expect reciprocal social interactions in their research endeavors. It also highlights the influence of extrinsic motivations in fostering a mindset that values networking and social exchanges within research communities.
The strong positive path coefficient on the relationship between Extrinsic Aspirations to Research Performance (0.493) reveals that extrinsic aspirations are a significant predictor of research performance and demonstrates that researchers who are motivated by external rewards (like additional income, recognition, or institutional prestige) are more likely to achieve better research performance.
The small but positive path coefficient on the relationship between Social Exchange Expectations to Research Performance (0.048) reflects a weak relationship between social exchange expectations and research performance. Although the expectation of reciprocal behaviors in academic settings is present, its direct influence on research performance appears to be minimal. Although social exchanges are part of the academic environment, they do not significantly enhance entrepreneurship research productivity in terms of publications or citations.
The R-squared value related to the construct of Social Exchange Expectations (0.160) indicates that 16% of the variance in social exchange expectations is explained by the structural model, specifically by intrinsic and extrinsic aspirations. While the R-squared value is relatively low, it suggests that extrinsic aspirations (with a stronger path coefficient of 0.363) are more valuable in shaping expectations for social interactions in entrepreneurship research.
The R-squared value related to the construct Research Performance (0.191) reflects that 19.1% of the variance in research performance is explained by intrinsic aspirations, extrinsic aspirations, and social exchange expectations. Extrinsic aspirations (path coefficient = 0.493) have a significant influence on research performance, while the weak influence of intrinsic aspirations (0.155) and social exchange expectations (0.048) further highlight that these factors can capture in a small extent the determinants of academic research success.
The Fornell-Larcker criterion was used to evaluate the discriminant validity among constructs. To demonstrate discriminant validity, the square root of each construct’s AVE (diagonal values) should be greater than its highest correlation with any other construct.
Extrinsic Aspirations has a square root of AVE of 0.711, which is greater than its correlations with other constructs, suggesting adequate discriminant validity. Intrinsic Aspirations (square root of AVE = 0.727) and Research Performance (square root of AVE = 0.851) also meet this criterion, indicating they are distinct constructs. Social Exchange Expectations (square root of AVE = 0.826) similarly demonstrate the discriminant validity (Table 3).
Table 3
Discriminant validity of the measurement model—Fornell-Larcker criterion
Extrinsic aspirations
Intrinsic aspirations
Research performance
Social exchange expectations
Extrinsic aspirations
0.711
Intrinsic aspirations
0.606
0.727
Research performance
0.418
0.157
0.851
Social exchange expectations
0.397
0.276
0.201
0.826
Source SmartPLS 4 software output
The Heterotrait-Monotrait ratio of correlations (HTMT) further supports discriminant validity, only if HTMT values are below 0.85. The HTMT values between constructs are relatively low, with the highest being between Extrinsic Aspirations and Intrinsic Aspirations (0.852), which is slightly above the commonly accepted threshold. However, other values such as between Research Performance and Intrinsic Aspirations (0.219) and Social Exchange Expectations and Research Performance (0.235) are well below 0.85, confirming that most constructs have acceptable discriminant validity (Table 4).
Table 4
Discriminant validity of the measurement model—Heterotrait-Monotrait ratio of correlations (HTMT)
Extrinsic aspirations
Intrinsic aspirations
Research performance
Social exchange expectations
Extrinsic aspirations
Intrinsic aspirations
0.852
Research performance
0.552
0.219
Social exchange expectations
0.607
0.33
0.235
Source SmartPLS 4 software output
The SRMR assesses the model fit, with values less than 0.10 indicating a good fit. In both the saturated and estimated models, the SRMR is reported as 0.090 (Table 5). While this is below the upper limit of the threshold, it suggests an adequate model fit. Additional fit indices like the normed fit index (NFI = 0.825) provide further insights into model fit, though the NFI value indicates a moderate fit.
Table 5
Determination of Standardized Root Mean Square Residual (SRMR)
Saturated model
Estimated model
SRMR
0.090
0.090
d_ULS
0.859
0.859
d_G
0.243
0.243
Chi-square
302.001
302.001
NFI
0.825
0.825
Source SmartPLS 4 software output
The bootstrapping procedure with 5,000 subsamples provides insights into the statistical significance of the path coefficients in the model, offering insights into hypotheses testing results (Table 6).
Table 6
Results of hypotheses testing after the bootstrapping procedure
Hypothesis path
T statistics
p values
Hypothesis
H1: Intrinsic aspirations—> Research performance
1.771
0.077
Rejected
H2: Extrinsic aspirations—> Research performance
5.887
0.000
Supported
H3: Intrinsic aspirations—> Social exchange expectations
0.542
0.588
Rejected
H4: Extrinsic aspirations—> Social exchange expectations
0.825
0.000
Supported
H5: Social exchange expectations—> Research performance
0.755
0.450
Rejected
Source SmartPLS 4 software output
The hypothesis path Intrinsic Aspirations → Research Performance (H1) outlines a T-value of 1.771, below the threshold of 1.96, suggesting that this relationship is not statistically significant at the 95% confidence level. The p-value of 0.077 supports the rejection of this hypothesis, as it is greater than the standard significance level of 0.05. This result implies that intrinsic aspirations do not have a significant direct impact on research performance.
The hypothesis path Extrinsic Aspirations → Research Performance (H2) highlights a T-value of 5.887, which is above the common threshold of 1.96 for a 95% confidence level, and consequently indicates that this relationship is statistically significant. The p-value of 0.000 confirms this, showing a high level of significance (p < 0.05). This suggests that extrinsic motivations, such as additional income, interdependent self-construal, and self-image, have a significant positive impact on research performance.
The hypothesis path Intrinsic Aspirations → Social Exchange Expectations (H3) reveals a T-value of 0.542, which is far below 1.96, pointing to a lack of statistical significance. The high p-value of 0.588 confirms that this relationship is not significant. Therefore, intrinsic aspirations do not appear to meaningfully influence expectations for social exchange in the case of researchers passionate about an entrepreneurship topic.
The hypothesis Extrinsic Aspirations → Social Exchange Expectations (H4) illustrates a T-value of 3.825, which is significantly above 1.96, indicating that this path is statistically significant. The p-value of 0.000 further confirms this finding (p < 0.05). Therefore, researchers with higher extrinsic aspirations are more likely to have stronger expectations of social exchanges in the academic environment.
The hypothesis Social Exchange Expectations → Research Performance (H5) reflects a T-value of 0.755 below 1.96, and a p-value of 0.450 above 0.05, suggesting that this relationship is not statistically significant. This finding implies that the expectation of social exchanges does not significantly impact research performance.
4.2 FsQCA results
The analysis identified multiple combinations of causal conditions considered sufficient for the outcomes of interest to occur. The consistency score should be greater than 0.75 for a configuration to be considered sufficient (Woodside 2014). This condition can be checked by inspecting the coverage and consistency scores on fuzzy-set XY plots for the desired outcome. These plots showed that the eight antecedent conditions (ANTECEDENT = fuzzyand (MR, PG, CC, AI, SI, INDSC, INTSC, SEE)) could lead to the desired outcome of research performance (RP). With a coverage score of 0.409104 and a consistency score of 0.908845, the model shows that ANTECEDENT is very similar to the outcome of research performance. Hence, the fuzzy-set distribution is highly consistent with the idea that ANTECEDENT is a subset of research performance and covers 40.91% of the outcome.
Although the consistency and coverage scores for the data indicated strong causality among the cases represented by this configuration, additional investigation was required. Truth table analysis was performed to provide the complex, parsimonious, and intermediate solutions for the model. Studies have shown that a frequency threshold should be set to determine how many cases a configuration explains. A higher threshold reduces coverage, and a lower threshold increases it. For larger samples (in this case, 210 respondents), the threshold may be three or higher. In this study, a threshold of three was chosen. Smaller samples may have a smaller threshold of two (Pappas and Woodside 2021). The numbers in the last row appear in bold. This highlighting shows that the solution identified by the software was below the recommended threshold of 0.7 for both SYM consistency and PRI consistency, thus reducing type II and type I errors (Dul 2016). As part of the model ANTECEDENT → Outcome (behavioral intention to achieve research performance), the truth table (Table 7) illustrates several case configurations. It lists all logically possible causal configurations of antecedent conditions, which could potentially lead to the outcome.
Table 7
Truth table for the outcome
MR
PG
CC
AI
SI
INDSC
INTSC
SEE
Number
RP
Raw consistency
PRI consistency
SYM consistency
1
0
0
1
1
0
1
1
7
1
0.982
0.806
0.806
0
0
0
1
1
0
0
1
3
1
0.980
0.767
0.767
1
0
0
1
1
0
0
1
2
1
0.976
0.742
0.742
0
0
0
1
1
0
1
0
4
1
0.981
0.740
0.739
0
0
1
1
1
0
1
1
15
1
0.971
0.733
0.733
0
0
0
1
1
1
1
0
12
1
0.979
0.733
0.733
0
0
0
1
1
0
0
0
5
1
0.974
0.727
0.727
0
1
0
1
1
0
0
1
3
1
0.975
0.707
0.707
0
0
1
1
1
1
1
1
1
1
0.962
0.703
0.703
0
0
1
1
1
0
0
1
9
1
0.972
0.693
0.693
Source fsQCA software
RP, research performance; SEE, social exchange expectations, INTSC, interdependent self-construal; INDSC, independent self-construal; SI, self-image; AI, additional income; CC, community contributions; PG, personal growth; MR, meaningful relationships
The truth table for the negated outcome (absence of the outcome) is shown in Table 8. It demonstrates probable configurations of antecedent conditions that might be hurdles for scholars to achieve research performance, given that these individuals have low or no intention to invest time and intellectual effort in this endeavor.
Table 8
Truth table for the absence of the outcome
MR
PG
CC
AI
SI
INDSC
INTSC
SEE
Number
RP
Raw consistency
PRI consistency
SYM consistency
0
0
1
0
0
0
0
0
3
1
0.981
0.818
0.818
0
0
0
0
0
0
0
1
3
1
0.974
0.794
0.794
1
0
0
0
0
0
0
0
3
1
0.962
0.645
0.649
Source fsQCA software
RP, research performance; SEE, social exchange expectations, INTSC, interdependent self-construal; INDSC, independent self-construal; SI, self-image; AI,additional income; CC, community contributions; PG, personal growth; MR, meaningful relationships. The symbol “ ~ ” denotes absence
The Quine-McCluskey algorithm was then used to reduce the truth table and compute the intermediate, parsimonious, and complex solutions for the positive and negative outcomes. The analysis of the positive outcome, RP = f(MR, PG, CC, AI, SI, INDSC, INTSC, SEE), revealed nine configurations in the complex solution, seven in the parsimonious solution, and nine in the intermediate solution. The intermediate solution included the complex and intermediate, with core and peripheral conditions. The solution of causal configurations of antecedent conditions possibly leading to the outcome appears in Table 9. Analysis of the negated outcome, ~ RP = f(MR, PG, CC, AI, SI, INDSC, INTSC, SEE), was also performed (Pappas et al. 2021). This analysis looked for pathways to low or no intention to invest time and effort to achieve research performance. This analysis showed seven configurations in the complex solution, two in the parsimonious solution, and seven in the intermediate solution leading to the negated outcome. These pathways appear in Table 10.
Table 9
Configurations of antecedent conditions that could lead to high research performance
Source: fsQCA software
A black dot indicates the presence of a condition. Circles with “x” (ⓧ) indicate the absence of a condition. The red dot indicates the presence of a singular core condition (AI). The blue dot (●) and blue circle with “x” indicate that in the solution there are combined core conditions (The combined core conditions according to parsimonious solutions are: MR* ~ PG; ~ PG*CC; MR*SEE; SI*SEE; INDSC*SEE; INTSC*SEE). Blank spaces indicate indifferent conditions. RP, research performance; SEE, social exchange expectations, INTSC, interdependent self-construal; INDSC, independent self-construal; SI, self-image; AI, additional income; CC, community contributions; PG, personal growth; MR, meaningful relationships
Table 10
Configurations of antecedent conditions that lead to low or no behavioral intention to focus on research performance
Source: fsQCA software
Black dot (●) indicates the presence of a condition. Circles with “x” indicate the absence of a condition. The red circle with “x” indicates an absent singular core condition. Blank spaces indicate indifferent conditions. RP = research performance; SEE = social exchange expectations, INTSC = interdependent self-construal; INDSC = independent self-construal; SI = self-image; AI = additional income; CC = community contributions; PG = personal growth; MR = meaningful relationships
The findings from the fsQCA reveal that high perceived behavioral intention to achieve high research performance is influenced by multiple configurations of core and contributing conditions. Specifically, the table showcases nine unique pathways that contribute to high research performance through different combinations of antecedent conditions.
Solution 1 reveals the existence of a monetary-driven pathway to high research performance, where financial incentives alone are sufficient to motivate researchers. The absence of other factors underscores that some researchers may focus primarily on tangible rewards, and thus, other motivational or relational aspects do not contribute significantly to their performance.
Solution 2 represents a multi-dimensional motivational pathway, where financial incentives (AI) act as a core motivator, but the presence of other conditions such as professional relationships, personal growth, community involvement, self-perception, and a balance of independent and interdependent motivations all contribute to high research performance. This pathway suggests that researchers in this category thrive when financial incentives are complemented by a comprehensive set of personal, social, and professional growth factors.
Solution 3 highlights a relationship-driven and socially motivated pathway for achieving high research performance. The importance of combined core conditions (MR, SI, INDSC, and INTSC paired with SEE) indicates that researchers in this pathway derive motivation from positive social interactions, self-perception, and alignment between their independent and interdependent identities within their research context. This solution demonstrates that high research performance can be achieved through a focus on community dynamics and self-identity, without relying on financial rewards or a singular focus on personal growth. The presence of PG and CC suggests that while development and contributions are valued, they are only effective when coupled with strong social support and recognition.
Solution 4 represents a dual-motivational pathway where high research performance is achieved through the integration of financial rewards (AI) and complex social and relational dynamics. The presence of multiple combined core conditions (MR, SI, INDSC, INTSC paired with SEE) highlights that these researchers value financial incentives alongside a supportive, identity-affirming environment. The interplay between self-image, interdependent self-construal, and social exchanges suggests that researchers in this pathway are highly associated to how their identity is constructed within their research community. This need for recognition and social validation, coupled with the tangible benefits of additional income, creates a powerful motivational profile.
Solution 5 presents a financially and socially balanced pathway, where high research performance is achieved by combining financial incentives (AI) with social and identity-driven factors. The presence of the three composed core conditions (SI + SEE, INDSC + SEE, INTSC + SEE) indicates that these researchers are highly responsive to how their self-concepts are reinforced by social exchanges, with financial rewards acting as the foundation of their motivation. The presence of supporting conditions like PG and CC shows that these researchers value growth and contributions to the research community, but only when aligned with their core drivers of financial and social recognition.
Solution 6 reflects a relationship-centric pathway to achieving high research performance, where the motivation comes exclusively from the presence of meaningful professional connections. These relationships serve as the main driver of performance, and there is no need for additional personal or professional development activities (absence of PG). The complete absence of other motivators such as financial rewards, self-perception, and social exchanges suggests that the relational aspect is sufficient on its own to inspire high performance for this group of researchers.
Solution 7 represents a community-driven pathway, where high research performance is primarily motivated by an external focus on community contributions (CC) rather than internal growth or self-enhancement. The absence of PG indicates that these researchers do not require personal growth as a motivator; instead, they prioritize making an impact on their academic community. This solution suggests that for some researchers, the ability to contribute meaningfully to the research community and the collective success of others is sufficient to drive high research performance. Personal advancement, financial rewards, and social exchange dynamics are irrelevant for their motivation.
Solution 8 represents a socially integrated and identity-driven pathway to high research performance, where a combination of meaningful relationships (MR) and community contributions (CC) in the absence of personal growth serves as the core motivator. The presence of both independent and interdependent self-construal (INDSC, INTSC) suggests that these researchers can navigate both personal and collective success, while the presence of self-image (SI) indicates that they are also motivated by their professional reputation. The absence of AI and SEE shows that neither financial incentives nor expectations of social exchange are necessary for them to perform at a high level. Instead, they are driven by the impact they make through relationships and community engagement.
Solution 9 represents a socially and identity-driven pathway where high research performance is achieved through a complex configuration of relational dynamics, social exchanges, and balanced self-construal orientations. Researchers in this pathway are highly motivated by the quality of their meaningful relationships (MR), how their self-image (SI) is validated through social exchanges (SEE), and the interaction between both independent (INDSC) and interdependent (INTSC) orientations with social exchanges. The multiple combined core conditions indicate that these researchers are attuned to social expectations and how their identity is perceived and reinforced within the community. The presence of SEE across the combined core conditions underscores the importance of social validation and reciprocities in driving high research performance.
The overall solution consistency of 0.84552 and solution coverage of 0.651743 indicate that the identified pathways are both reliable and cover a substantial proportion of high research performance cases. Ultimately, the analysis highlights that high research performance is achieved through diverse motivational and contextual factors, demonstrating the multifaceted nature of academic success.
Solution 1 represents a disconnected and demotivated pathway, where the lack of community contributions, meaningful relationships, and self-motivational factors results in low or no perceived intention to achieve high research performance. The absence of CC as a core condition, along with the absence of MR, PG, SI, INDSC, and INTSC, indicates a complete lack of connection to the research community and self-identity. Without these motivating factors, researchers in this group have little intention or drive to strive for better performance.
Solution 2 represents a disengaged pathway, where low or no intention to achieve high research performance is driven by the absence of Community Contributions (CC) and Social Exchange Expectations (SEE) as core conditions, along with the absence of other personal, social, and financial motivators. The absence of both CC and SEE indicates that these researchers lack a sense of community purpose and do not see value in participating in reciprocal social exchanges. The complete absence of growth, self-construal, and financial motivators shows that they are not driven by individual development or external rewards, resulting in a highly demotivated state.
Solution 3 represents an isolated and socially disconnected pathway for low or no intention to achieve high research performance, driven by the absence of Social Exchange Expectations (SEE) as a core condition and other critical personal and social motivators. The absence of SEE suggests that these researchers do not expect or value reciprocal support or recognition, which leads to a sense of isolation. The lack of meaningful relationships, self-construal, and self-image concerns indicates that these researchers have little connection to their research environment, either personally or socially. Without tangible or intangible motivators like AI, PG, and SI, their engagement in research remains minimal, resulting in a low intention to strive for better performance.
Solution 4 represents a motivationally conflicted pathway, where several positive conditions are present (MR, CC, SI, INDSC, and INTSC), but the absence of social exchange expectations (SEE) as a core condition undermines their overall intention to perform. The presence of supportive relationships, community involvement, and balanced self-construal indicates that these researchers have the potential to be highly motivated, but the lack of perceived social exchange and recognition (absence of SEE) creates a disconnect, leading to low or no intention to achieve high research performance.
Solution 5 represents a frustrated and unsupported pathway, where several positive motivational factors are present, but the absence of social exchange expectations (SEE) as a core condition undermines their overall intention to perform. The lack of SEE creates a disconnect between the researchers and their community, making them feel undervalued and unsupported, despite having strong relationships, opportunities for personal growth, community involvement, and a balanced self-construal orientation. This pathway suggests that positive conditions such as MR, PG, CC, SI, INDSC, and INTSC can lose their effectiveness when researchers do not perceive reciprocal support or social validation (SEE).
Solution 6 represents a disconnected and unanchored pathway, where several positive motivational factors (meaningful relationships, self-image, both independent and interdependent self-construal, and social exchange expectations) are present, but the absence of community contributions (CC) as a core condition undermines their intention to achieve high performance. The lack of community engagement disrupts the alignment between personal motivations and collective goals, making these researchers feel disconnected and unmotivated. The presence of supportive relationships, a positive self-image, and a balance of self- and group-oriented perspectives are not enough to sustain high motivation in the absence of community contributions. The absence of personal growth (PG) and financial incentives (AI) further weakens motivation, as there are no other tangible or self-development-related factors to compensate for the lack of community involvement.
Solution 7 represents a misaligned motivational pathway, where several positive motivational factors (e.g., meaningful relationships, personal growth, financial incentives, self-image, balanced independent and interdependent self-construal, and social exchange expectations) are present, but the absence of community contributions (CC) as a core condition undermines their overall intention to achieve high research performance. This solution indicates that these researchers have strong motivations for individual success and recognition, yet their lack of community involvement disrupts the alignment of their motivations, making it difficult for them to translate these positive conditions into high research performance. The absence of CC weakens the impact of other conditions, such as meaningful relationships, social exchanges, and independent and interdependent self-construal, as the lack of community engagement prevents these researchers from feeling a part of a larger collective effort.
According to Ragin (2000), configurational reasoning constitutes the fundamental basis of fsQCA. Causal complexity denotes that a specific outcome in a social context may arise from various combinations of causal conditions. In an academic setting, where researchers are driven by diverse motivations, this factor is critically significant. A primary advantage of fsQCA is its acceptance of equifinality, or multiple causation, indicating that various pathways can lead to the same outcome. FsQCA is founded on the principle of conjunctural causation. This concept signifies that the effect of a causal condition depends on its interaction with other conditions for an event to transpire. The conjunctural causation principle in fsQCA provides a more thorough understanding of how multiple factors can collectively influence the intention to dedicate time and effort to academic research performance.
The necessary conditions for either high or low/no perceived behavioral intention to achieve high research performance were also analyzed (Table 11). A consistency threshold of 0.9 was established to identify the factors driving the lack of intention to achieve high research performance.
Table 11
Necessary conditions for high and low/no behavioral intention to focus on research performance
Conditions tested for RP
Consistency
Coverage
Conditions tested for ~ RP
Consistency
Coverage
MR
0.760
0.712
MR
0.750
0.676
~ MR
0.654
0.731
~ MR
0.680
0.732
PG
0.755
0.691
PG
0.742
0.654
~ PG
0.622
0.715
~ PG
0.649
0.718
CC
0.782
0.675
CC
0.767
0.638
~ CC
0.580
0.721
~ CC
0.610
0.729
AI
0.702
0.743
AI
0.657
0.669
~ AI
0.687
0.675
~ AI
0.747
0.707
SI
0.878
0.759
SI
0.699
0.581
~ SI
0.516
0.640
~ SI
0.710
0.849
INDSC
0.800
0.725
INDSC
0.744
0.650
~ INDSC
0.614
0.713
~ INDSC
0.685
0.767
INTSC
0.788
0.686
INTSC
0.756
0.634
~ INTSC
0.579
0.712
~ INTSC
0.625
0.740
SEE
0.747
0.731
SEE
0.696
0.656
~ SEE
0.649
0.689
~ SEE
0.715
0.731
Source fsQCA software
RP, research performance; SEE, social exchange expectations, INTSC, interdependent self-construal; INDSC, independent self-construal; SI, self-image; AI, additional income; CC, community contributions; PG, personal growth; MR, meaningful relationships
The necessary conditions for behavioral intention to achieve high research performance were analyzed (Table 11). A consistency threshold of 0.90 was set to identify the factors that are essential for motivating high research performance. None of the conditions reached this threshold, indicating that no single condition is strictly necessary on its own. However, several conditions approached high levels of consistency, suggesting they play influential roles. Self-image (SI) had the highest consistency (0.87812), indicating its importance for achieving high research performance. Researchers who perceive a strong self-image tend to show a higher intention to perform well. Community contributions (CC) (0.782036), interdependent self-construal (INTSC) (0.788485), and independent self-construal (INDSC) (0.799514) also displayed relatively high consistency, highlighting that both community engagement and balanced self-perceptions are influential factors. Meaningful relationships (MR) and personal growth (PG), while still relevant, showed slightly lower consistency scores, suggesting their supporting role in achieving high research performance.
For low or no perceived behavioral intention to achieve research performance, the absence of several conditions reached high consistency scores. The absence of self-image (SI) had a high consistency score (0.710222), suggesting that a weak or unclear professional identity is a strong indicator of low intention to perform. Similarly, the absence of additional income (AI) (0.747403) and the absence of independent self-construal (INDSC) (0.685273) indicate that a lack of financial motivation and autonomy are key factors contributing to low research performance.
Overall, while no single condition alone is strictly necessary for high research performance, factors related to self-image, community contributions, and balanced self-construal orientations stand out as critical influences. Conversely, low intention is strongly associated with the absence of self-image, additional income, and autonomous identity, indicating that these are pivotal deterrents to research performance.
4.3 Overall results
In sum, the PLS-SEM results suggest that extrinsic motivations, such as recognition or additional income, exert a strong positive impact on research performance and significantly heighten social exchange expectations, whereas intrinsic motivations, such as personal growth, meaningful relationships, do not show a direct link to research output. Moreover, expectations for social exchanges do not significantly mediate the relationship between motivation and research performance.
In contrast, fsQCA reveals multiple factor configurations, such as a researcher’s self-image, community contributions, and the interplay of independent and interdependent self-construal, that drive high research performance. This asymmetrical perspective highlights that there is not only one path leading to high productivity. Rather, different combinations of motivational conditions and social factors may yield similar performance outcomes.
Together, these findings reinforce the importance of both linear and configurational approaches in capturing the nuanced ways motivation and social exchange expectations shape entrepreneurship scholars’ research performance.
5 Discussion
The results stem from an examination of a theory-based research model, which investigates the influence of intrinsic and extrinsic ambitions on the research performance of scholar and the mediating effect of social exchange expectations. The key finding of the study is that extrinsic aspirations have a positive influence on both social exchange expectations and research performance. This result is consistent with two of the hypotheses (H2 and H4). To the best of the authors’ knowledge, this finding is a novelty and has not yet been investigated in this context. The research approach of this study contributes to existing literature on what motivates researchers, as it not only refers to intrinsic motivation but also explores extrinsic motivation in the research environment. In addition, the understudied influence of social networks on collaboration relationships and the resulting expectations of social exchange between researchers as well as the influence of the different types of aspirations on these social exchange expectations were examined. The insight that extrinsic motivation can have a positive effect on such expectations has hardly been investigated to date.
To determine whether intrinsic ambitions were positively related to research performance (H1), intrinsic ambitions were measured based on community contributions, meaningful relationships, personal growth, and independent self-construal. A positive correlation was predicted for the individual results. The data was not sufficient to confirm that intrinsic ambition is positively related to the research performance, as none of the results showed a significant correlation. In the current literature both regarding academics (Peng and Gao 2019; Stupnisky et al. 2023) and other individuals (Cerasoli et al. 2014; Good et al. 2022), intrinsic motivation is constantly associated with better performance. Stupnisky et al. (2019a) found in a study of around 1,800 academic faculty members that intrinsic motivation is a predictor of perceived success and that it is moderately related to the number of publications and self-reported productivity. Horodnic and Zaiţ (2015) also concluded that researchers who are highly engaged in their work, i.e. are intrinsically motivated, had a higher research productivity. These results are consistent with SDT, which assumes that if someone particularly enjoys what they do and it is important to them, they will act accordingly (Deci and Ryan 1985a, 2000). In this case, it should have a positive effect on research performance if scholars enjoy conducting research and are particularly interested in their field of research. Since, according to previous results, the relationship between intrinsic ambitions and research performance was expected to be confirmed (Chen et al. 2006; Horodnic and Zaiţ, 2015; Peng and Gao 2019; Stupnisky et al. 2019a; Tien 2008), the lack of significance could be attributed to a problem with the design of the study or an insufficient sample rather than a lack of correlation.
Extrinsic ambitions were assessed to determine whether they were positively related to research performance (H2) by measuring additional income, self-image, and interdependent self-construal. The results confirmed that extrinsic ambitions are positively associated with research performance. While the findings for additional income and interdependent self-construal were moderately significant, the results for self-image were found to be highly significant. Even though a positive correlation was assumed and found, and this is confirmed by parts of the literature (Chen et al. 2006; Stupnisky et al. 2019a), some studies come to the opposite conclusion (Horodnic and Zaiţ, 2015; Peng and Gao 2019). Horodnic and Zaiţ (2015) as well as Peng and Gao (2019) found in their study that extrinsic motivation had a negative effect on research performance. Horodnic and Zaiţ (2015) explained this correlation by the fact that nowadays researchers who are externally motivated can find alternative ways to achieve their goals and therefore research does not have to be the focus. While this argument could provide a plausible explanation for the results of the study, the different results could also be due to the items used to measure extrinsic ambitions. Chen et al. (2006) and Tien (2008) found a positive effect of promotion as an extrinsic aspiration. In their study, Chen et al. (2006) differentiated between promotion and salary increase, among other things.
According to the researchers surveyed, higher research performance was most likely to lead to a permanent position and a promotion, and they rated the consequence of a higher salary much lower (Chen et al. 2006). In thisr study, promotion was not explicitly mentioned in the extrinsic ambition items but could be implicitly included in the significant result on self-image, as promotion not only leads to a higher income but also increases reputation (Lam 2011). In this context, the mixed findings may perhaps be because extrinsic ambitions cannot be equated in their influence and a distinction would have to be made between self-image and additional income when formulating the hypothesis. The deviating results may also be due to the nature of the extrinsic aspirations. In some cases, the term controlled extrinsic motivation is used, i.e. when the task is not interesting in itself and therefore requires an external incentive (Gagné and Deci 2005). However, extrinsic motivation can also be autonomous if the individual identifies with the goal behind it and the external incentive is no longer the only reason behind the behavior (Gagné and Deci 2005). Therefore, it would be interesting to observe the degree of internalization in the respective results, indicating the extent to which a motivation is autonomous or not.
H3 and H4 examine the relationship between intrinsic and extrinsic ambitions and social exchange expectations. Similarly, intrinsic ambitions were measured in terms of contributions to the community, meaningful relationships, personal growth, and independent self-construal, and extrinsic ambitions based on additional income, self-image, and interdependent self-construal. When examining the question of whether intrinsic ambitions are positively related to social exchange expectations (H3), a significant effect could not be found. Even if a trend towards significance can be seen concerning independent self-construal, the H3 hypothesis could not be confirmed due to the overall lack of significance. This result is noteworthy because, to the authors’ knowledge, this effect has not yet been studied with a view to the behavior of researchers. To contextualize the result, other areas of the literature must be consulted. In the case of volunteering, the positive influence of intrinsic motivation on the formation of social capital was examined i.e. the extent to which this type of motivation increases the formation of social networks (Degli Antoni 2009). In addition, Katoh et al. (2021) concluded that the intrinsic motivation of researchers has a positive effect on research collaboration. These results suggest that when individuals are intrinsically motivated, this can have a positive effect on the formation of relationships to realize their intrinsically motivated goal. Drawing on SET, which states that people expect positive behavior to be reciprocated (Cropanzano et al. 2017), intrinsic motivation is assumed to lead to higher expectations of social exchange in the course of increased collaboration. However, it is also possible that intrinsically motivated researchers help others in their studies for the sake of research and not to generate an advantage for themselves. This could be explained by the fact that intrinsic motivation, in contrast to extrinsic motivation, is not triggered by an external reward (Deci et al. 2017), in this case, the expected reciprocated support from colleagues. Therefore, the results could indicate a non-existent relationship between intrinsic aspirations and social exchange expectations.
However, significant results were obtained for the question of whether extrinsic ambitions are positively related to social exchange expectations (H4). It was found that additional income, self-image, and interdependent self-construal are positively associated with social exchange expectations. For this reason, H4 can be confirmed. As previously established, intrinsically motivated people are more socially engaging (Degli Antoni 2009) and tend to collaborate more in their research (Katoh et al. 2021). Regarding extrinsic motivation, Katoh et al. (2021) concluded that external rewards can have a positive effect on research collaboration, especially when there is little or no intrinsic motivation in this regard. Degli Antoni (2009) found that when people join networks for extrinsic reasons, this increases the number of connections, but these do not imply a deeper social connection. Based on these results, it can be assumed that when researchers work together for extrinsic reasons, this collaboration is primarily seen as a means to an end. In this case, the collaboration is not just for fun, but to generate long-term added value. These findings support the interpretation of this result as they suggest that when researchers support colleagues, they expect this in return to add value. This is a remarkable finding as, to the atuthors’ knowledge, this specific effect has not yet been studied.
The final hypothesis (H5) examined social exchange expectations as a mediator in the relationship between both extrinsic and intrinsic aspirations on research performance. In this case, the hypothesis could not be confirmed based on the results. Regarding the mediating effect on intrinsic aspirations and research performance, this result could be because there is no link between intrinsic aspirations and social exchange expectations to begin with. This interpretation would be confirmed by the rejection of H3. In contrast, however, a positive effect of intrinsic aspirations and social exchange expectations was found, i.e. H4 was confirmed. This discovery and the existing studies that highlight the connection between collaboration and research performance (Abramo et al. 2017; Kwiek 2016; Rodriguez Miramontes and Gonzalez-Brambila 2016; Wuchty et al. 2007) support the assumption of a mediating effect. The absence of this effect could be explained by the fact that although extrinsically motivated researchers try to achieve their goals in the form of social connections while expecting the support of their colleagues, this does not necessarily mean that they are more productive in research. This could be due to the lack of a deeper connection between the researchers, as they only work with each other for extrinsic reasons (Degli Antoni 2009), thus leading them to work less closely or consistently with each other. It may also be that just because an increased expectation is placed on the other party to reciprocate a service (Cropanzano et al. 2017), the recipient does not necessarily have to fulfill this expectation. For this reason, the result implies that although the findings suggest that extrinsically motivated scholars have higher expectations of their colleagues to reciprocate supportive behavior (H4), this does not necessarily have to be reciprocated by their counterparts and thus does not necessarily lead to more research productivity.
The findings are broadly in line with the findings in prior research. For example, Aryee et al.’s (2015) findings show that fulfilled psychological needs (via SDT) together with fair, reciprocal exchanges (via SET) jointly boost performance. Similarly, Henderson and Jeong (2024) highlight how LMX, which also represents a social exchange-based construct, fosters more self-determined motivation, which also improves performance. However, while, according to the results, social exchange expectations do not significantly mediate between motivation and performance, Aryee et al. (2015) find a more prominent synergy between SDT and SET factors. The reason for this discrepancy may be that in academia extrinsic rewards incentivize productivity in a stronger way than in other working contexts, whereas social exchange dynamics work in subtler ways.From the configuration research design perspective, the study successfully identifies various unique configurations of conditions that lead to high research performance. This highlights the complexity of achieving high performance and emphasizes that different combinations of factors, such as financial incentives, meaningful relationships, and self-construal orientations, can contribute to success. This insight adds depth to understanding academic motivation and performance. The consistency and coverage scores demonstrate that the proposed model is reliable and explains a substantial portion of the observed research outcome. This strong empirical backing increases the study’s validity and the relevance of the identified pathways. The findings show that self-image (SI) and community contributions (CC) play a crucial role in high research performance. With SI achieving the highest consistency score, the study underscores the importance of professional identity and community engagement in motivating researchers, in line with the findings from O’Meara (2013).
5.1 Theoretical implications
The findings of this study contribute to entrepreneurship research by applying SDT and SET to the academic research context. While SDT traditionally emphasizes the importance of intrinsic motivation, such as personal growth and enjoyment, for higher research performance, this study demonstrates that extrinsic motivations, like financial rewards and professional recognition, are highly relevant predictors in driving research performance among entrepreneurship scholars. This challenges the prevailing assumption in SDT that intrinsic motivation is always the strongest predictor of high-quality outcomes, suggesting that external rewards could enhance productivity in academic environments. Additionally, the integration of SET provides new insights into how social exchanges, such as collaborative relationships and reciprocal academic support, mediate in a low extent the impact of both intrinsic and extrinsic motivations on research performance. The study outlines that researchers with strong extrinsic aspirations are more likely to engage in social exchange, which further amplifies their research productivity. The findings also highlight the interconnectedness of motivation and social structures in academia, offering a clear understanding of motivation impact on performance within the global academic campus.
5.2 Practical implications
The results indicate practical implementation possibilities to better support researchers in their work and to contribute towards better performance. Even though the results are not conclusive in this area, it is in line with the existing literature that considers intrinsic motivation to be crucial for research performance (Chen et al. 2006; Horodnic and Zaiţ, 2015; Peng and Gao 2019; Stupnisky et al. 2019a; Tien 2008). Therefore, it seems essential to encourage researchers to explore and pursue questions in areas that are of interest to them. For scholars to further explore their areas of interest, universities could offer and promote workshops, various forms of collaboration, and sabbaticals.
In addition, the results indicate that extrinsic motivation leads to increased interaction with colleagues. While collaboration and networking have long been an essential part of scientific work (Beaver and Rosen 1979), this insight sheds light on another level of motivation, which can also be supported by enabling additional collaboration and networking. The results of this type of research are particularly important for higher education institutions that are keen to improve their productivity and quality of research. Therefore, these findings will lead to a better understanding of what motivates researchers, how this motivation affects their work, behavior, and expectations, and how this ultimately impacts their performance.
Academic institutions ‘leaders should recognize the value of both intrinsic and extrinsic motivators by creating environments that not only foster intellectual efforts and personal growth but also provide tangible rewards, such as financial incentives, recognition, and opportunities for career advancement. Additionally, promoting collaborative networks and social exchanges among faculty will lead to enhanced research outcomes. By strategically leveraging these factors, academic institutions will be able to create a more motivating and supportive environment for higher-quality research outcomes.
5.3 Limitations and future research
Even though the study has come to important conclusions, it was subject to some limitations that can be addressed in future research. This study was primarily based on a single motivational theory, SDT. In this research, motivation was generally categorized as intrinsic and extrinsic. For future studies, it could be of interest to make a more complex distinction and, in particular, to look at the degree of internalization (Gagné and Deci 2005). Furthermore, it may also be relevant to consider more recent understandings of SDT that also address the level of internalization within motivation (Sheldon et al. 2017).
In addition, the results of H1 indicate that the sample was not sufficiently large, making it difficult to obtain meaningful results. As far as extrinsic motivators are concerned, it still seems uncertain to what extent and which forms of extrinsic rewards have a positive influence on research performance, which is why this area should be studied in more detail. The separation of financial rewards, career rewards and intrinsic satisfaction as motivators within the study could be of interest (see Blind et al. 2018 and Lam 2011). Another limitation relating to the sample is the focus on editorial boards and on the first and second quartile of entrepreneurship journals. Therefore, entrepreneurship researchers who are not members of editorial boards or of thorse from the third and fourth quartile are not represented in the sample. It cannot be ruled out that the motivations of these researchers are different.
From a PLS-SEM perspective, a limitation of this study relates to the potential constraints on generalizability and model complexity. First, while PLS-SEM is effective for exploring relationships in complex models with latent variables, it often requires larger sample sizes for robust results, and the sample size in this study, though adequate, may not fully capture all relevant insights in the broader research community on entrepreneurship.
Despite identifying multiple pathways within the fsQCA approach, the study reveals that no single condition reached the established consistency threshold of 0.90, indicating that no factor is strictly necessary for high research performance. This lack of a definitive condition may limit the practical application of the findings, as it suggests that the factors influencing high performance are highly context-dependent and vary significantly across researchers.
Overall, the research on the relationship between motivation and social exchange expectations reveals a phenomenon that has hardly been investigated to date. As part of the research, SET was used, which proved to be a robust construct for the analysis. Building on this, further studies should shed more light on this area to gain a better understanding and more insights into the relationships between motivation, expectations of social exchange, as well as research performance.
Future research should explore several avenues to build on the findings of this study. First, a longitudinal design could be employed to examine how intrinsic and extrinsic motivations, as well as social exchange expectations, evolve and impact research performance in different stages of academic careers. Additionally, expanding the study to a larger and more diverse sample of scholars from various disciplines would help enhance the generalizability of the results. Lastly, future studies could investigate other mediating variables, such as institutional support and cultural differences, to better understand how different academic environments shape the motivation-performance dynamic.
6 Conclusion
This study provides valuable insights into the relationship between motivation and research performance among entrepreneurship scholars by integrating SDT and SET.
Notably, extrinsic motivations, such as the desire for recognition, financial incentives, and professional prestige, emerge as powerful drivers of research productivity. These findings open new avenues for research, challenging the traditional perspective, which predominantly emphasizes intrinsic motivation, by highlighting the significant role external rewards play in motivating scholars to produce higher-quality research. Another important finding is the role of social exchange expectations: researchers with strong extrinsic motivations are more inclined to engage in reciprocal collaborations, which further enhances their research output. Thus, the academic ecosystem, where collaboration and mutual support are valued, increases the impact of extrinsic motivators, leading to more robust research outcomes. These insights contribute to a broader understanding of how motivation interacts with the academic environment to influence research performance, particularly in the field of entrepreneurship. These results suggest that a balanced approach, recognizing the contributions of both intrinsic and extrinsic motivations, is essential for empowering researchers ‘success.
Acknowledgements
We thank the two anonymous reviewers for their insightful and constructive comments, which increased the overall quality of this paper. We used the support of AI tools to improve the argumentation and wording of some sections of the manuscript that was originally written by the authors.
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