Journal of Entrepreneurship, Management and Innovation (2024)

Volume 20 Issue 2: 53-74

DOI: https://doi.org/10.7341/20242023

JEL Codes: M1, L26

Rrezon Lajçi, Ph.D Candidate and Research Assistant, Technische Universität Ilmenau, Department of Economic Sciences and Media, Management/Organization Research Group Helmholtzplatz 3, 98693 Ilmenau, Germany, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Gentrit Berisha, Prof. Dr., Assistant Professor, University of Prishtina, Department of Management, Prishtina, Republic of Kosovo, Agim Ramadani Street, nn, 10000 Prishtina, Kosovo, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Besnik Krasniqi, Prof. Dr., Full Professor, University of Prishtina, Department of Management, Prishtina, Republic of Kosovo and Staffordshire University, Department of Economics, Stoke-On-Trent, UK, Agim Ramadani Street, nn, 10000 Prishtina, Kosovo, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract

PURPOSE: The entrepreneurship-ethics nexus draws considerable interest from researchers and practitioners with little resolution. Our purpose with this paper is to contribute to the debate by shedding light on the relationship between managers’ attitudes toward unethical behavior and their subsequent entrepreneurial intention (EI) in an emerging economy context. Given the complex and multifaceted interplay between unethical behavior and EI, we extend our investigation by including decision-making speed and attitude toward risk to explain the relationship further. We take a granular approach to facets of unethical behavior to gain deeper insights into the specificity of influences they pose on subsequent behavioral intentions. METHODOLOGY: Primary data were collected from 214 Kosovan managers employed in companies from different industries. Hypothesized relationships were tested by conducting hierarchical regression analyses. FINDINGS: Our results indicate that managers with higher EI are not necessarily unethical overall. We did not find support for the hypothesis that managers with stronger attitudes toward unethical behavior demonstrate higher entrepreneurial intentions. Focusing on dimensions of unethical behavior, we find that managers who favor bribery are more entrepreneurially inclined. Furthermore, we find that managers who are quick decision-makers and risk-takers express higher EI. IMPLICATIONS: Theoretically, we add to the existing body of research on ethics and entrepreneurship by empirically examining the relationship between attitude toward unethical behavior and EI and the viability of the Theory of Planned Behavior as a framework for integrating unethical behavior in entrepreneurship research. Our study affirms the extension of the theoretical and empirical underpinnings concerning ethics and entrepreneurship, contemplating that they are pervasive across contexts. We provide important practical implications for managers, especially in the corporate entrepreneurship and training context. Managers are encouraged to foster an entrepreneurial-friendly environment that abides by ethical standards. Our study also informs policymakers of the importance of formal education on entrepreneurship as a mechanism to enforce ethical awareness in future entrepreneurs and intrapreneurs. ORIGINALITY AND VALUE: This study is among the first attempts to test the relationship between unethical behavior and EI in a managerial sample and non-western context.

Keywords: entrepreneurial intention, unethical behavior, bribery, risk-taking, decision-making speed, intrapreneurial managers, entrepreneurship-ethics nexus, hierarchic regression analysis, corporate entrepreneurship, theory of planned behavior, ethical standards, entrepreneurship

INTRODUCTION

Ever since McClelland (1961) contemplated what determines the ethical behavior of entrepreneurs, the topic of ethics has appeared recurrently in entrepreneurship research. In the early days of entrepreneurship, when entrepreneurs were considered solely profit-driven risk-takers (Brockhaus, 1987), entrepreneurship and ethics were oxymoronic (Blockson, 2012). However, the move toward a ‚more-than-economic’ interpretation of entrepreneurship (Dey & Steyaert, 2015) has laid the riverbed for these two research streams to unite. Lately, there has been growing interest in bridging the fields of entrepreneurship and business ethics (for reviews, see Hannafey, 2003; Harris, Sapienza, & Bowie, 2009; Vallaster, Kraus, Lindahl, & Nielsen, 2019). There is a growing consensus that the entrepreneurship-ethics liaison has moved from an intense love-hate relationship (Fisscher, Frenkel, Lurie, & Nijhof, 2005) into a consolidated one.

Research has predominantly focused on examining entrepreneurs’ inclinations and their involvement in unethical behaviors (for a review, see Vallaster et al., 2019). However, the converse perspective, or how unethical behaviors may influence individuals’ propensity to become entrepreneurs, has largely been overlooked. Unethical behaviors can impact an individual’s reputation, prompting them to consider entrepreneurship a viable alternative to traditional employment, where a stained reputation could limit opportunities. Our study builds upon Bird’s (1988, 2015) work on EI. By revisiting her intention model of entrepreneurship, Bird (2015) emphasizes the need for future research to incorporate patterns prevalent in today’s world that shape EI. According to the author, investigating temporal tensions and urgencies stemming from competition or financial pressure that might push individuals to act in unethical ways in their entrepreneurial endeavors might be a promising research avenue.

The business ethics literature has been deprived of a theoretical grounding to guide research on unethical behaviors (Grover, 1993). Several underpinnings have been proposed; however, most studies are conducted without any theoretical grounding. The theoretical underpinning of this study is situated at the confluence of the scholarly discourse on unethical behavior and entrepreneurial decision-making and intentions. For this research, we dwell on the theory of planned behavior (TPB), which has been used considerably in unethical behavior literature (Kantor & Weisberg, 2002).

The TPB model has been attested as useful in explaining the attitude-intention-unethical behavior relationship (Chang, 1998). We include attitude toward unethical behavior as the attitude in our TBP framework, which has been previously evidenced in research (Kantor & Weisberg, 2002). As we rely on the theory rather than the model, we tread the established practice in research of modifying TPB (Sparks & Guthrie, 1998). Namely, we use attitude toward risk and a measure of decision-making speed as a facet of self-efficacy as drivers of entrepreneurship as well. TBP guides most studies concerning entrepreneurial intention (EI), the independent variable in our model (Rueda, Moriano, & Liñán, 2015). Following TPB, we can expect individuals to choose to engage in unethical behaviors based on their beliefs about the behaviors and their expectation of a positive outcome after engaging in such behavior (Harding, Mayhew, Finelli, & Carpenter, 2007).

Thompson (2009, p. 676) delineates EI as a “self-acknowledged conviction by a person who intends to set up a new business venture and consciously plans to do so at some point in the future.” Nevertheless, besides new venture creation, EI also involves new value creation in existing ventures (Bird, 1988), known as corporate entrepreneurship and intrapreneurship (Kuratko, Ireland, & Hornsby, 2004).

Corporate entrepreneurship and intrapreneurship are prevailing concepts employed in the literature to describe entrepreneurial undertakings within existing organizations (Blanka, 2019). Unlike corporate entrepreneurship or pursuing new endeavors from an organizational perspective, intrapreneurship is a bottom-up process initiated at the individual level (Sinha & Srivastava, 2013).

Concerning our independent variables, unethical behavior is defined as individuals’ attitude toward engaging in morally unacceptable or illegal actions to the larger community (Jones, 1991). Following Forbes (2005), we refer to decision-making speed as how quickly managers make decisions inherent in their individual characteristics. Whereas attitude toward risk-taking represents individuals’ preference toward engaging in highly uncertain activities (Dohmen et al., 2011).

An extended body of knowledge on entrepreneurship has been developed by focusing on intention as a proxy for subsequent behaviors (Ajzen, 1991). Nonetheless, only a few studies focus on the intentions of managers to act entrepreneurially as corporate entrepreneurs/intrapreneurs. The first endeavor to reconcile ethical behavior and corporate entrepreneurship is that of Chau and Siu (2000). The authors purport that organizational characteristics of the entrepreneurial environment temper the environmental adversity toward unethical behavior. This firm-level approach has prevailed in successive studies concerning ethical aspects of corporate entrepreneurship. Vallaster et al. (2019) find no occurrence of corporate entrepreneurship or intrapreneurship in their bibliometric analysis of ethics in entrepreneurship research. This suggests that corporate entrepreneurship/intrapreneurship and ethics are largely unexplored in research. The first-ever review on the entrepreneurship-ethics nexus calls for further research on the ethics constructs and intrapreneurship (Hannafey, 2003). We respond to this call by examining the EI of managers associated with individual unethical workplace behaviors in a non-Western context.

Our study is particularly important given the context in which it is placed. Post-socialist emerging economies differ from other contexts in the sense that the borders between the private and the public spheres are blurred (Takacs Haynes & Rašković, 2021). The institutional environment in non-Western, emerging economies provides more opportunities for organizational misconduct and unethical behavior (Anand, Rottig, Parameswar, & Zwerg‐Villegas, 2023). When employees perceive an inefficient and bureaucratic institutional environment, corruption or bribery become circumventing mechanisms to bring intrapreneurial or entrepreneurial ideas to life (Sánchez-Vidal, Ramón-Llorens, & La Rocca, 2024).

This paper purports a fivefold distinctive contribution to the existing body of research. First, we investigate how ethical behavior affects the EI of managers. Prior theorization and research considered ethical or moral aspects as dependent variables influenced by entrepreneurship constructs (Chau & Siu, 2000). Second, we assess the entrepreneurial intention instead of social entrepreneurial intention, which has dominated the intention-based studies of entrepreneurial ethics (Choi et al., 2021). Third, we conducted the study with a managerial sample, assessing how their ethical behavior affects their intrapreneurialism. Most studies relating personal values to entrepreneurship use student samples (Hueso, Jaén, & Liñán, 2021), making the representativeness and comparisons questionable. Fourth, our study evades the overwhelming normative and descriptive approach to studying ethics at the individual level (Alzola, 2011). Instead, we take a more applied ethics approach, explaining how attitude toward unethical behavior influences intentions. Attitudes have strong predictive power due to their nature as less stable, changing across time and situations, and being more domain-specific (Robinson, Stimpson, Huefner, & Hunt, 1991). Through attitudes (toward unethical behavior, toward decision speed, toward risk), we purport to predict (entrepreneurial) intentions, which in turn are considered the best predictors of (entrepreneurial/intrapreneurial) behavior (Krueger Jr, Reilly, & Carsrud, 2000). Fifth, we investigate the ethical behavior-EI nexus in the developing economy context of Kosovo, an Eastern European country. Entrepreneurship and ethics research has been largely inattentive to the emerging economies context (Ahmad & Ramayah, 2012).

LITERATURE REVIEW

Entrepreneurship and ethics are two of the most discussed issues in business nowadays (Kuratko & Goldsby, 2004). Management scholars have found an unequivocal resemblance between ethics and entrepreneurship. Solymossy and Masters (2002) find striking similarities between the characteristics of entrepreneurs that distinguish them from non-entrepreneurs and ethical behaviors concerning moral issues individuals face. Similarly, Buchholz and Rosenthal (2005) posit that entrepreneurial and ethical behavior require the same qualities: imagination, creativity, novelty, and sensitivity.

According to Brenkert (2002), ethical aspects of entrepreneurship are studied at the micro, meso, and macro levels. Notwithstanding, ethical entrepreneurship research has little theoretical and conceptual robustness (Vallaster et al., 2019). While theoretical underpinnings from both fields have been transcended to explain the phenomena in ethical entrepreneurship research (Chau & Siu, 2000), theoretical and empirical contributions twining EI and ethics are scarce (Tipu & Ryan, 2016). Harris et al. (2009) purport that most of the research focuses on the micro-level, with considerable attention devoted to individual differences that influence ethical behavior differences among entrepreneurs and non-entrepreneurs. One line of research focuses on differences between entrepreneurs and managers concerning ethical values, attitudes, and behaviors (Bucar, Glas, & Hisrich, 2003; Bucar & Hisrich, 2001; Carland III, Carland Jr, Carland, & Pearce, 1995).

Managers are the main bearers of corporate entrepreneurial activities, coordinating resources, interacting with customers, and creating new markets (Kuratko, 2017). Entrepreneurially-oriented managers are also an important resource for firms seeking to survive in dynamic environments (Clark, Pidduck, Lumpkin, & Covin, 2024). Building on the independent entrepreneurship literature, researchers have identified demographic and personal characteristics as key individual factors for engagement in entrepreneurship within organizations as well. Specifically, the review by Urbano, Turro, Wright, and Zahra (2022) emphasizes attitudes and emotional factors, including risk-taking, willingness to change, and self-evaluation, as central for inbound entrepreneurship. This is also mirrored in the measurement of entrepreneurship within existing organizations; risk-taking, proactiveness, and innovativeness are considered the three main components of intrapreneurship at the individual level (Rigtering & Weitzel, 2013).

Focusing on organizational characteristics, Sebora and Theerapatvong (2010) show that managerial risk-taking is associated with firm size and organizational support for entrepreneurial initiatives. In the same vein, Hornsby, Kuratko, and Zahra (2002) postulate that the availability of resources and a supportive environment for innovation foster managers’ attitudes towards risk-taking and intrapreneurship. Carland III et al. (1995) found that small business owners and managers have similar attitudes toward risk-taking.

Although risk is usually calculated and shared in intrapreneurship (Antoncic & Hisrich, 2001), managers still have to anticipate changes, acquire funding quickly, and secure support for their ideas (De Jong & Wennekers, 2008). Hence, decision speed and risk-taking are key features that enable managers to have the first-mover advantage in the workplace, identifying and capitalizing on good opportunities long before others can.

Exerting EI implies promptness and precariousness in seizing opportunities, which inherently raises moral dilemmas. The existing literature exemplifies a close relationship between EI, decision-making speed, and risk-taking, as they all share a cognitive base (Barbosa, Gerhardt, & Kickul, 2007; Bommer, Gratto, Gravander, & Tuttle, 1987; Brigham, De Castro, & Shepherd, 2007). Entrepreneurship constructs like EI have been tested with decision speed and risk-taking variables (Talaulicar, Grundei, & Werder, 2005). However, to the best of our knowledge, ours is the first instance that these variables are jointly tested in a model.

Decision-making speed has been considered the culprit of unethical behavior (Jenni & Lewis, 2019). Authors consider that in the current environment characterized by turbulence and rapid changes, leaders are required to make decisions on the spot. This, in turn, requires self-awareness and strong values as the foundation to rely on when speedy decisions are required without compromising values (Jenni & Lewis, 2019). On a similar note, Evans and Rand (2019) postulate that decision speed can be used to understand the underlying processes of human cooperation in confronting the challenges of unethical behavior and corruption.

Numerous studies have shown that people facing time limitations make riskier decisions (Chandler & Pronin, 2012). Kirchler et al. (2017) have tested the decision-making speed-risk-taking hypothesis in a gain-and-loss domain setting experiment. Their results suggest that speedy decision-making leads to less risk-taking in the gain domain and more in the loss domain.

In the following sections, the literature is analyzed, and hypotheses are developed. Our principal research focus lies in answering whether attitude toward unethical behavior influences EI. However, based on the argument below, we complement our central hypothesis and propose that decision-making speed and risk-taking influence EI in the same direction as unethical behavior.

Entrepreneurial intention and decision-making speed

Decision-making speed and other related constructs have found traction in career development literature (Gadassi, Gati, & Dayan, 2012; Lent & Brown, 2020). Decision speed has been primarily used to operationalize self-efficacy (Chuang, Lee, & Kwok, 2020). Drawing from vocational research, organizational scientists have imported decision-making speed construct, making it a significant topic of interest in strategic decision-making and entrepreneurship research (Talaulicar et al., 2005). Entrepreneurship results from the synergy between an individual and a project (Fayolle, 2004), and it depends on individuals’ decisions on how to undertake that project (Shane, Locke, & Collins, 2003). Previous empirical research shows that self-efficacy is indeed related to both entrepreneurial and intrapreneurial intentions (Douglas & Fitzsimmons, 2013). According to Adam and Fayolle (2015), even individuals with strong intentions will only act entrepreneurially if they recognize the opportunity and act at the right time, confirming the role of decision-making speed in the entrepreneurial process. Notwithstanding, the relationship between decision-making speed and entrepreneurial venture creation is poorly understood (Capelleras, Greene, Kantis, & Rabetino, 2010). Therefore, we respond to the call for further understanding of how decision-making speed operates in the emergence of EI.

Eisenhardt (2008) reports that rapid decision-making is associated with higher opportunity attainment and effective firm performance. Whereas focusing on the individual level, Forbes (2005) investigated how managers’ characteristics influence strategic entrepreneurial decision-making. The author found that managers of older cohorts with prior entrepreneurial experience make faster decisions.

In their pursuit to elucidate the interplay between decision-making speed and EI, Shepherd, Williams, and Patzelt (2015) hold that the uncertainty associated with entrepreneurship and the lack of adequate information induces entrepreneurs in faster decision-making to respond to emerging challenges or opportunities. Along the same line, Wang, Li, Zhou, and Lan (2020) confirm that opportunity identification is an essential characteristic that induces entrepreneurs to make quick decisions. Specifically, uncertainty and ambiguity promote the use of heuristics (Bryant, 2006) and intuition (Alvarez & Busenitz, 2001), which allows entrepreneurs to act quickly and capitalize on novel opportunities. Consequently, time pressure, which propels speedy decisions, negatively influences ethical behaviors (Bellé & Cantarelli, 2017).

To sum up, rapid decision-making and risk-taking are distinguished as the most salient characteristics of managers who need to make quick decisions on a tight schedule (Adams, 1974). Specifically, entrepreneurs take risks and make quicker decisions to seize emerging opportunities (Busenitz, 1999). Supporting these views, Wally and Baum (1994) also found that CEOs who use intuition have high cognitive abilities, tolerance for risk, propensity to act, and make speedy decisions. Previous theorization and research have relied on TBP as the theoretical underpinning in explaining the relationship between decision speed and outcomes (Meng & Choi, 2016). Dwelling on the self-efficacy component of TPB as an antecedent of intentions and its confluence with decision-making speed, the following hypothesis is posited:

H1: Decision-making speed is positively related to managers’ entrepreneurial intention.

Entrepreneurial intention and attitude toward risk-taking

Attitude toward risk-taking is contemplated as the single-most differentiating characteristic of entrepreneurs (Brockhaus Sr, 1980) and a significant predictor of EI (Barbosa et al., 2007). Employing student samples, previous research (Ang & Hong, 2000; Gürol & Atsan, 2006) revealed that participants with stronger attitudes toward risk-taking are more entrepreneurially inclined. Further empirical work has confirmed the positive association between risk-taking propensity and EI among intrapreneurial managers (Lajçi, Berisha, & Krasniqi, 2022).

Extant research has shown that risk-taking is also a significant determinant of intrapreneurship (Antoncic, 2003). Douglas and Fitzsimmons (2013) found that attitudes toward income, ownership, and autonomy relate to EI, whereas risk-taking relates to intrapreneurial intentions. Entrepreneurs consider risk as given; therefore, they focus on controlling the outcomes regardless of the level of risk by assuming greater personal responsibility (Sarasvathy, Simon, & Lave, 1998). Compared to entrepreneurs, intrapreneurs tend to share the risk with their firms (Razavi & Ab Aziz, 2017) and take calculated risks (Kuratko & Hodgetts, 2001).

Further empirical work confirms this proposition (Hornsby et al., 2002; Sebora & Theerapatvong, 2010), outlining the importance of individual and organizational characteristics that nurture risk-taking-entrepreneurship nexus. For instance, Li and Liu (2008) found that individuals with a higher level of intuition are more risk seekers, implying an association between decision-making speed and risk-taking. Whereas P. Zhang, Wang, and Owen (2015) attest that individuals with a short-time risk-taking preference value passion-driven over rational long-term planning to avoid the possibility of ‚missing the boat.’

To sum up, in an entrepreneurial setting, comprehensive analysis of the consequences and risk probabilities is generally too time-consuming; therefore, individuals act quickly and accept a greater risk (Busenitz, 1999). Given that risk-taking attitude is the single-most used attribute of entrepreneurial individuals and attitude is a factor predicting behavioral intention according to TPB, we rely on this theoretical underpinning to inform our following hypothesis:

H2: Attitude toward risk-taking is positively related to managers’ entrepreneurial intention.

Entrepreneurial intention and attitude toward unethical behavior

The central hypotheses in the entrepreneurial ethics scholarship are that entrepreneurs possess characteristics that are crucial to ethical behaviors (Buchholz & Rosenthal, 2005) and place a greater emphasis on ethical behavior (Bucar & Hisrich, 2001) or that entrepreneurs are action-oriented and, therefore, fail to consider ethical issues adequately (Bhide, 1996). Previous research pertaining to the second perspective (Brenkert, 2009; Z. Zhang & Arvey, 2009) depicts entrepreneurs as rule breakers and examines ethical tensions generated by entrepreneurial rule-breaking. We examine the role of unethical behavior among managers while pursuing entrepreneurial activities in the organization. Following the established practice of operationalizing the attitude toward unethical behavior of managers with dimensions of workplace ethics, we utilize Newstrom and Ruch’s (1975) scale. Attitude-based models are the best predictors of individual-level behavioral intentions and outcomes in organizational research (Woznyj, Banks, Whelpley, Batchelor, & Bosco, 2022). Attitudes are the most valuable constructs for understanding entrepreneurship and intrapreneurship (Douglas & Shepherd, 2002; Neessen, Caniëls, Vos, & de Jong, 2019). Hence, we rely on an attitude toward unethical behavior construct to operationalize individual unethical behavior (Kantor & Weisberg, 2002).

Lundmark and Westelius (2012) purport that entrepreneurship is associated with challenging the status quo, which implies misbehavior at the individual level and risk-bearing at the firm level. Drawing from entrepreneurial success stories that spurred from some misbehavior, authors conclude that defiance of norms has given life to many innovations by corporate entrepreneurs. In the face of resistance, they will either cease or exit.

According to Peixoto, Gouveia, Sousa, Faria, and Almeida (2023), entrepreneurs are more tolerant of unethical behaviors than non-entrepreneurs. Yu, Wang, Zheng, and Shi (2020) portray entrepreneurs as narcissists who tend to behave unethically in order to benefit their firms and achieve self-fulfillment. Given the limited resources and dynamic environment in which new ventures operate, entrepreneurs must adapt, act quickly, and ‚cut corners,’ which in turn encourages unethical manifestations (Baron, Zhao, & Miao, 2015). They will not hesitate to act unethically to save their business, provided they remain undiscovered (Gurău, 2020). Moreover, entrepreneurs are pragmatic and success-driven, which explains their tendency to act opportunistically, striving for personal success (Fassin, 2005). Entrepreneurs are focused on direct financial gain (Hannafey, 2003), even if it comes at the expense of others (Longenecker, McKinney, & Moore, 1988).

Previous research has investigated the interplay between ethical attitude/behavior and creativity and innovation as two of the most salient characteristics of entrepreneurs (Zhang & Arvey, 2009). Mai, Zhang, and Wang (2019) investigated the effect of entrepreneurs’ ethicality concerning product innovation of new ventures. The authors discovered that entrepreneurs with low levels of moral awareness tend to be more individually creative, whereas entrepreneurs with high levels of ethical behavior can make founding teams more creative. Comparing entrepreneurs’ and managers’ ethical attitudes and standards, Bucar and Hisrich (2001) found that entrepreneurs place a greater emphasis on ethical behavior due to higher equity stakes and risk assumed. As employees shift towards intrapreneurship or entrepreneurship, the relationships with different stakeholders encounter dilemmas that can have ethical ramifications (Dees & Starr, 1992). Considering the attitude towards unethical behavior as an attitudinal factor of our modified TBP framework and drawing on the literature review on unethical attitudes and behavior, the following hypothesis is formulated:

H3: Attitude toward unethical behavior is positively related to managers’ entrepreneurial intention.

Six predictors are used as subscales of unethical behavior: personal use, passing blame, bribery, falsification, padding expenses, and deception. Personal use refers to using company resources or time for personal purposes; Passing blame is defined as shifting responsibility for errors onto others to avoid consequences; Bribery involves giving gifts or favors in exchange for preferential treatment or accepting such benefits to gain an advantage; Falsification refers to the act of falsifying time, quality, or quantity reports and authorizing subordinates to violate company rules; Padding expenses is the act of inflating expenses to claim higher reimbursements; Deception encompasses actions like taking longer than necessary to complete a job, divulging confidential information, and failing to report violations of company policies. As a summary, the conceptual framework incorporating all study variables is presented below (Figure 1). Subsequently, a finer-grained literature analysis is provided on the role of different unethical behavior aspects on EI.

We posit that each of the six unethical behavior dimensions, as measured by the Newstrom and Ruch (1975) scale, could affect the EI of managers differently. Given the struggles to initiate new ventures due to difficulty obtaining external funding, the entrepreneurial ecosystem becomes a breeding ground for unethical behaviors (Peixoto et al., 2023). This holds especially for the Eastern European context, where individuals have been associated with a higher propensity to cheat (Teixeira & Rocha, 2010), building fortune quickly without considering ethical considerations in the absence of regulations (Fassin, 2005), even accepting bribery and corruption as a norm in doing business (Soulsby, Remišová, & Steger, 2021). Especially in the Western Balkan context, unethical practices are considered business-as-usual. A report by UNODC (2013) reiterates that in the Western Balkans, only 1.5 percent of bribes are reported to authorities. Meanwhile, in 43 percent of bribery cases, business representatives offer bribes without or before being asked or implied to do so. Narrowing the focus in Kosovo, the Western Balkan country with the highest level of informality, a study by Krasniqi and Williams (2020) reports that entrepreneurs operating informally perceive a higher likelihood of achieving desired growth.

Indeed, the link between bribery and EI has been propounded by Liñán (Heuer & Liñán, 2013), the author of the EI measure used in our study (Liñán & Chen, 2009). Moreover, individuals with EI might have a positive attitude toward misbehaving in situations, given that they can obtain some advantage (Cruz, Sousa, & Wilks, 2015). Wu (2002) found that padding expenses is a more accepted ethical behavior among general small and medium enterprises (SMEs), compared to the study-focus outstanding SMEs (top 20 Taiwanese SMEs with high ethical depth). In a study of Jordanian business managers, Al‐Shaikh (2003) unveils that padding expenses is the least acceptable practice.

Overwhelmingly, studies relating entrepreneurship with unethical behavior operationalize and refer to the latter in general terms. We endeavor to understand the interplay between EI and different dimensions of unethical behavior. Therefore, the following hypotheses are developed:

H3a: Personal use is positively related to managers’ entrepreneurial intention.

H3b: Passing blame is positively related to managers’ entrepreneurial intention.

H3c: Bribery is positively related to managers’ entrepreneurial intention.

H3d: Falsification is positively related to managers’ entrepreneurial intention.

H3e: Padding expenses is positively related to managers’ entrepreneurial intention.

H3f: Deception is positively related to managers’ entrepreneurial intention.

Figure 1. Conceptual model

METHODOLOGY

Data collection and participants

In conducting this research, we aimed to investigate managers’ entrepreneurialism in a context where it is important for both the country’s development and individuals’ career paths. Kosovo, an economically and culturally transitioning country with one of the fastest-growing economies in the Western Balkans (Mara, 2020) and one of the youngest populations in Europe (World Bank, 2019), was a population suited to test our hypotheses. Within this environment, managers emerge as central figures and are often considered the ‚usual suspects’ in exerting innovation and intrapreneurship (Kör, Wakkee, & van der Sijde, 2021). Following these arguments, we addressed managers as our survey’s target informants.

The present research is part of a larger study of individual differences as predictors of organizational practices of managers. Primary data is collected through self-report questionnaires, and the respondents were managers of Kosovan companies varying in size and industry. Using a database or a membership list provided by Kosovo’s Chamber of Commerce, we targeted 256 companies randomly, and 140 responded positively, permitting us to contact and survey managers. Since our study focused on individual instead of firm level, our inquiry implied that we wanted to survey individuals in managerial positions. Because no sampling frame for managers exists in Kosovo, non-probability sampling is used (Cumming, 1990).

To avoid biases and the dominance of a handful number of companies, we targeted surveying up to a maximum of ten participants per company. Upon acceptance by the HR managers or CEOs of companies participating in the study, questionnaires were dropped off to managers personally. Nevertheless, the maximum threshold of ten respondents per company was not always reached. This happened because some of the participating companies had less than ten employees in managerial roles. From 140 companies responding positively to participate in the study, we were able to distribute 400 questionnaires.

The survey consisted of demographic questions and self-report measures adopted by previous research. A back-translation procedure was followed to ensure the appropriate translation of the items into Albanian (Brislin, 1970). Out of 400 distributed questionnaires, 261 responses were received (65.3% return rate). Forty-seven questionnaires were discarded due to missing data, resulting in 214 valid questionnaires. This means that the number of respondents from 140 companies participating in the study ranged from 1 to 10. On average, this is translated as less than two respondents per company, underscoring our commitment to ensuring a diverse and representative sample in our study.

Table 1 presents the demographic characteristics of the respondents. The sample comprised 214 respondents (76.2% male; 23.8% female). Almost the majority of respondents (48.1%) are between 18 and 34 years old, followed by age 35-44 (29.0%), age 45-54 (18.2%), and age 55+ (4.7%). Concerning education, managers in possession of a university degree (Bachelor’s, Master’s, PhD) make up 83.2% of the sample, followed by those with an associate degree (9.3%) and high school diploma (7.5%).

Table 1. Demographic characteristics

	N=214	%
Gender
Female	51	23.8
Male	163	76.2
Age
18-24 years old	23	10.7
25-34 years old	80	37.4
35-44 years old	62	29.0
45-54 years old	39	18.2
55+ years old	10	4.7
Education
High School	16	7.5
Associate degree	20	9.3
Undergraduate (BA; BSc)	102	47.7
Graduate (MA; MSc)	66	30.8
Doctorate (PhD)	10	4.7
Organizational tenure
Less than 1 year	21	9.8
1-3 years	44	20.6
4-6 years	39	18.2
7-9 years	29	13.6
10+ years	81	37.9
Managerial tenure
Less than 1 year	12	5.6
1-3 years	44	20.6
4-6 years	49	22.9
7-9 years	34	15.9
10+ years	75	35.0
Level of management
Low-level management	23	10.7
Middle-level management	63	29.4
Top-level management	128	59.8

Measurement of variables

Entrepreneurial intention. The EI of managers was measured using six items from the Entrepreneurial Intention Questionnaire (EIQ) developed by Liñán and Chen (2009). A sample item is “My professional goal is to become an entrepreneur” (1=strongly disagree to 5=strongly agree). The coefficient alpha (α) of the scale in this study was 0.88. The complete item list of EI is represented in the Appendix (Table 1a).

Decision-making speed. The decision-making speed of managers was assessed using one item from Casey’s Decision-making Speed Scale (CDMSS; Casey, 2006). The item was “I consider myself a quick decision maker.” The respondents were asked to report their level of agreement with the statement using a five-point Likert scale (1=strongly disagree to 5=strongly agree).

Attitude toward risk-taking. Five items from Dahlbäck’s (1990) scale measured managers’ attitudes toward risk-taking. This is among the only scales measuring attitude toward risk-taking as an individual difference. However, due to its low reliability (α=0.53), the scale was considered a potentially faulty index. This led to the use of only one item, which is reasonably close to the general risk-taking question developed by Dohmen et al. (2011). The item was “I often dare to do risky things which other people are reluctant to do .”Each respondent was asked to self-report the pertinency of this statement (false=1 point; true=2 points) (Palmer et al., 2013).

Attitude toward unethical behavior. Newstrom and Ruch’s (1975) Ethical Behavior Scale (NREBS) was used to assess the manager’s attitude toward unethical behavior. The instrument consists of 17 common unethical behaviors that managers engage in. The measure comprises of the following six dimensions: personal use (e.g., “Using company services for personal use”), passing blame (e.g., “Passing blame for errors to an innocent co-worker”), bribery (e.g., “Giving gifts/favors in exchange for preferential treatment”), falsification (e.g., “Falsifying time/quality/quantity reports”), padding expenses (e.g., “Padding an expense account more than 10%”), and deception (e.g., “Divulging confidential information”). Respondents indicated their evaluation of their ethical behavior in terms of a five-point Likert scale with descriptive anchors (1=very unethical; 5=very ethical). An average score was generated from the 17 items to depict the likelihood of engaging in unethical behavior. The higher the score, the stronger the attitude toward unethical behavior is reported. As for the goal of this study, we employed both the composite NREBS score and its composing dimensions. The Cronbach’s alpha (α) was 0.87 in the current study. Whereas for the six dimensions, alpha coefficients were 0.69 (personal use), 0.51 (passing blame), 0.88 (bribery), 0.63 (falsification), 0.73 (padding expenses), and 0.74 (deception). The complete item list of NREBS is represented in the Appendix (Table 1a).

Control variables. Drawing from the previous literature (Balog, Baker, & Walker, 2014; De Jong, Parker, Wennekers, & Wu, 2011; Hornsby, Kuratko, Shepherd, & Bott, 2009; Lajçi et al., 2022), we control for several individual and organizational characteristics that might explain the EI of managers. Namely, gender (0=female, 1=male), age (1=age 18-24, 2=age 25-34, 3=age 35-44, 4= age 45-54, 5=age 55+), education (0=non-university education, 1=university education), religiousness (1=not at all important, 5=very important), organizational and managerial tenure (1=0-3 years, 2=4-9 years, 3=10+ years), level of management (0=low/middle management, 2=top management), as well as company size (number of employees) and age (in years) were controlled for in this study.

Data analysis

As mentioned above, a non-probability sampling technique is used since no sampling frame for managers exists in Kosovo (Cumming, 1990). As is usual with non-random sampling, such methods can be prone to selection bias (Forster, 2001). Nevertheless, several ex-ante and ex-post remedies were performed to deal with this drawback and ensure data quality.

Our sample comes from 140 companies participating in the study, which, on average, means less than two respondents per company. The relatively large number of companies participating in the study indicates a diverse and representative sample in our study. Additionally, the response rate in our study (65.3%) is also a positive aspect. According to Galloway (2005), a well-constructed study using non-probability methods is comparably more valuable than a probability survey to which only 10% of the sample responded.

Further, to address the issue of common method variance, we assured respondents verbally and with a cover letter that the survey was anonymous and that the measures were independent (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). Moreover, the questionnaire sections were organized in such a way as to create psychological and sequential separation. After data collection, we performed Herman’s single factor test, which showed that the percentage of variance was 20.43%, lower than the 50% threshold, implying that there is no common method bias (Fuller, Simmering, Atinc, Atinc, & Babin, 2016). In addition, we tested for multicollinearity using the variable inflated factor (VIF) in SPSS. The ratios range between 1.05 and 2.68, thus meeting the <4 cut-offs (Hair Jr, Page, & Brunsveld, 2019), which suggests that multicollinearity was not a problem in our estimation. Additional tests showed that our estimated models did not suffer from heteroscedasticity either.

Proceeding with further analyses, initially means, standard deviations, and correlations were calculated. Subsequently, hierarchical linear regression analysis was conducted to test our hypotheses. SPSS v29 was used for data analysis. To explore the association between control variables and EI, gender, age, education, religiousness, organizational tenure, managerial tenure, level of management, company size, and company age are entered in the first step. In the second and third steps, managers’ decision-making speed and risk-taking were entered, respectively. The fourth model included the total NREBS scale. Finally, in the fifth model, we exclude NREBS and analyze the six subscales of Enstrom and Ruch’s (1975) instrument (personal use, passing blame, bribery, falsification, padding expenses, deception) to better understand their impact on EI.

In addition to control variables and unethical behavior measures, we include decision-making speed and risk-taking as two antecedents of EI to increase the model’s explanatory power.

RESULTS

Table 2 includes the measured variables’ means and standard deviations. Whereas Table 3 reports Pearson’s correlation scores and reliability coefficients.

Table 2. Means and standard deviations

Variables	Mean	Standard deviation
Religiousness	3.30	1.18
Company size (number of employees)	172.88	54.53
Company age (in years)	13.76	10.24
Decision-making speed	2.34	1.13
Risk-taking	1.68	0.47
NREBS	1.56	0.50
Personal use	1.60	0.62
Passing blame	1.48	0.57
Bribery	1.74	1.09
Falsification	1.45	0.62
Padding expenses	1.27	0.53
Deception	1.77	0.80
Entrepreneurial intention	3.79	0.88

The correlation analysis reveals that EI is positively correlated with decision-making speed (r=0.16, p<0.05) and risk-taking (r=0.14, p<0.05). Meanwhile, the correlation between EI and NREBS shows no statistical significance. Of the correlations between the dependent variable and unethical behavior dimensions, EI positively correlates with personal use, bribery, and padding expenses. In contrast, it negatively correlates with passing blame, falsification, and deception. However, the correlation coefficients show no statistical significance.

Table 3. Pearson’s correlations

Variables	1	2	3	4	5	6	7	8	9	10
1. Decision-making speed	–
2. Risk-taking	-0.03	–
3. NREBS	0.26**	-0.16*	(0.87)
4. Personal use	0.14*	-0.04	0.74**	(0.69)
5. Passing blame	0.16*	-0.09	0.72**	0.46**	(0.51)
6. Bribery	0.33**	-0.12	0.69**	0.33**	0.33**	(0.88)
7. Falsification	0.20**	-0.15*	0.79**	0.48**	0.61**	0.37**	(0.63)
8. Padding expenses	0.10	-0.18**	0.64**	0.42**	0.48**	0.27**	0.59**	(0.73)
9. Deception	0.18**	-0.17*	0.77**	0.41**	0.38**	0.55**	0.50**	0.34**	(0.74)
10. Entrepreneurial intention	0.16*	0.14*	0.02	0.06	-0.01	0.08	-0.07	0.03	-0.01	(0.88)

Note: Internal consistency is provided along the diagonal; *p<0.05; **p<0.01.

Table 4 presents the hierarchical regression analysis results for managers’ EI. As is usually the case with this type of analysis, control variables are included first. In model 1, age (β=-0.217, p<0.05), level of management (β=0.191, p<0.01), and company size (β=-0.136, p<0.05) significantly predicted EI, and it explains approximately 11% of the variability in the response variable (R2=0.108, F (2.753), p<0.01). In the following two models, two important antecedents of EI are added. In the second model, decision-making speed (β=0.150, p<0.05) was entered, which is a statistically significant predictor of EI. The model explains 12.8% of the variance, which represents a modest improvement relative to model 1 (R2=0.12.8, F (2.987), p<0.01). Additionally, model 3 included risk-taking. Managers’ attitude towards risk-taking (β=0.331, p<0.05) yields a significant influence on EI, and the model explains 15.2% of the variance (R2=0.152, F (3.302), p<0.01). In model 4, the composite NREBS scale is added. However, the total NREBS shows no statistical significance, and the predicting power of the model shows no meaningful increase (R2=0.153, F (3.031), p<0.01). Consequently, we excluded the composite NREBS score from the final model to understand the influence of its subscales. In the fifth model, in addition to gender, age, education, religiousness, organizational tenure, managerial tenure, management level, company size, company age, decision-making speed, and risk-taking, we added the six subscales of NREBS. The predictive power of the model is significantly higher (23%) than in model 4 (R2=0.230, F (3.449), p<0.01). In model 5, out of six unethical behavior dimensions, only bribery significantly influences EI (β=0.253, p<0.01).

Of the demographic variables, age shows a negative (Models 1-5), whereas level of management (Models 1-4) has a positive significant impact on the outcome variable. Concerning organizational-level control variables, both the company size (Models 1 and 2) and age (Models 3 and 4) show a negative significant influence on managers’ EI. However, there is no significant effect of gender, religiousness, education, company, and managerial tenure on EI.

Finally, in the last regression analysis, we estimated a model including only significant variables (at p-value <5%) across previous models. Level of management (β=0.153, p<0.05), decision-making speed (β=0.130, p<0.05), and bribery (β=0.224, p<0.01) still significantly predicted EI. Risk-taking also positively influences EI, and the statistical significance was at the limit of the 5% level (β=0.131, p=0.051). In total, model 6 explained approximately 18% of the variability in the response variable (R2=0.178, F (6.387), p<0.01).

Table 4. Results of hierarchical regression analysis

Variables	Entrepreneurial intention
	Model 1			Model 2			Model 3			Model 4			Model 5			Model 6
	B	SE	Beta	B	SE	Beta	B	SE	Beta	B	SE	Beta	B	SE	Beta	B	SE	Beta
Control variables
Gender	0.083	0.146	0.040	0.178	0.151	0.086	0.171	0.150	0.083	0.172	0.150	0.083	0.246	0.148	0.119*
Age	-0.185	0.078	-0.217**	-0.177	0.077	-0.208**	-0.154	0.077	-0.181**	-0.159	0.078	-0.186**	-0.156	0.076	-0.183**	-0.104	0.062	-0.122*
Education	0.073	0.162	0.031	0.103	0.161	0.044	0.072	0.160	0.030	0.060	0.163	0.025	0.203	0.162	0.086
Religiousness	0.020	0.051	0.026	0.012	0.051	0.016	0.009	0.050	0.012	0.009	0.050	0.012	0.021	0.050	0.028
Organizational tenure	-0.013	0.106	-0.012	-0.016	0.105	-0.015	0.007	0.104	0.007	0.015	0.106	0.014	-0.051	0.104	-0.048
Managerial tenure	0.165	0.121	0.145	0.159	0.120	0.140	0.164	0.119	0.145	0.167	0.119	0.147	0.145	0.116	0.128
Level of management	0.345	0.126	0.191***	0.307	0.126	0.171**	0.285	0.125	0.158**	0.294	0.127	0.163**	0.205	0.125	0.114	0.276	0.120	0.153**
Company size	0.000	0.000	-0.136**	0.000	0.000	-0.156**	0.000	0.000	-0.122*	0.000	0.000	-0.117*	0.000	0.000	-0.127*	0.000	0.000	-0.118*
Company age	-0.012	0.007	-0.136*	-0.011	0.007	-0.131*	-0.014	0.007	-0.165**	-0.015	0.007	-0.168**	-0.010	0.007	-0.114	-0.009	0.006	-0.109
Independent variables
Decision-making speed				0.124	0.057	0.150**	0.111	0.057	0.135*	0.110	0.057	0.134*	0.144	0.056	0.175**	0.106	0.053	0.130**
Risk-taking							0.331	0.138	0.165**	0.326	0.139	0.162**	0.282	0.137	0.141**	0.262	0.134	0.131*
NREBS										0.054	0.124	0.031
Personal use													0.203	0.112	0.142*
Passing blame													-0.159	0.133	-0.102
Bribery													0.055	0.015	0.253***	0.049	0.014	0.224***
Falsification													-0.209	0.139	-0.145
Padding expenses													0.114	0.137	0.069
Deception													0.020	0.088	0.018
R2	0.108			0.128			0.152			0.153			0.230			0.178
Adjusted R2	0.069			0.085			0.106			0.103			0.164			0.150
ΔR2	0.108			0.020			0.024			0.001			0.077			-0.052
ΔF	2.753***			4.650**			5.758**			0.193			3.449***			6.387***
df. (regression, residual)	(9, 204)			(10, 203)			(11, 202)			(12, 201)			(17, 196)			(7, 206)
F	2.753***			2.987***			3.302***			3.031***			3.449***			6.387***

Note: *** p<0.01, ** p<0.05, * p<0.10; SE-Standard error.

Given the nature of cross-sectional data, regression analyses using these data can suffer from heteroscedasticity or the situation where error terms are not equally spread across independent variable values, violating the basic assumption for linear regression. Therefore, we tested for heteroscedasticity in our estimated regression models using the Heteroskedasticity V3 SPSS macro developed by Daryanto (2020). Following Daryanto (2020), we report the results of two statistical tests commonly used to examine the homoskedasticity assumption, namely the Breusch-Pagan and Koenker tests. Full results for all estimated models are presented in Table 5. The results show that for all models, the significance values were less than 0.05, indicating that the null hypotheses were rejected and heteroscedasticity was absent.

Table 5. Heteroscedasticity tests

Models	Model 1		Model 2		Model 3		Model 4		Model 5		Model 6
Tests	LM	Sig.	LM	Sig.	LM	Sig.	LM	Sig.	LM	Sig.	LM	Sig.
Breusch-Pagan	8.263	0.508	10.856	0.369	11.975	0.366	16.176	0.183	26.984	0.058	7.748	0.355
Koenker	6.309	0.709	8.448	0.585	9.933	0.536	13.764	0.316	20.217	0.263	6.548	0.477

Note: LM- Lagrange multiplier; Sig-Significance.

Robustness test

As shown above, the regression analysis revealed a significant positive impact of bribery in managers’ EI. As a further check, we analyzed median differences in bribery scores within our sample. We estimated the median differences by conducting the non-parametric Wilcoxon test to examine if values of bribery and other independent variables score differently among managers. As is usual when conducting similar analysis, we grouped our respondents into two groups. Given that the average EI score ranges from 1 to 5, we distinguished managers with “low” (≤2.5) and “high” (>2.5) EI levels. By and large, results were qualitatively similar to those reported in Table 3 and confirmed the differences revealed by the regression analysis. In particular, the Wilcoxon rank sum tests results show that the bribery’s median scores among “high” and “low” EI managers differ and this difference between the two groups is statistically significant: W=1533, Z=-2.17, p=0.030. Full results can be found in Table 2a in the Appendix.

DISCUSSION

This paper aimed to shed light on the role of attitude toward unethical behavior on managers’ EI. Additionally, we purported to reveal how the attitudes toward decision-making speed and risk-taking are associated with EI in the context of unethical behavior. The empirical results indicate that attitude toward unethical behaviors does not necessarily translate into higher EI. Notwithstanding, bribery, a particular type of unethical behavior, decision-making speed, and risk-taking are positively associated with EI. However, such effects are limited as they derive from a non-random sample in a specific context (Kosovo), hence suggesting a limited possibility to generalize sic et simpliciter the results. Moreover, although the empirical exercise yields a significant positive relationship between dependent and interdependent variables, the cross-sectional nature of our data does not allow us to infer any conclusion about the causality between them. Our findings are interpreted and contextualized in more detail below.

Hypothesis 1 argues a positive relationship between decision-making and EI. Hypothesis 1 is confirmed. A possible explanation for this positive relationship might be that rapid decision-makers often rely on limited information and must act quickly to seize emerging opportunities (Shepherd et al., 2015). Managers are expected to respond rapidly to organizational and environmental changes; therefore, quick decision-making should be a tool as they exploit opportunities and take advantage of the competitive environment (Guven, 2020). Under time pressure, they use information better and develop more alternatives (Eisenhardt, 1989). Furthermore, fast decision-makers gather real-time information and seek the advice of experienced counselors (Eisenhardt, 2008), which in turn grows the awareness of new entrepreneurial opportunities. This aligns with Krasniqi, Berisha, and Pula (2019), who prove that spontaneous managers making fast decisions will be more entrepreneurially inclined.

Hypothesis 2 posited that risk-taking is positively related to EI. The analysis yields a significant positive relationship, thereby supporting the hypothesis. This finding is intuitive and self-evident, as extant research and practice show that entrepreneurship is inherently grounded in risk-taking (Stewart Jr & Roth, 2001; Tipu, 2017). Entrepreneurial initiatives are based on the risk of loss, and managers cannot predict every scenario affected by organizational uncertainties (Antoncic, 2003). Therefore, managers with stronger risk-taking attitudes are more willing to make large and risky resource commitments to novel business endeavors (Lumpkin & Dess, 1996).

Focusing on the context of the present study, Kosovo firms operate in a highly uncertain business environment (Conahan, Deichmann, Krasniqi, & Peci, 2021). Moreover, Kosovan managers are opportunity-focused and tend to use every opportunity to increase business performance (Sadiku-Dushi, Dana, & Ramadani, 2019). Based on these views, we contemplate that managers with stronger attitudes toward risk-taking are more likely to have EI and subsequently behave entrepreneurially within their organizations to face uncertainties through opportunity exploitation.

Hypothesis 3 tested the effect of unethical behavior on managers’ EI. This hypothesis is not supported. The effect of the composite score of unethical behavior on EI is not significant. The insignificant relationship between NREBS and EI might be explained by the former being more workplace-related. This aligns with findings from several contributions on a special issue in the Journal of Business Ethics (Soulsby et al., 2021), demonstrating that only specific dimensions of unethical behavior are important in informing EI.

Considering that the overall unethical behavior does not relate to subsequent EI, we analyzed each dimension. Hypotheses 3a-3f proposed the influence of unethical behavior subscales on EI. Of six hypotheses, only hypothesis 3c is supported, implying that bribery significantly predicts EI. Namely, the findings indicate that in our sample, managers’ EI is influenced by their attitude toward bribing, whereas the relationship with other ethical dimensions is insignificant. This finding is consistent with the results from the study by Chadee, Roxas, and Kouznetsov (2021) with firms in Central and Eastern Europe, which suggest that bribery enables firm managers to exploit the environment of corruption to innovate.

It is conceivable that the context influences whether behaviors are perceived as ethical (Schneider & Enste, 2013). In the Western Balkan economies, building social capital through exchanging favors for preferential treatment is common (Džunić & Golubović, 2016). In this context, as is the case of Kosovo, social networks can prove helpful in identifying where, when, and to whom bribes need to be given to get things done more efficiently (Bozovic, 2017). The primary reason for bribery in Kosovo is to speed up the procedures (Zabyelina & Arsovska, 2013). This suggests that taking part in bribes is a means to gain an advantage and get things done quickly. This is in line with our hypothesized relationship between decision-making speed and EI.

As a fraction, the mechanism of bribery has been evidenced to work somewhat differently than corruption or unethical behavior as the overarching instances (Lee, Oh, & Eden, 2010; Ufere, Gaskin, Perelli, Somers, & Boland Jr, 2020), especially in the Kosovo context (Uberti, 2020). Previous reports (UNODC, 2013) on business practices of Kosovan entrepreneurs/owners show a slight prevalence of bribery, whereas other aspects of illicit or unethical behaviors are rare. This was reflected in our sample as well, as we note that the score value of the bribery scale in our study is (x̄=1.74) is higher compared to other studies, such as Akaah (1996) (x̄=1.42) and Liu and Ren (2017) (x̄=1.66). Contrary to other dimensions, we contemplate that the rationale behind bribery’s positive and significant influence on EI is that the latter is more workplace-related, whereas bribery is associated with stakeholder interactions.

Additionally, our study operationalized the bribery dimension as “giving and accepting gifts/favors in exchange for preferential treatment.” Based on this, the nature of these actions may not have been inherently perceived as negative by the respondents. In developing contexts like Kosovo, gifts and favors are commonly regarded as normal means to secure more favorable treatment in the workplace (Džunić & Golubović, 2016).

Bribery has barely been studied in the intrapreneurial context. Walter and Block (2016) purport that firms offer fewer intrapreneurship-like jobs in corruption-plagued countries. This, in turn, could mean that they will shift from intrapreneurship to new venture creation, given their growing network. We contemplate that the proclivity of managers to give/accept bribes could mean exerting it with external stakeholders to increase their social capital. According to a study of Kosovan business owners, roughly 45 percent consider using relationships and personal contacts acceptable for speeding up business-related procedures (UNODC, 2013). This demonstrates a widespread pattern of behavior that embodies bribery as a means to facilitate operations and achieve personal gain (Aupperle & Camarata, 2007; G. De Jong, Tu, & van Ees, 2012). Individuals who pay bribes do so to speed up bureaucratic processes. Personal ties compensate for institutional imperfections in transition economies (Tu, 2012). This is especially true for poorer developing countries, where high levels of corruption permeate individuals to engage in bribery to make it easier for them to materialize their EI (Nakara, Laouiti, Chavez, & Gharbi, 2020). This explains why managers who make quick decisions are also prone to bribes and have a higher intention to act entrepreneurially. Ergo, making quick decisions (H1) and paying bribes (H3c) are both associated with high EI in our study.

Kosovo has transformed from a communist to a transition economy, characterized by firms with informal practices, a deteriorating work environment, a lack of strategic orientation, and a lack of employee involvement (Prouska, Psychogios, & Rexhepi, 2016). Companies in Eastern European countries such as Kosovo are inherently bureaucratic and centralized (Svetlik et al., 2010). For firm managers in Central Eastern European countries like Kosovo, bribery can easily bypass the bureaucracy when applying for permits, securing government contracts, or ‚getting things done’ (Chadee et al., 2021).

Like other Western Balkan countries, Kosovo scores high on power distance. The evidence from this context suggests that high power distance enacts EI among individuals (Rajković, Nikolić, Ćoćkalo, Stojanović, & Kovačić, 2020). Also, high power distance discourages ethical behavior as managers who exert power have less sense of accountability toward employees and stakeholders (Nasierowski & Mikula, 1998).

Nevertheless, one has to be cautious when interpreting the positive variances in our dependent variable. The present study is based on self-report data, which might explain individuals’ high self-assessment concerning their EI. We purport that the high self-regard of EI could occur due to the self-serving bias inherent in cross-sectional survey studies (Friedrich, 1996). Additionally, the explanation for the higher evaluations of EI could be attributed to the unique characteristics of the context and our sample. First, Kosovo has one of Europe’s youngest populations, averaging 30.2 years (World Bank, 2019), which was also reflected in our sample (almost half of the respondents were between 18-34 years old). Hence, this youthful presence might explain the higher levels of entrepreneurial inclination, as demonstrated in previous research (Hisrich, 1990). Second, our sample indicates a high level of education (over 80% possess a university degree). This educational background could influence their self-evaluation of EI. Some managers may be employed in positions below their qualifications, potentially leading to increased self-perception (Krasniqi & Mustafa, 2016).

Of the demographic variables, age and management level were significantly associated with EI. In our study, age is negatively associated with EI. This aligns with previous research indicating that as individuals age, their openness to new experiences decreases; therefore, they regard time as a constraint and prefer to maintain the status quo (Adachi & Hisada, 2017; J. P. De Jong et al., 2011). At the same time, managers in higher hierarchical levels were found to be more entrepreneurially inclined. At upper hierarchical levels, managers have more opportunities to recognize and implement entrepreneurial ideas (Hornsby et al., 2009).

Regarding organizational-level characteristics, company age, and size are negatively associated with EI. Based on the findings, managers in more mature and larger companies perceive fewer opportunities to innovate and take risks, possibly due to a preference for maintaining career stability. This is supported by Global Entrepreneurship Monitor data (GEM, 2015), showing that Kosovan employees, especially in larger companies, show the lowest level of employee entrepreneurship. In other words, as large established firms need to be more specialized and bureaucratic (Kacperczyk, 2012), this, in turn, hinders employees’ entrepreneurialism.

CONCLUSION

Using a sample of managers situated in an emerging economy context, the set goals for this study were achieved, and the formulated hypotheses were confirmed (except for hypothesis 3). Based on the findings, our paper renders several important theoretical implications. Nevertheless, the present study focuses on a single country (Kosovo) and is based on cross-sectional data stemming from non-random sampling, which suggests caution in drawing conclusions. In the following paragraphs, the implications and limitations of this study are outlined.

We contribute to entrepreneurship and ethics research by empirically examining the relationship between unethical behavior and the EI of managers. In this light, our findings support TPB as a valuable framework to study unethical behavior in an entrepreneurial context. We extend the body of research and theorization in ethics and entrepreneurship by demonstrating the interrelatedness of ethical behavior and intrapreneurship as two inter-organizational individual manifestations. This paper presents a peculiar attempt to reconcile unethical behavior and EI in research using a manager sample. Moreover, we confirm the risk-taking hypothesis and, more importantly, declaim the positive relationship between decision-making speed, unethical behavior, and EI.

The overriding contribution of this study is to extend the theoretical and empirical underpinnings concerning ethics and entrepreneurship, upholding that they are pervasive across contexts. This implies that research on unethical behavior and EI as a subset of ethics and entrepreneurship research is as context-specific as the separate study of these constructs.

On a methodological plan, we attest that the unethical behavior measure (NREBS) is not unidimensional, indicating a lack of nomological validity. Instead, people differ across dimensions, supporting the issue-related moral intensity hypothesis (Morris & McDonald, 1995).

In addition to the theoretical implications, this paper provides relevant managerial implications. Our findings indicate the multifaceted nature of unethical behavior’s influence on EI. The EI of managers is likely to be influenced by their bribery behavior. Managers who are more positive towards giving and receiving bribes exert more EI. This knowledge should be used for corporate entrepreneurship and training purposes. Entrepreneurship within organizations is encouraged; however, it should be stimulated by the right reasons, not bribery. Senior managers should set the stage for intrapreneurial employees to thrive but also set the tone for their ethical conduct. It is recommendable for organizational training programs in general and corporate entrepreneurship programs to include ethical components (Kuratko, 2007). Organizations should strive to achieve both business ethics and corporate entrepreneurship simultaneously (Chau & Siu, 2000).

Our paper purports an important policy implication for entrepreneurship education. As we evidence in our study in a transition and emerging economy, education does not influence the ethical behavior of individuals, which has been evidenced in other studies focused on non-western contexts (Béchard & Grégoire, 2005; Berisha, Oliveira, & Humolli, 2023). We contemplate that entrepreneurship education should not be reduced to business venturing but should integrate ethical reasoning and behavior (Heinrichs, Minnameier, & Beck, 2014). Given the formal education system’s shortcomings in providing ethical prescriptions for managers and entrepreneurs (G. De Jong et al., 2012), organizations should focus on training programs to enact entrepreneurialism and ethical behavior. Non-formal education in the form of training helps reduce bribery incidence among entrepreneurs in an emerging economy context (Tu, 2012).

Despite our original and interesting findings, several avenues for further research remain. To gain a more comprehensive understanding of the intricate interplay between ethics and entrepreneurship, future research should explore additional factors that may influence unethical behaviors in entrepreneurial contexts. A promising research avenue would involve examining the impact of country-level, industry-level, and firm-level factors that leverage the moral compass of the individuals. This multi-level approach could provide a more nuanced understanding of the ethical dynamics of entrepreneurship, fostering a more holistic understanding.

Moreover, future studies might also consider adopting alternative analytical approaches to explore further the relationship between various factors influencing managers’ EI. For instance, there is a need for further exploration of mediating and moderating factors that influence the relationship between unethical behavior and EI. Additionally, it would be worthwhile to consider the variables used in this study, namely decision-making speed and risk-taking, and examine their potential moderating effects on the nexus between unethical behavior and EI. Scrutinizing these factors could provide valuable insights, contributing to a more nuanced understanding of the intricacies involved.

Additionally, future focuses on specific industries or sectors might provide a more nuanced understanding of the role of (un)ethical behavior and EI. By honing in on particular domains, future research can uncover industry-specific challenges and opportunities for promoting ethical entrepreneurship, yielding valuable insights for practitioners and policymakers alike. The insights from such focused studies can potentially inform strategies for cultivating ethical business practices and leadership qualities in specific professional contexts.

Finally, measuring ethical behavior raises the social desirability bias issue as there is a conscious tendency to over-report desirable behaviors (Randall & Fernandes, 1991). Thus, future research should control for social desirability bias by employing indirect questioning and observer rating to measure ethical behavior (Zuber & Kaptein, 2014).

Although the study provides some interesting and original insights, some limitations should be acknowledged. First, the present research is grounded on cross-sectional data. Thus, future research might consider employing longitudinal data through randomized sampling techniques to explore causal relationships between variables and increase the generalization of the findings.

Second, the sample consists of Kosovan respondents, which may pose a bias in the work experiences of managers driven by an Eastern geographic context. Therefore, future studies should include cross-cultural samples and compare characteristics of different cultures to explore generalizability.

Third, the empirical data is collected using self-report measures, which are subject to biases as respondents make judgments about themselves (Chan, 2010). Specifically, future research should control for self-serving bias by adopting neutral measures concerning their self/other focus. On a similar note, it is crucial to recognize a potential limitation of our single-item measure of decision-making speed. However, given the scale of the research project in which the current study is situated and the limited resources, our goal was to employ an efficient and economically usable scale. Nonetheless, future research might consider using an experiment to capture decision-making speed (i.e., ask the participants to make a decision as a part of the survey and then either monitor how long it took them to decide or ask them to report the length themselves).Fourth, although our study controls for several individual and organizational attributes, future research should consider other control variables that might play a role. In this light, the information about managers’ previous start-up experience might provide important insights by comparing the attitudes towards ethical concerns and entrepreneurship in two contexts, namely in a new venture versus in a matured company.

Finally, the unethical behavior of managers was measured using Newstrom and Ruch’s instrument, which was developed in 1975. This might posit an inherent limitation considering the past context in which the measure was conceptualized. Therefore, future studies on ethical behavior and intrapreneurship should include context-specific measures that include ethical dilemmas in today’s workplace and management.

Appendix

Table 1a. Measures

Attitude toward unethical behavior
Personal use	1 = Very unethical 5 = Very ethical
Using company services for personal use
Doing personal business on company time
Pilfering company materials and supplies
Taking extra personal time (lunch hour, breaks, early departure)
Passing blame
Concealing one’s error
Passing blame for errors to an innocent co-worker
Claiming credit for someone else’s work
Bribery
Giving gifts/favors in exchange for preferential treatment
Accepting gifts/favor in exchange for preferential treatment
Falsification
Falsifying time/quality/quantity reports
Calling in sick to take a day off
Authorizing a subordinate to violate company rules
Padding expenses
Padding an expense account up to 10%
Padding an expense account more than 10%
Deception
Taking longer than necessary to do a job
Divulging confidential information
Not reporting others’ violations of company policies and rules
Entrepreneurial intention
I am ready to do anything to be an entrepreneur	1 = Strongly disagree 5 = Strongly agree
My professional goal is to become an entrepreneur
I will make every effort to start and run my own firm
I am determined to create a firm in the future
I have very seriously thought of starting a firm
I have the firm intention to start a firm some day

Table 2a. Wilcoxon rank sum tests comparing medians of independent variables across two groups of managers (low versus high entrepreneurial intention)

	Low entrepreneurial intention		High entrepreneurial intention		Test statistics
	Mean rank	Sum of ranks	Mean rank	Sum of ranks	Wilcoxon	Z	p
Decision-making speed	92.42	1,756.00	108.97	21,249.00	1756.00	-1.16	0.245
Risk-taking	96.95	1,842.00	108.53	21,163.00	1842.00	-0.96	0.336
NREBS	84.03	1,596.50	109.79	21,408.50	1596.50	-1.73	0.083
Personal use	96.61	1,835.50	108.56	21,169.50	1835.50	-0.82	0.412
Passing blame	91.55	1,739.50	109.05	21,265.50	1739.50	-1.22	0.222
Bribery	80.68	1,533.00	110.11	21,472.00	1533.00	-2.17	0.030
Falsification	87.08	1,654.50	109.49	21,350.50	1654.50	-1.59	0.113
Padding expenses	76.50	1,453.50	110.52	21,551.50	1453.50	-2.86	0.004
Deception	101.68	1,932.00	108.07	21,073.00	1932.00	-0.44	0.663

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Biographical notes

Rrezon Lajçi is a PhD candidate at Technische Universität Ilmenau and serves as a teaching and research assistant in the Management/Organization research group. He is a Master’s graduate from the University of Padova, Italy, specializing in Management. His main research interests revolve around intrapreneurship, proactivity at work, and work attitudes. His research appeared in journals such as Management Research Review, International Review of Entrepreneurship, and International Journal of Innovation Management.

Gentrit Berisha, PhD, is an assistant professor of Management at the Faculty of Economics, University of Prishtina. His teaching and research are focused on organizational behavior, decision-making, intrapreneurship, and business ethics. His research is featured in the Academy of Management Proceedings and the European Academy of Management. He has published several research papers in reputable journals of publishers such as Emerald, Wiley, Springer, and Elsevier.

Besnik Krasniqi, a Fulbright Scholar, holds MA and Ph.D. in Economics from Staffordshire University (UK). He teaches Small Business and Entrepreneurship at the University of Prishtina. His career spans teaching and research in entrepreneurship at Maastricht School of Management (NL), Indiana University (US), University of Michigan (US), Université Nice Sophia Antipolis (France). His research appeared in journals such as Entrepreneurship Theory and Practice, Small Bus Econ, Int Entrep Manag J, IJEBR, Econ System.

Authorship contribution statement

Rrezon Lajçi: Data Analysis and Results, Discussion and Implications. Gentrit Berisha: Literature Review, Discussion and Implications. Besnik Krasniqi: Conceptualization, Discussion and Implications.

Conflicts of interest

The authors declare no conflict of interest.

Citation (APA Style)

Lajçi, R., Berisha, G., & Krasniqi, B. (2024). Making of intrapreneurial managers: Investigating unethical behavior, risk-taking, and decision-making speed as antecedents. Journal of Entrepreneurship, Management and Innovation 20(2), 53-74. https://doi.org/10.7341/20242023

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