Differences in Occurrence of Unethical Business Practices in a Post-Transitional Country in the CEE Region: The Case of Slovakia

Abstract

This study aims to contribute to the understanding of unethical practices in business and asks whether certain types of organizations are considerably more exposed to unethical business practices than others are. Drawing from the tenets of institutional theory, the paper investigates the occurrence of unethical practices in different organizational “fields”, namely the industry sector (with focus on Finance and Construction), company membership in professional networks, company ownership (public/private), and company age. The method of stratified random sampling by proportional allocation is used to establish the sample (n = 1295), composed mostly of company owners and higher managers. Results show that, in general, the industry sector, membership in professional networks, and company age are associated with significant variance in the perceived incidence of unethical practices, whereas company ownership has no significant effect in this regard. More specifically, the construction sector is significantly more exposed to unethical practices than other sectors in the sample, while the finance sector is not. Companies with membership in professional networks report a significantly lower occurrence of unethical practices. Young companies are significantly more exposed than their more mature counterparts; however, here the effect of company size must be accounted for. The research was conducted in one of the former CEE block countries—Slovakia. Given their common communist past and comparable peripeties with the transition process, these findings might be useful for understanding business ethics issues in a wider context of the CEE region.

1. Introduction

“You have principles and I have money”.—This statement appeared in a discussion between a university lecturer and one successful entrepreneur, and is the epitome of the current business ethics problems in Slovakia and, we believe, other post-communist countries in the Central and Eastern Europe region (CEE). The whole conversation started with a seemingly innocent question about the entrepreneur’s life story and his recipe for success, which he could then later share with students in class during his guest lecture. His reaction was swift, asking the teacher—“Do you pay taxes, my friend”? The teacher, taken by surprise, said “Yes, of course… I have principles, and after all, paying taxes is for our common good; as citizens we have some responsibility towards our society”. The businessman laughed, put his arm over the teacher’s shoulder, and said “Well, you see, you have your principles and I have my money… perhaps you should borrow my accountant, a very clever guy, indeed”.

This anecdotal real-life story reflects only one of the many ethical problems in business that still occur in the Slovak business environment thirty years after communism, suggesting some sort of separation, or even a gap, between business and other societal institutions. According to the survey on a sample of more than one hundred Slovak companies carried out by the Slovak Compliance Circle [1], the majority of respondents perceive business ethics in Slovakia negatively (88%), with almost half of them confirming having lost a business opportunity due to the unethical conduct of competitors. The results of more recent research on the specifics of the Slovak business environment show that in Slovakia, a business is not seen as nested firmly in society and cooperating along with other societal institutions and that the mentality of businesses is influenced by the weak rule of law and insufficient enforcement of compliance with the rules [2]. The advancement of business ethics in the country is impeded by a vicious circle of interlinked barriers including self-serving orientation of businesses, orientation to short-term profits, and mistreatment of company stakeholders [3].

Our approach to studying unethical practices is anchored in several theoretical frameworks. These include the new institutionalism theory, where the roots of unethical business phenomena are associated with the influence of formal and informal institutions on contemporary economic life [4,5,6,7]. Furthermore, in classifying various unethical practices examined in this research, we build on stakeholder theory [8,9,10,11]. The broader significance of this study follows from Enderle’s three-level theory of business ethics [12,13] and Goodpaster’s concept of the “subject matter” of business ethics [14], which emphasizes the close interconnectedness of societal, organizational, and individual levels of morality. Our study focuses on the mezzo level of analysis, that is, on organizations whose ethically questionable behavior within the “social territory” of business has far-reaching consequences for the overall quality of life within our societies.

This study attempts to contribute to the contemporary discourse on ethical issues in business in several ways:

(1) First, the daily reality of business ethics in the countries of the CEE region is somewhat understudied. We contend that our findings might be useful for understanding business ethics issues in a wider context of the CEE region. Considering their common communist past and comparable peripeties with the transition process, it is likely that the CEE countries share similar ethical problems and face comparable difficulties in the current business environment. Prior research [15,16,17,18,19,20] has shown that post-communist countries in the CEE block have to cope with the “heritage” of the common socialist past, and experience complex challenges connected with a drastic underestimation and general unpreparedness for the transition to the free market economy.

(2) Second, this paper presents an empiricist approach to the study of unethical business practices. It reacts to the so-called rhetoric–reality gap in business ethics studies, which has been noted by many scholars already, e.g., [21,22,23,24,25]. They claim that there might be a wide distance between what is being verbalized and what is being done by companies in terms of ethics. In general, research deals mostly with what firms verbalize in their CSR reports and codes of ethics [26,27,28,29]. The rhetoric–reality gap suggests the formalistic approach to ethics may not reflect fully upon the daily reality of business.

Given that, this study aims to delve into the real, perceived problems that firms experience in terms of business ethics. We build on the fact that experiences with (un)ethicality in the business environment ultimately shape the decisions of company owners with respect to a wide array of problems. In case company owners or managers perceive that the environment is plagued by systemic opportunism, this market force might bend the values of entrepreneurs and limit their ethical self-reflection as well [30]. Therefore, this study finds it useful to focus not on the ethics-related rhetoric but on the perceived occurrence of unethical practices and related experience of respondents from the corporate practice.

(3) Third, another contribution regards the relatively large scope of unethical practices which surpass the otherwise usual narrow focus on corruption reflected in quantitative surveys that pinpoint the problematic way of doing business in the CEE post-transitional societies. Their methodologies focus largely on commonly held impressions and are based on limited samples (e.g., [31,32,33]). By contrast, this study considers the subject matter in its complexity. It builds on a large sample of 1295 respondents, mostly business owners and higher-level managers, and examines a relatively wide array of 26 unethical practices. By this, we intend to shed light on the realm of unethical practices in substantially closer detail. The given sample size and the scope of unethical practices (for e.g., see Appendix A, Table A1 and Table A9) are exceptional, at least in the business ethics literature. This allows for drawing reasonable conclusions and setting grounds for future comparative studies across countries.

(4) Fourth, the aim is to test the hypothesized significant differences between certain types of companies in their exposure to unethical practices. The underlying question this study posits is whether certain types of organizations are considerably more exposed to unethical practices than others are. In this respect, we focus on four company-level variables, namely the industry sector (focusing on Finance and Construction), company membership in professional networks (e.g., professional and business associations, employers’ organizations), company ownership (public/private), and company age. Since in the literature on business ethics in the CEE block these factors have not been systematically examined yet, this study contributes to the current literature by providing novel insights into which types of companies are particularly burdened by immorality in business in one of the post-transitional countries in the CEE region.

In establishing our hypotheses about these four company-level variables, we build on the research tradition and tenets of the new institutionalism [5,6,34] as a useful theoretical lens for examining different organizational “fields”. According to DiMaggio and Powell, the key assertion of institutionalism is that, once an interactive network of organizations is established as a “field” and becomes a recognized area of organizational life, “powerful forces emerge that lead them to become more similar to one another” [5], p.148. Members of the field change and standardize their practices, and their strategies become increasingly isomorphic. Many of these underlying homogenization and mimicking processes are due to organizational decision-makers who model their companies after similar counterparts in their field to become more successful, socializing into the field, learning proper responses, and adjusting behavior according to the field norms [5,6,35,36]. Our research results indicate which organizational fields are particularly burdened by unethical business practices and need a more thoughtful approach and support from the institutional sphere.

First, as for the industrial sectors conceptualized as fields, we elaborate on the ideas of Beschorner and Hajduk [37] that industrial sectors serve as frames of reference for companies through which they gain distinct identity, resolve problems with distinct institutional logics, and adjust to the routines of their industry. Here, we focus specifically on Construction and Finance, because prior research [38,39,40,41,42,43,44] shows that these are the critical sectors in which an unethical business culture might be strongly embedded. As for the second company variable, company membership in professional networks, we derive from Scott’s idea that, along with the state, professional networks are the main actors who shape the current institutional environment [45]. Professional networks span their member organizations and produce normative pressure and isomorphic tendencies across the field [5]. They might be conceptualized as communities of practice, which shape the path of their members towards business ethics and compliance [46] and shelter their members against unethical business activities, creating and sustaining environments that support affirmative and positive ways of doing business. Third, this study looks at the exposure to unethical practices in public- and private-owned organizations. Public-owned organizations serve as an important ingredient of institutional life. They can be considered a specific field that has developed a particular set of norms, routines, regulations, and patterns of behavior. Prior research showed that, in comparison to private organizations, their public counterparts face far more ethical issues and suffer from underutilization of both formal and informal ethics management structures [47,48,49]. This may lead to lower preparedness of public organizations to cope with negative externalities related with unethical behavior. As for the fourth variable in our study, company age, we derive it from the idea that younger and less matured companies do not have formal and informal ethics management structures in place and, as such, are less prepared to deal with ethical challenges [38,50,51]. Importantly, in case the wider business environment is deformed by unethical practices, younger companies tend to assimilate with the prevalent unethical modus operandi, as prior research indicates that young companies are more compatible and isomorphic with the culture of their environment than companies in a mature stage are [52].

Here, we consider it necessary to note that, for the sake of potential theoretical and practical advancements, two levels of analysis were utilized in testing for significant differences in the sample. The first level includes the composite measure of all unethical business practices in total, while the second level of analysis takes a closer look at statistical differences with respect to the key company stakeholders, namely the business partners, customers, competitors, employees, and state/society. We contend that the stakeholder approach [9,10,11] facilitates a more complete picture of how a business fulfills its ethical obligations towards various stakeholders and where exactly an urgent intervention is needed to improve the business environment. Connected with that, the practical implications of this study are centered around suggestions for policymakers, company owners, and managers, who wish to streamline the preventive measures against unethical practices in business.

2. Theoretical Background

2.1. Research Context

As this research was carried out within a specific socio-cultural framework, we believe it might be instructive to first discuss some specifics of the development of business ethics nested in political and economic transformations that the CEE region has experienced in the last thirty years [4,53]. Although unethical practices are found in business universally, corporate choices about these tactics are influenced by their social and cultural contexts [34].

We follow up on Matten and Moon’s [34] delineation of “institutions” as not only the formal organization but also as norms, rules, and routines, representing recurring patterns of behavior, which define the boundaries of what is regarded as acceptable and constrains individual behavior. Clearly, the boundaries of what is regarded acceptable will vary across different socio-cultural frameworks. Due to close cultural and historical ties and the common communist past, countries in the CEE region face similar ethical issues in business. Therefore, the results of this study might be useful for understanding ethical problems in doing business in post-transformational countries of the CEE reagion.

The yearly country rankings in the Corruption Perception Index (CPI) by Transparency International reveal that the post-communist EU member states are still struggling with how to appropriately address the corruption in their countries. Authors agree that, after the fall of the Iron Curtain and the beginning of economic transformation from a centralized state-led to a free market economy, businesses in CEE were operating primarily for the profit of their owners, and only a few companies understood their obligations towards the society, the citizens, or the environment [29]. An antagonistic relationship between the state and business has evolved. As Bohatá [53] p.1574 observed, the business environment was burdened by “insufficient law and jurisdiction, low support of ethics in laws, and low interest of political leaders and government in ethics”, and it slowly became clear that these difficulties would not vanish automatically with growing market experience. Unfortunately, at that time, most businessmen as well as state administrators were unaware of the principles of the free market economy, and the formation of a new economy took place “without anchoring new economic subjects in social responsibility for privatized assets, restituted property, employees, or for the society as a whole” [54] p.152. The process of transformation in the CEE countries was painful. For the majority of the population, it was accompanied by a decline in the standard of living and severe disappointment with the new generation of politicians who were shown to be susceptible to corruption. The influence of various business groups and oligarchs was intense, which eventually led to the state capture and systemic political corruption [55].

However, positive changes in attitudes to corporate social responsibility and effective regulation of business activities began to materialize after a couple of decades. Larger businesses and professional associations in particular were at the heart of these changes because they realized that an unethical business environment impedes long-term economic success and imposes risks not only for companies but also for the long-term sustainability of the market economy itself [54]. Some studies indicate a positive trend in this respect. For instance, Uzelac et al. [56] found that the institutional setting in many CEE countries has improved over the past years, particularly in the control of corruption. The Eurobarometer [57] reports that the proportion of Slovaks who have experienced an act of corruption has substantially decreased since 2013 and that there is a considerable decline also in the proportion of Slovaks who believe that corruption cases go unreported due to the fear of getting into trouble for reporting them. Remišová et al. [54] maintain that Slovak businesses are becoming more aware that their long-term economic success cannot be achieved in an unethical business environment and that, as the country lacks a government-driven ethical framework, businesses must start to improve business ethics by themselves.

2.2. Unethical Practices in Business

One of the reasons we focus on unethical business practices lies in their undeniable gravity in undermining other societal institutions. Many business ethicists warn that the uni-dimensional perception of the company as a tool for profit maximization for the company owner or shareholders, greed, and the accompanying negligence of the legitimate interests of company stakeholders is at the forefront of business decisions and that this carries significant risks of further separation of business from other societal institutions [11,58,59].

Thus, the broader significance of studying the occurrence of unethical practices in business stems from the three-level theory of business ethics [12,13] and the related “subject matter” concept of business ethics [14], which emphasize the close interconnectedness of societal (macro), organizational (mezzo), and individual (micro) levels of morality. The development of business ethics takes place simultaneously on all three social levels. They are essential for the development of business ethics within a country, within a particular region, and globally. They overlap and interact, and if one level fails, its role may temporarily be replaced by another level. However, in the long run, one level cannot fully compensate the other [14].

The economic sphere forms one of the spheres of social life and is profoundly interconnected with other societal institutions, while its basic mission is to support the quality of life and sustainability of the current and future human population [60]. According to the concept of the subject matter of business ethics [14], business subjects represent a specific “social territory”, bearing predefined roles and specific ethical responsibilities.

Violations of these ethical obligations in the form of unethical business practices are extremely diverse in corporate practice. Thus, in the empirical research, there is a need to classify the bulk of unethical practices within a logical structure. The literature offers several typologies of unethical practices. Usually, various application areas such as ethical issues in finance, marketing, or human resources are considered. Alternatively, authors focus mostly on broad types of unethical activities such as fraud, corruption, blackmailing, conflicts of interests, or corporate espionage. For instance, one of the earliest typologies was proposed by Nicholson and Robertson [61]. However, their classification derived from a theoretical basis was somewhat complicated in merging together various ethical issues (e.g., product quality and safety, environmental protection, advertising, and discrimination) and stakeholders (e.g., customers, local community, and government). Another typology by Fassin [38] was based on theoretical reflection and anecdotical case evidence from the corporate practice and included ethical issues such as fraud, unfair competition, unfair communication, a lack of respect for agreements, unfair attitudes towards and unfair treatment of stakeholders, abuse of power, and conflicts of personal versus stakeholders’ interests. An interesting and rather unusual typology was put forward by Geva [62]. Its uniqueness lies in referring to the psychological-cognitive issues in ethics, emphasizing managerial perception, and referring to various types of moral problems, namely the “genuine ethical dilemma”, “compliance problem”, “moral laxity”, and “no-problem“ situations, when the person knows what the moral obligation is and has the will and the ability to fulfill it. A more novel classification of unethical practices by Lasthuizen et al. [63] was based on a conjunction of desk and empirical research and included 10 categories of ethical issues in business (e.g., bribing, favoritism, fraud, theft, and conflicts of interests). However, this classification was informed by findings from the counterproductive behavior and organizational deviance stream of research and therefore focused more on the company’s internal practices, giving less account of practices regarding the external stakeholders in the market.

In this study, we decided to use the stakeholder approach [8,9,10,11,59] for the categorization of various unethical business practices into meaningful subunits. By definition, stakeholders are groups that are influenced by the company operations, having a contractual link to the company (employees, suppliers, etc.) or the wider public (region, society, environment, etc.). The stakeholders have legitimate interests related to the company operations, and any responsible company should accept and respect these interests. Nevertheless, the relationship of the company with its stakeholders can be uneven due to power inequality (e.g., managers vs. employees and suppliers vs. customers). The influence of stakeholders over the company differs across various stakeholders due to their power position in negotiations with the company, legitimacy as a mandate to use power in claiming something from the company, and urgency, calling for immediate action of the company [10].

This study utilized the classification of unethical practices based on five specific company stakeholders, namely, business partners, customers, competitors, employees, and the state/society. They belong to the group of so-called primary stakeholders, including groups with a high level of interdependence without whose ongoing contribution the company cannot survive [8]. This choice was informed also by the qualitative research stream with several focus groups, which preceded the quantitative research in this study and shaped the content of the questionnaire items (see the Methodology section). More specifically, from the 26 unethical practices investigated in this study, six practices related to business partners, three practices were tied to customers, four practices concerned the competition, seven practices related to employees, and six practices were linked with the wider state/society (for a detailed overview, see the Appendix A, Table A1).

2.3. Differences in Occurrence of Unethical Practices in Business

As outlined in the Introduction, the underlying question this study posited was whether certain types of organizations are considerably more exposed to unethical practices than others are. In specifying the particular “types” of organizations, we built on institutionalism theory [5,6,34] as a useful theoretical framework for understanding the potential differences in occurrences of unethical practices in different organizational “fields”. We focused on four company variables, namely the industry sector (with a focus on Finance and Construction), company membership in professional networks, company ownership (public/private), and company age. In building our hypotheses about these four company-level variables, we strived to leverage the prior work of authors who examined unethical practices in different types of organizations. In the literature on business ethics in the CEE block, these factors have not been systematically examined yet. Nevertheless, although the extant research is predominantly Western-based, we regard it as a useful starting point for developing our hypotheses.

The first hypothesis deals with the linkage between unethical business practices and the industry sector in which the company operates. We focus on the industry because Beschorner and Hajduk state that the “industrial sectors—similarly to national cultures—can be seen as ‘frames’ for the actors (companies), which see themselves and are seen by others as belonging to a specific group with a distinct identity and distinct problems and ‘institutional logics’” [37], p. 637. Unique subcultures with specific norms of behavior are created within these operational frameworks, with companies adopting the same patterns of behavior, that is, the common “rules of the game” [64], with respect to company stakeholders. Furthermore, as Peeters et al. [65] note, specific industries tend to be involved in specific rule violations, and some industries are more criminogenic than others are. This implies that the industry might be a critical factor in the diffusion of unethical activities.

Research shows that critical sectors in which an unethical business culture might be strongly embedded are Construction and Finance. For instance, Fassin [38] states that, in the construction industry, the large general contractors seek to generate additional profit by squeezing the prices of their subcontractors, even at the expense of quality and safety. Vee and Skitmore [39] identify several ethical issues in the construction industry: unfair conduct, negligence, conflicts of interest, collusive tendering, fraud, confidentiality and propriety breach, bribery, and environmental damages. In another study, Abdul-Rahman et al. [41] conclude that the construction industry is plagued mainly by underbidding, bid shopping, or bid cutting, followed by bribery, corruption, negligence, front-loading, payment games, cover pricing, or withdrawal of payments.

As for the financial sector, the so-called “Goldman rule” suggesting that financial institutions are less likely to engage in ethics because the opportunity costs of such behavior are high [42]. The greed and related profit maximization are ingrained in the substance of financial institutions [43], and Watkins [42] states that the greater the profitable opportunities are, the more likely the banks will not regard the broader consequences of their actions. In addition, Cohn et al. [44] suggest that the prevailing way of how the banks operate undermines the norms of an honest business culture.

In the Slovak context, the studies on ethics in the banking sector are almost non-existent. One exception is the study by Belas et al. [66], although this study does not deal with ethical issues directly. The results of their empirical inquiry show that the last financial crisis led to a deterioration concerning banks’ employee acceptance of client needs as, meeting the needs of the client’s interest has decreased significantly in 2012 compared to 2008.

Given the discussion on unethical practices across both industries, we hypothesized the following:

Hypothesis 1a (H1a).

Experience with unethical business practices differs by the sphere of economic activity, in that the construction sector is significantly more exposed to unethical business practices than other sectors.

Hypothesis 1b (H1b).

Experience with unethical business practices differs by the sphere of economic activity, in that the finance sector is significantly more exposed to unethical business practices than other sectors.

The second hypothesis regards companies’ membership in professional networks. Here, we derive from Scott’s idea that, along with the state, professional networks are the main actors who shape the current institutional environment [45]. In the light of institutionalism, professional networks span their member organizations, producing normative pressure and isomorphic tendencies across the field [5]. They are significant, but rarely studied actors, co-creating the character of the entire business environment. As Besser and Miller [67] state, although the business networks are considered the key organizational form in the global economy, very little is known about how they affect the ethical and social performance of their members. Based on comprehensive research and multilevel analysis of a large number of data, the authors contend that members of the professional networks are likely to conform to the pattern of social performance prevailing in their association [67]. More currently, Weller [46] conceptualized professional associations as “communities of practice” that can determine the path of community members towards corporate responsibility and compliance.

This indicates that the role of professional networks in the modern business-driven society does not end with advocating the business interests but extends to developing business ethics in line with societal expectations. Slovak professional networks have a significant impact on the development of legislation [68], designing new measures to improve the ethical functioning of the business sector. In addition, besides interfering with the legislation process at the macro-level (i.e., state, politics, and legislation), the professional networks support businesses in a variety of ways by organizing educational activities, issuing specialized publications or quality certificates. They monitor and analyze current legislation and inform member companies about its changes; they support networking among companies and assist and strengthen the position of businesses with the state.

In line with the above-discussed literature [45,46,67], professional networks have normative and isomorphic tendencies via educational, informational, networking, and developmental functions in the business community. Therefore, we hypothesized the following:

Hypothesis 2 (H2).

Experience with unethical business practices differs by the membership in professional networks, in that the companies with membership in professional networks are significantly less exposed to unethical business practices than non-member companies.

The third hypothesis connects the unethical business practices and the public/private ownership of companies. Conventionally, public-owned organizations serve as an important ingredient of institutional life. They can be considered a specific field that has developed a distinct set of norms, routines, regulations, and patterns of behavior. Western-based research indicates that, compared to private-owned companies, their public counterparts face far more ethical issues. For instance, Svensson et al. [47] conducted research on ethics commitment in public and private sector organizations in Sweden and showed that, although both sectors suffered from relatively underutilized business ethics measures, the private organizations were somewhat more developed in this regard. According to some scholars, the ethicality of employees and managers in public-owned organizations is under great pressure. Wittmer and Coursey [48] found that public managers perceived the ethical climate in their organizations less favorably than private managers did. According to Boyne [49], public employees work in a complex and unstable environment, which is more prone to ambiguity and outside influences.

Interestingly, these findings are consistent with the Slovak research results showing that ethical leadership at the top of Slovak companies is less developed in public organizations. According to Kirchmayer et al. [69], the public sector in Slovakia is lagging behind the private sector in ethical leadership. In addition, their results indicate differences in favor of leaders in private companies regarding ethical decision-making as well as the level of knowledge leaders have in ethics. Similarly, Lašáková et al. [70] show that employees working in the public sector perceive their leaders as considerably less values-oriented.

The institutionalism literature pinpoints that organizational decision-makers are those who model their organizations after similar counterparts in their field to become more successful [5,6,35,36]. Likewise, in the behavioral stream of business ethics, it is widely acknowledged that company leaders influence the organizational culture and climate in terms of ethics and have a substantial effect on the ethical behavior of other employees e.g., [71,72,73,74]. In case the public sector is lagging behind the private sector in leadership ethics, the public companies might find it more difficult to cope with negative externalities related to unethical behavior.

Along this line of reasoning, we hypothesized the following:

Hypothesis 3 (H3).

Experiences with unethical business practices differ by the ownership, in that the public-owned companies are significantly more exposed to unethical business practices than private companies.

Another variable that might make a difference with respect to the experiences with unethical business practices is company age. We derive from the idea that younger and less matured companies do not have formal and informal ethics management structures in place and, as such, are less prepared to deal with ethical challenges [38,50,51]. Furthermore, when the wider business environment is deformed by unethical practices, younger companies tend to assimilate with the prevalent unethical modus operandi, as prior research indicates that young companies are more compatible and isomorphic with the culture of their environment than companies in a mature stage are [52].

The decision to embed the ethics into the company DNA right from the start in young companies is dependent on the owner–manager’s values. Lähdesmäki [30] asserts that it is the personality of the company owner-manager, more specifically the ability of the owner–manager to reconcile the profits orientation with the philanthropic social orientation, that shapes the way early-stage companies deal with ethical issues in business. More importantly, Morris et al. [50] conclude that the relationship between the company life cycle and ethical practices is based on the existence of formal management systems that have been implemented as the firm grew over time. Thus, mature companies with institutionalized ethics management structures sustain positive perceptions of the ethical performance of the firm as well as its preparedness to effectively deal with ethical challenges.

Due to a low level of ethics institutionalization in young firms, they may lack the necessary defense mechanisms against unethicality in the business environment. Start-ups face numerous unethical practices concerning intellectual property, confidentiality of information, insider trading, or conflicts of interest related to raising funds. Other ethical issues typical for less mature companies include a lack of fairness in personnel and customer relationships, untruthful communication, and distribution-channel-related ethical dilemmas [38].

Given the findings discussed above on ethical problems in young firms, the lack of formalized structures, and the isomorphism with the culture of the surrounding business environment, we hypothesized the following:

Hypothesis 4 (H4).

Experiences with unethical business practices differ by the company age, in that the early-stage companies are significantly more exposed to unethical business practices than more mature companies.

In what follows, a detailed description of the research methodology relating to the above-stated research inquiries is provided. Subsequently, the research outcomes are presented and discussed, and theoretical and practical implications are outlined, together with conclusions and limitations of the current research approach and future research avenues.

3. Materials and Methods

3.1. Method and Scale Development

This paper presents one portion of results from the quantitative research strand of a larger multi-method comprehensive research project. The data were acquired through a questionnaire comprising several sections on various aspects of business ethics in the Slovak business environment.

The questionnaire section dealing specifically with unethical business practices was derived from qualitative research consisting of several consecutive focus groups that preceded the quantitative phase of this research project. Thus, the list of researched unethical practices represents an original contribution to the understanding of contemporary ethical problems of the business environment in one of the post-transitional countries of the former CEE block.

The first four focus groups aimed to gather qualitative information on ethical issues in the Slovak business environment. These were organized in November 2017 and March and April 2018. The first focus group included eight representatives from prominent Slovak business and employer organizations; the second was with eight participants working in “Via Bona” award-winning organizations (this award-winning competition is organized by the Pontis Foundation for companies that are considered role models in business ethics in Slovakia); the third focus group entailed six representatives of the SME sector in Slovakia; the fourth was organized with seven representatives from six large companies operating in Slovakia and abroad.

After processing the substantial amount of rich qualitative data, a large list of unethical practices appearing in the current Slovak business environment was compiled. In the next step, this list was distributed to research team members and was critically analyzed. The aim was to drop practices that were infrequent or overlapping and thus to reduce the length of the list. Afterward, the first draft version of the questionnaire section on unethical business practices was put together.

Consecutively, four additional focus groups tested the pilot version of the questionnaire to ensure that the final version would be clear and understandable for respondents. These focus groups were carried out in October and November 2018 with a total of 32 company owners, managing directors, and top managers. Their critical assessment of the design and content of the draft questionnaire resulted in another portion of rich data, based on which the research team decided to edit the content, diction, and graphic outline of the research tool.

The final questionnaire section with the unethical business practices (test variables) entailed 26 individual items structured according to five primary stakeholders of the company (see Appendix A, Table A1).

3.2. Sampling Strategy and Procedure of Data Acquisition

The method of stratified random sampling from the population of Slovak companies by proportional allocation was chosen to establish the sample. The company size and company regional location were used as the stratification variables. The classification of the variable “company size” was based on the number of employees according to the European Commission recommendation no. 2003/361/EC [75]. It entailed four categories: 345 micro (1–9 employees), 413 small (10–49 employees), 294 medium-sized (50–249 employees), and 243 large companies (250 or more employees). The groupings within the variable “company regional location” were based on the classification system NUTS2 [76] and included 422 companies from the Bratislava region, 369 companies from the West Slovakia region, 261 companies from the Central Slovakia region, and 243 companies from the East Slovakia region. In line with the research design and the fact that the four examined variables were related to the company level of analysis, the sampling strategy was based on the inclusion of one participant from each organization. The required minimum number of individual respondents from participating organizations in each of the 16 categories (four regions × four company sizes) was determined based on well-established formulas [77,78] (for a detailed description of the procedure for calculating the sample size, see [79]).

The data acquisition took six months, from January to June 2019. Data were gathered via an identical e-questionnaire and its printed version. Members of the research team approached potential research participants through email addresses included in the database of Slovak companies provided by FinStat. Moreover, as it was challenging to gain the desired response rate from the medium-sized and large companies due to their limited numbers in the Slovak economy, the Cribis universal register of firms was utilized to contact the company owners and top managers. In addition, after the first round of the call for participation (January–February 2019), the research team used individual contact methods (email or telephone) to disseminate the call to medium-sized and large firms from distinct Slovak regions with a lower initial response rate (especially in the East Slovakia region). Some contacts were gained also with the help of prominent business and employer organizations (Slovak Compliance Circle, National Union of Employers, and Federation of Employers’ Associations of the Slovak Republic). In the second round of data gathering (March–June 2019), along with electronic calls, the dissemination of the printed questionnaires started. Three team members visited altogether eight conferences for business professionals, where the conference organizers kindly provided time and space to inform conference participants from the corporate practice of the research being undertaken and asked them to fill out the questionnaire.

3.3. Sample Demographics in Brief

The final sample consisted of n = 1295 respondents (for an instant overview, see Appendix A, Table A6). The proportion of women and men was quite balanced in the sample, with 46.3% females and 53.7% males. The majority (30.4%) were in the age category of 41–50 years, 26.2% were 51–60 years old, and 23% were in the category of 31–40 years old. The least populated were age categories of 60+ years (11%) and up to 30 years (9.3%). As for their educational level, 82.4% of respondents had a university education (8.7% with a Bachelor’s degree, 62.8% a Master’s degree, and 10.9% a Ph.D. degree or higher). Most of them (47.1%) had economic/management education, followed by technical education (28.6%). As for their position in organization, most respondents worked as managers (41.5% company owners/managing directors; 24.7% top managers; 5.1% managers (non-specified); 1.5% ethics and compliance managers), or their position included managerial roles that relate to addressing ethical issues in the company (0.8% internal lawyers; 0.8% internal auditors; 0.4% ethics officers). Last but not least, their seniority in the respective positions ranged from the following: less than one year (6.5%), one to three years (17%), four to ten years (29.3%), and more than ten years spent in the position (47.3%).

3.4. Grouping Variables

As for the company variables included in this study, the descriptive statistics for grouping variables are shown in Appendix A, Table A7 and Table A8. In percentage terms, slightly more than 39% of the sample was populated by companies with membership in professional networks. As for company ownership, 89% were private-owned. In terms of company age, 1.8% of companies were established less than three years prior, 15.8% had been operating for 4–10 years, 19.7% had been operating in the market for 11–15 years, 14.7% of the sample had run for 16–20 years, 33.3% of companies had been active from 21 to 30 years, and 14.7% of the sample included companies that had been in the market for 30+ years. The industry sectors were differentiated according to the NACE system of classification into 10 categories [75] and included general services (20.3%); wholesale trade, retail trade, transportation and warehousing, accommodation, and food services (19.4%); manufacturing, mining, quarrying, and related services (18.1%); construction (9.7%); professional, scientific, technical, administrative, and support services (8.6%); public administration, defense, education, healthcare, and social assistance (6.8%); agriculture, forestry, and fishing (5.2%); information and communication (6.7%); finance and insurance (3.5%); and real estate and related services (1.7%).

3.5. Test Variables

As outlined in Section 3.1, the 26 unethical practices related to five primary stakeholders of the company. These included business partners (six items), customers (three items), competitors (four items), employees (seven items), and the state/society in general (six items).

The descriptive statistics for the total score (composite) for the five stakeholder groups and for the individual 26 unethical business practices are shown in Appendix A, Table A9.

The main question in the respective questionnaire section given to respondents was whether they encounter these unethical practices when doing business in Slovakia, while the instruction was to answer this question on a five-point scale ranging from “yes, I encounter this practice” to “no, I do not encounter this practice”. In processing the results, the answers on the scale were coded reversely (with 1 indicating a low occurrence and 5 denoting a high occurrence of the unethical practices).

The main methodological approach (quantitative and survey-based) is linked with some limitations and potential epistemological problems. Traditionally, ethics studies build on the positivistic model and are predominantly quantitative. Since, in its essence, ethics studies try to answer qualitative questions (relating to morality, justice, fairness, etc.) via a quantitative approach [80], there is a strengthened call for a more pluralistic approach to the study of business ethics phenomena including interpretative modes of inquiry in the study of morality in business organizations [80,81]. Our approach in this study is quantitative and, as such, might not be immune to the traditional problems of the positivistic paradigm in social sciences. The general reluctance of respondents to answer questions about their own ethical behavior was shown in prior research, e.g., [38,51,81]. To minimize distortion in the meaningfulness of the acquired data, we avoided questions about respondents’ intentions, value preferences, or normative self-reflection. Instead, this research focused on mapping the perceived occurrence of unethical practices in business through respondents’ insights from their real-life business experience. This sort of indirect questioning approach was chosen deliberately to avoid the social desirability bias that could negatively affect the data [81,82,83]. Hence, to minimize biased responses, the central instruction did not ask respondents to evaluate their personal attributes, attitudes, or behaviors but invited them to assess their lived experience with various unethical practices occurring in the business environment.

3.6. Preliminary Data Analysis

After completing the dataset, the reliability analysis was conducted. Cronbach’s alpha for the 26 items altogether equaled α = 0.97, and the “if deleted” analysis did not prove to be reason for dropping any of the items (Appendix A, Table A1). Subsequently, the reliability analysis was also carried out for the individual five classes of unethical practices grouped according to company stakeholders, and results showed that all five groups of items were stable, with alpha values well above the threshold of 0.60, with α = 0.87 for unethical practices towards business partners, α = 0.93 for unethical practices towards customers, α = 0.90 for unethical practices towards competitors, α = 0.94 for unethical practices towards employees, and α = 0.96 for unethical practices towards the state/society (Appendix A, Table A2).

Interestingly, the exploratory factor analysis (Appendix A, Table A3 and Table A4, Figure A1) retained four instead of five factors. The total variance explained was 54% (cumulative 73%). While Factors 1, 3, and 4 matched the given groups of unethical practices with respect to employees (in Factor 1), the state and society (in Factor 3) and business partners (in Factor 4), the other two groups of variables (customers and competitors) were grouped into a single Factor 2. This result was unexpected and should be interpreted with caution. Given that we examined the occurrence of unethical business practices, this result implies that the ethical issues related to both the customers and competitors might be, actually, closer than originally thought and that the issues included in the questionnaire might be quite interconnected in practice. Thus, although theoretically distinct, the items under the “unethical practices towards competitors” (e.g., cartel agreements, unfair procurement practices, patent abuse, and purposeful damaging of competitors’ reputations) and items under the “unethical practices towards customers” (e.g., low-quality products, avoiding liability for complaints and errors, and misleading advertising) seem to be connected (at least in terms of their occurrence) in practice.

To assess the normality of distribution, the Kolmogorov–Smirnov and the Shapiro–Wilk tests were utilized (Appendix A, Table A5). Both tests showed that the data were not normally distributed (with p-values below the threshold of 0.05). Thus, the nonparametric tests were applied in the following process of testing for statistically significant differences in the sample.

In addition, to ascertain the potential effect of company regional location and company size as the two stratification criteria, based on which the representative sample composition was established, we performed in the preliminary analysis a series of partial correlation tests with unethical business practices (total score) and the examined four company-level variables (industry, membership in professional networks, company ownership, and company age). Results showed that the regional location and company size as control variables did not have any effect on the relationship between unethical practices and company ownership and industry. Regional location had an effect on the relationship between unethical practices and membership in professional networks and company age. Still, these relationships were significant in either case, and the differences before and after, including the control variable, were only trivial. The same was applicable for the effect of company size on the correlation between unethical practices and membership in professional networks. The only change in significance when controlling for the company size was found for the relationship of unethical practices and company age. From the preliminary analysis, we concluded that the analysis of differences in unethical practices based on company age needs to be interpreted cautiously due to contamination of these results by the effect of company size.

4. Research Results

Two levels of analysis were utilized in testing for significant differences in the sample. The first level included the composite measure of all unethical business practices in total, while the second level of analysis took a closer look at statistical differences with respect to the five stakeholders, namely the business partners, customers, competitors, employees, and the state/society. The statistical significance of differences in the sample was tested by nonparametric Mann–Whitney U test (Table 1, Table 2 and Table 3) and Kruskal–Wallis H test (Table 4 and Table 5). The sample statistics of the variables in the study and the correlations among the individual variables are included in Appendix A, Table A7 (grouping variables), Appendix A, Table A9 (test variables), and Appendix A, Table A10 (correlations). The comparison of mean values in unethical business practices (hereafter UBPs) based on the examined company variables is displayed in Appendix A, Table A11.

As per H1a and H1b, we argued that the experience with UBPs differs by the sphere of economic activity, in that the construction sector (H1a) and the finance sector (H1b) are significantly more exposed to UBPs than the other sectors in the sample. The results of data analysis (see Table 1) show that, in line with H1a, the UBP total score was significantly higher in the construction sector as compared with the other sectors (U = 62,637.500, p = 0.008). Likewise, the UBPs toward the five company stakeholders were higher for the construction companies. Here, however, the statistical significance of differences was confirmed only for business partners, customers, and competitors, while the UBPs towards the employees and the state/society were not significantly different (p = 0.332 and p = 0.341, respectively).

Findings for the finance sector (Table 1), however, demonstrated inconsistency with H1b. The difference between the finance companies and the rest of the sample in the UBP total score of U = 26,647.500 was insignificant (at p = 0.549). The same result was observed for the five company stakeholders (with p = 0.973 for business partners, p = 0.472 for customers, p = 0.545 for competitors, p = 0.180 for employees, and p = 0.869 for state/society). The line graph (Figure 1) with lines differentiated according to the five stakeholders shows a quite similar ascending trend across the examined industries. The only deviation occurs with respect to the stakeholder “business partners”, where, compared to the other sectors, the trend is slightly decreasing.

As per H2, we proposed that the experience with UBPs differs by the membership in professional networks, in that the member companies are significantly less exposed to UBPs than non-member companies. Consistently with H2, results of data analysis through the Mann–Whitney U test (Table 2) showed that companies with membership in professional networks are significantly less exposed to unethical practices in the UBP total score (U = 137,960, p = 0.000) as well as regarding the UBPs towards the five company stakeholders (U = 147,332.500, p = 001 for business partners, U = 138,932.500, p = 0.000 for customers, U = 136,398.500, p = 0.000 for competitors, U = 142,924, p = 0.000 for employees, and U = 142,776.500, p = 0.000 for the state/society). The trend stays stable across the five stakeholders, with increased UBPs towards the five stakeholders reported by companies that are not members of any professional network (Figure 2).

As per H3, we contended that the experiences with UBPs differ by ownership in that the public-owned companies are significantly more exposed than private companies. However, the results of the Mann–Whitney U test (Table 3) indicated that, contrary to H3, there were no statistically significant differences in the UBP total score nor the UBPs for the five stakeholders. The UBP total score showed U = 50,605 with p = 0.706, followed by U = 45,569.500 and p = 0.055 for business partners, U = 48,917, p = 0.369 for customers, U = 47,055.500, p = 0.143 for competitors, U = 48,436, p = 0.298 for employees, and U = 51,108.500, p = 0.823 for the state/society. Interestingly, the line graph (Figure 3) shows a divergent trend in UBPs across stakeholders in public and private companies. The UBPs towards employees and customers are increasing in the public companies, while the UBPs towards business partners, competition, and slightly towards the state/society show a decreasing tendency in the public companies, as compared to the private companies.

As per H4, we argued that the experiences with UBPs differ by company age (that is, the time a company has been in the market), in that the early-stage companies are significantly more exposed to UBPs than more mature companies. In line with H4, the Kruskal–Wallis H test (Table 4) showed that there was a statistically significant difference in the UBP total score between the companies based on their age, χ²(2) = 20.970, p = 0.001, as well as in UBPs towards the five stakeholders (χ²(2) = 12.721, p = 0.026 for business partners, χ²(2) = 13.678, p = 0.018 for customers, χ²(2) = 21.535, p = 0.001 for competitors, χ²(2) = 20.558, p = 0.001 for employees, and χ²(2) = 14.301, p = 0.014 for the state/society). As shown in Figure 4, the curves for UBPs towards the five stakeholders copy the common trend, according to which the early-stage companies (less than 3 years in the market) report a significantly higher occurrence of UBPs than companies operating in the market for a longer period of time. In contrast, companies operating in the market for more than 30 years seem to be significantly less exposed to unethical practices than the rest of the sample.

The preliminary analysis showed that, in the case of company age, the results might be contaminated by the effect of the company size. Therefore, we conducted a split analysis and replicated the Kruskal–Wallis H test (Table 5) layered by company size (micro, small, medium-sized, and large companies). The results show that the significant differences in exposure to UBPs (total) based on company age are located in medium-sized and large firms (χ²(2) = 11.111, p = 0.049, χ²(2) = 16.010, p = 0.007, respectively), while micro and small companies do not show any significant difference in this respect. As for the individual company stakeholders, differences are significant in large firms with respect to customers (p = 0.012), employees (p = 0.011), and the state/society (p = 0.009). Detailed description of the mean values for UPBs differentiated according to company age combined with company size is shown in Appendix A, Table A12.

5. Discussion

The industry sector. This study focused on two specific sectors, Construction and Finance, which have been hypothesized in past literature to be especially susceptible to immorality and irresponsible practices in business. Consistently with previous studies on ethical issues in Construction [38,39,40,41], our study showed that it was plagued with unethical practices substantially more than the other sectors in the sample (H1a). However, and contrary to theory, the incidence of unethical practices in the Finance sector did not differ significantly from the rest of the sample (H1b), and this result was confirmed also for the five company stakeholders included in this study. This outcome was quite unexpected since the academic literature gives evidence that the financial sector, including the banking subsector, is especially prone to some forms of unethical conduct such as abusing power over entrepreneurs who lack financial resources [38], prioritizing profits over ethics [42,43], and engaging in money laundering schemes [84]. These and similar problems weigh down the reputation of the financial sector. Still, in our sample, the Finance sector did not show any deviation from the overall level of perceived unethical conduct in other sectors.

This outcome could be explained by a stronger societal impetus for accountability in the Finance industry, which comes along with the changing role of the financial sector [85] as an institution embedded in the modern economy. According to the institutional theory, the firm’s sphere of economic activity represents a substantial operational frame, in which companies are linked together by a web of shared beliefs [37], which influences the firms’ predisposition towards short-term shareholders returns, managerial assumptions about personal moral obligations to the larger society [64], or firms’ tolerance of illegality [86]. In the past, the finance sector was perceived as an institution focusing exclusively on profits regardless of the impact on stakeholders and society. It was heavily criticized for taking unnecessary risks that could jeopardize the investments [43] or investing in complex financial instruments that promise higher profits. Unlike Construction, the Finance sector today is urged to keep up with the increased ethical standards of modern society as a catalyst and regulator of the economy. Its motivation for ethical conduct lies in increasing competitiveness and business position in responding to social and environmental changes. For instance, the banking sector is pushed to accept lower levels of returns and to participate in the real economy instead of the artificial secondary financial markets [87]. There is a shift in the perception of the financial sector as a responsible institution. Besides engagement in prosocial projects, it is urged to develop self-control mechanisms through institutionalization of ethics in internal processes (ethics and compliance programs) that can prevent an unwanted impact on stakeholders and society in general.

Membership in professional networks. By including this specific variable in our research, we reacted to the call of Besser and Miller [67] to expand the current knowledge about how business networks affect the ethical and social performance of their members. Our results showed that the membership in professional networks was indeed a differentiating point with respect to business ethics, with professional networks serving as a protective umbrella against unprincipled practices. Compared with companies, which were not affiliated with any professional network, the member companies reported a consistently lower occurrence of unethical practices in the business environment (H2).

This finding is in contrast with prior studies criticizing business networks that might actually be less inclusive and act like clubs where the big ones write the rules and do not pay attention to the needs of other, smaller members of the business environment [88]. Additionally, the international business associations were criticized due to weak child labor protection and prevailing non-specific content of their codes of ethics [89].

Our results provide an answer to the question posited in earlier research [90] of whether the professional networks are capable of addressing contemporary social and sustainability issues rather than serving merely as special interest groups detrimental to society. Our findings underline the positive side of professional networks and suggest that these associations can play an important role in educating, advising, networking, and developing business communities. This is in line with Enderle [91], an influential business ethicist, who pointed out the role of business associations in disseminating new knowledge about business ethics measures and in identifying individuals or companies that best embody ethical ideals that could serve for other business entities as role models in business. Consistent with the theory, our results give support to the idea that professional networks can serve as professional communities of practice, determining the path of community members towards corporate responsibility and compliance [46], instilling in their member companies the desired patterns of social performance [67], and sheltering their members against unethical practices in the business environment.

Company ownership. As companies within different organizational fields have different experiences with a wide range of aspects, such as problems in the regulatory environment or competitor- and customer-related ethical issues [37], we anticipated significant differences between public and private organizations with respect to the subject matter of this study. More specifically, we expected that public companies would report higher levels of unethical practices (H3). This assumption was informed by prior research that favored private-owned companies in this respect, showing that private companies were more developed in terms of the application of various business ethics measures [47], and private managers perceived the ethical climate in their organizations more favorably [48]. On the other hand, public employees had to cope with complex, ambiguous, and unstable environments [49], and public managers faced a more diverse set of stakeholders than private-sector managers [92]. The evidence discussed above showed that there might be some systematic differences between public and private companies in the way they perceive and handle various ethical challenges.

Surprisingly, and in contrast with the previous studies, the differences between public and private companies in our sample were insignificant. Our results show public-owned organizations in a quite different light, especially considering that the public sphere is criticized heavily in Slovakia. For instance, Nechala et al. [93] notes that the Slovak public companies are non-transparent and plagued by ineffective management of property, deficient risk management and control systems, non-disclosure of information, and ill practices in public procurement. Similarly, Nemec [94] showed in his recent study that there were numerous problems with the ethical principles of accountability and transparency in the Slovak public-sector organizations. However, results show that unethical practices do not occur less in private companies than in the public sector. This suggests that the ethical functioning of private companies should be scrutinized equally critically. Furthermore, it is likely that both sectors suffer from similar levels of unprincipled conduct and face similar ethical challenges.

Our study points out that the hypothesized gap in the perception of the business environment does not exist between the public and private companies in our sample, at least in terms of business ethics. This could be explained by an isomorphic tendency evolving across both the public and private spheres. These two organizational fields might be more mutually interdependent than it seems, and, as such, they might share a similar perspective. Both sectors are metaphorically in the same boat, sharing a very similar view over the ethical issues in business. These isomorphic tendencies might occur also due to changes and standardization of internal practices related to the recent pressures on the public sphere to professionalize and to apply measures for internal processes, quality control, and compliance, similar to those processes that are implemented in private companies. Thus, as their institutionalized ethics management strategies become increasingly isomorphic, perceived problems, their solutions, and strategies connected with business ethics in these two organizational fields are becoming more similar to each other.

Company age. We were interested in whether there are any systematic variations in perceptions of the business environment as the company grows and develops over time. Building a working hypothesis (H4) for this company attribute was challenging because studies concerning the effect of company age, or its proxy, the company life cycle, on business ethics are very limited.

The results of our data analysis suggested that young companies in the market for up to three years were substantially more exposed to unethical business practices than the rest of the sample and that the most senior companies reported a significantly lower incidence of unethical practices. The preliminary data analysis revealed that the relationship between unethical practices and company age might be contaminated by the effect of the company size, so we included the variable company size and carried out a layered analysis. This analysis showed that the significant differences were particularly noticeable in rapidly growing medium-sized and large companies in our sample.

These results can be explained by the institutionalization of ethics, or rather the lack of it in young companies and the related proclivity of young companies to adopt patterns of behavior typical for the surrounding business environment. We contend that the length of time that a company has survived seems to be attributed to increased professionalism and the related accumulation of knowledge on how to cope with immorality in business. We find support for this idea in the well-established framework of company culture change by Quinn and Cameron [95], which implies that the prototypical movement in time begins with an early clan culture with a friendly, informal, and family-like atmosphere, and as time passes, it evolves into a more bureaucratic, formalized, and compliance-oriented company culture. The institutionalization of ethics in young companies is usually underdeveloped, and their culture is strongly dependent on the owner-managers’ values and ethical outlook. This connects with the idea that the essence of ethics in the early-stage companies lies in responsible business practices that relate to the owner-managers’ mindset, trust, reputation, and a long-term view [21]. As the literature on the company life cycle [96,97] shows, during different developmental stages, the company culture and related strategy, management style, and control and reward systems transform substantially along with the firm’s evolution. This implies that, along with these transformations, the institutionalization of ethics in the company strengthens considerably over time. Our results resonate with prior findings that focusing on the social performance in young companies and start-ups is vital, as it is the first stage of company evolution in which a clear ethical strategy needs to be established, since company habits form right at the outset [98]. Especially in the early stage, companies lack their own mechanisms of coping with the surrounding business environment, while they face numerous ethical issues such as conflicts of interest related to raising funds, confidentiality of information, or insider trading [38]. In line with the ethics–entrepreneurship literature [50,51], we assume that, when the surrounding business environment is deformed by unethical practices, there is a higher probability that less matured firms will assimilate with the prevalent unethical modus operandi, whereas the formal and informal ethics management structures in place can help more mature companies to effectively cope with ethical challenges.

5.1. Theoretical Implications

The above-discussed research outcomes contribute to the business ethics theory in several ways. From a more general perspective, this study provides new stimuli for a theoretical reconceptualization of the most widespread ethical problems in business in the former Eastern block countries. As this study works with an original and empirically derived list of unethical business practices, the level of acquired detail allows for a deeper understanding of the dominant challenges that contemporary organizations face in the Slovak business environment. These outcomes indicate that a certain re-focus of empirical as well as theoretical studies is needed. As outlined in the Introduction, the CEE business ethics literature traditionally concentrates on the problem of corruption (e.g., [19,20,53,55]). This study shows that there are other, even more pressing problems that should be theoretically and empirically examined. In particular, results reveal that the central problem that necessitates profound theoretical reflection is the lack of trust in business partnerships. Results show that, rather than the corruption and the relationship between business partners, especially non-compliance with contracts and non-payments to business partners, represent the main “pain points” in the Slovak business environment.

Building on the tradition of institutionalism [5,6,34], this study examined differences in the occurrence of unethical practices. More specifically, it asked whether certain organizational fields, which serve for companies as a basic frame of reference, experience different rates of incidence of unethical business practices. Industry sectors, as specific organizational fields, are a basic source of identity for member companies, so it is assumed that different industries encounter distinct problems, and their adaptive response is governed by rules of specific institutional logics [37,64]. Compared with the rest of the sample, results point to a considerably higher rate of unethical practices in the construction sector, while the finance sector did not significantly differ in this respect. Probably, a shift in the perception of the financial sector as a responsible institution with developed self-control structures and institutionalized ethics mechanisms could explain this result. Although both sectors are heavily regulated, there is a stronger societal impetus for accountability in the financial companies than in the construction sector. In addition, the financial sector in Slovakia is predominantly multinational, which means that banks and insurance companies take over CSR and ethics management structures from their Western-based mother companies. On the other hand, the construction sector is considerably less internationalized and therefore cannot rely on an intensive transfer of best practices.

Furthermore, this study reacts to the call for clarification of the social influence of business associations [67]. Results add to the theoretical conceptualization of professional networks as active communities of practice [46] and underline their positive role in the development of business ethics. Our results show that membership in professional networks is connected with a more positive view of the business environment and a lower occurrence of unethical practices. Interpreted through the lens of the new institutionalism theory, professional networks may produce normative pressure and isomorphic tendencies across the field of member organizations. Networking in professional associations contributes to the standardization of practices in member organizations. Our results indicate that these adopted field norms and the mutual exchange of best practices can act like a shelter that allows member organizations to better cope with unethical business.

One unexpected result in this study regards the similarity in perceptions of the business environment in public and private organizations. Many works suggest that public organizations and their private counterparts experience different problems within their organizational fields (e.g., [37,47,48,69,92]). However, this study revealed a kind of isomorphic tendency across the two fields, at least in the Slovak context. This result deviates from the previous theory [49] and should be subject to closer examination in the future.

Additionally, the results contribute to the emerging theoretical debate on the link between company age and differences in the approach to business ethics in organizations at different stages of their life cycle [95,96,97]. This study offers a rare insight into the differences between young and senior companies in their perceptions of the business environment. We show that young firms perceive the surrounding business environment very critically as deeply permeated by unethicality. Results support the idea of vulnerability of young firms in the market that may stem from general unpreparedness of managers-owners and the lack of professionalism in early-stage firm management.

5.2. Practical Implications

Research results indicate which types of companies are particularly burdened by unethical business practices and therefore would need a more thoughtful approach and support from the institutional sphere. Several practical implications can be derived from our findings. In connection to that, we propose some measures and points to focus on for policymakers, company owners, and managers who wish to streamline the preventive measures against unethical practices in business.

Our results revealed that the Construction sector is particularly permeated by unethical practices in business. In addition, construction companies are heavily criticized in mass media due to non-payments to suppliers, non-compliance with contracts, and related abuse of their strong position in the market. Given the risks associated with the increased occurrence of unethical practices, this study implies a need for substantially increased attention from the regulatory authorities in this area, especially concerning the relationships of developers towards their clients, competitors, and business partners. To some extent, these implications apply to the financial sector as well. A closer look at the mean scores of the five company stakeholders in the Finance sector indicates that the occurrence of unethical practices with respect to business partners, customers, and competitors is higher than in respect to employees and society. Thus, it is required that future regulatory measures pay attention especially to the relationship of financial companies with these three stakeholders. However, it is not enough to translate this requirement into a series of measures enforced by external regulatory authorities. For a prompt improvement in practice, the measures must be reflected first and foremost in the internal ethics and compliance programs of financial companies. Therefore, we would recommend that financial companies scrutinize critically their ethics programs and revise those parts that regulate relationships with their business partners, customers, and competitors.

Another finding regards the role of professional networks in improving ethical standards in the business. According to results, member companies are substantially less exposed to unethical practices. This study calls for recognition of the essential role professional networks play in ethical development in the entrepreneurial environment and points to the significance of networking and community building in business. Professional networks can serve their member companies as buffers, protecting them from the negative impact of unethical business practices. Creating communities of companies with a similar pro-social mindset has great potential and can serve as a powerful driving force of progress in business ethics.

Furthermore, our study shows that there are no particular differences in the occurrence of unethical practices between public and private companies. However, at present, especially media and NGOs pay attention primarily to the functioning of public organizations in Slovakia. Compared to private companies, their public counterparts are more under scrutiny, and several initiatives are being developed to raise transparency in this field (e.g., the publicly available Register of Partners of the Public Sector, and the Central Register of Contracts, where state authorities and public organizations are required to publish all contracts). Our findings suggest that, besides attention brought to the better regulation of the public organizations, some of these measures could be mirrored in the private sector, as these companies face similar problems connected with unethicality in business. In order to raise the transparency and accountability of public and private organizations, attention should be paid to both sectors simultaneously, and initiatives that will contribute to deepening the prevention of unethical conduct should be developed in both fields.

In addition, this study contributes to the emerging debate on the effects of the company life cycle on the ethical outlook that changes along with the gradual transition from a young start-up to a well-establish mature company. The variance based on company age shows that young companies are the most vulnerable to unethical practices in business, whilst the companies surviving in the market for more than 30 years are the least exposed in this respect. This trend is especially visible in medium-sized and large companies. The swift growth in the number of employees in the early stages of company development is associated with the need to institutionalize ethics in the workplace, which relates to an improved response of companies to various ethical challenges. Given that, this study calls for greater protection and institutional support, specifically for early-stage firms. One solution could be to promote the sharing of best practices through an institutionally supported platform allowing for the exchange of ideas between young and senior firms. If a company has been exposed to a hostile business environment and manages to survive, the lessons learned can be passed over to early-stage companies. Such a platform may prevent these early businesses from adopting an unethical modus operandi as something normal or even necessary for survival in the market.

6. Conclusions

This study attempted to contribute to the current discourse on ethical issues in business in several ways. The main research question that this study posited was whether certain types of organizations are considerably more exposed to unethical practices than others are. We drew on the new institutionalism as a useful theoretical lens for framing our research of unethical practices in different organizational “fields”. Four types of organizational fields were examined in this respect, namely the industry sector (with a focus on Finance and Construction), company membership in professional networks, company ownership (public/private), and company age. In building the individual hypotheses, prior works of authors who investigated ethical issues in certain types of companies were leveraged. Although the extant research was predominantly Western-based, we regarded it as a useful starting point, since in the literature on business ethics in the CEE block, these factors were not systematically examined.

This study demonstrated that there are some major differences between companies in their exposure to unethical practices in business. Results suggested that, in general, the industry sector, membership in professional networks, and company age were associated with significant variance in the perceived incidence of unethical practices, whereas the company ownership (public/private) was rather isomorphic in this respect. Some of the results were quite unexpected. For instance, the Finance sector, which has a long-standing unflattering reputation as an ethically questionable sector, did not show a significantly higher occurrence of unethical practices compared to other sectors, while the companies in the Construction sector proved to be burdened by unprincipled conduct significantly more than the other companies in the sample. Interestingly, our results pointed out that the professional networks could be conceptualized as protective umbrellas against the unprincipled business practice because, compared with companies that were not affiliated with any professional association, member companies reported a consistently lower occurrence of unethical practices in the business environment. Furthermore, contrary to prior findings, public vs. private ownership did not prove to play any differentiating role, and both sectors reported similar levels of incidence of unethical practices in business. As for company age, our results showed that particular attention should be paid to young companies, especially when the company grows in size rapidly in the early stage of its development.

We believe that these findings might be useful for understanding business ethics issues in the wider context of the CEE region. Although the research was conducted in Slovakia, given their common communist past and comparable peripeties with the transition process, it is likely that CEE countries share similar ethical problems and face comparable difficulties in the current business environment. Furthermore, the daily reality of unethical business practices in the CEE region is still a somewhat understudied phenomenon. This study utilized an empirical approach and drew on the experience of respondents from the corporate practice, delving into the real, perceived problems of companies in terms of business ethics. Finally, we believe that another contribution of this study lies in its scope. Unlike other quantitative surveys that pinpoint the problematic way of doing business in the CEE post-transitional societies, this study surpassed the otherwise usual narrow focus on corruption and examined a relatively large number of 26 unethical practices on a large sample of respondents from 1295 individual companies. To our understanding, the given sample size and the scope of the investigated unethical practices are exceptional, at least in the business ethics literature. This allowed for drawing reasonable conclusions and setting grounds for future comparative studies across countries.

Limitations and Future Research

Despite the contributions of this study, some limitations need to be acknowledged. As outlined in the theoretical section of this paper, the domain of unethical business practices is multifaceted, including a multitude of interconnected phenomena. Thus, the scale regarding unethical business practices is not all-inclusive, and the list of 26 researched items does not cover all unethical practices in their vast diversity. On the other hand, it should be noted that the given list of unethical practices was created on the basis of extensive qualitative preliminary research and, as such, reflects relatively faithfully the current problems in the business environment in Slovakia. As inadequate research was dedicated to the development of valid scales for unethical practices, more studies are required in this respect. Our study can be considered one of the first attempts to examine the unethical business practices in a deeper and more comprehensive manner. We believe that, after careful validation, the respective research instrument could be utilized in different settings, at least in post-transitional societies, which are believed to cope with similar problems in business ethics.

Furthermore, the exploratory factor analysis in the phase of preliminary data analysis retained four factors instead of the expected five. Three factors perfectly matched the hypothesized groups of unethical practices with respect to employees, the state/society, and business partners, whilst the stakeholder groups of customers and competitors were grouped into a single factor. Although multicollinearity was not an issue in our research instrument, the hypothesized distinction of the items in these two groups should be considered with caution, and further research is needed to establish the nomological validity of the given scale.

The data collection procedure may have resulted in some biased information in the final dataset because gathering truthful answers to ethics-related questions is quite challenging. To cope with the issues of social desirability bias and the attitude–behavior gap, we did not ask respondents to evaluate their own personal attitudes or behaviors but to assess their lived experience with the examined unethical business practices. However, despite this methodological approach, there is still another source of bias that could potentially influence our data. In particular, the sample composition was skewed in favor of the managerial staff, mainly company owners and top-level managers. This may have influenced the data because previous research implies that the management level in the corporate hierarchy might influence respondents’ ethical perceptions [99,100]. From another point of view, the fact that approximately one quarter of the respondents did not have a managerial role can also be understood as a limitation. Nonetheless, since the research focused on the assessment of the daily business reality in terms of its ethicality, we believe that the inclusion of non-managerial employees is acceptable as these employees often have a close connection with the daily reality of business.

This study focused on the significant differences in occurrence of unethical business practices, and thus, the conducted statistical analysis was not predictive in nature. We consider this approach to be meaningful, because so far there has been a lack of substantial information on the subject area regarding the occurrence of unethical business practices with relevance to the region of Central and Eastern Europe. Furthermore, it is acknowledged that the data analysis could be more thorough if it included more control variables than only the company size and the regional location. These were chosen because the sample was stratified based on these two company characteristics. Future research could make use of more sophisticated statistical procedures to specify other potentially intervening variables on individual and organizational levels of analysis.

Finally, regarding the ethical quality of the business, we acknowledge that this environment is complex and is populated by, in addition to businesses, diverse social groups and institutions (e.g., state administration, NGOs, and higher education institutions). This study predominantly examined the viewpoint of companies. Further research should include different perspectives in order to understand the intricate processes and relations among various actors in the business environment.

Author Contributions

Conceptualization, A.L. and A.R.; methodology, A.L. and A.R.; validation, A.L., A.R. and Ľ.B.; formal analysis, A.L.; investigation, A.L., A.R. and Ľ.B.; data curation, A.L.; writing—original draft preparation, A.L.; writing—review and editing, A.L.; visualization, A.L.; supervision, A.R.; project administration, A.R.; funding acquisition, A.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the SLOVAK RESEARCH AND DEVELOPMENT AGENCY, contract no. APVV-16-0091.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures and Tables

Figure 1. Industry sectors and unethical business practices.

Figure 2. Membership in professional networks and unethical business practices.

Figure 3. Company ownership and unethical business practices.

Figure 4. Company age and unethical business practices.

Table 1

Differences in exposure to unethical business practices (UBPs) based on industry sectors (with a focus on Construction and Finance sectors vs. Other sectors, respectively).

Construction vs. Other Sectors	UBP Total	UBP Bus. Partners	UBP Customers	UBP Competitors	UBP Employees	UBP State/Society
Mann–Whitney U	62,637.500	57,175.000	61,306.500	59,920.500	69,276.000	69,351.000
Wilcoxon W	747,672.500	742,210.000	746,341.500	744,955.500	754,311.000	754,386.000
Z	−2.639	−4.020	−2.994	−3.332	−0.970	−0.952
Asymp. Sig.	0.008	0.000	0.003	0.001	0.332	0.341
Finance vs. Other sectors	UBP Total	UBP Bus. Partners	UBP Customers	UBP Competitors	UBP Employees	UBP State/Society
Mann–Whitney U	26,647.500	28,042.000	26,365.500	26,638.000	24,825.000	27,720.500
Wilcoxon W	808,522.500	29,077.000	808,240.500	808,513.000	806,700.000	809,595.500
Z	−0.599	−0.034	−0.719	−0.605	−1.341	−0.165
Asymp. Sig.	0.549	0.973	0.472	0.545	0.180	0.869

Mann–Whitney Test; Grouping Variables: Construction/Finance.

Table 2

Differences in exposure to UBPs based on company membership in professional networks.

	UBP Total	UBP Bus. Partners	UBP Customers	UBP Competitors	UBP Employees	UBPState/Society
Mann–Whitney U	137,960.000	147,332.500	138,932.500	136,398.500	142,924.000	142,776.500
Wilcoxon W	266,231.000	275,603.500	267,203.500	264,669.500	271,195.000	271,047.500
Z	−5.093	−3.454	−4.957	−5.382	−4.228	−4.258
Asymp. Sig.	0.000	0.001	0.000	0.000	0.000	0.000

Mann–Whitney Test; Grouping Variable: Membership in professional networks.

Table 3

Differences in exposure to UBPs based on company ownership.

	UBP Total	UBP Bus. Partners	UBP Customers	UBP Competitors	UBP Employees	UBPState/Society
Mann–Whitney U	50,605.000	45,569.500	48,917.000	47,055.500	48,436.000	51,108.500
Wilcoxon W	54,700.000	49,664.500	713,045.000	51,150.500	712,564.000	55,203.500
Z	−0.377	−1.917	−0.898	−1.464	−1.040	−0.224
Asymp. Sig.	0.706	0.055	0.369	0.143	0.298	0.823

Mann–Whitney Test; Grouping Variable: Ownership (Public/Private).

Table 4

Differences in exposure to UBPs based on company age.

	UBP Total	UBP Bus. Partners	UBP Customers	UBP Competitors	UBP Employees	UBPState/Society
Chi-Square	20.970	12.721	13.678	21.535	20.558	14.301
Asymp. Sig.	0.001	0.026	0.018	0.001	0.001	0.014

Kruskal–Wallis Test; Grouping Variable: Company Age.

Table 5

Differences in exposure to UBPs based on company age layered by company size.

		UBP Total	UBP Bus. Partners	UBP Customers	UBP Competitors	UBP Employees	UBPState/Society
Micro	Chi-Square	4.193	2.165	2.373	10.202	3.423	4.623
	Asymp. Sig.	0.522	0.826	0.795	0.070	0.635	0.464
Small	Chi-Square	3.017	0.934	7.004	3.856	6.283	3.675
	Asymp. Sig.	0.697	0.968	0.220	0.570	0.280	0.597
Medium	Chi-Square	11.111	3.447	3.664	7.168	7.702	7.131
	Asymp. Sig.	0.049	0.631	0.599	0.208	0.173	0.211
Large	Chi-Square	16.010	6.451	14.707	10.617	14.902	15.363
	Asymp. Sig.	0.007	0.265	0.012	0.060	0.011	0.009

Kruskal–Wallis Test; Grouping Variable: Company Age.

Appendix A

Table A1

Reliability analysis for the 26 unethical business practices (UBPs).

Cronbach’s Alpha		Cronbach’s Alpha Based on Standardized Items			N of Items
0.966		0.965			26
	Mean	Min.	Max.	Range	Max/Min	Variance
Item Means	3.082	2.429	3.951	1.521	1.626	0.183
Reliability analysis for the 26 UBPs (individual items)
	Scale Mean if Item Deleted	Scale Variance if Item Deleted	Corrected Item-Total Correlation	Squared Multiple Correlation	Cronbach’s Alpha if Item Deleted
UBPbuspart1_Non-payment	76.17	709.136	0.458	0.583	0.966
UBPbuspart2_Non-compliance with contracts	76.42	703.445	0.529	0.631	0.966
UBPbuspart3_Corrupt behavior of business partner	77.01	695.438	0.616	0.551	0.965
UBPbuspart4_Abuse of the position of large companies against the small comp.	76.33	700.412	0.596	0.564	0.965
UBPbuspart5_Nepotism in the business environment	76.54	701.817	0.566	0.478	0.965
UBPbuspart6_Purposeful bankruptcy	77.20	692.308	0.645	0.534	0.965
UBPcust1_Sale of poor-quality products or services	76.87	685.817	0.737	0.768	0.964
UBPcust2_Avoiding liability for complaints and errors	76.78	687.618	0.724	0.754	0.964
UBPcust3_Misleading advertising, deception	76.69	684.361	0.741	0.752	0.964
UBPcompet1_Abuse of a strong market position, cartel agreements	76.53	691.042	0.702	0.678	0.964
UBPcompet2_Unfair procurement practices	76.60	687.453	0.742	0.702	0.964
UBPcompet3_Patent abuse, theft of ideas/brands	77.20	691.947	0.712	0.651	0.964
UBPcompet4_Purposeful damaging of competitors’ reputation	77.00	688.280	0.737	0.668	0.964
UBPempl1_Employee discrimination	77.48	690.840	0.708	0.638	0.964
UBPempl2_Unlawful wage-paying practices	77.36	680.467	0.762	0.734	0.964
UBPempl3_Failure to comply with employee levies-related obligations	77.64	680.422	0.782	0.773	0.964
UBPempl4_Failure to respect employees’ privacy at the workplace	77.57	693.657	0.649	0.616	0.965
UBPempl5_Unethical behavior towards employees (indecent, unfair, arrogant)	77.37	686.591	0.724	0.740	0.964
UBPempl6_Bad work conditions	77.56	687.656	0.736	0.750	0.964
UBPempl7_Persecution of whistle-blowers	77.69	688.339	0.747	0.707	0.964
UBPstate1_Failure to comply with applicable laws	77.26	680.529	0.792	0.773	0.964
UBPstate2_Non-payment of taxes, tax fraud	77.34	676.111	0.803	0.823	0.963
UBPstate3_Corruption of civil servants	77.22	677.277	0.807	0.844	0.963
UBPstate4_Misuse of contacts with politicians and officials	76.99	678.193	0.790	0.856	0.964
UBPstate5_Unfair practices in obtaining public contracts, public/euro funds	76.99	676.824	0.790	0.852	0.964
UBPstate6_Environmental damages	77.21	683.078	0.768	0.719	0.964

Table A2

Reliability analysis for the 26 UBPs.

Variables	Cronbach’s Alpha	N of Items
UBP Business partners (UBPbuspart)	0.867	6
UBP Customers (UBPcust)	0.929	3
UBP Competitors (UBPcompet)	0.900	4
UBP Employees (UBPempl)	0.942	7
UBP State/society (UBPstate)	0.959	6

Table A3

Factor analysis (Extraction method: principal component analysis, rotation method: Varimax with Kaiser normalization).

Component	Initial Eigenvalues			Extraction Sums of Squared Loadings			Rotation Sums of Squared Loadings
	Total	% of Var.	Cumul. %	Total	% of Var.	Cumul. %	Total	% of Var.	Cumul. %
1	14.101	54.235	54.235	14.101	54.235	54.235	5.351	20.580	20.580
2	2.482	9.546	63.781	2.482	9.546	63.781	5.219	20.072	40.652
3	1.295	4.980	68.761	1.295	4.980	68.761	5.063	19.471	60.124
4	1.204	4.629	73.390	1.204	4.629	73.390	3.449	13.266	73.390
	...	...	...
26	0.088	0.340	100.000

Figure A1. Factor analysis—Scree plot and Component plot.

Table A4

Factor analysis (rotated component matrix).

	Rotated Component Matrix
	1	2	3	4
UBPbuspart1_Non-payment	0.99	0.80	0.127	0.842
UBPbuspart2_Non-compliance with contracts	0.138	0.189	0.120	0.826
UBPbuspart3_Corrupt behavior of business partner	0.179	0.358	0.205	0.641
UBPbuspart4_Abuse of the position of large comp. against small	0.109	0.494	0.141	0.584
UBPbuspart5_Nepotism in the business environment	0.279	0.441	0.32	0.496
UBPbuspart6_Purposeful bankruptcy	0.158	0.405	0.292	0.561
UBPcust1_Sale of poor-quality products or services	0.319	0.748	0.213	0.195
UBPcust2_Avoiding liability for complaints and errors	0.316	0.757	0.190	0.187
UBPcust3_Misleading advertising, deception	0.281	0.789	0.233	0.175
UBPcompet1_Abuse of a strong market position, cartel agreements	0.123	0.706	0.317	0.298
UBPcompet2_Unfair procurement practices	0.131	0.654	0.429	0.305
UBPcompet3_Patent abuse, theft of ideas/brands	0.249	0.660	0.303	0.234
UBPcompet4_Purposeful damaging of competitors’ reputation	0.289	0.667	0.297	0.240
UBPempl1_Employee discrimination	0.744	0.303	0.207	0.169
UBPempl2_Unlawful wage-paying practices	0.663	0.217	0.449	0.204
UBPempl3_Failure to comply with employee levies-related obligations	0.687	0.230	0.458	0.190
UBPempl4_Failure to respect employees’ privacy at the workplace	0.801	0.177	0.205	0.124
UBPempl5_Unethical behavior towards employees (indecent, unfair)	0.813	0.249	0.253	0.126
UBPempl6_Bad work conditions	0.780	0.211	0.344	0.132
UBPempl7_Persecution of whistle-blowers	0.704	0.266	0.388	0.128
UBPstate1_Failure to comply with applicable laws	0.445	0.273	0.678	0.189
UBPstate2_Non-payment of taxes, tax fraud	0.436	0.228	0.745	0.199
UBPstate3_Corruption of civil servants	0.345	0.295	0.799	0.169
UBPstate4_Misuse of contacts with politicians and officials	0.323	0.290	0.801	0.163
UBPstate5_Unfair practices in obtaining public contracts, euro funds	0.286	0.318	0.813	0.158
UBPstate6_Environmental damages	0.390	0.292	0.706	0.141

Table A5

Tests of normality.

	Kolmogorov–Smirnov a			Shapiro–Wilk
	Statistic	df	Sig.	Statistic	df	Sig.
UBP Total	0.45	1295	0.00	0.977	1295	0.00
UBP Bus. Partners	0.83	1295	0.00	0.956	1295	0.00
UBP Customers	0.151	1295	0.00	0.905	1295	0.00
UBP Competitors	0.103	1295	0.00	0.941	1295	0.00
UBP Employees	0.112	1295	0.00	0.932	1295	0.00
UBP State/Society	0.109	1295	0.00	0.913	1295	0.00

a. Lilliefors Significance Correction.

Table A6

Sample demographics.

		N	%
Gender	Male	695	53.7
	Female	600	46.3
Age	Up to 30 years	121	9.3
	31–40 years	298	23.0
	41–50 years	394	30.4
	51–60 years	339	26.2
	More than 60 years	143	11.0
Field of study	Economics/Management	610	47.1
	Law	70	5.4
	Natural Sciences	49	3.8
	Social Sciences	113	8.7
	Technical	371	28.6
	Other	82	6.3
Level of education	Primary education	4	0.3
	Secondary education	224	17.3
	Bachelor	113	8.7
	Master	813	62.8
	Ph.D.	141	10.9
Position	Company owner/Director	537	41.5
	Top manager	320	24.7
	Manager	66	5.1
	Ethics & Compliance manager	19	1.5
	Internal lawyer	11	0.8
	Internal auditor	10	0.8
	Ethics officer	5	0.4
	Other	327	25.3
Seniority	Less than 1 year	84	6.5
	1–3 year	220	17.0
	4–10 years	379	29.3
	More than 10 years	612	47.3

Table A7

Descriptive statistics for the four grouping variables.

	N Stat.	Range	Min.	Max.	Mean	Std.Dev.	Skewness	Kurtosis
Industry Sector	1295	9	1	10	5.48	3.141	0.286	−1.448
Membership in PNs	1166	1	0	1	0.43	0.496	0.267	−1.932
Ownership	1242	1	1	2	1.07	0.259	3.302	8.919
Company Age	1295	5	1	6	4.06	1.381	−0.298	−1.072

Note: Industry Sector, nominal, 10 categories (acc. To NACE), coded 1–10. Membership in professional networks (PNs), dummy coded 0 = No, 1 = Yes. Ownership, dummy coded 1 = Private, 2 = Public. Company age, nominal, six categories from less (1) to more matured (6).

Table A8

Frequencies for the four grouping variables.

		N	%
Industry Sector	Agriculture, Forestry and Fishing	67	5.2
	Manufacturing, Mining and Quarrying and other industries	235	18.1
	Construction	125	9.7
	Wholesale Trade, Retail Trade, Transportation and Warehousing, Accommodation and Food Services	251	19.4
	Information and Communication	87	6.7
	Finance and Insurance	45	3.5
	Real Estate-related activities	22	1.7
	Professional, Scientific, Technical, Administrative and Support Services	112	8.6
	Public Administration, Defense, Education, Healthcare and Social Assistance	88	6.8
	Other Services	263	20.3
Membership in PNs	Non-member	660	51.0
	Member	506	39.1
	N/A (missing)	129	10.
Ownership	Private	1152	89.0
	Public	90	6.9
	N/A (missing)	53	4.1
Company Age	0–3 years	23	1.8
	4–10 years	204	15.8
	11–15 years	255	19.7
	16–20 years	191	14.7
	21–30 years	431	33.3
	30+ years	191	14.7

Table A9

Descriptive statistics for the test variables.

	Mean	Std.Dev.	Variance	Skewness	Kurtosis
UBP Total (composite, all items)	3.08	1.049	1.100	−0.22	−0.908
UBP Business partners (total, 6 items)	3.51	1.062	1.128	−0.386	−0.721
UBP Customers (total, 3 items)	3.34	1.353	1.830	−0.353	−1.171
UBP Competitors (total, 4 items)	3.29	1.200	1.441	−0.410	−0.806
UBP Employees (total, 7 items)	2.60	1.232	1.517	0.344	−1.013
UBP State/society (total, 6 items)	2.95	1.382	1.910	−0.63	−1.357
UBPbuspart1_Non-payment	3.95	1.339	1.794	−0.903	−0.711
UBPbuspart2_Non-compliance with contracts	3.70	1.365	1.863	−0.568	−1.187
UBPbuspart3_Corrupt behavior of business partner	3.11	1.421	2.018	0.08	−1.371
UBPbuspart4_Abuse of the position of large comp. against small	3.79	1.313	1.724	−0.817	−0.599
UBPbuspart5_Nepotism in the business environment	3.58	1.333	1.777	−0.543	−0.969
UBPbuspart6_Purposeful bankruptcy	2.92	1.449	2.100	0.126	−1.303
UBPcust1_Sale of poor-quality products or services	3.25	1.443	2.082	−0.200	−1.397
UBPcust2_Avoiding liability for complaints and errors	3.34	1.420	2.016	−0.359	−1.278
UBPcust3_Misleading advertising, deception	3.43	1.472	2.166	−0.423	−1.292
UBPcompet1_Abuse of a strong market position, cartel agreements	3.59	1.372	1.882	−0.630	−0.884
UBPcompet2_Unfair procurement practices	3.52	1.393	1.940	−0.514	−1.012
UBPcompet3_Patent abuse, theft of ideas/brands	2.92	1.331	1.771	0.69	−1.047
UBPcompet4_Purposeful damaging of competitors’ reputation	3.12	1.380	1.906	−0.139	−1.219
UBPempl1_Employee discrimination	2.64	1.366	1.866	0.389	−1.093
UBPempl2_Unlawful wage-paying practices	2.76	1.530	2.339	0.176	−1.496
UBPempl3_Failure to comply with employee levies-related obligations	2.48	1.494	2.231	0.493	−1.241
UBPempl4_Failure to respect employees’ privacy at the workplace	2.55	1.403	1.968	0.421	−1.162
UBPempl5_Unethical behavior towards employees (indecent, unfair, arrogant)	2.75	1.448	2.096	0.227	−1.352
UBPempl6_Bad work conditions	2.56	1.398	1.956	0.446	−1.122
UBPempl7_Persecution of whistle-blowers	2.43	1.362	1.854	0.483	−0.954
UBPstate1_Failure to comply with appl. Laws	2.86	1.474	2.172	0.125	−1.414
UBPstate2_Non-payment of taxes, tax fraud	2.78	1.558	2.428	0.159	−1.520
UBPstate3_Corruption of civil servants	2.90	1.523	2.318	0.24	−1.465
UBPstate4_Misuse of contacts with politicians and officials	3.13	1.532	2.346	−0.221	−1.438
UBPstate5_Unfair practices in obtaining public contracts, public/euro funds	3.13	1.564	2.448	−0.203	−1.478
UBPstate6_Environmental damages	2.91	1.454	2.114	0.44	−1.349

Note: Mean values for UBPs measured on 5-point scale (with 5 indicating a very high level of perceived occurrence of unethical business practices).

Table A10

Correlations matrix (Kendall’s tau_b).

	UBP Total	1	2	3	4	5	6	7	8	9
1. UBP Bus. Partners	0.601 **
2. UBP Customers	0.642 **	0.483 **
3. UBP Competitors	0.689 **	0.539 **	0.593 **
4. UBP Employees	0.708 **	0.384 **	0.476 **	0.480 **
5. UBP State/Society	0.742 **	0.420 **	0.496 **	0.550 **	0.623 **
6. Industry Sector	0.046 *	0.14	0.074 **	0.052 *	0.31	0.044 *
7. Membership in PNs	−0.122 **	−0.085 **	−0.124 **	−0.133 **	−0.104 **	−0.105 **	−0.13
8. Ownership	−0.09	−0.46	0.22	−0.35	0.25	−0.05	0.171 **	0.088 **
9. Company Age	−0.065 **	−0.048 *	−0.057 **	−0.047 *	−0.067 **	−0.053 *	−0.072 **	0.245 **	0.225 **

**. Correlation is significant at the 0.001 level (2-tailed); *. Correlation is significant at the 0.05 level (2-tailed).

Table A11

Comparison of mean values of UBPs based on the examined company variables.

Variables		UBPBus.Partners	UBPCustomers	UBPCompetitors	UBPEmployees	UBPState/Society	UBP Total
Industry Sector	Construction	3.8600	3.7067	3.6100	2.6720	3.0653	3.3006
	Finance	3.5074	3.4815	3.3722	2.8381	2.9815	3.1821
Membership in PNs	Yes	3.3989	3.1423	3.1210	2.3995	2.7701	2.9124
	No	3.6098	3.5247	3.4788	2.7212	3.1220	3.2280
Ownership	Private	3.5326	3.3377	3.3118	2.5941	2.9656	3.0926
	Public	3.2981	3.4741	3.1528	2.7206	2.9333	3.0564
Company Age	0–3 years	3.7101	3.9565	3.7174	3.5031	3.5507	3.6472
	4–10 years	3.5866	3.4673	3.3480	2.6905	3.0523	3.1716
	11–15 years	3.4928	3.3399	3.2265	2.6168	2.9144	3.0649
	16–20 years	3.5340	3.3106	3.3534	2.6986	3.0812	3.1510
	21–30 years	3.5677	3.3766	3.3898	2.5326	2.9606	3.0995
	30+ years	3.2696	3.0663	2.9673	2.4009	2.6789	2.8294

Note: Abbrev. PNs—professional networks. Mean values for UBPs measured on a 5-point scale (with 5 indicating a very high level of perceived occurrence of unethical business practices).

Table A12

Comparison of mean values of UBPs based on company age layered by company size.

Comp. Size	Company Age	UBPBus.Partners	UBPCustomers	UBPCompetitors	UBPEmployees	UBPState/Society	UBP Total
Micro	0–3 years	3.9556	4.0222	3.8667	3.6286	3.4556	3.7462
	4–10 years	3.6445	3.6077	3.5177	2.7788	3.2507	3.2968
	11–15 years	3.6767	3.7028	3.5090	2.8279	3.1044	3.2933
	16–20 years	3.8661	3.6831	3.7090	2.9930	3.5191	3.5057
	21–30 years	3.6048	3.6381	3.6357	2.5571	3.2333	3.2456
	30+ years	3.8889	3.2222	3.8333	3.0000	2.6667	3.2821
Small	0–3 years	3.8333	4.3333	4.7500	2.2857	4.3333	3.7308
	4–10 years	3.4689	3.2881	3.1059	2.5351	2.7401	2.9726
	11–15 years	3.7207	3.3198	3.4966	2.6911	3.2185	3.2469
	16–20 years	3.5222	3.2556	3.3667	2.5619	3.0083	3.0904
	21–30 years	3.5847	3.3825	3.4631	2.4489	2.9208	3.0836
	30+ years	3.6944	3.3704	3.1875	2.2698	2.7407	2.9754
Medium	0–3 years	2.8333	3.8889	3.0833	4.0476	4.2778	3.6538
	4–10 years	3.5833	3.4583	3.2500	2.6786	2.8958	3.1154
	11–15 years	3.5058	3.3158	3.1667	2.6566	2.8889	3.0607
	16–20 years	3.4667	3.3167	3.2563	2.8179	3.0708	3.1510
	21–30 years	3.6059	3.3240	3.2897	2.6048	2.9361	3.1006
	30+ years	3.1111	3.0212	2.9603	2.4331	2.5608	2.7680
Large	0–3 years	3.4167	3.6667	3.3750	2.9286	3.1667	3.2500
	4–10 years	3.6458	2.8333	3.0313	2.6250	3.0208	3.0385
	11–15 years	2.6911	2.6748	2.2500	2.0000	2.0163	2.2795
	16–20 years	2.9722	2.6556	2.7333	2.2143	2.3500	2.5513
	21–30 years	3.4296	3.1831	3.1092	2.6157	2.8310	2.9946
	30+ years	3.1891	2.9700	2.8539	2.4109	2.7378	2.7986

Note: Mean values for UBPs measured on a 5-point scale (with 5 indicating a very high level of perceived occurrence of unethical business practices).

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