Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6, 2168-2188 2024 Publisher: Learning Gate DOI: 10.55214/25768484.v8i6.2410 © 2024 by the authors; licensee Learning Gate © 2024 by the authors; licensee Learning Gate * Correspondence: elafi.reda@gmail.com The impact of the entrepreneur’s profile on the entrepreneurial failure of Moroccan very small business Reda Elafi1*, Youssef Jouali2, Aumaima Wahbi3 1Research Laboratory in Economic Competitiveness and Managerial Performance, Faculty of Legal, Economic and Social Sciences Souissi, Mohammed V University, Rabat, Morocco; elafi.reda@gmail.com (R.E.) 2Moroccan School of Engineering Sciences, EMSI, Rabat, Morocco; y.jouali@emsi.ma (Y.J.) 3Laboratory of Research in Management of Organizations, Business Law, and Sustainable Development; Faculty of Legal, Economic, and Social Sciences- Souissi Mohammed V University, Rabat, Morocco; aumaima.wahbi@um5r.ac.ma (A.W.). Abstract: This article addresses a crucial and timely question: What are the critical factors in the entrepreneur’s profile that contribute to the failure of small Moroccan companies? To answer this question, this study seeks to meticulously analyze the failed entrepreneur's profile characteristics, drawing upon a myriad of previous academic studies. The present study study is based on data from a 2022 survey, which achieved a response rate of approximately 40%. The study utilizes a logistic regression model to test our hypothesis. Of significant importance are the findings of this study which reveal that an entrepreneur is more likely to witness company failure if he is a man under 35, driven by the need for income, and has established a SARL business1. Keywords: Entrepreneur profile, Entrepreneurial failure, Failed companies, Logistic regression, Very small business. 1. Introduction The state of affairs in Morocco is alarming. According to the latest data from Inforisk, staggering 8,080 companies have already succumbed to failure by January 1, 2022. This alarming trend underscores the urgent need for research into the factors contributing to business failure, particularly in the context of very small businesses (henceforth VSBs) in Morocco. This study aims to shed light on this pressing issue, providing valuable insights for researchers and policymakers in the economic domain. The growth of VSBs is considered as a driving force behind job creation and wealth generation. For several decades, it has become a strategic element in developing national economies and a focal point of debate. Developed countries have particularly shown interest in VSBs due to their significant contribution to economic growth. However, several factors can lead to the failure of VSBs, especially when considering the increased demands for quality and competitiveness of exports in a liberal economy affected by the international economic crisis. According to Chandler and Jansen (1992), the entrepreneur is often closely associated with the success or failure of VSBs. The fate of these businesses depends mainly on their leaders, often seen as "orchestra-men" (Ferrier, 2002) managing the company single-handedly. The characteristics of the entrepreneur can moderate both internal and external factors influencing the organization. Explaining entrepreneurial failures in terms of entrepreneurial error rather than lousy luck has attracted the attention of several researchers, such as Cardon, Stevens, and Potter (2003). Shiyuti, Zainol, and Ishak (2021) highlight the crucial role of entrepreneurs in innovation and resilience after failure. Jackson (2021) examines leadership strategies for overcoming SME failure. The literature highlights the need for more consensus on defining failure concepts and understanding these dynamics to improve SME survival. By the same token, Schumpeter (1934) argues that entrepreneurs' traits play a decisive role in understanding the failure of the companies they create. This perspective is widely supported in 2169 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2168-2188, 2024 DOI: 10.55214/25768484.v8i6.2410 © 2024 by the authors; licensee Learning Gate literature reviews. These findings motivated the choice of topic for this article, which aims to identify the factors that explain entrepreneurial failure and lead these economic units into critical situations. Before delving into data analysis, it is essential to define the concept of "entrepreneurial failure" to set the boundaries of this study, which poses the following question: What constitutes a failing company? Despite its apparent simplicity, this concept remains controversial among academics. Although this debate is ongoing, there is a consensus on the need for multidimensional approaches to address company failure's broad and complex nature effectively. Still, it is worth noting that public authorities have a growing demand to establish an effective system to support Moroccan small businesses (TPEs) in overcoming their temporary or chronic difficulties. Moreover, the mission of public authorities to highlight a policy for creating sustainable and viable businesses relies not only on the establishment of support organizations, which are an essential phase for any new business (Sammut, 2003a) but also on the quality of the entrepreneur. There are relatively few studies on Moroccan entrepreneurship that address the issue of failed VSBs1. Despite the importance and scope of existing research, little has been said about this specific issue. Therefore, further research is needed to enrich and complement the current literature, notably by proposing new ways to examine this phenomenon. Hence, this study adopts an approach that emphasizes the factors contributing to entrepreneurial failure. Additionally, this research aims to advance the studies conducted on the failure of VSBs. Hence, this study seeks to answer the following research question: • What are the entrepreneurial factors influencing VSBs' failure in Morocco? The prime objective of the present study is to understand the phenomenon of VSB failure, focusing mainly on the characteristics of the entrepreneur. Accordingly, this article aims to answer the following questions: • How do we set the practical foundations for a predictive model combining factors relating to the entrepreneur’s characteristics? • What theoretical approaches can be adopt to analyze the failed VSBs? This article is divided into three sections. The first section discusses the framework of this research, defining the various concepts related to the notion of failure, including failure and the factors associated with the entrepreneur. The second section presents the empirical methodology adopted. Section three displays analysis of the determinants of a "failing company" and the results obtained from econometric modeling. The following section is devoted to the literature review. 2. Literature Review Of paramount importance is the issue of failure. Such a concept puts researchers in a dilemma. On the one hand, there is a weak theoretical foundation. On the other hand, there is an absence of a theory dedicated to company failure, which might seem to reduce the concept's complexity. For these reasons, this study has embraced a one-dimensional approach to failure before delimiting the notion of failing companies. This section will first adopt a lexical approach, proposing a definition of the failed company and the VSBs. Second, it will adopt a one-dimensional approach to delimit the factors affecting the entrepreneur and formulate our research hypotheses. 2.1. Lexical Approach According to Bygrave and Hofer2 (1991), good science must begin with adequate definitions. What follows is an explanation of the concepts used throughout this work. Based on premises stemming from the literature review exploration, it is noticeable that the simplicity of the concepts, which are the subject of this article, is misleading. It is either the tiny 1kness of their For many authors, this is due to the lack of consensus on the definition of concepts (Headd, 2003), (Bates, 2005) and the wea operationalization (Berryman, 1983), (Rauch et al., 2009). Whether we are talking about performance, success, breakdown or failure, the outcome is the same: there is a lack of lucid definition of these concepts. 2.(Bygrave & Hofer, 1991: 15)“Good science has to Begin with good definitions” 2170 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2168-2188, 2024 DOI: 10.55214/25768484.v8i6.2410 © 2024 by the authors; licensee Learning Gate companies or the failing ones. Within the scientific community, the elucidation of concepts affects research on several levels, either theoretical positioning or methodological choice. What is meant by a failing company? The simplicity in which this question can be asked conceals a polemical debate among researchers. 2.1.1. Very Small Business (VSBs) Recognizable is definition of a VSB based on quantitative criteria (number of employees, turnover, etc.), because they are the most widely used and are essential to tracing the entity’s outline. The qualitative criteria are necessary to identify the organization's characteristics. Combining the two makes it possible to approach what a VSB is. 2.1.2. For the Economist: It is Enough to Draw the Outline Economic criteria are the first to be mentioned intuitively and spontaneously regarding segmenting companies. Empirical definitions based on size remain the rule. Even if this criterion does not necessarily indicate the management methods adopted by this category of companies (Ferrier, 2002). The criteria most commonly used to measure the size of an organization are the number of employees, turnover, capital, and the total balance sheet, the number of employees being the most widely used (Ferrier, 2002). This criterion is simple to use but covers very different realities. The sector of activity or technological intensity creates many differences between companies. With an equal number of employees, comparing companies' information technology with a manufacturing plant would be difficult. In addition, the criterion of the number of employees raises the failure to distinguish between permanent and seasonal employees and even between salaried and non-salaried workers. Indeed, the field shows that the head of a VSB is often surrounded by family members (Marchesnay, 2003). Therefore, this criterion needs to be refined according to several parameters, such as the sector of activity, the market share, the turnover, or the total balance sheet. The quantitative approach has the advantage that the criteria are simple and relatively easy to identify. It is essential for economic analyses (contribution to employment, wealth creation, etc.) and economic policies (e.g., to identify beneficiaries). However, from a management science point of view, quantitative criteria cannot provide information about how an organization operates, especially as crossing thresholds, even when clearly defined, does not necessarily transform the business (Foliard, 2008). Even if the qualitative approach is essential, the quantitative approach is insufficient to understand a population of companies that many consider too diverse and too specific to be categorized according to fixed criteria (Beaver, 2003). 2.1.3. For the Entrepreneur: The Black Box Must be Opened Categorizing a company according to the number of its employees or turnover is a starting point, and indeed essential but not enough. Understanding what a VSB or Small/Medium-sized Business (henceforth SMB) requires what Ferrier (2002: 26) calls a “nested quantitative typology,” i.e., it should be merged with other criteria, this time of a qualitative nature. The qualitative criteria aim to characterize the company from the point of view of the management and organizational modes. This approach is not specific to VSBs or SMBs, because many studies have tried to differentiate companies based on qualitative criteria and have classified them into three sub- approaches: • Ownership of the company: Ownership affects the organizational form and development of the business. A distinction is made between personal companies (controlled by the founders) and family companies (passed on to a family member). • Management strategy or objectives: This uses typologies based on strategy and growth potential, or, still, on the relationship between strategy and the entrepreneur’s interest in independence. • Stage of evolution of the firm: In line with the concept of the firm's life cycle, this view considers that firms are born small and evolve to grow or fall. The complexity of management and the degree of separation between the firm and its owner(s) follow the life cycles. 2171 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2168-2188, 2024 DOI: 10.55214/25768484.v8i6.2410 © 2024 by the authors; licensee Learning Gate When applied to MSB and VSB, the qualitative approach attempts to understand what a VSB is as an organization. It is based on the hypothesis that a small company fundamentally differs from a big one. However, it is necessary to grasp this difference from the available definition (Curran & Blackburn, 2000). In this sense, the most widely used definition is the one proposed by Julien (1990: 422-423) for the SMB: • Small-sized; • Centralized or even customized management; • Low specialization, both at the management level and at the employee level; • An intuitive or slightly formalized strategy; • A simple or slightly organized internal information system; • A simple external information system. Moreover, the Wiltshire Committee (1971: 7) defines a small business as follows: “A business in which one or two persons are required to make all the critical management decisions: finance, accounting, personnel, purchasing, processing or servicing, marketing, selling, without the aid of internal specialists and with specific knowledge in only one or two functional areas.” These definitions apply equally to SMBs and VSBs. The particularity of these two categories lies in the decision-making criterion, whose functions and actions are held in the hands of one or two people. 2.1.4. Failure and Breakdown: Multi-Systemic Concepts The research community agrees that the accumulation of knowledge on company dynamics is minimal (Cochran, 1981; Delmar et al., 2003). According to many authors, this is due to the lack of consensus on the definition of concepts (Headd, 2003), (Bates, 2005) and the weakness of their operationalization (Berryman, 1983) (Rauch et al., 2009). Whether we are talking about performance, success, failure, or breakdown, the conclusion remains the same: a lack of clear definition. Scientists have proven that understanding the failure of VSBs is paramount (Cochain, 1981). This could be explained by the preponderance of this category of companies within emerging and industrialized economies and the weakness of their material and human capacities. Therefore, they are more susceptible to the risk of failure (Julien, 2005). More importantly, Cochain (1981) points out that data are scarce, and there is a lack of reliability regarding the extermination of companies. Similar to concepts such as performance or success, many other concepts refer to failure, such as breakdown, bankruptcy, etc. Watson & Everett (1996) use the terms “exit, death, mortality, and failure” in a similar or even interchangeable way (P. 22). Although there is no agreement on the definition of failure, there is a broad consensus within the research community about its significance. However, some authors distinguish entirely between these different concepts. In this regard, Headd (2003) distinguishes between closure and failure (or breakdown). The former can be voluntary, whereas the latter is involuntary. Most analyses refer to objective criteria such as suspension of payments and deterioration of the financial situation by accumulating losses. On the contrary, other analyses include objective and subjective criteria such as stakeholder dissatisfaction and failure to achieve the entrepreneur’s objectives. In line with this, Bates (2005: 345) distinguishes between successful and unsuccessful closure, stating, "Departure from one’s business venture is not necessarily rooted in failure or even performance that lags behind one’s expectations; departure requires only that a superior alternative has become available to the entrepreneur.” Things are not as simple as we would like them to be. Another approach is that the term failure does not entity refer to the entrepreneur's failure. This may show that behind the scenes of each closed entity, there is a different scenario: success for some or failure for others. In this sense, Crutzen & Van Caillie (2009: 6) put forward the following argument: “The failure of a company is a dynamic phenomenon (…) of varying length. The latter is materialized by the increasing deterioration of the company’s organizational and financial situation and eventually ends in the company’s legal ownership or bankruptcy, a one-off situation 2172 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2168-2188, 2024 DOI: 10.55214/25768484.v8i6.2410 © 2024 by the authors; licensee Learning Gate characterized by the concomitant occurrence of a double solvency and liquidity crises” (Crutzen & Van Caillie, 2009, p. 6). Bankruptcy, therefore, occurs when a company can no longer fulfill its financial obligations, because it has failed to generate the resources necessary to maintain its activity (Thornhill & Amit, 2003). Within the same vein, a company's failure is also perceived as the consequence of its lack of efficiency, i.e., a poor matching between investment and outcome (Smida & Khelil, 2008). For Levy-Tadjine and Paturel (2006, cited in Smida and Khelil, 2008), an inefficient company does not use available resources most profitably. Therefore, this lack of efficiency is the first manifestation of economic failure. Indeed, closure can be voluntary or involuntary; it is deemed voluntary when determined by the will of the stakeholders, particularly in the case of VSB by the entrepreneur. This brings us back to the subjective criteria mentioned in the section on success, which is defended by many authors (Gupta & Govindarajan, 1984) (Cooper & Artz, 1995) (Jennings & Beaver, 1997). Moreover, for a good reason, is it possible to consider a VSB sold with an added value as a failure? Will the owner-entrepreneur who closes his company to set up another or even to seize the opportunity of a gratifying job (not only financially) consider himself to have failed? Nevertheless, the entrepreneur/company homogeneity is significant (Foliard, 2008). To remove any conceptual ambiguities, (Khelil, 2011) suggests a compound definition of failure as table 01 shows: Table 1. A few definitions of failure. Author Adopted definition Zacharakis, Meyer and DeCastro (1999) Bankruptcy and insolvency McGrath (1999) The end of an initiative that failed to achieve its objectives Cannon & Edmondson (2001). Deviation from desired and expected outcome Shepherd (2003) Failure occurs when a fall in income and an increase in expenses are of such magnitude that the company becomes insolvent and unable to attract new equity investment or take on new debt. As a result, it can no longer operate under current ownership and management. Bruno, Mcquarrie and Torgrimson (1992) Failure manifests through suspension of activity, possibly due to various reasons, including legal problems, litigation between partners, death, or a lack of interest in continuing the business. Source: Our synthesis from Singh et al. 2007. “It is a phenomenon that manifests itself when the new company falls into a spiral of economic failure (destruction of resources), and the entrepreneur enters a psychological state of disappointment. Without financial and moral support, the entrepreneur may see his or her company disappear”. This definition's advantage lies in incorporating the dimensions most widely recognized as manifestations of a failing company: the entrepreneur, the company, and the environment. To achieve this, the study will mobilize the factors linked to failure. These factors can be classified into three complementary and interdependent categories (Storey, 1994) (Lasch et al., 2005): the entrepreneur, the company, and the environment. The question that poses itself here is: If the terms associated with a failing company have been explained, what are the characteristics of the entrepreneur that give rise to them? 2.1.5. Factors Related to the Entrepreneur The literature mentions several variables to understand the characteristics of the individual (entrepreneur) that influence his company's failure. These characteristics can be classified into three dimensions: intra-psychic characteristics, human and social capital and technical competencies, and entrepreneurial and social skills3. 3Cited in numerous authors (Carland et al., 1984)(Baum & Locke, 2004)(Rauch, Wiklund, Lumpkin, & Frese, 2009) 2173 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2168-2188, 2024 DOI: 10.55214/25768484.v8i6.2410 © 2024 by the authors; licensee Learning Gate Following the main conclusions drawn from research on failure, we formulate the research hypotheses. Factors about the entrepreneur's profile are to be taken into account.4 • Link between the motivation to create and failure. Failure affects people’s motivation to become entrepreneurs (Shane et al., 2003). This aspect refers to entrepreneurial motivation, one of the factors influencing companies' failure. In this regard, Chu et al. (2007) believe that the greater the entrepreneur’s entrepreneurial motivation, the less likely his or her company is to fail. We formulate the following hypothesis: Hypothesis H1a: The failure of a VSB depends on the entrepreneur’s initial motivation. • Link between gender and failure. The majority of research confirms the significant relationship between gender and failure. However, the problem lies in understanding whether companies started by men are more sustainable than those started by women or vice versa. According to Dahlqvist et al. (2000) and Cliff et al. (2004), the entrepreneur's gender plays a vital and determining role in the success or failure of start-ups, particularly those created by women or ethnic minorities who find it challenging to grow. In their seminal study, Bosma et al. (2004) analyzed 1,000 new companies started up in the Netherlands between 1994 and 1997 and found that female entrepreneurs performed poorly compared to male entrepreneurs. However, Brüderl and Preisendörfer (1998) concluded that companies founded by women were twice as likely to fail as those founded by men. Lasch et al. (2005) point out that companies set up by women do not fail more often than others in terms of survival, but they do perform less frequently in terms of growth (Dahlqvist et al., 2000). In this research, the following hypothesis is formulated to be either confirmed or refuted: Hypothesis H1b: Companies set up by men are more likely to fail than those set up by women. • Link between entrepreneurial age and failure The work of Kraut and Grambsch (1987), Hisrich (1990), Kallerberg and Leicht (1991), Krueger (1993), Rowe et al. (1993), and Masuo et al. (2001) supports the link between age and entrepreneurial failure. These authors reported that age impacts company failure. By further implication, Other authors attribute old age of entrepreneurs to the time spent studying. Lasch (2003) concluded that entrepreneurs working in innovation and technology are, on average, two to five years older than those in non-innovative sectors. Cressy (1994), Wicker and King (1989) argue that young entrepreneurs have the lowest success rate (survival rate) of the company. The older entrepreneur has developed more robust and experienced networks and can quickly raise capital (Lasch, 2005). Hence, the following hypothesis is formulated: Hypothesis H1c: VSB failure would be higher for entrepreneurs aged less than 35. • The link between relationships and failure Social capital depends on individuals' ability to use their social relationships and networks to help and support their activities5. Based on Canadian statistics, Lentz and Laband (1990) have shown that most self-employed company directors are the children of self-employed people. Entrepreneurs whose parents were entrepreneurs have a greater chance of success than other entrepreneurs. This is due to the fact that they have acquired an informal business world experience in the context of the family company. Furthermore, Cooper et al. (1994) found that having parents who owned a company contributed to the business's survival. It should be noted that this finding contrasts with that of Brüderl et al. (1992), who found, in a sample of German companies, that the presence of a self-employed father did not increase the probability of the survival of newly-created companies. The following hypothesis, therefore, put forward: Hypothesis H1d: “Relationships” could impact the failure of SMBs. 4neur" and Many authors, including (Carland, Hoy, Boulton, & Carland, 1984), suggest that a distinction should be made between "entrepre "manager of a small company". As this distinction is not relevant to the present work, the terms entrepreneur, owner, manager, owner- manager refer to the same person, the one who creates and manages a VSB. 5resources. We agree While some studies refer explicitly to the theory of social capital, others refer to networking, social resources or external with Lin (1995: 687) that "(...) social resources constitute the central element of social capital". 2174 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2168-2188, 2024 DOI: 10.55214/25768484.v8i6.2410 © 2024 by the authors; licensee Learning Gate • Link between vocational training and failure: Openness to information networks provides accurate data, which encourages and assists the entrepreneur in detecting his business's weak points or strengths. Since the entrepreneur is not very well informed about the financing methods and institutional grants available, consulting professionals can provide a more comprehensive plan for launching projects (Aldrich et al., 1987). In this setting, several studies have examined the use of professional sources of support (Lavoisier, 2011). In this respect, Cooper et al. (1994) have shown that entrepreneurs who do not have enough luck surviving their business remain those who do not use professional advisers. Using accountants and advisers has been associated with better performance (O’Neill & Duker, 1986). Moreover, those who use entrepreneurial training may also have access to more financial resources. This research hypothesizes a negative relationship between using advisors, entrepreneurial training, and failure. The present research links the use of advisors to company failure. Hypothesis H1e: The probability of failure is higher for companies that do not use entrepreneurial training. 3. Presentation of the Field Research Methodology This section aims to present the source of information for our study and the criteria we set for selecting the companies to be surveyed. It also sets out the details of the design of the questionnaire adopted in this study, the means and instruments for measuring and evaluating the variables selected for this work, and the data collection process without sidestepping the difficulties encountered throughout this survey. 3.1. Questionnaire Construction Process The questionnaire was designed in three stages: Firstly, a review of the literature, then interviews with professionals in the field, and finally, the testing of the questionnaire. Review of the literature: In this context, the first step began with a review of the literature on the factors determining entrepreneurial failure in VSB. The purpose of this review was to: • Gain a thorough understanding of the issue of entrepreneurial failure. This task enabled the researchers of this study to identify existing research on the difficulties faced by VSB and to identify those that deal with the factors that lead to failure; • Define the factors that have been tested: studies of VSB failure, especially those that have tested the impact of several factors on them; • Gather information from the Moroccan context and elsewhere on the failure of VSB. This showed that there is a gap, particularly in terms of empirical studies dealing with the difficulties of VSB; • Opting for variables to measure the field of investigation via a decided literature review, which enabled the researchers to choose an initial set of variables that are likely to influence the failure of VSB; • Identify measurement scales formulated and validated in a specific research field, i.e., VSB in Morocco. Before launching the survey, these scales must be verified and adapted to our context. • It should be noted that the questionnaire of this survey was inspired by the questionnaires used in the following studies: “Creation of companies in the Casablanca-Settat region via the CRI6 “post- creation survey” carried out by the Casablanca-Settat regional investment center and the World Bank; “Survey of Moroccan SMBs” carried out by the Observatory of Moroccan SMBs; “Survey carried out in April 2020 by the HCP during the containment period.' 6e's policy on Regional Investment Centre : The Regional Investment Centre is responsible for contributing to the implementation of the Stat the development, encouragement and promotion of investment and overall support for companies, particularly VSBs. 2175 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2168-2188, 2024 DOI: 10.55214/25768484.v8i6.2410 © 2024 by the authors; licensee Learning Gate Table 2. The explanatory variables. Analysis level Determining factors Indicators N questions Symbol Items description Hypotheses E n tr ep re n eu r Motivation to create The entrepreneur’s motivation 13/14 Motiv 1: Entrepreneurial spirit 2: Seeking social status 3: Have an income 4: Supporting the Family Lack of adequately paid employment Hypothesis 1a: The failure of a VSB depends on the type of motivation the Gender Gender 1 Gender 1: Man 2: Woman Hypothesis 1b: Businesses created by men are more likely to fail than those created by women Age The age of the entrepreneur 2 Age Hypothesis 1c: Failure rates are higher for entrepreneurs under the age of 35 Entrepreneurial relationships Entrepreneurial relationships 15 En-re 1: Yes 2: No Hypothesis 1d : relationships could have an impact on the failure of VSBs. Use of entrepreneurial training Entrepreneurial training 19 En-tr 1: No 2: Yes, at my request and the expense of a public sector 3: Yes, at my request and expense Hypothesis 1e : The probability of failure is lower for companies that use entrepreneurial training. 2176 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2168-2188, 2024 DOI: 10.55214/25768484.v8i6.2410 © 2024 by the authors; licensee Learning Gate 3.2. Variable Explained: The Failing Company To measure this indicator, we have adopted an approach based on the scales used by Lorrain et al. (1998), which are based on the Churchill paradigm (1979). The purpose of this scale is to measure the entrepreneur’s attitude based on his or her opinion. This method aims to determine the score of a failing VSB reliably. This involves assigning a numerical value to our variable of interest. In order to give it a measurement scale of 1 to 5 following the intensity of the failure, we have opted, in this case, for five measurement scales, which we present in the following table: Table 3. The explained variable. Explained-variable Sub-variable Question no. Items Failure of the VSB Failure 12 On a scale of 1 to 5, how would you rate your company's failure? 3.3. Selection of Our Survey Sample When analyzed quantitatively, failure appears to be a complex issue. Researchers' major methodological problem relates mainly to data collection (Bruno et al., 1987). To overcome this difficulty, the survey sample size was built up using the “snowball” technique, which is the most suitable for targeting complex populations (Thiétart et al., 1999). To achieve this, authors of this study partnered with professional associations (Moroccan Junior- Enterprise Confederation, the National Federation of Small and Medium-sized Enterprises, etc.). Researchers of this study also worked in cooperation with “privileged witnesses.” According to Quivy and Van Campenhoudt (1995, p. 66), these are people who, through their professional activity, are in direct contact with the public targeted by the study. In the context of our research, these “privileged witnesses” are certified accountants who accompany and manage support structures (such as the Regional Centre of Investment, Morocco PME7, OFPPT8), bankers who manage credit departments, the National Association of Pharmacists, the National Association of Doctors, etc. In order to gradually build up the survey sample, researchers of this study asked participants in the questionnaire to introduce them to other people so as to be surveyed too, and so on... what follows, then, is mapping out of the data collection. 3.4. Data Collection Although the survey was launched online, 54 of the 300 e-mails were answered, representing a return rate of 18%. This response or return rate9 is often lower than a face-to-face or phone survey. At the same time, and in order to improve this rate, authors of the present study communicated the questionnaire to their partners: professional associations (the Moroccan Traders’ Association, the Moroccan Craftsmen Federation, the Moroccan Association of Women Business Owners, the Moroccan Junior Business Confederation, etc.) and they worked in cooperation with “privileged witnesses.” The latter are people who, through their professional activity, are in direct contact with the public concerned by the study, such as certified public accountants and entrepreneurs of support structures (such as the Regional Investment Centre, Morocco PME, OFPPT), bankers, and entrepreneurs of credit departments, the National Order of Pharmacists, the National Order of Doctors, etc. Interviewees were asked for their views on the subject. Interviewers also asked interviewees to introduce them to other people so that they could interview them in turn, and so on. However, the method of phone administration between December (2021) and February (2022) yielded an exciting return rate. Out of 260 identified, 195 responses were received, i.e., a return rate of (75%). 7cco's Morocco PME (formerly ANPME) is the government's operational tool for small business development, and is at the heart of Moro support system for companies. 8 or Professional Training and Work Promotion (OFPPT) is a public vocational training operator covering the entire territory ofThe Office f Morocco. 9contacted.The return rate measures the percentage of individuals who responded to the questionnaire as a proportion of all individuals 2177 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2168-2188, 2024 DOI: 10.55214/25768484.v8i6.2410 © 2024 by the authors; licensee Learning Gate The final sample obtained at the end of this rigorous selection process consists of 249 companies. In short, this choice was made almost solely based on constraints relating to scarcity and the gathering of information that would enable the researchers to identify failing companies. Nonetheless, the field constraints and the specificity of the statistical tool to be used later will modify the size of this survey’s sample, as will the variables have chosen. To achieve this rate, a significant number of responses were eliminated. Out of 249 responses received, 17 were eliminated for the following reasons: 1- Non-compliance with the status and independence criteria “shareholder or employee.” 2- Lack of information on turnover and number of employees. It should also be added that the final response rate (40%)10 was considerable, given the quality of the information obtained. It should be noted that the data was processed using SPSS.20 software11. The following section is allocated for the findings and discussion. 4. Results and Discussion Based on the results of this survey, this section highlights the most important characteristics of the VSB surveyed. 4.1. Univariate analysis 4.1.1. Gender The survey reveals that VSBs are slightly over-represented by men. In this respect, 72.84% of businesses were created by men, compared with only 27.16% by women. Figure 1. Gender distribution of the sample. 10ation or a community captive population. For an organization’s popul-The reference values are a response rate of over 10% or 15% for a non (a so-called "captive" audience), the 50% threshold represents a realistic objective (Ganassali, 2009:102). 11Indeed, SPSS is a SPSS is a software program capable of running all the statistical tests commonly used in the social sciences and psychology. very comprehensive software program compared with other software programs that allow only a limited amount of data. 2178 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2168-2188, 2024 DOI: 10.55214/25768484.v8i6.2410 © 2024 by the authors; licensee Learning Gate 4.1.1.1. Age Category The age of the individuals surveyed is classified into four categories. Entrepreneurs between the ages of 35 and 45 account for the most significant proportion of those surveyed (44%), followed by entrepreneurs under 35 (40%). Entrepreneurs aged over 45 were in the lowest category (16%). 4.1.1.2. Entrepreneurial Relationships Regarding the entrepreneurial environment, we can see that relationships facilitated the creation of (66.6%) entrepreneurs. This result is in line with several studies in the literature indicating that, in most cases, almost half of entrepreneurs come from their entrepreneurial entourage. Table 4. Distribution by business relationship. Was it more accessible to start your business because of your relationships with people? Number of employees Percentage Valid percentage Cumulative percentage No 77 33.4 33.4 33.4 Valid Yes 155 66.6 66.6 100.0 Total 232 100.0 100.0 4.1.1.3. Motivation The VSB survey reveals why entrepreneurs decide to set up a company in addition to gender and age. Figure 2. Distribution by motivation. Overall, it is noticeable that, on average, seeking social status in society is the determining factor in setting up company (40%), representing almost half of the percentage, and only (21.12%) declare that they desire to be independent entrepreneurs. On the other hand, income was the primary motivation for (19.4%) of entrepreneurs to launch an entrepreneurial project. In comparison (11.21%) replied that the 2179 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2168-2188, 2024 DOI: 10.55214/25768484.v8i6.2410 © 2024 by the authors; licensee Learning Gate fact of providing family support conditioned their motivation. However, (8%) of entrepreneurs’ motivation is driven by the lack of a well-paid job. 4.1.2. Statistical Analysis of Cross-Tabulations In what follows, and to complete this descriptive analysis, cross-tabulated statistics will be calculated for the different variables taken in pairs. To avoid making this section too long, other cross- tabulations will be presented in the section (Appendix 2: SPSS results). It can be seen that men are more likely to fail (68.6%) than women (46.3%). This same result has been demonstrated in the literature, where men have a higher failure rate than women (Bosma et al., 2004; Robb, 2002). Econometric analysis of this study will verify and show this assertion in the rest of this study to confirm or refute it (see Table 5). Table 5. Company activity status by gender. Cross-tabulation Binary failure Total Surviving In failure Gender Women Number of employees 34 29 63 % included in Gender 53.7% 46.3% 100.0% Men Number of employees 53 116 169 % included in Gender 31.4% 68.6% 100.0% Total Number of employees 87 145 232 % included in Gender 37.5% 62.5% 100.0% Entrepreneurs under the age of 35 represent the proportion most likely to fail (a failure rate of 74%). The higher the age of the entrepreneur is, the fewer difficulties the company will experience. In addition, this finding is consistent with the work of Zimmerrer and Scarborough (1998), which showed that most entrepreneurs start their business at 30 to 40. Likewise, Staw (1991) demonstrated that the age of the entrepreneur, in addition to his or her business experience, significantly influences the probability of the failure of the VSB. This could be explained by old age, which implies entrepreneurial experience (A remark that remains to be validated or refuted by the econometric study) (See Table 06). Table 6. Company activity status by age. Cross-tabulation age category * failure_binary Failure_binary Total Surviving In failure Age category Less than 35 years old Number of employees 30 74 104 % 26.0% 74.0% 100.0% Between 35 and 45 years old Number of employees 56 38 94 % 59.6% 40.4% 100.0% More than 45 years old Number of employees 21 13 34 % 61.8% 38.2% 100.0% Total Number of employees 107 125 232 % 46.12% 53.88% 100.0% Table 06 shows the relative proportions of the different types of motivation that led entrepreneurs to set up an SMB about the company's failure or lack of failure. This table shows that entrepreneurs 2180 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2168-2188, 2024 DOI: 10.55214/25768484.v8i6.2410 © 2024 by the authors; licensee Learning Gate seeking social status were the least likely to experience difficulties (30.4%), followed by those who wanted to help and support their families (34.6%). In comparison, those who chose to have an income were more likely to experience difficulties (77.8%) (See Table 06). Regarding the six types of public support, it can be seen that most entrepreneurs have not benefited from them, except for the investment subvention, for which only (12.9%) have not benefited. What is more, VSBs in failure are the most prominent recipients of each type of public support when compared to VSBs that are not in failure in terms of subsidies (87.5% compared to 12.9%), support grants, and social exemptions (66.7% compared to 33.3%), and finally tax exemptions (54.5% compared to 45.5%). This can be explained by the unfavorable effect of public aid on most SMBs in failure (see Table 06). Table 7. Company activity status by motivation. Cross-tabulation Binary failure Total Surviving Failed What was your primary motivation in setting up your company? Lack of well-paid job Number of employees 11 8 19 % 57.9% 42.1% 100.0% Help and support the family. Number of employees 17 9 26 % 65.4% 34.6% 100.0% Have an income Number of employees 10 35 45 % 22.2% 77.8% 100.0% Seeking social status in society Number of employees 64 28 92 % 69.6% 30.4% 100.0% Entrepreneurial spirit and social independence Number of employees 26 23 49 % 53.1% 46.9% 100.0% None Number of employees 0 1 1 % 0.0% 100.0% 100.0% Total Number of employees 128 104 232 % 55.17% 44.83% 100.0% 5. Presentation of the Model and Discussion of the Results This section aims to test the research hypotheses and discuss the results. To do so, motives for choosing logistic regression will first be presented. An attempt will be, then, made to confirm the results using a multivariate model of the X variables about the Y variable (Failure). Finally, the following equation will be attained, which will be used to express the results of this attempt at the modeling applied to the difficulties of VSBs. 5.1. Opting for Logistic Regression Our analysis is part of a growing body of research initiated by E. Altman (1968), Aziz, Emanuel, and Lawson (1988; Ohlson, 1980), who preferred using empirical logistic regression based on a multi- variable risk analysis. The aim is to develop a statistical model capable of “rating” companies on their failure using less restrictive statistical assumptions. More importantly, the advantages of the Logit model should be mentioned. 2181 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2168-2188, 2024 DOI: 10.55214/25768484.v8i6.2410 © 2024 by the authors; licensee Learning Gate Logistic modeling or dichotomous regression remains the most favored econometric expression for investigating and analyzing the dependency relationship between a qualitative dichotomous variable and a certain number of quantitative and qualitative factors of socio-economic phenomena of a qualitative nature (Régis Bourbonnais, 2009). 5.1.1. Formalization of the Model The expression for this model is as follows: P (y=1) = exp [−(α+ βX1+⋯+βX𝐧) ] (1+ exp [−(α+ βX1+⋯+βX𝐧)]) Where y represents the weighted sum of the independent variables in the Logit analysis, Xi (i=1, ..., n) are the independent variables, and α, βi (i=1, ..., n) are the estimated parameters. With this logistic model equation, whatever the Mean of X, the P (y) value lies within the interval [0; 1]. In other words, the Logit model generates the probability of belonging to a group that varies between 0 and 1. The principle of this method is to estimate the coefficients α and βi using the Maximum Likelihood estimation. After a logarithmic transformation, the model can be written as follows: The present study seeks to explain the company’s failure by a set of factors likely to have statistically significant explanatory value. To do this, the model can be expressed as follows: (multiple- regression) Y=Log 𝐏(y) 1−P(y) = α + β1X1 + β2X2 + ⋯ + βnXn12 In the present model, “Y” stands for the natural logarithm of the probabilities of the VSB being in failure. “y” can be transformed into a probability by the model equation above (1). This allows for the analysis the impact of the “regressors” on the risk of a VSB failing. Next, the independent variables used to estimate the parameters of the logistic regression model selected are herein presented, namely: X1 = “Motiv”, motivation; X2 = “gender”, gender; X3 = age; X4 = “enter-relat”, entrepreneurial relationships; X5 = “entr-form”, entrepreneurial formation 5.2. Results of the Chi-Square Independence Test, ANOVA Interpretation 5.2.1. Chi-Square Test of Independence 5.2.1.1. Motivation Analyzing the “motivation” variable, it is noted that the dependence is significant at the 5% threshold because the p-value is less than 5%. Having an entrepreneurial spirit, having a new idea or an opportunity, represents an advantage that diminishes the probability of failure in VSB, which is about an entrepreneur whose idea to create a company comes from being unemployed. This result is in line with Cressy's research (2012). Having seized an opportunity reduces the failure of the entrepreneur for whom the creation of a VSB was an act of poverty to escape the unemployment situation. Table 8. Chi-square tests. Chi-square tests Mean Ddl Asymptotic significance (One-sided) Pearson chi-square 8.064a 5 0.000 Likelihood ratio 8.366 5 0.000 Number of valid observations 232 Note: a. two cells (16.7%) have a theoretical size of less than 5. The minimum theoretical number of cells is .34. Therefore, the null hypothesis (H0.1a) is rejected, while hypothesis H1.1a is valid. 12 The equation of the multiple linear regression model 2182 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2168-2188, 2024 DOI: 10.55214/25768484.v8i6.2410 © 2024 by the authors; licensee Learning Gate Hypothesis H1a is Valid: The failure of VSBs depends on the entrepreneur’s initial motivation. 5.2.1.2. Gender In terms of the estimated results, the “gender” variable is significant, which means that businesses created by men are more likely to fail (68.6%) than those created by women (46.3%) at the 5% threshold. This result suggests that the gender variable explains failure. An econometric study examines this conclusion. However, it goes against the findings of Robb and Watson (2012), who, in their research, rejected the belief that women-owned companies are more likely to fail than those owned by men. This would be explained by the risk aversion women take compared to men. In other words, women minimize their risk of loss rather than the project that offers favorable profit prospects. Table 9. Chi-square tests. Chi-square tests Mean DDL Asymptotic significance (two-sided) Exact Significance (One-sided) Exact significance (One-sided) Pearson chi-square 12.424a 1 0.000 Number of valid observations 232 Note: a. 0 cells (.0%) have a theoretical number of cells of less than 5. The minimum theoretical number of cells is 21.18. b. Calculated only for a 2x2 network Therefore, the null hypothesis (H0.1b) is refuted, and hypothesis H1.1b is confirmed. Hypothesis H1b is confirmed: VSBs set up by men are more likely to fail than those set up by women. 5.2.1.3. Entrepreneur’s Ages Taking into account the age of the entrepreneur, it can be seen that this variable is significant at the 5% threshold since the p-value (=0.002) is below the 5% risk threshold. Suppose those under 35 years of age as our reference category are chosen. In that case, it can be seen that an entrepreneur who has created a VSB under 35 significantly affects the VSB's failure, increasing the probability of failure. This result can be interpreted as follows: high age implies entrepreneurial experience. In the American context, this finding is consistent with studies by Zimmerrer and Scarborough (1998), showing that most entrepreneurs start their business at 30 to 40. Also, Staw (1991) has shown that an entrepreneur’s age, in addition to his or her experience in the business world, significantly influences his or her success. Table 10. Chi-square tests. Chi-square tests Mean DDL Asymptotic significance (two-sided) Pearson chi-square 11.009a 2 0.002 Likelihood ratio 5.069 2 0.002 Number of valid observations 232 Note: a. 0 cells (.0%) have a theoretical number less than 5. The minimum theoretical number of cells is 11.43. Therefore, the null hypothesis (H0.1c) is refuted, and the hypothesis (H1 1c) is accepted. Hypothesis H1c is confirmed: Failure is higher for entrepreneurs aged less than 35. 5.2.1.4. Relationships The “Relationship” variable is significant at the 5% threshold since the p-value (=0.00) is below the 5% risk threshold. The estimates show that having a professional relationship reduces the probability of business failure. This finding aligns with the analyses carried out via the theory of social capital and the 2183 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2168-2188, 2024 DOI: 10.55214/25768484.v8i6.2410 © 2024 by the authors; licensee Learning Gate theory of networks (Alrich & Zimmer, 1986), which refer to the individual’s ability to derive advantages from the entrepreneurial context in which he lives (Cf. table .10.11.12). Table 11. State of VSB according to relationship. Cross tabulation: Was the start-up of your business made easier by relationships?* Binary failure Binary Failure Total Surviving Failed Was the start-up of your business made more accessible by good relationships? Non Number of employees 42 82 124 % 33.9% 66.1% 100.0% Oui Number of employees 72 36 108 % 66.7% 33.3% 100.0% Total Number of employees 78 118 232 % 49.14% 50.86% 100.0% Table 12. Symmetrical measurements. Symmetrical measurements Mean Approximate significance Nominal per nominal Contingency coefficient 0.456 0.000 Number of valid observations 232 Therefore, the null hypothesis (H0.1c) is refuted, and the hypothesis (H1 1c) is confirmed. Hypothesis H1d is confirmed: “Relationships” impact the failure of VSBs. 5.2.1.5. Entrepreneurial Training The variable “recourse to entrepreneurial training” significantly affects the failure of VSB when the training is requested and paid for by a public institution. In other words, businesses fail less when entrepreneurs take entrepreneurial training before project implementation, paid for by the public sector. This enables the entrepreneur to explore the world of business. However, when this training is requested by the entrepreneur and paid for by a public institution, this variable becomes increasingly significant, because some entrepreneurs choose to use this training only to benefit from a training certificate but not to benefit from the content of the training. Table 13. Chi-square tests. Chi-square tests Mean DDL Asymptotic significance (Two-sided) Exact significance (Two-sided) Exact significance (One-sided) Pearson Chi-square 13.367a 2 0.000 Likelihood ratio 12.007 2 0.003 Number of valid observations 232 Note: a. 0 cells (.0%) have a theoretical number less than 5. The minimum theoretical number of cells is 11.77. Consequently, the null hypothesis (H0.1e) is refuted, and hypothesis H1 1e is confirmed. 2184 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2168-2188, 2024 DOI: 10.55214/25768484.v8i6.2410 © 2024 by the authors; licensee Learning Gate Hypothesis H1e is confirmed: The probability of failure is higher for companies that do not engage in entrepreneurial training. 5.3. Results of the Logistic Regression Model We developed our regression by introducing variables related to the entrepreneur’s characteristics (motivation, gender, age, relationship, entrepreneurial training). The results of our model were calculated using the SPSS software. The results of the model are presented in the table below. The second column shows the estimations of the β parameters. This parameter evaluates the impact of each explaining variable on the logarithm of the risk of failure. However, it is easy to analyze the exponential of the β coefficient, given in the last column of the table, which refers to what is known as the “hazard ratio” of the given variable about the reference variable. If the exponential of the β coefficient is less than 1, this Mode helps to reduce the risk of failure. On the contrary, if the exponential of the β coefficient is greater than 1, then this Mode increases the probability of exit (increasing the failure for the company). With different combinations of several explaining variables, this study attempted to present the most robust model. It turned out that the selected model with the highest (R two) is given in “Table 14”. Table 14. Variables in the equation. Variables in equation B E.S. Wald DDL Sig. Exp (B) Motivation 6.689 5 0.022 Motivation(1) -1.980 0.423 21.910 1 0.030 0.138 Motivation(2) -2.721 0.840 10.493 1 0.420 0.066 Motivation(3) -1.040 0.620 2.814 1 0.000 0.353 Motivation(4) -0.431 0.120 12.900 1 0.120 0.650 Motivation(5) 1.134 0.450 6.350 1 0.010 0.322 Constant value 1.603 1.212 14.423 1 0.012 4.968 Note: a. Variable(s) entered in step 1: Legal_status, Main_motivation, Relational, Initial_capital_sufficiency, Binding_tax_system. b. Motivation (1) = Lack of well-paid jobs Motivation (2) = To provide help and support for the family. Motivation (3) = To have an income Motivation (4) = To seek social status in society Motivation (5) = A desire to be an independent entrepreneur 𝑃(𝑦 = 1) = 1 ⁄ 1 + 𝑒𝑥𝑝( −[1.603 − 1,980X1(1) − 2,721X1(2) − 1,040X1(3) − ,431X1(4) + 1,134X1(5))] ) We can, therefore, see that the relationship is positive for the variables: entrepreneurial spirit is positive. This means that a low level of entrepreneurial spirit predicts the failure of VSB. On the other hand, the relationship is harmful to the motivation variable; this means that the types of entrepreneurial motivation (lack of a sufficiently remunerated job, providing help and support to the family, having an income, seeking social status in society) act to reduce the probability of failure of VSB. The other variables tested remain insignificant, which explains why they are excluded from our statistical model. 2185 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 8, No. 6: 2168-2188, 2024 DOI: 10.55214/25768484.v8i6.2410 © 2024 by the authors; licensee Learning Gate 5.4. Results Summary Table 15. Test results. Level Hypothesis Results C/I Entrepreneur H1a Type of entrepreneurial motivation influences business failure Confirmed H1b VSBS MSEs created by men are more likely to fail than those created by women. Confirmed H1c Age has a significant impact on VSE failure VSB Confirmed H1d The probability of failure is higher among entrepreneurs with an entrepreneurial entourage. Confirmed H1e The likelihood of failure is higher for businesses that have taken entrepreneurial training. Confirmed 6. Conclusion This article aims to understand the impact of the entrepreneur’s profile on the failure of VSB. To address the issue of VSBs’ failure, authors of this study began by using a lexical approach to distinguish between closely related concepts, proposing a definition of the failed company. This was done through a refined theoretical reading that allowed us to examine the origin of this concept and its evolution through the various academic schools. For this reason, various figures have set out the dimensions of the failing company by mobilizing the factors of failure. Regarding the hypothesis tested based on data from a survey of the VSB in Morocco, the impact of factors relating to the entrepreneur’s profile on the failure of the VSBs was revealed. Researchers of this study deduced that an entrepreneur sees his business fail when he is less than 35 years of age, motivated to have an income, and who has benefited from entrepreneurial training. In this respect, the question that needs to be raised is: Is there any other way to help us identify how VSBs fail? 6.1. Limitations and Perspectives Indeed, within the framework of the selected variables, authors of this study encountered some difficulties regarding certain information about the financial situation and balance sheets. Unfortunately, data used in this study do not provide any information on these issues. Another limitation arises from the nature of the data, which is restricted to a sample. This raises the question of whether these results can be generalized to the entire country. Our work opens up several research perspectives. It has highlighted the emerging aspect of failing small businesses. This field of study and investigation could be expanded in various ways, such as implementing methods for identifying the Cox or Cox PLS duration. This would help to determine the timeline of business failures among TPEs and propose appropriate programs and solutions promptly to mitigate negative impacts. Author Contributions: R. ELAFI described the research problem, defined vital concepts, and presented the research methodology; Y. JOUALI collected and processed data; and A. WAHBI, the third author, handled the data's writing, analysis, and interpretation. Copyright: © 2024 by the authors. 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