Keywords

Nascent entrepreneurship, Motivation, Opportunities and Necessity, Personal characteristics, Entrepreneurial behavior, Self-efficacy.

Introduction

In general, entrepreneurship is defined as the creation of a new venture (Gartner, 1985), and it is important for innovation, job growth, and productivity (Reynolds, 2007). It is clear that entrepreneurial activity is needed for economic growth and that the effectiveness of innovation, entrepreneurship, and new business can be enhanced (Farhat et al., 2018). The decision of individuals, the culmination of the start-up of a business, and the resource organization and identification of individuals are the stages related to the creation of a new business (Fairlie, 2005; Reynolds & Curtin, 2008). In terms of “nascent entrepreneurship”, one individual or more individuals start to commit time and resources to set up a new firm; (Aldrich, 1999; Carter et al., 1996).

Research on nascent entrepreneurs was largely spearheaded by (Reynolds, 2007) Reynolds (2000), who addresses the methodological defect to build some knowledge. Furthermore, some researchers have indicated that the resources of the founder are important for founding success (Davidsson & Honig, 2003; Parker & Belghitar, 2006; Van Gelderen et al., 2001), as are environmental conditions (Hansen & Allen, 1992; Larson & Starr, 1993; Liao & Gartner, 2006). In general, local and national governments encourage the development of a culture of entrepreneurship to promote economic growth, innovation and new job opportunities (Acs & Armington, 2006; Audretsch, 2007; Fletcher et al., 2011; Schramm, 2013). In particular, the nascent entrepreneurship phenomenon has received significant attention in starting up a business (Davidsson, 2006) and has different varieties of contexts with different theoretical standpoints (Parker & Belghitar, 2006). Some individuals take the opportunity to be an entrepreneur, while others neglect the opportunity; additionally, the culture that an individual lives in has an influence on the decision to become an entrepreneur, as do prior knowledge, social networks, experience networks and contact with other entrepreneurs (Davidsson & Honig, 2003; Kim et al., 2006; Shane, 2000; Shepherd & DeTienne, 2005). The process of starting up a business needs at least one individual to take the initiative. Accordingly, a nascent entrepreneur is "someone who initiates serious activities that are intended to culminate in a viable business startup" (Aldrich, 1999) or is a part owner of a new organization, as defined by the Panel Study of Entrepreneurial Dynamics (PSED) (Reynolds, 2000; Reynolds, Carter, Gartner, & Greene, 2004; Shaver, Carter, Gartner, & Reynolds, 2001).According to the Global Entrepreneurship Monitor (GEM) (2000; Reynolds, Hay, & Camp, 1999), a nascent entrepreneur is an active individual who has been trying to start up a business in the past 12 months or an individual who does not have the cash flow to cover his or her expenses or to pay salaries for more than three months.

As stated by Johnson et al. (2006), some people engage in nascent entrepreneurship, while others do not, and some nascent entrepreneurs make the transition into business, while others work on their business ideas or abandon them. Nascent entrepreneurs invest their capital and time in their entrepreneurial activity, and nascent entrepreneurs expect success in their business, such as the prospect of achieving an operating enterprise. Individuals expect the venturing process to continue in self-employment or to require additional time and capital to invest (Gimeno et al., 1997; McCarthy, Schoorman & Cooper, 1993). Moreover, being self-employed and founding a business are related to each other, depending on the constituents of an entrepreneur (Katz, 1990; Learned, 1992). There are three types of nascent entrepreneurship, as stated by Carter et al. (1996), namely, “started a business”, “gave up” and “still trying”, and nascent entrepreneurs’ level of activity is considered the main distinguishing feature of those three types.

Indeed, some scholars argue that employees with a managerial position are more likely to be nascent entrepreneurs due to their experience in establishing networks with others and hiring employees and because of their relationships with suppliers and customers; however, other researchers cannot confirm this point (Bates, 1995; Davidsson & Honig, 2003; Gimeno et al., 1997; Kim et al., 2006). The expectations regarding the behavior of individuals have consequences for stakeholders and the economy in regard to making inaccurate or biased systematic predictions in terms of the choices of entrepreneurial activities. Wagner and Sternberg (2004) mentioned two stylized facts in some empirical studies in many countries: the characteristics of cities that play a role in the decision to enter a new ventures are different from one city to another, such as age, educational level, attitude towards risk taking, and municipal policy, which are all influenced by attitudes and sociodemographic factors. However, many studies acknowledge that males are more likely to be entrepreneurs than females due to their attitude towards risk taking (Bosma & Levie, 2010). In general, the most entrepreneurially active period for males and females is between 25 and 34 years of age (Reynolds, Carter, et al., 2004), and different studies show that becoming nascent entrepreneurs has a negative effect on the age group between 25 and 34 years old (Bosma & Levie, 2010).

The process of creating a new business might take months or even years, and the reasons behind creating an enterprise differ from one individual to another (Carter, Gartner, Shaver, & Gatewood, 2003). A study by the GEM across 35 countries shows that the activities of nascent entrepreneurship vary greatly, and some countries exceed 10% nascent entrepreneurship, while other countries are below 5% (Reynolds, Bygrave, et al., 2004).

Hypothesis Development

This paper provides a theoretical framework to assist with the development of our hypotheses. Then, we explain our methodology and present the results examining the impact of personal characteristics and the self-efficacy (SE), motivation (MO), and opportunities and necessity (OP), of our shop-on-wheel sample on entrepreneurial behavior (EB).

Gartner (1985) mentioned that there are many factors in the propensity of individuals and the complex decision to start up a business. Many scholars agree that males do not face complexity in the decision to start a business compared to their female counterparts and that females tend to be more sensitive than men to a variety of nonmonetary issues ((Manolova, Brush, Edelman, & Shaver, 2012). The nascent venture concept, which refers to the process of creating or thinking of a new business, was developed in the 1990s, and this process has four stages: conception, gestation, infancy, and adolescence (Honig & Karlsson, 2004).

H1: There is a positive association between SE and EB.

SE refers to the beliefs of individuals in their ability and skill to perform a task to be successful (Bandura, 1999). Meanwhile, personal experience is the most effective at enhancing one’s level of SE. Mastery experiences give a boost to one’s belief in oneself with regard to what one can do with the capabilities one possesses (Gist, 1987; Wood & Bandura, 1989). Researchers have suggested that perceived SE may also determine the desire for opportunities and decisions (Markman et al., 2002). In addition, Owens et al. (2013) mentioned that the most imperative variable is SE, which is related to the success of difficult dreams and the improvement of an entrepreneurial business. In addition, prior studies have noted the importance of SE in individuals as being among the foremost factors for understanding the complex dynamics of entrepreneurial activities and intentions and that SE enhances the development of formal start-up plans (Laviolette et al., 2012).

H2: There is a positive association between OP and EB.

The core aspect of the entrepreneurial process is entrepreneurial opportunities because entrepreneurship is concerned with the exploitation and discovery of profitable opportunities (Shane & Venkataraman, 2000). Furthermore, the choice to take an opportunity can be determined through perceived SE (Kickul et al., 2009), and the reasons individuals start up a business, which is considered a problem and a failure to focus on two categories, are individuals neglected an opportunity and the necessity that drives entrepreneurship to describe ongoing conditions (Zhao & Smallbone, 2019). It is possible that changes in regulations, society and market needs are due to entrepreneurial opportunities. Entrepreneurs’ awareness of these changes allows them to identify opportunities that are represented by a market gap (Venkataraman, 1997). According to Gibb and Ritchie (1982), determining an entrepreneur's behavior is complicated. At the same time, becoming an entrepreneur is considered innate or inherited.

Some studies have stated that opportunities might come accidently in some cases , and entrepreneurs who found opportunities by accident have a higher level of awareness and are sensitive to any changes compared to entrepreneurs who found opportunities through a systematic search (Shane & Venkataraman, 2000). Furthermore, due to the exploitation of business opportunities, it is not easy to describe the entrepreneurial market and the level of competition in regard to entrepreneurs’ decision to start their own business. (Zhao & Smallbone, 2019) adopted a behavioral model to examine entrepreneurial proactiveness. Previous studies have shown that an essential component in the development of starting new businesses is MO (Herron & Sapienza, 1992). There is a notable evidence-based literature showing that greater economic growth is driven by the opportunities of entrepreneurs (Kerr et al., 2017).

Furthermore, entrepreneurs have been criticized based on the difference between opportunities and necessity due to changes in EB or the external environment associated with entrepreneurial learning (Smallbone & Welter, 2004). However, in regard to opportunities versus necessity, entrepreneurs’ start-up motivation is related to postentry firm performance (Mohan, 2019). The lack of employment might drive some entrepreneurs to obtain opportunities to start up their business and avoid any risk (Mota et al., 2019).

Although studies have shown the association between OP and MO and business performance mostly in the context of developing countries, in developing countries, entrepreneurs do not take advantage of business opportunities due to poverty and lack of employment. A country’s institutions and culture and the context in which a business operates have been studied in the context of developed countries (Desai, 2011; Naudé, 2010). However, it is not necessary for opportunities to accrue in developed countries.

H3: There is a positive association between MO with EB.

Entrepreneurs have different reasons that lead them to take certain actions. The two most common distinctions between intrinsic and extrinsic MO are that intrinsic MO allows individuals to enjoy that which interests them, while extrinsic MO leads them to separable outcomes (Bergin et al., 1993). In addition, Shaver and Scott (1992) pointed out a positive association between EB and achievement MO. However, strong MO is needed for individuals to start up a business (Levesque, Shepherd, & Douglas, 2002). Additionally, the characteristics that influence MOs allow a perspective on the entrepreneurial process, while both the process and MO influence the decision of individuals to start up a business (Mota et al., 2019).

Valliere (2015) reported that MO is evidence that explains EB, and MO plays an important role in individuals creating their own business (Herron & Sapienza, 1992). According to some studies, entrepreneurial MO is related to market opportunities (Kontinen & Ojala, 2011) and other factors, such as intention and management roles, motivate entrepreneurs (Alessa, 2018). Research on the MO of entrepreneurs has been growing rapidly, as has the understanding of the MO that drives the start-up, growth, and exit of businesses (Murnieks et al., 2020). Furthermore, the characteristics of individuals affect entrepreneurial MO (Baron et al., 2016; Miller & Le Breton-Miller, 2017).

H4: SE, OP, and MO explain the nascent behavior of entrepreneurs.

GEM data indicate that compared to their female counterparts, males lead more new businesses and hire more employees (Arenius & Minniti, 2005), and men are less quick than females in completing the gestational period (Davidsson & Honig, 2003). In fact, one study shows that the expectation of business growth in Denmark resulted in male nascent entrepreneurs having higher expectations compared to their female counterparts, while another study showed no differences between males and females in terms of their growth expectations among US PSED respondents (Matthew & Human, 2000). This paper includes a theoretical framework to support the development of our hypotheses.

H5a: There is an effect of personal characteristics on SE. H5b There is an effect of personal characteristics on OP. H5c There is an effect of personal characteristics on MO. H5d There is an effect of personal characteristics on EB.

We compare and contrast the personal characteristics of entrepreneurs to identify gaps in EB, specifically SE, OP, and MO. There are several important areas where this study makes an original contribution to the literature. The focus of our survey is based on four core themes: SE, OP, MO, and EB. In addition, this study contributes to the knowledge of the impact of SE, MO, and OP on EB among shop-on-wheel businesses. To the best of our knowledge, this study is the first to examine the characteristics and behavior of shop-on-wheel entrepreneurs. Additionally, this study is the first to examine the associations among SE, OP, MO, and EB in terms of shop- on-wheel experiences. Most studies focused on behavior have examined entrepreneurial practice opportunities or the impact of SE on entrepreneurship. A few studies have mentioned a positive association between EBs and achievement MOs. We hope the findings of this study will be utilized by others to compare EB in publications. Additionally, there are different proportions of shop-on-wheel businesses that are well known, and such businesses have spread in foreign countries. Such businesses are one of the new and innovative businesses that have appeared significantly in Arab countries in recent times, requiring a small amount of capital to start a business.

Method

Design and Sample

This paper uses quantitative data analysis to address and evaluate our research hypotheses related to SE, MO, OP, on EB. Additionally, we use descriptive analysis, one-way ANOVA, t-tests, linear regression, and correlation analysis as appropriate.

This analysis aimed to test the association between the SE, MO, and OP of nascent entrepreneurs on EB in three different cities: Riyadh, Jeddah, and Dammam. Based on this method, it was possible to analyze some of the research hypotheses that were derived from the literature review. The SE of entrepreneurs allows us to understand the complexity of entrepreneurial activities. Entrepreneurs have been criticized based on the difference between opportunities and necessity due to changes in EB, while there was an association between MO and EB. The Statistical Package for the Social Sciences (SPSS) version 20 was used for all analyses. The questionnaires for this study were adopted from different sources, such as the Kauffman Firm Survey (KFS), GEM data (Global Entrepreneurship Monitor 2012-2019), and the PSED.

Our hypotheses aim to examine the associations between SE, MO, and OP on EB of nascent entrepreneurs who started a shop-on-wheel business and to see whether there is a positive relationship between our independent variables and our dependent variable, EB. Additionally, because we are interested in the effect of personal characteristics on SE, OP, MO and EB, the data are based on three samples of randomly selected nascent entrepreneurs living in Saudi Arabia, which requires us to use random sampling to select entrepreneurs living in Riyadh, Jeddah, and Dammam.

Moreover, we distributed the survey in three different ways: first, we distributed self- administered questionnaires to our sample; second, questionnaires were given to a family to distribute in different cities; and third, questionnaires were given to a close friend to distribute to our sample. This process took us approximately one year; however, it allowed us to have a large amount of data to compare the three cities in the Middle East. The survey was carried out between summer 2019 and spring 2020, and 293 surveys were returned. The number of surveys that were invalid was 137 because of incomplete answers, and these surveys were removed from the final analysis.

Instrument Development

The instrument of this paper was a questionnaire that was adopted from the different sources mentioned above; however, the research instrument was a shop-on-wheel questionnaire, and the target was to gather the data we needed to profile such businesses. A review of the previous entrepreneur literature, especially studies describing nascent entrepreneurs, was performed. All of the questions were open-ended, allowing the participants to answer the questions in a short period of time. Furthermore, this paper targeted nascent entrepreneurs who started up their businesses in the past one to two months. In general, validity and reliability are needed in some research, and both are critical. Thus, the validity of the instrument indicates the degree to which the instrument measures what it is supposed to measure, which has an influence on the population of questions, while reliability provides consistent results (Creswell & Creswell, 2017).

In addition, all independent variables and dependent variables of this paper were included and analyzed in the final data set. For the other variables (characteristics of entrepreneurs), sum scores were calculated for each item. Furthermore, the researcher’s measurement knowledge of the type of variables used plays a crucial role in quantitative research, clarifying the research problems and developing the hypotheses (Kumar, 2019). The total number items in the survey was 42, and different scale levels of were used (nominal/ordinal). This use depended on the content and the design of the questionnaire. The sum scores for the SE, OP, MO, and EB items as well as the number of participants and their percentage are shown in Table 1. The items for the independent and dependent variables used a 5-point Likert scale. Additionally, there were questions regarding personal characteristics (demographic information), such as gender, age, and marital status.

Table 1 Distribution Mode
Questionnaire	Distribution mode- city	Number of  questionnaires distributed	Valid number	Invalid
Personal characteristics Self-efficacy Motivation  Opportunities and necessity Entrepreneurial behavior	Personally distributed Riyadh	250	198	52
Personal characteristics Self-efficacy Motivation  Opportunities and necessity Entrepreneurial behavior	Personally distributed and distributed by family Dammam	100	40	60
Personal characteristics Self-efficacy Motivation Opportunities and necessity Entrepreneurial behavior	Distributed by friends Jeddah	90	55	25

We utilized a multitude of data collection methods in three different cities to minimize bias to have different opinions of individuals rather than focusing on only one city. The survey also contains demographic characteristics such as entrepreneurs’ gender, age, marital status, educational level, major and other personal characteristics. Our shop-on-wheel sample included 42 questions distributed, and more details are given in Table 1 regarding the distribution mode based on the city.

Results

The results are discussed based on the personal characteristics of the entrepreneur respondents, starting with a description of their characteristics.

Demographic Variables

Table 2 shows a summary of the personal characteristics of the entrepreneur participants. The results show that the sample consists of 247 male and 46 female respondents. A total of 67.6% of the respondents were from Riyadh, 18.8% were from Jeddah, and the least, 13.7%, were from Dammam. The sample also includes individuals with varying age levels: 110 (37.5%) are 18-24 years of age, 152 (51.9%) are 25-34 years of age, and 28 (9.6%) are 45-44 years of age. More than 71.3% of the sample had a bachelor’s degree, while 14.7% had a primary school educational level. Moreover, 78.2% of individuals do not have any previous experiences, and for approximately 238 (81.25%) of the respondents, their parents were not involved in any business.

Table 2 Demographic Profile of the Respondents (N=293)
Variable name	Description	Number of respondent	Percentage (%)	Mean	Std. Dev.	Min.	Max.
Gender	1= Male	247	84.3	1.16	0.364	1	2
	2= Female	46	15.7
	1= 18-24	110	37.5
Age	2= 25-34	152	51.9	1.75	0.668	1	4
	3= 45-44	28	9.6
	4= 45-54	3	1
	1= Riyadh	198	67.6
City	2= Jeddah	55	18.8	1.46	0.723	1	3
	3= Dammam	40	13.7
	1= Single	144	49.1
Marital status	2= Married	131	44.7	1.57	0.608	1	3
	3= Divorced	18	6.1
	1= Primary school	43	14.7
	2= High school diploma 3= Bachelor’s degree	29	9.9
Educational level	4= Master’s degree	209	71.3	2.65	0.788	1	4
	5= Doctoral degree	12	4.1
		0	0
	1= Business management/finance/marketi ng/accounting/human resources	92	31.4
	2= Life sciences/health sciences/agriculture
	3= Social sciences
	4= Liberal arts/humanities	23	7.8
	5= Engineering
Major	6= Computer and information sciences 7=Mathematics/statistics 8= None	28	9.6	4	2.79	1	8
		32	10.9
		20	6.8
		12	4.1
		16	5.5
		70	23.9
	1= Government employee	89	30.4
Current employment status	2= Private employee	96	32.8	2.4	1.23	1	4
	3= Student	10	3.4
	4= Unemployed	98	33.4
Start-up experience	1= Yes	62	21.2
	2= No	229	78.2	1.8	0.421	1	3
	3= I do not know	2	7
Parents operated a business	1= Yes	55	18.8	1.81	0.391	1	2
	2= No	238	81.2

One-way ANOVA and a post hoc test were conducted to compare the effect of the independent variables and to observe any statistically significant differences between the means of our independent variables (gender, age, city, employment status, marital status, and educational level, whether parents operated a business, major, previous start-up experience, SE, OP and MO). ANOVA showed that there was a significant effect of the respondents’ major on EB, F (7, 0.056) = 2.618, p=0.012. The test indicated that the mean score for the major in computer and information sciences (M= 1.690, SD=.242) was significantly different from the mean score for the other majors. No significant differences were found for gender, age, city, employment status, marital status, educational level, whether parents operated a business, major, previous start-up experience, SE, OP, MO or EB

Additionally, comparing personal characteristics and SE, we found that the educational level and previous start-up experience of entrepreneurs are highly significant, F (3, 289) = 5.844, p= 0.001. As opposed to those with a different educational level (high school diploma, master’s degree), the mean score for those with a bachelor’s degree was M= 3.647, SD= 0.542, while for entrepreneurs who had previously started a business, the results show F (2, 290) = 9.596, p= 0.000, and the mean score for "I do not know" is M= 4.062, SD= 0.4419. In terms of OP, we found that for entrepreneurs whose parents own a business, the results show F (1, 291) = 7.356, p= 0.007, while the mean score for entrepreneurs whose parents do not have any business was M= 1.586, SD= 0.239.

Furthermore, regarding MO, we found that the effect of gender, marital status, educational level, major, and whether parents own a business were significant for males, F (1, 291) = 12.435, p= 0.000, (M= 3.874, SD= 0.6672), F (2, 290) = 10.423, p= 0.000, and the mean score for marital status was M= 4.011, SD= 0.670. Regarding educational level and the life sciences major, the results show F (3, 289) = 2.859, p= 0.037, and there is a significantly higher mean score for those with a bachelor’s degree (M= 3.886, SD= 0.7070), F (7,285) = 2.191, p= 0.035, (M= 4.094, SD= 0.722). For the respondents whose parents own a business, the results show F (1,291) = 47.031, p=0.000, and the post hoc test for the respondents whose parents do not own a business show M= 3.937, SD= 0.624.

Self-Efficacy Variables

We display the descriptive statistics of our variables, as we calculated the mean (μ) using the 5- point scale. Regarding the entrepreneurs’ SE, the scale ranged from completely agree (5) to completely disagree (1) to investigate the absolute difference in each item of each domain to check which item the respondents had the highest score on. The sample size is 293, and the highest mean was obtained for "The individual is confident to put in the effort needed to start up a business" (μ= 4.44, SD =1.123), where 72.7% (n=213) completely agree, followed by "Starting up a business is more desirable than other career opportunities" (μ= 4.41, SD = 1.142), where 72.4% (n=212) completely agree, and "You will be successful when confronting obstacles" (μ= 3.86, SD = 1.429), where 50.9% (n=149) completely agree.

Opportunities and Necessity Variables

The mean value of the OP item scale ranged from yes (1) to no (2) to I do not know (3). Interestingly, the mean for "This business introduces new products or services" (μ= 1.92, SD = 0.642) was the highest. For "This business develops more efficient production methods in a profitable manner" (μ= 1.77, SD = 0.657), 58.4% (n=171) of individuals answered "no". Additionally, 51.5% (n=151) of individuals answered "no" in response to "This business develops more efficient production methods in a profitable manner", while in response to "The most important motive for pursuing this opportunity" and starting a business, 67.9% (n=199) of respondents answered that it is to increase their personal income (μ= 1.75, SD = 0.511).

Motivation Variables

Additionally, the MO items also use a 5-point scale ranging strongly agree (5) to strongly disagree (1). Regarding the "Desire for independence and working for myself" (μ= 4.38, SD = 1.152), 72.4% of the respondents (n=212) strongly agree. Regarding "Flexibility in lifestyle", 71.3% of the participants (n=209) strongly agree (μ= 4.37, SD = 1.150). For "There is no limit on how long I would give the maximum effort to establish a business", 58.4% of the respondents (n=171) strongly agree (μ= 4.18, SD = 1.268).

Entrepreneurial Behavior Variables

Regarding EB, the items use a scale consisting of yes (1) and no (2), and some items include I do not know (3). The highest mean was found for "Attending or had attended classes on starting a business", where 34.8% of the participants (n=102) attended classes (μ= 1.99, SD = 0.830), followed by "We had a business plan", where 48.1% of the respondents (n=141) had a business plan (μ= 1.72, SD = 0.782). In response to "Were in the process of developing a product or service", 63.8% (n=187) of the respondents answered no (μ= 1.64, SD = 0.481).

Simple Linear Regression

Linear regression analysis was carried out, and the results are presented in Table 4. To determine the linear regression coefficients, the statistical significance of the t-value in our model and the values of SE, OP, and MO and personal characteristics (independent variables) contributed by the dependent variable (EB) as well as the multiple correlation coefficient (adjusted R²) were determined based on two hundred ninety-three samples (n=293). We developed models that are shown as follows Table 3:

Table 3 Linear Regression
					95% CI
Dependent	Predictor	t value	Β	Sig.	for B		Tolerance	VIF
					Lower bound	Upper bound
EB	SE	1.124	0.03	0.262	-0.022	0.081	0.893	1.12
EB	OP	-0.816	-0.048	0.415	-0.163	0.068	0.973	1.028
EB	MO	0.519	0.011	0.604	-0.023	0.054	0.894	1.118
EB	Gender	1.375	0.054	0.17	-0.023	0.132	0.932	1.073
EB	Age	-0.911	-0.022	0.363	-0.068	0.025	0.773	1.294
EB	City	-0.726	-0.043	0.468	-0.053	0.025	0.949	1.054
EB	Marital status	-0.231	-0.006	0.817	-0.055	0.043	0.842	1.187
EB	Educational level	-0.628	-0.015	0.531	-0.063	0.032	0.548	.1.826
EB	Major	-2.626	-0.018	0.009	-0.031	-0.004	0.553	1.807
EB	Employment status	-1.04	-0.012	0.299	-0.035	0.011	0.962	1.04
EB	Previous start-up	1.348	0.047	0.179	-0.022	0.117	0.884	1.131
EB	Parents own a business	-0.612	-0.023	0.541	-0.096	-0.051	0.91	1.098

The linear regression established to predict the EB dependent variable showed that SE, OP, and MO did not predict EB (R = 0.100, R² = 0.010, df = 3, p=0.408). The value of 0.010 indicates that the independent variables explain only 10% of the variance in the dependent variable which is not significant, which means that 90% was determined by other factors. Moreover, we examined whether personal characteristics significantly predicted EB (R = 0.241, R² = 0.058, df= 9, p=.048). In regard to the personal characteristic categories, the value of 0.058 indicates that they explain nearly 6% of the variance in EB. This means that ~6% of EB is determined by personal characteristics and that 94% is determined by other factors, as shown in Table 3. In summary, it appears that personal characteristics, such as SE, OP, and MO, explain approximately 18% of EB, while other factors not identified in the present study explain 82%.

In summary, our hypothesis regarding a positive association between SE and EB (H1) is rejected. The hypothesis regarding a positive association between OP and EB (H2) is also rejected, the hypothesis regarding a positive association between MO and EB (H3) is rejected. However, SE, OP, and MO dos not statistically explain the nascent behavior of entrepreneurs (H4).

Correlation Coefficients

Our hypotheses identify the associations between three independent variables, namely, SE, OP, and MO, on EB and we calculate the degree of linear correlation between our variables (Feng, Zhu, Zhuang, & Yu, 2019). Thus, Pearson correlation analysis is used in this paper to evaluate the strength of our variables based on the correlation coefficient (r). The p-value of the correlation is computed to determine whether our items are correlated or not, and the strength of the relationship (r) is considered strong when the value is -/+0.7 and above, moderate when the value is -/+ 0.3 to 0.7 or weak when the value is -/+ 0.0 to 0.3, which allows us to determine either a positive or negative correlation between our variables. An association is considered significant at the 0.05 level. Figure 1 presents the coefficients of correlation between SE, OP, MO, EB and gender, age, city, marital status, employment status, previous start-up experience, major, educational level, and whether parents who own a business. There is a negative correlation between MO and gender (r= -0.202, p=0.000) and marital status (r = 0.150, p=0.010). In addition, there is a correlation between MO and having parents who own an established business (r = 0.373, p=0.000), previous entrepreneurial experience (r = 0.230, p=0.000), and educational level (r = 0.118, p=0.044), and SE correlates with MO (r = 0.300, p=0.000).

No significant correlation was observed between employment status and SE, OP, MO, or EB. The total correlation between SE, OP, MO, and EB was not significant. Significant negative correlations were detected between SE and EB (r = -0.154, p=0.008). SE has a negative correlation with age (r = -0.121, p=0.038) and previous entrepreneurial experience (r = 0.249, p=0.000), and there are negative correlations between SE and major (r = -0.154, p=0.008) and having parents who own a business (r = 0.217, p=0.000).

Additionally, another correlation was detected between OP and having parents who have their own business (r = 0.157, p=0.007). EB is negatively correlated with major (r = -0.179, p=0.002). However, strongly significant coefficients were observed for the correlation between MO and having parents who have their own business, and MO is strongly correlated with the SE of entrepreneurs.

Personal characteristics influenced SE, OP and MO. We found that MO correlated with gender, marital status, educational level, previous business experiences, and having parents who own a business, and EB was correlated with only age, while EB correlated with the respondents’ major, and OP was correlated only with having parents who own their own business. Thus, H5a, H5b, H5c, and H5d, which state that there is an effect of personal characteristics on SE, OP, MO, and EB, respectively, are accepted (Figure 2).

Discussion

As mentioned above, shop-on-wheel businesses are projects that are popular and that have spread globally. They are widespread in the United States, England, Canada and various parts of Europe and the world, and recently, they have spread widely in Arab cities in general and in Saudi Arabia in particular, where the first such business appeared in the Kingdom in 2016. Since then, such start-ups have spread to the point where there are thousands of vehicles in different cities. Examining the reasons that have led to the spread of this kind of business, we find that there are many: the cost of establishment compared to fixed restaurants, the nonpayment of rents, freedom of movement and the ability to be present at the sites of events and gatherings and to offer cheap products compared to the products sold by fixed restaurants. Shop-on-wheel businesses are businesses that many people prefer over restaurants and fixed shops. Therefore, it is never a bad idea to start a shop-on-wheel business, and doing so may bring great success and profits in any Arab city.

The idea of starting a small, profitable and inexpensive business has become a dream for many people, especially young people, at the beginning of their scientific careers, with little capital available to them.

The findings of this paper are of interest for several reasons. First, this study is the first to investigate the SE, OP, MO and personal characteristics on EB of individuals who have created a
business in the last year and whose business is a shop-on-wheel business. We believe that there is an advantage to choosing shop-on-wheel businesses due to the rarity of research on this type of business. Second, this paper contributes to theory as discussed above. We argue that this study is the first to investigate the relationships among SE, OP, MO and EB.

The goal of our study was to assess the effect of SE, OP, and MO on EB among nascent entrepreneurs in the first year of their business start-up. Overall, our results support some of our hypotheses. According to a report from the PSED, 57% of nascent entrepreneurs “spent a lot of time thinking about starting business”, which supports our overall finding regarding EB. Our study showed that 69.6% of our entrepreneur respondents are thinking about starting up a business and that 34.8% “took classes on starting a business”, compared to 16% in the PSED report. According to our findings, 58.0% of our participants are saving money to start up their business, compared to 15% in another study (Carter et al., 2003). Importantly, the results of this paper confirm some of the findings of such entrepreneurial SE (H. Zhao, Seibert, & Hills, 2005). We confirmed that entrepreneurs with high SE and MO to succeed in completing new tasks and gaining abilities will start a business, achieve other important goals, have the advantages of flexibility and independence and obtain the economic opportunity to start a business. As the unique contribution of this paper, we found a strong correlation between MO and previous start- up experience; additionally, entrepreneurs whose parents operate a business are more motivated to start up their own business. However, our paper showed that 78.2% of our respondents did not have previous start-up experience but became entrepreneurs, and for 81.2% of them, their parents do not have a business.

This finding is consistent with Morris and Lewis (1995), who agreed that the development of entrepreneurs is influenced by family background experiences and their previous start-up business experiences. Having a successful role model in the family, business network, and workplace is considered an advantage for entrepreneurs Aldrich (1999). In agreement with Alessa (2018), the environment and encouragement from the family that surrounds individuals will motivate entrepreneurs to start up a business. Interestingly, we found a strong link between EB and the major of entrepreneurs while studying at university, such as business management, social sciences, and engineering. Individuals who majored in business had the most potential to start up a business, followed by individuals who did not have any major (i.e., "none") (31.4% and 23.9%, respectively). Additionally, this paper established a strong motivational link between having parents who own a business and SE that leads individuals to start their business, and 37.5% of our sample entrepreneurs completely agree in regard to being motivated by success when preforming new tasks and engaging in similar tasks (Bandura, 1999). We found that gender differences can play an important role in motivating individuals to be entrepreneurs. In agreement with Lückgen et al. (2004), there is a relationship between nascent entrepreneurship and gender. Males are more involved than females in creating a business. As a result, EB is less likely to be related to other variables that we tested, i.e., SE, OP, and MO. Consistent with our hypotheses, we found strong ties between SE and MO and educational level (primary school, high school diploma, bachelor’s degree, master’s degree), increasing the SE and MO to start a business. Conversely, EB is not associated with the educational level of entrepreneurs. In agreement with Mota et al. (2019), the advantages of good opportunities and better opportunities lead individuals to start their own business.

More generally, the study findings with regard to the SE and MO of nascent entrepreneurs are of interest and are consistent with those of Mota et al. (2019), who show that individuals start a business for many reasons, and one important reason is motivation, such as being an entrepreneur or the need to be an entrepreneur. However, our study’s findings are inconsistent with those of research showing the importance of independence for nascent entrepreneurs; this paper found a mean of 1.75 for both male and female entrepreneurs, compared to the mean of 4.25 in the other study. Regarding MO, this paper found the highest mean for the idea that individuals would rather have their own business than pursue another promising career (Cassar, 2007).

Comparing our findings to those from studies conducted in other countries, we find that there are positive effects of individuals who had a business plan, compared to Swedish nascent entrepreneurs (Honig & Karlsson, 2004). Thus, this paper’s findings are inconsistent with those regarding Swedish nascent entrepreneurs, who show a positive economic MO, while our findings indicate that individuals prioritize independence and flexibility rather than taking advantage of economic opportunities and other alternatives such as unemployment (Reynolds et al, 2003). Additionally, the findings do not support extant theories suggesting that to start a business, individuals need a strong business MO (Omar et al., 2019). However, individuals have many reasons for starting a business, such as personal interest, financial success, independence, and self-actualization (Carter et al., 2003).

Importantly, our paper agrees with Gartner and Carter (2003), who find that regarding EB, 57% of individuals "spent a lot of time thinking about starting a business"; we obtain a strong positive result, with 69.6% of individuals thinking a lot about starting a business. In addition, in their sample, 16% of participants "took classes or workshops on starting a business", 15% were "saving money to invest in business", and 14% and 12% "developed models or procedures for a product/service". However, our findings show higher percentages, with 34.8% of our respondents taking business classes, 58% saving money to start up a business, and 36.2% being "in the process of developing a product or service".

Limitation and Future Research

Several limitations need to be taken into consideration. First, our sample is focused on shop-on- wheel businesses, and no other study has examined this domain; therefore, there are limited data for comparison. However, we believe that our findings provide valuable insights into the EB of individuals in regard to starting a business, and they contribute to the scarce research on this sample, where more variables need to be added and considered to focus more on this sample. Second, while this study investigated SE, OP, and MO on EP other factors and variables might impact nascent entrepreneurs. Third, this study involves both men and women, but there are fewer women than men in our sample. We agree that we cannot generalize our findings from this sample of individual entrepreneurs. In fact, we cannot know the exact number of shop-on-wheel businesses and the types of businesses that there are, which provides us with further research opportunities.

Further research might be needed where our questionnaires may have missed capturing nascent entrepreneurs, and our dependent variable, EB, may have not captured the reality of Saudi individuals; thus, more in-depth questions are needed to explore EB. However, the reasons individuals start a shop-on-wheel business, such as independence, opportunities, and flexibility, might be similar to those for any other type of business. This result has major implications for research and practice.

We believe that all reasons mentioned in prior research are not limited to nascent entrepreneurs (Gartner & Carter, 2003). While we consider these general reasons, researchers need to conduct in-depth research to investigate other matters that might be found for individuals. Importantly, our findings push us to find other EB factors that affect individuals’ decision to start up a business (Gartner & Carter, 2003). Consequently, SE and business plans have a significant impact on career choice (Krueger Jr et al., 2000), but based on our findings, we believe that regardless of what kind of business individuals create, SE, OP, MO and business plans are important. It is important to have a business plan study for any business as well as for shop-on-wheel businesses if people intend to establish this kind of business because such a business is suitable for those who do not have enough money to set up a different business. The only resources required are the money to cover the cost of a small truck and some initial equipment. Importantly, to test our variables, we did not study data from small towns, which may be different from major cities. Future research is needed to compare the EB in small town to that in major cities.

Conclusion

This research provides evidence that SE, OP and MO has no association with EB individual, while SE has a positive association with MO. The current study showed that general feasibility studies are needed to start up a business. Flexibility, and opportunities in addition to other factors lead nascent entrepreneurs to create their business. Meanwhile, our participants indicated the need to overcome the constraints faced by nascent entrepreneurs in Saudi Arabia, such as the lack of economic opportunities, as an alternative for unemployment. This study conducts data collection in different ways in three different cities to minimize bias instead of focusing on the capital city or different cities. However, one issue that should not be underestimated is that there is scarce research on shop-on-wheel businesses. Moreover, regarding shop-on-wheel businesses, over the past few years, Saudi Arabia have seen an increased number of mobile food vehicles and other business vehicles in different cities in the Kingdom as new and innovative businesses. We believe the results of this study will contribute to previous and future research.

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