Chapter 2: literature review Introduction: 2-1 Underpinning theories: To provide evidence for the hypothesized relationships proposed by this study, t
Chapter 2: literature revie
Introduction:
2-1 Underpinning theories:
To provide evidence for the hypothesized relationships proposed by this study, this research will make use of the following established theories generated by prior scholars.
Theory of planned behavior:
The concept of the Theory of Planned Behavior (TBP) was derived from a previous theory named the theory of reasoned action. It was introduced for the first time by Icek Ajzen (1985). Each theory suggests that an individual's intentions and attitudes towards a certain behavior are influenced by comprehending their behavioral beliefs, normative convictions along with social norms of their social environment. The dissimilarity between TRA and TBP results in greater possibility to comprehend one’s actual attitudes through the latter which leads to physical behavior (Martin, 2017). Perceived Behavioral Control is considered as its primary strength since it helps determine whether an individual truly believes in having authority over their desired behavior or not. (U.S. Department of Health and Human Services, 2005).
The Theory of Planned Behavior as illustrated in the figure below is comprised of three components: personal attitude, perceived behavioral control and the subjective norms of society. All these things affect a person's intention and, in the end, their actual behavior.
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Source: https://ua.pressbooks.pub/persuasiontheoryinaction/chapter/theory-of-planned-behavior/
According to (Ajzen, 1991), Behavioral intentions denote the motivational elements that shape behavior. The greater the strength of the intention to engage in a particular behavior, the greater the probability of executing that behavior. The degree to which an individual approves or disapproves of a particular behavior is indicative of their attitude towards it. This attitude is influenced by their beliefs about the behavior and their evaluation of its consequences. subjective norm, conversely, embodies the influence of social pressure on an individual's decision to engage or abstain from a particular behavior. It is the fusion of normative beliefs and the motivation to conform. The TPB accords significant importance to perceived behavioral control, which indicates an individual's perception of the level of ease or difficulty associated with executing a particular behavior.
The scope of this theory is broad, as it can be utilized in a multitude of fields and industries, including healthcare, politics, and general businesses and organizations. The theory's core concept revolves around understanding and predicting human behaviors, which accounts for its extensive range of applications (Martin, 2017). Intentional planning is a prerequisite for engaging in entrepreneurial activity. Therefore, the entrepreneurial intention (EI) can be measured using the theory of planned behavior (TPB).
Big five personality traits theory:
The aim of the literature review was to identify various personal traits that could potentially exist. Various numbers have been suggested by previous theories. Gordon Allport's list consisted of 4,000 personality traits, Raymond Cattell identified 16 personality factors, and Hans Eysenck proposed a three-factor theory. Some researchers found Cattell's theory to be overly complex, while Eysenck's was viewed as too restricted in its scope. Hence, the Big 5 personality traits were developed to describe the general traits that constitute personality. Several experts support the notion that personality can be categorized into five central traits. Over time, psychology has found increasing proof to support this hypothesis, commencing with D.W. Fiske's research in 1949 and subsequently explicated by other researchers such as Norman (1967), Smith (1967), Goldberg (1981), and McCrae & Costa (1987) (Cherry, 2023). The model is constituted by five essential personality traits, known as OCEAN which represent conscientiousness, neuroticism, agreeableness, extraversion, and openness to experience. The five-factor model not only facilitates individuals in comprehending their traits and distinguishing them from others but also enables the examination of the correlation between personality and many aspects of life, such as physical health, well-being, social status, academic performance, and professional success. The five-taxonomy model is an effective means of comprehending the distinct personalities of individuals in diverse populations. This study is founded on the big five personality theory.
2-2 Literature review findings review:
Digital entrepreneurship:
Digital entrepreneurship, as per Hull et al (2007, p.293), is “a subcategory of entrepreneurship in which some or all of the physical components of an organization have been digitized”. Thus, an organization's products and services, distribution channels, workplace, and all other physical aspects can be converted into a digital format.? this can be viewed as the unification of conventional entrepreneurship with the novel approach of conducting and establishing business in the digital era (Le Dinh et al., 2018, p. 1). In a slightly different take on the matter, Davidson and Vaat (2010) have posited that digital entrepreneurship involves the pursuit of new business opportunities that are made possible by the emergence of new media and internet technologies. Sussan and Acs (2017, p. 66) introduced a wider perspective on digital entrepreneurship by including the user dimension, which involves any agent participating in a venture that utilizes digital technologies, regardless of its purpose - whether it is commercial, social, government, or corporate. The basic principles of identifying opportunities, generating ideas, and commercializing products/services are comparable in both traditional and digital entrepreneurship (Ngoasong, 2018). The distinction between them is based on their business models, along with the approach taken by entrepreneurs in handling their products, setting marketing strategies, and managing online distribution (HAIR et al., 2012). Digital entrepreneurship can be classified into three categories, namely mild, moderate, and extreme, based on the level of technology tools integration in venture-related activities. In the case of mild digital entrepreneurship, the website serves as a complement to the physical aspect of the business, whereas in moderate digital entrepreneurship, the marketing function is digitized. In the extreme type, the website is one of the digital interfaces where the product is entirely digital (Hull et al., 2007).?
Entrepreneurship intentions:
The concept of Entrepreneurial intention refers to an individual's inclination to create a new business venture at some point in the future (Thompson, 2009). Bird (1988) defines entrepreneurial intention as a purposeful state of mind that guides an individual's attention towards achieving the goal of developing a venture. Using these definitions, we can define digital entrepreneurship intentions as the aspirations and objectives of a person to exploit the capabilities of digital technologies, such as the internet, social media, mobile devices, and cloud computing to establish an innovative business model in the future. The research area of entrepreneurial intentions has been extensively covered with numerous studies, but digital entrepreneurship has not received the same level of attention and needs to be explored Thoroughly. Several theoretical frameworks were used to assess technology and digital entrepreneurship intentions comprising psychological career theory (Millman et al., 2010), goal setting theory (Chang et al., 2018), social cognitive career theory (Chen and Claire, 2013), and many others, but the scarcity of studies suggests that only a few variables have been examined. In this study we will use the TPB theory, and the big five personality trait model to examine the entrepreneurial intentions among university students in Morocco.
Personal traits:
There are two distinct schools of thought that aim to explain the choices and decision-making processes of an individual. The first group emphasizes on demographic features (e.g., Bem, 1981), while the other is dedicated to exploring psychological factors such as personality (e.g., Ajzen, 1991). The literature has demonstrated that personality traits play a significant role in influencing entrepreneurial intention. Personality traits are the durable and consistent psychological characteristics that individuals have (Costa and McCrae, 1992). Conscientiousness stands out for its high levels of organization, determination, thoughtfulness, good impulse control, and goal-directed behaviors (Talwar et al., 2022). People who are highly conscientious are typically detail-oriented and organized. They tend to think ahead, consider the impact of their actions on others, and respect deadlines. Neuroticism is a personality trait that is marked by a negative emotional state, which can lead to emotional instability. This trait is often linked to feelings of anxiety, depression, moodiness, guilt, anger, distress, insecurity, and aggression (Talwar et al., 2022). Those who score lower in this personality trait are generally more stable and better equipped to handle emotional challenges. Agreeableness is characterized by a variety of positive attributes, including trust, altruism, kindness, affection, and other prosocial behaviors (Power & Pluess, 2015). Agreeable individuals are more likely to display empathy and cooperative behavior, whereas those lacking in this personality trait are more inclined towards nastiness and competitive and manipulative behavior. The trait of extroversion or extraversion is distinguished by high levels of excitement, sociability, talkativeness, assertiveness, and a willingness to express emotions more openly (Power & Pluess, 2015). Extraverted individuals are sociable and tend to derive energy from social interactions. They feel stimulated and enthusiastic when surrounded by others. When compared to the other five personality traits, openness (also known as openness to experience) gives the most importance to imagination and insight (Power & Pluess, 2015). Individuals with a high degree of openness tend to have diverse interests. They are naturally curious and find the world and other people captivating. They are excited to learn new things and enjoy experiencing new things. It is widely accepted that men and women have more similarities than what traditional social science suggests, although there are some exceptions. In 2011, Weinsberg and DeYoung conducted a study that focused on the analysis of the five major personality traits, with a specific emphasis on how gender affects them. Results revealed that women tend to score higher than men in Extraversion, Agreeableness, and Neuroticism. Other studies have found that while there may be differences, some qualities are not entirely distinct. As people age, their behavioral traits, such as agreeableness and extraversion, tend to align, resulting in lower scores for both genders (2022).
2-3 Hypotheses design:
Openness to experience and digital entrepreneurship intentions:
Individuals who possess this personality trait exhibit curiosity, open-mindedness, and creativity. They have a strong desire to explore and uncover new and innovative concepts and ideas, much like entrepreneurs. (Costa & McCrae, 1992; Zhao & Seibert, 2006; Ariani, 2013). The ability to recognize opportunities in entrepreneurship is significantly associated with imagination, creativity, and a willingness to embrace new ideas (Ciavarella et al., 2004). One of the defining characteristics that sets entrepreneurs apart from non-entrepreneurs is their possession of key traits such as openness to experience, emotional stability, and extraversion (Chan et al., 2015). Self-employment is a mode of work that is not widely adopted and is more attractive to those who are willing to embrace atypical lifestyles. Consequently, we theorize that:
H1: Openness to experience is positively linked to digital entrepreneurship intentions.
Conscientiousness and digital entrepreneurial intentions:
The personality trait of Conscientiousness reflects an individual's drive for success, discipline, perseverance, organization and planning, the level of adherence to conventional norms, and consideration for others (Ariani, 2013; Roberts et al., 2005; Costa & McCrae, 1992). According to Locke (2000), entrepreneurship is often linked with work goal orientation, hard work, and perseverance in the face of challenging obstacles. It also sounds more appealing to individuals with a high need for achievement, as it provides them with complete autonomy over results, moderate exposure to failure, and instant and explicit evaluation of their performance more than conventional employment options (McClelland, 1961). Connor-Smith and Falshsbart (2007) found that individuals with conscientiousness tend to excel in solving concrete problems due to their ability to organize their thoughts effectively. Zhao et al. (2009) conducted a meta-analysis that identified conscientiousness as a powerful and reliable predictor of entrepreneurial intentions. Ahmed et al., (2020), ?ahin et al., (2019), and more researchers reported these same results, further supporting the importance of conscientiousness in entrepreneurial pursuits. The evidence is believed to be sufficient to suggest the following hypothesis:
H2: Conscientiousness and digital entrepreneurial intentions have a positive association.
Extraversion and digital entrepreneurial intentions:
People who score high on extraversion are often outgoing, friendly, warm, and sociable. They are full of energy, dynamism, confidence, and dominance in social gatherings. They tend to have a more optimistic outlook on life and experience positive emotions more frequently. Additionally, they have a desire for excitement and stimulation (e.g., Goldberg, 1990; Costa & McCrae, 1992; Baron, 1999; Locke, 2000). An entrepreneurial career can be perceived as more appealing than traditional employment, making it a more attractive option for extroverted individuals. Those who possess an entrepreneurial mindset tend to score high on the extraversion trait (Howard and Howard, 1995). However, the inconclusive results regarding this trait prevent full support of the relationship. The correlation between extraversion and entrepreneurial intentions was deemed insignificant by Zhao and Seibert (2006), Ahmed et al., (2020), and Sobaih & Elshaer, (2022). In contrast to the previous statement, the findings of Rauch and Frese (2007), Zhao et al., (2009), and ?ahin et al., (2019) provided evidence of a strong and significant association between the two attributes. Based on the collective evidence, we can infer the following:
H3: There is a strong positive correlation between extraversion and digital entrepreneurial intentions.
Agreeableness and digital entrepreneurial intentions:?
Agreeableness is a measure of how one interacts and behaves with other individuals. Individuals who score high on agreeableness are recognized for being trustworthy, altruistic, cooperative, and humble. They show empathy and care for the well-being of others and usually give in to others during disagreements. An individual who lacks agreeableness can be described as manipulative, self-centered, suspicious, and ruthless (Zhao et al., 2009). While patience, cooperation, and friendliness are valuable traits for entrepreneurs, they alone are insufficient for achieving success in the business world. Entrepreneurs must also demonstrate motivation and energy, which may require them to temporarily suspend their social life (Antoncic et al., 2015). According to Zhao and Seibert (2006), the survival of entrepreneurial firms necessitates entrepreneurs to be self-centered or even manipulative, even though agreeable people may not appreciate this approach. To keep their businesses running, entrepreneurs are often forced to make tough decisions that may have a negative impact on their former employers, partners, suppliers, and even their own personnel (Zhao et al., 2009). The literature suggests that there is a negative relationship between agreeableness and entrepreneurship intentions (e.g., Wooten, Timmerman, & Folger, 1999). other studies demonstrated that this correlation was insignificant (Zhao et al., 2009; Ahmed et al., 2020). While some studies proved a significant positive association between these attributes (Jain et al., 2022; Sobaih & Elshaer, 2022). Based on the previous discussion, we assume:
H4: Digital entrepreneurial intentions have an inverse correlation with agreeableness.
Neuroticism and digital entrepreneurial intentions:
Neuroticism or emotional instability is a factor that explains variations in emotional stability among individuals. People who score high in Neuroticism tend to experience a range of negative emotions, including hostility, anxiety, self-consciousness, low self-esteem, depression, sadness, vulnerability, and impulsiveness (Costa & McCrae, 1992; Zaho et al., 2009). Negative feedback tends to affect them deeply, causing them to become discouraged even by minor setbacks. According to academic literature and popular perception, entrepreneurs are often characterized as resilient, positive, and unwavering when confronted with social expectations, pressure, and unpredictability (Locke, 2000). An individual with a low level of neuroticism is characterized by exhibiting entrepreneurial traits and behaviors, such as taking on physical and emotional burdens and persevering in the face of obstacles, failures, or self-doubt. The success or failure of a new venture rests heavily on the shoulders of entrepreneurs, who bear a significant amount of personal responsibility (Baron & Markman, 1999; Zhao & Seibert, 2006; Zhao et al., 2009). This includes a demanding workload, leading and hiring employees, creating strategies, making crucial decision, and frequently facing substantial financial risks. Therefore, the likelihood of individuals initiating their own business ventures is higher among those with low neuroticism, whereas individuals with high neuroticism show a lower tendency towards starting their own businesses. From this, we can set the following hypothesis:?
H5: There is a significant negative correlation between neuroticism and digital entrepreneurial intentions.
Subjective norm and digital entrepreneurial intentions:
The intention to perform a behavior in TPB is shaped by three attitudinal antecedents that ultimately determine the behavior (Attitude toward behavior, subjective or social norm, and perceived behavioral control). The subjective norm refers to the perceived social pressure that influences an individual's decision to perform or avoid a particular behavior. The attitude and behavior of an individual towards a specific behavior can be influenced by the presence of social support from different sources, such as close relatives, friends, peers, mentors, employers, university, faculty, community, and others. (Ajzen, 1991). In Morocco, family members especially parents, hold the most significant influence over individuals due to their proximity. As such, they play a crucial role in shaping a person's behavior and actions.? Scholars have contended that subjective norms might be a crucial factor in promoting entrepreneurial behavior among individuals (Farooq et al., 2018). The impact of subjective norms on an individual's drive to excel with entrepreneurial intentions has been found to be positive in previous research (Zhang et al., 2015; Ahmad et al., 2019; Saraih et al., 2020; Noor and Malek, 2021). Thus, the following hypothesis can be proposed:
H6: Subjective norm affects positively digital entrepreneurial intentions.
Attitude and digital entrepreneurship intentions:
According to Ajzen (1987), attitude towards behavior refers to an individual's evaluation of the measures required to execute a particular action. The degree to which an individual considers something useful or not determines their attitude towards the activity (Ridha et al., 2017). TPB highlights that the first step towards entrepreneurial intention is the cultivation of an entrepreneurial attitude, which denotes an individual's behavioral inclination, affection, or predisposition towards a specific behavioral action (profession, career path). Entrepreneurial attitudes can be observed in the inclination towards finding the idea of starting a business interesting, taking entrepreneurship seriously, being drawn towards exploring business ideas, considering the possibility of starting a business, and experiencing personal fulfillment in doing so (Maydiantoro et al., 2021). The attitude towards entrepreneurship plays a vital role in molding the future entrepreneur. Students who possess the right attitude are more likely to be self-reliant and start their own business right after graduation (Yaacob & Wan Jusoh, 2004; Fitzsimmons & Douglas, 2005). Nabi and Holden (2008) suggest that the growing inclination of students towards entrepreneurship may lead to a rise in start-up ventures in the near future. The positive relationship between an individual's entrepreneurial intention and their entrepreneurial attitude has been supported by earlier research studies (Segal et al., 2005; Pruett et al., 2009; Bazan et al., 2019; Anwar et al., 2020). A comprehensive analysis of the literature has revealed that the TPB has been applied to assess the impact of behavior attitude on entrepreneurship intentions of university students in KSA (Sobaih & Elshaer, 2022), engineering and non-engineering students (Law & Breznik, 2016), South African Enactus students (Tshikovhi & Shambare, 2015), Austrian students (Schwarz et al., 2009), and business management students (Jena, 2020). The validity of this relationship in the Moroccan context will be confirmed through our investigation of the impact of attitude on entrepreneurial intentions among university students in Morocco. We propose the following hypothesis:
H7: There is a strong positive correlation between personal attitude and digital entrepreneurial intentions.
Subjective norm and attitude:
The classic TPB model suggested that the three antecedents mentioned earlier have independent effect on behavioral intention. Nevertheless, several scholars have claimed that the current socio-psychological theory is inadequate and requires additional causal pathways connecting these constructs (Han et al., 2020; Yeh et al., 2021). The research conducted by Han et al. (2020) indicated that there is a connection between attitude and subjective norm. A study conducted by (Wang et al., 2022) has demonstrated that the link between subjective norm and travel intention is partially mediated by attitude, as proved by the results of the mediation test. (Aziz et al., 2020) stated that here exists a noteworthy correlation between subjective norms and the attitude as well as the intention to procure family takaful schemes. The influence of subjective norm on behavioral intention was found to be insignificant in a recent study conducted by Yeh et al., (2021). As a result, they investigated the mediating effect of attitude between subjective norm and behavioral intention. Daxini et al. (2019) claimed that subjective norm influences not just attitude, but also perceived behavioral control. On a different note, Li and Wu (2019) argued that attitude is shaped by both subjective norm and perceived behavioral control. However, they solely focused on the analysis of supplementary paths, without any mention of the mediation effect. The connection between subjective norms and attitude has not been extensively investigated, despite evidence from a few studies indicating a meaningful association (Shimp & Kavas, 1984; Vallerand et al., 1992). The additional path between subjective norm and attitude holds particular importance in the present study, as we are going to assess both the relationship between subjective norms and personal attitude towards digital entrepreneurship intentions, and the mediating effect of attitude between subjective norms and digital entrepreneurship intentions. Hence, we suggest the following hypotheses:
H8: There is a positive relationship between subjective norms and personal attitudes toward digital entrepreneurship intentions.
H9: The Mediating Effect of Attitude to link between subjective norms and Digital entrepreneurship Intentions.
Personality traits and attitude towards digital entrepreneurship intentions:
The research conducted by Hu (2008) indicates that a positive association exists between Big-Five personality traits (particularly agreeableness, extraversion, conscientiousness, and openness to experience), and personal attitude towards entrepreneurship. On the other hand, neuroticism has a negative impact on this attitude. As per previous research (Lüthje & Franke, 2003; Schwarz et al., 2009), personality traits can play a role in shaping the attitude towards entrepreneurship, which is considered as one of the most significant factors determining entrepreneurial intention, as stated. In light of the literature, we put forth the following hypotheses:
H10: openness to experience has an impact on personal attitude towards digital entrepreneurship intentions.
H11: Conscientiousness has an impact on personal attitude towards digital entrepreneurship intentions.
H12: Extraversion has an impact on personal attitude towards digital entrepreneurship intentions.
H13: Agreeableness has an impact on personal attitude towards digital entrepreneurship intentions.
H14: Neuroticism has an impact on personal attitude towards digital entrepreneurship intentions.
The mediation effect of attitude toward digital entrepreneurship on the relationship between big-five personality traits and digital entrepreneurial intentions:
The analysis of personal attributes indicated that they have a bearing on an individual's attitude towards entrepreneurship, which in turn affects their inclination towards starting a business. In their study, Jing and Sung (2012) found that individuals who possess dominant and energetic traits are more inclined towards entrepreneurship and tend to show a positive attitude towards it. This positive attitude, accordingly, has a favorable effect on their intention to pursue entrepreneurship. Entrepreneurship appeals more to individuals who are comfortable with taking risks and those who value being part of a team. Similarly, the more people are motivated to engage in strenuous work and exhibit persistence, the more their attraction towards entrepreneurship will amplify (Rothmann & Coetzer, 2003). Entrepreneurial intention cannot be solely determined by personality traits (Hu, 2008); hence individuals must consider the consequences of entrepreneurship which would help them cultivate a constructive attitude towards it. Results from Baron and Kenny (1986), and (Bazkiaei et al., 2020) confirmed that the link between personality traits and entrepreneurial intention is partially mediated by attitude towards entrepreneurship. This is because even with a mediator, the direct impact of big-five personality traits on entrepreneurial intention remains significant. As a result, the current research study put forward the following hypotheses:
H15: The link between openness to experience and digital entrepreneurial intentions is mediated by attitude towards entrepreneurship intentions.
H16: The link between conscientiousness and digital entrepreneurial intentions is mediated by attitude towards entrepreneurship intentions.
H17: The link between extraversion and digital entrepreneurial intentions is mediated by attitude towards entrepreneurship intentions.
H18: The link between agreeableness and digital entrepreneurial intentions is mediated by attitude towards entrepreneurship intentions.
H19: The link between neuroticism and digital entrepreneurial intentions is mediated by attitude towards entrepreneurship intentions.
Conceptual model:
Based on the big five model theory and the TPB theory, we have developed a model to understand Factors controlling students’ intentions to pursue digital entrepreneurial career in the future. This study has devised the following conceptual holistic model that treats the five personality traits as an independent variable measured using Openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism. Subjective norm is a second independent variable. Personal attitude towards digital entrepreneurship intentions is a mediating variable. Finally, the dependent variable is digital entrepreneurship intentions. The conceptual model was developed as a holistic model inspired by the framework stated by the authors (Sobaih & Elshaer, 2022) as shown below.
?
The authors' recommendation was to include subjective norms in future studies, which was considered after reviewing the existing literature and the available evidence on this matter. As a result, we decided to incorporate subjective norms into this framework and proposed a new relationship as our personal theoretical contribution.? Specifically, we hypothesized that subjective norm would serve as an independent variable in this model. As mentioned earlier, the classic TPB model postulates that the intention towards behavior is influenced by three independent variables, namely, attitude towards the behavior, subjective norm, and perceived behavioral control. However, Attitude has been found to act as a mediator between subjective norms and entrepreneurial intentions, as per recent research. Moreover, past studies have demonstrated a connection between subjective norm and attitude. Thus, it was crucial to consider these supplementary factors, to comprehend and forecast behavioral intention. This has resulted to the addition of the following relationship:?
Our proposed conceptual framework will be utilized to examine the subject: Analysis and Results
Missing Values
The missing values are find out to check that is any respondent exist in our data collection which did not respond our questionnaire.?
Statistics
Horodateur What is your gender? (Only mark one oval) How old are you? (Only mark one oval) What is you education level? (Only mark one oval) In which university/ institute? do you study? Where are you from? (Only mark one oval) What other suggestions do you have for this research?
N Valid 305 305 305 305 305 305 305
? Missing 0 0 0 0 0 0 0
Statistics
DEI1 DEI2 DEI3 ATB1 ATB2 ATB3 ATB4 AGR1 AGR2 AGR3 EXT1 EXT2 EXT3 CON1 CON2 CON3 CON4
N Valid 305 305 305 305 305 305 305 305 305 305 305 305 305 305 305 305 305
? Missing 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Statistics
OTE1 OTE2 OTE3 NEU1 NEU2 NEU3 SUN1 SUN2 SUN3 SUN4
N Valid 305 305 305 305 305 305 305 305 305 305
? Missing 0 0 0 0 0 0 0 0 0 0
The missing values are find out using the SPSS>Frequencies portion. There are total 305 values in our dataset and no one question has problem of missing values in our dataset.
Outlier Test
The outlier is the problem which most of time exist in the dataset. It can be check through boxplot, scatter plot, Mahalanobis method, etc. In our study the Mahalanobis method was utilized to check the outlier of multiple variables using the SPPS. Out of 305 values 43 values are removed on the base of Mahalanobis cut point range such as 43-47 or above.?
Normality Test
The normality test is use to check the behavior of dataset is dataset belongs to normal distribution or not. It can be check by Skewness, Kurtosis, Kolmogorov, Shapiro wilk method, etc. In our study it check through Kolmogorov-Smirnov method because our sample size is greater than 50 observations.?
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
? Statistic df Sig. Statistic df Sig.
DEI1 .303 262 .000 .801 262 .000
DEI2 .299 262 .000 .842 262 .000
DEI3 .232 262 .000 .882 262 .000
ATB1 .297 262 .000 .784 262 .000
ATB2 .313 262 .000 .796 262 .000
ATB3 .328 262 .000 .822 262 .000
ATB4 .290 262 .000 .813 262 .000
AGR1 .319 262 .000 .824 262 .000
AGR2 .202 262 .000 .902 262 .000
AGR3 .222 262 .000 .900 262 .000
EXT1 .260 262 .000 .884 262 .000
EXT2 .301 262 .000 .851 262 .000
EXT3 .213 262 .000 .887 262 .000
CON1 .314 262 .000 .843 262 .000
CON2 .232 262 .000 .888 262 .000
CON3 .313 262 .000 .827 262 .000
CON4 .216 262 .000 .898 262 .000
OTE1 .265 262 .000 .869 262 .000
OTE2 .277 262 .000 .862 262 .000
OTE3 .194 262 .000 .910 262 .000
NEU1 .278 262 .000 .867 262 .000
NEU2 .282 262 .000 .859 262 .000
NEU3 .179 262 .000 .911 262 .000
SUN1 .239 262 .000 .862 262 .000
SUN2 .288 262 .000 .824 262 .000
SUN3 .227 262 .000 .854 262 .000
SUN4 .232 262 .000 .887 262 .000
a. Lilliefors Significance Correction
Hypothesis
? Ho: Data follow Normality
? Ha: Data not follow Normality
The p-values of all variables is less than from 0.05 (alpha value) which indicate that there is no statistical evidence to reject Ho and conclude that our data follow normal distribution or normality.??
Descriptive statistics?
Statistics
N Median Range Minimum Maximum
? Valid Missing ?
OTE1 262 0 4.00 4 1 5
OTE2 262 0 4.00 4 1 5
OTE3 262 0 3.00 4 1 5
NEU1 262 0 2.00 4 1 5
NEU2 262 0 4.00 4 1 5
NEU3 262 0 3.00 4 1 5
SUN1 262 0 4.00 4 1 5
SUN2 262 0 4.00 4 1 5
SUN3 262 0 4.00 4 1 5
SUN4 262 0 4.00 4 1 5
DEI1 262 0 4.00 4 1 5
DEI2 262 0 4.00 4 1 5
DEI3 262 0 4.00 4 1 5
ATB1 262 0 4.00 4 1 5
ATB2 262 0 4.00 4 1 5
ATB3 262 0 4.00 4 1 5
ATB4 262 0 4.00 4 1 5
AGR1 262 0 4.00 4 1 5
AGR2 262 0 3.00 4 1 5
AGR3 262 0 3.00 4 1 5
EXT1 262 0 4.00 4 1 5
EXT2 262 0 4.00 4 1 5
EXT3 262 0 4.00 4 1 5
CON1 262 0 4.00 4 1 5
CON2 262 0 4.00 4 1 5
CON3 262 0 4.00 4 1 5
CON4 262 0 3.00 4 1 5
The above table present the Descriptive statistics of the DEI1, DEI2, DEI3, ATB1, ATB2, ATB3, ATB4, AGR1, AGR2, AGR3, EXT1, EXT2, EXT3, CON1, CON2, CON3, CON4, OTE1, OTE2, OTE3, NEU1, NEU2, NEU3, SUN1, SUN2, SUN3, and SUN4 variables. There is no missing values exist within variables and minimum value is 1, maximum value of all variables is 5, range is 4, and median is from 3 to 4 range of all variables.
Reliability Analysis
The reliability analysis is used to check the reliability or consistency of the samples. The Cronbach's alpha reliability coefficient should use to check the reliability which has normally ranges between 0 and 1. The closer Cronbach's alpha coefficient is to 1.0 the greater the internal consistency of the items in the scale.
Reliability Statistics
Cronbach's Alpha N of Items
.835 27
The Cronbach's alpha reliability coefficient should is .835 which is closer to 1 which indicate that greater internal consistency of the items in the scale.
Item-Total Statistics
Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted
DEI1 93.49 114.289 .503 .825
DEI2 93.77 113.401 .569 .823
DEI3 94.03 112.501 .556 .823
ATB1 93.41 113.829 .515 .825
ATB2 93.52 114.496 .513 .825
ATB3 93.70 114.218 .492 .825
ATB4 93.48 114.327 .506 .825
AGR1 93.67 116.635 .364 .829
AGR2 94.42 112.804 .393 .828
AGR3 94.32 113.949 .310 .832
EXT1 94.01 113.655 .426 .827
EXT2 93.81 115.123 .426 .827
EXT3 93.89 115.397 .333 .830
CON1 93.81 113.854 .423 .827
CON2 93.92 112.442 .426 .827
CON3 93.64 115.175 .411 .828
CON4 94.52 114.557 .285 .833
OTE1 93.77 116.420 .325 .831
OTE2 93.73 114.189 .449 .826
OTE3 94.33 115.066 .275 .834
NEU1 95.15 119.532 .116 .839
NEU2 94.28 121.589 .033 .842
NEU3 94.40 120.426 .088 .840
SUN1 93.66 117.321 .289 .832
SUN2 93.53 115.561 .402 .828
SUN3 93.58 114.612 .434 .827
SUN4 93.95 115.197 .349 .830
The reliability analysis revealed that our all question are reliable and questionable because all question has grater Cronbach's alpha reliability coefficient value which is close to 1.?
Factor Analysis or Exploratory Factor Analysis
The factor analysis has two type Exploratory Factor Analysis and confirmatory factor analysis. We use exploratory factor analysis to check how many factor should be made.
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .797
Bartlett's Test of Sphericity Approx. Chi-Square 2679.750
? df 351
? Sig. .000
The above table present the KMO and bartlett’s Test value which use to check the sampling adequacy exist or not. A KMO value greater than 0.60 acceptable which present the sampling adequacy exist in our dataset and in our case we have .797 which is wonderful value.? A significance level for the Bartlett's test below 0.05 suggest there is substantial correlation in the data in our case p-value is less than from 0.05 which indicate that substantial correlation in our variables.
Total Variance Explained
Component Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings
? Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %
1 6.266 23.206 23.206 6.266 23.206 23.206 3.956 14.651 14.651
2 2.336 8.652 31.859 2.336 8.652 31.859 2.450 9.075 23.725
3 2.263 8.381 40.240 2.263 8.381 40.240 2.408 8.919 32.645
4 2.064 7.645 47.885 2.064 7.645 47.885 2.336 8.652 41.296
5 1.393 5.158 53.042 1.393 5.158 53.042 2.085 7.721 49.017
6 1.356 5.023 58.065 1.356 5.023 58.065 1.949 7.219 56.236
7 1.137 4.210 62.275 1.137 4.210 62.275 1.631 6.039 62.275
8 .944 3.497 65.772
9 .921 3.411 69.183
10 .877 3.247 72.429
11 .757 2.805 75.234
12 .753 2.788 78.022
13 .615 2.277 80.299
14 .563 2.085 82.384
15 .551 2.042 84.426
16 .545 2.017 86.443
17 .487 1.804 88.247
18 .441 1.633 89.879
19 .420 1.556 91.436
20 .404 1.497 92.932
21 .358 1.328 94.260
22 .309 1.143 95.403
23 .307 1.136 96.540
24 .283 1.049 97.589
25 .253 .937 98.525
26 .206 .763 99.289
27 .192 .711 100.000
Extraction Method: Principal Component Analysis.
The above table present the total variance explained by the Exploratory factor analysis using the principle component analysis extraction method. The almost 62% variation explained by the seven factor which is acceptable for further analysis process.?
?
The above scree plot present there should be seven components should be made for DEI1, DEI2, DEI3, ATB1, ATB2, ATB3, ATB4, AGR1, AGR2, AGR3, EXT1, EXT2, EXT3, CON1, CON2, CON3, CON4, OTE1, OTE2, OTE3, NEU1, NEU2, NEU3, SUN1, SUN2, SUN3, and SUN4 variables. Where the line goes straight from right side which indicate the how many factor should be construct.?
Rotated Component Matrixa
Component
? 1 2 3 4 5 6 7
ATB2 .800
ATB1 .773
ATB4 .766
ATB3 .717
DEI1 .682 .447
DEI2 .662 .306
DEI3 .481 .452 .302
SUN2 .830
SUN3 .302 .687
SUN4 .686
SUN1 .655
CON2 .773
CON1 .626
CON3 .518 .436
EXT2 .770
EXT3 .765
EXT1 .646
AGR1 .384
CON4 .710
AGR2 .300 .654
AGR3 .450 .581
OTE3 .580
NEU2 .812
NEU3 .738
NEU1 .360 .678
OTE1 .304 .784
OTE2 .340 .693
Extraction Method: Principal Component Analysis.?
?Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 7 iterations.
The above table is rotated component matrix which explain which variable is belong to which factor on the base of factor loading or correlation.?
Correlation
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
? Statistic df Sig. Statistic df Sig.
Openess_to_experience .138 262 .000 .967 262 .000
Conscientiousness .100 262 .000 .978 262 .000
Extraversion .156 262 .000 .962 262 .000
Agreeableness .114 262 .000 .973 262 .000
Neuroticism .105 262 .000 .976 262 .000
Subjective_norm .139 262 .000 .946 262 .000
Attitude_toward_behaviour .192 262 .000 .895 262 .000
Digital_entrepreneurship_intention .192 262 .000 .895 262 .000
a. Lilliefors Significance Correction
The normality test performed on the Openess to experience, Conscientiousness, Extraversion, Agreeableness, Neuroticism, Subjective norm, Attitude toward behavior, Digital entrepreneurship intention. All variables does not follow the normality assumption because the p-value is less than? from 0.05 which indicate that we have to accept Ho( Null) Hypothesis and conclude that variables not follow normality.?
Correlations
Openess_to_experience Conscientiousness Extraversion Agreeableness Neuroticism Subjective_norm Attitude_toward_behaviour
Openess_to_experience 1 .429** .369** .326** .026 .318** .206**
? .000 .000 .000 .675 .000 .001
? 262 262 262 262 262 262 262
Conscientiousness .429** 1 .420** .454** -.021 .301** .332**
? .000 .000 .000 .741 .000 .000
? 262 262 262 262 262 262 262
Extraversion .369** .420** 1 .282** -.019 .183** .248**
? .000 .000 .000 .761 .003 .000
? 262 262 262 262 262 262 262
Agreeableness .326** .454** .282** 1 .077 .097 .341**
? .000 .000 .000 .215 .119 .000
? 262 262 262 262 262 262 262
Neuroticism .026 -.021 -.019 .077 1 -.020 .008
? .675 .741 .761 .215 .752 .899
? 262 262 262 262 262 262 262
Subjective_norm .318** .301** .183** .097 -.020 1 .403**
? .000 .000 .003 .119 .752 .000
? 262 262 262 262 262 262 262
Attitude_toward_behaviour .206** .332** .248** .341** .008 .403** 1
? .001 .000 .000 .000 .899 .000
? 262 262 262 262 262 262 262
Digital_entrepreneurship_intention .206** .332** .248** .341** .008 .403** 1.000**
? .001 .000 .000 .000 .899 .000 .000
? 262 262 262 262 262 262 262
**. Correlation is significant at the 0.01 level (2-tailed).
The above table present the correlation between the Openess to experience, Conscientiousness, Extraversion, Agreeableness, Neuroticism, Subjective norm, Attitude toward behavior, Digital entrepreneurship intention. There is significant positive small correlation (.429**) found between the Conscientiousness and Openess_to_experience. Similarly the Extraversion, Agreeableness, Subjective_norm, Attitude_toward_behaviour, Digital_entrepreneurship_intention also has significant small positive correlation such as (.369**,.326**, .318**, .206**, .206** ) respectively with Openess_to_experience.? The Conscientiousness has significant small positive correlation such as (.420**,.454**, .301**, .332**, .332** ) with Extraversion, Agreeableness, Subjective_norm, Attitude_toward_behaviour, and Digital_entrepreneurship_intention respectively. The Extraversion has significant small positive correlation such as (.282**, .183**, .248**, .248**) with Agreeableness, Subjective_norm, Attitude_toward_behaviour, and Digital entrepreneurship intention respectively. The Agreeableness has significant small positive correlation such as (.341**, .341**) with Attitude_toward_behaviour, and Digital entrepreneurship intention respectively. The Subjective_norm has significant small positive correlation such as (.403**, .403**) with Attitude_toward_behaviour, and Digital entrepreneurship intention respectively.
Regression
Descriptive Statistics
Mean Std. Deviation N
Digital_entrepreneurship_intention 4.0038 .64955 262
Openess_to_experience 3.5840 .68831 262
Conscientiousness 3.5573 .65949 262
Extraversion 3.6310 .74707 262
Agreeableness 3.3944 .72925 262
Neuroticism 2.9186 .81031 262
Subjective_norm 3.8502 .66970 262
The above table describe the Mean standard deviation of the Digital_entrepreneurship_intention,? Openess_to_experience, Conscientiousness, Extraversion, Agreeableness, Neuroticism, and Subjective_norm. There are 262 total observations of all variables and the center of these variables or average point presenting by Mean and variation present by standard deviation.?
Correlations
Digital_entrepreneurship_intention Openess_to_experience Conscientiousness Extraversion Agreeableness Neuroticism Subjective_norm
Digital_entrepreneurship_intention 1.000 .206 .332 .248 .341 .008 .403
Openess_to_experience .206 1.000 .429 .369 .326 .026 .318
Conscientiousness .332 .429 1.000 .420 .454 -.021 .301
Extraversion .248 .369 .420 1.000 .282 -.019 .183
Agreeableness .341 .326 .454 .282 1.000 .077 .097
Neuroticism .008 .026 -.021 -.019 .077 1.000 -.020
Subjective_norm .403 .318 .301 .183 .097 -.020 1.000
Digital_entrepreneurship_intention . .000 .000 .000 .000 .450 .000
Openess_to_experience .000 . .000 .000 .000 .337 .000
Conscientiousness .000 .000 . .000 .000 .370 .000
Extraversion .000 .000 .000 . .000 .381 .001
Agreeableness .000 .000 .000 .000 . .107 .059
Neuroticism .450 .337 .370 .381 .107 . .376
Subjective_norm .000 .000 .000 .001 .059 .376 .
Digital_entrepreneurship_intention 262 262 262 262 262 262 262
Openess_to_experience 262 262 262 262 262 262 262
Conscientiousness 262 262 262 262 262 262 262
Extraversion 262 262 262 262 262 262 262
Agreeableness 262 262 262 262 262 262 262
Neuroticism 262 262 262 262 262 262 262
Subjective_norm 262 262 262 262 262 262 262
Model Summaryb
Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics
? R Square Change F Change df1 df2 Sig. F Change
1 .521a .272 .255 .56080 .272 15.858 6 255 .000
a. Predictors: (Constant), Subjective_norm, Neuroticism, Agreeableness, Extraversion, Openess_to_experience, Conscientiousness
b. Dependent Variable: Digital_entrepreneurship_intention
The above table present the model summary in the form of R (overall correlation), R-square, F-value, degree of freedom (DF) and significant value. The R=.521 which indicate that there is small positive correlation exist between the Digital_entrepreneurship_intention and Subjective_norm, Neuroticism, Agreeableness, Extraversion, Openess_to_experience, Conscientiousness independent variables. The Adjusted R-square is .225 which explained that overall 22.5% our model is good fitted or 22.5% variation explained by independent variables on dependent variables. The F-value is significant?
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 29.924 6 4.987 15.858 .000b
? Residual 80.197 255 .314
? Total 110.121 261
a. Dependent Variable: Digital_entrepreneurship_intention
b. Predictors: (Constant), Subjective_norm, Neuroticism, Agreeableness, Extraversion, Openess_to_experience, Conscientiousness
The above present the F-value of ANOVA table with its significant value. The p-value is .000 which is less than from 0.05 which indicate that at least one independent variable has relationship with dependent variable.?
Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig. Correlations Collinearity Statistics
? B Std. Error Beta Zero-order Partial Part Tolerance VIF
1 (Constant) 1.494 .302 4.943 .000
? Openess_to_experience -.062 .059 -.066 -1.048 .296 .206 -.065 -.056 .720 1.390
? Conscientiousness .096 .066 .097 1.443 .150 .332 .090 .077 .628 1.592
? Extraversion .082 .053 .094 1.544 .124 .248 .096 .083 .774 1.292
? Agreeableness .230 .055 .258 4.197 .000 .341 .254 .224 .756 1.323
? Neuroticism .000 .043 .000 .008 .994 .008 .001 .000 .989 1.011
? Subjective_norm .342 .056 .352 6.108 .000 .403 .357 .326 .859 1.165
a. Dependent Variable: Digital_entrepreneurship_intention
The above table present the coefficient of regression of the model. The agreeableness and subjective norm has positive effect on Digital_entrepreneurship_intention because there p-value is less than from 0.05 which indicate statistical evidence of effect. Other all has no effect on Digital_entrepreneurship_intention variable. If we increase the one unit in Agreeableness then .230 positive change will show on Digital_entrepreneurship_intention and if we increase one unit in subjective norm then .342 positive change will show on Digital_entrepreneurship_intention. The tolerance is less than 4 and VIF also greater than 0.25 which indicate that there is no problem of multicollinearity exist.
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