“Exploratory and confirmatory factor analysis of digital entrepreneur skills”

Research in the field of entrepreneurship has become an intriguing area for further investigation. In an era where digital advancements are ubiquitous, previous researchers have identified a gap: the lack of a specific instrument to identify digital entrepre-neur skills. Therefore, this study aims to determine the constructs of students’ digital entrepreneur skills. The analysis techniques include confirmatory factor analysis (CFA), exploratory factor analysis (EFA), Pearson correlation, Kendall’s, Spearman’s, and Cronbach’s alpha. The study was conducted over five phases with 235 participants from university students in Indonesia who run or own a business. The results revealed strong instrument validity with robustness ranging from significant Pearson, Kendall’s, and Spearman’s analyses (<0.05) and Cronbach’s alpha (>0.60). The exploratory factor analysis indicated a Kaiser-Meyer-Olkin value of 0.954 (>0.05) and Bartlett’s test (0.000 < 0.05), with all items having values of anti-image (>0.50), communalities (> 0.50), and factor loadings (> 0.40), uncovering three components. Lastly, the CFA demonstrated an overall good fit model, with high first-order factor loadings (>0.60) and a second-order construct digital entrepreneur skills comprising three components: interpersonal digital skills with a factor loading of 0.890, idea and technology management skills (0.920), and adaptation and innovation skills (1.020). The study highlights the critical need for students to develop digital entrepreneurial skills encompassing interpersonal digital skills, ideation, and technology management, as well as adaptation and innovation abilities to thrive in the digital economy and enhance their personal and professional growth.


INTRODUCTION
Integrating technological advancements with entrepreneurial activities is becoming increasingly important in the rapidly evolving digital entrepreneurial landscape.This extends to the demand for enhanced capabilities.This relationship between digital technologies and entrepreneurship reshapes economic opportunities, driving innovation and influencing global business markets.This ultimate goal marks the urgency of further examination of this topic through a scientific approach.Digital transformation, characterized by the proliferation of digital tools and platforms, has democratized the entrepreneurial ecosystem, allowing individuals to launch and grow digital businesses more efficiently.Ease then becomes the framework of capability in preparing a generation ready for the changes in the ecosystem.However, while digital transformation simplifies some aspects of entrepreneurship, it also demands a unique set of skills to utilize its potential fully.Higher education has been highlighted as a place to serve as an incubator for skills development.The importance of higher education institutions in this context cannot be overstated, as they play a critical role in equipping students with the competencies required to thrive in the digital entrepreneurship ecosystem.These competencies cover a wide range of skills: computational ability, critical thinking, creativity, and basic entrepreneurial skills.

LITERATURE REVIEW
The field of digital entrepreneurship has become a crucial aspect, contributing to economic opportunities, innovation, and business markets (Elia et Wirtz, 2019).Hsieh and Wu (2019), Khumsamart (2022), Kuester et al. (2018), Song (2019), and Wirtz (2019) have argued that advancements in digitization have made it easier for individuals to initiate and develop digital business initiatives.For example, Anderson (2012) emphasized that digital transformation has facilitated online interactions within the industrial sector.However, despite the improved ease provided by digital transformation, digital transformation in the entrepreneurial sector still requires skills to harness its potential (Hsieh & Wu, 2019;Khumsamart, 2022;Kuester et al., 2018;Song, 2019;Wirtz, 2019).In this regard, the role of higher education institutions, such as universities and colleges, is central in equipping students with essential skills to effectively participate in the digital entrepreneurial ecosystem.These skills include specific abilities related to computation skills ( Winarno, 2016) have developed or analyzed entrepreneurial skills in a general sense.This created a need for more specific instruments to identify or reflect the digital entrepreneurial skills of individuals, particularly within the university context.This is of high urgency as identifying the fundamental aspects is crucial for enhancing entrepreneurial skills in the digital era.Therefore, the need for a valid instrument is paramount for further decision-making.To achieve a valid instrument, a series of validity tests are required to assess the reliability and factors formed by each statement item used.
Entrepreneurial skills are essential for individuals in the field of entrepreneurship (Gieure et al., 2019;Koyuncuoglu, 2021;Mojab et al., 2011).An entrepreneur is an individual who operates and maintains a business venture (Ratten, 2019).More specifically, these skills refer to the abilities and qualities that help individuals become more effective in running a business or entrepreneurial initiative (Meissner & Shmatko, 2019;Mojab et al., 2011).These skills are highly important in today's dynamic and competitive business world, and they can be developed under certain circumstances (Meissner & Shmatko, 2019).These skills can be reflected through teamwork skills, initiative, ambition, adaptability, flexibility, risk-taking, and a willingness to learn (Mojab et al., 2011).Unfortunately, previous instrument development in this area has left a gap in the form of entrepreneurial skills instruments that have not been adapted to the developments in the digital sector.Yet, the digital sector offers great opportunities for entrepreneurship (Elia et al., 2020;Hsieh & Wu, 2019;Kraus et al., 2019;Verhoef & Bijmolt, 2019;Wirtz, 2019).Digital entrepreneurship is an important aspect that contributes significantly to economic opportunity and innovation.However, previous research has shown a need for more development of specific instruments to measure digital entrepreneurship skills.Higher education, especially universities and colleges, equips students with the necessary skills to succeed in this field, including computational ability, critical thinking, and creativity.
This study aims to address the gap by conducting exploratory and confirmatory factor analysis to develop a valid and reliable instrument to measure digital entrepreneurship skills in university students.The hypothesis is as follows: H1: The newly developed instrument for measuring digital entrepreneurial skills among undergraduates is a valid and reliable tool capable of accurately assessing the specific competencies required for success in the digital entrepreneurship sector.
To achieve the set goal, the study identified three main components -interpersonal digital skills, ideation and technology management skills, and adaptation and innovation skills -essential for success in the digital entrepreneurship sector.

METHOD
Primary analysis techniques include exploratory factor analysis and confirmatory factor analysis, along with supporting analysis techniques such as Pearson correlation analysis, Kendall's tau_b analysis, Spearman's rho analysis, and Cronbach's alpha analysis.This is done as a robustness check to obtain statement items that can reflect a construct with high reliability.Thus, this study not only seeks to fill a gap in the existing literature but also provides a more robust methodology for vali-dating the instrument.

Phase 1 -DES instrument concept
In this phase, the process of formulating statement items is carried out by adapting the findings of previous researchers, where entrepreneurial skills are recognized as crucial skills for an entrepreneur (Gieure et

Q2
I interact with most of my friends on the internet.

Q3
I prefer working in a team to complete tasks/jobs rather than working alone.

Q4
I explore current business opportunities on the internet.

Q5
When facing a problem, I solve it systematically, starting from identifying the issue to finding a solution.

Q6
I strive to develop my creativity and innovation in fields that align with my talents and interests.

Q7
I think about ways to achieve success in the future.

Q8
I develop my skills to compete with others.

Q9
I easily adapt to new environments.

Q10
I quickly become acquainted with people I have just met.

Q11
I am open to other people's opinions.

Q12
I do not impose my will on others.

Q13
I take risks in a job/task.

Q14
I try new things that I find on the internet.

Q15
I want to learn something new.

Q16
I want to master various skills that match my talents.

Q17
I like to read books that I think can broaden my knowledge.

Q18
I write down ideas that suddenly come to my mind.

Q19
I understand current information technology.

Q20
I read books from start to finish.

Q21
I calculate all my expenses in a period (daily, weekly, monthly, annually).

Q22
I apply mathematical knowledge in daily life (such as calculating expenses and savings).

Q23
I consider all my expenses and income in a period.

Q24
I delve into the science of technology.

Q25
I spend my free time browsing the internet.

Q26
I visit websites that provide useful information for me.

Q27
I strive to interact properly with others.

Q28
I analyze the truth of every piece of information I receive.

Q29
When interacting with others, I give my conversation partner a chance to speak first.

Q30
I evaluate the achievements I have made.

Q31
I seek various sources (books or internet) to solve difficult problems.

Q32
I am careful when analyzing an event to avoid making wrong decisions.

Q33
I evaluate the ideas I present.

Phase 2 -Data collection
Once the instrument is declared valid by experts, data collection is carried out at one of the major universities in Indonesia.Every randomly encountered student is asked for their willingness to fill out the instrument.The study assures participants that the collected data will be kept confidential, solely used for research purposes, and devoid of any conflicts of interest.Eventually, a total of 235 data points were gathered from 300 participants who took part in this study, with 65 data points excluded because participants did not complete the statement items in the instrument.

Phase 3 -Classical validation instrument
The results of the analysis in this phase indicate that all the statement items tested using Pearson correlation, Kendall's tau, and Spearman's rho analysis have p < 0.05.This means that all the items withstand the robustness check with these three analysis techniques.Additionally, data reliability is confirmed through Cronbach's alpha test, which yields a value of 0.970 > 0.6.Furthermore, the significant correlations (see Table 2) suggest that the tested items reflect the same construct.

Phase 5 -Confirmatory factor analysis
The CFA analysis yielded two steps to achieve the required model fit in this phase.Starting with the first step, a CFA model (see Figure 2) was constructed based on the results of the EFA conducted in the previous phase.In this step, the first order was encoded with components 1 (F1), 2 (F2), and 3 (F3) for each statement item within these respective components.Subsequently, the second order was encoded with F4 for each component F1, F2, and F3.
The first step in this phase revealed that all the aspects required for CFA model fit showed unsatisfactory justification results (see Table 5).This indicates redundancy among the statement items within one component or with other components.Therefore, elimination based on high modification indices (MI) (see Table 6) in confirmatory factor analysis (CFA) is an appropriate approach to remove redundancy and enhance model clarity (Thakkar, 2020).In this step, a total of 17 statement items were eliminated due to having relatively high MI values and high covariances with other items (Thakkar, 2020).As a result, in the second step, 12 statement items were found to have been refined to reflect the components and constructs previously identified.The specification of components is as follows: six statement items for component   Following the elimination of statement items, the second step of the CFA resulted in the model (see Figure 3).In the first order, the first component (F1) consists of the following statement items with their respective loading factors: Q2 (0.756), Q4 (0.748), Q12 (0.741), Q15 (0.870), Q16 (0.823), and Q33 (0.726).All of these statement items have loading factors falling into the high category.Moving to the second component (F2), it includes the following statement items along with their respective loading factors: Q18 (0.755) and Q21 (0.614), both of which have loading factors in the high category, and Q24 (0.692) with a loading factor also in the high category.The third component (F3) compris-es the following statement items and their respective loading factors: Q9 (0.656), Q13 (0.776), and Q14 (0.797), all of which have loading factors in the high category (Hair et al., 2010).
The second-order model (see Figure 3) reveals that F1 (0.887), F2 (0.917), and F3 (1.023) have loading factors falling into the high to very high category (Hair et al., 2010) in reflecting F4 (see Table 7).This indicates that directly, the "first-order" statement items reflect their respective components (F1, F2, F3), and each of these components strongly reflects an overarching construct (F4) at the "second order."Based on the obtained results, the hypothesis is accepted.This means that the newly developed in-strument for measuring digital entrepreneurship skills among university students is a valid and reliable tool capable of accurately assessing the competencies required for success in the digital entrepreneurship sector.

DISCUSSION
This study has identified 12 statement items that exhibit strong reliability as they have undergone correlation testing (Pearson, Kendall's, and and developments and produce innovative products is crucial.This is reflected through statement items indicating several aspects, starting with adaptability (Q9), which expresses ease in adapting to new environments, demonstrating flexibility, resilience, and openness to change (Harari et al., 2023;Szemző et al., 2022).This is an essential quality in a rapidly changing world, both professionally and personally.Being risk-oriented (Q13) reflects a willingness to take risks in work or tasks and show the courage to face uncertainty and the potential for innovation.It also reflects a proactive attitude in tackling challenges and a willingness to step out of one's comfort zone (Gurel et al., 2021).The desire to try new things (Q14), which indicates an interest in trying new things found on the internet, demonstrates strong curiosity, acceptance of learning and innovation, and the ability to leverage digital resources for personal and professional growth (Hameed & Irfan, 2019).

CONCLUSION
This study successfully identified 12 statement items that reflect strong digital entrepreneurial skills.This paper demonstrated the validity and reliability of the research instrument.Interpersonal digital skills encompass digital interaction awareness, comfort with technology, and the ability to leverage social networks.It is closely related to awareness of business opportunities, respect for others, a desire to learn, and the ability to critically evaluate ideas.Ideation and technology management skills emphasize the need to manage ideas in alignment with evolving technology.This component includes documenting ideas, financial management, and in-depth knowledge of technology.Adaptation and innovation skills are crucial in entrepreneurship, where the ability to adapt to changes and generate innovative products is highly necessary.This aspect includes flexibility, resilience, risk-taking courage, and a willingness to try new things.Overall, this study underscores that digital entrepreneurship skills encompass a combination of interpersonal skills, ideation, and technology management skills, as well as adaptation and innovation skills, all of which are vital in fostering success in today's digital era.The findings are expected to contribute to policymakers, educators, students, and other researchers as a fundamental part of developing students' skills, especially digital entrepreneurship skills.

Figure 3 .
Figure 3. Model CFA step 2Furthermore, after identifying 12 statement items with high robustness, each component reflected by these statement items is assigned an identity.The first component (F1) is identified as digital interpersonal skills, the second component (F2) as ideation and technology management skills, the third component (F3) as adaptation and innovation skills, and the overarching construct (F4) as digital entrepreneurial skills.

Table 1 .
). Draft instrument of DES Q1I negotiate to reach an agreement with others.

Table 3 )
due to the presence of statement items that did not meet the predetermined communality prerequisites.Consequently, these items were eliminated, and a retest of EFA was conducted.

Table 2 .
Correlation and reliability test

Table 4 .
Loading factor in EFA

Table 5 .
Model fit summary

Table 7 .
Loading factor and identity of components Adaptation and innovation skills (F3) are an intriguing component(Bramwell etal., 2019; Harari et al., 2023; Szemző et al., 2022) in entrepreneurship, where the ability to adapt to societal changes