Examining determinants of digital entrepreneurial intention: A case of graduate students
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DOIhttp://dx.doi.org/10.21511/ppm.20(3).2022.13
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Article InfoVolume 20 2022, Issue #3, pp. 153-163
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This study aims to identify the determining factors of digital entrepreneurial intention among university graduate students in Bangladesh. The study considered university students as a study sample (n = 358) who were either in their final year of bachelor’s program or in the master’s program from three private universities located in Dhaka city, Bangladesh. This study was quantitative in nature, and a survey questionnaire was used based on the previous studies. There were three parts: a questionnaire, demographic information analysis, and a Likert-based measurement of study variables. A Cronbach (α) coefficient value of 0.70 or above was regarded to examine the reliability of the constructs. A factor loading value of 0.50 or above was considered to measure the research validity of all constructs’ items. Regression analysis was run to test the hypotheses. A Google form-based online survey questionnaire was used to collect the data, followed by a non-probability sampling method. After scrutiny, incomplete responses were discarded, and finally, 358 responses were deemed usable. The paper used SPSS version 26.0 to perform relevant statistical analyses. The results show that digital entrepreneurial self-efficacy, digital literacy, entrepreneurship education, innovativeness, and creativity positively and significantly impact university students becoming digital entrepreneurs. Regression result shows that students’ innovativeness and entrepreneurship education have more impact on their digital entrepreneurial intentions, implying that policymakers and universities should design their academic policy to promote innovative and entrepreneurship activities in the academic pedagogy.
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JEL Classification (Paper profile tab)M10, M13, M21
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References59
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Tables3
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Figures2
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- Figure 1. Research model
- Figure 2. Regression coefficient
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- Table 1. Reliability and validity analysis
- Table 2. Demographic information analysis
- Table 3. Regression coefficient analysis
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