Towards a more integrated view of entrepreneurial careers
Bibliographic record
Abstract
Purpose – The purpose of this paper is to employ intelligent career theory to simultaneously explore the relationships between three types of entrepreneurial career capital (i.e. motivations, human, and social capital). It illustrates the interconnectedness of these three forms of capital as an important way to study entrepreneurial careers and provide a new lens for understanding both personal and venture success. Design/methodology/approach – This qualitative study of 22 in depth semi-structured interviews explores career stories of entrepreneurs in the high tech industry. The interviews focus on examining three aspects of their career, motivations to become an entrepreneur, ways of learning and developing their human and social capital. Interviews were transcribed and coded using grounded theory approach. Findings – The findings describe how entrepreneurial careers as simultaneously shaped by three types of career capital: motivations (knowing-why), knowledge (knowing-how), and relationships (knowing-whom). It also illustrates the accumulation of career capital as a continuous cycle of interrelationships between these three types of capital. Research limitations/implications – In sum, the findings add to the knowledge on entrepreneurial careers and the role that the three types of capital play in venture formation and success. It also points to the importance of a more integrated view of these careers, embedded in a web of motivational, social, and human capital. Practical implications – The study’s findings suggest that entrepreneurs should paid equal attention and nurture each form of career capital throughout their careers. It also has implications for entrepreneurship programs as well career advisers to. Originality/value – Prior entrepreneurship research has examined aspects of entrepreneur’s career capital (e.g. intentions, social, and human capital) typically in isolation from one another and little is known about their reinforcing relationships in entrepreneurial careers. This study provides novel insights for understanding the three types of career capital and the importance of this more integrated view in entrepreneurship education and career counseling.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".