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Record W6930038015 · doi:10.5281/zenodo.10817805

Comprehending the factors responsible for creating successful leadership among women leaders in the United Kingdom's fintech start-up sector

2024· dissertation· en· W6930038015 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicFinTech, Crowdfunding, Digital Finance
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Qualitative researchFace (sociological concept)Representation (politics)Leadership stylePhenomenon

Abstract

fetched live from OpenAlex

In the present era, women have shown their proficiency in every sphere of the corporate environment and have developed competencies in achieving greater efficiency at the workplace. The FinTech start-up sector is also witnessing an increase in the number of women employees. However, despite a quarter of representation of women in the FinTech start-up sector, only one-seventh is placed among the board of directors. In this context, this study aims to evaluate the phenomenon of female leadership within FinTech start-up companies in the UK’s financial sector. The main aim of the study was to identify the factors responsible for successful female leadership in the UK’s FinTech start-up sector. The literature review revealed that there are four critical factors responsible for the outcome of female leadership-individual, organisational, social and technological. This was further examined using primary research. For this purpose, the researcher used a mixed-method comprising of both quantitative and qualitative approach. Under the quantitative approach, the researcher surveyed 100 employees working in the FinTech start-up sector through a close-ended questionnaire to examine the factors that impact the success of female leadership and the shortcomings under women leadership. On the other hand, under the qualitative analysis, the researcher interviewed the 5 managers through an open-ended questionnaire to understand the effectiveness of women leadership, leadership strategies and the challenges faced by women leaders. The findings indicated that women often face challenges in terms of the vertical limits created by society. All the factors significantly impact the leadership performance of females in the UK’s FinTech start-up sector. In addition to this, women often find it difficult to handle family and job responsibilities. Further, the findings indicate that women are more creative and need to be motivated. Lastly, organisations can play an important role in successful female leadership by adopting new management and leadership styles that provide women with equal opportunities.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.261
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0030.000
Scholarly communication0.0050.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.142
GPT teacher head0.284
Teacher spread0.143 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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