MétaCan
Menu
Back to cohort
Record W4415190980 · doi:10.53555/29mbsr72

Financial Decision Making during Midlife Crisis among Citizens of Mangalore through the lens of Behaviour Finance

2023· article· en· W4415190980 on OpenAlexvenueno aff
Adithya Narayana

Bibliographic record

VenueJournal of Survey in Fisheries Sciences · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsnot available
Fundersnot available
KeywordsFinancial crisisFinancial planStructural equation modelingFinancial securityFinancial stabilityGeography of financeFinancial literacyFinancial analysis

Abstract

fetched live from OpenAlex

  Midlife crisis is a period often marked by emotional and psychological changes, usually between the ages of 40 and 60 years, where individuals may re-evaluate their achievements, future goals, and personal identity. These experiences, combined with responsibilities such as raising children, paying loans, and preparing for retirement, can strongly influence financial behaviour. Since financial decisions made in midlife play a key role in shaping retirement security and long-term well-being, understanding this link has become increasingly important. This study focuses on people in Mangalore, aged 40-60 years, to explore how midlife crisis intensity affects financial decision-making. Primary data was collected using a structured questionnaire, and responses were analysed through statistical tools and structural equation modeling. The study examined three psychological factors emotional instability, psychological stress, and midlife crisis intensity and tested their influence on financial decision-making, as well as the mediating role of financial decisions in building financial resilience. The findings show that psychological stress has a more significant impact on financial behaviour compared to emotional instability or midlife crisis intensity. While midlife crisis does not always lead to poor financial choices, it often encourages individuals to reassess their spending and saving habits. Results further confirm that financial decisions strongly improve financial resilience, aligning with earlier research that highlights the role of budgeting, saving, and disciplined planning in financial stability. By focusing on the cultural and social setting of Mangalore, this research contributes to behavioral finance literature with a regional perspective. The insights are valuable for financial advisors, policymakers, and individuals, as they emphasize the importance of integrating emotional well-being with financial planning to strengthen resilience during midlife transitions.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.164
GPT teacher head0.280
Teacher spread0.117 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Survey in Fisheries SciencesSame topicMicrofinance and Financial InclusionFrench-language works237,207