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Record W4409320557 · doi:10.5430/ijfr.v16n2p17

Assessing the Effect of Financial Literacy on Investment Decisions Among Matatu Savings and Credit Cooperative Societies in Kenya

2025· article· en· W4409320557 on OpenAlexvenueno aff
Moses Gathecha Wakanyi, Salome Musau

Bibliographic record

VenueInternational Journal of Financial Research · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsnot available
Fundersnot available
KeywordsFinancial literacyInvestment (military)BusinessLiteracyEconomicsFinanceFinancial systemActuarial scienceEconomic growthPolitical science

Abstract

fetched live from OpenAlex

Financial literacy has garnered significant attention in the realm of investment on a global scale over the years. This phenomenon is ascribed to its pivotal role in the process of making investment decisions. The global economy has undergone increased complexity; thus, it is imperative for each individual to engage actively and astutely in investment decision-making to effectively navigate the escalating cost of living. Numerous individuals exhibit interest in various forms of investments, finding them captivating due to the ability to make decisions and subsequently observe the consequences of those decisions. Nevertheless, not all investment endeavors yield profits, given that investors may not invariably be accurate in their decision-making. Therefore, this research sought to analyze the influence of financial literacy on the investment decisions of designated Matatu SACCO employees in Nanyuki town, Kenya. Specifically, the research involved evaluating the influence of savings techniques, debt management, financial planning, and project appraisal methods on investment decisions. Underpinning theories were information asymmetry, behavioral economics and financial education. A causal research design was employed, focusing on 8 Matatu SACCOs in Nanyuki Town, Kenya, as the units of analysis. Data was gathered from 195 employees of the SACCOs, representing various departments, utilizing a stratified sampling method and simple random sampling techniques for participant selection. The study encompassed a sample of 131 participants. Primary data was acquired through questionnaire. Descriptive analysis, correlation and multiple regression was utilized for data synthesis. The study revealed that saving techniques, debt management techniques, financial planning and project appraisal techniques had a positive significant effect on investment decisions. The study concludes that savings strategies often encourage financial literacy and education. As Matatu SACCO employees engage in saving, they may also seek information on various investment options available to them. Debt management strategies often involve education on financial planning, budgeting, and investment options enabling employees to gain a better understanding of their financial situation, which enhances their ability to make informed investment choices.. The study recommends that the Matatu SACCO should organize regular workshops focusing on financial literacy, covering topics such as budgeting, saving, and investment options. The Matatu SACCO should create a clear debt management policy that outlines acceptable debt levels, repayment schedules, and consequences of default. The Matatu SACCO should invite financial experts and successful investors to share their experiences and insights, providing real-world context to theoretical knowledge. The Matatu SACCO employees in Nanyuki town, Kenya should organize regular workshops and seminars focused on project evaluation methodologies, financial analysis, and investment decision-making.

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)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.562
Threshold uncertainty score0.859

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.049
GPT teacher head0.395
Teacher spread0.346 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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