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Record W4364297267 · doi:10.46632/rmc/1/3/9

Evaluation of Management of Financial Services and Institutions using the DEMATEL Method

2020· article· en· W4364297267 on OpenAlexaff
K Prabhakaran Anuradha

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Issues in Ukraine
Canadian institutionsCanadian Imperial Bank of Commerce (Canada)Royal Bank of Canada
Fundersnot available
KeywordsBusinessFinancial servicesFinanceAccounting

Abstract

fetched live from OpenAlex

Management of Financial Service and Institutions.Simply described, financial management is the process of allocating available financial resources to a corporation to maximize profitability and return on investment (ROI).All business transactions are organized, planned, and managed by experts in financial management.Making financial decisions and maintaining control over the organization's money are the primary responsibilities of financial managers.They employ methods including financial forecasting, profit and loss analysis, and ratio analysis.Planning, arranging and controlling financial processes aid businesses in running efficiently and making good profits.Financial managers have a key role in making decisions that take into account the company's shortand long-term goals.Budgeting, investing (spending money), and financing are among the responsibilities of a financial manager (raising money).Raising the company's value is the major goal of the financial manager, whose decisions frequently have long-term consequences.The five pillars of investments, income planning, insurance, tax planning, and estate planning are simple yet extensive approaches to financial planning.They serve as the cornerstone of the financial independence curriculum in every financial program.The five main goals of financial management are prospecting, acquisition, allocation, allocation, and financial estimates.The main facets of financial management, which is an essential element of overall management, are planning, raising, regulating, and administering the finances used in business.Financial organizations lend money to both businesses and individuals.Small enterprises and startups can launch their venture by utilizing the long-and medium-term loans offered by these institutions.New employment possibilities and economic expansion will result from this.Assisting in the creation of new enterprises and jobs, facilitating savings and investments, providing risk protection, and other critical activities are all carried out by the financial industry.The sector must make efforts to offer these activities to society in a way that is both sustainable and sustainable.DEMATEL (Decision-Making Trial and Evaluation Laboratory).They are divided into analyses using the Management of Financial Services and Institutions of the Marketing, Finance, Operations, Planning, and Systems Evaluation Parameters Marketing, Finance, Operations, Planning, and Systems in the value.Marketing, Finance, Operations, Planning, and Systems.Marketing, Finance, Operations, Planning, and Systems.Systems have the highest rank whereas Planning has the lowest level.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0120.006
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0150.002

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 head0.210
GPT teacher head0.343
Teacher spread0.133 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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