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Record W2587039444 · doi:10.1504/ijids.2017.10003123

Location of a new banking agency in Sfax: a multi-criteria approach

2017· article· en· W2587039444 on OpenAlexaff
Jean Marc Martel, Hela Moalla Frikha, Habib Chabchoub

Bibliographic record

VenueInternational Journal of Information and Decision Sciences · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicMulti-Criteria Decision Making
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsProfitability indexAgency (philosophy)Order (exchange)Ranking (information retrieval)BusinessPromotion (chess)PreferenceFinanceCarry (investment)EconomicsComputer scienceMicroeconomics

Abstract

fetched live from OpenAlex

Sfax is an important economic pole in Tunisia, distinguished in all economic sectors of activity by its increasing rate of employment. Besides, many new projects are implemented in Sfax as well as in its suburbs. These factors contribute to increase the necessity of resorting to banks either to deposit the collected funds or to obtain credits. Since banks play an important and indispensable role for the promotion of the national economy, Tunisian banks follow propagation policies in order to ensure coverage of Tunisian territory through the installation of news banking agencies. To maximise its profitability, the 'Tunisian Development Bank' carry out a survey in order to choose the best sites to set up its new agencies. In this framework, we will develop in this paper a preference disaggregation approach based on PROMETHEE method. The proposed approach deduces, in an objective way, PROMETHEE's parameters from binary preference relations provided by the decision maker and then allows ranking the different sites for the setting up of the new banking agency.

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)0.010
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.966
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0020.008
Open science0.0030.000
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 head0.235
GPT teacher head0.488
Teacher spread0.253 · 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.

Study designOther design
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
Published2017
Admission routes1
Has abstractyes

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