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Record W2588466371 · doi:10.5539/ibr.v10n3p193

An Empirical Study about Customer Preferences of Retail Sellers’ Qualifications

2017· article· en· W2588466371 on OpenAlexvenueno aff
Najah Hassan Salamah

Bibliographic record

VenueInternational Business Research · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsnot available
Fundersnot available
KeywordsHonestyPatienceSeriousnessMarketingBusinessPurchasingPreferenceSample (material)Personal sellingDescriptive statisticsQuality (philosophy)Data collectionPsychologyEconomicsSales managementStatisticsSocial psychologyMathematicsMicroeconomicsSales promotion

Abstract

fetched live from OpenAlex

The purpose behind the study was to analyze the skills and behaviors required by Saudi retail sellers in developing interest of the consumers towards purchasing from retail stores. The sample size of 384 participants has been considered for data collection. Descriptive statistics and frequencies have been used to generate and analyze the data. Results have indicated that majority of respondents embarked on retail shops with Saudi sales men, because they were characterized by truthfulness, honesty, and patience. Moreover, approximately 96.10% of respondents gave preference to the retail shops, which were managed by properly trained Saudi seller. It has been observed that it is important to consider that Saudi seller should possess the qualities of patience, faithfulness, seriousness in work, while recruiting, and appointing them. The importance of qualities, which should be possessed by seller, has been highlighted through outcomes. Moreover, the emphasis is given to provide training to the seller for enhancing their selling skills and capabilities.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.254
GPT teacher head0.465
Teacher spread0.212 · 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 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
Published2017
Admission routes1
Has abstractyes

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