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Record W1489371372 · doi:10.5539/ibr.v8n7p78

Entertainment in Jordanian Malls

2015· article· en· W1489371372 on OpenAlexvenueno aff
Salem Ahmad Alrhaimi, Thair Abed-Alrahman Habboush

Bibliographic record

VenueInternational Business Research · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Retail Behavior Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEntertainmentAdvertisingCompetitor analysisBusinessMarketingMovie theaterEntertainment industryGeographyVisual artsArt

Abstract

fetched live from OpenAlex

Modern lifestyle is hard to imagine without the hustle and bustle that takes place in shopping malls that have become part and parcel of the economic and social life of every modern global citizen. Shopping malls are on the increase in major cities with Jordan being a hub for competitors in the mall industry. Hence, there is a growing need to understand consumers’ perceptions, dispositions and preferences as to the mall image nowadays. The purpose of this research is to determine the effect and significance of entertainment on the mall industry in Jordan. The data were conducted by structured questionnaire from 450 shoppers who visit the five largest malls, namely, AL-Mukhtar, Sameh, Arabella, Irbid, and AL-Safeway in Irbid as the biggest and high density city in the north territory of Jordan. The results of study showed that the age group less than 25 years of shoppers ranked first in patronage of the shopping malls mainly for reasons related to leisure, fun and entertainment. The study concludes by emphasizing the need for huge entertainment facilities, such as, family entertainment centers, cinema, gym, bowling alley, billiard hall and video games.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.217
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.163
GPT teacher head0.386
Teacher spread0.223 · 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 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
Published2015
Admission routes1
Has abstractyes

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