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Record W2622677365 · doi:10.5539/ibr.v10n7p34

"The Role of Domestic Tourism in Supporting the National Economy, from the Point View of Employers" Field Study on Aqaba Economical City

2017· article· en· W2622677365 on OpenAlexvenueno aff
Hanem Rajab Ibrahem Al-Darwesh

Bibliographic record

VenueInternational Business Research · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in MENA
Canadian institutionsnot available
Fundersnot available
KeywordsTourismLikert scaleBusinessDomestic tourismMarketingObstaclePoint (geometry)Scale (ratio)Special economic zoneGeographyTourism geographyMathematicsStatisticsCartographyChina

Abstract

fetched live from OpenAlex

The research dealt with the role of internal tourism in supporting the Jordanian economy, considering that Aqaba is a special case that represents an important part of the Jordanian domestic tourism. The problem of the research was to answer the following questions: Is Aqaba area characterized as an attractive tourist destination? Is Aqaba special economic zone authority (ASEZA) contributes to increase the Jordanian national income? Is the lack of infrastructure considers an obstacle to the development of domestic tourism in Aqaba? The data collected through the questionnaire were consisted of 30 paragraphs using the forth Likert scale.The importance of the research lies in its benefits to the decision makers of (ASEZA) in avoiding some of the obstacles and pitfalls that face employers and tourists. Data were collected from employers in Aqaba by using simple random sampling. Analytical descriptive methods, standard deviations, percentages, and T-tests were used. The results of the research showed that there are special characteristics that promote the internal tourism in Aqaba. It concluded that (ASEZA) plays a large role in promoting the internal tourism to Aqaba through tourism awareness and through providing the infrastructure and metadata. In contrast, the research found obstacles that hinder the internal tourism to Aqaba, and the high cost of tourism was one of them. The research recommended the need to intensify the planned advertisements and promotions according to the tourist seasons, establish extra parking spaces and hotel rooms, and conduct other researches that represent the tourist's opinion themselves.

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)0.006
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.105
GPT teacher head0.458
Teacher spread0.353 · 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
Published2017
Admission routes1
Has abstractyes

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