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Record W2562927802 · doi:10.5539/ibr.v10n1p153

Study of the Social and Cultural Aspects of Saudi Tourists and Evaluate the Services Provided to Tourist of Saudi - An Applied Study for the Tourism Sector in the Kingdom of Saudi Arabia

2016· article· en· W2562927802 on OpenAlexvenueno aff
Amal Mohammed Sheikh Damanhouri

Bibliographic record

VenueInternational Business Research · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in MENA
Canadian institutionsnot available
Fundersnot available
KeywordsTourismGovernment (linguistics)HospitalityBusinessMarketingTertiary sector of the economyTest (biology)Economic growthGeographyEconomics

Abstract

fetched live from OpenAlex

The current study is based on the tourism sector in Saudi Arabia. Kingdom’s tourism industry earnings from international travelers and tourism services are poised to hit SAR80 billion in 2015. The tourism industry in Saudi Arabia has witnessed an increasing level of growth in recent years and is seen to continue this trend moving forward. The industry has undergone a major transformation led by the commitment to upgrade the Kingdom’s infrastructure as well as improving its hospitality sector. Religious tourism is the main attraction for inbound tourists and will continue to be so for the foreseeable future, the government has taken steps to increase domestic tourism and persuade potential outbound tourists from vacationing abroad. However, large investment in the sector is required to bring these ambitious plans to fruition. The tourism sector comprises only 2% of government funding compared to the industrial sector. In this report random sampling was used as it is the best known form of probability sample. Pilot study was conducted by taking convenience sampling. To find the quantitative analysis SPSS 18.0 software is used. In this report factor analysis is used for the reliability test of the questionnaire. Chi-Square test is used for comparing the collected data with the desired data from the certain hypothesis on the other hand Pearson Correlation is used to measure means of a statistical test. The study evaluates the services provided to the tourist visiting the kingdom and at the same time it measures the satisfaction level of the tourists. The report is based on primary and secondary data for the primary data the questionnaire was used and being distributed to the tourists visiting the kingdom. Five hypothesis was proposed and are being analyzed using Chi – Square test and correlation test. The current study states that there are several variables, where excellent satisfaction is being rated by the tourists where as there are several factors where the authority needs to pay importance, which is mentioned in detail in this report. The outcome of this report also suggests some major policy recommendation by which convenience, excellence and comfort could be given to the tourists visiting the kingdom.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.456
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.119
GPT teacher head0.440
Teacher spread0.320 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

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