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Record W2047715276 · doi:10.5539/ibr.v8n2p143

Guidelines for Developing Competencies of Travel Agent Manager: A Comparative Study of Thailand and Laos

2015· article· en· W2047715276 on OpenAlexvenueno aff
Chaiyong Chaicharoenthaweekit, Krit Jarinto

Bibliographic record

VenueInternational Business Research · 2015
Typearticle
Languageen
FieldPsychology
TopicCompetency Development and Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsSnowball samplingBusinessStatisticVariablesMarketingHospitalityKnowledge managementService (business)Variable (mathematics)Operations managementTourismComputer scienceGeographyStatisticsEngineeringMathematics

Abstract

fetched live from OpenAlex

This paper aims to develop guidelines for developing the competency required by a travel agent manager in the leisure and hospitality industry in Thailand and Laos. The conceptual framework is consisted of independent variables (core competency, common competency, and managerial competency) and dependent variable (guideline for Developing the competency of the manager). The data is collected from two sources: 1) 128 travel agents in both Laos and Thailand, and 2) additional 142 responses which are derived from snowball sampling, total 270 samples. Questionnaire is used as the data collecting tool. Multi-Layer Perceptron (MLP), which is a type of neural network statistic, is used for analysis and interpreting the factors to order prioritize of factors. The MLP is a mathematic network model which replicates neural network and it is used for anticipating the pattern of variables. It can be used for single variable analysis and multivariate analysis to describe variable significance and to map the variable linear. The results suggest at least three significant indications for developing the competency of travel agent manager in Thailand and Laos. The findings also indicate that Thailand leisure and hospitality industry has focus on organizational culture development, change management, and self-management, while in Laos there is an emphasis on operation development, personnel administration, and product and service. This study shows what aspects of competency the managers of travel agencies in Thailand and in Laos are possessing and what are lacking. This helps the organizations to initiate the most suitable guideline for development the missing aspects. It can also be seen that both travel agencies in Thailand and in Laos do not pay sufficient attention on working competency nor strengthen their managers’ competency to cope with either domestic competition or the more intense competition within and out of ASEAN region.

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)0.005
metaresearch head score (Gemma)0.011
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.612
GPT teacher head0.548
Teacher spread0.064 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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