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Research on the Satisfaction Degree of Basic Level Employees in Chain Hotels —— Take Jinan Rujia Chain Hotel as an Example

2019· article· en· W2924410750 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicStrategic Planning and Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsJob satisfactionInterpersonal communicationTurnoverBusinessChain (unit)PsychologyBusiness administrationMarketingSocial psychologyManagementEconomics

Abstract

fetched live from OpenAlex

In recent years, there is a common problem in hotels. The turnover of grass-roots staffs is frequent and the turnover rate of staffs is high. This paper takes Jinan Rujia Chain Hotel as an example, designing a questionnaire to investigate the satisfaction of the grass-roots employees of Rujia Hotel. The principal component analysis of the data obtained from the survey was carried out by using SPSS analysis tools, then the conclusions were drawn as follows: The overall satisfaction of the grassroots staff of Rujia Hotel in Jinan is not very high. Among the five main factors, the employee satisfaction of the job treatment factor is the highest, while the interpersonal relationship factor is the lowest, which is only 0.0373. Personal development factor is second only to interpersonal relationship factor, employee satisfaction is 0.0482, but on the whole, the employee satisfaction of the five main factors is low.

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.

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)0.000
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 score0.491
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.120
GPT teacher head0.271
Teacher spread0.152 · 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