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Record W2078499105 · doi:10.4236/ti.2015.61004

A Study on the Work Well-Being of Personnel in Telecommunication Marketing as Well as Its Influencing Factors in China —Based on the Researches in the Guangzhou Branch of China Telecom

2015· article· en· W2078499105 on OpenAlexvenueno aff
Yuanqing Shen, Long Li

Bibliographic record

VenueTechnology and Investment · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsChinaWork (physics)Compensation (psychology)MarketingBusinessTelecommunicationsPsychologyComputer scienceEngineeringSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

Based on literature research and interviews, this study proposes three main Work Well-Being dimensions in line with the telecommunications marketing personnel characteristics. They are organizational commitment, overall reward and family support. Then the study builds the concept model. With data from questionnaires of 155 samples, this research analyzes the work well-being of telecommunications marketing personnel as well as its influencing factors with living examples. The results show that organizational commitment and total compensation have a significant positive correlation with work well-being, while family support is insignificantly negative correlated with work well-being. There are some factors that have more positive contribution to work well-being: Non-economic compensation, economic compensation, ideal expectation, social norms, economic costs, while the negative factors are emotion recognition, career opportunity, family time and family behavior.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.291

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.031
GPT teacher head0.268
Teacher spread0.237 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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