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Record W2004888809 · doi:10.5539/ass.v10n7p96

Impact of Leadership Styles on Employee Adaptability in Call Center: A Perspective of Telecommunication Industry in Malaysia

2014· article· en· W2004888809 on OpenAlexvenueno aff
Rajendran Muthuveloo, Kanagaletchumy Kathamuthu, Teoh Ai Ping

Bibliographic record

VenueAsian Social Science · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsAdaptabilityExploratory researchBusinessPerspective (graphical)Test (biology)Leadership styleMaturity (psychological)MarketingPublic relationsPsychologyManagementComputer scienceEconomicsSociologyPolitical science

Abstract

fetched live from OpenAlex

The purpose of this study is to find how employees adapt to different leadership styles in call centers in the telecommunication industry. This exploratory research was conducted among employees in call centers in the telecommunication industry to test the relationship between Leadership Styles and Employee Adaptability. The researcher used statistical inference and more specifically Linear Regression to test the relationship between the two variables. Results indicated that all the three Leadership Styles have an influencing role on the Employee Adaptability. Due to company policy, high volume of responses was not achieved. Job functions of the employees not directly reporting to their managers causing employee not interested in responding the surveys. Also, this study did not investigate the maturity level of the employees which has influence on the adaptability. And, the researcher was not able to get responses from all employees working in shifts. Few studies have been explored in the Leadership Styles and Employee Adaptability, this study expands our knowledge of leadership styles effect on employees’ adaptability in call centers in telecommunication industry in Malaysia.

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)0.000
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 score0.025
Threshold uncertainty score0.471

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.039
GPT teacher head0.308
Teacher spread0.268 · 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

Citations13
Published2014
Admission routes1
Has abstractyes

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