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Record W3216781062 · doi:10.33897/fujbe.v2i1.117

Goal Setting and Job Related Outcomes-Mediations of Employee Engagement and Workplace Optimism in IT Supplier Industry

2017· article· en· W3216781062 on OpenAlexaff
Ali Raza Nasir, Muhammad Awais, Hussaun A. Syed

Bibliographic record

VenueFoundation University Journal of Business & Economics · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsOptimismRespondentJob satisfactionWork engagementPsychologyEmployee engagementTest (biology)Applied psychologySocial psychologyWork (physics)Public relationsPolitical scienceEngineering

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the role of goal setting on job related outcomes, employee engagement and workplace optimism mediates the relationship between goal setting and work place optimism in the supplier industry of IT sector. Employee engagement and work place optimism mediations are examined on the relationship between goal setting and job related outcomes. Job satisfaction, organizational commitment and turnover intentions are examined as the job related outcomes. Questionnaire method was used to collect data from targeted respondent. A total of 180 questionnaires were distributed from which 152 were received in useable form. Simple linear regression is used to test the first hypothesis and Baron and Kenny (1986) regression analysis is used to test remaining three hypotheses. It is determined that, to improve the job related outcomes effective goal setting by the management is important. Employee engagement and workplace optimism are also important factors to improve the outcomes

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)0.002
metaresearch head score (Gemma)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.018
GPT teacher head0.228
Teacher spread0.210 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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