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Record W2996916339 · doi:10.5539/ibr.v13n1p268

Influencing Factors of Organizational Performance in Nepal Airlines Corporation

2019· article· en· W2996916339 on OpenAlexvenueno aff
Shrijan Gyanwali, John Walsh

Bibliographic record

VenueInternational Business Research · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicAviation Industry Analysis and Trends
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessGovernment (linguistics)MarketingCorporationProactivityService (business)Resource (disambiguation)Public relationsFinanceEconomicsManagement

Abstract

fetched live from OpenAlex

The objective of the study is to evaluate performance influencing factors in Nepal Airlines Corporation (NAC) through mixed research method, qualitative and quantitative analysis. The primary data were obtained from in-depth interview with fifteen government and NAC executives. Secondary data were collected from Nepal Government, NAC publications and International Air Transport Association (IATA). Revenue generation and passenger movement rate is found with average performance. Motivated employee, entrepreneurial marketing, collective leadership, ownership feeling of government and environmental support were explored as key performance factors. Sophisticated technology, airworthiness, and international standard and recommended practice were found as unique features. Lack of aircraft, unfair political influence and alienation of staffs in unionism were identified the reasons of lacking the business growth. A performance framework is proposed which comprises entrepreneurial marketing (proactiveness, risk taking, innovativeness, opportunity focused, resource leveraging, customer intensity and value creation), collective leadership, sophisticated technology and sufficient number of modern aircrafts, service reliability and safety, and government support. The study recommends Nepal government to take ownership of NAC, and adopt fair and professional management practice rather than political quota distribution in its governing body, board of directors.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.087
GPT teacher head0.307
Teacher spread0.221 · 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.

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

Citations11
Published2019
Admission routes1
Has abstractyes

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