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Record W3034438850 · doi:10.5539/mas.v14n7p26

Organizational Integration and its Impact on the Effectiveness of Operational Processes (A Case Study on Hikma Pharmaceuticals)

2020· article· en· W3034438850 on OpenAlexvenueno aff
Ayyoub. A. Alsawalhah

Bibliographic record

VenueModern Applied Science · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Leadership and Management Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessProcess managementSample (material)Knowledge managementOrganizational performanceWork (physics)Operational effectivenessOperations managementComputer scienceMarketingEngineering

Abstract

fetched live from OpenAlex

This study aimed to identify the effect of organizational integration (cultural integration, leadership authority integration, functional integration, and structural integration) on the effectiveness of the operational processes (the effectiveness of the strategic plan, the effectiveness of resources and technologies, the effectiveness of performance and results) in the global pharmaceutical company, Hikma Pharmaceuticals. The researcher used the descriptive and analytical method and represented the study population in all Hikma Pharmaceuticals employees. The total number of included 520 administrative employees, the study sample consisted of 129 workers. The study concluded that the level of importance of organizational integration and the effectiveness of operational processes was high. Furthermore, it found that there is an effect of organizational integration in all its dimensions on the effectiveness of the operational processes at the company. The study recommended that Hikma Pharmaceuticals should work on building a comprehensive strategy for organizational development and integration, in addition to developing an integrated plan for developing the operational processes in the company.

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)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0030.001
Open science0.0000.003
Research integrity0.0010.001
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 head0.055
GPT teacher head0.306
Teacher spread0.251 · 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 designQualitative
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
Published2020
Admission routes1
Has abstractyes

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