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Record W2852632361 · doi:10.5539/ibr.v11n8p1

Organization Factors for ERP Projects in a Developing Country: A Case Study Jordan

2018· article· en· W2852632361 on OpenAlexvenueno aff
Mohammad Alzoubi, Ahmad Al-Haija

Bibliographic record

VenueInternational Business Research · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicERP Systems Implementation and Impact
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessScrutinyProcess managementProcess (computing)Enterprise resource planningKnowledge managementOrder (exchange)Business processChange management (ITSM)MarketingComputer scienceWork in processPolitical science

Abstract

fetched live from OpenAlex

The organization factors integral to the successful implementation of ERP systems are identified in this paper, and the organization factors under scrutiny include: Change Management, Business Process Management, and Top Management Support. Survey questionnaires were circulated to ERP users in companies in Jordan, which led to the collection and analysis of 314 responses in total. The results evidence significant relationship between change Management and top management support with ERP implementation success. However, the outcomes did not support the relationship between Business Process Management and ERP implementation success. This study could assist ERP vendors and consultants in developing countries in preparing certain strategies for dealing with the oddity between their ERP products and ERP adopting organizations. Also, both ERP adopting organizations and managers could attain awareness regarding the intricacies that are inherent in ERP installations in order to prevent obstacles while increasing the possibility of attaining the looked-for results.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0010.002
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 head0.179
GPT teacher head0.439
Teacher spread0.260 · 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 designCase report
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
Published2018
Admission routes1
Has abstractyes

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