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Record W3119350750 · doi:10.5267/j.msl.2020.12.001

Strategic alignment maturity criteria as a catalyst for enhancing operational excellence in Jordanian industrial companies

2021· article· en· W3119350750 on OpenAlexvenueno aff
Adel AL-Hashem, Tareq Abu Orabi

Bibliographic record

VenueManagement Science Letters · 2021
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
FundersAl-Balqa' Applied University
KeywordsMaturity (psychological)Scope (computer science)ExcellenceBusinessOperational excellenceProcess managementMarketingPopulationKnowledge managementOperations managementComputer scienceEngineering

Abstract

fetched live from OpenAlex

High convergence level of strategic alignment between business and information technology helps companies enhance operational excellence. This research aims to identify strategic alignment maturity criteria level and their impacts on operational excellence in Jordanian industrial companies. The population of the study consists of all managers at top and middle management and a purposive sample is used to answer questionnaire items. In this survey, 288 valid responses are collected for analysis using SPSS (20) and smart PLS "V. 3". The study reveals that there is a significantly positive impact of strategic alignment maturity criteria (communication, competency-value Measurement, governance, partnership, scope & architecture and skills) on operational excellence. The most maturity criteria have a mid-level of maturity except scope & architecture and competency-value measurement criteria which maintain a low level. Thus, the study concluded that the researched companies have to recognize the business value of information technology (IT) investment and harmonizing IT architecture with business structure.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.616
Threshold uncertainty score0.705

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.031
GPT teacher head0.261
Teacher spread0.230 · 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 designBench or experimental
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

Citations8
Published2021
Admission routes1
Has abstractyes

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