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Record W1965038051 · doi:10.4018/jsita.2010040105

Leadership and Processes

2010· article· en· W1965038051 on OpenAlexaff
M. Gordon Hunter

Bibliographic record

VenueInternational Journal of Strategic Information Technology and Applications · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicERP Systems Implementation and Impact
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsBusinessOfficerCompetitive advantageEnterprise resource planningPosition (finance)Knowledge managementSenior managementStrategic planningStrategic managementProcess managementResource (disambiguation)Information technologyInformation systemTheme (computing)Strategic leadershipManagementPublic relationsPolitical scienceComputer scienceMarketingEconomics

Abstract

fetched live from OpenAlex

A senior management committee sets the direction for the organization by establishing strategic initiatives. A common theme across all strategic initiatives is the requirement to make management decisions and thus the pre-requisite of possessing the necessary data and information. This manuscript discusses two strategic initiatives relating to the recognition of data and information as a valuable resource. One initiative relates to structure and the establishment of a leadership role, in the form of a Chief Information Officer (CIO) position, to facilitate the exploitation of information technology. Another initiative involves the radical improvement of business processes through the implementation of a cross-functional integrated information system, in the form of an Enterprise Resource Planning (ERP) system. Both of these initiatives of leadership and processes, championed by all the members of the senior management committee, are necessary for the future operation of the business and to contribute to establishing and maintaining competitive advantage.

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)0.011
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0070.004
Scholarly communication0.0110.003
Open science0.0020.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0350.019

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 head0.042
GPT teacher head0.293
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 designNot applicable
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

Citations1
Published2010
Admission routes1
Has abstractyes

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