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Record W3164736995 · doi:10.5539/jms.v11n2p32

Digital Entrepreneurship Perspective of Smart Organization and Technological Innovation: A Conceptual Model

2021· article· en· W3164736995 on OpenAlexvenueno aff
Mushira A. Eneizat, Mohammed Mufaddy Al-Kasasbeh

Bibliographic record

VenueJournal of Management and Sustainability · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsnot available
Fundersnot available
KeywordsEntrepreneurshipExtant taxonKnowledge managementConceptual modelAdaptation (eye)Perspective (graphical)BusinessBusiness modelConceptual frameworkMarketingSociologyComputer sciencePsychologySocial science

Abstract

fetched live from OpenAlex

To be successful in today’s rapid and increasing changes, innovation is the only option for maintaining growth and competitiveness. Organizations actually need to become “smart” to confront the growing customer needs, and changing markets. Digital entrepreneurship (DE) is perceived as a key pillar for innovation. However, there are a number of concerns surrounding smart organization (SO), DE, and technological innovation (TI), and how they are related is complex and important to understand in this digital age. While the extant literature presents several models for innovation, however, these studies are considered to be incomplete as they do not emphasize the relation between these variables. Based on conducting a deep literature review, this study proposes a conceptual model for SO focusing on TI (i.e., Product and process). This integrated model argues that SO’s components namely business intelligence, creative orientation, environment understanding, adaptation, and continuous learning significantly contribute to TI. In addition, it proposes that DE mediates the relationship between the SO and TI. Hypotheses development and suggesting further areas of research are discussed.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.261
Threshold uncertainty score0.349

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.014
GPT teacher head0.233
Teacher spread0.218 · 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 designTheoretical or conceptual
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

Citations6
Published2021
Admission routes1
Has abstractyes

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