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Record W3097817354 · doi:10.1080/02681102.2020.1824990

The process of resource bricolage and organizational improvisation in information technology innovation: a case study of BDZX in China

2020· article· en· W3097817354 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInformation Technology for Development · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsMacEwan University
FundersChina Scholarship CouncilNational Natural Science Foundation of China
KeywordsBricolageImprovisationBusinessResource (disambiguation)Knowledge managementProcess (computing)Context (archaeology)ChinaInformation technologyProcess managementComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Research has shown there is a connection between bricolage and improvization, but discussion about their dynamic relationship in fixed situations is limited. In the context of information technology (IT) innovation, three aspects of corporate strategic actions are analyzed in this article by the exploratory single case study of BDZX in China. The following results were found: (1) IT innovation has experienced a transformation from component to architectural innovation, triggering corporate strategic actions; (2) Resource bricolage in IT innovation process is divided into combined resources and resetting resources, and organizational improvization in IT innovation process is divided into integration capabilities and development capabilities; (3) In IT innovation, the impact of resource bricolage on companies is gradually increasing, while the impact of organizational improvization on companies is gradually decreasing.

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.

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)0.001
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 score0.654
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
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 head0.009
GPT teacher head0.221
Teacher spread0.212 · 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