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Determinants of Manufacturing Firms' Use of Web-Based IOISs to Share Inventory Information with Key Partners

2010· book-chapter· en· W2503993968 on OpenAlexaffabout
Pierre Hadaya, Robert Pellerin

Bibliographic record

VenueIGI Global eBooks · 2010
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Strategy and Innovation
Canadian institutionsPolytechnique MontréalUniversité du Québec à Montréal
Fundersnot available
KeywordsKey (lock)BusinessTobit modelMarketingInformation exchangeKnowledge managementIndustrial organizationComputer scienceTelecommunications

Abstract

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Based on the literature on the diffusion of innovations and on information systems, and building on emerging concepts in electronic collaboration (e-collaboration), this chapter analyses the influence of various determinants on manufacturing firms’ intent to use Web-based interorganizational information systems (IOISs) to share inventory information with their key suppliers. This theoretical model is tested on data collected from 498 senior managers of Canadian manufacturing firms. Findings indicate that a manufacturing firm’s organizational readiness, its past experience with e-commerce and its business relationships all affect its future use of Web-based IOISs to share inventory information with its key suppliers. The results of Tobit regressions also provide supporting evidence that firm size moderates the impact of the present use of e-commerce with suppliers on manufacturing firms’ intent to use Web-based IOISs to share inventory information with key suppliers. Finally, subsequent analyses also demonstrate that the determinants of manufacturing firms’ intent to use Web-based IOISs to exchange inventory information with key partners are the same whether the intended e-collaboration is to support relationships with key suppliers or key customers.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.906
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.029
GPT teacher head0.238
Teacher spread0.209 · 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.

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

Citations0
Published2010
Admission routes2
Has abstractyes

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