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Record W2897931383 · doi:10.1108/jkm-01-2018-0019

The mediating role of supply chain collaboration on the relationship between information technology and innovation

2018· article· en· W2897931383 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

VenueJournal of Knowledge Management · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsYork University
Fundersnot available
KeywordsSupply chainBusinessEnablingIndustrial organizationKnowledge managementProduct (mathematics)Product innovationCompetition (biology)Competitive advantageNew product developmentSample (material)Supply chain managementMarketingComputer science

Abstract

fetched live from OpenAlex

Purpose The high level of competition in the globalized business environment forces companies to innovate to remain competitive. Previous literature often cites information technology (IT) and supply chain collaboration as direct contributors to product innovation and IT as a direct enabler of supply chain collaboration. This suggests that IT could have an indirect effect on product innovation through supply chain collaboration, although this relationship has not been addressed yet. This paper aims to analyze empirically the direct impacts of IT and supply chain collaboration on incremental and radical product innovation and the indirect effect of IT on both types of product innovation through supply chain collaboration by using data collected from a sample of 200 manufacturing firms. Design/methodology/approach Structural equation modeling was used to check the research hypotheses with a sample of 200 manufacturing companies. Findings The results show supply chain collaboration has a positive effect on technological innovation, showing that the collaboration with external agents foster both incremental and radical innovations. Furthermore, results show that IT directly enhances both types of product innovation (incremental and radical) indirectly through supply chain collaboration. Research limitations/implications This article supports the pursuit of open innovation that suggests the need to acquire external knowledge to be able to develop innovation projects. The use of tools that facilitate this transmission of knowledge becomes indispensable in environments in which companies must be involved in supply chains in which different external agents intervene and in which collaboration can promote the creation of synergies and superior competitive advantages. Practical implications Innovation requires more and more the use of knowledge management practices that capture external information to be used in the creation of new products. In this case, collaboration within a supply chain facilitates incremental and radical innovations. However, to strengthen this transfer of information and the adoption of behaviors that stimulate innovation, the company must use ITs. Originality/value This paper focus on the indirect effect of IT on product innovation through the creation of the collaborations with external agents. In spite of the importance of this relation, it has been poorly studied by previous literature. The paper’s greatest interest lies in the fact that ITs not only facilitate the transmission of knowledge but also facilitate other types of behavior among supply chain agents that invite collaboration and generate innovations.

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)0.003
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: none
Teacher disagreement score0.730
Threshold uncertainty score0.415

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0010.000
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 head0.020
GPT teacher head0.257
Teacher spread0.237 · 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