The mediating role of supply chain collaboration on the relationship between information technology and innovation
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".