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Record W3147862767 · doi:10.2307/41410418

Value Cocreation and Wealth Spillover in Open Innovation Alliances1

2012· article· en· W3147862767 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

VenueMIS Quarterly · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Strategy and Innovation
Canadian institutionsMcGill University
Fundersnot available
KeywordsOpen innovationSpillover effectValue (mathematics)BusinessIndustrial organizationValue creationKnowledge spilloverMarketingKnowledge managementEconomicsMicroeconomicsComputer science

Abstract

fetched live from OpenAlex

In this study, we investigate the economic and strategic value of open innovation alliances (OIAs), in which collaborators and competitors integrate in the pursuit of the codevelopment of technological innovations. Given that OIAs differ substantially from traditional, closed alliances in many aspects, including their strategic scope and scale, governing mechanisms, and member composition, it is important to understand and assess the potential value inherent in these new modes of collaboration. Furthermore, OIAs evolve over time as the participating members are free to enter and leave at will. Therefore, we also examine the on-going value creation and wealth spillover that result from changes in membership. Moreover, we investigate how a firm’s participation in an IT-based open alliance alters the market value of its rivals operating within the same marketplace. To gain additional insight into the factors that moderate the market valuation of OIA participation, several contextual factors, including the degree of partner heterogeneity, innovation type, and degree of openness of the OIAs are used to account for variability in abnormal returns. Based on 194 observations, we found that allying firms realize significant positive abnormal returns when their entry into an OIA is made public. The results also suggest that substantial excessive returns accrue to the allying firms with the belated entry of a market leader firm. Furthermore, we discovered that a firm’s entry into an OIA increases, rather than decreases, the market valuation of its rivals. Interestingly, an incumbent rival that did not participate in the alliance appears to gain greater “free-riding” benefits from the OIA, as compared to peer rivals. Innovation type and openness were significantly associated with the amount of abnormal returns accruing to allying firms, while no significance was found for partner heterogeneity. Finally, we conclude with a discussion of the implications of our findings for research and practice with respect to value cocreation in multifirm environments.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.668
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.004
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 head0.033
GPT teacher head0.273
Teacher spread0.241 · 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