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Record W2083318486 · doi:10.1177/0149206310362102

Alliance Management Capability: An Investigation of the Construct and Its Measurement

2010· article· en· W2083318486 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 Management · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsAllianceConstruct (python library)PortfolioBusinessKnowledge managementProactivityProcess managementComputer scienceManagementEconomicsPolitical science

Abstract

fetched live from OpenAlex

This research conceptualizes and operationalizes alliance management capability. The authors develop alliance management capability as a second-order construct to capture the degree to which organizations possess relevant management routines that enable them to effectively manage their portfolio of strategic alliances. In addition to identifying and measuring specific organizational routines as critical dimensions of alliance management capability, the authors advance knowledge on the performance effects of dedicated alliance structures and alliance experience based on survey data from 204 firms. Their primary contribution is a theoretically sound alliance management capability measure that is reflected by five underlying routines: interorganizational coordination, alliance portfolio coordination, interorganizational learning, alliance proactiveness, and alliance transformation. One of the key findings is that alliance management capability has a positive impact on alliance portfolio performance and mediates the performance effects of dedicated alliance structures and alliance experience.

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)0.002
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.848
Threshold uncertainty score0.586

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.227
Teacher spread0.197 · 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