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Record W2132692878 · doi:10.1177/0170840606067927

The Impact of Governmental Policies in Institutional Fields: The Case of Innovation in the Dutch Concrete Industry

2007· article· en· W2132692878 on OpenAlexaff
Patrick A.M. Vermeulen, Rutger Büch, Royston Greenwood

Bibliographic record

VenueOrganization Studies · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsOrganizational fieldLegitimacyCompetitor analysisOrder (exchange)Government (linguistics)Corporate governanceInstitutional theoryField (mathematics)Process (computing)EmbeddednessInstitutional changeBusinessEconomic systemResistance (ecology)State (computer science)Market economyIndustrial organizationEconomicsMarketingPoliticsPolitical scienceSociologyPublic administrationManagement

Abstract

fetched live from OpenAlex

The creation of markets for new products involves interplay between various field constituents. A major challenge in this process is to establish a sufficient level of legitimacy in order for a market to become accepted in the organization field. Yet, this process of market creation may be suppressed by established institutional arrangements that actively block the diffusion of innovations and constrain change. In this paper, we examine the roles of regulatory structures, professional associations and competitors in market suppression. We pay particular attention to the actions and circumstances preventing change in a mature sector of the economy, despite state policies directed at change. Active resistance from professional associations and corporate actors inhibited creation of a new market. We draw upon institutional theory to provide an account of the different communities of interest involved in an institutional field, exploring how they are developed and negotiated. We argue that the role of the government and the impact of its policies in market construction may be overemphasized and that the complexity of its interaction with organizational fields may be underestimated.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.230
Threshold uncertainty score0.294

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.027
GPT teacher head0.293
Teacher spread0.267 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations82
Published2007
Admission routes1
Has abstractyes

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