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Record W3168266804 · doi:10.1108/ci-07-2020-0123

IPD-inspired framework for measuring stakeholder integration in public-private partnerships

2021· article· en· W3168266804 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

VenueConstruction Innovation · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPublic-Private Partnership Projects
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsStakeholderGeneral partnershipProcess managementOriginalityStakeholder engagementBusinessPrivate sectorKnowledge managementComputer scienceEconomicsQualitative research

Abstract

fetched live from OpenAlex

Purpose In a public-private partnership (PPP), the private sector is represented by a company termed the special purpose vehicle (SPV), which combines different stakeholders including designers, contractors and service providers under one umbrella. Correct SPV team selection is critical to ensure PPP success as the SPV must act as an integrated entity. In fact, unless the SPV takes an active role in developing trust and promoting integration principles, segmentation of interests, highly adversarial atmospheres, loss of value and economic inefficiency will prevail. Absence of awareness of such principles among stakeholders and the scarcity of literature investigating SPV stakeholder integration create great risks that jeopardize project success. Accordingly, to mitigate the aforementioned risks and provide stakeholders with both the knowledge and the tools to instigate and maintain integration, this paper aims to develop and test a framework to measure SPV stakeholder integration, inspired by the correlation between integrated project delivery (IPD) and SPV operations. Design/methodology/approach Following a design science research approach, a structured review is conducted to develop the SPV integration metrics and framework. The framework is then validated through face validation by a panel of industry and academic experts to assess its applicability in measuring SPV integration. Finally, the framework is tested on a well-recognized international PPP project to measure the SPV integration level, and the outcomes are discussed and analyzed. Findings The framework was able to assess the integration level of the studied SPV highlighting several areas of low-integration settings and providing guidance for achieving better integration. Originality/value This research is the first that develops a model to investigate the SPV’s integration level, from a holistic IPD perspective, to enable successful relationship management and enhance collaboration success. This study inspires practical recommendations for PPP practitioners to reduce the risks of segregated SPVs and their contribution to PPP failure.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0000.000
Scholarly communication0.0010.003
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 head0.246
GPT teacher head0.297
Teacher spread0.051 · 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