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Record W4416286525 · doi:10.1109/tem.2025.3632770

Beyond Bias and Error: Institutionalizing the Fifth Hand to Explain Infrastructure Project Cost Misperformance

2025· article· W4416286525 on OpenAlex
Peter E.D. Love, Lavagnon A. Ika

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

VenueIEEE Transactions on Engineering Management · 2025
Typearticle
Language
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsInstitutional theoryNormativeLegitimacyRationalityOrganizational theoryTransaction costInstitutional economicsOrganizational ecologyFoundation (evidence)

Abstract

fetched live from OpenAlex

Cost misperformance, when final construction costs exceed a client's approved budget, continues to be a challenge when procuring infrastructure delivery worldwide. Traditional explanations often emphasize individual and organizational errors and/or biases, while overlooking the institutional contexts that shape decision-making. Our paper extends the Fifth Hand, an emergent theory of project behavior, by embedding it within a neo-institutional perspective, linking micro-level ecological rationality with meso-level organizational pressures and macro-level institutional logics. We integrate isomorphic mechanisms (e.g., coercive, mimetic, normative) with institutional logics (e.g., professional [cost control]; market [competitiveness], collaborative [risk-sharing]) to explain the recurrence and legitimacy of behavioral patterns across infrastructure projects. The Fifth Hand is thus mapped to isomorphic pressures and institutional logics, illustrating how they shape a project's cost performance. By adopting a multi-level, institutional lens, we strengthen the Fifth Hand's explanatory foundation by connecting individual and organizational decisions to broader structural and normative forces. We conclude by outlining research directions to explore how isomorphic mechanisms and institutional logics evolve across projects, interact over time, and sustain cost misperformance.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.924
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.041
GPT teacher head0.310
Teacher spread0.269 · 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