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Record W1930087483

Information technology and collaboration in the canadian construction industry

2006· article· en· W1930087483 on OpenAlexaboutno aff
François Chiocchio, Caroline Lacasse, Hugues Rivard, Daniel Forgues, Claude Bédard

Bibliographic record

VenueProceedings of the Joint CIB W78, W102, ICCCBE, ICCC, and DMUCE International Conference on Computing and Decision Making in Civil and Building Engineering, Montreal, Canada, 14-16 June · 2006
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsRespondentContext (archaeology)Knowledge managementBusinessInformation exchangeProduct (mathematics)Information technologyInformation transferOrder (exchange)Computer scienceTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

Information plays an essential role in construction because it specifies either the resulting product (design information) or the activities that need to be carried out in order for the product to be constructed (management information). The new information technology is impacting how this information is exchanged and how organizations operate because its purpose is to facilitate the exchange and management of information and it holds a lot of potential for the fragmented construction industry. To better understand this impact, a survey was carried out in Canada to inquire about communication, efficiency, and IT usage. Its focus is on collaboration among the various stakeholders. Collaboration implies that people with at least one common goal interact (through efficient communication), share (through generous cooperation) and coordinate themselves (through synchronicity). Little is known about the technologies used and how they impact collaboration. How do stakeholders interact? What information is shared? How does coordination occur between firms and within firms across functional lines? This exploratory study aims at providing insight into these questions. The authors created a questionnaire designed to assess issues related to information technology usages. The questionnaire has eight parts: socio-demographic questions to identify the context of the respondent and his/her firm; questions on IT usage which listed 17 different communication methods or devices (from fax to web portals and groupware) and evaluated their usage frequency as well as their perceived efficiency; questions on preferred IT use requested the most efficient technology or communication modality for contacting specific stakeholders; questions on the frequency of electronic transfer of key documents; questions to assess the perceived performance of the individual 1 Professor, Psychology Dept., Universite de Montreal, 90, ave. Vincent-d’indy, Montreal, Canada, H2V 2S9, Phone +1 514/343-6498, FAX + 1 514/343-2285, f.chiocchio@umontreal,ca Correspondance regarding this paper may be sent to Francois Chiocchio at f.chiocchio@umontreal.ca. This paper was made possible by a research grant from the FQRSC. 2 Doctoral Student, Psychology Dept., Universite de Montreal, 90, ave. Vincent-d’indy, Montreal, Canada, H2V 2S9, Phone +1 514/343-6498, FAX + 1 514/343-2285, caroline.lacasse@umontreal,ca 3 Professor, Construction Engrg. Dept., ETS, 1100 Notre-Dame St West, Montreal, Canada, H3C 1K3, Phone +1 514/396-8667, FAX +1 514/396-8584, hugues.rivard@etsmtl.ca 4 Professor, Construction Engrg. Dept., ETS, 1100 Notre-Dame St West, Montreal, Canada, H3C 1K3, Phone +1 514/396-8668, FAX +1 514/396-8584, daniel.forgues@etsmtl.ca 5 Professor, Construction Engrg. Dept., ETS, 1100 Notre-Dame St West, Montreal, Canada, H3C 1K3, Phone +1 514/396-8829, FAX +1 514/396-8525, claude.bedard@etsmtl.ca June 14-16, 2006 Montreal, Canada Joint International Conference on Computing and Decision Making in Civil and Building Engineering

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.535
Threshold uncertainty score0.879

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.016
GPT teacher head0.271
Teacher spread0.255 · 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

Citations3
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Joint CIB W78, W102, ICCCBE, ICCC, and DMUCE International Conference on Computing and Decision Making in Civil and Building Engineering, Montreal, Canada, 14-16 JuneSame topicConstruction Project Management and PerformanceFrench-language works237,207