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Record W3045621045 · doi:10.1108/ecam-05-2020-0299

Identifying enablers for coordination across construction supply chain processes: a systematic literature review

2020· article· en· W3045621045 on OpenAlexaff
Qian Chen, Daniel Hall, Bryan T. Adey, Carl T. Haas

Bibliographic record

VenueEngineering Construction & Architectural Management · 2020
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSupply chainInterdependenceKnowledge managementProcess managementComputer scienceProcess (computing)Systematic reviewEnablingStakeholderBusiness

Abstract

fetched live from OpenAlex

Purpose Managing stakeholders' reciprocal interdependencies is always a challenging issue. Stakeholders need to find out different ways to communicate information and coordinate material flows during the supply chain processes. Many recent studies have advanced construction supply chain coordination from multiple perspectives. However, the field still lacks a comprehensive analysis to summarize existing research, to explicitly identify all the possible enablers for coordination and to investigate how the enablers can be carried out at the supply chain interfaces. To fill the gap, this study aims to conduct a systematic review in order to examine the relevant literature. Design/methodology/approach A systematic literature review process was conducted to identify and synthesize relevant publications (published in the past 20 years) concerning the coordination of construction supply chain functions. These publications were coded to link main research findings with specific enabler categories. In addition, how these enablers can be used at the interfaces across supply chain processes was reviewed with an in-depth analysis of reciprocal communications between stakeholders at design-to-production, production-to-logistics and production-to-site-assembly phases. Findings The coordination enablers were classified into three categories: (1) contractual enablers (including subtopics on relational contracts and incentive models), (2) procedural enablers (including subtopics on multiagent knowledge sharing systems and the last planner system) and (3) technological enablers (including subtopics on linked databases for design coordination, design for manufacturing software platforms and automated monitoring technologies). It was found that interfacing different functions requires a certain level of integration of stakeholders for quick response and feedback processes. The integration of novel contractual forms with digital technologies, such as smart contracts, however, was not adequately addressed in the state of the art. Research limitations/implications The scope of the systematic review is limited to the static analysis of selected publications. Longitudinal studies should be further included to sharpen the inductions of enablers considering organizational changes and process dynamics in construction projects. Practical implications Different enablers for coordination were summarized in a concise manner, which provides researchers and project stakeholders with a reinforced understanding of various ways to manage reciprocal interdependencies at different supply chain interfaces. Originality/value This study constitutes an important input for research on the construction supply chain by illuminating the thematic topic of coordination from inductively developed review processes, which included a holistic framing of the emerging coordination enablers and their use across supply chain functions. Consequently, it closes some identified knowledge gaps and offers additional insights to improve the supply chain performance of construction projects.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.029
metaresearch head score (Gemma)0.105
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.035
Threshold uncertainty score0.151

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.105
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0050.006
Bibliometrics0.0350.023
Science and technology studies0.0020.002
Scholarly communication0.0050.007
Open science0.0020.004
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.039
GPT teacher head0.315
Teacher spread0.276 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations102
Published2020
Admission routes1
Has abstractyes

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