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Record W3000901499 · doi:10.1108/ijlss-03-2019-0026

Digitalizing supply chains potential benefits and impact on lean operations

2020· article· en· W3000901499 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

VenueInternational Journal of Lean Six Sigma · 2020
Typearticle
Languageen
FieldEngineering
TopicDigital Transformation in Industry
Canadian institutionsAthabasca University
Fundersnot available
KeywordsSupply chainBusinessSupply chain managementCompetitive advantageMarketingLean manufacturingKey (lock)Process managementOperations managementKnowledge managementIndustrial organizationComputer scienceEngineering

Abstract

fetched live from OpenAlex

Purpose New technological trends continue to emerge, and businesses adopt them in different capacity in a pursuit of improving current ways of doing things and to gain competitive advantages over rivals. One of the key business functions that is impacted by the implementation of different disruptive technologies is the supply chain management. As a result, there is a continuous need to identify where digitalizing supply chains may provide businesses with benefits to capitalize such gains. This study aims to examine potential impacts of digitalizing supply chains on five selected lean operations practices through the identification of key areas and benefits under each of these practices. Design/methodology/approach Data were collected from 74 participants mainly from the academic community and who were university scholars through the use of an online survey. The used online survey consists of six main parts in total, but three were included in this paper and these were designed to gather data about participants’ general information, level of influence of seven technological trends on supply chain performance and management and potential impact of digitalizing supply chains on five lean operations practices. Findings The authors were able to confirm the significant impact of digitalizing supply chains on the five examined lean operations practices. Most of the examined potential impacts were found to improve certain areas that directly improve the practices of the explored five lean operations practices as well as the overall supply chain and business performance. They were also able to determine the level of influence of the seven examined enabling technologies on supply chain performance and management. Originality/value To the best of the authors’ knowledge, this study is the first of its kind. Although some literature explored different aspects related to the concept of Industry 4.0 and digitalizing supply chains, no study has specifically explored potential impacts of digitalizing supply chains on lean operations. The results from this study can be beneficial to academic scholars interested in the researched themes, business professionals specializing in supply chain management and lean operations, organizations within different industrial sectors particularly manufacturing where lean thinking is adopted and any other party interested in understanding more about the impact of digitalizing supply chain on lean operations and on an overall business performance.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.230
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.020
GPT teacher head0.251
Teacher spread0.231 · 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