Evidence map›Paper›PMID 37273574›Full record

ArticleComputers & industrial engineering2023

The future of industry 4.0 and supply chain resilience after the COVID-19 pandemic: Empirical evidence from a Delphi study.

Alexander Spieske, Maximilian Gebhardt, Matthias Kopyto, Hendrik Birkel, Evi Hartmann

Abstract read
In one paragraph

Article in Computers & industrial engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Alexander SpieskeChair of Supply Chain Management, Friedrich-Alexander University Erlangen-Nuremberg, Lange Gasse 20, 90403 Nuremberg, Germany.
Maximilian GebhardtChair of Supply Chain Management, Friedrich-Alexander University Erlangen-Nuremberg, Lange Gasse 20, 90403 Nuremberg, Germany.
Matthias KopytoChair of Supply Chain Management, Friedrich-Alexander University Erlangen-Nuremberg, Lange Gasse 20, 90403 Nuremberg, Germany.
Hendrik BirkelChair of Supply Chain Management, Friedrich-Alexander University Erlangen-Nuremberg, Lange Gasse 20, 90403 Nuremberg, Germany.
Evi HartmannChair of Supply Chain Management, Friedrich-Alexander University Erlangen-Nuremberg, Lange Gasse 20, 90403 Nuremberg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic has caused major supply chain disruptions and unveiled the pressing need to improve supply chain resilience (SCRES). Industry 4.0 (I4.0) is a promising lever; however, its future in supply chain risk management (SCRM) is highly uncertain and largely unexplored. This paper aims to evaluate I4.0's potential to improve SCRES in a post-COVID-19 world. Based on current literature and multiple workshops, 13 future projections on potential I4.0 application areas in SCRM were developed. A two-round Delphi study among 64 SCRM experts with digital expertise was conducted to evaluate and discuss the projections regarding their probability of occurrence until 2030, their impact on SCRES, and their desirability. A fuzzy c-means algorithm was applied to cluster the projections based on the expert assessments. The expert evaluations led to three clusters on I4.0 application in SCRM: Four projections on generating data, increasing visibility, and building digital capabilities received considerable approval and are reliable to improve SCRES in 2030. Four projections enabling data sharing and processing were predominantly supported and demonstrated realization potential for 2030. Finally, five projections that require major supply network adaptations were deemed unlikely to improve SCRES in 2030. This paper answers several research calls by presenting empirical evidence on the pathway of I4.0 implementation in SCRM following the COVID-19 pandemic. Moreover, it evaluates a holistic set of technologies and indicates prioritization potentials to achieve SCRES improvements.

Indexed as

COVID-19 pandemicDelphi studyDigital supply chainIndustry 4.0Supply chain ResilienceSupply Chain Risk

Identifiers

PMID37273574
PMCPMC10214766

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.