Supply chain research overview from the early eighties to Covid era – Big data approach based on Latent Dirichlet Allocation

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24310%2F23%3A00011475" target="_blank" >RIV/46747885:24310/23:00011475 - isvavai.cz</a>

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S0360835223005442" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0360835223005442</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.cie.2023.109520" target="_blank" >10.1016/j.cie.2023.109520</a>

Result language

angličtina

Original language name

Supply chain research overview from the early eighties to Covid era – Big data approach based on Latent Dirichlet Allocation

Original language description

In recent years, supply chain research has grown at a tremendous pace. Many review papers use systematic literature reviews to describe longer-term trends and perspectives. However, many of these studies analyze a limited number of documents, which does not always guarantee representativeness of results. This paper presents a smart bibliometric literature review of supply chain research. The objectives are: (i) to identify supply chain research interest and research impact across subject areas; (ii) to capture trends of supply chain research in the last four decades; (iii) to identify research domains related to supply chain and development of these research domains over time; (iv) to explore the impact of COVID-19 on areas of supply chain research. Authors process 116,759 documents related to supply chain research, published between 1969 and 2021, retrieved from the Scopus database. After providing statistics regarding research interest and research impact, they use a corpus of abstracts to perform topic modeling. Using Latent Dirichlet Allocation (LDA) with Gibbs sampling, 13 research domains related to supply chain research are identified: Ecology; Food supply chain; IT support of supply chain; Retail-oriented supply chain; Risk and disruptive aspects of supply chain; Performance management; Value management and social aspect; Production; Sustainability & development; Models & optimization; Effective inventory management; Supply chain management systems; Supplier and logistic analytics. We also present the individual areas of supply chain research during COVID-19 pandemic.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10200 - Computer and information sciences

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Computers & Industrial Engineering

ISSN

0360-8352

e-ISSN

—

Volume of the periodical

183

Issue of the periodical within the volume

September 2023

Country of publishing house

US - UNITED STATES

Number of pages

23

Pages from-to

1-23

UT code for WoS article

001097353300001

EID of the result in the Scopus database

2-s2.0-85168255022