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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10200 - Computer and information sciences

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

Computers & Industrial Engineering

ISSN

0360-8352

e-ISSN

—

Svazek periodika

183

Číslo periodika v rámci svazku

September 2023

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

23

Strana od-do

1-23

Kód UT WoS článku

001097353300001

EID výsledku v databázi Scopus

2-s2.0-85168255022