Evidence map›Paper›PMID 39641072›Full record

ArticleHeliyon2024

Modelling capability factors of logistics industry based on ISM-MICMAC.

Mohammad Kamrul Hasan, Xunping Lei, Arbia Hlali, Zixiang Bian

Abstract read
In one paragraph

Article in Heliyon, 2024. 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

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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

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3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Mohammad Kamrul HasanSchool of Business Administration, Tongling University, Tongling, Anhui, 244061, China.
Xunping LeiSchool of Business Administration, Tongling University, Tongling, Anhui, 244061, China.
Arbia HlaliDepartment of Management, Taibah University, Saudi Arabia.
Zixiang BianSchool of Communications and Transportation, Shijiazhuang Tiedao University, Shijiazhuang, Hebei, 050043, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Supply chain disruptions and global pandemics have revealed vulnerabilities within the logistics industry in recent years. Consequently, there has been a growing emphasis across various industries on enhancing logistics capabilities. The focus on improving logistics performance through capability factors has shifted the paradigm toward prioritizing these factors. In light of this transition, this study develops a structural model to identify the logistics capability factors (LCFs) that contribute to logistics performance. To define the interrelationships and interdependencies among LCFs, expert-based interpretive structural modeling (ISM) combined with cross-impact matrix multiplication applied to classification (MICMAC) is used. A complex ISM model and a MICMAC diagram, based on driving and dependency power, are constructed to determine and categorize LCFs. The findings indicate that the demand management interface (DMI) of service capability is a pivotal factor in enhancing logistics capability, followed by the significance of information management and technological innovation capabilities. The results of this study have several implications for understanding the relationships among LCFs and for extending knowledge through the application of the ISM-MICMAC technique. Both theoretical and managerial insights are highlighted, providing guidance for supply chain leaders and operational managers.

Indexed as

ISM-MICMACLogistics capability factorsPerformanceStructural modelling

Identifiers

PMID39641072
PMCPMC11617766

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LicenceCC BY
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Registered trials

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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.