Modeling social relationship strength in HR systems: a DEMATEL-ANP approach for the railway sector

This study develops a data-driven framework to evaluate employee social relationship strength using structured human resource (HR) records in the railway sector. We construct a hierarchical indicator system capturing three relationship bases—Geopolitical Relations, Blood Relations, and Industry Relations—and apply DEMATEL to model causal interdependencies among indicators, followed by ANP to derive their relative importance and generate hybrid weights. Using a railway HR database (2021–2023) as the empirical setting, the results indicate that kinship-related ties and workplace/education-based ties exert the strongest influence on relationship strength. Distinct from survey-based or communication-log-based approaches, the proposed framework operationalizes relationship indicators directly from administrative HR records, enabling scalable and auditable assessment in a highly regulated, safety-critical railway context. The proposed approach provides an objective and scalable tool for HR governance, supporting the identification of relational risks (e.g. favoritism and conflicts of interest) through interpretable, structured-data-driven measurement. By bridging social relationship theory with decision-science methods, this study offers operational insights for HR management in large-scale transport organizations.

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Publication Details

Journal
Cogent Business & Management
Published
2026-03-08
DOI
https://doi.org/10.1080/23311975.2026.2640668
Primary Topic
AI and HR Technologies
Type
article
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article

Modeling social relationship strength in HR systems: a DEMATEL-ANP approach for the railway sector

Wei Hui
Cogent Business & Management
AI and HR Technologies
article

Modeling social relationship strength in HR systems: a DEMATEL-ANP approach for the railway sector

Wei Hui
article en

Abstract

This study develops a data-driven framework to evaluate employee social relationship strength using structured human resource (HR) records in the railway sector. We construct a hierarchical indicator system capturing three relationship bases—Geopolitical Relations, Blood Relations, and Industry Relations—and apply DEMATEL to model causal interdependencies among indicators, followed by ANP to derive their relative importance and generate hybrid weights. Using a railway HR database (2021–2023) as the empirical setting, the results indicate that kinship-related ties and workplace/education-based ties exert the strongest influence on relationship strength. Distinct from survey-based or communication-log-based approaches, the proposed framework operationalizes relationship indicators directly from administrative HR records, enabling scalable and auditable assessment in a highly regulated, safety-critical railway context. The proposed approach provides an objective and scalable tool for HR governance, supporting the identification of relational risks (e.g. favoritism and conflicts of interest) through interpretable, structured-data-driven measurement. By bridging social relationship theory with decision-science methods, this study offers operational insights for HR management in large-scale transport organizations.

Cogent Business & ManagementVol. 13(1)
Institute of Computing Technology (CN), China Academy of Railway Sciences (CN)
Openalex Percentile: Top 33%
AI and HR Technologies
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Modeling social relationship strength in HR systems: a DEMATEL-ANP approach for the railway sector — Wei Hui · Cogent Business & Management (2026) | TGRS Research Map | TGRS