Evidence map›Paper›PMID 41775777›Full record

ArticleScientific reports2026

Workforce restoration time analysis for a two grade manpower system under heavy tail distribution and dual regime decisions latency.

K Parameswari, K Kannan, A Menaga

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Article in Scientific reports, 2026. 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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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

K ParameswariDepartment of Mathematics, Srinivasa Ramanujan Centre, SASTRA Deemed to be University, Kumbakonam, Tamil Nadu, 612001, India. parameswari@src.sastra.edu.
K KannanDepartment of Mathematics, Srinivasa Ramanujan Centre, SASTRA Deemed to be University, Kumbakonam, Tamil Nadu, 612001, India. anbukkannan@rediffmail.com.
A MenagaDepartment of Computer Science and Engineering, Srinivasa Ramanujan Centre, SASTRA Deemed to be University, Kumbakonam, Tamil Nadu, 612001, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Workforce restoration time (WRT) and man power planning are very essential for administrative as well as production oriented organizations. In recent days, several researchers worked on two-grade manpower system with a homogeneous attrition rate to obtain workforce restoration time. In the present paper, a stochastic methodology for examining workforce restoration time in a two-grade manpower system that is impacted by heavy-tailed threshold behaviors and organizational decision latencies is presented and four probabilistic models are developed to describe grade-specific breakdown limits under both independent and correlated dual-regime choice processes for inter-decision time. To achieve this, Lomax distribution is used to obtain the closed-form formulas for the mean and variance of workforce restoration time by taking into account both homogeneous and heterogeneous attrition rates, are obtained. Our results reveal that E[T] shows a direct and almost linear dependency on c and β, and it decreases monotonically as decision activity (K) increases. Temporal dependencies slightly lengthen the restoration period, as confirmed by the correlation parameter R, which has a less pronounced but steady effect. It is supported by the simulation tests that measure the sensitivity of restoration time with the help of various parameters like attrition rate c, inter decision interval β, decision correlation R, and decision count K. Further, our model predictions are statistically stable with tight confidence ranges.

Indexed as

Decision latencyDual-regime processLomax distributionStochastic modelingWorkforce restoration

Identifiers

PMID41775777
PMCPMC13066007

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