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Chapter

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Title

Modeling for Human Resources Management by Data Mining, Analytics and Artificial Intelligence in the Logistics Departments

Authors

[ 1 ] Instytut Inżynierii Bezpieczeństwa i Jakości, Wydział Inżynierii Zarządzania, Politechnika Poznańska | [ 2 ] Instytut Zarządzania i Systemów Informacyjnych, Wydział Inżynierii Zarządzania, Politechnika Poznańska | [ P ] employee | [ SzD ] doctoral school student

Scientific discipline (Law 2.0)

[6.6] Management and quality studies

Year of publication

2020

Chapter type

chapter in monograph

Publication language

english

Keywords
EN
  • Professional skills
  • Labor market
  • Supply chain management
  • Logistics
  • HRM
  • MARS
  • ANN
Abstract

EN As a result of the environment changes, all Logistic Departments need to cover gaps between their needs and possibilities in regard to resources potential available in market and customer requirements. In addition to material re-sources, there are also intangible resources like knowledge, attitude and skills (part of HR). A pioneering mathematic-supported study was done with respect to technical skills of students from IT Departments at technical high schools. We achieve a mathematical model representing possible contributions of students into jobs through professional skills, subject to soft skills, common skills and other socio-economic variables in time. A general aim is to explore the effects between variables, the structure, stability and sensitivity of the model. Thus, the needs in Logistics are addressed through decision aid, educational improvements, programs and measurements. We take a genuine lead to networking and modelling side of HRM by modern Data Mining, Analytics and AI. Herewith, human and educational factors are addressed in Logistics, eventually for a best balance between job offers and demands. The resulting models are compared by the help of statistical performance criteria, they are discussed, interpreted, evaluated, and economic as well as educational implications are derived.

Date of online publication

13.12.2020

Pages (from - to)

291 - 303

DOI

10.1007/978-3-030-61947-3_20

URL

https://link.springer.com/chapter/10.1007/978-3-030-61947-3_20

Book

Smart and sustainable supply chain and logistics - trends, challenges, methods and best practices. Volume 1

Ministry points / chapter

20

Ministry points / chapter (humanities, social sciences and theology)

20

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