A quantitative approach to HCM using PAV: Method and robustness

H. Iwamoto, H. Suzuki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study focuses on Human Capital Management (HCM). It provides Added value (AV) indicator considering HCM, tools to utilize them and also verify robustness of the tools. The aim of this study is to provide a quantitative technique for managers to make decisions by objectively evaluating HCM as well as projecting profit increase, which is generated by HCM. AV has been often used as a value measurement. However, profit structure supported by tangible assets has been changed to be supported by intangible assets in recent years. It is necessary to redefine AV for considering influence of intangible assets. Therefore, this study provides Personnel adjusted AV (PAV); AV indicator considering HCM. It also creates tools to utilize them using statistical methods. Then, verify the robustness of the tools. In the process of verifying robustness, this study extracts particular indices. It is possible to obtain suggestions for social issue from particular indices.

Original languageEnglish
Title of host publication24th International Conference on Production Research, ICPR 2017
EditorsMarek Fertsch, Agnieszka Stachowiak, Beata Mrugalska, Joanna Oleskow-Szlapka, Lukasz Hadas, Piotr Cyplik, Paulina Golinska-Dawson
PublisherDEStech Publications
Pages25-30
Number of pages6
ISBN (Electronic)9781605955070
Publication statusPublished - 2017
Externally publishedYes
Event24th International Conference on Production Research, ICPR 2017 - Poznan, Poland
Duration: 2017 Jul 302017 Aug 3

Publication series

Name24th International Conference on Production Research, ICPR 2017

Conference

Conference24th International Conference on Production Research, ICPR 2017
Country/TerritoryPoland
CityPoznan
Period17/7/3017/8/3

Keywords

  • Added value
  • Human capital
  • Human capital management
  • Intangibles
  • Measuring

ASJC Scopus subject areas

  • Computer Science Applications
  • Industrial and Manufacturing Engineering
  • Control and Systems Engineering

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