Structural analysis between HR systems and HR outcomes to motivate employees based on Harvard Model

Yusuke Sato, Nobuyuki Kobayashi, Seiko Shirasaka

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

Abstract

Rapid economic changes have recently been requesting human resource departments in Japanese firms to transform their roles and services. However, Paul et al. state that the focus of work on HRM is oriented towards HRM Policy Choices and short-term HR outcomes in Harvard Model. Therefore, Sato et al. insisted that we need to consider long-term consequences. The goal of this paper is to discover a causal relationship between HR Systems which is HRM Policy Choices and HRM outcomes including short-term HR outcomes and long-term consequences based on the Harvard model, in order to increase HRM outcomes including short-term HR outcomes and long-term consequences. We made the questionnaire survey and collected 516 answers. After that, we performed exploratory analysis (Multiple regression analysis) and confirmatory analysis (Covariance structure analysis). As a result, we confirmed that "Expectation in the Recruiting"plays an important role in increasing HR Outcomes.

Original languageEnglish
Title of host publicationProceedings - 2020 9th International Congress on Advanced Applied Informatics, IIAI-AAI 2020
EditorsTokuro Matsuo, Kunihiko Takamatsu, Yuichi Ono, Sachio Hirokawa
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages570-575
Number of pages6
ISBN (Electronic)9781728173979
DOIs
Publication statusPublished - 2020 Sep
Event9th International Congress on Advanced Applied Informatics, IIAI-AAI 2020 - Kitakyushu, Japan
Duration: 2020 Sep 12020 Sep 15

Publication series

NameProceedings - 2020 9th International Congress on Advanced Applied Informatics, IIAI-AAI 2020

Conference

Conference9th International Congress on Advanced Applied Informatics, IIAI-AAI 2020
Country/TerritoryJapan
CityKitakyushu
Period20/9/120/9/15

Keywords

  • Harvard Model
  • HR Systems
  • HRM
  • Motivation

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Information Systems and Management

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