Utilizing big data for the next-generation safety management system: Information provision to maintain workers' motivation

2016 Fiscal Year Final Research Report

• Project/Area Number: 26350458
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Social systems engineering/Safety system
• Research Institution: Keio University
• Principal Investigator: NAKANISHI Miwa 慶應義塾大学, 理工学部(矢上), 准教授 (70408722)
• Research Collaborator: HIRANO Ryo ; KATAYAMA Keijiro
• Project Period (FY): 2014-04-01 – 2017-03-31
• Keywords: 安全管理活動 / モチベーション / ビッグデータ

Outline of Final Research Achievements

In psychology, there is a theory that intrinsic motivation is increased through internal specifics and suitable gap in each aspect of emotion, cognition, and ability for the object. In this paper, to construct a method to maintain motivation for safety management activities, we report 1) distance quantification with each worker's internal, specific, and safety management activities and 2) the identification of suitable gap between them. We investigated workers, and positioned a plot in the three-dimensional space of each safety management activities constructed for every worker in a scale of 0-1 on every axis of emotion, cognition, and ability. The results shows that the plots with highest motivation was concentrated in a scale of 0.2-0.4 on the axes of cognition and ability. We hypothesized that we could maintain the intrinsic motivation by repeatedly providing information on the motivated activities, and we verified the same through experiments.

Free Research Field

人間工学／ヒューマンファクターズ