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The Integration of the Kano Model and SERVQUAL into the House of Quality for Developing Occupational Safety and Health Training Program

  • Mohd Saiful Izwaan Saadon
  • Zainol Mustafa
  • Khairul Za’im Kamarulzaman
Conference paper

Abstract

Knowledge on occupational safety and health (OSH) management system is very important to any industrial organization in order for them to make sure that the safety and health elements in their organization are well maintained and according to the law. It is very important for the industrial management and workers to know and understand the correct OSH knowledge and concept. Because of that it is very important for them to attend sufficient and relevant OSH training in order for them to attain the OSH knowledge. These trainings must be effective and have sufficient impact. For that purpose a new method is used in this research. The Kano model and SERVQUAL have been integrated into the house of quality (HOQ) for the purpose of developing an OSH training course that would satisfy not only the requirement and needs of the industry but also unexpected factors towards the trainee who attends the course. By using this method we can see that the level of understanding for the training participant using this new model is higher compared to the level of understanding for the participant from the conventional OSH training program that has been conducted by the training provider. With the increment in the level of understanding, the level of effectiveness for doing OSH-related job for the training participant would also be different. We can prove this by using Kirkpatrick’s Evaluation Model, whereby we would evaluate the trainee from the conventional OSH training program against the newly developed OSH training program. The evaluation would be based on their level of understanding and the level of effectiveness of doing OSH-related jobs in their respective workplace.

Keywords

Service Quality Intellectual Capital Quality Function Deployment Training Provider Training Participant 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgment

The authors would like to acknowledge the financial support received in the form of fundamental research grant scheme FRGS/1/2013/SG04/UKM/02/4 from the Ministry of Higher Education Malaysia.

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Copyright information

© Springer Japan 2015

Authors and Affiliations

  • Mohd Saiful Izwaan Saadon
    • 1
  • Zainol Mustafa
    • 2
  • Khairul Za’im Kamarulzaman
    • 3
  1. 1.Faculty of Science and TechnologyOpen University MalaysiaShah AlamMalaysia
  2. 2.Faculty of Science and TechnologyNational University of MalaysiaBangiMalaysia
  3. 3.Malaysian Institute of Industrial TechnologyKuala Lumpur UniversityJohor BahruMalaysia

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