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3D IPEA Model to Improving the Service Quality of Boarding School

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  • Asep Chalim

Abstract

he service quality is an important factor which affecting student performance, expectation and satisfaction in a boarding school. The traditional of Importance-performance analysis used to evaluate strength and weaknesses of a service quality factors. The models of Importance-Performance-GAP Analysis (IPGA) have developed by integrating the strengths of the importance and performance analysis (IPA) and the GAP analysis (Lin, et al. 2009). This study develops a 3D (three dimensions) service quality and gap model by extending the IPGA model through adding student expectations attribute. This method shows the useful of the IPEA (Importance-performance-expectation analysis) in 3D grid view and this method useful in evaluating service quality of school. This study identified 40 items and each item was rated using Likert scales that have a 5-point of levels. The results were obtained from 175 students from grade 7 to grade 12. The final result was divided in two different aspect; (1) management aspect and (2) building services and facility aspect. The IPA grid for management aspect shows that four items fall into fist quadrant (Keep up the good work), and seven items fall into the second quadrant (Concentrate here), two items fall into third quadrant (Low priority), and two items fall into forth quadrant (Possible overkill). The results of 3D IPEA are shown that two attribute putted in quadrant 3 and one attribute in quadrant 6. The findings of the study show that a management aspect and building facilities aspect are necessary to enhance the service quality of school. The results are useful to identifying real condition of building facility and help a boarding school to develop better service quality.Â

Suggested Citation

  • Asep Chalim, 2016. "3D IPEA Model to Improving the Service Quality of Boarding School," Asian Social Science, Canadian Center of Science and Education, vol. 12(7), pages 119-119, July.
    • Handle: RePEc:ibn:assjnl:v:12:y:2016:i:7:p:119
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    References listed on IDEAS

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    1. Abalo, Javier & Varela, Jesus & Manzano, Vicente, 2007. "Importance values for Importance-Performance Analysis: A formula for spreading out values derived from preference rankings," Journal of Business Research, Elsevier, vol. 60(2), pages 115-121, February.
    2. Kurt Matzler & Elmar Sauerwein & Kenneth Heischmidt, 2003. "Importance-performance analysis revisited: the role of the factor structure of customer satisfaction," The Service Industries Journal, Taylor & Francis Journals, vol. 23(2), pages 112-129, March.
    3. Hsin-Hung Wu & Jiunn-I Shieh, 2010. "Quantifying uncertainty in applying importance-performance analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 44(5), pages 997-1003, August.
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    Cited by:

    1. Hui-Wen Vivian Tang & Lynne Lee, 2021. "Developing an Organizational Climate Diagnostic Instrument for Junior High Schools in Taiwan," SAGE Open, , vol. 11(1), pages 21582440219, February.

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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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