IDEAS home Printed from https://ideas.repec.org/a/lrc/larrss/v1y2016i2p1-6.html
   My bibliography  Save this article

Improving the Service Quality of Islamic Boarding School based on Importance Performance Analysis Results

Author

Listed:
  • Asep Saifuddin Chalim

    (State Islamic University of Sunan Ampel (UINSA), Surabaya Indonesia, Islamic Religious Institutes of Al-khoziny, Buduran, Sidoarjo, Indonesia)

  • Mauhibur Rakhman

    (Faculty of Tarbiyah, Institut Pesantren KH Abdul Chalim, Mojokerto, Indonesia)

  • Fadly Usman

    (Department of Urban and Regional Planning, Brawijaya University, Indonesia)

Abstract

Service quality is very importance aspect in a boarding school. In this research, an importance-performance analysis enables to evaluate the weaknesses of an Islamic boarding school according to service quality factors. This study attempts to understand stakeholders’ expectations and perceptions toward boarding school and shows the usefulness of the Importance-performance analysis grid in evaluating the service quality of school. This research identifies 35 items and each item is rated using the 5-point of Likert scale. The results are obtained from 350 respondents from students, teachers, and parents. The final results of importance-performance grid show that 12 items fall into quadrant of “Keep up the good work”, and 18 items fall into the “Concentrate here” quadrant, 3 items fall into quadrant of “Low priority”, and 2 items fall into “Possible overkill” quadrant. The findings of the research show that a school management and facilities aspect are necessary to better organizational characteristics and enhance the service quality of school. The results are useful in identifying marketing strategic and help the boarding school develop better service quality. Classification JEL : A21; C38; I23; M12.

Suggested Citation

  • Asep Saifuddin Chalim & Mauhibur Rakhman & Fadly Usman, 2016. "Improving the Service Quality of Islamic Boarding School based on Importance Performance Analysis Results," Review of Social Sciences, LAR Center Press, vol. 1(2), pages 1-6, February.
  • Handle: RePEc:lrc:larrss:v:1:y:2016:i:2:p:1-6
    as

    Download full text from publisher

    File URL: http://www.socialsciencejournal.org/index.php/site/article/view/22/6
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Michele Preziosi & Alessia Acampora & Maria Claudia Lucchetti & Roberto Merli, 2022. "Delighting Hotel Guests with Sustainability: Revamping Importance-Performance Analysis in the Light of the Three-Factor Theory of Customer Satisfaction," Sustainability, MDPI, vol. 14(6), pages 1-20, March.
    3. Harman Preet Singh & Mohammad Alshallaqi & Mohammed Altamimi, 2023. "Predicting Critical Factors Impacting Hotel Online Ratings: A Comparison of Religious and Commercial Destinations in Saudi Arabia," Sustainability, MDPI, vol. 15(15), pages 1-25, August.
    4. Lai, Ivan Ka Wai & Hitchcock, Michael, 2015. "Importance–performance analysis in tourism: A framework for researchers," Tourism Management, Elsevier, vol. 48(C), pages 242-267.
    5. Nyarku Kwamena Minta & Oduro Stephen, 2017. "Importance-Performance Matrix Analysis (IPMA) of Service Quality and Customer Satisfaction in the Ghanaian Banking Industry," International Journal of Academic Research in Business and Social Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Business and Social Sciences, vol. 7(7), pages 532-550, July.
    6. Esmailpour, Javad & Aghabayk, Kayvan & Abrari Vajari, Mohammad & De Gruyter, Chris, 2020. "Importance – Performance Analysis (IPA) of bus service attributes: A case study in a developing country," Transportation Research Part A: Policy and Practice, Elsevier, vol. 142(C), pages 129-150.
    7. Lai, Ivan Ka Wai & Hitchcock, Michael, 2016. "A comparison of service quality attributes for stand-alone and resort-based luxury hotels in Macau: 3-Dimensional importance-performance analysis," Tourism Management, Elsevier, vol. 55(C), pages 139-159.
    8. Tsung-Chi Cheng & Chao-Yin Lin & Shu-Chen Wang, 2023. "Exploring factors related to agreement between importance and satisfaction of subjective well-being indicators: evidence from Taiwan," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2811-2839, June.
    9. Yanchun Jin & Yoonseo Park, 2019. "An Integrated Approach to Determining Rural Tourist Satisfaction Factors Using the IPA and Conjoint Analysis," IJERPH, MDPI, vol. 16(20), pages 1-16, October.
    10. Azzopardi, Ernest & Nash, Robert, 2013. "A critical evaluation of importance–performance analysis," Tourism Management, Elsevier, vol. 35(C), pages 222-233.
    11. Yulu Zhao & Xinye Xu & Gangwei Cai & Zhetao Hu & Yan Hong, 2022. "Promoting Strategies for Healthy Environments in University Halls of Residence under Regular Epidemic Prevention and Control: An Importance—Performance Analysis from Zhejiang, China," IJERPH, MDPI, vol. 19(23), pages 1-19, November.
    12. Sheng, Xiaojing & Simpson, Penny M. & Siguaw, Judy A., 2014. "U. S. winter migrants' park community attributes: An importance–performance analysis," Tourism Management, Elsevier, vol. 43(C), pages 55-67.
    13. Teodoro Luque Martínez & Luis Doña Toledo & Nina Faraoni, 2019. "Auditing Marketing and the Use of Social Media at Ski Resorts," Sustainability, MDPI, vol. 11(10), pages 1-24, May.
    14. Wong, R.C.P. & Szeto, W.Y., 2018. "An alternative methodology for evaluating the service quality of urban taxis," Transport Policy, Elsevier, vol. 69(C), pages 132-140.
    15. Dwyer, Larry & Cvelbar, Ljubica Knežević & Edwards, Deborah & Mihalic, Tanja, 2012. "Fashioning a destination tourism future: The case of Slovenia," Tourism Management, Elsevier, vol. 33(2), pages 305-316.
    16. Ryglová Kateřina & Rašovská Ida & Šácha Jakub, 2017. "Rural Tourism – Evaluating the Quality of Destination," European Countryside, Sciendo, vol. 9(4), pages 769-788, December.
    17. Guizzardi, Andrea & Stacchini, Annalisa, 2017. "Destinations strategic groups via Multivariate Competition-based IPA," Tourism Management, Elsevier, vol. 58(C), pages 40-50.
    18. Yan Hong & Gangwei Cai & Zhoujin Mo & Weijun Gao & Lei Xu & Yuanxing Jiang & Jinming Jiang, 2020. "The Impact of COVID-19 on Tourist Satisfaction with B&B in Zhejiang, China: An Importance–Performance Analysis," IJERPH, MDPI, vol. 17(10), pages 1-19, May.
    19. Chu, Chun-Hsiao & Guo, Yu-Jian, 2015. "Developing similarity based IPA under intuitionistic fuzzy sets to assess leisure bikeways," Tourism Management, Elsevier, vol. 47(C), pages 47-57.
    20. Jih-Kuang Chen, 2021. "A New Approach for Diagonal Line Model of Importance-Performance Analysis: A Case Study of Tourist Satisfaction in China," SAGE Open, , vol. 11(1), pages 21582440219, January.

    More about this item

    Keywords

    Boarding school; importance-performance analysis; Islamic education.;
    All these keywords.

    JEL classification:

    • A21 - General Economics and Teaching - - Economic Education and Teaching of Economics - - - Pre-college
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • M12 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Personnel Management; Executives; Executive Compensation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:lrc:larrss:v:1:y:2016:i:2:p:1-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: H Kabir (email available below). General contact details of provider: http://www.socialsciencejournal.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.