IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i10p3564-d173856.html
   My bibliography  Save this article

An Approach to Discovering Product/Service Improvement Priorities: Using Dynamic Importance-Performance Analysis

Author

Listed:
  • Jiacong Wu

    (School of International Business, Jinan University (Zhuhai Campus), Zhuhai 519070, China
    Institute of Management Science and Engineering, Jinan University (Zhuhai Campus), Zhuhai 519070, China)

  • Yu Wang

    (School of International Business, Jinan University (Zhuhai Campus), Zhuhai 519070, China
    Institute of Management Science and Engineering, Jinan University (Zhuhai Campus), Zhuhai 519070, China)

  • Ru Zhang

    (School of International Business, Jinan University (Zhuhai Campus), Zhuhai 519070, China
    Institute of Management Science and Engineering, Jinan University (Zhuhai Campus), Zhuhai 519070, China)

  • Jing Cai

    (University of Aberdeen Business School, Scotland AB24 5UA, UK)

Abstract

The cost budget and resources of a business are limited. In order to be competitive sustainably in the market, it is necessary for a businesses to discover the improvement priorities of their product/service features effectively and allocate their resources appropriately for higher customer satisfaction. Online customer review mining has been attracting increasing attention for businesses to discover priorities of product/service improvement from online customer reviews. Despite some prior related studies, their methods have several limitations, such as simply using the frequencies of mentioned product features in reviews as an indicator of importance; neglecting the market competition; and focusing only on the static importance and performance of the target product/service features. To address those limitations, this study proposes a novel approach to discovering a product/service’s improvement priorities through dynamic importance-performance analysis of online customer reviews. It first clusters similar features into a feature group and calculate the relative performance of the feature groups using sentiment analysis. Next, the importance of each feature group’s performance to overall customer satisfaction is measured by the factor categories based on the Kano’s model. The factor categories are determined by the significance values of each feature group in both positive and negative sentiment polarities derived from the constructed decision tree. Finally, feature improvement priorities of a target product/service will be discovered based on the dynamic performance trend and predicted importance using a dynamic importance-performance analysis. The evaluation results show that the dynamic importance-performance analysis approach proposed in this study is a much better approach for product/service improvement priorities discovering than the product opportunity mining approach proposed in the prior studies. This study makes new research contributions to automatic discovery of product/service improvement priorities from large-scale online customer reviews. The proposed approach can also be used for product/service performance monitoring and customer needs analysis to improve product/service design and marketing campaigns.

Suggested Citation

  • Jiacong Wu & Yu Wang & Ru Zhang & Jing Cai, 2018. "An Approach to Discovering Product/Service Improvement Priorities: Using Dynamic Importance-Performance Analysis," Sustainability, MDPI, vol. 10(10), pages 1-26, October.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:10:p:3564-:d:173856
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/10/3564/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/10/10/3564/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Guo, Yue & Barnes, Stuart J. & Jia, Qiong, 2017. "Mining meaning from online ratings and reviews: Tourist satisfaction analysis using latent dirichlet allocation," Tourism Management, Elsevier, vol. 59(C), pages 467-483.
    2. Kun-Tzu Yu, 2013. "A measurement model for service capability from the customer perspective," Service Business, Springer;Pan-Pacific Business Association, vol. 7(4), pages 563-582, December.
    3. Fallon, Paul & Schofield, Peter, 2006. "The dynamics of destination attribute importance," Journal of Business Research, Elsevier, vol. 59(6), pages 709-713, June.
    4. Wei-Jaw Deng & Ying-Feng Kuo & Wen-Chin Chen, 2008. "Revised importance--performance analysis: three-factor theory and benchmarking," The Service Industries Journal, Taylor & Francis Journals, vol. 28(1), pages 37-51, January.
    5. Gary Akehurst, 2009. "User generated content: the use of blogs for tourism organisations and tourism consumers," Service Business, Springer;Pan-Pacific Business Association, vol. 3(1), pages 51-61, March.
    6. Bomi Song & Changyong Lee & Byungun Yoon & Yongtae Park, 2016. "Diagnosing service quality using customer reviews: an index approach based on sentiment and gap analyses," Service Business, Springer;Pan-Pacific Business Association, vol. 10(4), pages 775-798, December.
    7. 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.
    8. Seyed Hosseini & Alireza Ziaei Bideh, 2014. "A data mining approach for segmentation-based importance-performance analysis (SOM–BPNN–IPA): a new framework for developing customer retention strategies," Service Business, Springer;Pan-Pacific Business Association, vol. 8(2), pages 295-312, June.
    9. 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.
    10. Taplin, Ross H., 2012. "Competitive importance-performance analysis of an Australian wildlife park," Tourism Management, Elsevier, vol. 33(1), pages 29-37.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chi-Hung Lo, 2021. "Application of Refined Kano’s Model to Shoe Production and Consumer Satisfaction Assessment," Sustainability, MDPI, vol. 13(5), pages 1-22, February.
    2. Hanyang Luo & Wugang Song & Wanhua Zhou & Xudong Lin & Sumin Yu, 2023. "An Analysis Framework to Reveal Automobile Users’ Preferences from Online User-Generated Content," Sustainability, MDPI, vol. 15(18), pages 1-29, September.
    3. Kuen-Suan Chen & Chang-Hsien Hsu & Ting-Hsin Hsu, 2021. "Attribute Service Performance Index Based on Poisson Process," Mathematics, MDPI, vol. 9(23), pages 1-10, December.
    4. Teng-Chiao Lin & Hsing-Hui Chen & Kuen-Suan Chen & Yen-Po Chen & Shao-Hsun Chang, 2023. "Decision-Making Model of Performance Evaluation Matrix Based on Upper Confidence Limits," Mathematics, MDPI, vol. 11(16), pages 1-11, August.
    5. Mingyuan Li & Kuen-Suan Chen & Chun-Min Yu & Chun-Ming Yang, 2021. "A Fuzzy Evaluation Decision Model for the Ratio Operating Performance Index," Mathematics, MDPI, vol. 9(3), pages 1-12, January.
    6. Chun-Hung Yu & Chin-Chia Liu & Kuen-Suan Chen & Chun-Min Yu, 2020. "Constructing Fuzzy Hypothesis Methods to Determine Critical-To-Quality Service Items," Mathematics, MDPI, vol. 8(4), pages 1-16, April.
    7. Michal Pohludka & Hana Štverková, 2019. "The Best Practice of CRM Implementation for Small- and Medium-Sized Enterprises," Administrative Sciences, MDPI, vol. 9(1), pages 1-17, March.
    8. Tai-Shan Lee & Ching-Hsin Wang & Chun-Min Yu, 2019. "Fuzzy Evaluation Model for Enhancing E-Learning Systems," Mathematics, MDPI, vol. 7(10), pages 1-11, October.
    9. Lifeng He & Dongmei Han & Xiaohang Zhou & Zheng Qu, 2020. "The Voice of Drug Consumers: Online Textual Review Analysis Using Structural Topic Model," IJERPH, MDPI, vol. 17(10), pages 1-18, May.

    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. Chen, Kuan-Yu, 2014. "Improving importance-performance analysis: The role of the zone of tolerance and competitor performance. The case of Taiwan's hot spring hotels," Tourism Management, Elsevier, vol. 40(C), pages 260-272.
    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. 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.
    4. 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.
    5. Phadermrod, Boonyarat & Crowder, Richard M. & Wills, Gary B., 2019. "Importance-Performance Analysis based SWOT analysis," International Journal of Information Management, Elsevier, vol. 44(C), pages 194-203.
    6. 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.
    7. Guizzardi, Andrea & Stacchini, Annalisa, 2017. "Destinations strategic groups via Multivariate Competition-based IPA," Tourism Management, Elsevier, vol. 58(C), pages 40-50.
    8. Seungju Nam & Hyun Cheol Lee, 2019. "A Text Analytics-Based Importance Performance Analysis and Its Application to Airline Service," Sustainability, MDPI, vol. 11(21), pages 1-24, November.
    9. 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.
    10. Junegak Joung & Ki-Hun Kim & Kwangsoo Kim, 2021. "Data-Driven Approach to Dual Service Failure Monitoring From Negative Online Reviews: Managerial Perspective," SAGE Open, , vol. 11(1), pages 21582440209, January.
    11. 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.
    12. Azzopardi, Ernest & Nash, Robert, 2013. "A critical evaluation of importance–performance analysis," Tourism Management, Elsevier, vol. 35(C), pages 222-233.
    13. Prasad, Prashant & Maitra, Bhargab, 2019. "Identifying areas of interventions for improvement of shared modes for school trips," Transportation Research Part A: Policy and Practice, Elsevier, vol. 121(C), pages 122-135.
    14. 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.
    15. 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.
    16. Bomi Song & Changyong Lee & Byungun Yoon & Yongtae Park, 2016. "Diagnosing service quality using customer reviews: an index approach based on sentiment and gap analyses," Service Business, Springer;Pan-Pacific Business Association, vol. 10(4), pages 775-798, December.
    17. Na Rang Kim & Soon Goo Hong, 2020. "Text mining for the evaluation of public services: the case of a public bike-sharing system," Service Business, Springer;Pan-Pacific Business Association, vol. 14(3), pages 315-331, September.
    18. Reema Bera & Bhargab Maitra, 2023. "Identification of Priority Areas of Improvement for Small Passenger Car Segment in Indian Market," Vision, , vol. 27(2), pages 225-242, April.
    19. Hsin-Hung Wu & Yung-Tai Tang & Jyh-Wei Shyu, 2010. "A case of applying importance-performance analysis in identifying key success factors to develop marketing strategies," Quality & Quantity: International Journal of Methodology, Springer, vol. 44(6), pages 1207-1218, October.
    20. Kar, Manaswinee & Sadhukhan, Shubhajit & Parida, Manoranjan, 2022. "Assessing commuters’ perceptions towards improvement of intermediate public transport as access modes to metro stations," Transport Policy, Elsevier, vol. 129(C), pages 140-155.

    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:gam:jsusta:v:10:y:2018:i:10:p:3564-:d:173856. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.