Skip to main content
SpringerLink
Log in

Diagnosing service quality using customer reviews: an index approach based on sentiment and gap analyses

  • Empirical article
  • Published:
Service Business Aims and scope Submit manuscript

Abstract

Recognizing the importance and potential benefits of customer reviews as a source of the voice of customers, this study proposes an analytic framework and procedures for analyzing customer reviews—termed a customer review-based gap analysis—that are tailored to diagnosing service quality. To this end, we conduct sentiment analysis on customer reviews to capture customers’ perceptions and expectations at the service-feature level, which are not expressed explicitly in their reviews. A case study of a mobile navigation service shows that the customer review-based gap analysis can provide the practical information required to diagnose service quality from customer review data. The suggested indexes for capturing customers’ perceptions and expectations reveal quality strengths and drawbacks at the service-feature level. In addition, incorporating these indexes into those for quality performance and objectives based on a service-feature hierarchy provides a diagnostic tool capable of examining service quality in both overall as well as detailed aspects.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Akbaba A (2006) Measuring service quality in the hotel industry: a study in a business hotel in Turkey. Int J Hosp Manag 25(2):170–192

    Article  Google Scholar 

  • Akehurst G (2009) User generated content: the use of blogs for tourism organisations and tourism consumers. Serv Bus 3(1):51–61

    Article  Google Scholar 

  • Behara RS, Gundersen DE (2001) Analysis of quality management practices in services. Int J Qual Reliab Manag 18(6):574–604

    Article  Google Scholar 

  • Benamara F, Cesarano C, Picariello A, Recupero DR, Subrahmanian VS (2007) Sentiment analysis: adjectives and adverbs are better than adjectives alone. In: Proceedings of international conference on weblogs and social media, Boulder, CO, USA, pp 1–7

  • Bickart B, Schindler RM (2001) Internet forums as influential sources of consumer information. J Interact Mark 15(3):31–40

    Article  Google Scholar 

  • Büyüközkan G, Baykasoğlu A, Dereli T (2007) Integration of internet and web-based tools in new product development process. Prod Plan Control 18(1):44–53

    Article  Google Scholar 

  • Chang C-H, Lin JT (1991) Data flow model of total service quality management system. Comput Ind Eng 21(1–4):117–121

    Article  Google Scholar 

  • Cheng L-C, Ke Z-H, Shiue B-M (2011) Detecting changes of opinion from customer reviews. In: Proceedings of 2011 8th international conference on fuzzy systems and knowledge discovery, Shanghai, China, pp 1798–1802

  • Chou C-C, Liu L-J, Yih J-M, Huang S-F, Han T-C (2011) An evaluation of airline service quality using the fuzzy weighted SERVQUAL method. Appl Soft Comput 11(2):2117–2128

    Article  Google Scholar 

  • Cronin JJ Jr, Taylor SA (1992) Measuring service quality: a reexamination and extension. J Mark 56(3):55–68

    Article  Google Scholar 

  • Dabholkar PA, Thorpe DI, Rentz JO (1996) A measure of service quality for retail stores: scale development and validation. J Acad Mark Sci 24(1):3–16

    Article  Google Scholar 

  • Duan W, Cao Q, Yu Y, Levy S (2013) Mining online user-generated content: using sentiment analysis technique to study hotel service quality. In: Proceedings of 2013 46th Hawaii international conference on system sciences, Maui, Hawaii, pp 3119–3128

  • Fenn J, LeHong H (2012) Hype cycle for emerging technologies. Gartner, Stamford

    Google Scholar 

  • Hu M, Liu B (2004) Mining and summarizing customer reviews. In: Proceedings of the tenth ACM SIGKDD international conference on knowledge discovery and data mining, Seattle, WA, pp 168–177

  • Jain SK, Gupta G (2004) Measuring service quality: SERVQUAL vs. SERVPERF scales. Vikalpa 29(2):25–37

    Google Scholar 

  • Jiang L, Jun M, Yang Z (2015) Customer-perceived value and loyalty: how do key service quality dimensions matter in the context of B2C e-commerce?. Serv Bus: 1–17

  • Kim S-M, Hovy E (2004) Determining the sentiment of opinions. In: Proceedings of the 20th international conference on computational linguistics, Geneva, Switzerland

  • Landrum H, Prybutok VR (2004) A service quality and success model for the information service industry. Eur J Oper Res 156(3):628–642

    Article  Google Scholar 

  • Lemke F, Clark M, Wilson H (2011) Customer experience quality: an exploration in business and consumer contexts using repertory grid technique. J Acad Mark Sci 39(6):846–869

    Article  Google Scholar 

  • Liu B, Hu M, Cheng J (2005) Opinion observer: analyzing and comparing opinions on the Web. In: Proceedings of the 14th international conference on world wide web, Chiba, Japan, pp 342–351

  • Min H, Min H, Chung K (2002) Dynamic benchmarking of hotel service quality. J Serv Mark 16(4):302–321

    Article  Google Scholar 

  • Mullen T, Collier N (2004) Sentiment analysis using support vector machines with diverse information sources. In: Proceedings of the 2004 conference on empirical methods in natural language processing, Barcelona, Spain, pp 412–418

  • Parasuraman A, Zeithaml VA, Berry LL (1985) A conceptual model of service quality and its implications for future research. J Mark 49(4):41–50

    Article  Google Scholar 

  • Parasuraman A, Zeithaml VA, Berry LL (1988) SERVQUAL: a multiple-item scale for measuring consumer perceptions of service quality. J Retail 64(1):12–40

    Google Scholar 

  • Parasuraman A, Zeithaml VA, Malhotra A (2005) E-S-QUAL a multiple-item scale for assessing electronic service quality. J Serv Res 7(3):213–233

    Article  Google Scholar 

  • Raposo ML, Alves HM, Duarte PA (2009) Dimensions of service quality and satisfaction in healthcare: a patient’s satisfaction index. Serv Bus 3(1):85–100

    Article  Google Scholar 

  • Riloff E, Wiebe J, Wilson T (2003) Learning subjective nouns using extraction pattern bootstrapping. In: Proceedings of the 7th conference on natural language learning at HLT-NAACL 2003-volume 4, Edmonton, Canada, pp 25–32

  • Seth N, Deshmukh SG, Vrat P (2005) Service quality models: a review. Int J Qual Reliab Manag 22(9):913–949

    Article  Google Scholar 

  • Taboada M, Brooke J, Tofiloski M, Voll K, Stede M (2011) Lexicon-based methods for sentiment analysis. Comput Linguist 37(2):267–307

    Article  Google Scholar 

  • To WM, Tam JF, Cheung MF (2013) Explore how Chinese consumers evaluate retail service quality and satisfaction. Serv Bus 7(1):121–142

    Article  Google Scholar 

  • Turney PD (2002) Thumbs up or thumbs down? semantic orientation applied to unsupervised classification of reviews. In: Proceedings of the 40th annual meeting of the association for computational linguistics, Philadelphia, PA, USA, pp 417–424

  • Yang Z, Jun M, Peterson RT (2004) Measuring customer perceived online service quality: scale development and managerial implications. Int J Oper Prod Manag 24(11):1149–1174

    Article  Google Scholar 

  • Yu KT (2013) A measurement model for service capability from the customer perspective. Serv Bus 7(4):563–582

    Article  Google Scholar 

  • Ziegler CN, Skubacz M, Viermetz M. (2008) Mining and exploring unstructured customer feedback data using language models and treemap visualizations. In: Proceedings of the 2008 IEEE/WIC/ACM international conference on web intelligence and intelligent agent technology-volume 01, Sydney, Australia, pp 932–937

Download references

Acknowledgments

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. 2011-0030814).

Author information

Authors and Affiliations

  1. Department of Industrial Engineering, College of Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 151-742, Republic of Korea

    Bomi Song & Yongtae Park

  2. School of Business Administration, Ulsan National Institute of Science and Technology (UNIST), 50 UNIST-gil, Ulsan, 689-798, Republic of Korea

    Changyong Lee

  3. Department of Industrial and System Engineering, College of Engineering, Dongguk University, 30 Pildong-ro1-gill, Jung-gu, Seoul, 100-715, Republic of Korea

    Byungun Yoon

Authors
  1. Bomi Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Changyong Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Byungun Yoon
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yongtae Park
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yongtae Park.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Song, B., Lee, C., Yoon, B. et al. Diagnosing service quality using customer reviews: an index approach based on sentiment and gap analyses. Serv Bus 10, 775–798 (2016). https://doi.org/10.1007/s11628-015-0290-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11628-015-0290-1

Keywords

Search

Navigation