IDEAS home Printed from https://ideas.repec.org/a/spr/soinre/v156y2021i2d10.1007_s11205-020-02294-y.html
   My bibliography  Save this article

Restricted Common Component and Specific Weight Analysis: A Constrained Explorative Approach for the Customer Satisfaction Evaluation

Author

Listed:
  • Pietro Amenta

    (University of Sannio)

  • Antonio Lucadamo

    (University of Sannio)

  • Antonello D’Ambra

    (University of Campania “Vanvitelli”)

Abstract

Servqual is a service measurement multidimensional model (Parasuraman et al. in J Mark 49(4):41–50, 1985; Parasuraman et al. in J Retail 64:12–40, 1988) which involves a set of five dimensions representing service quality. It is based on a questionnaire to measure the gaps between customers’ expectations and perceptions of service. A re-examination and extension of this model, named Servperf, is instead based only on the perceptions (Taylor in J Mark 56(3):55–68, 1992; Taylor in J Mark 58:125–131, 1994). Common Components and Specific Weights Analysis (Qannari et al. in Food Qual Prefer 11:151–154, 2000) (CCSWA) is a useful tool to analyze customer satisfaction evaluation data. The rationale behind this method is the existence of a common structure to the data tables. Therefore, it determines a common space of representation for all data. Each table, which represents a ServPerf dimension, assesses a specific weight to each dimension of the common space. Customer satisfaction can be then investigated with respect to a common reference system where all the dimensions contribute to forming it. Sometimes we may have additional knowledge about some relationships among the service variables that can be incorporated in the analysis as external information. The aim of this paper is then to provide an extension of CCSWA based on an objective function which takes directly into account the external information (as linear constraints). This extension may lead to a simpler interpretation of the analysis results and to explore new relationships. A student satisfaction evaluation study highlights this hypothesis.

Suggested Citation

  • Pietro Amenta & Antonio Lucadamo & Antonello D’Ambra, 2021. "Restricted Common Component and Specific Weight Analysis: A Constrained Explorative Approach for the Customer Satisfaction Evaluation," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 409-427, August.
  • Handle: RePEc:spr:soinre:v:156:y:2021:i:2:d:10.1007_s11205-020-02294-y
    DOI: 10.1007/s11205-020-02294-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11205-020-02294-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11205-020-02294-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Paul Horst, 1961. "Relations amongm sets of measures," Psychometrika, Springer;The Psychometric Society, vol. 26(2), pages 129-149, June.
    2. Takane, Yoshio & Yanai, Haruo & Hwang, Heungsun, 2006. "An improved method for generalized constrained canonical correlation analysis," Computational Statistics & Data Analysis, Elsevier, vol. 50(1), pages 221-241, January.
    3. John Geer, 1984. "Linear relations amongk sets of variables," Psychometrika, Springer;The Psychometric Society, vol. 49(1), pages 79-94, March.
    4. J. Carroll & Jih-Jie Chang, 1970. "Analysis of individual differences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition," Psychometrika, Springer;The Psychometric Society, vol. 35(3), pages 283-319, September.
    5. Yoshio Takane & Tadashi Shibayama, 1991. "Principal component analysis with external information on both subjects and variables," Psychometrika, Springer;The Psychometric Society, vol. 56(1), pages 97-120, March.
    6. Henk Kiers, 1991. "Hierarchical relations among three-way methods," Psychometrika, Springer;The Psychometric Society, vol. 56(3), pages 449-470, September.
    7. Lavit, Christine & Escoufier, Yves & Sabatier, Robert & Traissac, Pierre, 1994. "The ACT (STATIS method)," Computational Statistics & Data Analysis, Elsevier, vol. 18(1), pages 97-119, August.
    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. Tsuen-Ho Hsu & Sen-Tien Her & Jia-Jeng Hou, 2021. "Developing Universally Applicable Service Quality Assessment Model Based on the Theory of Consumption Values, and Using Fuzzy Linguistic Preference Relations to Empirically Test Three Industries," Mathematics, MDPI, vol. 9(20), pages 1-32, October.

    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. Pietro Amenta & Antonio Lucadamo & Antonello D’Ambra, 2019. "Customer satisfaction evaluation by common component and specific weight analysis using a mixed coding system," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(5), pages 2491-2505, September.
    2. Kunert, Joachim & Qannari, El Mostafa, 1998. "A simple alternative to Generalized Procrustes Analysis: Application to sensory profiling data," Technical Reports 1998,32, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    3. Casin, Ph., 2001. "A generalization of principal component analysis to K sets of variables," Computational Statistics & Data Analysis, Elsevier, vol. 35(4), pages 417-428, February.
    4. Tenenhaus, Arthur & Tenenhaus, Michel, 2014. "Regularized generalized canonical correlation analysis for multiblock or multigroup data analysis," European Journal of Operational Research, Elsevier, vol. 238(2), pages 391-403.
    5. Mariela González-Narváez & María José Fernández-Gómez & Susana Mendes & José-Luis Molina & Omar Ruiz-Barzola & Purificación Galindo-Villardón, 2021. "Study of Temporal Variations in Species–Environment Association through an Innovative Multivariate Method: MixSTATICO," Sustainability, MDPI, vol. 13(11), pages 1-25, May.
    6. Hanafi, Mohamed & Kiers, Henk A.L., 2006. "Analysis of K sets of data, with differential emphasis on agreement between and within sets," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1491-1508, December.
    7. Lei-Hong Zhang & Li-Zhi Liao & Li-Ming Sun, 2011. "Towards the global solution of the maximal correlation problem," Journal of Global Optimization, Springer, vol. 49(1), pages 91-107, January.
    8. Herbert Marsh & Robert Boik, 1993. "Reviews," Psychometrika, Springer;The Psychometric Society, vol. 58(1), pages 145-152, March.
    9. Tenenhaus, Arthur & Philippe, Cathy & Frouin, Vincent, 2015. "Kernel Generalized Canonical Correlation Analysis," Computational Statistics & Data Analysis, Elsevier, vol. 90(C), pages 114-131.
    10. Lei-Hong Zhang & Li-Zhi Liao, 2012. "An alternating variable method for the maximal correlation problem," Journal of Global Optimization, Springer, vol. 54(1), pages 199-218, September.
    11. Michael Windham & J. Hutchinson & Shizuhiko Nishisato & Ludovic Lebart & George Furnas & Richard Dubes & Frank Critchley & A. Gordon & Fionn Murtagh & Ulf Bockenholt & Philip Hopke & Daniel Wartenberg, 1988. "Book reviews," Journal of Classification, Springer;The Classification Society, vol. 5(1), pages 105-154, March.
    12. Michel Tenenhaus & Arthur Tenenhaus & Patrick J. F. Groenen, 2017. "Regularized Generalized Canonical Correlation Analysis: A Framework for Sequential Multiblock Component Methods," Psychometrika, Springer;The Psychometric Society, vol. 82(3), pages 737-777, September.
    13. Vartan Choulakian, 2011. "Picture of all Solutions of Successive 2-Block Maxbet Problems," Psychometrika, Springer;The Psychometric Society, vol. 76(4), pages 550-563, October.
    14. Albert Maydeu-Olivares & Ishwar Sethi & Phipps Arabie & A. Tanguiane & K. Klauer & Pierre Hansen & Klaas Sijtsma & M. Windham, 1995. "Book reviews," Journal of Classification, Springer;The Classification Society, vol. 12(1), pages 137-158, March.
    15. Jacques Bénasséni & Mohammed Bennani Dosse, 2012. "Analyzing multiset data by the Power STATIS-ACT method," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 6(1), pages 49-65, April.
    16. Vivien, Myrtille & Sabatier, Robert, 2004. "A generalization of STATIS-ACT strategy: DO-ACT for two multiblocks tables," Computational Statistics & Data Analysis, Elsevier, vol. 46(1), pages 155-171, May.
    17. Anwa Zhou & Xin Zhao & Jinyan Fan & Yanqin Bai, 2018. "Tensor maximal correlation problems," Journal of Global Optimization, Springer, vol. 70(4), pages 843-858, April.
    18. Husson, F. & Pages, J., 2006. "INDSCAL model: geometrical interpretation and methodology," Computational Statistics & Data Analysis, Elsevier, vol. 50(2), pages 358-378, January.
    19. Beaton, Derek & Chin Fatt, Cherise R. & Abdi, Hervé, 2014. "An ExPosition of multivariate analysis with the singular value decomposition in R," Computational Statistics & Data Analysis, Elsevier, vol. 72(C), pages 176-189.
    20. Carmen C. Rodríguez-Martínez & Mitzi Cubilla-Montilla & Purificación Vicente-Galindo & Purificación Galindo-Villardón, 2021. "Sparse STATIS-Dual via Elastic Net," Mathematics, MDPI, vol. 9(17), pages 1-15, August.

    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:spr:soinre:v:156:y:2021:i:2:d:10.1007_s11205-020-02294-y. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.