IDEAS home Printed from https://ideas.repec.org/a/spr/metron/v74y2016i3d10.1007_s40300-016-0100-0.html
   My bibliography  Save this article

A multilevel latent class analysis of the purchasing channels among European consumers

Author

Listed:
  • Chiara Dal Bianco

    (Ca’ Foscari University of Venice)

  • Omar Paccagnella

    (University of Padua)

  • Roberta Varriale

    (ISTAT-Italian National Statistical Institute)

Abstract

This work aims at investigating similarities and differences in the ways of purchasing goods and services by European citizens—in particular the consumer behaviour on the preferred purchasing channels among web, phone, mail and sales representatives—by exploiting data collected through the Eurobarometer 69.1 survey in 2008. To this aim, we adopt a multilevel latent class solution, which allows to simultaneously cluster individuals and countries. The overall result is that most countries can be grouped in classes that follow a geographical division, while European citizens can be divided in classes with some specific profiles: a large proportion of consumers have not confidence with alternative purchasing channels yet, particularly among older respondents; most consumers still prefer to buy from sellers or providers located in their own country; more educated individuals show a widespread use of the web; a class of potential purchasers may be determined, particularly among younger people.

Suggested Citation

  • Chiara Dal Bianco & Omar Paccagnella & Roberta Varriale, 2016. "A multilevel latent class analysis of the purchasing channels among European consumers," METRON, Springer;Sapienza Università di Roma, vol. 74(3), pages 293-309, December.
    • Handle: RePEc:spr:metron:v:74:y:2016:i:3:d:10.1007_s40300-016-0100-0
    DOI: 10.1007/s40300-016-0100-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40300-016-0100-0
    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/s40300-016-0100-0?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. Bhatnagar, Amit & Ghose, Sanjoy, 2004. "A latent class segmentation analysis of e-shoppers," Journal of Business Research, Elsevier, vol. 57(7), pages 758-767, July.
    2. Vermunt, Jeroen K. & Magidson, Jay, 2003. "Latent class models for classification," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 531-537, January.
    3. Formann, Anton K., 2007. "Mixture analysis of multivariate categorical data with covariates and missing entries," Computational Statistics & Data Analysis, Elsevier, vol. 51(11), pages 5236-5246, July.
    4. Bartolucci, Francesco & Bacci, Silvia & Gnaldi, Michela, 2014. "MultiLCIRT: An R package for multidimensional latent class item response models," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 971-985.
    5. Lemmens, A. & Croux, C. & Dekimpe, M.G., 2007. "Consumer confidence in Europe : United in diversity," Other publications TiSEM ea8c3268-2c0b-4fcc-9d4a-6, Tilburg University, School of Economics and Management.
    6. Hamparsum Bozdogan, 1987. "Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 345-370, September.
    7. Bijmolt, T.H.A. & Paas, L.J. & Vermunt, J.K., 2004. "Country and consumer segmentation : Multi-level latent class analysis of financial product ownership," Other publications TiSEM fb506162-d125-4091-9083-9, Tilburg University, School of Economics and Management.
    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. Oppewal, Harmen & Paas, Leonard J. & Crouch, Geoffrey I. & Huybers, Twan, 2010. "Segmenting consumers based on how they spend a tax rebate: An analysis of the Australian stimulus payment," Journal of Economic Psychology, Elsevier, vol. 31(4), pages 510-519, August.
    2. Luca De Angelis, 2013. "Latent class models for financial data analysis: some statistical developments," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 22(2), pages 227-242, June.
    3. Fonseca, Jaime R.S., 2009. "Customer satisfaction study via a latent segment model," Journal of Retailing and Consumer Services, Elsevier, vol. 16(5), pages 352-359.
    4. Grewal, Rajdeep & Chakravarty, Anindita & Ding, Min & Liechty, John, 2008. "Counting chickens before the eggs hatch: Associating new product development portfolios with shareholder expectations in the pharmaceutical sector," International Journal of Research in Marketing, Elsevier, vol. 25(4), pages 261-272.
    5. Leonard Paas & Tammo Bijmolt & Jeroen Vermunt, 2015. "Long-term developments of respondent financial product portfolios in the EU: a multilevel latent class analysis," METRON, Springer;Sapienza Università di Roma, vol. 73(2), pages 249-262, August.
    6. Lasarov, Wassili & Mai, Robert & García de Frutos, Nieves & Egea, José Manuel Ortega & Hoffmann, Stefan, 2019. "Counter-arguing as barriers to environmentally motivated consumption reduction: A multi-country study," International Journal of Research in Marketing, Elsevier, vol. 36(2), pages 281-305.
    7. Chiou, Yu-Chiun & Jou, Rong-Chang & Kao, Chu-Yun & Fu, Chiang, 2013. "The adoption behaviours of freeway electronic toll collection: A latent class modelling approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 266-280.
    8. Ioana Gutu & Daniela Tatiana Agheorghiesei & Alexandru Tugui, 2023. "Assessment of a Workforce Sustainability Tool through Leadership and Digitalization," IJERPH, MDPI, vol. 20(2), pages 1-30, January.
    9. Neslin, Scott A., 2022. "The omnichannel continuum: Integrating online and offline channels along the customer journey," Journal of Retailing, Elsevier, vol. 98(1), pages 111-132.
    10. Daniela Andreini & Diego Rinallo & Giuseppe Pedeliento & Mara Bergamaschi, 2017. "Brands and Religion in the Secularized Marketplace and Workplace: Insights from the Case of an Italian Hospital Renamed After a Roman Catholic Pope," Journal of Business Ethics, Springer, vol. 141(3), pages 529-550, March.
    11. S. A. Abu Bakar & Saralees Nadarajah & Z. A. Absl Kamarul Adzhar, 2018. "Loss modeling using Burr mixtures," Empirical Economics, Springer, vol. 54(4), pages 1503-1516, June.
    12. Yeung, Matthew C.H. & Ramasamy, Bala & Chen, Junsong & Paliwoda, Stan, 2013. "Customer satisfaction and consumer expenditure in selected European countries," International Journal of Research in Marketing, Elsevier, vol. 30(4), pages 406-416.
    13. Byrd, T. A. & Marshall, T. E., 1997. "Relating information technology investment to organizational performance: a causal model analysis," Omega, Elsevier, vol. 25(1), pages 43-56, February.
    14. Herbert Hoijtink & Meinte Vollema, 2003. "Contemporary Extensions of the Rasch Model," Quality & Quantity: International Journal of Methodology, Springer, vol. 37(3), pages 263-276, August.
    15. Jaewoong Yun, 2023. "Strategies for Improving the Sustainability of Fare-Free Policy for the Elderly through Preferences by Travel Modes," Sustainability, MDPI, vol. 15(20), pages 1-14, October.
    16. Malerba, Martino E. & Connolly, Sean R. & Heimann, Kirsten, 2015. "An experimentally validated nitrate–ammonium–phytoplankton model including effects of starvation length and ammonium inhibition on nitrate uptake," Ecological Modelling, Elsevier, vol. 317(C), pages 30-40.
    17. Aline Riboli Marasca & Maurício Scopel Hoffmann & Anelise Reis Gaya & Denise Ruschel Bandeira, 2021. "Subjective Well-Being and Psychopathology Symptoms: Mental Health Profiles and their Relations with Academic Achievement in Brazilian Children," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 14(3), pages 1121-1137, June.
    18. Vermunt, Jeroen K., 2007. "A hierarchical mixture model for clustering three-way data sets," Computational Statistics & Data Analysis, Elsevier, vol. 51(11), pages 5368-5376, July.
    19. Monica Pratesi & Claudio Ceccarelli & Stefano Menghinello, 2021. "Citizen-Generated Data and Official Statistics: an application to SDG indicators," Discussion Papers 2021/274, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    20. Friederike Paetz, 2016. "Persönlichkeitsmerkmale als Segmentierungsvariablen: Eine empirische Studie [Personality traits for market segmentation: An empirical study]," Schmalenbach Journal of Business Research, Springer, vol. 68(3), pages 279-306, 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:metron:v:74:y:2016:i:3:d:10.1007_s40300-016-0100-0. 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.