IDEAS home Printed from https://ideas.repec.org/a/khe/journl/v7y2015i3p158-161.html
   My bibliography  Save this article

Health, Spa, Wellness Tourism. What is the Difference?

Author

Listed:
  • Gabriela Cecilia Stanciulescu
  • Gabriela Nicoleta Diaconescu
  • Dan Mihnea Diaconescu

Abstract

Significant changes in technical and product technology since the eighteenth century with the Industrial Revolution in Great Britain still have an important impact on tourism. Tourists are direct beneficiaries of the technology particularly when health and spa tourism. Purpose The proposed theme represents a new marketing approach of health and wellness tourism from the point of view of tourists segments taken into account and the products that are offered. In this particular case 20 distinct market segments emerged. Based on within cluster sum of squares, the most homogeneous segments were identified. The authors were seeking within cluster sum of squares to be as close to zero as possible indicating a tight spread around the centroid. In addition, they were interested in clusters being as dissimilar to each other as possible in order to achieve heterogeneity across segments.

Suggested Citation

  • Gabriela Cecilia Stanciulescu & Gabriela Nicoleta Diaconescu & Dan Mihnea Diaconescu, 2015. "Health, Spa, Wellness Tourism. What is the Difference?," Knowledge Horizons - Economics, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 7(3), pages 158-161, September.
  • Handle: RePEc:khe:journl:v:7:y:2015:i:3:p:158-161
    as

    Download full text from publisher

    File URL: http://orizonturi.ucdc.ro/arhiva/khe-vol7-nr3-2015/Stanciulescu_Diaconescu2.pdf
    Download Restriction: no

    File URL: http://orizonturi.ucdc.ro/arhiva/khe-vol7-nr3-2015/Stanciulescu_Diaconescu2.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Glenn Milligan, 1980. "An examination of the effect of six types of error perturbation on fifteen clustering algorithms," Psychometrika, Springer;The Psychometric Society, vol. 45(3), pages 325-342, September.
    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. Kim, Junyung & Shah, Asad Ullah Amin & Kang, Hyun Gook, 2020. "Dynamic risk assessment with bayesian network and clustering analysis," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    2. Goethner, Maximilian & Hornuf, Lars & Regner, Tobias, 2021. "Protecting investors in equity crowdfunding: An empirical analysis of the small investor protection act," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    3. John C. McCabe-Dansted & Arkadii Slinko, 2006. "Exploratory Analysis of Similarities Between Social Choice Rules," Group Decision and Negotiation, Springer, vol. 15(1), pages 77-107, January.
    4. Ali Abdelzadeh, 2014. "The Impact of Political Conviction on the Relation Between Winning or Losing and Political Dissatisfaction," SAGE Open, , vol. 4(2), pages 21582440145, May.
    5. Bordt, Michael, 2018. "Discourses in Ecosystem Accounting: A Survey of the Expert Community," Ecological Economics, Elsevier, vol. 144(C), pages 82-99.
    6. Chang, Yuan-Chieh & Chen, Min-Nan, 2016. "Service regime and innovation clusters: An empirical study from service firms in Taiwan," Research Policy, Elsevier, vol. 45(9), pages 1845-1857.
    7. Glenn Milligan, 1981. "A monte carlo study of thirty internal criterion measures for cluster analysis," Psychometrika, Springer;The Psychometric Society, vol. 46(2), pages 187-199, June.
    8. Geertsema, Paul & Lu, Helen, 2020. "The correlation structure of anomaly strategies," Journal of Banking & Finance, Elsevier, vol. 119(C).
    9. Cyril Atkinson-Clement & Eléonore Pigalle, 2021. "What can we learn from Covid-19 pandemic’s impact on human behaviour? The case of France’s lockdown," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-12, December.
    10. Johanna Mair & Julie Battilana & Julian Cardenas, 2012. "Organizing for Society: A Typology of Social Entrepreneuring Models," Journal of Business Ethics, Springer, vol. 111(3), pages 353-373, December.
    11. Önsel, Sule & Ülengin, Füsun & Ulusoy, Gündüz & Aktas, Emel & Kabak, Özgür & Topcu, Y. Ilker, 2008. "A new perspective on the competitiveness of nations," Socio-Economic Planning Sciences, Elsevier, vol. 42(4), pages 221-246, December.
    12. Aurora Torrente & Juan Romo, 2021. "Initializing k-means Clustering by Bootstrap and Data Depth," Journal of Classification, Springer;The Classification Society, vol. 38(2), pages 232-256, July.
    13. Glenn Milligan & Richard Cheng, 1996. "Measuring the influence of individual data points in a cluster analysis," Journal of Classification, Springer;The Classification Society, vol. 13(2), pages 315-335, September.
    14. Mingoti, Sueli A. & Lima, Joab O., 2006. "Comparing SOM neural network with Fuzzy c-means, K-means and traditional hierarchical clustering algorithms," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1742-1759, November.
    15. S. Martin & F. McLeay, 1998. "The Diversity of Farmers' Risk Management Strategies in a Deregulated New Zealand Environment," Journal of Agricultural Economics, Wiley Blackwell, vol. 49(2), pages 218-233, June.
    16. Ja-Shen Chen & Russell K H Ching & Yi-Shen Lin, 2004. "An extended study of the K-means algorithm for data clustering and its applications," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(9), pages 976-987, September.
    17. A. Gordon, 1990. "Constructing dissimilarity measures," Journal of Classification, Springer;The Classification Society, vol. 7(2), pages 257-269, September.
    18. Henner Gimpel & Daniel Rau & Maximilian Röglinger, 2018. "Understanding FinTech start-ups – a taxonomy of consumer-oriented service offerings," Electronic Markets, Springer;IIM University of St. Gallen, vol. 28(3), pages 245-264, August.
    19. Joan R. Rodgers & Abbas Valadkhani, 2006. "A Multidimensional Ranking of Australian Economics Departments," The Economic Record, The Economic Society of Australia, vol. 82(256), pages 30-43, March.
    20. Michael Brusco & Douglas Steinley, 2015. "Affinity Propagation and Uncapacitated Facility Location Problems," Journal of Classification, Springer;The Classification Society, vol. 32(3), pages 443-480, October.

    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:khe:journl:v:7:y:2015:i:3:p:158-161. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/ffucdro.html .

    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: Adi Sava (email available below). General contact details of provider: https://edirc.repec.org/data/ffucdro.html .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.