Skip to main content
SpringerLink
Log in

Commerce Districts: Conditions for Customer Overall Satisfaction in a Multi-attribute Framework

  • Chapter
  • First Online:
Applications of Artificial Intelligence and Neural Systems to Data Science

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 360))

  • 259 Accesses

Abstract

Extra-urban shopping malls are harming little retailers in Italian historic cities, as they do in many city centres across the world, and commercial districts are a possible way to sustain retail. The aim of the paper is to highlight what makes commercial districts located in urban centres attractive. We analyse data coming from eight Commerce Districts of the Northern Italy Veneto Region. Data were obtained by means of a survey in which customers were asked for their satisfaction concerning specific features of a district, like parking, accessibility or feeling welcome, and their overall satisfaction about the visiting experience. We use the Dominance-based Rough Set Approach (DRSA) to uncover the city centre district features that are deemed more significant by visitors. The results are presented in terms of “if… then” decision rules and to analyse them we propose a new synthetic indicator (the overall value of condition attribute strength) that highlights the conditions that most influence the overall assessment of the district. The premises for a high overall evaluation of the district turn out to be related to the quality of stay in the district, while surprisingly transport and security are not.

All authors contributed equally to this work.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    https://www.regione.veneto.it/web/attivita-produttive/distretti-del-commercio.

References

  1. Błaszczyński, J., Greco, S., Matarazzo, B., Słowiński, R., Szela̧g, M.: jMAF-Dominance-based rough set data analysis framework. In: Skowron, A., Suraj, Z. (eds.) Rough Sets and Intelligent Systems-Professor Zdzisław Pawlak in Memoriam, pp. 185–209. Springer, Berlin, Heidelberg (2013)

    Google Scholar 

  2. Brunetta, G., Caldrice, O.: Self-organisation and retail-led regeneration: A new territorial governance within the Italian context. Local Econ. 29(4–5), 334–344 (2014)

    Article  Google Scholar 

  3. Celotto, E., Ellero, A., Ferretti, P.: Conveying tourist ratings into an overall destination evaluation. Procedia Soc. Behav. Sci. 188, 35–41 (2015)

    Article  Google Scholar 

  4. Chen, L.F., Tsai, C.T.: Data mining framework based on rough set theory to improve location selection decisions: A case study of a restaurant chain. Tour. Manage. 53, 197–206 (2016)

    Article  Google Scholar 

  5. Greco, S., Matarazzo, B., Słowiński, R., Stefanowski, J.: Variable consistency model of dominance-based rough sets approach. In: Ziarko, W., Yao, Y. (eds.) International Conference on Rough Sets and Current Trends in Computing, pp. 170–181. Springer, Berlin, Heidelberg (2000)

    Google Scholar 

  6. Greco, S., Matarazzo, B., Słowiński, R.: Rough approximation of a preference relation by dominance relations. Eur. J. Oper. Res. 117(1), 63–83 (1999)

    Article  MATH  Google Scholar 

  7. Greco, S., Matarazzo, B., Słowiński, R.: Multicriteria classification. In: Klosgen, W., Zytkow, J. (eds.) Handbook of data mining and knowledge discovery, pp. 318–327. Oxford University Press, (2002)

    Google Scholar 

  8. Martucci, S.: Shopping streets and neighborhood identity: Retail theming as symbolic ownership in New York. City Community 18(4), 1123–1141 (2019)

    Article  MathSciNet  Google Scholar 

  9. Morandi, C.: Retail and public policies supporting the attractiveness of Italian town centres: The case of the Milan central districts. Urban Design Int. 16(3), 227–237 (2011)

    Article  Google Scholar 

  10. Słowiński, R., Greco, S., Matarazzo, B.: Rough sets in decision making. In: Meyers R (eds.) Encyclopedia of complexity and Systems Science, pp. 7753–7787. Springer, New York, NY (2009)

    Google Scholar 

  11. Teller, C., Reutterer, T.: The evolving concept of retail attractiveness: What makes retail agglomerations attractive when customers shop at them? J. Retail. Consum. Serv. 15(3), 127–143 (2008)

    Article  Google Scholar 

  12. Valli, C., Hammami, F.: Introducing business improvement districts (BIDs) in Sweden: A social justice appraisal. European Urban Region. Stud. 28(2), 155–172 (2021)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Economics, Ca’ Foscari University, Venice, Italy

    Nicola Camatti & Paola Ferretti

  2. Department of Management, Ca’ Foscari University, Venice, Italy

    Andrea Ellero

Authors
  1. Nicola Camatti
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Andrea Ellero
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Paola Ferretti
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Paola Ferretti .

Editor information

Editors and Affiliations

  1. Department of Psychology, University of Campania "Luigi Vanvitelli, Caserta, Italy

    Anna Esposito

  2. Fundació Tecnocampus, Pompeu Fabra University, Mataró, Barcelona, Spain

    Marcos Faundez-Zanuy

  3. Department of Civil, Energy, Environmental and Materials Engineering, University Mediterranea of Reggio Calabr, Reggio Calabria, Reggio Calabria, Italy

    Francesco Carlo Morabito

  4. Dipartimento di Elettronica e Telecomunicazioni, Politecnico di Torino, Torino, Italy

    Eros Pasero

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Camatti, N., Ellero, A., Ferretti, P. (2023). Commerce Districts: Conditions for Customer Overall Satisfaction in a Multi-attribute Framework. In: Esposito, A., Faundez-Zanuy, M., Morabito, F.C., Pasero, E. (eds) Applications of Artificial Intelligence and Neural Systems to Data Science. Smart Innovation, Systems and Technologies, vol 360. Springer, Singapore. https://doi.org/10.1007/978-981-99-3592-5_21

Download citation

  • DOI: https://doi.org/10.1007/978-981-99-3592-5_21

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-3591-8

  • Online ISBN: 978-981-99-3592-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation