Skip to main content
SpringerLink
Log in

Enhanced Buying Experiences in Smart Cities: The SMARTBUY Approach

  • Conference paper
  • First Online:
Ambient Intelligence (AmI 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11912))

Included in the following conference series:

Abstract

The establishment of shopping malls and the growth of online shopping increasingly diminishes the turnover of “small”, independent retailers in urban environments. However, retailers could reverse this trend through complementing the offline experiences they already offer with online offerings and establishing business “alliances” to achieve economies of scale and enable the provision of innovative digital services. The EU-funded project SMARTBUY aims at realizing the concept of a “distributed shopping mall” ecosystem which allows retailers to band together in a large commercial coalition which generates added-value for its retailers-members and customers: centralized products and services inventory management; geo-located marketing of products/services; location-based search for products offered by nearby retailers; personalized recommendations for purchasing products based on innovative recommendation systems. In effect, SMARTBUY proposes a blended shopping paradigm, wherein the benefits of online shopping are combined with the appeal of traditional store shopping. The article provides an overview of the main outcomes and achievements of SMARTBUY. It also reports on conclusions drawn in the context of the project’s official pilot execution in four European cities.

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 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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.

    http://smartbuy.tech/.

  2. 2.

    http://90.83.46.3/.

  3. 3.

    CF is a method of making automatic predictions (filtering) about the interests of a user by collecting preferences or ‘taste’ information from many users (collaborating). The underlying assumption of the CF approach is that, if a person A has the same opinion as a person B on a subject, A is more likely to share B’s opinion on a different subject than that of a randomly chosen person.

  4. 4.

    https://play.google.com/store/apps/details?id=com.smartbuyshopping.app .

References

  1. Amaxilatis, D., Giannakopoulou, K.: Evaluating retailers in a smart-buying environment using smart city infrastructures. In: 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), pp. 284–288 (2018)

    Google Scholar 

  2. Chatzigiannakis, I., Mylonas, G., Vitaletti, A.: Urban pervasive applications: challenges, scenarios and case studies. Comput. Sci. Rev. 5(1), 103–118 (2011)

    Article  Google Scholar 

  3. Chen, B.W., Ji, W.: Intelligent marketing in smart cities: crowdsourced data for geo-conquesting. IT Prof. 18(4), 18–24 (2016)

    Article  Google Scholar 

  4. Gavalas, D., Kenteris, M.: A web-based pervasive recommendation system for mobile tourist guides. Pers. Ubiquitous Comput. 15(7), 759–770 (2011)

    Article  Google Scholar 

  5. Gavalas, D., Konstantopoulos, C., Mastakas, K., Pantziou, G.: Mobile recommender systems in tourism. J. Netw. Comput. Appl. 39, 319–333 (2014)

    Article  Google Scholar 

  6. Gensler, S., Neslin, S.A., Verhoef, P.C.: The showrooming phenomenon: it’s more than just about price. J. Interact. Mark. 38, 29–43 (2017)

    Article  Google Scholar 

  7. Giffinger, R., Fertner, C., Kramar, H., Meijers, E.: City-ranking of European medium-sized cities. Cent. Reg. Sci. Vienna UT, 1–12 (2007)

    Google Scholar 

  8. Hsiao, M.H.: Shopping mode choice: physical store shopping versus e-shopping. Transp. Res. Part E: Logistics Transp. Rev. 45(1), 86–95 (2009)

    Article  Google Scholar 

  9. Kowatsch, T., Maass, W.: In-store consumer behavior: how mobile recommendation agents influence usage intentions, product purchases, and store preferences. Comput. Hum. Behav. 26(4), 697–704 (2010)

    Article  Google Scholar 

  10. Vinod Kumar, T.M., Dahiya, B.: Smart economy in smart cities. In: Vinod Kumar, T.M. (ed.) Smart Economy in Smart Cities. ACHS, pp. 3–76. Springer, Singapore (2017). https://doi.org/10.1007/978-981-10-1610-3_1

    Chapter  Google Scholar 

  11. Lin, C., Hong, C.: Using customer knowledge in designing electronic catalog. Expert Syst. Appl. 34(1), 119–127 (2008)

    Article  Google Scholar 

  12. OrganiCity project. http://organicity.eu/

  13. Pantano, E., Timmermans, H.: What is smart for retailing? Procedia Environ. Sci. 22, 101–107 (2014)

    Article  Google Scholar 

  14. Pantano, E., Priporas, C.V.: The effect of mobile retailing on consumers’ purchasing experiences: a dynamic perspective. Comput. Hum. Behav. 61, 548–555 (2016)

    Article  Google Scholar 

  15. Pantano, E., Rese, A., Baier, D.: Enhancing the online decision-making process by using augmented reality: a two country comparison of youth markets. J. Retail. Consum. Serv. 38, 81–95 (2017)

    Article  Google Scholar 

  16. Piotrowicz, W., Cuthbertson, R.: Introduction to the special issue information technology in retail: toward omnichannel retailing. Int. J. Electron. Commer. 18(4), 5–16 (2014)

    Article  Google Scholar 

  17. Sanyal, P., Ghosh, A.: Attractiveness of retail agglomeration based on product type: an experimental study. Available at SSRN 2989281 (2017)

    Google Scholar 

  18. Sapiezynski, P., Stopczynski, A., Gatej, R., Lehmann, S.: Tracking human mobility using WiFi signals. PLoS ONE 10(7), e0130824 (2015)

    Article  Google Scholar 

  19. Sassi, I.B., Mellouli, S., Yahia, S.B.: Context-aware recommender systems in mobile environment: on the road of future research. Inf. Syst. 72, 27–61 (2017)

    Article  Google Scholar 

  20. SMARTBUY Deliverable 2.8: SMARTBUY system – final prototypes (2019)

    Google Scholar 

  21. SMARTBUY Deliverable 3.2: Wireless geo-located marketing tool (2017)

    Google Scholar 

  22. SMARTBUY Deliverable 4.4: Integration of advanced tools for products digitalization and monitoring (2017)

    Google Scholar 

  23. SMARTBUY Deliverable 5.4: Deliverable 5.4 report on feedback from real-life customers and retailers (2019)

    Google Scholar 

  24. Theodoridis, E., Mylonas, G., Chatzigiannakis, I.: Developing an IoT smart city framework. In: IISA 2013, pp. 1–6 (2013)

    Google Scholar 

  25. Yang, W.S., Cheng, H.C., Dia, J.B.: A location-aware recommender system for mobile shopping environments. Expert Syst. Appl. 34(1), 437–445 (2008)

    Article  Google Scholar 

  26. Yuan, S.T., Tsao, Y.W.: A Recommendation mechanism for contextualized mobile advertising. Expert Syst. Appl. 24(4), 399–414 (2003)

    Article  Google Scholar 

Download references

Acknowledgement

This work has been partly supported by the University of Piraeus Research Center. The research has also been supported by the EU H2020 Programme under grant agreement no. 687960 (SMARTBUY). The research work of D. Gavalas and T. Chatzidimitris has been co-financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH – CREATE – INNOVATE (project code: T1EDK-01572).

Author information

Authors and Affiliations

  1. Planet Media Studios, Madrid, Spain

    Lorena Bourg

  2. Department of Cultural Technology and Communication, University of the Aegean, Mytilene, Greece

    Thomas Chatzidimitris & Vlasios Kasapakis

  3. Department of Computer, Control and Informatics Engineering, Sapienza University of Rome, Rome, Italy

    Ioannis Chatzigiannakis

  4. Department of Product and Systems Design Engineering, University of the Aegean, Syros, Greece

    Damianos Gavalas

  5. Department of Computer Engineering and Informatics, University of Patras, Patras, Greece

    Kalliopi Giannakopoulou & Christos Zaroliagis

  6. Department of Informatics, University of Piraeus, Piraeus, Greece

    Charalampos Konstantopoulos & Damianos Kypriadis

  7. Department of Informatics and Computer Engineering, University of West Attica, Athens, Greece

    Grammati Pantziou

  8. Computer Technology Institute and Press (CTI), Patras, Greece

    Thomas Chatzidimitris, Ioannis Chatzigiannakis, Damianos Gavalas, Kalliopi Giannakopoulou, Vlasios Kasapakis, Charalampos Konstantopoulos, Damianos Kypriadis, Grammati Pantziou & Christos Zaroliagis

Authors
  1. Lorena Bourg
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Thomas Chatzidimitris
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ioannis Chatzigiannakis
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Damianos Gavalas
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Kalliopi Giannakopoulou
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Vlasios Kasapakis
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Charalampos Konstantopoulos
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Damianos Kypriadis
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Grammati Pantziou
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Christos Zaroliagis
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Damianos Gavalas .

Editor information

Editors and Affiliations

  1. Sapienza University of Rome, Rome, Italy

    Ioannis Chatzigiannakis

  2. Philips Research, Eindhoven, The Netherlands

    Boris De Ruyter

  3. Hellenic Open University, Patras, Greece

    Irene Mavrommati

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Bourg, L. et al. (2019). Enhanced Buying Experiences in Smart Cities: The SMARTBUY Approach. In: Chatzigiannakis, I., De Ruyter, B., Mavrommati, I. (eds) Ambient Intelligence. AmI 2019. Lecture Notes in Computer Science(), vol 11912. Springer, Cham. https://doi.org/10.1007/978-3-030-34255-5_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-34255-5_8

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-34254-8

  • Online ISBN: 978-3-030-34255-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Societies and partnerships

Search

Navigation