IDEAS home Printed from https://ideas.repec.org/a/eee/joreco/v51y2019icp304-310.html
   My bibliography  Save this article

Store buildings as tourist attractions: Mining retail meaning of store building pictures through a machine learning approach

Author

Listed:
  • Pantano, Eleonora
  • Dennis, Charles

Abstract

The aim of this paper is to understand the extent to which a store building can function as a tourism attraction, using a large luxury department store as case research. The study draws upon the idea that people complete a hermeneutic circle to create an extraordinary tourism experience to share with others. The data gathering is based on the collection of pictures posted online on Flickr and analysed using a machine learning approach. A sample of 1,557 pictures related to a specific area in London (UK) were collected and analysed by means of a cluster analysis in order to determine which objects are most photographed. Findings reveal that the store building of a luxury department store is the central object in the majority of pictures within a 1km radius of the store main entrance, which demonstrates the role of store building attractiveness in tourism experience. The theoretical contribution is that this is the first paper adding the exterior of the building as attribute of the department store, and demonstrating the role of department stores in place attractiveness.

Suggested Citation

  • Pantano, Eleonora & Dennis, Charles, 2019. "Store buildings as tourist attractions: Mining retail meaning of store building pictures through a machine learning approach," Journal of Retailing and Consumer Services, Elsevier, vol. 51(C), pages 304-310.
    • Handle: RePEc:eee:joreco:v:51:y:2019:i:c:p:304-310
    DOI: 10.1016/j.jretconser.2019.06.018
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0969698919300967
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jretconser.2019.06.018?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. Bradlow, Eric T. & Gangwar, Manish & Kopalle, Praveen & Voleti, Sudhir, 2017. "The Role of Big Data and Predictive Analytics in Retailing," Journal of Retailing, Elsevier, vol. 93(1), pages 79-95.
    2. Erevelles, Sunil & Fukawa, Nobuyuki & Swayne, Linda, 2016. "Big Data consumer analytics and the transformation of marketing," Journal of Business Research, Elsevier, vol. 69(2), pages 897-904.
    3. Pearce, Philip L. & Wang, Zhe, 2019. "Human ethology and tourists’ photographic poses," Annals of Tourism Research, Elsevier, vol. 74(C), pages 108-120.
    4. Rasouli, Soora & Timmermans, Harry, 2013. "Assessment of model uncertainty in destinations and travel forecasts of models of complex spatial shopping behaviour," Journal of Retailing and Consumer Services, Elsevier, vol. 20(2), pages 139-146.
    5. Yamamoto, Toshiyuki & Li, Cheng & Morikawa, Takayuki, 2014. "An empirical analysis of the factors raising the interest in new shopping destinations," Journal of Retailing and Consumer Services, Elsevier, vol. 21(6), pages 950-957.
    6. Xu, Zhenning & Frankwick, Gary L. & Ramirez, Edward, 2016. "Effects of big data analytics and traditional marketing analytics on new product success: A knowledge fusion perspective," Journal of Business Research, Elsevier, vol. 69(5), pages 1562-1566.
    7. Germann, Frank & Lilien, Gary L. & Rangaswamy, Arvind, 2013. "Performance implications of deploying marketing analytics," International Journal of Research in Marketing, Elsevier, vol. 30(2), pages 114-128.
    8. Balomenou, Nika & Garrod, Brian & Georgiadou, Andri, 2017. "Making sense of tourists' photographs using canonical variate analysis," Tourism Management, Elsevier, vol. 61(C), pages 173-179.
    9. Dolega, Les & Pavlis, Michalis & Singleton, Alex, 2016. "Estimating attractiveness, hierarchy and catchment area extents for a national set of retail centre agglomerations," Journal of Retailing and Consumer Services, Elsevier, vol. 28(C), pages 78-90.
    10. Bitty Balducci & Detelina Marinova, 2018. "Unstructured data in marketing," Journal of the Academy of Marketing Science, Springer, vol. 46(4), pages 557-590, July.
    11. Kim, Hany & Stepchenkova, Svetlana, 2015. "Effect of tourist photographs on attitudes towards destination: Manifest and latent content," Tourism Management, Elsevier, vol. 49(C), pages 29-41.
    12. Lo, Iris Sheungting & McKercher, Bob, 2015. "Ideal image in process: Online tourist photography and impression management," Annals of Tourism Research, Elsevier, vol. 52(C), pages 104-116.
    13. Kim, Samuel Seongseop & Timothy, Dallen J. & Hwang, Jinsoo, 2011. "Understanding Japanese tourists’ shopping preferences using the Decision Tree Analysis method," Tourism Management, Elsevier, vol. 32(3), pages 544-554.
    14. Shim, Changsup & Santos, Carla Almeida, 2014. "Tourism, place and placelessness in the phenomenological experience of shopping malls in Seoul," Tourism Management, Elsevier, vol. 45(C), pages 106-114.
    15. Choi, Miju & Law, Rob & Heo, Cindy Yoonjoung, 2016. "Shopping destinations and trust – Tourist attitudes: Scale development and validation," Tourism Management, Elsevier, vol. 54(C), pages 490-501.
    16. Blut, Markus & Teller, Christoph & Floh, Arne, 2018. "Testing Retail Marketing-Mix Effects on Patronage: A Meta-Analysis," Journal of Retailing, Elsevier, vol. 94(2), pages 113-135.
    17. Murphy, Laurie & Moscardo, Gianna & Benckendorff, Pierre & Pearce, Philip, 2011. "Evaluating tourist satisfaction with the retail experience in a typical tourist shopping village," Journal of Retailing and Consumer Services, Elsevier, vol. 18(4), pages 302-310.
    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. Chen, Chin-Tsu, 2024. "Atmospherics fosters customer loyalty: Exploring the mediating effects of memorable customer experience and customer satisfaction in factory outlet malls in Taiwan," Journal of Retailing and Consumer Services, Elsevier, vol. 80(C).
    2. AbedRabbo, Majd & Hart, Cathryn & Ellis-Chadwick, Fiona & AlMalak, Zeina, 2022. "Towards rebuilding the highstreet: Learning from customers’ town centre shopping journeys," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    3. Morimura, Fumikazu & Sakagawa, Yuji, 2023. "The intermediating role of big data analytics capability between responsive and proactive market orientations and firm performance in the retail industry," Journal of Retailing and Consumer Services, Elsevier, vol. 71(C).
    4. Thanh-Hieu Bui, 2021. "Discovering shopping visitors’ behavior and preferences using geo-tagged social photos: a case study of Los Angeles City," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(2), pages 127-143, June.
    5. Hagtvedt, Henrik & Chandukala, Sandeep R., 2023. "Immersive retailing: The in-store experience," Journal of Retailing, Elsevier, vol. 99(4), pages 505-517.
    6. Yan Liu & Linchuan Yang & Kwong Wing Chau, 2020. "Impacts of Tourism Demand on Retail Property Prices in a Shopping Destination," Sustainability, MDPI, vol. 12(4), pages 1-14, February.
    7. Zheng, Wei-Quan & Cheung, Sze-Man & Zhu, Bo-Wei & Xiong, Lei & Tzeng, Gwo-Hshiung, 2024. "A hybrid multi-attribute decision-making model for the systematic evaluation of exoticism-themed retail spaces from the perspective of consumer experience," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
    8. Lu, Jialiang & Zheng, Xu & Nervino, Esterina & Li, Yanzhi & Xu, Zhihua & Xu, Yabo, 2024. "Retail store location screening: A machine learning-based approach," Journal of Retailing and Consumer Services, Elsevier, vol. 77(C).

    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. Giglio, Simona & Pantano, Eleonora & Bilotta, Eleonora & Melewar, T.C., 2020. "Branding luxury hotels: Evidence from the analysis of consumers’ “big” visual data on TripAdvisor," Journal of Business Research, Elsevier, vol. 119(C), pages 495-501.
    2. Dawn Iacobucci & Maria Petrescu & Anjala Krishen & Michael Bendixen, 2019. "The state of marketing analytics in research and practice," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(3), pages 152-181, September.
    3. Purva Grover & Arpan Kumar Kar, 2017. "Big Data Analytics: A Review on Theoretical Contributions and Tools Used in Literature," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 18(3), pages 203-229, September.
    4. Jin, Haipeng & Moscardo, Gianna & Murphy, Laurie, 2017. "Making sense of tourist shopping research: A critical review," Tourism Management, Elsevier, vol. 62(C), pages 120-134.
    5. Blasco-Arcas, Lorena & Lee, Hsin-Hsuan Meg & Kastanakis, Minas N. & Alcañiz, Mariano & Reyes-Menendez, Ana, 2022. "The role of consumer data in marketing: A research agenda," Journal of Business Research, Elsevier, vol. 146(C), pages 436-452.
    6. Imran Bashir Dar & Muhammad Bashir Khan & Abdul Zahid Khan & Bahaudin G. Mujtaba, 2021. "A qualitative analysis of the marketing analytics literature: where would ethical issues and legality rank?," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(3), pages 242-261, September.
    7. “Jimmy” Xu, Zhenning & Ramirez, Edward & Liu, Pan & Frankwick, Gary L., 2024. "Evaluating underlying factor structures using novel machine learning algorithms: An empirical and simulation study," Journal of Business Research, Elsevier, vol. 173(C).
    8. Irina Maiorescu & Mihaela Bucur & Bogdan Georgescu & Daniel Moise & Vasile Alecsandru Strat & Ion Daniel Zgură, 2020. "Social Media and IOT Wearables in Developing Marketing Strategies. Do SMEs Differ From Large Enterprises?," Sustainability, MDPI, vol. 12(18), pages 1-18, September.
    9. Brewis, Claire & Dibb, Sally & Meadows, Maureen, 2023. "Leveraging big data for strategic marketing: A dynamic capabilities model for incumbent firms," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    10. O'Driscoll, Conor & Crowley, Frank & Doran, Justin & McCarthy, Nóirín, 2022. "Retail sprawl and CO2 emissions: Retail centres in Irish cities," Journal of Transport Geography, Elsevier, vol. 102(C).
    11. Miikka Blomster & Timo Koivumäki, 2022. "Exploring the resources, competencies, and capabilities needed for successful machine learning projects in digital marketing," Information Systems and e-Business Management, Springer, vol. 20(1), pages 123-169, March.
    12. Côrte-Real, Nadine & Oliveira, Tiago & Ruivo, Pedro, 2017. "Assessing business value of Big Data Analytics in European firms," Journal of Business Research, Elsevier, vol. 70(C), pages 379-390.
    13. Morimura, Fumikazu & Sakagawa, Yuji, 2023. "The intermediating role of big data analytics capability between responsive and proactive market orientations and firm performance in the retail industry," Journal of Retailing and Consumer Services, Elsevier, vol. 71(C).
    14. Vinicius Luiz Ferraz Minatogawa & Matheus Munhoz Vieira Franco & Izabela Simon Rampasso & Rosley Anholon & Ruy Quadros & Orlando Durán & Antonio Batocchio, 2019. "Operationalizing Business Model Innovation through Big Data Analytics for Sustainable Organizations," Sustainability, MDPI, vol. 12(1), pages 1-29, December.
    15. Patrick Mikalef & Ilias O. Pappas & John Krogstie & Michail Giannakos, 2018. "Big data analytics capabilities: a systematic literature review and research agenda," Information Systems and e-Business Management, Springer, vol. 16(3), pages 547-578, August.
    16. Nguyen Anh Khoa Dam & Thang Le Dinh & William Menvielle, 2019. "A systematic literature review of big data adoption in internationalization," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(3), pages 182-195, September.
    17. Mariani, Marcello M. & Borghi, Matteo & Laker, Benjamin, 2023. "Do submission devices influence online review ratings differently across different types of platforms? A big data analysis," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    18. Aljumah, Ahmad Ibrahim & Nuseir, Mohammed T. & Alam, Md. Mahmudul, 2021. "Traditional Marketing Analytics, Big Data Analytics, Big Data System Quality and the Success of New Product Development," OSF Preprints 9auec, Center for Open Science.
    19. Elisabetta Raguseo & Claudio Vitari, 2017. "Investments in big data analytics and firm performance: an empirical investigation of direct and mediating effects," Grenoble Ecole de Management (Post-Print) halshs-01923259, HAL.
    20. Pantano, Eleonora & Dennis, Charles & De Pietro, Michela, 2021. "Shopping centers revisited: The interplay between consumers’ spontaneous online communications and retail planning," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).

    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:eee:joreco:v:51:y:2019:i:c:p:304-310. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/journal-of-retailing-and-consumer-services .

    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.