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Purchase Decision Support with Internet of Things-Based Systems

  • Monika KuliszEmail author
  • Jerzy Lipski
  • Agnieszka Bojanowska
Conference paper
Part of the Springer Proceedings in Business and Economics book series (SPBE)

Abstract

While current studies in the field of Internet of Things (IoT) tend to focus on the technical aspects, such as programming, hardware and software, publications on the behavioural aspects of IoT remain few. Therefore, the primary objective of this chapter is to contribute to the discussion by providing a conceptual framework for an IoT-based system supporting customer purchase decisions. The system operates on several levels. The major level of operation is customer behaviour and purchase decision support. The second level concerns generating information regarding the shelf content status and reporting on the dynamics of stock-level changes, in order to shape an appropriate marketing strategy and develop effective stocking management processes. The third foundation of the system encompasses the technology and the essential elements ensuring efficient operation of the system. The capabilities of IoT are constantly progressing and expanding, thus leading to the development of software and hardware tools compatible with particular phases of service and customer support process. The presented study employs two research methods: self-observation and the literature study. The proposed solution requires that the system is equipped with necessary software and sensors connected in a wireless data transmission network of Internet of Things.

Keywords

Internet of Things Consumer Purchase decision support 

References

  1. 1.
    Amazon.com: Amazon Dash Button. https://www.amazon.com/b/%3fnode%3d10667898011%26sort%3ddate-desc-rank%26lo%3ddigital-text (2019). Accessed 3 Jan 2019
  2. 2.
    Bojanowska, A.: Customer data collection with Internet of Things. MATEC Web Conf. 252, 03002 (2019).  https://doi.org/10.1051/matecconf/201925203002CrossRefGoogle Scholar
  3. 3.
    Chan, C.O., Lau, H.C.W., Fan, Y.: IoT data acquisition in fashion retail application: fuzzy logic approach. In: 2018 International Conference on Artificial Intelligence and Big Data (ICAIBD), Chengdu, pp. 52–56 (2018)Google Scholar
  4. 4.
    Charucka, O.: Kluczowe czynniki konkurencyjności MSP i ich wpływ na rozwój gospodarki. Zesz. Nauk. Uczel. Vistula 35, 45–67 (2014)Google Scholar
  5. 5.
    Gaur, L., Singh, G., Ramakrishnan, R.: Understanding consumer preferences using IoT smartmirrors. Pertanika J. Sci. Technol. 25(3), 939–948 (2017)Google Scholar
  6. 6.
    Gross, J.J.: Emotion regulation: affective, cognitive, and social consequences. Psychology 39, 281–291 (2002)Google Scholar
  7. 7.
    Gubbi, J., Buyya, R., Marusic, S., Palaniswami, M.: Internet of Things (IoT): a vision, architectural elements, and future. Future Gener. Comput. Syst. 29(7), 1645–1660 (2013)CrossRefGoogle Scholar
  8. 8.
    Kaur, J., Kaur, P.D.: CE-GMS: a cloud IoT-enabled grocery management system. Electron. Commer. Res. Appl. 28, 63–72 (2018)CrossRefGoogle Scholar
  9. 9.
    Kokoszka, P.: 11 trends in ambient commerce that will change retail over next two years. https://www.retail-insight-network.com/features/trends-in-ambient-commerce/ (2018a). Accessed 7 Jan 2019
  10. 10.
    Kokoszka, P.: Ambient commerce set to boost retail spending on IoT tech to $5.3bn, report. https://www.retail-insight-network.com/news/ambient-commerce-boost-retail-spending/ (2018b). Accessed 7 Jan 2019
  11. 11.
    Liao, C., Hwang, A.: 7-Eleven opens unstaffed store in Taipei. https://www.digitimes.com/news/a20180726PD201.html?chid=9 (2018). Accessed 7 Jan 2019
  12. 12.
    Liu, L., Zhou, B., Zou, Z., Yeh, S., Zheng, L.: A smart unstaffed retail shop based on artificial intelligence and IoT. In: 2018 IEEE 23rd International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), Singapore, pp. 1–4 (2018)Google Scholar
  13. 13.
    Marszał, K.: Sterowanie ruchem klienta w obiektach handlowych. In: Grzegorczyk, A., Wiśniewska, A. (eds.) Merchandising, pp. 56–73. Wyższa Szkoła Promocji, Warszawa (2014)Google Scholar
  14. 14.
    Möhring, M., Keller, B., Schmidt, R., Pietzsch, L., Karich, L., Berhalter, C., Kilian, K.: Using smart edge devices to integrate consumers into digitized processes: the case of Amazon dash-button. In: Teniente, E., Weidlich, M. (eds.) Business Process Management Workshops. BPM 2017. Lecture Notes in Business Information Processing, vol. 308, pp. 374–383. Springer, Cham (2018)CrossRefGoogle Scholar
  15. 15.
    Sai Ganesh, S., Sahithi, B., Akhila, S., Venumadhav, T.: RFID based shopping cart. Int. J. Innov. Res. Eng. Manag. (IJIREM) 2(3), 24–30 (2015)Google Scholar
  16. 16.
    Sawant, R., Krishnan, K., Bhokre, S., Bhosale, P.: The RFID based smart shopping cart. Int. J. Eng. Res. Gen. Sci. 3(2), 275–280 (2015)Google Scholar
  17. 17.
    Tao, B.: Vivante Internet of Things (IoT) Solutions. https://bensontao.wordpress.com/2013/10/06/vivante-internet-of-things/ (2019). Accessed 3 Jan 2019
  18. 18.
    Witek, L.: Merchandising w małych i dużych firmach handlowych. C.H. Beck, Warszawa (2007)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Monika Kulisz
    • 1
    Email author
  • Jerzy Lipski
    • 1
  • Agnieszka Bojanowska
    • 1
  1. 1.Lublin University of TechnologyLublinPoland

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