Skip to main content
SpringerLink
Log in

Towards Analyzing High Street Customer Trajectories - A Data-Driven Case Study

  • Conference paper
  • First Online:
Book cover Business Information Systems Workshops (BIS 2019)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 373))

Included in the following conference series:

Abstract

Nowadays, many high streets face the problem of declining attractiveness. City management and high street retailers hardly know their customers. Therefore, they can scarcely react to the customers’ needs and wishes to make the customer experience more attractive. We aim at studying how customers behave in high streets using a data-driven approach by recording and evaluating customer trajectories with modern positioning technology. For doing so, we carry out a pilot test in order to check whether our approach is suitable for recognizing customer behavioral patterns. The result obtained by a cluster analysis reveals five clusters in the analyzed customer trajectories.

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 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 99.99
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

References

  1. Adair, J.G.: The Hawthorne effect: a reconsideration of the methodological artifact. J. Appl. Psychol. 69(2), 334 (1984)

    Article  Google Scholar 

  2. Arnold, M.J., Reynolds, K.E.: Hedonic shopping motivations. J. Retail. 79(2), 77–95 (2003)

    Article  Google Scholar 

  3. Babin, B.J., Darden, W.R., Griffin, M.: Work and/or fun: measuring hedonic and utilitarian shopping value. J. Consum. Res. 20(4), 644–656 (1994)

    Article  Google Scholar 

  4. Bartelheimer, C., Betzing, J.H., Berendes, I., Beverungen, D.: Designing multi-sided community platforms for local high street retail. In: 26th European Conference on Information Systems, ECIS 2018, Portsmouth, UK (2018)

    Google Scholar 

  5. Benbasat, I., Goldstein, D.K., Mead, M.: The case research strategy in studies of information systems. MIS Q. 11(3), 369–386 (1987)

    Article  Google Scholar 

  6. Berendes, C.I., Bartelheimer, C., Betzing, J.H., Beverungen, D.: Data-driven customer journey mapping in local high streets: a domain-specific modeling language. In: 39th International Conference on Information Systems, ICIS 2018, San Francisco, CA, USA (2018)

    Google Scholar 

  7. Betzing, J.H.: Beacon-based customer tracking across the high street: perspectives for location-based smart services in retail. In: 24th American Conference on Information Systems, AMCIS: New Orleans, p. 2018, LA (2018)

    Google Scholar 

  8. Betzing, J.H., Bartelheimer, C., Niemann, M., Berendes, C.I., Beverungen, D.: Quantifying the impact of geospatial recommendations: a field experiment in high street retail. In: 27th European Conference on Information Systems, ECIS 2019, Stockholm, SE (2019)

    Google Scholar 

  9. Bhattacherjee, A.: Social science research: principles, methods, and practices. Global Text Project (2012)

    Google Scholar 

  10. Bloch, P.H., Ridgway, N.M., Dawson, S.A.: The shopping mall as consumer habitat. J. Retail. 70(1), 23–42 (1994)

    Article  Google Scholar 

  11. Bollweg, L., Lackes, R., Siepermann, M., Weber, P.: Carrot-or-stick: how to trigger the digitalization of local owner operated retail outlets? In: 51st Hawaii International Conference on System Sciences, HICSS 2018, pp. 3811–3820, Big Island (2018)

    Google Scholar 

  12. Borgers, A., Timmermans, H.: A model of pedestrian route choice and demand for retail facilities within inner-city shopping areas. Geogr. Anal. 18(2), 115–128 (1986)

    Article  Google Scholar 

  13. Bromley, R.D.F., Thomas, C.T.: Small town shopping decline: dependence and inconvenience for the disadvanged. Int. Rev. Retail Distrib. Consum. Res. 5(4), 433–456 (1995)

    Google Scholar 

  14. Cay, E., Mert, Y., Bahcetepe, A., Akyazi, B.K., Ogrenci, A.S.: Beacons for indoor positioning. In: 2017 International Conference on Engineering and Technology (ICET), pp. 1–5 (August 2017)

    Google Scholar 

  15. Eichholz-Klein, S., Preißner, M., Lerch, C., Brylla, T.: Stadt, land, handel 2020. Technical report, IFH Institut für Handelsforschung Köln, Cologne, Germany (2015)

    Google Scholar 

  16. Gable, G.G.: Integrating case study and survey research methods: an example in information systems. Eur. J. Inf. Syst. 3(2), 112–126 (1994)

    Article  Google Scholar 

  17. Ghose, A., Li, B., Liu, S.: Mobile targeting using customer trajectory patterns. Manag. Sci. forthcoming, 1–51 (2018)

    Google Scholar 

  18. Grönroos, C., Voima, P.: Critical service logic: making sense of value creation and co-creation. J. Acad. Mark. Sci. 41(2), 133–150 (2013)

    Article  Google Scholar 

  19. Hirschman, E.C., Holbrook, M.B.: Hedonic consumption: emerging concepts, methods and propositions. J. Mark. 46(3), 92–101 (1982)

    Article  Google Scholar 

  20. Homburg, C., Jozić, D., Kuehnl, C.: Customer experience management: toward implementing an evolving marketing concept. J. Acad. Mark. Sci. 45(3), 377–401 (2015)

    Article  Google Scholar 

  21. Köln, I.F.H.: Vitale innenstädte 2016. Technical report, IFH Institut für Handelsforschung Köln, Cologne, Germany (2017)

    Google Scholar 

  22. Jarboe, G.R., McDaniel, C.D.: A profile of browsers in regional shopping malls. J. Acad. Mark. Sci. 15(1), 46–53 (1987)

    Article  Google Scholar 

  23. Jones, M.A., Reynolds, K.E., Arnold, M.J.: Hedonic and utilitarian shopping value: investigating differential effects on retail outcomes. J. Bus. Res. 59(9), 974–981 (2006)

    Article  Google Scholar 

  24. Kim, Y.-K.: Consumer value: an application to mall and internet shopping. Int. J. Retail Distrib. Manag. 30(12), 595–602 (2002)

    Article  Google Scholar 

  25. Kumar, V., Anand, A., Song, H.: Future of retailer profitability: an organizing framework. J. Retail. 93(1), 96–119 (2017)

    Article  Google Scholar 

  26. Lemon, K.N., Verhoef, P.C.: Understanding customer experience and the customer journey. J. Mark. 80(6), 69–96 (2016)

    Article  Google Scholar 

  27. Milligan, G.W., Sokol, L.M.: A two-stage clustering algorithm with robust recovery characteristics. Educ. Psychol. Meas. 40(3), 755–759 (1980)

    Article  Google Scholar 

  28. Miyazaki, A.D., Fernandez, A.: Consumer perceptions of privacy and security risks for online shopping. J. Consum. Aff. 35(1), 27–44 (2001)

    Article  Google Scholar 

  29. Park, Y.-J., Chang, K.-N.: Individual and group behavior-based customer profile model for personalized product recommendation. Expert Syst. Appl. 36(2), 1932–1939 (2009)

    Article  Google Scholar 

  30. Ricci, F., Rokach, L., Shapira, B.: Recommender systems: introduction and challenges. In: Ricci, F., Rokach, L., Shapira, B. (eds.) Recommender Systems Handbook, pp. 1–34. Springer, Boston, MA (2015). https://doi.org/10.1007/978-1-4899-7637-6_1

    Chapter  MATH  Google Scholar 

  31. Rintamäki, T., Kanto, A., Kuusela, H., Spence, M.T.: Decomposing the value of department store shopping into utilitarian, hedonic and social dimensions: evidence from Finland. Int. J. Retail Distrib. Manag. 34(1), 6–24 (2006)

    Article  Google Scholar 

  32. Rintamäki, T., Kuusela, H., Mitronen, L.: Identifying competitive customer value propositions in retailing. Managing Serv. Qual. Int. J. 17(6), 621–634 (2007)

    Article  Google Scholar 

  33. Ruiz, J.-P., Chebat, J.-C., Hansen, P.: Another trip to the mall: a segmentation study of customers based on their activities. J. Retail. Consum. Serv. 11(6), 333–350 (2004)

    Article  Google Scholar 

  34. Saarloos, D., Joh, C.-H., Zhang, J., Fujiwara, A.: A segmentation study of pedestrian weekend activity patterns in a central business district. J. Retail. Consum. Serv. 17(2), 119–129 (2010)

    Article  Google Scholar 

  35. Seeger, G., Bick, M.: Mega and consumer trends - towards car-independent mobile applications. In: International Conference on Mobile Business (2013)

    Google Scholar 

  36. Stadt Paderborn - Stadtplanungsamt. Innenstadtverkehrskonzept endbericht, June 2013

    Google Scholar 

  37. Stephen Statler. Beacon Technologies: The Hitchhiker’s Guide to the Beacosystem. Apress (2016)

    Google Scholar 

  38. Tauber, E.M.: Why do people shop? J. Mark. 36(4), 46–49 (1972)

    Google Scholar 

  39. Teller, C.: Shopping streets versus shopping malls - determinants of agglomeration format attractiveness from the consumers’ point of view. Int. Rev. Retail Distrib. Consum. Res. 18(4), 381–403 (2008)

    Google Scholar 

  40. Teller, C., Reutterer, T., Schnedlitz, P.: Hedonic and utilitarian shopper types in evolved and created retail agglomerations. Int. Rev. Retail Distrib. Consum. Res. 18(3), 283–309 (2008)

    Google Scholar 

  41. Verhoef, P.C., Lemon, K.N., Parasuraman, A., Roggeveen, A., Tsiros, M., Schlesinger, L.A.: Customer experience creation: determinants, dynamics and management strategies. J. Retail. 85(1), 31–41 (2009)

    Article  Google Scholar 

  42. Voorhees, C.M., et al.: Service encounters, experiences and the customer journey: defining the field and a call to expand our lens. J. Bus. Res. 79, 269–280 (2017)

    Article  Google Scholar 

  43. Xiao, B., Benbasat, I.: E-commerce product recommendation agents: use, characteristics, and impact. MIS Q. 31(1), 137–209 (2007)

    Article  Google Scholar 

  44. Yin, R.K.: Case study research design and methods third edition. Appl. Soc. Res. Methods Ser. 5 (2003)

    Google Scholar 

  45. Yoshimura, T., Hasegawa, H.: Comparing the precision and accuracy of GPS positioning in forested areas. J. Forest Res. 8(3), 147–152 (2003)

    Article  Google Scholar 

  46. Yoshimura, Y., Amini, A., Sobolevsky, S., Blat, J., Ratti, C.: Analysis of pedestrian behaviors through non-invasive Bluetooth monitoring. Appl. Geogr. 81, 43–51 (2017)

    Article  Google Scholar 

  47. Zomerdijk, L.G., Voss, C.A.: Service design for experience-centric services. J. Serv. Res. 13(1), 67–82 (2010)

    Article  Google Scholar 

Download references

Acknowledgements

This paper was developed in the research project smartmarket\(^{2}\), which is funded by the German Federal Ministry of Education and Research (BMBF), promotion sign 02K15A073. The authors thank the Project Management Agency Karlsruhe (PTKA).

Author information

Authors and Affiliations

  1. Paderborn University, 33098, Paderborn, Germany

    C. Ingo Berendes

Authors
  1. C. Ingo Berendes
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to C. Ingo Berendes .

Editor information

Editors and Affiliations

  1. Poznań University of Economics and Business, Poznan, Poland

    Witold Abramowicz

  2. University of Seville, Seville, Spain

    Rafael Corchuelo

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

Berendes, C.I. (2019). Towards Analyzing High Street Customer Trajectories - A Data-Driven Case Study. In: Abramowicz, W., Corchuelo, R. (eds) Business Information Systems Workshops. BIS 2019. Lecture Notes in Business Information Processing, vol 373. Springer, Cham. https://doi.org/10.1007/978-3-030-36691-9_27

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-36691-9_27

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-36690-2

  • Online ISBN: 978-3-030-36691-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation