Millennials’ perspective on multiple distribution channels

Inga Słowikowska

Abstract


Theoretical background: The idea of multichanneling gained popularity in the late 1990s mostly due to the development of the Internet. Distribution changed from using single to several channels and integrating them, which allowed consumers to access multiple channels at every stage of the buyer decision process. Using multiple channels is referred to as multi-, cross-, or omni-channelling, depending on the level of channel interaction and integration. Transforming distribution from multi-, to omni-channelling can require important and expensive changes in the organization. In Poland, most of the retailers do not meet the requirements of omnichanneling, which leaves the consumers mostly with the experience of multi-, and cross-channelling distribution.

Purpose of the article: The purpose of this article is to explore the consumer journey of Millennials in multichannel shopping by examining the usage of distribution channels by Generation Y and preferences about the delivery of products bought online. The factors that can encourage them to choose online channel and click-and-collect delivery more often are also investigated.

Research methods: To test the hypotheses, literature research and quantitative study was implemented using an online survey (CASI). The study involved a group of 266 respondents from Generation Y and was conducted in January 2019. Research results were also compared to the prior research found in the literature.

Main findings: Research results show that online channels are more popular for information seeking by Millennials but traditional stores are preferred by them for purchase decisions. There is also diversity in the channels used for purchasing researched group of products, which shows that integrating the channels in selected aspects may provide a more positive buying experience and create loyalty. Aspects differentiating multi- and cross-channels from omnichannels, such as lower prices and special offers in online stores, can increase the usage of online channels. The popularity of mobile devices is not well used in distribution channels – it is more popular to use a store’s website on a smartphone than a mobile application to purchase a product. Generation Y is also more likely to use the effect of ROPO (webrooming) than reversed-ROPO (showrooming). The aspects well known for omnichanneling can increase the popularity of click-and-collect among Millennials.


Keywords


multichanneling; multichannel behaviour; consumer behaviour; Generation Y, Millennials

Full Text:

PDF

References


Badrinarayanan, V., & Becerra, E. P., & Madhavaram, S. (2014). Purchase Intentions in Online Stores of Multichannel Retailers: Influence of Congruity in Store-Attribute Dimensions and Self-Image, Journal of Retailing and Consumer Services, 21(6). DOI: 10.1016/j.jretconser.2014.01.002.

Balasubramanian, S., Raghunathan, R., & Mahajan, V. (2005). Consumers in a Multichannel Environment: Product Utility, Process Utility, and Channel Choice, Journal of Interactive Marketing, 19(2). DOI: 10.1002/dir.20032.

Beck, N., & Ryg, L.D. (2015). Categorization of multiple channel retailing in Multi-, Cross-, and Omni‐Channel Retailing for retailers and retailing, Journal of Retailing and Consumer Services, 27. DOI: 10.1016/j.jretconser.2015.08.001.

Blom, A., Lange, F., & Hess R.L. (2017). Omnichannel-based promotions’ effects on purchase behavior and brand image, Journal of Retailing and Consumer Services, 39. doi: 10.1016/j.jretconser.2017.08.008.

Chiou, J.S., Chou, S.Y., & Shen, G.C.C. (2017). Consumer choice of multichannel shopping: The effects of relationship investment and online store preference, Internet Research, 27(1). DOI: 10.1108/IntR-08-2013-0173.

Czerpak, E. (2017). Omnichannel po polsku. Jak zatrzymać klientów sklepów stacjonarnych w dobie e-commerce, Knight Frank.

Dahmen, P. (2004). Multi-Channel Strategies for Retail Financial Services: A Management-Frimework for Designing and Implementing Multi-Channel Strategies, Deutscher Universitatverlag. DOI: 10.1007/978-3-322-81828-7.

Eriksson, N., Rosenbroijer, C. J., & Fagerstrom, A. (2017). The relationship between young consumers decision making styles and propensity to shop clothing online with a smartphon,. Procedia Computer Science, 121. DOI: 10.1016/j.procs.2017.11.069.

Gołąb-Andrzejak, E. (2016). Konsumenci pokolenia Y – nowe wyzwanie dla komunikacji marketingowej, Handel Wewnętrzny, 2(361).

Jaciow, M. (2016). Pokolenie Y na zakupach – wyzwania dla współczesnego marketingu, Handel Wewnętrzny, 2(361).

Kaczorowska-Spychalska, D. (2017). Consumer perspective of omnichannel commerce, Management, 21(2). DOI: 10.1515/manment-2017-0007.

Lembrych-Furtak, R. (2017). Marketing Challenges and Opportunities in Multi-Channel Distribution, Annales Universitatis Mariae Curie-Skłodowska, sectio H – Oeconomia, 51(2). DOI: 10.17951/h.2017.51.2.151.

Levy, M., Weitz, B. A., & Grewal, D. (2013). Retailing Management, 9th ed., McGraw-Hill/Irwin.

Lipowski, M. (2015). Konsument multikanałowy–przyczyny i implikacje zjawiska, Zeszyty Naukowe Uniwersytetu Szczecińskiego, 39(2).

Lipowski, M., & Bondos, I. (2016). Omnikanałowość - czy rynek zweryfikuje koncepcję teoretyczną?, Organizacja i Zarządzanie, 1(33).

Lipowski, M., (2017). The Differences between Generations in Consumer Behavior in the Service Sales Channel, Annales Universitatis Mariae Curie-Skłodowska, sectio H – Oeconomia, 51(2). DOI: 10.17951/h.2017.51.2.159.

Pozza, I.D., Heitz-Spahn, S. & Texier, L. (2017). Generation Y multichannel behaviour for complex services: the need for human contact embodied through a distance relationship, Journal of Strategic Marketing, 25(3). DOI: 10.1080/0965254X.2017.1299785.

Rodriguez‐Torrico, P. ,Cabezudo, R.S.J., & San‐Martin, S. (2017). Tell me what they are like and I will tell you where they buy. An analysis of omni channel consumer behavior, Computers in Human Behavior, 68. DOI: 10.1016/j.chb.2016.11.064.

Von Briel, F. (2018). The future of omnichannel retail: A four-stage Delphi study, Technological Forecasting & Social Change, 132. DOI: 10.1016/j.techfore.2018.02.004.




DOI: http://dx.doi.org/10.17951/h.2019.53.1.69-76
Date of publication: 2019-10-14 10:02:09
Date of submission: 2019-02-09 21:13:07


Statistics


Total abstract view - 1337
Downloads (from 2020-06-17) - PDF - 0

Indicators



Refbacks

  • There are currently no refbacks.


Copyright (c) 2019 Inga Słowikowska

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.