Factors That Determine Online Purchase Behavior: A Cross-Generational Approach. The Influence of COVID-19

  1. Coloma Álvarez Santamaría 1
  2. Arkaitz Bañuelos Campo 1
  1. 1 Universidad de La Rioja
    info

    Universidad de La Rioja

    Logroño, España

    ROR https://ror.org/0553yr311

Actas:
35th EBES Conference (Abstract book)

Editorial: EBES

ISBN: 978-605-80042-5-2

Año de publicación: 2021

Páginas: 28-29

Congreso: 35th EBES Conference. Rome, Italy, April 7-9, 2021

Tipo: Aportación congreso

Repositorio institucional: lock_openAcceso abierto Editor

Resumen

The expansion of e-commerce has been strengthened by Covid-19 sanitary crisis. Thus, in the current context influenced by the uncertainty resulting from the pandemic, companies in many sectors are facing difficult times; consumers, on the other hand, have become more aware of safety issues and are taking the highest safety precautions to protect themselves (Ota et al., 2020). Social distancing, as well as mandatory quarantine, has led to changes in everyday life in society (Nielsen, 2020). All of this, has drastically changed the way consumers have been shopping during this period, with one of the most observed reactions being the choice of the internet as a shopping channel (Sheth, 2020). The pandemic seems to have accelerated this process, but once the health crisis is over, will consumers continue to opt for online shopping? This paper identifies which factors affect online consumer behavior and analyses the effect of the pandemic on e-commerce adoption. In addition, we examine whether there are generational differences between online consumers. This study is justified by the need for marketers to analyze these traits, not only to attract consumers, but also to build consumer loyalty. In order to answer our research questions, we will carry out a principal component analysis with Varimax rotation to measure the unidimensionality or multidimensionality of the measurement scales used. Next, we will carry out a regression analysis to test the extent to which each of the previously obtained factors influences online consumer behavior. Finally, we will carry out a discriminant analysis to identify whether these dimensions differ between the generations considered. We will use SPSS v.23 to perform the analyses. Our results show that the factors influencing online consumer behavior are related to the product, to the consumer, to the Internet as a sales channel and to the website. We conclude that the current pandemic has led to a significant increase in online shopping that is likely to continue when the crisis is over. In addition, we conclude that there are differences between Millennials and Baby Boomers, with the former being more likely to purchase online mainly due to their greater comfort with new payment methods (PWC, 2015). Finally, a very similar effect of the pandemic is observed in both age groups. Lastly, future research could explore whether there are differences in the factors that influence online consumer behavior for different product categories.