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Unsupervised Modelling of E-Customers’ Profiles: Multiple Correspondence Analysis with Hierarchical Clustering of Principal Components and Machine Learning Classifiers
16 references·0 citing·51 second hop
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References

  • 2000AGE DIFFERENCES IN TECHNOLOGY ADOPTION DECISIONS: IMPLICATIONS FOR A CHANGING WORK FORCE1,721 cited
  • 2015The fickle P value generates irreproducible results766 cited
  • 2018The Influence of Online Shopping Determinants on Customer Satisfaction in the Serbian Market306 cited
  • 2015Influences of gender and product type on online purchasing204 cited
  • 2009Shopping orientation and online clothing purchases: the role of gender and purchase situation193 cited
  • 2011Role of demographics, social connectedness and prior internet experience in adoption of online shopping: Applications for direct marketing106 cited
  • 2022Implementing E-Commerce from Logistic Perspective: Literature Review and Methodological Framework92 cited
  • 2020Generation Z and Key-Factors on E-Commerce: A Study on the Portuguese Tourism Sector82 cited
  • 2019E-Commerce Participation and Household Income Growth in Taobao Villages73 cited
  • 2023Online consumer shopping behaviour: A review and research agenda67 cited
  • 2023Consumers’ Experience and Satisfaction Using Augmented Reality Apps in E-Shopping: New Empirical Evidence66 cited
  • 2022Online shopping cart abandonment: A review and research agenda63 cited
  • 2024Enhancing Continuous Usage Intention in E-Commerce Marketplace Platforms: The Effects of Service Quality, Customer Satisfaction, and Trust55 cited
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Consumer Decision-Making of Older People: A 45-Year Review
43 cited
  • 2015Dynamic joint construction and optimal operation strategy of multi-period reverse logistics network: a case study of Shanghai apparel E-commerce enterprises38 cited
  • 2024The Main Drivers of E-Commerce Adoption: A Global Panel Data Analysis37 cited
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