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E-Commerce Purchasing Behaviour and the Level of Consumers‘ Income in Poland and Great Britain

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  • Katarzyna Szalonka
  • Agnieszka Sadowa
  • Aleksandra Wicka
  • Ludwik Wicki

Abstract

Purpose: The aim of the paper is to identify the purchasing behaviour of buyers from Poland and Great Britain under the influence of online advertising depending on the amount of income. The paper shows how customers with different income levels react to advertising in Poland and the UK. An attempt has been made to compare the British e consumer with the Polish one – their online behaviour influenced by online advertising. Design/Methodology/Approach: To achieve the aim of the study, international research was carried out from November 2017 to February 2018 in Poland and Great Britain using an online questionnaire. After assessing the completeness of the respon¬ses, 487 responses from Poland and 173 from Great Britain were finally qualified for further analysis. It is an international comparative study conducted on a large group of respondents on a very important and topical topic. Findings: It was found that there are differences in the way Poles and British people use the Internet, but the majority of respondents in each country watched the appearing advertisements. Over 60% of respondents from Great Britain and about 50% from Poland found the advertisements interesting. In addition, in Poland, lower-income respondents were more likely to be interested in viewing advertisements and found them interesting more often. Among UK respondents, this was not income related. Practical Implications: The outcomes have given detailed and valuable information on the impact of online advertising on the purchasing decisions of Polish and UK households with different income levels. Originality/value: International comparative research conducted on a large group of respondents, on a very important and topical subject.

Suggested Citation

  • Katarzyna Szalonka & Agnieszka Sadowa & Aleksandra Wicka & Ludwik Wicki, 2020. "E-Commerce Purchasing Behaviour and the Level of Consumers‘ Income in Poland and Great Britain," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 2), pages 552-568.
  • Handle: RePEc:ers:journl:v:xxiii:y:2020:i:special2:p:552-568
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    References listed on IDEAS

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    1. Van den Poel, Dirk & Buckinx, Wouter, 2005. "Predicting online-purchasing behaviour," European Journal of Operational Research, Elsevier, vol. 166(2), pages 557-575, October.
    2. Maira Turysbekovna Davletova & Nazym Satbekovna Dulatbekova & Galim Gabdulsanovich Sadykov, 2017. "Current State and Prospects for Development of Internet Advertising in Kazakhstan," European Research Studies Journal, European Research Studies Journal, vol. 0(2A), pages 380-407.
    3. Pokul V.O. & Voronina L.A. & Malkova E.M., 2018. "Content Generation in Social Media Based on Consumer Behavior," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 2), pages 923-935.
    4. Agus Salim, 2018. "Factors Affecting the Consumers\' Willingness to Claim Product Replacement," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 348-361.
    5. Agus Salim, 2018. "Factors Affecting the Consumers\' Willingness to Claim Product Replacement," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 348-361.
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    Cited by:

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    More about this item

    Keywords

    Consumer behaviour; e-commerce; internet advertising.;
    All these keywords.

    JEL classification:

    • D19 - Microeconomics - - Household Behavior - - - Other
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L68 - Industrial Organization - - Industry Studies: Manufacturing - - - Appliances; Furniture; Other Consumer Durables
    • M37 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Advertising

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