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E-Commerce Flexibility Measurement Model Based on Empirical Research of Polish Enterprises

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  • Barbara Buraczyńska
  • Dariusz Majerek

Abstract

Purpose: The main purpose of this article is to create e-commerce flexibility measurement model. The additional goal is to verify whether four proposed factors differentiate e-commerce flexibility. The examined factors are the company size, the number of employees, the number of years in e-commerce, and the geographic coverage of sales. Design/Methodology/Approach: In order to achieve this goal, an online survey was conducted. The questionnaire was based on literature studies. It was filled in by over 200 owners or managers of e-commerce enterprises. The collected data was analysed statistically using exploratory factor analysis, Cronbach's method, Pillai's statistic of MANOVA omnibus test. Findings: The e-commerce flexibility measurement model has been created. The statistical analysis revealed groups of the implicit factors of the flexibility of e-commerce enterprises. The results confirmed the dependence between the factors differentiating flexibility and the groups of flexibility of an e-commerce company. Practical Implications: The research showed that flexibility, which is a desirable feature of these companies, can mature along with their sustainable development. Originality/Value: The underlying structure of e-commerce flexibility was created. The discovery of the implicit factors of the flexibility of e-commerce enterprises is the starting point for further research on online stores.

Suggested Citation

  • Barbara Buraczyńska & Dariusz Majerek, 2021. "E-Commerce Flexibility Measurement Model Based on Empirical Research of Polish Enterprises," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 2), pages 112-126.
  • Handle: RePEc:ers:journl:v:xxiv:y:2021:i:special2:p:112-126
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    References listed on IDEAS

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    1. Purwanto & Kuswandi, 2017. "Effects of Flexibility and Interactivity on the Perceived Value of and Satisfaction with E-Commerce (Evidence from Indonesia)," Tržište/Market, Faculty of Economics and Business, University of Zagreb, vol. 29(2), pages 139-159.
    2. Wagner, Stephan M. & Grosse-Ruyken, Pan Theo & Erhun, Feryal, 2018. "Determinants of sourcing flexibility and its impact on performance," International Journal of Production Economics, Elsevier, vol. 205(C), pages 329-341.
    3. Dreyer, Bent & Gronhaug, Kjell, 2004. "Uncertainty, flexibility, and sustained competitive advantage," Journal of Business Research, Elsevier, vol. 57(5), pages 484-494, May.
    4. Lee Cronbach, 1951. "Coefficient alpha and the internal structure of tests," Psychometrika, Springer;The Psychometric Society, vol. 16(3), pages 297-334, September.
    5. Yan Jin & Ngozi Oriaku, 2013. "E-service flexibility: meeting new customer demands online," Management Research Review, Emerald Group Publishing Limited, vol. 36(11), pages 1123-1136, October.
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    Cited by:

    1. Jiang, Yi & Lai, Po-Lin & Yang, Ching-Chiao & Wang, Xinchen, 2023. "Exploring the factors that drive consumers to use contactless delivery services in the context of the continued COVID-19 pandemic," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).

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    More about this item

    Keywords

    Determinants of flexibility; e-commerce; e-commerce enterprise; e-commerce flexibility; e-shop; factor analysis; flexibility; flexibility measurement model; online sales; types of flexibility.;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • F14 - International Economics - - Trade - - - Empirical Studies of Trade

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