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Modelling consumers’ acceptance for the click and collect service

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  • Milioti, Christina
  • Pramatari, Katerina
  • Kelepouri, Ioanna

Abstract

This study investigates possibilities for developing a click and collect service in the context of e-commerce and attempts to identify the consumer characteristics that determine the acceptance of this service. Data of 285 e-commerce consumers were collected through an online questionnaire using banners uploaded in seven online retailers' sites. Binary logit models are developed to analyze the data and relate consumer characteristics to their intention to use and pay for the click and collect service. Perceived environmental contribution of the click and collect service, perceived time pressure, car use in the city center and frequency of online shopping significantly affect consumers’ intention to use the service. The model results provide information that can be used to choose location points and design marketing and pricing policies that will make the click and collect service attractive to customers.

Suggested Citation

  • Milioti, Christina & Pramatari, Katerina & Kelepouri, Ioanna, 2020. "Modelling consumers’ acceptance for the click and collect service," Journal of Retailing and Consumer Services, Elsevier, vol. 56(C).
    • Handle: RePEc:eee:joreco:v:56:y:2020:i:c:s0969698919304539
    DOI: 10.1016/j.jretconser.2020.102149
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    References listed on IDEAS

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    Cited by:

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    2. Iacocca, Kathleen & Mahar, Stephen & Daniel Wright, P., 2022. "Strategic horizontal integration for drug cost reduction in the pharmaceutical supply chain," Omega, Elsevier, vol. 108(C).
    3. Hallikainen, Heli & Luongo, Milena & Dhir, Amandeep & Laukkanen, Tommi, 2022. "Consequences of personalized product recommendations and price promotions in online grocery shopping," Journal of Retailing and Consumer Services, Elsevier, vol. 69(C).
    4. Li, Xinwei & Xu, Mao & Zeng, Wenjuan & Tse, Ying Kei & Chan, Hing Kai, 2023. "Exploring customer concerns on service quality under the COVID-19 crisis: A social media analytics study from the retail industry," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).
    5. Kim, Woojung & Wang, Xiaokun Cara, 2022. "The adoption of alternative delivery locations in New York City: Who and how far?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 158(C), pages 127-140.

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