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Acceptance and use of big data techniques in services companies

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  • Cabrera-Sánchez, Juan-Pedro
  • Villarejo-Ramos, Ã ngel F.

Abstract

Companies able to take advantage of the information coming from the use of Big Data will have a competitive advantage by being able to make decisions based on greater knowledge of customers and competition. Besides, the access to the software for the treatment of this great amount of data is free. So, the objective of this paper is to study the level of acceptance and use of these technologies, Big Data techniques, by services companies. To analyse the intention and use it extends the acceptance technologies model- Unified Theory of Acceptance and Use of Technology (UTAUT) - to the context of Big Data techniques, incorporating the effect on it of three new variables: resistance to use, perceived risk and opportunity cost. The structural model was evaluated using partial least squares structural equation modelling (PLS-SEM) with an adequate global fit. The verification is carried out with a sample of 199 Spanish services companies, and its main results are the strong effect of the facilitating conditions on the intention and use of Big Data, as well as the direct effect of the opportunity cost and the resistance to use on the intention, and the indirect inhibiting effect of the perceived risk through the resistance to use on intention behaviour.

Suggested Citation

  • Cabrera-Sánchez, Juan-Pedro & Villarejo-Ramos, à ngel F., 2020. "Acceptance and use of big data techniques in services companies," Journal of Retailing and Consumer Services, Elsevier, vol. 52(C).
    • Handle: RePEc:eee:joreco:v:52:y:2020:i:c:s0969698919302589
    DOI: 10.1016/j.jretconser.2019.101888
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    4. Perdana, Arif & Lee, Hwee Hoon & Arisandi, Desi & Koh, SzeKee, 2022. "Accelerating data analytics adoption in small and mid-size enterprises: A Singapore context," Technology in Society, Elsevier, vol. 69(C).
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    7. Abdalwali Lutfi & Akif Lutfi Al-Khasawneh & Mohammed Amin Almaiah & Ahmad Farhan Alshira’h & Malek Hamed Alshirah & Adi Alsyouf & Mahmaod Alrawad & Ahmad Al-Khasawneh & Mohamed Saad & Rommel Al Ali, 2022. "Antecedents of Big Data Analytic Adoption and Impacts on Performance: Contingent Effect," Sustainability, MDPI, vol. 14(23), pages 1-23, November.
    8. Rayburn, Steven W. & Anderson, Sidney T. & Zank, Gail M. & McDonald, Imani, 2022. "M-atmospherics: From the physical to the digital," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    9. Luis-Edwin Chimborazo-Azogue & Marta Frasquet & Alejandro Molla-Descals & Maria-Jose Miquel-Romero, 2021. "Understanding Mobile Showrooming Based on a Technology Acceptance and Use Model," Sustainability, MDPI, vol. 13(13), pages 1-17, June.
    10. Swaraj S. Bharti & Kanika Prasad & Shwati Sudha & Vineeta Kumari, 2023. "Customer acceptability towards AI-enabled digital banking: a PLS-SEM approach," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 28(4), pages 779-793, December.
    11. Youssef, Mayada Abd El-Aziz & Eid, Riyad & Agag, Gomaa, 2022. "Cross-national differences in big data analytics adoption in the retail industry," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
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    13. Huang, Yung-Chuan, 2023. "Integrated concepts of the UTAUT and TPB in virtual reality behavioral intention," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).

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