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Traditional Marketing Analytics, Big Data Analytics, Big Data System Quality and the Success of New Product Development

Author

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  • Aljumah, Ahmad Ibrahim
  • Nuseir, Mohammed T.
  • Alam, Md. Mahmudul

    (Universiti Utara Malaysia)

Abstract

Objective/Purpose: This study investigates the impact of traditional marketing analytics and big data analytics on the success of a new product. Moreover, it assesses the mediating effects of the quality of big data system. Methodology/Design: This study is based on primary data that were collected through an online questionnaire survey from large manufacturing firms operating in UAE. Out of total distributed 421 samples, 327 samples were used for final data analysis. The survey was conducted from March-April 2020 and data analysis was done via Structural Equation Modelling (SEM-PLS). Findings: It emerges that big data analysis (BDA), traditional marketing analysis (TMA) and big data system quality (BDSQ) are significant determinants of new product development (NPD) success. Meanwhile, the BDA and TMA significantly affect the BDSQ. Results of the mediating role of BDSQ in the relationship between the BDA and NPD as well as TMA and NPD are significant. Implications: There are significant policy implications for practitioners and researchers concerning the role of analytics, particularly big data analytics and big data system quality, when attempting to achieve success in developing new products. Originality/Value: This is an original study based on primary data from UAE.

Suggested Citation

  • Aljumah, Ahmad Ibrahim & Nuseir, Mohammed T. & Alam, Md. Mahmudul, 2021. "Traditional Marketing Analytics, Big Data Analytics, Big Data System Quality and the Success of New Product Development," OSF Preprints 9auec, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:9auec
    DOI: 10.31219/osf.io/9auec
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    Cited by:

    1. Mirjana Pejić Bach & Amir Topalović & Lejla Turulja, 2023. "Data mining usage in Italian SMEs: an integrated SEM-ANN approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(3), pages 941-973, September.

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