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Customer agility and big data analytics in new product context

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  • Tseng, Hsiao-Ting
  • Aghaali, Niloofar
  • Hajli, Dr Nick

Abstract

New product development is s complicated process in marketing. New product success is an important part of new product development. Firms can use big data analytics to track new product success. Therefore, we develop quantitative research to see how big data analytics can help the firms on the new product success process. Using a survey, we collect data from the industry. The results of our PLS analysis show the effective use of data interpretation tools and effective use of data analysis tools are important factors to share customer agility in new product success. Our research has theoretical contributions and practical implications, which we discuss at the end of the paper.

Suggested Citation

  • Tseng, Hsiao-Ting & Aghaali, Niloofar & Hajli, Dr Nick, 2022. "Customer agility and big data analytics in new product context," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
  • Handle: RePEc:eee:tefoso:v:180:y:2022:i:c:s0040162522002177
    DOI: 10.1016/j.techfore.2022.121690
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    References listed on IDEAS

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    7. Sepasgozar, Samad M.E. & Hawken, Scott & Sargolzaei, Sharifeh & Foroozanfa, Mona, 2019. "Implementing citizen centric technology in developing smart cities: A model for predicting the acceptance of urban technologies," Technological Forecasting and Social Change, Elsevier, vol. 142(C), pages 105-116.
    8. Tena Žužek & Žiga Gosar & Janez Kušar & Tomaž Berlec, 2021. "A New Product Development Model for SMEs: Introducing Agility to the Plan-Driven Concurrent Product Development Approach," Sustainability, MDPI, vol. 13(21), pages 1-22, November.
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    Cited by:

    1. Sun, Pengfei & Yuan, Chunhui & Li, Xiaolong & Di, Jia, 2024. "Big data analytics, firm risk and corporate policies: Evidence from China," Research in International Business and Finance, Elsevier, vol. 70(PB).
    2. Sivarajah, Uthayasankar & Kumar, Sachin & Kumar, Vinod & Chatterjee, Sheshadri & Li, Jing, 2024. "A study on big data analytics and innovation: From technological and business cycle perspectives," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    3. Anwar, Muhammad Azfar & Zong, Zupan & Mendiratta, Aparna & Yaqub, Muhammad Zafar, 2024. "Antecedents of big data analytics adoption and its impact on decision quality and environmental performance of SMEs in recycling sector," Technological Forecasting and Social Change, Elsevier, vol. 205(C).
    4. Tseng, Hsiao-Ting, 2023. "Customer-centered data power: Sensing and responding capability in big data analytics," Journal of Business Research, Elsevier, vol. 158(C).
    5. Mansour Alyahya & Meqbel Aliedan & Gomaa Agag & Ziad H. Abdelmoety, 2023. "Understanding the Relationship between Big Data Analytics Capabilities and Sustainable Performance: The Role of Strategic Agility and Firm Creativity," Sustainability, MDPI, vol. 15(9), pages 1-17, May.

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