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Cloud-based big data analytics for customer insight-driven design innovation in SMEs

Author

Listed:
  • Liu, Ying
  • Soroka, Anthony
  • Han, Liangxiu
  • Jian, Jin
  • Tang, Min

Abstract

Fast development of IT and ICT facilitate customers to post a large volume of their concerns and expectation online, which are widely accepted to be a valuable resource for product designers. However, it is found that only a small number of small and medium-sized enterprises (SMEs) have capabilities to leverage customer online insights for design innovation, which often demonstrate a significant share in national economies growth. To discover the beneath reasons regarding the barrier that prevent them to make effective utilization, in this study, as a concrete example, manufacturing SMEs in the South Wales and Greater Manchester industrial areas of the UK are focused and their potential motivations for using and knowledge of big data-based customer analytics are investigated. An exploratory survey was conducted in terms of the type of customer data they have, the storage approaches, the volume of customer data, etc. Next, a carefully devised exploratory study was undertaken to understand how SMEs perceive the relations between customer data and product design, how about their expectations from big customer data analytics and what really challenges SMEs to exploit the value of big customer data. Besides, a demonstration platform is developed to present SMEs an automatic process of analysing customer online reviews and the capacity on customer insights acquisition and strategic decision making. Finally, findings from two focus groups indicate the different managerial and technical considerations required for SMEs considering implementing big data and customer analytics. This study encourages SMEs to welcome big customer data and suggests that a cloud-based approach may be the most appropriate way of giving access to big data analytics techniques.

Suggested Citation

  • Liu, Ying & Soroka, Anthony & Han, Liangxiu & Jian, Jin & Tang, Min, 2020. "Cloud-based big data analytics for customer insight-driven design innovation in SMEs," International Journal of Information Management, Elsevier, vol. 51(C).
    • Handle: RePEc:eee:ininma:v:51:y:2020:i:c:s0268401219305183
    DOI: 10.1016/j.ijinfomgt.2019.11.002
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    Citations

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    Cited by:

    1. Shivam Gupta & Théo Justy & Shampy Kamboj & Ajay Kumar & Eivind Kristoffersen, 2021. "Big data and firm marketing performance: Findings from knowledge-based view," Post-Print hal-03609916, HAL.
    2. Friday O Ugbebor, 2024. "Intelligent Cloud Solutions Bridging Technology Gaps for Small and Medium-Sized Enterprises," Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, Open Knowledge, vol. 7(01), pages 161-186.
    3. Xia Liu & Yanhan Sun & Shengshi Zhou & Yu Li & Shan Zhuang, 2024. "Research on time-value-oriented business model innovation path in life services enterprises and its impact on customer perceived value," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    4. Justy, Théo & Pellegrin-Boucher, Estelle & Lescop, Denis & Granata, Julien & Gupta, Shivam, 2023. "On the edge of Big Data: Drivers and barriers to data analytics adoption in SMEs," Technovation, Elsevier, vol. 127(C).
    5. Guojun Ji & Muhong Yu & Kim Hua Tan & Ajay Kumar & Shivam Gupta, 2024. "Decision optimization in cooperation innovation: the impact of big data analytics capability and cooperative modes," Annals of Operations Research, Springer, vol. 333(2), pages 871-894, February.
    6. Perdana, Arif & Lee, Hwee Hoon & Koh, SzeKee & Arisandi, Desi, 2022. "Data analytics in small and mid-size enterprises: Enablers and inhibitors for business value and firm performance," International Journal of Accounting Information Systems, Elsevier, vol. 44(C).
    7. Sabeen Hussain Bhatti & Wan Mohd Hirwani Wan Hussain & Jabran Khan & Shahbaz Sultan & Alberto Ferraris, 2024. "Exploring data-driven innovation: What’s missing in the relationship between big data analytics capabilities and supply chain innovation?," Annals of Operations Research, Springer, vol. 333(2), pages 799-824, February.
    8. Itzhak Gnizy, 2025. "When and how digital novel technologies matter to firm marketing performance," Journal of Marketing Analytics, Palgrave Macmillan, vol. 13(1), pages 218-235, March.
    9. Arash Moghadasi, 2024. "Do SMEs Consider Open Data as a Vital Intellectual Asset? a Systematic Literature Review," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 11784-11818, September.
    10. Maya Vachkova & Arsalan Ghouri & Haidy Ashour & Normalisa Binti Md Isa & Gregory Barnes, 2023. "Big data and predictive analytics and Malaysian micro-, small and medium businesses," SN Business & Economics, Springer, vol. 3(8), pages 1-28, August.
    11. Jianmin Song & Senmao Xia & Demetris Vrontis & Arun Sukumar & Bing Liao & Qi Li & Kun Tian & Nengzhi Yao, 2022. "The Source of SMEs’ Competitive Performance in COVID-19: Matching Big Data Analytics Capability to Business Models," Information Systems Frontiers, Springer, vol. 24(4), pages 1167-1187, August.

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