IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v168y2023ics0148296323005842.html
   My bibliography  Save this article

Examining the role of big data and marketing analytics in SMEs innovation and competitive advantage: A knowledge integration perspective

Author

Listed:
  • Cadden, Trevor
  • Weerawardena, Jay
  • Cao, Guangming
  • Duan, Yanqing
  • McIvor, Ronan

Abstract

The age of digitisation has resulted in an explosion of studies investigating the benefits of Big Data Analytics (BDA) as a means to enhance competitive advantage in organisations. However, the best way to leverage BDA is still inconclusive. Moreover, there is paucity of studies investigating how SMEs, who are recognised as having high levels of entrepreneurial orientation, can utilise big data and marketing analytics to support innovation and competitive advantage in dynamic environments. This study employs dynamic capabilities as a lens to investigate the nuanced relationships. Adopting a partial least squares (PLS) path modelling method with 194 UK SMEs, this study finds that knowledge integration mechanisms are particularly critical value creation enablers by transforming EO and BDA into organisational wide capabilities in support of innovation and competitive advantage. These novel and nuanced insights are of value to both practitioner and researchers.

Suggested Citation

  • Cadden, Trevor & Weerawardena, Jay & Cao, Guangming & Duan, Yanqing & McIvor, Ronan, 2023. "Examining the role of big data and marketing analytics in SMEs innovation and competitive advantage: A knowledge integration perspective," Journal of Business Research, Elsevier, vol. 168(C).
  • Handle: RePEc:eee:jbrese:v:168:y:2023:i:c:s0148296323005842
    DOI: 10.1016/j.jbusres.2023.114225
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296323005842
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jbusres.2023.114225?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Erevelles, Sunil & Fukawa, Nobuyuki & Swayne, Linda, 2016. "Big Data consumer analytics and the transformation of marketing," Journal of Business Research, Elsevier, vol. 69(2), pages 897-904.
    2. Duan, Yanqing & Cao, Guangming & Edwards, John S., 2020. "Understanding the impact of business analytics on innovation," European Journal of Operational Research, Elsevier, vol. 281(3), pages 673-686.
    3. Baker, William E. & Mukherjee, Debmalya & Gattermann Perin, Marcelo, 2022. "Learning orientation and competitive advantage: A critical synthesis and future directions," Journal of Business Research, Elsevier, vol. 144(C), pages 863-873.
    4. Mikalef, Patrick & Pateli, Adamantia, 2017. "Information technology-enabled dynamic capabilities and their indirect effect on competitive performance: Findings from PLS-SEM and fsQCA," Journal of Business Research, Elsevier, vol. 70(C), pages 1-16.
    5. Xu, Zhenning & Frankwick, Gary L. & Ramirez, Edward, 2016. "Effects of big data analytics and traditional marketing analytics on new product success: A knowledge fusion perspective," Journal of Business Research, Elsevier, vol. 69(5), pages 1562-1566.
    6. Danny Miller, 1983. "The Correlates of Entrepreneurship in Three Types of Firms," Management Science, INFORMS, vol. 29(7), pages 770-791, July.
    7. Tanya Menon & Jeffrey Pfeffer, 2003. "Valuing Internal vs. External Knowledge: Explaining the Preference for Outsiders," Management Science, INFORMS, vol. 49(4), pages 497-513, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Patrick Mikalef & Ilias O. Pappas & John Krogstie & Michail Giannakos, 2018. "Big data analytics capabilities: a systematic literature review and research agenda," Information Systems and e-Business Management, Springer, vol. 16(3), pages 547-578, August.
    2. Ladi Daodu & Prof. Dr. Amiya Bhaumik, 2024. "Impacts of Innovation and Business Analytics on the Performance of the Service Sector in Nigeria," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(6), pages 77-91, June.
    3. Irina Maiorescu & Mihaela Bucur & Bogdan Georgescu & Daniel Moise & Vasile Alecsandru Strat & Ion Daniel Zgură, 2020. "Social Media and IOT Wearables in Developing Marketing Strategies. Do SMEs Differ From Large Enterprises?," Sustainability, MDPI, vol. 12(18), pages 1-18, September.
    4. Akhtar, Pervaiz & Khan, Zaheer & Tarba, Shlomo & Jayawickrama, Uchitha, 2018. "The Internet of Things, dynamic data and information processing capabilities, and operational agility," Technological Forecasting and Social Change, Elsevier, vol. 136(C), pages 307-316.
    5. Brewis, Claire & Dibb, Sally & Meadows, Maureen, 2023. "Leveraging big data for strategic marketing: A dynamic capabilities model for incumbent firms," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    6. Jingmei Gao & Zahid Sarwar, 2024. "How do firms create business value and dynamic capabilities by leveraging big data analytics management capability?," Information Technology and Management, Springer, vol. 25(3), pages 283-304, September.
    7. Osama Musa Ali Al-Darras & Cem Tanova, 2022. "From Big Data Analytics to Organizational Agility: What Is the Mechanism?," SAGE Open, , vol. 12(2), pages 21582440221, June.
    8. Claudio Vitari & Elisabetta Raguseo, 2019. "Big data analytics business value and firm performance: Linking with environmental context," Post-Print hal-02293765, HAL.
    9. Giorgi Shuradze & Yevgen Bogodistov & Heinz-Theo Wagner, 2018. "The Role Of Marketing-Enabled Data Analytics Capability And Organisational Agility For Innovation: Empirical Evidence From German Firms," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 22(04), pages 1-32, May.
    10. Côrte-Real, Nadine & Oliveira, Tiago & Ruivo, Pedro, 2017. "Assessing business value of Big Data Analytics in European firms," Journal of Business Research, Elsevier, vol. 70(C), pages 379-390.
    11. 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.
    12. Braganza, Ashley & Brooks, Laurence & Nepelski, Daniel & Ali, Maged & Moro, Russ, 2017. "Resource management in big data initiatives: Processes and dynamic capabilities," Journal of Business Research, Elsevier, vol. 70(C), pages 328-337.
    13. Krzysztof Borodako & Jadwiga Berbeka & Michał Rudnicki, 2021. "Innovation Orientation in Business Services," Books, Edward Elgar Publishing, number 19897.
    14. Lin, Shunzhi & Lin, Jiabao, 2023. "How organizations leverage digital technology to develop customization and enhance customer relationship performance: An empirical investigation," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    15. Vinicius Luiz Ferraz Minatogawa & Matheus Munhoz Vieira Franco & Izabela Simon Rampasso & Rosley Anholon & Ruy Quadros & Orlando Durán & Antonio Batocchio, 2019. "Operationalizing Business Model Innovation through Big Data Analytics for Sustainable Organizations," Sustainability, MDPI, vol. 12(1), pages 1-29, December.
    16. Purva Grover & Arpan Kumar Kar, 2017. "Big Data Analytics: A Review on Theoretical Contributions and Tools Used in Literature," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 18(3), pages 203-229, September.
    17. Nguyen Anh Khoa Dam & Thang Le Dinh & William Menvielle, 2019. "A systematic literature review of big data adoption in internationalization," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(3), pages 182-195, September.
    18. Rialti, Riccardo & Zollo, Lamberto & Ferraris, Alberto & Alon, Ilan, 2019. "Big data analytics capabilities and performance: Evidence from a moderated multi-mediation model," Technological Forecasting and Social Change, Elsevier, vol. 149(C).
    19. Elisabetta Raguseo & Claudio Vitari, 2017. "Investments in big data analytics and firm performance: an empirical investigation of direct and mediating effects," Grenoble Ecole de Management (Post-Print) halshs-01923259, HAL.
    20. Pantano, Eleonora & Dennis, Charles, 2019. "Store buildings as tourist attractions: Mining retail meaning of store building pictures through a machine learning approach," Journal of Retailing and Consumer Services, Elsevier, vol. 51(C), pages 304-310.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jbrese:v:168:y:2023:i:c:s0148296323005842. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbusres .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.