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An integrated artificial intelligence framework for knowledge creation and B2B marketing rational decision making for improving firm performance

Author

Listed:
  • Surajit Bag

    (UJ - University of Johannesburg [South Africa], NUS - North South University)

  • Shivam Gupta

    (NEOMA - Neoma Business School)

  • Ajay Kumar

    (EM - EMLyon Business School)

  • Uthayasankar Sivarajah

    (University of Bradford)

Abstract

This study examines the effect of big data powered artificial intelligence on customer knowledge creation, user knowledge creation and external market knowledge creation to better understand its impact on B2B marketing rational decision making to influence firm performance. The theoretical model is grounded in Knowledge Management Theory (KMT) and the primary data was collected from B2B companies functioning in the South African mining industry. Findings point out that big data powered artificial intelligence and the path customer knowledge creation is significant. Secondly, big data powered artificial intelligence and the path user knowledge creation is significant. Thirdly, big data powered artificial intelligence and the path external market knowledge creation is significant. It was observed that customer knowledge creation, user knowledge creation and external market knowledge creation have significant effect on the B2B marketing-rational decision making. Finally, the path B2B marketing rational decision making has a significant effect on firm performance.

Suggested Citation

  • Surajit Bag & Shivam Gupta & Ajay Kumar & Uthayasankar Sivarajah, 2021. "An integrated artificial intelligence framework for knowledge creation and B2B marketing rational decision making for improving firm performance," Post-Print hal-03188195, HAL.
    • Handle: RePEc:hal:journl:hal-03188195
    DOI: 10.1016/j.indmarman.2020.12.001
    Note: View the original document on HAL open archive server: https://hal.science/hal-03188195v1
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    References listed on IDEAS

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    2. Bag, Surajit & Sabbir Rahman, Muhammad & Rogers, Helen & Srivastava, Gautam & Harm Christiaan Pretorius, Jan, 2023. "Climate change adaptation and disaster risk reduction in the garment industry supply chain network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 171(C).
    3. Feifei Huang & Mingxia Lin & Shoukat Iqbal Khattak, 2024. "Form Uncertainty to Sustainable Decision-Making: A Novel MIDAS–AM–DeepAR-Based Prediction Model for E-Commerce Industry Development," Sustainability, MDPI, vol. 16(14), pages 1-24, July.
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    6. Zahid Sarwar & Jingmei Gao & Adnan Khan, 2024. "Nexus of digital platforms, innovation capability, and strategic alignment to enhance innovation performance in the Asia Pacific region: a dynamic capability perspective," Asia Pacific Journal of Management, Springer, vol. 41(2), pages 867-901, June.
    7. Kirti Nayal & Shashank Kumar & Rakesh D. Raut & Maciel M. Queiroz & Pragati Priyadarshinee & Balkrishna E. Narkhede, 2022. "Supply chain firm performance in circular economy and digital era to achieve sustainable development goals," Business Strategy and the Environment, Wiley Blackwell, vol. 31(3), pages 1058-1073, March.
    8. Liu, Yang & Ying, Zhenzhou & Ying, Ying & Wang, Ding & Chen, Jin, 2024. "Artificial intelligence orientation and internationalization speed: A knowledge management perspective," Technological Forecasting and Social Change, Elsevier, vol. 205(C).
    9. Nadeem, Kashif & Wong, Sut I. & Za, Stefano & Venditti, Michelina, 2024. "Digital transformation and industry 4.0 employees: Empirical evidence from top digital nations," Technology in Society, Elsevier, vol. 76(C).
    10. Rahman, Muhammad Sabbir & Bag, Surajit & Gupta, Shivam & Sivarajah, Uthayasankar, 2023. "Technology readiness of B2B firms and AI-based customer relationship management capability for enhancing social sustainability performance," Journal of Business Research, Elsevier, vol. 156(C).
    11. Manis, K.T. & Madhavaram, Sreedhar, 2023. "AI-Enabled marketing capabilities and the hierarchy of capabilities: Conceptualization, proposition development, and research avenues," Journal of Business Research, Elsevier, vol. 157(C).
    12. Lai-Ying Leong & Teck-Soon Hew & Keng-Boon Ooi & Bhimaraya Metri & Yogesh K. Dwivedi, 2023. "Extending the Theory of Planned Behavior in the Social Commerce Context: A Meta-Analytic SEM (MASEM) Approach," Information Systems Frontiers, Springer, vol. 25(5), pages 1847-1879, October.
    13. Liang, Xiaoning & Li, Guoxin & Zhang, Hao & Nolan, Eimear & Chen, Fadong, 2022. "Firm performance and marketing analytics in the Chinese context: A contingency model," Journal of Business Research, Elsevier, vol. 141(C), pages 589-599.
    14. Sagarika Mishra & Michael T. Ewing & Holly B. Cooper, 2022. "Artificial intelligence focus and firm performance," Journal of the Academy of Marketing Science, Springer, vol. 50(6), pages 1176-1197, November.
    15. Edwards, John & Miles, Morgan P. & D'Alessandro, Steven & Frost, Mark, 2022. "Linking B2B sales performance to entrepreneurial self-efficacy, entrepreneurial selling actions," Journal of Business Research, Elsevier, vol. 142(C), pages 585-593.
    16. Wang, Lei & Zhou, Yahong & Chiao, Benjamin, 2023. "Robots and firm innovation: Evidence from Chinese manufacturing," Journal of Business Research, Elsevier, vol. 162(C).
    17. Pervaiz Akhtar & Arsalan Mujahid Ghouri & Haseeb Ur Rehman Khan & Mirza Amin ul Haq & Usama Awan & Nadia Zahoor & Zaheer Khan & Aniqa Ashraf, 2023. "Detecting fake news and disinformation using artificial intelligence and machine learning to avoid supply chain disruptions," Annals of Operations Research, Springer, vol. 327(2), pages 633-657, August.

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