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Achieving the Success of Sustainability Development Projects through Big Data Analytics and Artificial Intelligence Capability

Author

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  • Haili Zhang

    (School of Economics and Management, Xi’an Technological University, Xi’an 710021, China)

  • Michael Song

    (School of Economics and Management, Xi’an Technological University, Xi’an 710021, China)

  • Huanhuan He

    (School of Economics and Management, Xi’an Technological University, Xi’an 710021, China)

Abstract

There has been increased interest in studying how big data analytics capability (BDAC) and artificial intelligence capability (AIC) lead to sustainable innovation and performance. Yet, few studies have investigated how these two emerging capabilities affect the success of sustainability development projects through the mediating effects of the sustainability design and commercialization processes. Based on Day and Wensley’s theoretical framework for diagnosing competitive superiority, we propose a research model to investigate how sustainability design and commercialization mediate the relationships between two emerging capabilities and sustainable growth and performance. To test the proposed research model, we collected empirical data from 905 sustainability development projects from China and the United States. This study makes theoretical and managerial contributions to sustainable development theory. The study findings reveal several interesting results. First, BDAC and AIC not only increase the proficiency of sustainability design and commercialization but also directly enhance sustainable growth and performance. Second, sustainability design and commercialization mediate the positive effects of BDAC and AIC on sustainable growth and performance. Finally, the empirical analyses uncovered several cross-national differences. For sustainability design, BDAC is more important than AIC in the United States, while AIC is more important than BDAC in China.

Suggested Citation

  • Haili Zhang & Michael Song & Huanhuan He, 2020. "Achieving the Success of Sustainability Development Projects through Big Data Analytics and Artificial Intelligence Capability," Sustainability, MDPI, vol. 12(3), pages 1-23, January.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:3:p:949-:d:313831
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    References listed on IDEAS

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    2. Huynh, Minh-Tay & Nippa, Michael & Aichner, Thomas, 2023. "Big data analytics capabilities: Patchwork or progress? A systematic review of the status quo and implications for future research," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    3. Omar. A. Alghamdi & Gomaa Agag, 2023. "Boosting Innovation Performance through Big Data Analytics Powered by Artificial Intelligence Use: An Empirical Exploration of the Role of Strategic Agility and Market Turbulence," Sustainability, MDPI, vol. 15(19), pages 1-19, September.
    4. H. Kava & K. Spanaki & T. Papadopoulos & S. Despoudi & O. Rodriguez Espindola & M. Fakhimi, 2024. "Data analytics diffusion in the UK renewable energy sector: an innovation perspective," Post-Print hal-04478933, HAL.
    5. Yufan Wang & Haili Zhang, 2020. "Achieving Sustainable New Product Development by Implementing Big Data-Embedded New Product Development Process," Sustainability, MDPI, vol. 12(11), pages 1-20, June.
    6. Harkaran Kava & Konstantina Spanaki & Thanos Papadopoulos & Stella Despoudi & Oscar Rodriguez-Espindola & Masoud Fakhimi, 2021. "Data Analytics Diffusion in the UK Renewable Energy Sector: An Innovation Perspective," Post-Print hal-03781046, HAL.
    7. Jose Andres-Jimenez & Jose-Amelio Medina-Merodio & Luis Fernandez-Sanz & Jose-Javier Martinez-Herraiz & Estefania Ruiz-Pardo, 2020. "An Intelligent Framework for the Evaluation of Compliance with the Requirements of ISO 9001:2015," Sustainability, MDPI, vol. 12(13), pages 1-23, July.
    8. Xiaoli Wang & Ying Gu & Mahmood Ahmad & Chaokai Xue, 2022. "The Impact of Digital Capability on Manufacturing Company Performance," Sustainability, MDPI, vol. 14(10), pages 1-24, May.
    9. Philipp Korherr & Dominik Kanbach, 2023. "Human-related capabilities in big data analytics: a taxonomy of human factors with impact on firm performance," Review of Managerial Science, Springer, vol. 17(6), pages 1943-1970, August.
    10. Shin-Cheng Yeh & Ai-Wei Wu & Hui-Ching Yu & Homer C. Wu & Yi-Ping Kuo & Pei-Xuan Chen, 2021. "Public Perception of Artificial Intelligence and Its Connections to the Sustainable Development Goals," Sustainability, MDPI, vol. 13(16), pages 1-34, August.

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