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Agile manufacturing practices: the role of big data and business analytics with multiple case studies

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  • Angappa Gunasekaran
  • Yahaya Y. Yusuf
  • Ezekiel O. Adeleye
  • Thanos Papadopoulos

Abstract

The purpose of this study was to examine the role of big data and business analytics (BDBA) in agile manufacturing practices. Literature has discussed the benefits and challenges related to the deployment of big data within operations and supply chains, but there has not been a study of the facilitating roles of BDBA in achieving an enhanced level of agile manufacturing practices. As a response to this gap, and drawing upon multiple qualitative case studies undertaken among four UK organisations, we present and validate a framework for the role of BDBA within agile manufacturing. The findings show that market turbulence has negative universal effects and that agile manufacturing enablers are being progressively deployed and aided by BDBA to yield better competitive and business performance objectives. Further, the level of intervention was found to differ across companies depending on the extent of deployment of BDBA, which accounts for variations in outcomes.

Suggested Citation

  • Angappa Gunasekaran & Yahaya Y. Yusuf & Ezekiel O. Adeleye & Thanos Papadopoulos, 2018. "Agile manufacturing practices: the role of big data and business analytics with multiple case studies," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 385-397, January.
    • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:385-397
    DOI: 10.1080/00207543.2017.1395488
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    Cited by:

    1. Omar, Yamila M. & Minoufekr, Meysam & Plapper, Peter, 2019. "Business analytics in manufacturing: Current trends, challenges and pathway to market leadership," Operations Research Perspectives, Elsevier, vol. 6(C).
    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. Sheshadri Chatterjee & Ranjan Chaudhuri & Sachin Kamble & Shivam Gupta & Uthayasankar Sivarajah, 2023. "Adoption of Artificial Intelligence and Cutting-Edge Technologies for Production System Sustainability: A Moderator-Mediation Analysis," Information Systems Frontiers, Springer, vol. 25(5), pages 1779-1794, October.
    4. Ahmad Ibrahim Aljumah & Mohammed T. Nuseir & Md. Mahmudul Alam, 2021. "Traditional marketing analytics, big data analytics and big data system quality and the success of new product development," Post-Print hal-03538161, HAL.
    5. Priyank Srivastava & Dinesh Khanduja & V. P. Agrawal, 2020. "Agile maintenance attribute coding and evaluation based decision making in sugar manufacturing plant," OPSEARCH, Springer;Operational Research Society of India, vol. 57(2), pages 553-583, June.
    6. Sundarakani, Balan & Ajaykumar, Aneesh & Gunasekaran, Angappa, 2021. "Big data driven supply chain design and applications for blockchain: An action research using case study approach," Omega, Elsevier, vol. 102(C).
    7. Bag, Surajit & Rahman, Muhammad Sabbir & Srivastava, Gautam & Shore, Adam & Ram, Pratibha, 2023. "Examining the role of virtue ethics and big data in enhancing viable, sustainable, and digital supply chain performance," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
    8. Gillani, Fatima & Chatha, Kamran Ali & Sadiq Jajja, Muhammad Shakeel & Farooq, Sami, 2020. "Implementation of digital manufacturing technologies: Antecedents and consequences," International Journal of Production Economics, Elsevier, vol. 229(C).
    9. Slobodan Acimovic & Nenad Stajic, 2022. "Startups – Business Models For Enhancing Supply Chain 4.0," Business Logistics in Modern Management, Josip Juraj Strossmayer University of Osijek, Faculty of Economics, Croatia, vol. 22, pages 171-190.
    10. Ciampi, Francesco & Faraoni, Monica & Ballerini, Jacopo & Meli, Francesco, 2022. "The co-evolutionary relationship between digitalization and organizational agility: Ongoing debates, theoretical developments and future research perspectives," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    11. Dmitry Ivanov, 2022. "Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic," Annals of Operations Research, Springer, vol. 319(1), pages 1411-1431, December.
    12. Chih-Hung Hsu & Ming-Ge Li & Ting-Yi Zhang & An-Yuan Chang & Shu-Zhen Shangguan & Wan-Ling Liu, 2022. "Deploying Big Data Enablers to Strengthen Supply Chain Resilience to Mitigate Sustainable Risks Based on Integrated HOQ-MCDM Framework," Mathematics, MDPI, vol. 10(8), pages 1-35, April.
    13. Gullelala Jadoon & Ikram Ud Din & Ahmad Almogren & Hisham Almajed, 2020. "Smart and Agile Manufacturing Framework, A Case Study for Automotive Industry," Energies, MDPI, vol. 13(21), pages 1-13, November.
    14. Alberto Bertello & Alberto Ferraris & Stefano Bresciani & Paola Bernardi, 2021. "Big data analytics (BDA) and degree of internationalization: the interplay between governance of BDA infrastructure and BDA capabilities," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 25(4), pages 1035-1055, December.
    15. Acciarini, Chiara & Cappa, Francesco & Boccardelli, Paolo & Oriani, Raffaele, 2023. "How can organizations leverage big data to innovate their business models? A systematic literature review," Technovation, Elsevier, vol. 123(C).
    16. Anna-Theresa Walter, 2021. "Organizational agility: ill-defined and somewhat confusing? A systematic literature review and conceptualization," Management Review Quarterly, Springer, vol. 71(2), pages 343-391, April.
    17. 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).
    18. Raut, Rakesh D. & Mangla, Sachin Kumar & Narwane, Vaibhav S. & Dora, Manoj & Liu, Mengqi, 2021. "Big Data Analytics as a mediator in Lean, Agile, Resilient, and Green (LARG) practices effects on sustainable supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    19. Yang, Miying & Fu, Mingtao & Zhang, Zihan, 2021. "The adoption of digital technologies in supply chains: Drivers, process and impact," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    20. Shao, Xiao-Feng, 2020. "What is the right production strategy for horizontally differentiated product: Standardization or mass customization?," International Journal of Production Economics, Elsevier, vol. 223(C).
    21. Aljumah, Ahmad Ibrahim & Nuseir, Mohammed T. & Alam, Md. Mahmudul, 2021. "Organizational Performance and Capabilities to Analyze Big Data: Do the Ambidexterity and Business Value of Big Data Analytics Matter?," OSF Preprints an8er, Center for Open Science.
    22. Qamar, A. & Gardner, E.C. & Buckley, T. & Zhao, K., 2021. "Home-owned versus foreign-owned firms in the UK automotive industry: Exploring the microfoundations of ambidextrous production and supply chain positioning," International Business Review, Elsevier, vol. 30(1).
    23. Mashalah, Heider Al & Hassini, Elkafi & Gunasekaran, Angappa & Bhatt (Mishra), Deepa, 2022. "The impact of digital transformation on supply chains through e-commerce: Literature review and a conceptual framework," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).

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