IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v145y2021ics1366554520308139.html
   My bibliography  Save this article

Big Data Analytics as a mediator in Lean, Agile, Resilient, and Green (LARG) practices effects on sustainable supply chains

Author

Listed:
  • Raut, Rakesh D.
  • Mangla, Sachin Kumar
  • Narwane, Vaibhav S.
  • Dora, Manoj
  • Liu, Mengqi

Abstract

The effect of big data on the lean, agile, resilient, and green (LARG) supply chain has not been explored much in the literature. This study investigates the role of ‘Big Data Analytics’ (BDA) as a mediator between ‘sustainable supply chain business performance’ and key factors, namely, lean practices, social practices, environmental practices, organisational practices, supply chain practices, financial practices, and total quality management. A sample of 297 responses from thirty-seven Indian manufacturing firms was collected. The paper is beneficial for managers and practitioners to understand supply chain analytics, and it addresses challenges in the management of LARG practices to contribute to a sustainable supply chain.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:transe:v:145:y:2021:i:c:s1366554520308139
    DOI: 10.1016/j.tre.2020.102170
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554520308139
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tre.2020.102170?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. Ajay Kumar & Ravi Shankar & Alok Choudhary & Lakshman S. Thakur, 2016. "A big data MapReduce framework for fault diagnosis in cloud-based manufacturing," International Journal of Production Research, Taylor & Francis Journals, vol. 54(23), pages 7060-7073, December.
    2. Wang, Minke & Wu, Jiang & Kafa, Nadine & Klibi, Walid, 2020. "Carbon emission-compliance green location-inventory problem with demand and carbon price uncertainties," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    3. Ma-Lin Song & Yuan-Xiang Zhou, 2015. "Analysis of Carbon Emissions and Their Influence Factors Based on Data from Anhui of China," Computational Economics, Springer;Society for Computational Economics, vol. 46(3), pages 359-374, October.
    4. Li, Guo & Li, Lin & Sun, Jiasen, 2019. "Pricing and service effort strategy in a dual-channel supply chain with showrooming effect," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 32-48.
    5. Nurlan Orazalin, 2020. "Do board sustainability committees contribute to corporate environmental and social performance? The mediating role of corporate social responsibility strategy," Business Strategy and the Environment, Wiley Blackwell, vol. 29(1), pages 140-153, January.
    6. Youngseok Choi & Habin Lee & Zahir Irani, 2018. "Big data-driven fuzzy cognitive map for prioritising IT service procurement in the public sector," Annals of Operations Research, Springer, vol. 270(1), pages 75-104, November.
    7. Fang, Yuan & Yu, Yugang & Shi, Ye & Liu, Jie, 2020. "The effect of carbon tariffs on global emission control: A global supply chain model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    8. Tsao, Yu-Chung, 2017. "Managing default risk under trade credit: Who should implement Big-Data analytics in supply chains?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 276-293.
    9. Hau L. Lee & Hongtao Zhang, 2019. "Introduction to the Special Issue on Innovations and Sustainability," Production and Operations Management, Production and Operations Management Society, vol. 28(12), pages 2929-2929, December.
    10. Goldbeck, Nils & Angeloudis, Panagiotis & Ochieng, Washington, 2020. "Optimal supply chain resilience with consideration of failure propagation and repair logistics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    11. Chris K. Y. Lo & Christopher S. Tang & Yi Zhou & Andy C. L. Yeung & Di Fan, 2018. "Environmental Incidents and the Market Value of Firms: An Empirical Investigation in the Chinese Context," Manufacturing & Service Operations Management, INFORMS, vol. 20(3), pages 422-439, July.
    12. Chieh-Yuan Tsai & Sheng-Hsiang Huang, 2015. "A data mining approach to optimise shelf space allocation in consideration of customer purchase and moving behaviours," International Journal of Production Research, Taylor & Francis Journals, vol. 53(3), pages 850-866, February.
    13. Mihalis Giannakis & Michalis Louis, 2016. "A Multi-Agent Based System with Big Data Processing for Enhanced Supply Chain Agility," Post-Print hal-01353916, HAL.
    14. Song, Ma-Lin & Cao, Shao-Peng & Wang, Shu-Hong, 2019. "The impact of knowledge trade on sustainable development and environment-biased technical progress," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 512-523.
    15. Zhong, Ray Y. & Huang, George Q. & Lan, Shulin & Dai, Q.Y. & Chen, Xu & Zhang, T., 2015. "A big data approach for logistics trajectory discovery from RFID-enabled production data," International Journal of Production Economics, Elsevier, vol. 165(C), pages 260-272.
    16. Gunasekaran, Angappa & Papadopoulos, Thanos & Dubey, Rameshwar & Wamba, Samuel Fosso & Childe, Stephen J. & Hazen, Benjamin & Akter, Shahriar, 2017. "Big data and predictive analytics for supply chain and organizational performance," Journal of Business Research, Elsevier, vol. 70(C), pages 308-317.
    17. Hsiu‐Hua Chang & Shin‐Hua Tsai & Chun‐Chen Huang, 2019. "Sustainable development: The effects of environmental policy disclosure in advertising," Business Strategy and the Environment, Wiley Blackwell, vol. 28(8), pages 1497-1506, December.
    18. Zhang, Qiao & Zaccour, Georges & Zhang, Jianxiong & Tang, Wansheng, 2020. "Strategic pricing under quality signaling and imitation behaviors in supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    19. Dubey, Rameshwar & Gunasekaran, Angappa & Childe, Stephen J. & Roubaud, David & Fosso Wamba, Samuel & Giannakis, Mihalis & Foropon, Cyril, 2019. "Big data analytics and organizational culture as complements to swift trust and collaborative performance in the humanitarian supply chain," International Journal of Production Economics, Elsevier, vol. 210(C), pages 120-136.
    20. Theophilus Lartey & Diana Owusu Yirenkyi & Samuel Adomako & Albert Danso & Joseph Amankwah‐Amoah & Ashraful Alam, 2020. "Going green, going clean: Lean‐green sustainability strategy and firm growth," Business Strategy and the Environment, Wiley Blackwell, vol. 29(1), pages 118-139, January.
    21. Fosso Wamba, Samuel & Akter, Shahriar & Edwards, Andrew & Chopin, Geoffrey & Gnanzou, Denis, 2015. "How ‘big data’ can make big impact: Findings from a systematic review and a longitudinal case study," International Journal of Production Economics, Elsevier, vol. 165(C), pages 234-246.
    22. Yu, Wantao & Chavez, Roberto & Jacobs, Mark A. & Feng, Mengying, 2018. "Data-driven supply chain capabilities and performance: A resource-based view," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 371-385.
    23. Frederik Dahlmann & Jens K. Roehrich, 2019. "Sustainable supply chain management and partner engagement to manage climate change information," Business Strategy and the Environment, Wiley Blackwell, vol. 28(8), pages 1632-1647, December.
    24. Velibor V. Mišić & Georgia Perakis, 2020. "Data Analytics in Operations Management: A Review," Manufacturing & Service Operations Management, INFORMS, vol. 22(1), pages 158-169, January.
    25. David Roubaud & Rameshwar Dubey & Cyril Foropon & Angappa Gunasekaran & Stephen J. Childe & Zongwei Luo & Fosso Wamba Samuel, 2018. "Examining the role of big data and predictive analytics on collaborative performance in context to sustainable consumption and production behaviour," Post-Print hal-02051276, HAL.
    26. Junliang Wang & Jie Zhang, 2016. "Big data analytics for forecasting cycle time in semiconductor wafer fabrication system," International Journal of Production Research, Taylor & Francis Journals, vol. 54(23), pages 7231-7244, December.
    27. Tan, Kim Hua & Zhan, YuanZhu & Ji, Guojun & Ye, Fei & Chang, Chingter, 2015. "Harvesting big data to enhance supply chain innovation capabilities: An analytic infrastructure based on deduction graph," International Journal of Production Economics, Elsevier, vol. 165(C), pages 223-233.
    28. 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.
    29. Arunachalam, Deepak & Kumar, Niraj & Kawalek, John Paul, 2018. "Understanding big data analytics capabilities in supply chain management: Unravelling the issues, challenges and implications for practice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 416-436.
    30. Akter, Shahriar & Wamba, Samuel Fosso & Gunasekaran, Angappa & Dubey, Rameshwar & Childe, Stephen J., 2016. "How to improve firm performance using big data analytics capability and business strategy alignment?," International Journal of Production Economics, Elsevier, vol. 182(C), pages 113-131.
    31. Prasanta Kumar Dey & Chrisovalantis Malesios & Debashree De & Soumyadeb Chowdhury & Fouad Ben Abdelaziz, 2019. "Could lean practices and process innovation enhance supply chain sustainability of small and medium‐sized enterprises?," Business Strategy and the Environment, Wiley Blackwell, vol. 28(4), pages 582-598, May.
    32. Shashi & Piera Centobelli & Roberto Cerchione & Myriam Ertz, 2020. "Managing supply chain resilience to pursue business and environmental strategies," Business Strategy and the Environment, Wiley Blackwell, vol. 29(3), pages 1215-1246, March.
    33. Abhijeet Digalwar & Rakesh D. Raut & Vinay S. Yadav & Balkrishna Narkhede & Bhaskar B. Gardas & Ashwini Gotmare, 2020. "Evaluation of critical constructs for measurement of sustainable supply chain practices in lean‐agile firms of Indian origin: A hybrid ISM‐ANP approach," Business Strategy and the Environment, Wiley Blackwell, vol. 29(3), pages 1575-1596, March.
    34. Hazen, Benjamin T. & Boone, Christopher A. & Ezell, Jeremy D. & Jones-Farmer, L. Allison, 2014. "Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications," International Journal of Production Economics, Elsevier, vol. 154(C), pages 72-80.
    35. Roberto Chavez & Wantao Yu & Muhammad Shakeel Sadiq Jajja & Antonio Lecuna & Brian Fynes, 2020. "Can entrepreneurial orientation improve sustainable development through leveraging internal lean practices?," Business Strategy and the Environment, Wiley Blackwell, vol. 29(6), pages 2211-2225, September.
    36. Ma-Lin Song & Ron Fisher & Jian-Lin Wang & Lian-Biao Cui, 2018. "Environmental performance evaluation with big data: theories and methods," Annals of Operations Research, Springer, vol. 270(1), pages 459-472, November.
    37. Hau L. Lee, 2019. "Introduction to the Special Issue on Value Chain Innovations in Developing Economies," Manufacturing & Service Operations Management, INFORMS, vol. 21(2), pages 252-253, April.
    38. Ray Y. Zhong & Chen Xu & Chao Chen & George Q. Huang, 2017. "Big Data Analytics for Physical Internet-based intelligent manufacturing shop floors," International Journal of Production Research, Taylor & Francis Journals, vol. 55(9), pages 2610-2621, May.
    39. Wamba, Samuel Fosso & Gunasekaran, Angappa & Akter, Shahriar & Ren, Steven Ji-fan & Dubey, Rameshwar & Childe, Stephen J., 2017. "Big data analytics and firm performance: Effects of dynamic capabilities," Journal of Business Research, Elsevier, vol. 70(C), pages 356-365.
    40. Erik Hofmann, 2017. "Big data and supply chain decisions: the impact of volume, variety and velocity properties on the bullwhip effect," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 5108-5126, September.
    41. Opresnik, David & Taisch, Marco, 2015. "The value of Big Data in servitization," International Journal of Production Economics, Elsevier, vol. 165(C), pages 174-184.
    42. Michel Tuan Pham & Leonard Lee, 2019. "Introduction to Special Issue: Consumer Emotions in the Marketplace," Journal of the Association for Consumer Research, University of Chicago Press, vol. 4(2), pages 98-101.
    43. Shirish Jeble & Rameshwar Dubey & Stephen J. Childe & Thanos Papadopoulos & David Roubaud & Anand Prakash, 2018. "Impact of big data and predictive analytics capability on supply chain sustainability," Post-Print hal-02061341, HAL.
    44. Christina W.Y. Wong & Chee Yew Wong & Sakun Boon‐itt, 2018. "How Does Sustainable Development of Supply Chains Make Firms Lean, Green and Profitable? A Resource Orchestration Perspective," Business Strategy and the Environment, Wiley Blackwell, vol. 27(3), pages 375-388, March.
    Full references (including those not matched with items on IDEAS)

    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. Claudio Vitari & Elisabetta Raguseo, 2019. "Big data analytics business value and firm performance: Linking with environmental context," Post-Print hal-02293765, HAL.
    2. 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).
    3. Sheng, Jie & Amankwah-Amoah, Joseph & Wang, Xiaojun, 2017. "A multidisciplinary perspective of big data in management research," International Journal of Production Economics, Elsevier, vol. 191(C), pages 97-112.
    4. Vikash Sharma & Rakesh D. Raut & Sachin Kumar Mangla & Balkrishna E. Narkhede & Sunil Luthra & Ravindra Gokhale, 2021. "A systematic literature review to integrate lean, agile, resilient, green and sustainable paradigms in the supply chain management," Business Strategy and the Environment, Wiley Blackwell, vol. 30(2), pages 1191-1212, February.
    5. 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).
    6. Pan Liu & Shu-ping Yi, 2018. "Investment decision-making and coordination of a three-stage supply chain considering Data Company in the Big Data era," Annals of Operations Research, Springer, vol. 270(1), pages 255-271, November.
    7. Roßmann, Bernhard & Canzaniello, Angelo & von der Gracht, Heiko & Hartmann, Evi, 2018. "The future and social impact of Big Data Analytics in Supply Chain Management: Results from a Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 135-149.
    8. Pournader, Mehrdokht & Ghaderi, Hadi & Hassanzadegan, Amir & Fahimnia, Behnam, 2021. "Artificial intelligence applications in supply chain management," International Journal of Production Economics, Elsevier, vol. 241(C).
    9. Vicky Ching Gu & Bin Zhou & Qing Cao & Jeffery Adams, 2021. "Exploring the relationship between supplier development, big data analytics capability, and firm performance," Annals of Operations Research, Springer, vol. 302(1), pages 151-172, July.
    10. Wamba, Samuel Fosso & Dubey, Rameshwar & Gunasekaran, Angappa & Akter, Shahriar, 2020. "The performance effects of big data analytics and supply chain ambidexterity: The moderating effect of environmental dynamism," International Journal of Production Economics, Elsevier, vol. 222(C).
    11. Li, Ying & Dai, Jing & Cui, Li, 2020. "The impact of digital technologies on economic and environmental performance in the context of industry 4.0: A moderated mediation model," International Journal of Production Economics, Elsevier, vol. 229(C).
    12. 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).
    13. Dubey, Rameshwar & Gunasekaran, Angappa & Childe, Stephen J. & Bryde, David J. & Giannakis, Mihalis & Foropon, Cyril & Roubaud, David & Hazen, Benjamin T., 2020. "Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations," International Journal of Production Economics, Elsevier, vol. 226(C).
    14. Ashrafi, Amir & Zare Ravasan, Ahad & Trkman, Peter & Afshari, Samira, 2019. "The role of business analytics capabilities in bolstering firms’ agility and performance," International Journal of Information Management, Elsevier, vol. 47(C), pages 1-15.
    15. 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).
    16. Pan Liu & Shu-ping Yi, 2018. "A study on supply chain investment decision-making and coordination in the Big Data environment," Annals of Operations Research, Springer, vol. 270(1), pages 235-253, November.
    17. de Camargo Fiorini, Paula & Roman Pais Seles, Bruno Michel & Chiappetta Jabbour, Charbel Jose & Barberio Mariano, Enzo & de Sousa Jabbour, Ana Beatriz Lopes, 2018. "Management theory and big data literature: From a review to a research agenda," International Journal of Information Management, Elsevier, vol. 43(C), pages 112-129.
    18. Ray Qing Cao & Dara G. Schniederjans & Vicky Ching Gu, 2021. "Stakeholder sentiment in service supply chains: big data meets agenda-setting theory," Service Business, Springer;Pan-Pacific Business Association, vol. 15(1), pages 151-175, March.
    19. Dubey, Rameshwar & Gunasekaran, Angappa & Childe, Stephen J. & Papadopoulos, Thanos & Luo, Zongwei & Wamba, Samuel Fosso & Roubaud, David, 2019. "Can big data and predictive analytics improve social and environmental sustainability?," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 534-545.
    20. Wang, Hui & Gong, Qiguo & Wang, Shouyang, 2017. "Information processing structures and decision making delays in MRP and JIT," International Journal of Production Economics, Elsevier, vol. 188(C), pages 41-49.

    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:transe:v:145:y:2021:i:c:s1366554520308139. 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/wps/find/journaldescription.cws_home/600244/description#description .

    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.