IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v11y2024i1d10.1057_s41599-024-03424-4.html
   My bibliography  Save this article

Enhancing organizational sustainable innovation performance through organizational readiness for big data analytics

Author

Listed:
  • Muhammad Arshad

    (Yunnan University of Finance and Economics)

  • Aneela Qadir

    (Guangzhou Huashang College)

  • Waqar Ahmad

    (University of Central Punjab)

  • Muhammad Rafique

    (Xian Jiaotong University Xian)

Abstract

Organizations must employ big data analytics to maintain sustained innovation in the highly dynamic and evolving business landscape. Even though BDA has a transformative power to revolutionize how businesses do things and engage with their customers’ adopting BDA has faced significant challenges, especially in developing countries. This research aims to create a theoretical framework to understand how organizational readiness for BDA can influence sustainable innovation performance. Sampling errors were mitigated through a time-lagged study design, and the data was collected in three phases. The test results using Partial Least Squares Structural Equation Modeling show that organizational readiness is a critical mediator, establishing a robust chain between BDA skills and sustainable innovation performance. The results of this study imply the need for organizational foundation and alignment, which are critical to the compelling strategic deployment of BDA for sustainability innovation performance. Thus, this study can offer a valuable contribution to this topic in the future and a profound implication of the phenomenon at receptive stages.

Suggested Citation

  • Muhammad Arshad & Aneela Qadir & Waqar Ahmad & Muhammad Rafique, 2024. "Enhancing organizational sustainable innovation performance through organizational readiness for big data analytics," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.
    • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-03424-4
    DOI: 10.1057/s41599-024-03424-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-024-03424-4
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/s41599-024-03424-4?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. Hemlata Gangwar, 2018. "Understanding the Determinants of Big Data Adoption in India: An Analysis of the Manufacturing and Services Sectors," Information Resources Management Journal (IRMJ), IGI Global, vol. 31(4), pages 1-22, October.
    2. Yen, Yu-Xiang & Yen, Shang-Yung, 2012. "Top-management's role in adopting green purchasing standards in high-tech industrial firms," Journal of Business Research, Elsevier, vol. 65(7), pages 951-959.
    3. Vidgen, Richard & Shaw, Sarah & Grant, David B., 2017. "Management challenges in creating value from business analytics," European Journal of Operational Research, Elsevier, vol. 261(2), pages 626-639.
    4. 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.
    5. Pasquale Del Vecchio & Gioconda Mele & Valentina Ndou & Giustina Secundo, 2018. "Open Innovation and Social Big Data for Sustainability: Evidence from the Tourism Industry," Sustainability, MDPI, vol. 10(9), pages 1-15, September.
    6. Aboelmaged, Mohamed Gamal, 2014. "Predicting e-readiness at firm-level: An analysis of technological, organizational and environmental (TOE) effects on e-maintenance readiness in manufacturing firms," International Journal of Information Management, Elsevier, vol. 34(5), pages 639-651.
    7. Yu-Shan Chen & Shyh-Bao Lai & Chao-Tung Wen, 2006. "The Influence of Green Innovation Performance on Corporate Advantage in Taiwan," Journal of Business Ethics, Springer, vol. 67(4), pages 331-339, September.
    8. 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.
    9. Nuno Queiroz & Nicolas E. Humphries & Ana Couto & Marisa Vedor & Ivo Costa & Ana M. M. Sequeira & Gonzalo Mucientes & António M. Santos & Francisco J. Abascal & Debra L. Abercrombie & Katya Abrantes &, 2021. "Reply to: Caution over the use of ecological big data for conservation," Nature, Nature, vol. 595(7866), pages 20-28, July.
    10. Paul Chwelos & Izak Benbasat & Albert S. Dexter, 2001. "Research Report: Empirical Test of an EDI Adoption Model," Information Systems Research, INFORMS, vol. 12(3), pages 304-321, September.
    11. Maroufkhani, Parisa & Tseng, Ming-Lang & Iranmanesh, Mohammad & Ismail, Wan Khairuzzaman Wan & Khalid, Haliyana, 2020. "Big data analytics adoption: Determinants and performances among small to medium-sized enterprises," International Journal of Information Management, Elsevier, vol. 54(C).
    12. Abraham Carmeli, 2005. "Exploring determinants of job involvement: an empirical test among senior executives," International Journal of Manpower, Emerald Group Publishing Limited, vol. 26(5), pages 457-472, July.
    13. van den Broek, Tijs & van Veenstra, Anne Fleur, 2018. "Governance of big data collaborations: How to balance regulatory compliance and disruptive innovation," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 330-338.
    14. 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).
    15. Sarstedt, Marko & Hair, Joseph F. & Ringle, Christian M. & Thiele, Kai O. & Gudergan, Siegfried P., 2016. "Estimation issues with PLS and CBSEM: Where the bias lies!," Journal of Business Research, Elsevier, vol. 69(10), pages 3998-4010.
    16. Chien-Lung Chan & Chi-Chang Chang, 2022. "Big Data, Decision Models, and Public Health," IJERPH, MDPI, vol. 19(14), pages 1-9, July.
    17. Haklae Kim, 2019. "Analysis of standard vocabulary use of the open government data: the case of the public data portal of Korea," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(3), pages 1611-1622, May.
    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. Qiwei Zhou & Lingqiao Zang & Feiqiang Fu, 2024. "Influence of employee impact on their evaluation of enterprise digital capability: a mediated moderation model," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.

    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. Kristoffersen, Eivind & Mikalef, Patrick & Blomsma, Fenna & Li, Jingyue, 2021. "The effects of business analytics capability on circular economy implementation, resource orchestration capability, and firm performance," International Journal of Production Economics, Elsevier, vol. 239(C).
    2. Kalaitzi, Dimitra & Tsolakis, Naoum, 2022. "Supply chain analytics adoption: Determinants and impacts on organisational performance and competitive advantage," International Journal of Production Economics, Elsevier, vol. 248(C).
    3. Ashaari, Mohamed Azlan & Singh, Karpal Singh Dara & Abbasi, Ghazanfar Ali & Amran, Azlan & Liebana-Cabanillas, Francisco J., 2021. "Big data analytics capability for improved performance of higher education institutions in the Era of IR 4.0: A multi-analytical SEM & ANN perspective," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    4. Kristoffersen, Eivind & Mikalef, Patrick & Blomsma, Fenna & Li, Jingyue, 2021. "Towards a business analytics capability for the circular economy," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    5. Amit Kumar & Bala Krishnamoorthy, 2020. "Business Analytics Adoption in Firms: A Qualitative Study Elaborating TOE Framework in India," International Journal of Global Business and Competitiveness, Springer, vol. 15(2), pages 80-93, December.
    6. Shafique, Muhammad Noman & Yeo, Sook Fern & Tan, Cheng Ling, 2024. "Roles of top management support and compatibility in big data predictive analytics for supply chain collaboration and supply chain performance," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
    7. Luqman, Adeel & Wang, Liangyu & Katiyar, Gagan & Agarwal, Reeti & Mohapatra, Amiya Kumar, 2024. "Unpacking associations between positive-negative valence and ambidexterity of big data. Implications for firm performance," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    8. Tabesh, Pooya & Mousavidin, Elham & Hasani, Sona, 2019. "Implementing big data strategies: A managerial perspective," Business Horizons, Elsevier, vol. 62(3), pages 347-358.
    9. Papanagnou, Christos & Seiler, Andreas & Spanaki, Konstantina & Papadopoulos, Thanos & Bourlakis, Michael, 2022. "Data-driven digital transformation for emergency situations: The case of the UK retail sector," International Journal of Production Economics, Elsevier, vol. 250(C).
    10. Oesterreich, Thuy Duong & Anton, Eduard & Teuteberg, Frank & Dwivedi, Yogesh K, 2022. "The role of the social and technical factors in creating business value from big data analytics: A meta-analysis," Journal of Business Research, Elsevier, vol. 153(C), pages 128-149.
    11. 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.
    12. Marcos Carchano & Inmaculada Carrasco & Ángela González, 2024. "Eco‐innovation and environmental performance: Insights from Spanish wine companies," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 95(2), pages 595-623, June.
    13. Elisa Giampietri & Samuele Trestini, 2020. "Analysing farmers' intention to adopt web marketing under a technology-organisation-environment perspective: A case study in Italy," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 66(5), pages 226-233.
    14. Leal-Rodríguez, Antonio L. & Ariza-Montes, Antonio J. & Morales-Fernández, Emilio & Albort-Morant, Gema, 2018. "Green innovation, indeed a cornerstone in linking market requests and business performance. Evidence from the Spanish automotive components industry," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 185-193.
    15. Liu, Hua & Xu, Xiaoping & Cheng, T.C.E. & Yu, Yugang, 2024. "Building resilience or maintaining robustness: Insights from relational view and information processing perspective," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 188(C).
    16. Morimura, Fumikazu & Sakagawa, Yuji, 2023. "The intermediating role of big data analytics capability between responsive and proactive market orientations and firm performance in the retail industry," Journal of Retailing and Consumer Services, Elsevier, vol. 71(C).
    17. Jing Yi Yong & Mohd Yusoff Yusliza & Thurasamy Ramayah & Bruno Michel Roman Pais Seles, 2022. "Testing the stakeholder pressure, relative advantage, top management commitment and green human resource management linkage," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 29(5), pages 1283-1299, September.
    18. García-Granero, Eva M. & Piedra-Muñoz, Laura & Galdeano-Gómez, Emilio, 2020. "Measuring eco-innovation dimensions: The role of environmental corporate culture and commercial orientation," MPRA Paper 119909, University Library of Munich, Germany.
    19. Chen, Yantai & Luo, Haibei & Chen, Jin & Guo, Yanlin, 2022. "Building data-driven dynamic capabilities to arrest knowledge hiding: A knowledge management perspective," Journal of Business Research, Elsevier, vol. 139(C), pages 1138-1154.
    20. Bag, Surajit & Dhamija, Pavitra & Bryde, David J. & Singh, Rajesh Kumar, 2022. "Effect of eco-innovation on green supply chain management, circular economy capability, and performance of small and medium enterprises," Journal of Business Research, Elsevier, vol. 141(C), pages 60-72.

    More about this item

    Statistics

    Access and download statistics

    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:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-03424-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: https://www.nature.com/ .

    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.