IDEAS home Printed from https://ideas.repec.org/a/sae/sagope/v13y2023i4p21582440231217902.html
   My bibliography  Save this article

Factor Influencing the Adoption of Big Data Analytics: A Systematic Literature and Experts Review

Author

Listed:
  • Showimy Aldossari
  • Umi Asma’ Mokhtar
  • Ahmad Tarmizi Abdul Ghani

Abstract

In the current market landscape, enterprises face tremendous pressure to remain competitive and innovative to extend their businesses globally. Thus, a need exists for a new data analysis technique and a tool known as Big Data Analytics (BDA), which refers to massive data sets in light of their volume, velocity, variety, and veracity. Small and Medium Enterprises (SMEs) face challenges in obtaining and utilizing the knowledge derived from big data to make informed decisions regarding market selection and adopting appropriate internationalization strategies. These enterprises encounter resource limitations that hinder their ability to effectively acquire and implement big data insights for strategic decision-making in these areas. This systematic literature review aims to investigate the state of research on adopting big data analytics in SMEs. The study focuses on identifying key factors that influence the adoption of BDA. The study extracted 13 significant factors that are the highest influencers for BDA in SMEs. Those factors are top management support, training, relative advantage, it infrastructure, security, compatibility, complexity, adaptability, government it policies, competency, collaboration, digital transformation tools, and decision quality. The findings of this review are useful for practitioners, researchers, and decision-makers in understanding the factors that influence the adoption of big data analytics and the potential benefits and challenges associated with its implementation. Findings will shed light on the interplay between data governance and other factors influencing adoption, providing valuable insights for organizations seeking to establish robust data governance frameworks that support successful BDA initiatives.

Suggested Citation

  • Showimy Aldossari & Umi Asma’ Mokhtar & Ahmad Tarmizi Abdul Ghani, 2023. "Factor Influencing the Adoption of Big Data Analytics: A Systematic Literature and Experts Review," SAGE Open, , vol. 13(4), pages 21582440231, December.
    • Handle: RePEc:sae:sagope:v:13:y:2023:i:4:p:21582440231217902
    DOI: 10.1177/21582440231217902
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/21582440231217902
    Download Restriction: no
    File URL: https://libkey.io/10.1177/21582440231217902?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
    ---><---

    References listed on IDEAS

    as
    1. Charlie Chen & Hoon Seok Choi & Peter Ractham, 2022. "Data, attitudinal and organizational determinants of big data analytics systems use," Cogent Business & Management, Taylor & Francis Journals, vol. 9(1), pages 2043535-204, December.
    2. Youssef, Mayada Abd El-Aziz & Eid, Riyad & Agag, Gomaa, 2022. "Cross-national differences in big data analytics adoption in the retail industry," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    3. Ebrahim A. A. Ghaleb & P. D. D. Dominic & Suliman Mohamed Fati & Amgad Muneer & Rao Faizan Ali, 2021. "The Assessment of Big Data Adoption Readiness with a Technology–Organization–Environment Framework: A Perspective towards Healthcare Employees," Sustainability, MDPI, vol. 13(15), pages 1-33, July.
    4. Sivarajah, Uthayasankar & Kamal, Muhammad Mustafa & Irani, Zahir & Weerakkody, Vishanth, 2017. "Critical analysis of Big Data challenges and analytical methods," Journal of Business Research, Elsevier, vol. 70(C), pages 263-286.
    5. Cheng-Kui Huang & Tawei Wang & Tzu-Yen Huang, 2020. "Initial Evidence on the Impact of Big Data Implementation on Firm Performance," Information Systems Frontiers, Springer, vol. 22(2), pages 475-487, April.
    6. Hamza Saleem & Yongjun Li & Zulqurnain Ali & Aqsa Mehreen & Muhammad Salman Mansoor, 2020. "An empirical investigation on how big data analytics influence China SMEs performance: do product and process innovation matter?," Asia Pacific Business Review, Taylor & Francis Journals, vol. 26(5), pages 537-562, October.
    7. 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).
    8. 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).
    9. Muhammad Shahbaz & Changyuan Gao & Lili Zhai & Fakhar Shahzad & Adeel Luqman & Rimsha Zahid, 2021. "Impact of big data analytics on sales performance in pharmaceutical organizations: The role of customer relationship management capabilities," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-22, April.
    10. Raguseo, Elisabetta, 2018. "Big data technologies: An empirical investigation on their adoption, benefits and risks for companies," International Journal of Information Management, Elsevier, vol. 38(1), pages 187-195.
    11. Cabrera-Sánchez, Juan-Pedro & Villarejo-Ramos, à ngel F., 2020. "Acceptance and use of big data techniques in services companies," Journal of Retailing and Consumer Services, Elsevier, vol. 52(C).
    12. Luther Yuong Qai Chong & Thien Sang Lim, 2022. "Pull and Push Factors of Data Analytics Adoption and Its Mediating Role on Operational Performance," Sustainability, MDPI, vol. 14(12), pages 1-19, June.
    13. Tuba Bakici & André Nemeh & Öncü Hazir, 2023. "Big Data Adoption in Project Management: Insights From French Organizations," Post-Print hal-04183058, HAL.
    14. Amankwah-Amoah, Joseph, 2019. "Big data analytics and business failures in data-Rich environments: An organizing framework," MPRA Paper 91264, University Library of Munich, Germany.
    15. Abdalwali Lutfi & Adi Alsyouf & Mohammed Amin Almaiah & Mahmaod Alrawad & Ahmed Abdullah Khalil Abdo & Akif Lutfi Al-Khasawneh & Nahla Ibrahim & Mohamed Saad, 2022. "Factors Influencing the Adoption of Big Data Analytics in the Digital Transformation Era: Case Study of Jordanian SMEs," Sustainability, MDPI, vol. 14(3), pages 1-17, February.
    16. Nam, Dalwoo & Lee, Junyeong & Lee, Heeseok, 2019. "Business analytics adoption process: An innovation diffusion perspective," International Journal of Information Management, Elsevier, vol. 49(C), pages 411-423.
    17. Hassan Keshavarz & Akbariah Mohd Mahdzir & Hosna Talebian & Neda Jalaliyoon & Naoki Ohshima, 2021. "The Value of Big Data Analytics Pillars in Telecommunication Industry," Sustainability, MDPI, vol. 13(13), pages 1-36, June.
    18. Rameshwar Dubey & Angappa Gunasekaran & Stephen J. Childe & Samuel Fosso Wamba & David Roubaud & Cyril Foropon, 2021. "Empirical investigation of data analytics capability and organizational flexibility as complements to supply chain resilience," International Journal of Production Research, Taylor & Francis Journals, vol. 59(1), pages 110-128, January.
    19. Lei, Zhimei & Chen, Yandan & Lim, Ming K., 2021. "Modelling and analysis of big data platform group adoption behaviour based on social network analysis," Technology in Society, Elsevier, vol. 65(C).
    20. Côrte-Real, Nadine & Oliveira, Tiago & Ruivo, Pedro, 2017. "Assessing business value of Big Data Analytics in European firms," Journal of Business Research, Elsevier, vol. 70(C), pages 379-390.
    21. Patrick Mikalef & John Krogstie, 2020. "Examining the interplay between big data analytics and contextual factors in driving process innovation capabilities," European Journal of Information Systems, Taylor & Francis Journals, vol. 29(3), pages 260-287, May.
    22. 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.
    23. Akter, Shahriar & Bandara, Ruwan & Hani, Umme & Fosso Wamba, Samuel & Foropon, Cyril & Papadopoulos, Thanos, 2019. "Analytics-based decision-making for service systems: A qualitative study and agenda for future research," International Journal of Information Management, Elsevier, vol. 48(C), pages 85-95.
    24. Jian Jin & Ying Liu & Ping Ji & Hongguang Liu, 2016. "Understanding big consumer opinion data for market-driven product design," International Journal of Production Research, Taylor & Francis Journals, vol. 54(10), pages 3019-3041, May.
    25. El-Haddadeh, Ramzi & Osmani, Mohamad & Hindi, Nitham & Fadlalla, Adam, 2021. "Value creation for realising the sustainable development goals: Fostering organisational adoption of big data analytics," Journal of Business Research, Elsevier, vol. 131(C), pages 402-410.
    26. Ranjan, Jayanthi & Foropon, Cyril, 2021. "Big Data Analytics in Building the Competitive Intelligence of Organizations," International Journal of Information Management, Elsevier, vol. 56(C).
    27. Gruenhagen, Jan Henrik & Parker, Rachel, 2020. "Factors driving or impeding the diffusion and adoption of innovation in mining: A systematic review of the literature," Resources Policy, Elsevier, vol. 65(C).
    28. 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.
    29. Mladen Pancić & Dražen Ćućić & Hrvoje Serdarušić, 2023. "Business Intelligence (BI) in Firm Performance: Role of Big Data Analytics and Blockchain Technology," Economies, MDPI, vol. 11(3), pages 1-19, March.
    30. Li, Lei & Lin, Jiabao & Ouyang, Ye & Luo, Xin (Robert), 2022. "Evaluating the impact of big data analytics usage on the decision-making quality of organizations," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    31. Roth, Steffen & Schwede, Peter & Valentinov, Vladislav & Pérez-Valls, Miguel & Kaivo-oja, Jari, 2020. "Harnessing big data for a multifunctional theory of the firm," European Management Journal, Elsevier, vol. 38(1), pages 54-61.
    32. Ghasemaghaei, Maryam, 2020. "The role of positive and negative valence factors on the impact of bigness of data on big data analytics usage," International Journal of Information Management, Elsevier, vol. 50(C), pages 395-404.
    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. Mpho Kgakatsi & Onthatile P. Galeboe & Kopo K. Molelekwa & Bonginkosi A. Thango, 2024. "The Impact of Big Data on SME Performance: A Systematic Review," Businesses, MDPI, vol. 4(4), pages 1-64, November.

    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. Korayim, Diana & Chotia, Varun & Jain, Girish & Hassan, Sharfa & Paolone, Francesco, 2024. "How big data analytics can create competitive advantage in high-stake decision forecasting? The mediating role of organizational innovation," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
    2. 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.
    3. Anwar, Muhammad Azfar & Zong, Zupan & Mendiratta, Aparna & Yaqub, Muhammad Zafar, 2024. "Antecedents of big data analytics adoption and its impact on decision quality and environmental performance of SMEs in recycling sector," Technological Forecasting and Social Change, Elsevier, vol. 205(C).
    4. 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).
    5. 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.
    6. Alshawawreh, Ali Ra’Ed & Liébana-Cabanillas, Francisco & Blanco-Encomienda, Francisco Javier, 2024. "Impact of big data analytics on telecom companies' competitive advantage," Technology in Society, Elsevier, vol. 76(C).
    7. 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.
    8. 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).
    9. Maryia Zaitsava & Elona Marku & Maria Chiara Guardo & Azar Shahgholian, 2023. "A fine-grained perspective on big data knowledge creation: dimensions, insights, and mechanism from a pilot study," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 27(2), pages 547-573, June.
    10. Dignity Paradza & Olawande Daramola, 2021. "Business Intelligence and Business Value in Organisations: A Systematic Literature Review," Sustainability, MDPI, vol. 13(20), pages 1-27, October.
    11. Sun, Pengfei & Yuan, Chunhui & Li, Xiaolong & Di, Jia, 2024. "Big data analytics, firm risk and corporate policies: Evidence from China," Research in International Business and Finance, Elsevier, vol. 70(PB).
    12. 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).
    13. 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.
    14. 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).
    15. Tugba Karaboga & Cemal Zehir & Ekrem Tatoglu & H. Aykut Karaboga & Abderaouf Bouguerra, 2023. "Big data analytics management capability and firm performance: the mediating role of data-driven culture," Review of Managerial Science, Springer, vol. 17(8), pages 2655-2684, November.
    16. 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.
    17. Luther Yuong Qai Chong & Thien Sang Lim, 2022. "Pull and Push Factors of Data Analytics Adoption and Its Mediating Role on Operational Performance," Sustainability, MDPI, vol. 14(12), pages 1-19, June.
    18. 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.
    19. Wong, David T.W. & Ngai, Eric W.T., 2023. "The impact of advanced manufacturing technology, sensing and analytics capabilities, and planning comprehensiveness on sustained competitive advantage: The moderating role of environmental uncertainty," International Journal of Production Economics, Elsevier, vol. 265(C).
    20. Kirti Nayal & Rakesh D. Raut & Vinay Surendra Yadav & Pragati Priyadarshinee & Balkrishna E. Narkhede, 2022. "RETRACTED: The impact of sustainable development strategy on sustainable supply chain firm performance in the digital transformation era," Business Strategy and the Environment, Wiley Blackwell, vol. 31(3), pages 845-859, March.

    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:sae:sagope:v:13:y:2023:i:4:p:21582440231217902. 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: SAGE Publications (email available below). General contact details of provider: .

    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.