Các nhân tố ảnh hưởng đến việc áp dụng phân tích dữ liệu lớn: Nghiên cứu tại Việt Nam
Từ khóa:
Dữ liệu lớn, doanh nghiệp, tiến bộ công nghệ, Việt NamTóm tắt
Phân tích dữ liệu lớn không chỉ giúp cải thiện hiệu suất và ra quyết định mà còn cung cấp các cơ hội mới để đổi mới và phát triển. Trong bối cảnh ngày càng có nhiều dữ liệu được tạo ra và thu thập, khả năng phân tích và tận dụng dữ liệu lớn sẽ trở nên ngày càng quan trọng. Nghiên cứu này được thực hiện nhằm xác định mức độ ảnh hưởng của các yếu tố đến việc áp dụng phân tích dữ liệu lớn trong các doanh nghiệp tại Việt Nam. Phân tích định lượng được thực hiện trên dữ liệu khảo sát gồm 330 công ty tại Việt Nam. Kết quả chỉ ra rằng, lợi thế tương đối, cơ sở hạ tầng công nghệ, khả năng hấp thụ thông tin, cạnh tranh trong ngành và sự hỗ trợ của các cơ quan nhà nước ảnh hưởng đến mức độ áp dụng phân tích dữ liệu lớn. Từ đó, nhóm tác giả đề xuất một số khuyến nghị nhằm tăng cường áp dụng phân tích dữ liệu lớn vào các doanh nghiệp.
Tài liệu tham khảo
Addo-Tenkorang, R., & Helo, P.T. (2016), ‘Big data applications in operations/supply-chain management: A literature review’, Computers & Industrial Engineering, 101, 528-543, DOI: https://doi.org/10.1016/j.cie.2016.09.023.
Agrawal, K. (2015), ‘Investigating the determinants of Big Data Analytics (BDA) adoption in Asian emerging economies’, Academy of Management Proceedings, 2015(1), 11290-11290, DOI: 10.5465/AMBPP.2015.11290abstract.
Almoqren, N., & Altayar, M. (2016), ‘The motivations for big data mining technologies adoption in Saudi banks’, In 2016 4th Saudi International Conference on Information Technology (Big Data Analysis) (KACSTIT), 1-8, DOI: 10.1109/KACSTIT.2016.7756075.
Anuradha, J. (2015), ‘A brief introduction on Big Data 5Vs characteristics and Hadoop technology’, Procedia Computer Science, 48, 319-324, DOI: https://doi.org/10.1016/j.procs.2015.04.188.
Attaran, M., Stark, J., & Stotler, D. (2018), ‘Opportunities and challenges for big data analytics in US higher education: A conceptual model for implementation’, Industry and Higher Education, 32(3), 169-182, DOI: https://doi.org/10.1177/095042221877.
Chen, J., Chen, Y., Du, X., Li, C., Lu, J., Zhao, S., & Zhou, X. (2013), ‘Big data challenge: a data management perspective’, Frontiers of Computer Science, 7, 157-164, DOI: 10.1007/s11704-013-3903-7.
Dang-Pham, Duy & Nkhoma, Mathews (2013), ‘Contributing Factors of Cloud Computing Adoption: a Technology-Organisation-Environment Framework Approach’, International Journal of Information Systems and Engineering, 1, 38-49, DOI: 10.24924/ijise/2013.04/v1.iss1/30.41.
Erind, H. (2015), ‘The technological, organizational and environmental framework of IS innovation adaption in small and medium enterprises. Evidence from research over the last 10 years’, International Journal of Business and Management, 3(4), 1-14.
Fan, J., Han, F., & Liu, H. (2014), ‘Challenges of big data analysis’, National Science Review, 1(2), 293-314, DOI: https://doi.org/10.1093/nsr/nwt032.
Francisco, K., & Swanson, D. (2018), ‘The supply chain has no clothes: Technology adoption of blockchain for supply chain transparency’, Logistics, 2(1), 2, DOI: https://doi.org/10.3390/logistics2010002.
Gandomi, A., & Haider, M. (2015), ‘Beyond the hype: Big data concepts, methods, and analytics’, International Journal of Information Management, 35(2), 137-144, DOI: https://doi.org/10.1016/j.ijinfomgt.2014.10.007.
Ghobakhloo, M., Arias‐Aranda, D., & Benitez‐Amado, J. (2011), ‘Adoption of e‐commerce applications in SMEs’, Industrial Management & Data Systems, 111(8), 1238-1269, DOI: https://doi.org/10.1108/02635571111170785.
Gobble, M.M. (2013), ‘Big data: The next big thing in innovation’, Research-Technology Management, 56(1), 64-67, DOI: https://doi.org/10.5437/08956308X5601005.
Govindan, K., Cheng, T.E., Mishra, N., & Shukla, N. (2018), ‘Big data analytics and application for logistics and supply chain management’, Transportation Research Part E: Logistics and Transportation Review, 114, 343-349, DOI: https://doi.org/10.1016/j.tre.2018.03.011.
Gunasekaran, A., Yusuf, Y.Y., Adeleye, E.O., & Papadopoulos, T. (2018), ‘Agile manufacturing practices: the role of big data and business analytics with multiple case studies’, International Journal of Production Research, 56(1-2), 385-397, DOI: https://doi.org/10.1080/00207543.2017.1395488.
Gupta, M., & George, J.F. (2016), ‘Toward the development of a big data analytics capability’, Information & Management, 53(8), 1049-1064, DOI: https://doi.org/10.1016/j.im.2016.07.004.
Hurwitz, J.S., Nugent, A., Halper, F., & Kaufman, M. (2013), Big data for dummies, John Wiley & Sons.
Kauffman, R.J., Srivastava, J., & Vayghan, J. (2012), ‘Business and data analytics: New innovations in the management of e-commerce’, Electronic Commerce Research and Applications, 11(2), 85-88, DOI: http://doi.org/10.1016/j.elerap.2012.01.001.
Kumar, A., & Kumar, T.V. (2015), ‘Big data and analytics: issues, challenges, and opportunities’, International Journal of Data Science, 1(2), 118-138, DOI: https://doi.org/10.1504/IJDS.2015.072412.
Ling, E.K., & Wahab, S.N. (2020), ‘Integrity of food supply chain: going beyond food safety and food quality’, International Journal of Productivity and Quality Management, 29(2), 216-232, DOI: https://doi.org/10.1504/IJPQM.2020.105963.
Neaga, I., Liu, S., Xu, L., Chen, H., & Hao, Y. (2015), ‘Cloud enabled big data business platform for logistics services: A research and development agenda’, Paper presented at the Decision Support Systems V–Big Data Analytics for Decision Making: First International Conference, ICDSST 2015, Belgrade, Serbia, May 27-29, 2015, Proceedings 1, DOI: 10.1007/978-3-319-18533-0_3.
Park, J.-H., Kim, M.-K., & Paik, J.-H. (2015), ‘The factors of technology, organization and environment influencing the adoption and usage of big data in Korean firms’, In 26th European Regional ITS Conference, Madrid 2015 (No. 127173), International Telecommunications Society (ITS), https://www.econstor.eu/bitstream/10419/127173.
Raut, R.D., Mangla, S.K., Narwane, V.S., Gardas, B.B., Priyadarshinee, P., & Narkhede, B.E. (2019), ‘Linking big data analytics and operational sustainability practices for sustainable business management’, Journal of Cleaner Production, 224, 10-24, DOI: https://doi.org/10.1016/j.jclepro.2019.03.181.
Sangari, M.S., & Razmi, J. (2015), ‘Business intelligence competence, agile capabilities, and agile performance in supply chain: An empirical study’, The International Journal of Logistics Management, 26(2), 356-380, DOI: https://doi.org/10.1108/IJLM-01-2013-0012.
Sivarajah, U., Kamal, M.M., Irani, Z., & Weerakkody, V. (2017), ‘Critical analysis of Big Data challenges and analytical methods’, Journal of Business Research, 70, 263-286, DOI: https://doi.org/10.1016/j.jbusres.2016.08.001.
Tan, K.H., Zhan, Y., Ji, G., Ye, F., & Chang, C. (2015), ‘Harvesting big data to enhance supply chain innovation capabilities: An analytic infrastructure based on deduction graph’, International Journal of Production Economics, 165, 223-233, DOI: https://doi.org/10.1016/j.ijpe.2014.12.034.
Van der Meulen, R., & Woods, V. (2015), ‘Gartner survey shows more than 75 percent of companies are investing or planning to invest in big data in the next two years’, Gartner, retrieved on Feb 10th 2025, from <https://www.gartner.com/en/newsroom/press-releases/2014-09-17-gartner-survey-reveals-that-73-percent-of-organizations-have-invested-or-plan-to-invest-in-big-data-in-the-next-two-years>.
Wahab, S., Olugu, E., Lee, W., & Tan, S. (2018), ‘Big data analytics adoption in Malaysia warehousing industry’, In The 32nd International Business Information Management Association Conference, IBIMA 2018, 2349-2365, DOI: https://doi.org/10.1016/j.jbusres.2016.08.009.
Wahab, S.N., Hamzah, M.I., Sayuti, N.M., Lee, W.C., & Tan, S.Y. (2021), ‘Big data analytics adoption: an empirical study in the Malaysian warehousing sector’, International Journal of Logistics Systems and Management, 40(1), 121-144, DOI: https://doi.org/10.1504/IJLSM.2021.117703.
Wang, G., Gunasekaran, A., Ngai, E.W., & Papadopoulos, T. (2016), ‘Big data analytics in logistics and supply chain management: Certain investigations for research and applications’, International Journal of Production Economics, 176, 98-110, DOI: https://doi.org/10.1016/j.ijpe.2016.03.014.
Williamson, J. (2014), Getting a big data job for dummies, John Wiley & Sons.
Zhang, Y., Ren, S., Liu, Y., & Si, S. (2017), ‘A big data analytics architecture for cleaner manufacturing and maintenance processes of complex products’, Journal of Cleaner Production, 142, 626-641, DOI: https://doi.org/10.1016/j.jclepro.2016.07.123.
