Challenges And Opportunities In The Implementation Of Big Data Analytics In Management Information Systems In Bangladesh
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DOI: 10.26480/aim.02.2023.122.130
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- 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.
- Bag, Surajit & Dhamija, Pavitra & Singh, Rajesh Kumar & Rahman, Muhammad Sabbir & Sreedharan, V. Raja, 2023. "Big data analytics and artificial intelligence technologies based collaborative platform empowering absorptive capacity in health care supply chain: An empirical study," Journal of Business Research, Elsevier, vol. 154(C).
- Prashant Jain & Dhanraj P. Tambuskar & Vaibhav S. Narwane, 2023. "Is the Implementation of Big Data Analytics in Sustainable Supply Chain Really a Challenge? The Context of the Indian Manufacturing Sector," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 20(05), pages 1-39, August.
- Ágnes Szukits, 2022. "The illusion of data-driven decision making – The mediating effect of digital orientation and controllers’ added value in explaining organizational implications of advanced analytics," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 33(3), pages 403-446, September.
- Amirhossein Dehkhodaei & Bahar Amiri & Hasan Farsijani & Abbas Raad, 2023. "Barriers to big data analytics (BDA) implementation in manufacturing supply chains," Journal of Management Analytics, Taylor & Francis Journals, vol. 10(1), pages 191-222, January.
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Academic libraries; digital evolution; open access; technological challenges; knowledge dissemination.;All these keywords.
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