Tech-Business Analytics in Primary Industry Sector
-
Published:2023-06-30
Issue:
Volume:
Page:381-413
-
ISSN:2581-6942
-
Container-title:International Journal of Case Studies in Business, IT, and Education
-
language:en
-
Short-container-title:IJCSBE
Author:
Kumar Sachin1, K. Krishna Prasad2, Aithal P. S.3
Affiliation:
1. Post-Doctoral Research Fellow, Institute of Computer Science and Information Science, Srinivas University, Mangalore, India 2. Institute of Computer & Information Science, Srinivas University, Mangalore, India 3. Institute of Business Management & Commerce, Srinivas University, Mangalore, India
Abstract
Purpose: The TBA in the primary industry sector is to organize the efficiency and sustainability of agricultural extraction activities. The primary sector is heavily reliant on natural resources and environmental conditions, and TBA can help businesses in this sector make data-driven decisions to optimize their operations and reduce their environmental impact. For example, TBA can help agricultural businesses optimize their crop yields by analysing data from weather sensors, soil sensors, and other sources. By using predictive analytics, businesses can anticipate weather patterns and adjust their planting schedules and crop management practices accordingly. This can lead to higher crop yields, improved resource utilization, and reduced environmental impact. Similarly, TBA can help natural resource extraction businesses optimize their operations by analysing data from sensors, drones, and other sources. By using advanced analytics techniques, businesses can identify opportunities to improve resource utilization, reduce waste, and minimize the impact of their activities on the environment. Hence, the primary industry sector faces many challenges, including climate change, resource depletion, and environmental degradation. By using TBA, businesses in this sector can make data-driven decisions to improve their operations, reduce their environmental impact, and ensure the long-term sustainability of their activities. Design/Methodology/Approach: The TBA in primary industry sector involves a combination of data collection, analysis, and interpretation techniques. The specific methodology used will depend on the industry and the specific business objectives. Hence, the TBA methodology for the primary industry sector is focused on using data-driven insights to improve efficiency, productivity, and sustainability. By collecting and analysing data from various sources, businesses in this sector can make informed decisions that lead to improved outcomes for both the business and the environment. Findings/Result: It is discussed in the paper how Tech Business Analytics in the Primary industry sector will have managed the growth itself from its evolution to till date. Originality/Value: An explanation of how Tech Business Analytics in the Primary industry sector differs from business analytics. A generic architecture is also available, which looks at 30 recently presented TBA in Primary industry sector research proposals and is useful for technical purposes. Paper Type: Exploratory research.
Publisher
Srinivas University
Reference91 articles.
1. Kumar, S., Krishna Prasad, K., & Aithal, P. S., (2022). Technology for Better Business in Society. International Journal of Philosophy and Languages (IJPL), 1(1), 117-144. 2. Kumar, S., Krishna Prasad, K., & Aithal, P. S., (2023). Tech-Business Analytics – a Review-based New Model to Improve the Performances of Various Industry Sectors. International Journal of Applied Engineering and Management Letters (IJAEML), 7(1), 67-91. 3. Kumar, S., Krishna Prasad, K., & Aithal, P. S., (2023). Tech-Business Analytics – a New Proposal to Improve Features and Quality of Products and Services in Various Industry Sectors – An Explorative Study. International Journal of Management, Technology, and Social Sciences (IJMTS), 8(2), 53-70. 4. Yiu, L. D., Yeung, A. C., & Jong, A. P. (2020). Business intelligence systems and operational capability: an empirical analysis of high-tech sectors. Industrial Management & Data Systems, 120(6), 1195-1215. 5. Bravo, C., Saputelli, L., Rivas, F., Pérez, A. G., Nikolaou, M., Zangl, G., ... & Nunez, G. (2014). State of the art of artificial intelligence and predictive analytics in the E&P industry: a technology survey. Spe Journal, 19(04), 547-563.
Cited by
31 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. INFLUENCE OF PRODUCTION OF PRIMARY PRODUCTS ON THE RATE OF INFLATION IN THE REPUBLIC OF SERBIA;Ekonomika poljoprivrede;2024-06-19 2. Tech-Business Analytics in the Circular Economy;International Journal of Management, Technology, and Social Sciences;2024-05-30 3. Tech-Business Analytics in Blue Economy;International Journal of Applied Engineering and Management Letters;2024-05-16 4. Big Data Management and Analytics in Drug Research;Advances in Healthcare Information Systems and Administration;2024-04-22 5. Exploring Neuro Management: Bridging Science and Leadership – An Overview;International Journal of Applied Engineering and Management Letters;2024-04-12
|
|