Faccia, Alessio and Pandey, Vishal (2022) Business planning and big data, budget modelling upgrade through data science. In: 6th International conference on information systems engineering, November 12-14, 2021, Shanghai, China.
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Abstract
The business planning process can be considered a strategic phase of any business. Since the business plan is a management accounting tool, countless approaches can be adopted to prepare it since there is no legal requirement other than financial accounting obligations. A general structure usually consists of numerical statements and descriptive notes. This research is based on the authors’ experiences and commonly used theories, and it highlights a standard process that can be adaptable to the business plan of any activity. The use of big data is an essential part of feeding the data of almost all Budget steps. The authors then determine a generally applicable standard process, indicating all the data necessary to prepare an accurate and reliable business plan. A case study will provide adequate support to the demonstration of the immediate applicability of the proposed model.
Item Type: | Conference or Workshop Item (Paper) |
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Keywords: | Big data | Business plan | Budgeting | Business strategy |
Subjects: | Social Sciences and humanities > Business, Management and Accounting > Business and International Management Social Sciences and humanities > Business, Management and Accounting > Management of Technology and Innovation |
JGU School/Centre: | Jindal Global Business School |
Depositing User: | Mr. Syed Anas |
Date Deposited: | 18 Mar 2022 16:50 |
Last Modified: | 24 Jun 2022 06:13 |
Official URL: | https://doi.org/10.1145/3503928.3503933 |
Additional Information: | The contribution of the authors in this research can be distributed as follows: Alessio Faccia [41-49] came across the main idea of the standardised/flexible budgeting path; therefore, he focused on the introduction, findings and conclusions; Vishal Pandey focused his research on the literature review. |
URI: | https://pure.jgu.edu.in/id/eprint/1744 |
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