Document Type : Research Paper
Authors
1 Professor, Department of Business Administration, Payam Noor University, Tehran, IranM_azami@pnu.ac.ir Corresponding Author: Assistant
2 Department of Business Management, Abadan branch, Islamic Azad University, Abadan, Iran
3 Department of Business management, Qom Branch, Islamic Azad University, Qom, Iran
Abstract
Waterfall failures are one of the most important challenges and risks of this modern type of business, which can cause damage to other parts of the system in a chain manner and lead to the collapse of the entire system. The aim of this research is to investigate various factors related to waterfall failures in cloud business models and to introduce appropriate approaches for predicting, preventing and managing these types of failures. In this research, the literature review method using natural language processing was used to collect information and analyze the topic. The sources used included scientific articles in the field of information technology and business from 2015 to 2024 from IEEE Xplore, Google Scholar, and arXiv datasets, of which 23 articles were analyzed with natural language processing methods. The use of advanced NLP techniques allows for a more accurate assessment and deeper analysis of the factors associated with cascading failures. Also, rooting for errors and developing a practical roadmap for their better management allows businesses to facilitate improvement and productivity in their cloud environment and take a more sustainable path. These steps not only help to increase the quality and efficiency of cloud services, but also greatly reduce the costs and time required to fix problems. Various factors related to waterfall failures in cloud business models have been investigated in detail. These factors include technical problems, management problems and marketing problems. Also, different approaches have been introduced to predict, prevent and manage these types of failures.
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