ItemConference Paper

Analyzing Technology Ecosystem Business Models: A Predictive Modelling Approach

Title
Analyzing Technology Ecosystem Business Models: A Predictive Modelling Approach
Creator
Chebbi, Nandan Shrinivas; Mahashabde, Roshan Balaji; Shrinivas, Bharath Masthi; Makam, Prashasth Kishore; Kumar, Sandeep; Kiran, V.
Description
In the rapidly changing landscape of technology, companies are devoting an increasing amount of their resources to developing product ecosystems that collaborate to deliver enhanced consumer experiences and strengthen their business models. As opposed to traditional standalone solutions, these ecosystems are intended to facilitate everyday tasks, increase user engagement, and provide seamless integration, all of which ensure a steady stream of revenue and dedicated customer base. This analysis provides an overview of the many ecosystem models that are now transforming the technology industry. An examination of ecosystems that help businesses maintain long-term revenue sustainability and high customer retention rates is provided by the model analysis, along with insights into how ecosystems may enhance user experience by being more connected, straightforward, and user-friendly. Technology ecosystems' quantitative effects are lacking, which makes it difficult to comprehend how they affect long-term revenue sustainability and customer retention. It is challenging to understand how technological ecosystems impact long-term revenue sustainability and customer retention due to the lack of measurable consequences. Through the use of multiple linear regression, this study illustrates the ecosystem business models' long-term revenue and customer retention. The study visualized the relationships of the technology ecosystem with an accuracy of 90-99%. This shows how to measure ecosystem impact and gives firms data-driven insights to improve their ecosystem initiatives. 2025 IEEE.
Source
Proceedings of 2025 IEEE International Conference on Contemporary Computing and Communications, InC4 2025;
Date
01-01-2025
Publisher
Institute of Electrical and Electronics Engineers Inc.
Subject
Customer Retention; Ecosystem Business Models; Machine Learning; Predictive Modeling
Coverage
Chebbi N.S., RV College of Engineering, Department of ECE, Bengaluru, India; Mahashabde R.B., RV College of Engineering, Department of ECE, Bengaluru, India; Shrinivas B.M., RV College of Engineering, Department of ECE, Bengaluru, India; Makam P.K., RV College of Engineering, Department of ECE, Bengaluru, India; Kumar S., Christ University, Department of AI, ML and DS, Bengaluru, India; Kiran V., RV College of Engineering, Department of ECE, Bengaluru, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISBN: 979-833152118-9;
Format
online
Language
English
Type
Conference paper

Citation

Chebbi, Nandan Shrinivas; Mahashabde, Roshan Balaji; Shrinivas, Bharath Masthi; Makam, Prashasth Kishore; Kumar, Sandeep; Kiran, V., “Analyzing Technology Ecosystem Business Models: A Predictive Modelling Approach,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 19, 2026, https://archives.christuniversity.in/items/show/26166.

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