Community-Based Service Ecosystem Evolution Analysis

TL;DR

This paper introduces a method to analyze the evolution of service ecosystems from a business perspective by predicting community changes and providing actionable insights for service providers.

Contribution

It presents a novel community evolution prediction model and explains how various factors influence service ecosystem dynamics from a business-oriented view.

Findings

Model accurately predicts service community evolution patterns

Provides interpretable insights for business decision-making

Open source data and code support reproducibility

Abstract

The prosperity of services and the frequent interaction between services contribute to the formation of the service ecosystem. Service ecosystem is a complex dynamic system with continuous evolution. Service providers voluntarily or compulsorily participate in this evolutionary process and face great opportunities and challenges. Existing studies on service ecosystem evolution are more about facilitating programmers to use services and have achieved remarkable results. However, the exploration of service ecosystem evolution from the business level is still insufficient. To make up this deficiency, in this paper, we present a method for analyzing service ecosystem evolution patterns from the perspective of the service community. Firstly, we train a service community evolution prediction model based on the community evolution sequences. Secondly, we explain the prediction model, showing how different factors affect the evolution of the service community. Finally, using the interpretable predictions and prior knowledge, we present how to assist service providers in making business decisions. Experiments on real-world data show that this work can indeed provide business-level insights into service ecosystem evolution. Additionally, all the data and well-documented code used in this paper have been fully open source.