Evolutionary Game Analysis on Cloud Providers and Enterprises' Strategies for Migrating to Cloud-Native under Digital Transformation

被引:7
作者
Zhang, Rui [1 ]
Li, Yuewen [1 ]
Li, Hongyan [1 ]
Wang, Qiaosong [2 ]
机构
[1] Shanghai Univ Engn Sci, Sch Management, Shanghai 201620, Peoples R China
[2] Donghua Univ, Student Dept, Shanghai 201620, Peoples R China
关键词
cloud-native; digital transformation; evolutionary game theory; selection; knowledge spillover; empirical analysis; MICROSERVICES; STABILITY;
D O I
10.3390/electronics11101584
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cloud-native is an innovative technology and methodology that is necessary to realize the digital transformation of enterprises. Promoting the wide adoption of cloud-native in cloud providers and enterprises has gained popularity in recent years. According to the technological and commercial characteristics of cloud-native, this paper analyzes the game relationship between cloud providers and enterprises on the selection of cloud-native, and combines evolutionary game theory to establish a model. In addition, empirical analysis indicates the impact of parameter changes on the dynamic evolution process. The results show that (1) enterprises are more vulnerable to the impact of direct benefit to adopt cloud-native, and cloud providers are especially affected by the cost of providing cloud-native; (2) enterprises are more likely to be impacted by the invisible benefit than cloud providers, but the impact has a marginal decreasing effect; (3) the low price is one of the reasons to attract enterprises; (4) enterprises are more concerned about the potential loss caused by the supply and demand mismatch. The results of the discussion provide a reference for all stakeholders to promote the implementation of cloud-native and the digital transformation of enterprises.
引用
收藏
页数:22
相关论文
共 56 条
[1]   Evolutionary Game Theoretic Analysis of Advanced Persistent Threats Against Cloud Storage [J].
Abass, Ahmed A. Alabdel ;
Xiao, Liang ;
Mandayam, Narayan B. ;
Gajic, Zoran .
IEEE ACCESS, 2017, 5 :8482-8491
[2]   Cloud-Native Repositories for Big Scientific Data [J].
Abernathey, Ryan P. ;
Blackmon-Luca, Charles C. ;
Crone, Timothy J. ;
Henderson, Naomi ;
Lepore, Chiara ;
Augspurger, Tom ;
Banihirwe, Anderson ;
Gentemann, Chelle L. ;
Hamman, Joseph J. ;
Henderson, Naomi ;
Lepore, Chiara ;
McCaie, Theo A. ;
Robinson, Niall H. ;
Signell, Richard P. .
COMPUTING IN SCIENCE & ENGINEERING, 2021, 23 (02) :26-35
[3]  
[Anonymous], CLOUD NATIVE ARCHITE
[4]  
[Anonymous], LOGISTICS SOLUTION D
[5]  
[Anonymous], CHINA CONTAINER CLOU
[6]  
[Anonymous], 2020, CLOUD NATIVE DEV WHI
[7]  
[Anonymous], SOURCE COST REDUCTIO
[8]  
[Anonymous], CLOUD NATIVE 20 WHIT
[9]  
[Anonymous], CHINA CLOUD NATIVE U
[10]  
[Anonymous], CNCF CLOUD NATIVE DE