The aim of this study is to explore the dynamics and impediments in exploring the digital transformation process of energy enterprises, considering industry competition and government involvement. Compared with other industries, energy enterprises have both economic tasks and social responsibilities at the same time, while their business modes have certain “inertia”. Therefore, the process of their digital transformation cannot avoid the balance of interests between the different agents. From the perspective of competition and cooperation in the sector, this study constructs a tripartite evolutionary game model among the government and energy enterprises, analyzes the evolutionary stable strategies of the game system, and simulates different initial intentions and key parameters for all roles. The results show that in the process of digital transformation, the symbiotic relationship between energy enterprises and the cooperative relationship between enterprises and government can be embodied, and the effective game process has sufficient economic guidance. The government plays the guiding role in the digital transformation of energy enterprises, and its initial intention has a significantly stronger impact than the energy enterprise’s intentions. The effective strategy reflects the principle of “waiting for an opportunity to act, giving priority to efficiency, and giving consideration to justice”. Under the given policy environment, energy enterprises with comparative advantages in terms of transformation costs, direct benefits and synergy will become the leading role that is more sensitive to the opportunities of digital transformation, and the following energy enterprise will adjust its own strategies in time according to the effect of the leading role’s digital transformation so as to achieve the stability of the system. Accordingly, this study can provide reference support for energy enterprises to develop digital transformation strategies and for governments to formulate reasonable and effective policies.
Read full abstract