Research on Bayesian Network Decision-Making of Chinese Real Estate Enterprises Technology-Driven Business Model Innovation under the Background of Smart City

With the gradual advancing of the construction of smart city, the new generation of information technology represented by the Internet of Things, Big Data, Mobile Internet, etc. has caused a strong impact on the existing business model of Chinese Real Estate enterprises. In this situation, how to choose the right business model innovation（BMI）strategy has become very important. Because the uncertainty of BMI decision-making scenarios and the complexity of decision-making data sources, most of the BMI decision-making methods proposed in previous literature are qualitative decision-making methods based on expert subjective knowledge. In order to fill in the gaps and improve the effectiveness of technology-driven BMI in the background of smart cities, this study uses Bayesian network mathematical tools to construct a decision-making model suitable for technology-driven BMI of enterprises, and to achieve computer-aided adaptive decision-making for BMI. Firstly, this paper identifies the types of BMI strategies of Real Estate enterprises under the background of smart city and the key factors affecting the choice of BMI strategies. Then, using the data of 86 Real Estate enterprises to train network parameters, a complete Bayesian network decision model is formed. Finally, the feasibility and validity of this method are verified by an example of Longfor Real Estate BMI. This paper can theoretically enrich and expand the relevant research on BMI and smart city, and can assist managers in BMI strategy decision-making, in order to achieve the purpose of improving the innovation effect of technology-driven business model in the background of smart city