Abstract:

Manufacturing enterprises can provide better solutions for customers and gain global competitive advantages through servitization transformation. The rapid development of big data technology has provided the source power for the transformation of data-driven manufacturing industries into services. It is of great significance to study how to use online comments and other Internet information to mine customer potential demand， and put forward a series of methods to transform customer demand into multi-value chain collaborative innovation solutions， so as to solve the problem of integrating customer demand into multi-value chain collaborative innovation solutions for manufacturing enterprises. Taking manufacturing enterprises as the research object， a multi-value chain collaborative innovation management method is proposed oriented to the construction of data space system. Python web crawler is used to collect user comment information， and customer demand topics are identified from user comments based on Latent Dirichlet Allocation （LDA） model. Secondly， by referring to the idea of quality function deployment （QFD）， the identified requirements would be transformed into innovation elements by using the probabilistic semantic term set （PLTS） and then the importance is ranked. Then， a three-layer coupled innovation scheme generation Method called “chain-dimension-method” （CDM） is proposed. From the perspective of multi-value Chain， the dimension of innovation elements is divided by using multidimensional technology innovation map technology， and a series of alternative innovation schemes are generated by coupling with multiple innovation rules. Based on the research results， the data space system of manufacturing servitization is constructed. Finally， taking an electric power equipment manufacturing enterprise as an example， 10，445 user comment data of Tmall e-commerce platform are crawled and the multi-value chain collaborative innovation management method proposed in this paper is used to verify the effectiveness of the proposed data space system. The research results show that the construction of the manufacturing servitization data space system can help enterprises optimize multi-value chain collaborative innovation management decisions.

Key words: data space, multi value chain collaboration, manufacturing servitization, customer demand, innovative management method