Complexity analysis of manufacturing service ecosystem: a mapping-based computational experiment approach

Abstract

The trend of servitisation is increasingly affecting manufacturing enterprises. Traditional manufacturing enterprises cannot handle the related challenges of service innovation by themselves. Recently, manufacturing service ecosystem (MSE) has been proposed to support service innovation by facilitating collaboration. The construction and development of MSE need to handle a series of complexities, such as individual complexity, interaction complexity and ecological complexity. However, it is still very difficult to clearly identify the possible effect of various influence factors on MSE evolution, which is necessary analyse the complex dynamic interactive relationship among participants, so as to maintain the sustainable and healthy development of MSE. To change such a situation, this paper proposes a mapping-based computational experiment approach to analyse the evolution of MSE. This approach has three main parts, i.e. model construction of real world, model mapping of computational system and experiment evaluation of various factors of MSE evolution. By adopting the proposed approach, several case studies are conducted to investigate the possible effect of cooperation preference on the MSE evolution in various market environments. The results demonstrate that the proposed approach is effective.

Keywords:

• manufacturing service ecosystem (MSE)
• model mapping
• competition and cooperation
• computational experiment
• ecosystem evolution

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant number 61175066], [grant number 61379126], [grant number 41701133]; Program for Science＆Technology Innovation Talents of Henan Province [grant number 2017JQ0008]; Program for Science＆Technology Innovation Talents in Universities of Henan Province [grant number 2012HASTIT013]; National Natural Science Foundation of Henan Province [grant number 162300410121]; and Key Scientific Research Project in Universities of Henan Province [grant number 16A520012].