| With the growing participation of various stakeholders in the smart product service system,it is essential to meticulously consider and integrate the diverse experiences of these stakeholders when designing,implementing,and managing product service solutions.The prevailing approaches to smart product service design are predominantly driven by customer needs,making it challenging to enhance the experiences of various stakeholders and to facilitate the positive operation of the product service system.Therefore,based on the current researches on smart product service systems and their designing approaches,this dissertation investigates the optimization of such systems with a focus on enhancing the experiences of multiple stakeholders.The principal research endeavors and innovative highlights are detailed subsequently.(1)An optimized design framework for smart product service systems,which are centered on the experiences of multiple stakeholders,is proposed.This framework is based on the analysis of the elements,structure,and characteristics of smart product service systems tailored to multi-stakeholder experiences.By embracing AIOE as the fundamental principle of optimization,focusing on enhancing the experiences of multiple stakeholders,utilizing the key techniques such as requirement mining,component and module optimization,as well as module configuration and delivery process optimization,the framework can equip designers with both theoretical and operational guidance.(2)A method for mining and analyzing the optimized requirements for smart product services tailed to enhance multi-stakeholder experiences is proposed.To effectively identify explicit requirements from various stakeholders,this method thoroughly examines the demand elements of various stakeholders across diverse activity cycles,establishes an experience system for these stakeholders,and designs an evaluation approach for the experience system by leveraging the TOPSIS framework.To mine implicit requirements,this dissertation employs the "multiplicative decomposition-LSTM-LSTM" and the "multiplicative decomposition-ELM-KRR" decomposition and integration prediction model.Subsequently,the significance of these requirements is ranked utilizing the rough-fuzzyBWM method.(3)An optimized modular configuration method for smart product service systems is proposed.This method utilizes functional characteristic scenario diagrams to capture both product and service technical characteristics,and estimates their significance using rough grey relational analysis.Then it employs newly proposed cyber-physical product service blueprint to identify the fundamental service components within the smart product service systems.Based on three correlation criteria,such as service function,smart flow,and technical characteristic,a network depicting the co-intelligence relationships among these service components can be constructed,enabling the generation of modularization schemes through a weighted GN algorithm.Finally,a combination of rough-fuzzy DEA for product service scheme configuration optimization and TOPSIS based on rough set theory is employed to select the optimal configuration that meets technical characteristics.(4)An optimization method for pricing and delivery operations of smart product service systems is proposed.This method establishes a Stackelberg model that considers user experience preferences and market competition factors for innovative services,allowing supplier to derive optimal investment and pricing strategies in both competitive and collaborative scenarios.For optimized services,this dissertation presents a game model centered on user expected experience value,leveraging a particle swarm optimization algorithm to efficiently identify pricing solutions that maximize revenue.Additionally,a multi-stakeholder experience blueprint is constructed to illustrate the intricate activities and relationships among various stakeholders.To verify the feasibility and effectiveness of the above research results,a systematic application and analysis of the entire set of methods and techniques were conducted through a practical example of a smart fire alarm system for early fire warning.The engineering practice results showed that the research findings in this dissertation can provide theoretical guidance and references for improving the design of smart product services considering multi-stakeholder experiences,as well as refining business models.Consequently,they possess considerable engineering application value. |
