Service Innovation and Quality Assessment of Industry 4.0 Microservice through Data Modeling and System Simulation Evaluation Approaches

Abstract

This study proposes a system construction approach under Industry 4.0 infrastructure that is validated by the proposed framework of microservice quality assessment with framework with data modeling and simulation methodology to achieve innovation and value cocreation goals. The framework, which combines a dynamic process flow with service-dominant logic design and reliability assessment using a multilayer perceptron (MLP) prediction model can assist decision makers in optimizing their service innovation and decision-making processes. The service innovation and evaluation approaches have implications for optimizing the corporation cooperation. The corporation can form a much more comprehensive manufacturing infrastructure or system by considering the requirements and assessment results of third parties. To help the corporation redefine its value proposition and system structure, we must examine the system interaction between different hierarchical layers within the Industry 4.0 system infrastructure. This study used a production dataset from the NASDAQ-listed electronics corporation and two top German and Japanese automobile firms. The proposed system framework had already been validated and introduced to improve 12% of service quality. The system integrated with anticipated functions will accelerate service innovation and optimization by combining MLP and Kaplan–Meier estimation methodologies by extracting the characteristics of realistic datasets.

Impact of process and outcome quality on intention for continued use of voice assistants

“…Evaluating VAs requires understanding their responsiveness in both aspects. Outcome quality gauges user satisfaction, influencing positive word-of-mouth, while service quality impacts perceived usefulness (Wen and Chen, 2022). However, VAs' usefulness also depends on process quality, reflecting interaction effectiveness.…”