A state-driven modeling approach to human interactions for knowledge intensive services

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Knowledge intensive service activities have become to play a fundamentally important role in various industrial fields. Human workers generally undertake complex operations relying heavily on professional knowledge in service processes to develop and deliver the knowledge intensive services. That means the ability of humans to create, disseminate, or utilize the knowledge is the dominant factor in the processes. Therefore, the processes should be managed in a human-oriented way. In order to help humans work together, a strong representation of processes should be provided to facilitate them to clearly understand who they should interact with, which resources are exchanged, and what activities need to be performed. Human Interaction Management (HIM) has been suggested to comprehensively support the human-oriented processes, but it cannot provide a way to structure and visualize the interaction works although the interaction is the most basic nature of human works. Therefore, this paper presents a state-driven approach to modeling human interactions which clearly visualizes the interactions so that human workers can be guided through it. However, it cannot be expected for human workers to follow the guidelines completely. They continuously and dynamically redefine their processes towards the way that they want throughout the life of the processes. To support the dynamic human work behavior, this paper also presents a hybrid modeling methodology that consists of the top-down specification of interaction models for guideline modeling and the bottom-up evolution of the models for flexible enactment. The suggested methodology for human interactions based on the state-driven modeling approach provides a way to effectively manage the complex interactions in a human-oriented way.

论文关键词:Knowledge intensive service processes,Collaborative human work,Human Interaction Management,State-driven interaction modeling,Hybrid modeling methodology,Metamodeling

论文评审过程:Available online 3 August 2010.

论文官网地址:https://doi.org/10.1016/j.eswa.2010.07.124