Exploring complex service design: Understanding the Diamonds of Context

Purpose – The paper aims to describe the way of mind model creation in service design. The second target is to describe how the different mind models, coming from different domains can be united and understood in situation of solving complex service with practical examples in Smart City domain. Design/Methodology/approach – The paper will show the limitations of current modeling tools. Using Service Science and System thinking we will show the main ideas of complex mind modelling and introduce the model of individual mind modelling. Following the idea of multidisciplinarity, the second part of the paper proposes how to combine different mind models with the emphasis of understanding different contexts and the shared value within (value-in-context). The proposed approaches will be validated by practical examples from the Smart City domain, and smart mobility particurarly. Findings – The paper proposes a new approach to understand complex services and provides the systematic way of how to combine the different domains to find optimal multidisciplinary solution, represented by complex service design. Research limitations/implications – The model proposed by the paper is mostly theoretically oriented and more practical approaches will be developed. We expect to obtain more insights to prove the value of the model in practice. Practical implications – The problem of understanding the opinions and problems cross more than one discipline is critical in complex service design. By establishing of common vocabulary that will be understood by all members of the team, we can avoid the issues of misunderstanding and wasting of resources. Originality/value – The paper shows practical implications of Service Dominant Logic, Service Science, as well as Network and Systems Theory by providing an effective application of methodological framework to understand complex service problems. Both theoretical and practical contributions can be used in multidisciplinary teams to understand the key problem and improve the service design