A Model Transformation for Increasing Value in Service Networks through Intangible Value Exchanges Daniel J. Dubois Dipartimento di Elettronica e Informazione Politecnico di Milano Milan, Italy e-mail: dubois@elet.polimi.it Christos Nikolaou, Manolis Voskakis Transformation Services Laboratory University of Crete Heraklion, Greece e-mail: {nikolau,voskakis}@tsl.gr Abstract—One of the main goals in service science is to find efficient ways to analyze and increment the value in a service network. The approach we propose in this paper is to increase the agility of the system in such a way that the network and the underlying business processes are able to spontaneously react to changes in the requirements or in the environment. This is done by making extensive use of knowledge transfer and intangible interactions among network participants. The final outcome is a transformation and analysis methodology that may be applied to a wide variety of service networks with the aim of finding possible reconfigurations for increasing customer satisfaction, reducing transaction risks, and therefore increasing the overall value of the network. Keywords-component; value networks, business process management, service networks, value analysis I. INTRODUCTION Modern business systems are becoming more complex over time since the cost and speed of storing and exchanging information is becoming lower and the number of participants is becoming higher. These systems are not only large, but they are set in an environment that is always changing both in requirements and in the number of participants. Therefore we need an intelligent way to analyze them and provide a methodology to keep or improve the value of participation into the system even in such dynamic conditions. The ability of the system to react to environmental perturbations is defined as the agility of the system. In this context we propose a methodology for transforming a business network, known also as a service network, to improve the value for their participants even if their requirements change over time or some participant acts in a way that decreases the value of the network. The two key technologies that we are exploiting are: (1) value estimation based on revenues and offerings from each participant; (2) risk reduction and transparency that emerges after making extensive use of intangible interactions and knowledge transfers. The methodology we propose has been applied in the context of a traditional car sharing company [20] and its possible transformation into a more “agile” network. The final result is that a business network designer has now a method for taking strategic decisions whether to modify its business network or not, basing his decisions on the environment/participants characteristics gathered over a certain period of time. Related work on this type of business networks, known also as service value networks, or simply service networks may be found in [15, 14, 8, 16, 5, 4, 13]. In these networks entities are either companies or different roles within a company, connections are offerings from one entity to another. These networks may be agile, in such a case agility is their level of flexibility in dealing with changing requirements [17]. In [7] we can also find a definition of value as “benefits of an agent accrued by his participation in the network minus any costs involved in setting up the network links directly and indirectly”. However there is a problem with the actual evaluation of this “amount of benefits”. The evaluation method we will base the rest of the paper is explained in [9]: in this work all the interactions are expressed as offerings and payments occurred per time unit, then the total revenues for all offerings exported by each participants are computed and used to estimate future revenues. However according to this work the total value is not simply a subtraction of revenues minus costs, but there is another value-contributing component called Satisfaction Index: it measures the perceived preference for a relationship. Other metrics for evaluating service networks are proposed in the following works: the work from Parolini [15] describes a methodology called “Value NET” for taking strategic decisions on the service network by doing a qualitative analysis over it to identify bottlenecks, dominant relationships, and to predict the effects of possible structure/relationship modifications; in Allee works [1,2,3,4] there are other metrics related to the structure of the network such as stability and risk, she also points out an analysis methodology that focuses on the intangible exchanges from the network; additional works that try to understand and evaluate the value of services networks may be found in [19,5,8,18]. Our way for evaluating value takes some inspiration from all the works above, especially [9,1] since structure is not stable in an agile dynamic network, therefore we will focus on the measurement on actual revenues, costs, and satisfaction of each participant of the network. Another concept that this work relates to is the concept of business ecosystem coordination mechanism [12], in which business networks are kept together by so-called