Abstract
Industry 4.0 is characterized by the key role of new technologies in the development of relationships between companies and their stakeholders. Thus, the most recent theories on service redefine organizations as complex service systems that create and co-create value thanks to the interactions between actors, enhanced by smart technologies and ICTs. 
 
 In particular, the concept of service systems- introduced in Service Science- seems to be suitable for the exploration of how service design, and the processes of innovation sharing and emergence, can be strengthened thanks to the application of smart technologies. 
 
 Despite the adoption of a system logic, service systems, and their conceptualization, need to be reinterpreted according to a perspective that applies a total and all-encompassing view to the processes of value generation and to the interpretation of the information and data exchanged (data-driven decision-making).
 
 Therefore, the study proposes a conceptual model that integrates the key enabling factors of value co-creation in service systems with the main strategic drivers introduced in data-driven approach to redefine the entire service experience as a service journey. In this continuous information flow, providers, customers and users share and combine data streams, to be turned into relevant information and value, through an integrated and interacting set of touch points that connect the different stages of service creation, delivery and co-creation.
Highlights
In today’s interconnected world, the huge amount of data available to companies, at an increasingly rapid pace, unimaginable until a few years ago, reshapes inevitably the social and economic configuration of markets, by determining the transition to the so-called industry 4.0 (Kagermann, Lukas, & Wahlster, 2011)
That allows resources combination, can result in increased skills of the people involved in the process, by enabling continuous collection of data and by transforming the data into information; 4) the computation of information, carried out by means of an integrated set of analytics, is supervised by decision-makers through process management and optimization that facilitate the transformation of information into knowledge and encourage the emergence of data-based value co-creation; 5) the value, generated from the synergistic knowledge exchanges, is stored within the organization, and “accumulated” as new value and knowledge useful for the stimulation of continuous improvement
Starting from the application of data-driven orientation to service systems, in line with the steps of Big Data lifecycle (Lemon & Verhoef, 2016), which defines the procedural stages for data utilization, it is possible to reinterpret the diverse phases of the service journey as complex processes of data research, integration, collection, selection, analysis, interpretation, storage and reuse
Summary
In today’s interconnected world, the huge amount of data available to companies, at an increasingly rapid pace, unimaginable until a few years ago, reshapes inevitably the social and economic configuration of markets, by determining the transition to the so-called industry 4.0 (Kagermann, Lukas, & Wahlster, 2011). If on the one hand the multiplication of the points of contact and interaction between organizations and their stakeholders, the so-called touchpoints, seems to offer an immeasurable benefit, on the other hand there is still the need to shed light on the way in which data flows can be optimized In this way, the potentiality of smart technologies and ICTs (information and communication technologies) can be exploited fully by preventing the risk of transforming technological opportunities into threats (Gandomi & Haider, 2015). The study aims at reinterpreting contemporary complex organizations as smart service systems according to a data-driven perspective that can permit to explore: 1) how ICTs can act as enablers of value and potential innovation; 2) how to optimize and manage strategically data, information and value through the multiple technological channels connecting users and providers. The classification of the main dimensions of smart service systems (see paragraph 2) and DDDM (see paragraph 3) derives from a critical re-elaboration of extant studies on Service Science and on information management and business decisions
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
