Technology as Actors in Service Systems

Service systems are defined as dynamic configurations of resources (people, organizations, technology and shared information), interconnected internally and externally by value propositions with other service systems. Resources are constantly evolving, as are the capabilities and roles of resources in service systems. Cognitive technologies incorporate rapidly advancing artificial intelligence (AI) capabilities. Therefore, their roles are on a trajectory of increasing agency and self-directed interactions with other resources and service systems. With this in mind, a framework for service systems in which AI- based cognitive assistants (CAs) become responsible actors is the current research challenge. Because AI- based CAs have already started to play different roles in service systems. One contribution of this research is to clarify that service system entities are responsible actors, and address the question: Under what conditions does a technology such as a Cognitive Assistant (CA) become a responsible actor

On the Performance Estimation and Resource Optimisation in Process Petri Nets

Many artificial systems can be modeled as discrete dynamic systems in which resources are shared among different tasks. The performance of such systems, which is usually a system requirement, heavily relies on the number and distribution of such resources. The goal of this paper is twofold: first, to design a technique to estimate the steady-state performance of a given system with shared resources, and second, to propose a heuristic strategy to distribute shared resources so that the system performance is enhanced as much as possible. The systems under consideration are assumed to be large systems, such as service-oriented architecture (SOA) systems, and modeled by a particular class of Petri nets (PNs) called process PNs. In order to avoid the state explosion problem inherent to discrete models, the proposed techniques make intensive use of linear programming (LP) problems

Distributed tuning of boundary resources: the case of Apple's iOS service system

The digital age has seen the rise of service systems involving highly distributed, heterogeneous, and resource-integrating actors whose relationships are governed by shared institutional logics, standards, and digital technology. The cocreation of service within these service systems takes place in the context of a paradoxical tension between the logic of generative and democratic innovations and the logic of infrastructural control. Boundary resources play a critical role in managing the tension as a firm that owns the infrastructure can secure its control over the service system while independent firms can participate in the service system. In this study, we explore the evolution of boundary resources. Drawing on Pickering’s (1993) and Barrett et al.’s (2012) conceptualizations of tuning, the paper seeks to forward our understanding of how heterogeneous actors engage in the tuning of boundary resources within Apple’s iOS service system. We conduct an embedded case study of Apple’s iOS service system with an in-depth analysis of 4,664 blog articles concerned with 30 boundary resources covering 6 distinct themes. Our analysis reveals that boundary resources of service systems enabled by digital technology are shaped and reshaped through distributed tuning, which involves cascading actions of accommodations and rejections of a network of heterogeneous actors and artifacts. Our study also shows the dualistic role of power in the distributed tuning process

The moderating role of utilitarian/hedonic user motivation on user behaviour towards web 2.0 applications

The paper presents and discusses the notion of service scenarios. A service is work done by a service executor in interaction with a service consumer. A service scenario is a model of a service system and the roles that are played by the actors that participate and interact during the execution of a service. The model represents the roles and the interactions between the participants. Service scenarios can be used to model specific services and the roles played by human beings and IT systems in the execution of services. The use of service scenarios is demonstrated by means of a case study in a public library. The case study indicates that service systems should be understood as socio-technical systems in which service executors and service consumers co-create value in mutual interaction with each other and with a set of shared resources

Service Innovation | A Service Blueprinting for Industry4.0

This research aims to conceptualize a service blueprinting framework to map the digital interaction and shared access to service system resources in Industry 4.0 operations. From the literature review we found that in Industry 4.0 operations, customer and provider are value co-creators, and thus, mapping the service process using such service blueprinting becomes useful to boost new dynamics generating positive and measurable innovation outcomes using either quantitative or qualitative indicators, indexed to the different stakeholders’ concerns. As recommended by the of Service Science, wealth comes from service innovation among service systems, so, it is necessary to know at the outset which resources are involved in value propositions along the service process. With this research, we have conceptualized an innovative service blueprinting framework for the digital innovation to visualize the bridge between the physical world and the virtual world in Industry 4.0 operations

Self-organising agent communities for autonomic resource management

The autonomic computing paradigm addresses the operational challenges presented by increasingly complex software systems by proposing that they be composed of many autonomous components, each responsible for the run-time reconfiguration of its own dedicated hardware and software components. Consequently, regulation of the whole software system becomes an emergent property of local adaptation and learning carried out by these autonomous system elements. Designing appropriate local adaptation policies for the components of such systems remains a major challenge. This is particularly true where the system’s scale and dynamism compromise the efficiency of a central executive and/or prevent components from pooling information to achieve a shared, accurate evidence base for their negotiations and decisions.In this paper, we investigate how a self-regulatory system response may arise spontaneously from local interactions between autonomic system elements tasked with adaptively consuming/providing computational resources or services when the demand for such resources is continually changing. We demonstrate that system performance is not maximised when all system components are able to freely share information with one another. Rather, maximum efficiency is achieved when individual components have only limited knowledge of their peers. Under these conditions, the system self-organises into appropriate community structures. By maintaining information flow at the level of communities, the system is able to remain stable enough to efficiently satisfy service demand in resource-limited environments, and thus minimise any unnecessary reconfiguration whilst remaining sufficiently adaptive to be able to reconfigure when service demand changes