Tobias Conte

Cluster Analysis of Smart Metering Data

The introduction of smart meter technology is a great challenge for the German energy industry. It requires not only large investments in the communication and metering infrastructure, but also a redesign of traditional business processes. The newly incurring costs cannot be fully passed on to the end customers. One option to counterbalance these expenses is to exploit the newly generated smart metering data for the creation of new services and improved processes. For instance, performing a cluster analysis of smart metering data focused on the customers’ time-based consumption behavior allows for a detailed customer segmentation. In the article we present a cluster analysis performed on real-world consumption data from a smart meter project conducted by a German regional utilities company. We show how to integrate a cluster analysis approach into a business intelligence environment and evaluate this artifact as defined by design science. We discuss the results of the cluster analysis and highlight options to apply them to segment-specific tariff design.

A multidimensional procurement auction for trading composite services

Recently, static value chains have gradually been giving way to highly agile service value networks. This involves novel economic and organizational challenges. Added value for customers is created by feasible compositions of distributed service components. This work focuses on the design of a multidimensional procurement auction for trading service compositions and the analysis of strategies for service providers that participate in the procurement process. The mechanism implementation is incentive-compatible, so that it results in an equilibrium in which revealing the true multidimensional type (quality of service and valuation) is a weakly-dominant strategy for all service providers. Due to combinatorial restrictions imposed by the underlying graph topology, the winner determination problem can be solved in polynomial time, in contrast to computationally-intractable combinatorial auctions which cannot be solved this way. Furthermore, we provide a simulation-based analysis based on a reinforcement learning model of bundling and unbundling strategies of service providers that participate in the auction. Based on our results we discuss strategic recommendations for service providers depending on how they are situated within the network.

How to Coordinate Value Generation in Service Networks

The fundamental paradigm shift from traditional value chains to agile service value networks implies new economic and organizational challenges. As coordination mechanisms, auctions have proven to perform quite well in situations where intangible and heterogeneous goods are traded. Nevertheless, traditional approaches in the area of multidimensional combinatorial auctions are not quite suitable to enable the trade of composite services. A flawless service execution and therefore the requester’s valuation highly depends on the accurate sequence of the functional parts of the composition, meaning that in contrary to service bundles, composite services only generate value through a valid order of their components. The authors present an abstract model as a formalization of service value networks. The model comprehends a graph-based mechanism implementation to allocate multidimensional service offers within the network, to impose penalties for non-performance and to determine prices for complex services. The mechanism and the bidding language support various types of QoS attributes and their (semantic) aggregation. It is analytically shown that this variant is incentive compatible with respect to all dimensions of the service offer (quality and price). Based on these results, the authors numerically analyze strategic behavior of participating service providers regarding possible collusion strategies.

Service Value Networks: Unleashing the Combinatorial Power of Service Mashups

The long tail phenomenon has been heavily discussed in recent years. What has been neglected so far is its striking relevance for electronic services. Whereas consumers expectations about information goods are often vague and transient, their requirements are pronounced and specific when it comes to the functional and non-functional characteristics of electronic services. Moreover, modular services can be combined and configured into service mashups that have the potential to meet complex consumer requirements. In this vein, the long tail phenomenon can be leveraged into a new dimension – the long valley, where every service exerts positive network externalities on the remaining services, thereby spurring an increase in supply and demand. The combinatorics of constructible service mashups are enabled by universally accessible service orchestration platforms known as Service Value Networks (SVNs). This article shall not only pave the way for a rising research area on a new business trend, but will also help business actors to harness the opportunities opened up by SVNs.

Business Aspects of Web Services

Driven by maturing Web service technologies and the wide acceptance of the service-oriented architecture paradigm, the software industrys traditional business models and strategies have begun to change: software vendors are turning into service providers. In addition, in the Web service market, a multitude of small and highly specialized providers offer modular services of almost any kind and economic value is created through the interplay of various distributed service providers that jointly contribute to form individualized and integrated solutions. This trend can be optimally catalyzed by universally accessible service orchestration platforms service value networks (SVNs) which are the underlying organizational form of the coordination mechanisms presented in this book.Here, the authors focus on providing comprehensive business-oriented insights into todays trends and challenges that stem from the transition to a service-led economy. They investigate current and future Web service business models and provide a framework for Web service value networks. Pricing mechanism basics are introduced and applied to the specific area of SVNs. Strategies for platform providers are analyzed from the viewpoint of a single provider, and so are pricing mechanisms in service value networks which are optimal from a network perspective. The extended concept of pricing Web service derivatives is also illustrated. The presentation concludes with a vision of how Web service markets in the future could be structured and what further developments can be expected to happen.This book will be of interest to researchers in business development and practitioners such as managers of SMEs in the service sector, as well as computer scientists familiar with Web technologies. The books comprehensive content provides readers with a thorough understanding of the organizational, economic and technical implications of dealing with Web services as the nucleus of modern business models, which can be applied to Web services in general and Web service value networks specifically..

Clusteranalyse von Smart-Meter-Daten

ZusammenfassungDie Einführung der Smart-Meter-Technologie stellt die Energiewirtschaft in Deutschland vor große Herausforderungen. Neben hohen Investitionen in die Zähler- und Kommunikationsinfrastruktur ist auch die Neugestaltung vieler Geschäftsprozesse erforderlich. Da die neu entstehenden Kosten nur begrenzt an Endkunden übertragbar sind, gilt es die Aufwendungen der Energiewirtschaft durch neue Dienste und verbesserte Prozesse auf Basis von Smart Metering zu kompensieren. So ist durch die Clusteranalyse der detaillierteren Verbrauchsdaten eine deutlich feinere Kundensegmentierung auf Basis des zeitlichen Verbrauchsverhaltens möglich. Im Rahmen eines Smart-Metering-Projektes bei einem regionalen Energieversorger wurde eine Clusteranalyse für die real vorliegenden Kundenverbrauchsdaten entwickelt und in eine Business-Intelligence-Umgebung integriert. In diesem Beitrag beschreiben und evaluieren wir dieses Artefakt im Sinne der Design Science. Wir gehen dabei insbesondere auf die Ergebnisse der Clusteranalyse von Realdaten und den möglichen Einsatz zur segmentspezifischen Tarifgestaltung ein.AbstractThe introduction of smart meter technology is a great challenge for the German energy industry. It requires not only large investments in the communication and metering infrastructure, but also a redesign of traditional business processes. The newly incurring costs cannot be fully passed on to the end customers. One option to counterbalance these expenses is to exploit the newly generated smart metering data for the creation of new services and improved processes. For instance, performing a cluster analysis of smart metering data focused on the customers’ time-based consumption behavior allows for a detailed customer segmentation. In the article we present a cluster analysis performed on real-world consumption data from a smart meter project conducted by a German regional utilities company. We show how to integrate a cluster analysis approach into a business intelligence environment and evaluate this artifact as defined by design science. We discuss the results of the cluster analysis and highlight options to apply them to segment-specific tariff design.

Towards Objectives-Based Process Redesign

Continuously growing and changing multinational companies oftentimes struggle with feterogeneous degrees of standardization. Especially in case of redesigning business processes that have been historically grown over decades, the capability of handling semi-structures process is central. Nevertheless, for competitive advantages, it is essential for a company to work on the optimization of all processes. Existing redesign techniques either focus on completely unstructured or structured processes. The Redesign Model presented in this paper transforms semi-structured processes into processes with an increased degree of standardization. Our technique consists of four main steps: (i) we extract the objectives for an efficient business process redesign from existing literature; (ii) we formulate a list of requirements an innovative redesign model has to fulfill; (iii) we present a design science based Business Process Redesign Framework including our Redesign model; (iv) we evaluate our model showing its applicability and completeness.

Co-Opetitive Contracting in Service Value Networks

Based on the graph-based Vickrey auction in service value networks introduced by Blau et al. [1], we analyze strategic behavior of service providers in networked formations regarding their opportunities to foster bilateral cooperative agreements. Introducing enforceable ex-ante agreements between adjacent service providers in a Service Value Network (SVNs), we investigate beneficial investment strategies that aim at reducing communication cost between sequentially composed services. The contribution at hand is twofold: Based on the foundation of SVNs and the efficient allocation of services through a graph-based Vickrey auction as presented in Blau et al. [1], [2] we (i) develop a model of cooperation and show analytically that, in the overall non-cooperative setting at hand, our model of cooperation implements a mutual weakly dominant strategy for adjacent service providers to reduce the cost of communication by customizing their service offerings. Transferring our results into practice, we (ii) demonstrate the valuable properties of our model of cooperation by providing a comprehensive application scenario.

Designing Auctions for Coordination in Service Networks

The evolving service ecologies show new ways of value co-creation through combinations of multiple service components which are described in service offerings. An open issue in such a large service ecology is how to efficiently coordinate and price service offerings. Service offerings provide different functionality and quality. Customers need to distinguish their preferences on different combinations of service attributes. In this chapter we address this issue of service offerings allocation and introduce a structure design approach, Market Engineering, as an appropriate method to design such mechanism. In order to apply this approach to service systems we introduce a formal model and a definition of service value networks. Examples exemplify our approach and we show one possible step towards implementing such a mechanism.

Managing the Quality of Modular Services -- A Process-Oriented Aggregation of Expected Service Levels Based on Probability Distributions

Service oriented architectures provide modular service components which can be combined to complex services. Besides the problem of finding optimal combinations of service components the quality of the overall service (the complex service) is important. It is often assumed in literature that the quality of the individual service components is expressed as one single value (e.g. the average). In fact, we observe different probabilities for certain quality levels which are summarized in a probability distribution of the service level indicators. Given the distribution of the quality levels of the individual service components we present an approach to aggregate these distribution functions. As such, we are able to derive one distribution function for the overall complex service. The distribution function of the complex service carries much more information than a single value. This fact is essential for analyzing, managing and controlling the overall process in order to detect weaknesses and to approve overall quality.