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Systems – a Product-Service System

Approach

Completed Research Paper

Holger Schrödl

Otto-von-Guericke University

Magdeburg

Universitaetsplatz 2

39106 Magdeburg, Germany

holger.schroedl@ovgu.de

Stefan Bensch

University of Augsburg

Universitaetsstr. 16

86156 Augsburg, Germany

stefan.bensch@wiwi.uni-augsburg.de

Abstract

The way of providing information systems for companies changes dramatically. Topics like cloud computing serve as a promoter for the replacement of traditional monolithic business applications towards distributed and orchestrated application landscapes. This leads to new challenges in the development and provisioning of information systems. The question is now how to purchase appropriate application components, which may be integrated into an application landscape, rather than how to develop an information system from scratch. This leads to a shift in paying more attention to an appropriate procurement process of application components rather than to software development. This paper answers this issue by providing a sophisticated procurement process for cloud-based information systems by adapting a reference model for the procurement of product-service systems. Based on this procurement model, IT providers may provide solutions with higher complexity and better customer demand alignment to gain competitive advantage in a growing and dynamic market segment.

Key words: Cloud computing, E-procurement, Enterprise applications, Enterprise software/systems, Design Science

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Introduction

In current industrial practice, the prov isioning of information technology (IT) resources has changed significantly. One key issue is whether IT resources supporting the company ’s business processes should be provided by an internal IT serv ice provider or should be purchased from one or several external serv ice prov iders. In scientific discussions, these questions are summarized by the concept of “make or buy” (Matiaske and Mellewigt 2002). Research results show that the sourcing of IT resources from external service providers may lead to adv antages in terms of costs, quality , and flexibility (Böhm et al. 2009; Loh and Venkatraman 1995). Based on these positive results, a growing ecosystem for IT resources has been established and is increasing constantly (Briscoe and Marinos 2009). This ecosystem prov ides methods and technology to provide IT resources with appropriate market mechanisms, giv ing industry companies the option to source IT resources aligned with their needs for their optimal business process support. One example of such an ecosystem is an open marketplace for software components. In these marketplaces, companies are able to source specific IT resources to integrate them in their company IT. While this scenario is a well-accepted way in current industrial practice and works well in relatively small settings, several challenges arise when conducting this method in large-scale, dy namic environments. This paradigm shift to “make or buy” may lead to highly fragmented, complex networks of resources and service prov iders which require intelligent and sophisticated design business process for their management. Therefore, one core challenge is the design of a highly automated, lean procurement processes for IT resources to avoid losing the economic benefit due to high transaction costs. Recent research shows that the transfer of concepts, which have been successful impl emented in other industry sectors, might be a promising way to gain new insights for the IT industry (Brenner et al. 2007 ). Keeping this in mind, IT resources ecosystems may be understood as v alue networks, consisting of different market actors, who are offering, aggregating, integrating, and using IT resources within appropriate market mechanisms. In general, value networks extend the concept of supply chains for the exchange of phy sical goods between different companies towards the exchange of v alue bet ween networked business partners in the new v alue currencies financials, knowledge, and intangible benefits (Allee 2000).

In current IT prov isioning for industry companies, the “make or buy” concept has been extended to a “make and buy” concept (Parmigiani 2007). Current IT resources, which are often denoted as information sy stem landscapes, consist of several sub-sy stems, some of which are provided by the internal IT department and others by an external service prov ider and integrated into the common sy stem landscape. To follow the analogy of the IT resource value network, cloud-based information systems may be conceptualized as configurable information sy stems consisting of components which are (partly) prov ided from cloud serv ice providers v ia the Internet. This conceptualization draws the challenge to the appropriate procurement of cloud-based IT resources. The market for cloud computing is still growing with an annual average rate of app. 29% until 2015 (Demirkan et al. 2011). There is a lack of studies on how this paradigm shift affects existing procurement processes to the delivery of cloud serv ices; therefore, procurement in v alue networks is of growing interest in Information Sy stems (IS) research (Germonprez and Hov orka 2008). Recently, v alue networks in the context of cloud computing have been discussed (Böhm et al. 2009), and new technological capabilities are a key driver for further development. Such service networks prov ide flexible managed cloud serv ices for customers. Selected other serv ices are in contrast prov ided by the vendor. These serv ices are assigned to the classical structure of cloud layers as conceptually illustrated in Figure 1, left side. For a particular serv ice, the different structural requirements could align the proposed solution. These concepts are increasingly characterized by IT serv ices and cloud software services. Thus, there is a shift towards software and technical IT services (Figure 1 , right side).

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Figure 1. Types of Managed Cloud Services and Service Integration in Classical Product-Service Systems as Composed Enterprise Cloud Services

The value network for cloud solutions as a whole will bring together different isolated cloud services. Bundles of services consisting of infrastructure (IaaS), platform (PaaS), and software as-a-service (SaaS) for an intended purpose are from an industrial v iew slightly studied (Berkovich et al. 2009). Here, the transferability of "processes and methods" of "traditional procurement" to "IT serv ices" is analy zed (IT industrialization). One promising concept is the concept of product-serv ice sy stems. Product-serv ice sy stems are specific combinations of material goods, intangible services, and other intangible elements bundled into one single solution. Product-serv ice sy stems are scientifically researched in the field of hy brid v alue creation (e.g. Becker et al. 2008a, 2008b; Bev erungen et al. 2008). Central to the concept of product-service sy stems is the deep integration of service aspects into the proposed methods. This serv ice integration might be the key factor in responding to two fundamental issues in an ecosy stem of cloud-based IT resources. First, there is a high diversification of serv ice level agreements (SLA) in a federated service provider structure. Second, the prov ision of the specific IT resources will not be done by one particular service prov ider, but by a federated serv ice provider infrastructure. Comparing this concept to the situation of the procurement of cloud-based IT resources, it seems reasonable to elaborate on transferring concepts from product-service systems to develop a sophisticated procurement process for cloud-based information systems. These concepts are increasingly characterized by IT services and technical IT-engineering services.

A systematic study of the subject "procurement of cloud solutions in value networks" is intended to identify potentials and issues for designing effective value networks to support the acquisition of cloud solutions. The optimal design of these v alue networks will support all relev ant stakeholders in the cloud computing market (aggregator, integrator, vendor, customer and consultant, see Leimeister et al. 2010) to design their core business processes closely aligned to the specific requirements of cloud solutions procurement processes. Aim of this paper is the development of a procurement model for cloud -based IT services in a cloud computing ecosystem, which can be regarded as a cloud value network. This procurement model will help all stakeholders in the cloud computing ecosy stem to develop their core business processes efficiently and aligned to the specific requirements of the procurement of cloud -based IT resources in large-scale, dynamic ecosy stems. This paper follows the design science method for design-oriented research as an accepted method of information systems research (Hev ner et al. 2004; Peffers et al. 2008). It is structured as follows: in Section 2 we give an introduction to the current state of research of cloud-based information sy stems, e-procurement, service bundling as well as a brief overv iew of the research methods. In Section 3, we transfer the concept of product-serv ice sy stems to design a procurement process for cloud-based information sy stems. Based on a reference process for the procurement of product-serv ice sy stems in v alue networks, we offer an adopted data model for the procurement demand and the v alue network. Furthermore, we present a process model for the selection of an appropriate supply chain which is able to fulfill the requested demand. In Section 4, we demonstrate

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and evaluate the applicability of the proposed model with a simulated use case, and in Section 5 we prov ide a summary of the work as well as an outlook for further research steps.

Research Background

In various industry sectors, value added services are provided increasingly by a value network (Gereffi et al. 2001). A frequently cited and striking example is the automotive industry (Sturgeon et al. 2008). This industry sector has dramatically decreased the weight of added v alue by establishing complex, widely distributed supplier networks. Similar to the automotive industry, the developing cloud computing market can be explained economically as a v alue network (Böhm et al. 2009). Customers purchase services (Barros and Dumas 2006), such as platforms (Böhm et al. 2009) and infrastructure individually or in aggregate form (Tapscott et al. 2000) from the service provider or serv ice aggregator. Cloud resources (e.g. power, storage, and bandwidth) can be bundled as services which are offered to cloud users (Pueschel and Neumann 2009). What these and other scenarios have in common is that the supplier network is of strategic importance to the participating companies.

Cloud-Based Information Systems

While Cloud Computing has become increasingly popular recently, there is no commonly accepted definition (Vaquero et al. 2008); However, recent articles have accumulated scientific publications, expert opinions, and pragmatic descriptions of practice to establish a comprehensive one (e.g. Leimeister et al. 2010, 2009; Vaquero et al. 2008). The definitions generally agree that the term cloud computing addresses an infrastructure-, platform- and application-layer. Youseff et al. developed ontology with an additional layer: kernel software and firmware/ hardware to arrange access to overlaying layers of v irtualization technologies and pre-existing hardware (Youseff et al. 2008). Infrastructure as a Serv ice (IaaS) is characteristic for the flexible and adaptive use of IT resources. One example is the use of v irtual servers or storage (Remote Storage) from the cloud, which can be provided dy namically through v irtualization. The cloud software infrastructure layer prov ides resources to other higher-level layers (Leimeister et al. 2010). An additional lev el of abstraction is Platform as a Service (PaaS). Instead of a v irtual infrastructure, software platforms will be prov ided if required, integrating runtime and development environments as a service. A familiar example is the Google App Engine (Google Inc. 2011). At the application level, serv ices are offered (SaaS), and users can access the hosted cloud serv ices. SaaS is defined as a method for the deployment of software applications available on the Internet as a service, ty pically through a browser. In the narrow sense of the term "Serv ice", functionality can also be accessed v ia a "web serv ice" interface. Thus, the integration of external services into one’s own applications is possible (Becker et al. 2008b).

Cloud-based information systems consisting of hardware and software systems that support business processes are complex software sy stems consisting of several sub-systems from different stack levels of cloud services (Brehm et al. 2007 ). For example, an enterprise resource planning sy stem (ERP sy stem) as cloud-based information system may consist of different modules which reside in different cloud serv ice stack lev els with different business content, linked together to a companywide or even intercompany application landscape (Brehm and Marx -Gómez 2007 ). These different modules may be provided by different serv ice prov iders. The challenge for the company using the ERP sy stem is to identify, select, and dev elop the appropriate service providers for the application landscape (Abels et al. 2006).

E-Procurement Process Model for Cloud-Based Value Bundles

A major task of supply chain management is to support the traditional procurement with information technology (Puschmann and Alt 2005). E-Procurement includes all web-based processes for the procurement of goods and services and thus represents a trade perspective (Baldi and Borgman 2001). Recently, the use of e-procurement in value networks has highlighted various fields (Zweck et al. 2008). Of particular interest is the establishment of electronic v alue networks, the digital conversion in supply networks, the safe use of electronic markets, and the impact of cloud computing in e-procurement to reduce costs and organizational barriers between product and service prov iders (Zweck et al. 2008). Changing market conditions have dominated global sourcing. The global purchase includes the company´s overall planning, management, and control of material information and money flow.

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Companies work with these requirements in networks (Bause and Kaczmarek 2001). Value networks represent companies and their social and technical resources within and between businesses (Pibernik 2001). In a v alue network, a product is prov ided by the network. A network of suppliers spans over several tiers and communicates using the internet, based on information of suppliers. Information technology supports this approach. Procurement processes are key components in value networks. The relevance of e-procurement (Riemer and Klein 2002) can be illustrated by the multiple relationships in v alue networks (Fettke and Loos 2007 ). A serv ice package requires the cooperation of enterprises in value networks (Knackstedt et al. 2009). Besides the efficiency improvement and cost reduction, manufacturers and distributors use the opportunity to exchange information faster electronically (Walter et al. 2010).

The discussion of the constellation of value networks with cloud computing for serv ice packages and suppliers is still pending. Bensch and Schrödl propose a reference model for the procurement of cloud-based product-service bundles (Bensch and Schrödl 2011). This reference model aggregates existing industry standards in procurement and extends them with the specific characteristics of product -serv ice sy stems and cloud computing. An overview on the process steps is depicted in Figure 2.

Figure 2. Reference Procurement Process for Cloud-Based Product-Service Systems (Bensch and Schrödl 2011)

Service Bundling and Product-Service Systems

For a long time, procurement was considered exclusively as an in intracompany executive organ which had to make production and distribution related administrativ e decisions (Arnold and Essig 2000; Kaufmann 2002b). Today, however, the high strategic importance of the procurement function is widely recognized in practice and science (Holbach 2002; Kaufmann 2002a; Krampf 2000). Strategic procurement as a part of the entire procurement process has the primary task of analy sis and goal-oriented creation respectively influencing of sourcing-relevant factors (Roland 1993; Large 2006). These factors can be classified in three areas: market, suppliers, and the company itself (Roland 1993). In current literature, a multitude of contributions for the strategic sourcing of products or serv ices can be found. But as the economic importance of isolated products and serv ices tends to drop because of lacking differentiation, combinations of material products and services being offered as bundles become more and more crucial in the industry. These combinations are called product-serv ice sy stems and are a

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combination of phy sical products, serv ices as well as intangible values like guarantees. These combinations are specially tailored to solve a particular customer problem (Hirschheim et al. 1995). Product-serv ice sy stems can be segmented into customizable or standardized serv ices or material products (see figure 3, left picture). The division of these four elements is not dichotomous, but the transitions between these elements are linear in the sense that there are several possibilities to incorporate these elements into a product-service sy stem.

Integration is a key component of product-service sy stems. This integration means not only bundling products and services for the purpose of a combined solution, but also for process integration on the customer and supplier side (Janiesch et al. 2006). The degree of integration between services in kind and services is v ariable (Fettke and Loos 2007) and has a direct impact on the services. (see Figure 3, right side).

Figure 3. Types of Product-Service Systems and their Integration in a Product Line

The customer orientated development of product-service systems represents new challenges for the subprocesses along the value chain. A key design feature of hybrid value -added process is the establishment of network structures. Reiss and Präuer (Reiss and Präuer 2001) showed in an empirical study that the cooperative organizational forms, such as strategic v alue-added partnerships, networks, and cross-company project-orientated cooperation are the most appropriate organization forms to prov ide product-service sy stems. The concept of product-service systems may be directly transferred to the introduced concept of cloud-based information sy stems before. Div iding cloud-based information sy stems into their own separate modules makes it possible to interpret these modules as ones of a product-service sy stem. These modules may be purchased from different cloud serv ice prov iders and may be integrated into a global business application.

Research Design

The paper follows the design science approach as a recognized method for information systems research (Boudreau et al. 2001; Wilde and Hess 2007 ). In practice, the contribution is based on the seven research guidelines according to Hevner et al. (Hev ner et al. 2004). The method is characterized as an iterative process with alternating phases of construction and ev aluation ("build and ev aluate") (Hev ner et al. 2004). Peffers et al. describes in accordance with existing approaches how to design-oriented research, a structured process that includes six steps for implementing design-oriented research with four possible entry points. The approach supports situational action steps in the sense of a minimum common understanding of the presentation and evaluation of design-oriented research (Peffers et al. 2008). Figure 4 shows the recommended and applied approach. Due to the complexity of procurement processes presented by cloud-based information sy stems, a continuous process in accordance to Peffers et al. and Hev ner et al. is promising. In the following the assumed methodology is described based on Hev ner’s sev en design guidelines (G), starting from Peffers’ entry point (Problem-Centered Initiation).

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Figure 4. Applied Research Design

The Problem-Centered initiation is done by analy zing corresponding literature in the field of procurement. This literature study shows the importance of an adopted procurement process for cloud solutions, but also the lack of existing concepts for the realization of such a process. By using the concept of product-service sy stems as an implementation form for cloud solutions, it can be shown, that several procurement artefacts exists in the current literature, but they suffer from a lack of applicability in the cloud computing ecosy stem. Based on this analy sis, relevant objectives for a specific solution for the procurement of the cloud computing market could be identified for the second research step. With these objectives as a design foundation, existing artifacts from classic and current procurement process models and business procurement systems (in this study SAP-SCM and MS Dy namics Nav ) are analyzed in the third process step. The focus is the design and evaluation of the sourcing model to describe potentials for cloud-based information systems. This is developed gradually in several iterations in accordance with the Guideline "Design as a Search Process" (G6). For this purpose , recursive design alternatives are tested against requirements and restrictions (Peffers et al. 2008). The requirements of the research guidelines "Design as an Artifact" (G1) and "Problem Relev ance" (G2) are described in Sections 1 and 2. As an artifact, a procurement model for cloud based information sy stems is designed (G1). The support of sourcing complex serv ice packages in value networks especially in the context of structural change in information and communication industry (ICT) is significant for practice as well as for the scientific community (G2). The evaluation follows the method of descriptive evaluation with regard to Hev ner et al. (Hev ner et al. 2004). Descriptive evaluation can be conducted in two way s: First, an informed argument based on the findings of the current knowledge base may be used to build a conv incing argument. Second, a detailed scenario may be constructed to demonstrate the utility of the artifact. In this paper, the second option was chosen. Following this, the implementation concept is checked by a constructed reference use case (G3). The procurement model contributes to the growth and structuring of the current body of knowledge, thus making it a "Research Contribution" (G4). The directive "Research Rigor" examines the application of proven approaches to value networks and purchasing in strategic procurement and IT sourcing (G5). To the directive, "Communication of Research", further publications of the model and further discussions with domain experts from business and scientific groups are planned (G7).

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Product-Service Systems as E-procurement Model for Cloud-based

Solutions

Starting from the basic model of the value chain according by Porter (Porter 1969), v alue-added activ ities contribute to the provision of services. Primary activities are activ ities that will lead to immediate value-added contribution. The procurement activity as a support activ ity provides a direct contribution to services. The v alue chain of a company is linked to the v alue chains of suppliers and buyers. Together they create the value network. The procurement process begins with the individualized requirements elicitation. With an increasing complexity of requirements across different cloud stack levels, the number of manageable criteria that must be addressed in the specification increases. A strong customer-supplier relationship for a given serv ice package of cloud services is required. A result of the needs assessment could be a specification that describes all the potential customer requirements (DIN 2009). The process is similar to the traditional procurement; cloud solutions, however, affect the level of the infrastructure requirements in the amount of the target dimensions. During the specification phase, cloud solutions are described in a formalized manner. The related goal is a complete, consistent, and unambiguous description of the external view of the performance. The specifications cover all customer requirements at the component level, derived here as manageable requirements. The focal company specializes for the delivery network the identified requirements. Suppliers, which in the cloud network are described as prov ider, can be determined for cloud artifacts of the network. Components and subcomponents are harmonized according to their cloud-specific characteristics. Specification includes decomposition. Infrastructure, platform, software, and other intangible services were derived. The aim of the hy bridization is to identify features for an application domain systematically. This is done by taking the rules for the configuration of selected services into account. The conception of cloud artifacts, also known as the design phase, corresponds on one hand to the composition and organization of individual serv ice components by their purpose. Thus, to ensure that a cloud service bundle is the choice of various cloud stack components, the bundling should be customized according to the needs assessment. On the other hand, within the design phase, services requirements are brought into relationship. It is necessary to consider cloud stack components of differentiated. When creating serv ices, especially for different stack levels, the customer should be involv ed more than for traditional products (Schuh et al. 2008). On the other hand, in the conception of cloud solutions, the cloud components are structured according to their application infrastructure requirements. This ensures that the cloud components are advertised in the appropriate configuration to the prov ider network. Not every cloud service has the same requirements in its application infrastructure. Therefore, for procurement purposes, the individual requirements have to be taken into account. Specified components can be isolated in the intermediate stage of serv ice decomposition and composition. The single process steps are illustrated in Figure 5, left side. In the sourcing and provider identification phase, identification of strategic supply partners (prov iders) in a dy namic value network, the demand for services to existing and potential suppliers of Tier-1 is reported. According to the report's requirements due to Tier-1 supplier in turn needs to suppliers. In the other direction, the requested information is returned, aggregated, and confirmed in the v alue network, making it complete. The network formation is an iterative process. The value network as a whole bears the creation of cloud solutions. The individual cloud stack changes the requirements for the v alue network. The design of v alue networks can be called the main task for controlling the balance between customer flexibility and value network stability. The process of service delivery to the customer as well as the structural and organizational performance is therefore typically between property and serv ice components for value networks to separate consideration.

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Figure 5. Recursive service decomposition-composition in IT specification

In this context, it is a complex task to specify cloud solution requirements. Therefore, serv ice bundles consist of products (hardware requirements) and services (software requirements). Virtualization is the enabler for cloud components. The services offered in the cloud layer are commonly differentiated into computational resources, latency, network, storage, and security as manageable workloads (see Figure 5, right side). Capable software packages with seamless extension in the cloud perform expensive computing requirements. Network throughput is the average rate of successful data transfer through a network connection. It is necessary to distinguish this term from network bandwidth. Network bandwidth is the capacity for a given system to transfer data over a connection. From a clients’ perspective, throughput is more v aluable, although prov iders base their billing on bandwidth. The required storage resources may be procured on demand from cloud computing provider e.g. from an operating sy stem prov ider (WebOS service prov ider) (Messerschmidt and Lilienthal 2010). Analogous to the use of computing resources from the cloud, data storage-as-a-Service (DaaS) offers users storage flexibility by demand. DaaS allows users access ubiquitously on remote discs. As with other storage sy stems, differences in the requirements have to be taken in account. Criteria in the selection of storage are availability, reliability, performance, replication, and consistency. These requirements are manifested in service level agreements (SLAs) between serv ice prov iders and they can be grouped (Leimeister et al. 2010). Security, in particular data security, is an crucial topic in purchasing cloud computing solutions (Zhang et al. 2010) as artifacts of value bundles. Service providers shall prov ide the opportunity to specify security settings remotely e.g. for a v irtual private cloud. So, the focal supplier must rely on the infrastructure prov ider to achieve full data security. The infrastructure prov ider in this context achieve s confidentiality for secure data access and transfer and auditability to v erify the security settings (Li et al. 2009; Santos et al. 2009).

Details of supplier selection in supply networks and the implementation phase are not deepened. On the basis of the identified serv ices, bundles are offered opportunities for a rule base. Configurable reference models include a rule base, is described in, can be represented as follows from an initial model models (Becker et al. 2009; Beverungen et al. 2008). Repeated customer requests can therefore be identified by the customer based on the package of serv ices in the course as a subset of the original starting model based on rules configured by the customer (Becker and Delfmann 2007 ). From the customer's specific application context, configurable models can be derived. Central business functions like demand specification, supply network identification and supply chain selection are described in detail in the following subsections. The integration of the designed procurement specification steps for cloud-based IT serv ices in a holistic procurement process is illustrated in Figure 6.

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Figure 6. Decomposition-Composition Approach for Cloud Computing in Strategic Sourcing

Demand Specification

The first business function of the model is demand specification. In the context of product-serv ice sy stems, a semantic data model for demand specification was prov ided by Schrödl et. al (Schrödl et al. 2011). This semantic data model serves as the basis for the demand specification of cloud-based information systems as depicted in Figure 7.

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With the starting point of the specification of the customer demand which displays an initialization of a product-service system, data are collected by the direct suppliers as well as by all subsuppliers to support the strategic network modeling. The indiv idual customer demand consists of a specific configuration of modules and outcomes which are in the solution space of the product-serv ice system. Besides, the solution space corresponds to all allowed configurations of a product-serv ice system and is designated in the chart as a product-serv ice sy stem (ty pe). Product-serv ice sy stems are also composed of modules and outcomes. Modules are the building blocks which can contain themselves and include a certain amount of outcomes. These modules can be reused in different product-serv ice systems. Outcomes are the result of an economic process and, hence, can be IaaS modules, PaaS modules, SaaS modules, or customer resources. Modules and outcomes are described by attributes. The combinations of different modules and outcomes may be limited. To present these restrictions, configuration rules are used. These configuration rules limit the solution space and guarantee the consistency of the product-service system.

Supply network Modeling

This article follows the suggestions in Schrödl et. al (Schrödl et al. 2010) for the structured modeling of strategic supply networks. Besides, the single functions of the modeling of a possible net of delivery are segmented in three subsegments: identification, ev aluation and selection of supply networks. For the identification of a possible supply network, the demand is specified for a value bundle and is communicated to prospective or existing suppliers in the supply network. First, the focal supplier sends the demand for the v alue bundle to the suppliers in tier-1. These suppliers check whether they can fulfill the demand or, if this does not apply, communicate a need for their part to their subsuppliers in tier-2. Besides, it is a possible situation that the supplier cannot fulfill the entire demand and forwards this entirely to his suppliers in tier-2. On the other hand, it is possible that the supplier is only able to fulfill the demand partially. In this case, he forwards the remaining demand to his subsuppliers in tier-2. This procedure continues subsequently on every available level inside the supply network. At last, the information requested by the focal suppliers ov er the supply network are collected, aggregated and at least the supply network can be visualized. This procedure possibly leads to several supply networks which would be able to cover the demand of the product-service sy stem. In this case, the focal supplier must decide which of these potential supply networks is selected to cover the specified need. Outgoing from the customer demand which is displayed with an instance of a product-serv ice sy stem it is necessary to collect all supplier's information of tier-1 to tier-n. The supply network, which was selected by the focal supplier to fulfill the customer demand, is a network on supplier who transmits information to the customer. This information is used for the development of the supply network. In the data model, the network of suppliers is represented as a complex monitoring object and every single supplier are displayed as an elementary monitoring object (see figure 8). At a special time, every supplier delivers information about the serv ice stamping, the product stamping, the configuration of the product-service sy stem, finance data and other relevant data. This information is designated supplier-generated data. Supplier-generated data can be planning data or current performance data.

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Figure 8. Semantic Data Model for Demand Specification

Supply Chain Selection

The process of selecting supply chains follows the process of the strategic demand planning in the overall process of the development of strategic supply networks. Starting with a demand, the first step is to fulfill a product-service system assignment. The demand is represented as a product-service sy stem instance, which leads to a specific configuration. The configuration is used to achieve decomposition of the product-service system. In this step, the specified configuration will be decomposed in modules. These modules are not only separate parts in the sense of a bill of materials but might also be a v alue bundle instance. The decomposition of a configuration in modules marks the granularity for the sourcing of the single modules. Therefore, modules might be regarded as the smallest unit to source the demand. This step needs procurement expertise in the possible decomposition variants and is therefore typically done by an engineering department. The result is an identified module demand which can be communicated to the supply network. The module demand is communicated to the supply network. This will be done by the purchasing department. When the demand is communicated, the purchasing department awaits the quotes from the different suppliers form the supply networks. Incoming quotes will be checked whether they fulfill the requirements of the certain modules or not. This step repeats until there are quotes for ev ery module for the specific demand. For the process summary, see figure 9.

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Figure 9. Event-driven Process Chain (EPC) for Supply Chain Selection

The checked quotes are taken from the engineering department and are composed to all possible configurations. This leads to all possible configuration variants which might be derived from the checked quotes. To illustrate this process an example for a selected criteria e.g. serv ice level agreement is used (figure 10). The example is displayed as supply network with the corresponding suppliers and the criteria linked to ev ery single supplier.

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Depending on which supplier delivers one or more modules for the specific demand there might be different possible configurations. To ensure that there is the appropriate selection among all possible configuration v ariants there is an examination of the variants if they fulfill the needs of the specified demand. All configuration fulfilling the demand will be entitles as valid configurations. By considering these valid configurations and the checked quotes, the purchasing department generates the possible supply network set. This step leads to a list of identified possible supply networks which are able to fulfill the demand of the specified demand. Following this the next process step will be the supply network ev aluation. The following section verifies these design-oriented paradigms in a case study for reference by a comprehensive practical example.

Reference Use Case

From the authors’ current knowledge, there is no other procurement process aligned with the specific circumstances relating to the procurement of cloud-based information systems in current scientific discussions. According to Bensch & Schrödl, there are several procurement processes for tangible goods, only few processes for serv ices, and no procurement processes for product-serv ice sy stems (Bensch and Schrödl 2011). Therefore, it is not appropriate to discuss the proposed results in relation to other concurring results. To demonstrate the plausibility of the proposed model, a use case is described. The use case is a real case from a company providing ICT solutions and is typical for procurement problems with complex product-serv ice bundles including cloud-solutions in value networks. Crucial elements of the case have been discussed with experts from the prov iding company in the areas of product management, marketing, IT operations and senior management. All discussions have been reflected to the proposed procurement model. Therefore, the proposed use case can be regarded as an industry -relevant, ty pical use case for the procurement of cloud-based IT services in a large-scale, dynamic env ironment. Since all relev ant details are reflected in the use case, it can be considered as a relev ant evaluation instrument for a descriptiv e ev aluation in design science research (Hev ner et al. 2004). The considered application is the offer for a prov ider of information technology. This package is a web -based enterprise IT workplace, which can be used as a standard workplace for typical office activities. The scope of this IT workplace includes v arious software packages prov ided by different serv ice providers. Furthermore, a customer relationship management system (CRM) along with online backup is integrated which is connected to a digital marketplace for the office supply purchasing management. Finally, there is a serv ice level agreement (SLA), which allows the user either to call a hotline or an on-site serv ice center in case of problems.

Table 1. Requirements Determination solution com ponent

own production workplace hardware, network connection, service level agreement (SLA) procurement needs software packages, customer relationship management (CRM) system,

online-backup solution, market place connection

In the first procurement step, the focal supplier has to determine its procurement need. Therefore, the customer solution as described above is div ided into "own production" and "procurement needs" (see Table 1). During the specification phase of the procurement, components were decomposed into indiv idual components and subcomponents. Here, a cloud stack classification and workload requirements (see Fig. 6 and 7 ) are made (see Table 2). Based on the focal supplier decision, clear division for specific components is not always possible.

Table 2. Demand Specification Cloud

Stack Ty pe

Workload specification

Com pute Latency Network Storage Security Software package 1 (sp1) SaaS Low Low Low Medium Tier II Phy sical Software package 2 (sp2) PaaS Low Medium Low Medium Tier II Logical

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CRM Sy stem (crm) SaaS Low High Medium Large Tier I Logical Online backup solution (obs) IaaS Low Medium High Large Tier I Phy sical Market Place Connection

(mpc)

IaaS Medium Medium High Medium Tier II Logical

In the phase of the sourcing of the cloud-based components, the different components are grouped together by combining similar workload requirements to achieve positive effects in the procurement of components belonging to the same workload group (see Table 3). The abbrev iations can be obtained from Table 2.

Table 3. Workload Grouping Low Medium High Medium

Tier II Large Tier I Phy sical Logical Com pute sp1, sp2,

cr m, obs m pc n .a. n .a. n .a. n .a. n .a.

Latency sp1 sp2, obs,

m pc cr m n .a. n .a. n .a. n .a.

Network sp1, sp2 cr m obs, mpc n .a. n .a. n .a. n .a. Storage n .a. n .a. n .a. sp1, sp2,

m pc cr m, obs n .a. n .a.

Security n .a. n .a. n .a. n .a. n .a. sp1, obs sp2, crm, m pc

In the phase of sourcing, the grouped demand is formalized and announced. All components and specifications are advertised in the v alue network. In the phase of the bundling of services, the deals are based on the tenders of the components takes place in the v alue network, tested, completed and bundled. This collection is combined with the components of the manufacturer's own products and is packaged as the product-service bundle that is offered to the customer. The bundling of services now depends on the heterogeneity of the suppliers. If individual suppliers are able to cover v arious components, the bundling differs from that if there is a v ariety of suppliers and subcontractors in turn.

Since this is an artificial use case, which is based on current industrial practice from leading industry experts, more insights will be achieved by conducting real industry business cases. These business cases will strengthen the evaluation of the proposed artifact and will probably lead to some refinements of the solution. But, on the other hand, we assume that a useful behavior of the proposed procurement process can be derived from this simulation approach. The main benefit of this proposed procurement process can be seen in the potential for process automation. The segmentation of the demand and the automated classification of the individual items prov ides the potential for an automated procurement bundling starting from the procurement need. By extending this process to the realization of request-for-quotes over the automated comparison of the proposals up to the contracting and delivery phase, the entire procurement process may be automated like it can be observed in traditional industries for tangible goods. This would lead a truly new dy namic in the cloud computing market for all participating actors. Valuable insight for this holistic approach may be achieved from the upcoming industry case study as future research.

Conclusion and Further Research

Aim of this paper is the development of a procurement process for cloud -based information sy stems. For this purpose, concepts for product-service sy stems have been transferred and adapted to the specific requirements of cloud computing. Based on an existing reference process for the procurement of product-service systems, key data models and business processes have been developed. The procurement process covers four strategic industrial sourcing process steps and fiv e manageable workloads to source cloud solutions in alignment to established industrial procurement process steps in a value network. Sematic

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data models for the demand formulation and the supply network modelling have been prov ided. Supply chain selection as the central business process for identify ing and selecting appropriate suppliers has been proposed. For ev aluation, the procurement process was simulated by conducting a designed case study showing the applicability of the procurement model.

The integration of logistic aspects for the procurement processes holds significant adv antages for focal suppliers of cloud solutions over traditional procurement. There are more than reduced transaction costs. The presented design proposal is a way out for those companies that challenges the integration of cloud stack components in cloud solutions but faces a shortfall of procurement strategy to source cloud artefacts from their value network. The strategic approach to procurement has bundling effects in t he design of cloud components. Offering companies are able to identify systematically cloud compositions from different integrated offerings to achieve economic and logistic advantages. In many scenarios, such proposals are the missing component to a seamless procurement process. This approach offers companies a basis for process changes that support the procurement of cloud bundles in v alue networks. Processes are adjusted according to the company and market dy namics.

Current and future research will examine the extent how cloud sourcing requirements are supported by business information systems. This research will provide new insights to the developers of ICT sy stems for enterprise resource planning (ERP) and supply chain management (SCM) on how to align these business requirements to ICT functionality. Future research should examine how the implementation of the procurement function in existing business information systems supports cloud solutions in value networks. Furthermore, the issue how existing ERP sy stems must be designed to implement the procurement process for cloud solutions in value networks should be investigated. This research requires an inv estigation to identify more specific cloud solutions and their relev ant factors like feasibility, relev ance and acceptability.

References

Abels, S., Brehm, N., Hahn, A., and Marx -Gómez, J. 2006. “Change management issues in Federated ERP

sy stems: an approach for identifying requirements and possible solutions,” International Journal of

Information Systems and Change Management (1:3), pp. 318–335.

Allee, V. 2000. “Reconfiguring the Value Network,” Journal of Business Strategy (21:4), pp. 36–39.

Arnold, H. U., and Essig, M. 2000. “Sourcing-Konzepte als Grundelemente der Beschaffungsstrategie,”

Wirtschaftswissenschaftliches Studium (29:3), pp. 122–128.

Baldi, S., and Borgman, H. P. 2001. “Betreiberstrukturen von Elektronischen B2B-Marktplätzen - Eine

Fallstudie in der Automobilindustrie,” WIRTSCHAFTSINFORMATIK , pp. 543–554.

Barros, A. P., and Dumas, M. 2006. “The Rise of Web Serv ice Ecosystems,” IT Professional (8:5), pp. 31–

37 .

Bause, F., and Kaczmarek, M. 2001. “Modellierung und Analyse von Supply Chains,”

WIRTSCHAFTSINFORMATIK , pp. 569–578.

Becker, J., Bev erungen, D., and Knackstedt, R. 2008a. “Reference Models and Modeling Languages for

Product-Service Sy stems - Status-Quo and Perspectives for Further Research,” in Proceedings of the

41st Annual International Conference on System Sciences, Waikoloa, Big Island, Hawaii. January 7 -10, 2008, pp. 105‐114.

Becker, J., Bev erungen, D., and Knackstedt, R. 2008b. “Wertschöpfungsnetzwerke v on Produzenten und Dienstleistern als Option zur Organisation der Erstellung hy brider Leistungsbündel,” in

Wertschöpfungsnetzwerke: Phy sica, pp. 3‐31.

Becker, J., Bev erungen, D., Knackstedt, R., and Müller, O. 2009. “Konzeption einer Modellierungssprache zur tool-unterstützten Modellierung, Konfiguration und Bewertung hybrider Leistungsbündel,” in

Dienstleistungsmodellierung: Phy sica-Verlag HD, pp. 53–7 0.

Becker, J., and Delfmann, P. (eds.) 2007. Reference Modeling: Efficient Information Systems Design

Through Reuse of Information Models, Heidelberg: Phy sica-Verlag.

Bensch, S., and Schrödl, H. 2011. “Purchasing Product-Service Bundles in Value Networks - Exploring the

Role of SCOR,” in Proceedings of the 19th European Conference on Information Systems: Helsinki,

Finland, June 9 - 11, 2011, V. Tuunainen, J. Nandhakumar, M. Rossi, and W. Soliman (eds.), Helsinki, Finland. 09.-11. June 2011, Helsinki.

(17)

Berkov ich, M., Esch, S., Leimeister, J. M., and Krcmar, H. 2009. “Requirements Engineering for Hy brid Products as Bundle of Hardware, Software and Service Elements - a Literature Rev iew,” in

Tagungsband der 9. Internationalen Tagung Wirtschaftsinformatik, Wien, Wien. Bev erungen, D., Kaiser, U., Knackstedt, R., Krings, R., and Stein, A. 2008. “Konfigurative

Prozessmodellierung der hybriden Leistungserstellung in Unternehmensnetzwerken des Maschinen -

und Anlagenbaus,” in Multikonferenz Wirtschaftsinformatik 2008, M. Bichler, T. Hess, H. Krcmar,

U. Lechner, F. Matthes, A. Picot, B. Speitkamp, and P. Wolf (eds.), München. 26.-28.02.2008, Berlin. Böhm, M., Leimeister, S., Riedl, C., and Krcmar, H. 2009. “Cloud Computing: Outsourcing 2.0 oder ein

neues Geschäftsmodell zur Bereitstellung v on IT-Ressourcen?” Information Management und

Consulting (24:2), pp. 6–14.

Boudreau, M.-C., Gefen, D., and Straub, D. W. 2001. “Validation in Information Sy stems Research: A State-of-the-Art Assessment,” MIS Quarterly (25:1), p. 1.

Brehm, N., Lübke, D., and Gómez, J. M. 2007 . “Federated Enterprise Resource Planning Sy stems,”

Handbook of Enterprise Systems Architecture in Practice , p. 290.

Brehm, N., and Marx -Gómez, J. 2007. “The Web Serv ice-Based Combination of Data and Logic

Integration in Federated ERP Sy stems,” in Managing worldwide operations and communications

with information technology: Proceedings of the 2007 Information Resources Management

Association international conference, M. Khosrow-Pour (ed.), Vancouver, British Columbia, Canada. May 19-13, 2007, Hershey, Pa: IGI Publ, pp. 1559–1564.

Brenner, W., Ebert, N., Hochstein, A., and Übernickel, F. 2007 . IT-Industrialisierung: Was ist das?

http://www.computerwoche.de/management/it-strategie/592035/index.html. Accessed 30 Nov ember 2011.

Briscoe, G., and Marinos, A. 2009. “Digital ecosystems in the clouds: towards community cloud

computing,” DEST 2009 .

Demirkan, H., Harmon, R. R., and Goul, M. 2011. “A Service -Oriented Web Application Framework,” IT

Professional (13:5), pp. 15–21.

DIN 2009. Project management - Project management systems - Part 1: Fundamentals: Beuth (DIN

69901 -1:2009-01).

Fettke, P., and Loos, P. (eds.) 2007 . Reference modeling for business systems analysis, Hershey, PA: Idea Group Pub.

Gereffi, G., Humphrey , J., Kaplinsky, R., and Sturgeon*, T. J. 2001. “Introduction: Globalisation, Value Chains and Dev elopment,” IDS Bulletin (32:3), pp. 1 –8.

Germonprez, M., and Hov orka, D. 2008. “The information se rvice view,” in Information Technology in

the Service Economy Challenges and Possibilities for the 21st Century: IFIP TC8 WG8.2

International Working Conference August 1013, 2008, Toronto, Ontario, Canada, M. Barrett, E. Dav idson, J. I. DeGross, and C. Middleton (eds.), New Y ork, NY, Berlin ;Heidelberg: Springer, pp. 365–366.

Google Inc. 2011. Google App Engine - Google Code. http://code.google.com/intl/en/appengine/.

Accessed 6 December 2011.

Hev ner, A. R., March, S. T., Park, J., and Ram, S. 2004. “Design Science in Information Sy stems

Research,” MIS Quarterly (28:1), pp. 75–105.

Hirschheim, R., Klein, H. K., and Ly y tinen, K. 1995. Information systems development and data

modeling: Conceptual and philosophical foundations, Cambridge: Cambridge Univ . Press.

Holbach, D. 2002. Beschaffungsmarktforschung in der digitalen vernetzten Welt: Grundlagen, Analyse

und Anwendungen, Frankfurt am Main: DVS, Digitaler Vervielfältigungs- und Verlagsservice. Janiesch, C., Pfeiffer, D., Seidel, S., and Becker, J. 2006. “Ev olutionary Method Engineering: Towards a

Method for the Analysis and Conception of Management Information Sy stems,” in Proceedings of the

12th Americas Conference on Information Systems, Acapulco, Mexico. 04.-06.08.2006, pp. 3922– 3933.

Kaufmann, L. (ed.) 2002a. Handbuch industrielles Beschaffungsmanagement: Internationale Konzepte -

innovative Instrumente - aktuelle Praxisbeispiele, Wiesbaden: Hahn.

Kaufmann, L. 2002b. “Purchasing and Supply Management: A Conceptual Framework,” in Handbuch

industrielles Beschaffungsmanagement: Internationale Konzepte - innovative Instrumente - aktuelle Praxisbeispiele, L. Kaufmann (ed.), Wiesbaden: Hahn, pp. 3 –33.

Knackstedt, R., Stein, A., and Becker, J. 2009. “Modellierung integrierter Produktion und Dienstleistung mit dem SCOR-Modell - Bestehende Ansätze und Entwicklungsperspektiven,” in

(18)

Wirtschaftsinformatik 2009, H. R. Hansen, D. Karagiannis, and H.-G. Fill (eds.), Wien. 25.-27 .02.2009, pp. 119–128.

Krampf, P. 2000. Strategisches Beschaffungsmanagement in industriellen Gro ssunternehmen: Ein

hierarchisches Konzept am Beispiel der Automobilindustrie, Lohmar: Eul.

Large, R. 2006. Strategisches Beschaffungsmanagement eine praxisorientierte Einführung ; mit

Fallstudien, Wiesbaden: Gabler.

Leimeister, S., Böhm, M., Riedl, C., and Krcmar, H. 2010. “The Business Perspective of Cloud Computing:

Actors, Roles and Value Networks,” in ECIS 2010 Proceedings, Pretoria, South Africa.

06.-09-06.2010, pp. Paper 56.

Li, B., Li, J., Huai, J., Wo, T., Li, Q., and Zhong, L. 2009. “EnaCloud: An Energy-Saving Application Liv e

Placement Approach for Cloud Computing Env ironments,” in Proceedings of 2009 IEEE

International Conference on Cloud Computing, I. The Institute of Electrical and Electronics Engineers (ed.), Bangalore, India. 21-25 September 2009, pp. 17–24.

Loh, L., and Venkatraman, N. 1995. “An Empirical Study of Information Technology Outsourcing:

Benefits, Risks, and Performance Implications,” ICIS 1995 Proceedings .

Matiaske, W., and Mellewigt, T. 2002. “Motive, Erfolge und Risiken des Outsourcings - Befunde und Defizite der empirischen Outsourcing-Forschung: zfb0602: Autor: Wenzel Matiaske / Thomas

Mellewigt Ausgabe: 6/2002,” Zeitschrift für Betriebswirtschaft (72:6), pp. 641–659.

Messerschmidt, C. M., and Lilienthal, M. 2010. “Acceptance of a Web OS as a Commercial Consumer Serv ice Bundle,” in ECIS 2010 Proceedings, Pretoria, South Africa. 06.-09-06.2010.

Parmigiani, A. 2007. “Why do firms both make and buy? An inv estigation of concurrent sourcing,”

Strategic Management Journal (28:3), pp. 285–311.

Peffers, K. E., Tuunanen, T., Rothenberger, M. A., and Chatterjee, S. 2008. “A Design Science Research

Methodology for Information Sy stems Research,” Journal of Management Information Systems

(24:3), pp. 45–77.

Pibernik, R. 2001. “Flexibilitätsplanung in Wertschöpfungsnetzwerken,” Zeitschrift für

Betriebswirtschaft (8), pp. 893–913.

Porter, M. E. 1969. “What is Strategy?” Harvard business review , pp. 61 –78.

Pueschel, T., and Neumann, D. 2009. “Management of Cloud Infastructures: Policy-Based Revenue

Optimization,” in Proceedings of the ICIS 2009, Phoenix, Arizona. 15.-18.12.2009.

Puschmann, T., and Alt, R. 2005. “Successful Use of e -Procurement in Supply Chains,” Supply Chain

Management - An International Journal (2:10), pp. 122-133.

Reiss, M., and Präuer, A. 2001. “Solutions Providing: Was ist Vision-was Wirklichkeit?” Absatzwirtschaft

(5:44), pp. 48–53.

Riemer, K., and Klein, S. 2002. “Supplier Relationship Management Supplier Relationships im Rahmen

des Partner Relationship Managements,” HMD - Praxis der Wirtschaftsinformatik (39:228), pp. 5–

22.

Roland, F. 1993. BeschaffungsstrategienVoraussetzungen, Methoden und EDV -Unterstützung einer

adäquaten Auswahl. Dissertation, Göttingen.

Santos, N., Gummadi, K. P., and Rodrigues, R. 2009. “Towards Trusted Cloud Computing,” in Hotcloud

2009: Workshop on Hot Topics in Cloud Computing, USENIX Annual Technical Conference (ed.), San Diego. 15.06.2009.

Schrödl, H., Gugel, P., and Turowski, K. 2010. “Modellierung strategischer Liefernetze für hy bride

Leistungsbündel,” in Dienstleistungsmodellierung 2010: Interdisziplinäre Konzepte und

Anwendungsszenarien, O. Thomas, and M. Nüttgens (eds.), Klagenfurt. 24.03.2010, Heidelberg: Springer-Verlag Berlin Heidelberg, pp. 1‐18.

Schrödl, H., Gugel, P., and Turowski, K. 2011. “Towards a Reference Model for the Identification of

Strategic Supply Chains for Value Bundles,” in Proceedings of the 44th Annual Hawaii International

Conference on System Sciences, R. H. Sprague (ed.), Koloa, Kauai, Hawaii. 4-7 January 2011, Piscataway, NJ: IEEE, pp. 1 –10.

Schuh, G., Lenders, M., Bartoschek, M., and Bender, D. 2008. “Preisfindungsprozess für

Leistungssysteme im Maschinen- und Anlagenbau,” Controlling (8/9), pp. 481–487.

Sturgeon, T., v an Biesebroeck, J., and Gereffi, G. 2008. “Value chains, networks and clusters: reframing

the global automotive industry,” Journal of Economic Geography (8:3), pp. 297 –321.

Tapscott, D., Ticoll, D., and Lowy , A. 2000. Digital capital: Harnessing the power of business webs, Boston: Harv ard Business School Press.

(19)

Vaquero, L. M., Rodero-Merino, L., Caceres, J., and Lindner, M. 2008. “A break in the clouds: towards a

cloud definition,” SIGCOMM Comput. Commun. Rev (39), pp. 50‐55.

Walter, P., Blinn, N., Schlicker, M., and Thomas, O. 2010. “IT-gestützte Wertschöpfungspartnerschaften

zur Integration v on Produktion und Dienstleistung im Maschinen- und Anlagenbau,” in Hybride

Wertschöpfung, O. Thomas, P. Loos, and M. Nüttgens (eds.), Berlin, Heidelberg: Springer Berlin Heidelberg, pp. 299–313.

Wilde, T., and Hess, T. 2007 . “Forschungsmethoden der Wirtschaftsinformatik: Eine empirische

Untersuchung,” WIRTSCHAFTSINFORMATIK (49:4), pp. 280–287.

Y ouseff, L., Butrico, M., and da Silv a, D. 2008. “Towards a Unified Ontology of Cloud Computing: Grid Computing Env ironments Workshop (GCE08), held in conjunction with SC08 (Nov ember, 2008),” in

2008 Grid Computing Environments Workshop: (GCE) ; Austin, Texas, USA, 16 November 2008, Piscataway, NJ: IEEE Serv ice Center, pp. 1 –10.

Zhang, Q., Cheng, L., and Boutaba, R. 2010. “Cloud computing: state-of-the-art and research challenges,”

Journal of Internet Services and Applications (1:1), pp. 7 –18.

Zweck, A., Korte, S., and Rijkers-Defrasne, S. 2008. “Hy bride Wertschöpfung: Statusbericht aktueller Forschungsvorhaben,” 78, Zukünftige Technologien Consulting der VDI Technologiezentrum GmbH (ed.), Düsseldorf.

Figure

Figure 1.  Types  of  Managed  Cloud  Services and  Service Integration  in   Classical Product-Service  Systems as Composed  Enterprise   Cloud  Services
Figure 2.  Reference Procurement  Process for Cloud-Based  Product-Service  Systems (Bensch and  Schrödl 2011)
Figure 3.  Types  of  Product-Service  Systems and  their Integration  in a Product  Line
Figure 4.  Applied  Research Design
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