Change search
Refine search result
1 - 18 of 18
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Johnson, Pontus
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Iacob, M. E.
    Välja, Margus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Van Sinderen, M.
    Magnusson, C.
    Ladhe, T.
    Business model risk analysis: Predicting the probability of business network profitability2013In: Lecture Notes in Business Information Processing, 2013, p. 118-130Conference paper (Refereed)
    Abstract [en]

    In the design phase of business collaboration, it is desirable to be able to predict the profitability of the business-to-be. Therefore, techniques to assess qualities such as costs, revenues, risks, and profitability have been previously proposed. However, they do not allow the modeler to properly manage uncertainty with respect to the design of the considered business collaboration. In many real collaboration projects today, uncertainty regarding the business' present or future characteristics is so significant that ignoring it becomes problematic. In this paper, we propose an approach based on the Predictive, Probabilistic Architecture Modeling Framework (P2AMF), capable of advanced and probabilistically sound reasoning about profitability risks. The P2AMF-based approach for profitability risk prediction is also based on the e3-value modeling language and on the Object Constraint Language (OCL). The paper introduces the prediction and modeling approach, and a supporting software tool. The use of the approach is illustrated by means of a case.

  • 2.
    Johnson, Pontus
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Iacob, Maria Eugenia
    Välja, Margus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    van Sinderen, Marten
    Magnusson, Christer
    Ladhe, Tobias
    A method for predicting the probability of business network profitability2014In: Information Systems and E-Business Management, ISSN 1617-9846, E-ISSN 1617-9854, Vol. 12, no 4, p. 567-593Article in journal (Refereed)
    Abstract [en]

    In the design phase of business collaboration, it is desirable to be able to predict the profitability of the business-to-be. Therefore, techniques to assess qualities such as costs, revenues, risks, and profitability have been previously proposed. However, they do not allow the modeler to properly manage uncertainty with respect to the design of the considered business collaboration. In many real collaboration projects today, uncertainty regarding the business' present or future characteristics is so significant that ignoring it becomes problematic. In this paper, we propose an approach based on the predictive, probabilistic architecture modeling framework (P2AMF), capable of advanced and probabilistically sound reasoning about profitability risks. The P2AMF-based approach for profitability risk prediction is also based on the e3-value modeling language and on the object constraint language. The paper introduces the prediction and modeling approach, and a supporting software tool. The use of the approach is illustrated by means of a case study originated from the Stockholm Royal Seaport smart city project.

  • 3.
    Korman, Matus
    et al.
    KTH, School of Electrical Engineering (EES), Network and Systems engineering.
    Lagerström, Robert
    KTH, School of Electrical Engineering (EES), Network and Systems engineering.
    Välja, Margus
    KTH.
    Ekstedt, Mathias
    KTH, School of Computer Science and Communication (CSC).
    Blom, Rikard
    KTH.
    Technology Management through Architecture Reference Models: A Smart Metering Case2016In: PORTLAND INTERNATIONAL CONFERENCE ON MANAGEMENT OF ENGINEERING AND TECHNOLOGY (PICMET 2016): TECHNOLOGY MANAGEMENT FOR SOCIAL INNOVATION / [ed] Kocaoglu, DF Anderson, TR Daim, TU Kozanoglu, DC Niwa, K Perman, G, IEEE , 2016, p. 2338-2350Conference paper (Refereed)
    Abstract [en]

    Enterprise architecture (EA) has become an essential part of managing technology in large enterprises. These days, automated analysis of EA is gaining increased attention. That is, using models of business and technology combined in order to analyze aspects such as cyber security, complexity, cost, performance, and availability. However, gathering all information needed and creating models for such analysis is a demanding and costly task. To lower the efforts needed a number of approaches have been proposed, the most common are automatic data collection and reference models. However these approaches are all still very immature and not efficient enough for the discipline, especially when it comes to using the models for analysis and not only for documentation and communication purposes. In this paper we propose a format for representing reference models focusing on analysis. The format is tested with a case in a large European project focusing on security in advanced metering infrastructure. Thus we have, based on the format, created a reference model for smart metering architecture and cyber security analysis. On a theoretical level we discuss the potential impact such a reference model can have.

  • 4.
    Korman, Matus
    et al.
    KTH, School of Electrical Engineering (EES), Network and Systems engineering.
    Välja, Margus
    KTH, School of Electrical Engineering (EES), Network and Systems engineering.
    Björkman, Gunnar
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Ekstedt, Mathias
    KTH, School of Electrical Engineering (EES), Network and Systems engineering.
    Vernotte, Alexandre
    KTH, School of Electrical Engineering (EES), Network and Systems engineering.
    Lagerström, Robert
    KTH, School of Electrical Engineering (EES), Network and Systems engineering.
    Analyzing the effectiveness of attack countermeasures in a SCADA system2017In: Proceedings - 2017 2nd Workshop on Cyber-Physical Security and Resilience in Smart Grids, CPSR-SG 2017 (part of CPS Week), Association for Computing Machinery, Inc , 2017, p. 73-78Conference paper (Refereed)
    Abstract [en]

    The SCADA infrastructure is a key component for power grid operations. Securing the SCADA infrastructure against cyber intrusions is thus vital for a well-functioning power grid. However, the task remains a particular challenge, not the least since not all available security mechanisms are easily deployable in these reliability-critical and complex, multi-vendor environments that host modern systems alongside legacy ones, to support a range of sensitive power grid operations. This paper examines how effective a few countermeasures are likely to be in SCADA environments, including those that are commonly considered out of bounds. The results show that granular network segmentation is a particularly effective countermeasure, followed by frequent patching of systems (which is unfortunately still difficult to date). The results also show that the enforcement of a password policy and restrictive network configuration including whitelisting of devices contributes to increased security, though best in combination with granular network segmentation.

  • 5.
    Välja, Margus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Determinants of the Ease of Hacking2012Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Software security is a problem. Software development mistakes end up as vulnerabilities that can be exploited. The easier a software exploit makes attacking a target, the less skilled people are able to do it. Various prioritisation systems exist to address software security issues. The author of this paper finds that they are either too complex and hard to access, or product specific. This thesis takes a whole new approach to the prioritisation by studying exploit completeness and the factors that relate to it. First an exploit completeness scale is constructed, then the author conducts a study to analyse vulnerability and exploit data with statistical methods. The results show that seven factors influence exploit completeness. Five factors are used to build a linear regression model for completeness prediction. The time needed to collect the data for the factors is measured.

  • 6.
    Välja, Margus
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Improving IT Architecture Modeling Through Automation: Cyber Security Analysis of Smart Grids2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Contemporary organizations depend on IT to reach their goals but the organizations are constantly adapting to changing market conditions and these changes need to be reflected in the IT architecture. Modeling is often used to manage complex architectures allowing to abstract details and focus on the most important aspects. Metamodels are central to modeling and used as a mechanism for modeling different phenomena and describing evolving designs such as IT architectures. However, it can be difficult to model IT architecture especially in large organizations due to the amount and diversity of systems, software, data, et cetera. Previous studies have found problems with metamodels and the support modeling tools provide to the users. The topics mentioned by numerous authors are lacking cyber security analysis capabilities and the support for automated model creation using enterprise data. These two topics are studied in this thesis with the focus on smart grids. 

    The contribution of this thesis is to offer support for IT architecture modeling processes with the following propositions that are described in four papers. The contribution includes a metamodel extension for analyzing insider threats and reachability (Paper A), a framework for automatic modeling (Paper B), a framework for improving semantic accuracy and granularity matching in automatic modeling (Paper C) and a reference model for cyber security analysis of smart grid load balancing (Paper D).

  • 7.
    Välja, Margus
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Honeth, Nicolas
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Buschle, Markus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Lagerström, Robert
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Sasi, Kottayil K.
    Somasundaran, Nithin
    An Archimate based analysis of Microgrid Control Systems Architectures2014Conference paper (Refereed)
    Abstract [en]

    The architectures containing embedded systems such as microgrid controllers are becoming more complex. While there are several known methodologies for embedded system modeling and design, they mostly cover development related performance issues. There exists a gap in the management of architectures implementing embedded systems for power systems applications. This paper proposes to use enterprise architecture analysis, based on earlier work, to fill that gap. Availability, interoperability and cost analysis are in focus. Enterprise architecture models are important in order to abstract the technical detail for planning and design in order to provide a basis for discussion of technical scalability and cost management amongst stakeholders and technical experts. A microgrid control architecture based example is given to illustrate the analysis possibilities.

  • 8.
    Välja, Margus
    et al.
    KTH, School of Electrical Engineering (EES), Network and Systems engineering.
    Korman, Matus
    KTH, School of Electrical Engineering (EES), Network and Systems engineering.
    Lagerström, Robert
    KTH, School of Electrical Engineering (EES), Network and Systems engineering.
    A study on software vulnerabilities and weaknesses of embedded systems in power networks2017In: Proceedings - 2017 2nd Workshop on Cyber-Physical Security and Resilience in Smart Grids, CPSR-SG 2017 (part of CPS Week), Association for Computing Machinery, Inc , 2017, p. 47-52Conference paper (Refereed)
    Abstract [en]

    In this paper we conduct an empirical study with the purpose of identifying common software weaknesses of embedded devices used as part of industrial control systems in power grids. The data is gathered about the devices and software of 6 companies, ABB, General Electric, Schneider Electric, Schweitzer Engineering Laboratories, Siemens and Wind River. The study uses data from the manufacturersfi online databases, NVD, CWE and ICS CERT. We identified that the most common problems that were reported are related to the improper input validation, cryptographic issues, and programming errors.

  • 9.
    Välja, Margus
    et al.
    KTH.
    Korman, Matus
    KTH.
    Lagerström, Robert
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Franke, Ulrik
    Swedish Inst Comp Sci, Stockholm, Sweden..
    Ekstedt, Mathias
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Automated Architecture Modeling for Enterprise Technology Management Using Principles from Data Fusion: A Security Analysis Case2016In: PORTLAND INTERNATIONAL CONFERENCE ON MANAGEMENT OF ENGINEERING AND TECHNOLOGY (PICMET 2016): TECHNOLOGY MANAGEMENT FOR SOCIAL INNOVATION / [ed] Kocaoglu, DF Anderson, TR Daim, TU Kozanoglu, DC Niwa, K Perman, G, IEEE , 2016, p. 14-22Conference paper (Refereed)
    Abstract [en]

    Architecture models arc used in enterprise management for decision support. These decisions range from designing processes to planning for the appropriate supporting technology. It is unreasonable for an existing enterprise to completely reinvent itself. Incremental changes are in most cases a more resource efficient tactic. Thus, for planning organizational changes, models of the current practices and systems need to be created. For mid-sized to large organizations this can be an enormous task when executed manually. Fortunately, there's a lot of data available from different sources within an enterprise that can be used for populating such models. The data are however almost always heterogeneous and usually only representing fragmented views of certain aspects. In order to merge such data and obtaining a unified view of the enterprise a suitable methodology is needed. In this paper we address this problem of creating enterprise architecture models from heterogeneous data. The paper proposes a novel approach that combines methods from the fields of data fusion and data warehousing. The approach is tested using a modeling language focusing on cyber security analysis in a study of a lab setup mirroring a small power utility's IT environment.

  • 10.
    Välja, Margus
    et al.
    KTH, School of Electrical Engineering (EES), Electric power and energy systems.
    Korman, Matus
    KTH, School of Electrical Engineering (EES), Electric power and energy systems.
    Shahzad, Khurram
    KTH, School of Electrical Engineering (EES), Electric power and energy systems.
    Johnson, Pontus
    KTH, School of Electrical Engineering (EES), Electric power and energy systems.
    Integrated metamodel for security analysis2015In: 2015 48TH HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES (HICSS), IEEE Computer Society, 2015, p. 5192-5200Conference paper (Refereed)
    Abstract [en]

    This paper proposes a metamodel for analyzing security aspects of enterprise architecture by combining analysis of cybersecurity with analysis of interoperability and availability. The metamodel extends an existing attack graph based metamodel for cybersecurity modeling and evaluation, (PCySeMoL)-Cy-2, and incorporates several new elements and evaluation rules. The approach improves security analysis by combining two ways of evaluating reachability: one which considers ordinary user activity and another, which considers technically advanced techniques for penetration and attack. It is thus permitting to evaluate security in interoperability terms by revealing attack possibilities of legitimate users. Combined with data import from various sources, like an enterprise architecture data repository, the instantiations of the proposed metamodel allow for a more holistic overview of the threats to the architecture than the previous version. Additional granularity is added to the analysis with the reachability need concept and by enabling the consideration of unavailable and unreliable systems.

  • 11.
    Välja, Margus
    et al.
    KTH, School of Electrical Engineering (EES), Electric power and energy systems.
    Ladhe, Tobias
    Towards Smart City Marketplace at the example of Stockholm2015In: 2015 48TH HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES (HICSS), IEEE Computer Society, 2015, p. 2375-2384Conference paper (Refereed)
    Abstract [en]

    The authors in this paper argue that for cities to meet their smart city goals much more is needed than just top down solutions, or open city data. The authors suggest that a city aiming for future smartness should engage the citizens, the entrepreneurs and innovators of that city, in the creation of smart solutions via the platform that is, for the sake of argument in this paper, called "The Smart City Marketplace". The authors find that the platform fills a technological gap by allowing simplified business experimentation and mixing public data with private data, while providing support for the new type of knowledge based economy. For this platform, ideas have been drawn from interviews and workshops in Stockholm, and researchers in areas such as open innovation, platform strategy and smart cities.

  • 12.
    Välja, Margus
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Lagerström, Robert
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Ekstedt, Mathias
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Korman, Matus
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    A Requirements Based Approach for Automating Enterprise IT Architecture Modeling Using Multiple Data Sources2015In: 2015 IEEE 19th International Enterprise Distributed Object Computing Workshop (EDOCW), Adelaide, SA, 2015, p. 79-87Conference paper (Refereed)
    Abstract [en]

    Enterprise Architecture (EA) is an approach where models of an enterprise are used for decision support. An important part of EA is enterprise IT architecture. Creating models of both types can be a complex task. EA can be difficult to model due to unavailable business data, while in the case of enterprise IT architecture, there can be too much IT data available. Furthermore, there is a trend of a growing availability of data possibly useful for modeling. We call the process of making use of available data, automatic modeling. There have been previous attempts to achieve automatic model creation using a single source of data. Often, a single source of data is not enough to create the models required. In this paper we address automatic modeling when data from multiple heterogeneous sources are needed. The paper looks at the potential data sources, requirements that the data must meet and proposes a four-part approach. The approach is tested in a study using the Cyber Security Modeling Language in order to model a lab setup at KTH Royal Institute of Technology. The lab aims at mirroring a small power utility's IT setup. The paper demonstrates that it is possible to create timely and scalable enterprise IT architecture models from multiple sources, and that manual modeling and data quality related problems can be resolved using known data processing methods.

  • 13.
    Välja, Margus
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Lagerström, Robert
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Franke, Ulrik
    RISE ICT/SICS.
    Increasing Precision in IT Architecture Modeling using an Ontology FrameworkManuscript (preprint) (Other academic)
    Abstract [en]

    Modeling is a vital part of IT architecture management. However, it is a complex and resource demanding task. Automation of IT architecture modeling aims to simplify model creation using data already available. The data collected from enterprise systems, however, often lacks context. One reason is that the automated models become less precise in terms of domain knowledge than the ones that an expert human modeler would create. The lack of domain knowledge in modeling automation can be addressed with ontologies. In this paper we introduce an ontology based framework that has been developed to complement heterogeneous data from enterprise systems for the purpose of automatic modeling. The ontology itself is stored as a graph in a graph database. The framework is able to use the captured ontology to standardize software names for merging data across multiple sources, classify software products and vulnerabilities, and to group software names and data flows to adapt the granularity level of the data used in the model. The framework is shown to improve the precision of enterprise data and help to abstract the information to the required level in a case study. Three different data sets from a small scale utility lab, from a water utility control network, and from a university IT environment are analyzed.

  • 14.
    Välja, Margus
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Lagerström, Robert
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Franke, Ulrik
    RISE ICT/SICS.
    Ericsson, Göran
    KTH, School of Electrical Engineering and Computer Science (EECS).
    A framework for automatic IT architecture modeling: applying truth discoveryManuscript (preprint) (Other academic)
    Abstract [en]

    Modeling IT architecture is a complex, time consuming, and error prone task. However, many systems produce information that can be used in order to automate modeling. Early studies show that this is a feasible approach if we can overcome certain obstacles. Often more than one source is needed in order to cover the data requirements of an IT architecture model and the use of multiple sources means that heterogeneous data needs to be merged. Moreover, the same collection of data might be useful for creating more than one kind of model for decision support.

    IT architecture is constantly changing and data sources provide information that can deviate from reality to some degree. There can be problems with varying accuracy (e.g. actuality and coverage), representation (e.g. data syntax and file format), or inconsistent semantics. Thus, integration of heterogeneous data from different sources needs to handle data quality problems of the sources. This can be done by using probabilistic models. In the field of truth discovery, these models have been developed to track data source trustworthiness in order to help solving conflicts while making quality issues manageable for automatic modeling.

    We build upon previous research in modeling automation and propose a framework for merging data from multiple sources with a truth discovery algorithm to create multiple IT architecture models. The usefulness of the proposed framework is demonstrated in a study where models using three tools are created, namely; Archi, securiCAD, and EMFTA.

  • 15.
    Välja, Margus
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Lagerström, Robert
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Franke, Ulrik
    KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID. RISE Research Institutes of Sweden, 164 40 Kista, Sweden.
    Ericsson, Göran
    KTH, School of Electrical Engineering and Computer Science (EECS).
    A Framework for Automatic IT Architecture Modeling: Applying Truth Discovery2019In: Complex Systems Informatics and Modeling Quarterly, E-ISSN 2255-9922, no 20Article in journal (Refereed)
    Abstract [en]

    Modeling IT architecture is a complex, time consuming, and error prone task. However, many systems produce information that can be used for automating modeling. Early studies show that this is a feasible approach if we can overcome certain obstacles. Often more than one source is needed in order to cover the data requirements of an IT architecture model; and the use of multiple sources means that heterogeneous data needs to be merged. Moreover, the same collection of data might be useful for creating more than one kind of models for decision support. IT architecture is constantly changing and data sources provide information that can deviate from reality to some degree. There can be problems with varying accuracy (e.g. actuality and coverage), representation (e.g. data syntax and file format), or inconsistent semantics. Thus, integration of heterogeneous data from different sources needs to handle data quality problems of the sources. This can be done by using probabilistic models. In the field of truth discovery, these models have been developed to track data source trustworthiness in order to help solving conflicts while making quality issues manageable for automatic modeling. We build upon previous research in modeling automation and propose a framework for merging data from multiple sources with a truth discovery algorithm to create multiple IT architecture models. The usefulness of the proposed framework is demonstrated in a study where models using three tools are created, namely; Archi, securiCAD, and EMFTA.

  • 16.
    Välja, Margus
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Lagerström, Robert
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Korman, Matus
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Franke, Ulrik
    Bridging the gap between business and technology in strategic decision-making for cyber security management2016In: Proceedings of 2016 Portland International Conference on Management of Engineering and Technology, 2016, p. 32-42Conference paper (Refereed)
    Abstract [en]

    System architectures are getting more and more complex. Thus, making strategic decisions when it comes to managing systems is difficult and needs proper support. One arising issue that managers need to take into account when changing their technology is security. No business is spared from threats in today's connected society. The repercussions of not paying this enough attention could result in loss of money and in case of cyber physical systems, also human lives. Thus, system security has become a high-level management issue. There are various methods of assessing system security. A common method that allows partial automation is attack graph based security analysis. This particular method has many variations and wide tool support. However, a complex technical analysis like the attack graph based one needs experts to run it and interpret the results. In this paper we study what kind of strategic decisions that need the support of threat analysis and how to improve an attack graph based architecture threat assessment method to fit this task. The needs are gathered from experts working with security management and the approach is inspired by an enterprise architecture language called ArchiMate. The paper contains a working example. The proposed approach aims to bridge the gap between technical analysis and business analysis making system architectures easier to manage.

  • 17.
    Välja, Margus
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Österlind, Magnus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Iacob, Maria-Eugenia
    University of Twente, Enschede, Centre for Telematics and Information Technology.
    van Sinderen, Marten
    University of Twente, Enschede, Centre for Telematics and Information Technology.
    Johnson, Pontus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Modeling and prediction of monetary and non-monetary business values2013In: 2013 17th IEEE International Enterprise Distributed Object Computing Conference (EDOC), IEEE , 2013, p. 153-158Conference paper (Refereed)
    Abstract [en]

    In existing business model frameworks little attention is paid to a thorough understanding of the perceived customer value of a business' offering as compared to competing offers. In this paper, we propose to use utility theory in combination with e3value models to address this issue. An actor's joint utility function specifies how much value the actor attaches to a given product or service's different qualities. Competing value offerings map to different points on the customer utility function, since they provide certain quantities of each quality. Since the customer can be expected to exhibit a utility maximizing behavior, his/her choices between offerings can be predicted. Thus, given the proposed utility extension, it becomes possible to quantitatively reason about the relative customer value of an offering compared to those of the competition. This, in turn, allows the optimization of price, the key ingredient in any business model.

  • 18.
    Österlind, Magnus
    et al.
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Johnson, Pontus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Karnati, Kiran
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Lagerström, Robert
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Välja, Margus
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Enterprise Architecture Evaluation using Utility theory2013In: Proceedings 17th IEEE International Enterprise Distributed Object Computing Conference Workshops (EDOCW), IEEE Computer Society, 2013, p. 347-351Conference paper (Refereed)
    Abstract [en]

    With the increase in the number of quality attributes (e.g. cost, availability, reusability), that are being considered in the process of enterprise architecture analysis, the decision maker needs a systematic way to balance these attributes against each other to obtain the best possible architecture. Utility theory addresses this need by providing methods for numerical representation of preferences of a stakeholder involved in a decision-making process. In this paper utility theory key concepts are explained with examples. The process of calculating the utility metric, which reflects stake holder's set of preferences to select the most preferred architecture scenario is explained. The paper provides an explanation of how utility theory can be applied in enterprise architecture models which are meta-object facility compliant. This paper concludes by an example comparing two quality attributes on two architecture scenarios using utility theory and calculating the decision maker's overall utility metric across both quality attributes is provided. This shows the applicability of utility theory on architecture scenario analysis with multiple quality attributes.

1 - 18 of 18
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf