DOCSLIB.ORG

The Information Value of Unstructured Analyst Opinions – Studies on the Determinants of Information Value and Its Relationship to Capital Markets

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
The Information Value of Unstructured Analyst Opinions – Studies on the Determinants of Information Value and Its Relationship to Capital Markets The Information Value of Unstructured Analyst Opinions – Studies on the Determinants of Information Value and its Relationship to Capital Markets Dissertation zur Erlangung des wirtschaftswissenschaftlichen Doktorgrades der Wirtschaftswissenschaftlichen Fakultät der Georg-August-Universität Göttingen Vorgelegt von: Matthias Eickhoff, M.Sc. Göttingen, 2017 Betreuungsausschuss Erstbetreuer Prof. Dr. Jan Muntermann Zweitbetreuer Prof. Dr. Matthias Schumann Drittbetreuer Prof. Dr. Lutz M. Kolbe ii Table of Contents List of Figures ...................................................................................................... v List of Tables ....................................................................................................... vi Abbreviations ..................................................................................................... vii Symbols .............................................................................................................. viii A. Foundations .............................................................................................. 1 1 Motivation ................................................................................................. 1 2 Research Questions.................................................................................... 3 3 Structure of the Thesis ............................................................................... 6 3.1 Part A: Foundations ......................................................................... 7 3.2 Part B: Research Areas .................................................................... 7 3.3 Part C: Contributions ....................................................................... 9 4 Research Background .............................................................................. 10 4.1 The Information Value of Analyst Opinion .................................. 10 4.2 Theoretical Background ................................................................ 12 4.2.1 Wisdom of Crowds........................................................... 12 4.2.2 Decision Making and Information Overload ................... 13 4.2.3 Media Richness Theory .................................................... 14 4.3 Methods ......................................................................................... 16 4.3.1 Text Mining Pre-Processing ............................................. 16 4.3.2 Sentiment Analysis ........................................................... 17 4.3.3 Topic Modeling ................................................................ 19 4.3.4 Event Study Analysis ....................................................... 21 4.3.5 Literature Review ............................................................. 22 4.3.6 Taxonomy Development .................................................. 23 4.4 Datasets.......................................................................................... 25 4.4.1 Social Media ..................................................................... 25 4.4.2 News Media...................................................................... 26 4.4.3 Analyst Opinion ............................................................... 26 4.4.4 Startup Profiles ................................................................. 28 5 Research Paradigms ................................................................................. 29 5.1 Behavioral Science ........................................................................ 29 5.2 Design Science .............................................................................. 31 iii B. Studies: Individual Research Contributions ............................................... 32 I. Research Area: Entrepreneurial Environment .......................................... 33 I.1. FinTech Business Model Taxonomy ......................................................... 34 II. Research Area: Methodological .................................................................. 35 II.1. Topic Modelling Methodology Review .................................................... 36 1 Introduction ............................................................................................. 37 2 Topic Models ........................................................................................... 38 2.1 Meta theoretical Foundations of Topic Modelling Research ........ 39 3 Research Design ...................................................................................... 40 1.1 Phase 1: Identify a Research Goal ................................................. 40 3.1 Phase 2: Research Methodology ................................................... 41 3.2 Phase 3: Analysis ........................................................................... 42 4 Results and Discussion ............................................................................ 44 5 Conclusion ............................................................................................... 49 II.2. Hybrid Sentiment Analysis Framework ................................................. 53 III. Research Area: Analyst Opinion ............................................................... 54 III.1. Stock Analysts vs. the Crowd ................................................................. 55 III.2. Identifying relevant Topics in Business Communication..................... 56 III.3. Topic Transfer between Earnings Calls and Analyst Reports ............ 57 1 Introduction ............................................................................................. 58 2 Theoretical Background .......................................................................... 58 3 Data and Pre-Processing .......................................................................... 60 4 Method ..................................................................................................... 61 5 Results ..................................................................................................... 63 5.1 Limitations ..................................................................................... 65 5.2 Future Research ............................................................................. 65 6 Conclusion ............................................................................................... 67 III.4. Media Richness and the Information Value of Analyst Opinion ........ 68 1 Introduction ............................................................................................. 69 2 Theory ...................................................................................................... 69 2.1 Analyst opinion ............................................................................. 69 2.2 Media Richness Theory ................................................................. 71 3 Structured, unstructured Data and Media Richness Theory .................... 73 3.1 Low Richness (Structured Data) ................................................... 73 3.2 High Richness (Unstructured Data)............................................... 74 4 Method ..................................................................................................... 75 iv 4.1 Sentiment Analysis ........................................................................ 75 4.2 Topic Mining ................................................................................. 76 4.3 Abnormal Returns ......................................................................... 77 4.4 Topic Selection .............................................................................. 78 5 Analysis and Results ................................................................................ 80 5.1 Implications and Limitations ......................................................... 82 5.2 Future Research ............................................................................. 83 6 Conclusion ............................................................................................... 84 C. Contributions ......................................................................................... 85 1 Summary of Results................................................................................. 86 1.1 Research Area I: Entrepreneurial Environment ............................ 86 1.2 Research Area II: Methodological ................................................. 87 1.3 Research Area III: Analyst Opinion .............................................. 89 2 Implications ............................................................................................. 94 2.1 Research Area I: Entrepreneurial Environment ............................ 94 2.2 Research Area II: Methodological ................................................. 95 2.3 Research Area III: Analyst Opinion .............................................. 95 3 Limitations ............................................................................................... 98 3.1 Research Area I: Entrepreneurial Environment ............................ 98 3.2 Research Area II: Methodological ................................................. 98 3.3 Research Area III: Analyst Opinion .............................................. 98 4 Future Research ..................................................................................... 100 4.1 Research Area I: Entrepreneurial Environment .......................... 100 4.2 Research Area II: Methodological ............................................... 100 4.3 Research Area III:
Load more

Recommended publications
  • The Sciences of Design: Observations on an Emerging Field Working Paper
    The Sciences of Design: Observations on an Emerging Field Sandeep Purao Carliss Y. Baldwin Alan Hevner Veda C. Storey Jan Pries-Heje Brian Smith Ying Zhu Working Paper 09-056 Copyright © 2008 by Sandeep Purao, Carliss Y. Baldwin, Alan Hevner, Veda C. Storey, Jan Pries-Heje, Brian Smith, and Ying Zhu Working papers are in draft form. This working paper is distributed for purposes of comment and discussion only. It may not be reproduced without permission of the copyright holder. Copies of working papers are available from the author. The Sciences of Design: Observations on an Emerging Field Sandeep Purao College of IST, Penn State University, Carliss Baldwin Harvard Business School Alan Hevner University of South Florida Veda C. Storey Georgia State University Jan Pries-Heje Roskilde University Brian Smith Penn State University Ying Zhu Georgia State University Excerpted from The Sciences of Design: Observations on an Emerging Field by Purao, Baldwin, Hevner, Storey, Pries-Heje, Smith and Zhu, (c) 2008. Used with permission from Association for Information Systems, Atlanta, GA; 404-413-7444; www.aisnet.org. All rights reserved. Working papers are in draft form. This working paper is distributed for purposes of comment and discussion only. It may not be reproduced without permission of the copyright holder. Copies of working papers are available from the authors. THE SCIENCES OF DESIGN OCTOBER 9, 2008 ABSTRACT The boundaries and contours of design sciences continue to undergo definition and refinement. In many ways, the sciences of design defy disciplinary characterization. They demand multiple epistemologies, theoretical orientations (e.g. construction, analysis or intervention) and value considerations.
    [Show full text]
  • Design Science Research and the Grounded Theory
    Association for Information Systems AIS Electronic Library (AISeL) European Conference on Information Systems ECIS 2010 Proceedings (ECIS) 2010 Design Science Research and the Grounded Theory Method: Characteristics, Differences, and Complementary Uses Robert Gregory Goethe University Frankfurt, [email protected] Follow this and additional works at: http://aisel.aisnet.org/ecis2010 Recommended Citation Gregory, Robert, "Design Science Research and the Grounded Theory Method: Characteristics, Differences, and Complementary Uses" (2010). ECIS 2010 Proceedings. 44. http://aisel.aisnet.org/ecis2010/44 This material is brought to you by the European Conference on Information Systems (ECIS) at AIS Electronic Library (AISeL). It has been accepted for inclusion in ECIS 2010 Proceedings by an authorized administrator of AIS Electronic Library (AISeL). For more information, please contact [email protected]. 18th European Conference on Information Systems DESIGN SCIENCE RESEARCH AND THE GROUNDED THEORY METHOD: CHARACTERISTICS, DIFFERENCES, AND COMPLEMENTARY USES Journal: 18th European Conference on Information Systems Manuscript ID: ECIS2010-0045.R1 Submission Type: Research Paper Research methods/methodology, Design/design science, Behavioral Keyword: science, IS research methodologies Page 1 of 12 18th European Conference on Information Systems DESIGN SCIENCE RESEARCH AND THE GROUNDED THEORY METHOD: CHARACTERISTICS, DIFFERENCES, AND COMPLEMENTARY USES Gregory, Robert Wayne, Goethe University Frankfurt, Grüneburgplatz 1, 60323 Frankfurt am Main, Germany, [email protected] Abstract Two research strategies that have received increasing scholarly attention recently in IS are design science research (DSR) and the grounded theory method (GTM). In this paper, we conduct a systematic comparison of the most salient characteristics of both research strategies to identify the differences as well as possible complementary uses in a pluralistic research design.
    [Show full text]
  • An Application of the Design Science Research Theoretical Framework
    Journal of Advances in Information Technology Vol. 7, No. 4, November 2016 An Application of the Design Science Research Theoretical Framework and Methodology in the Construction of an Approach for Designing Applications in 3D Virtual Worlds William Sawyerr Anglia Ruskin University, Cambridge, United Kingdom Email: [email protected] Abstract—This paper discusses the use of the design science In spite of these ideals, the application development research theoretical framework and methodology for process in VWs is currently at an early stage of constructing an approach for designing applications in 3D development, largely utilising existing methods and tools virtual worlds. The research is about the need for a suitable for application design. These methods and tools were method and tools for designing virtual world applications, mostly developed for managing application design which is evidenced by many of the problems that virtual worlds continue to suffer due to poor design. The proposed activities for the classic types of applications in SE. approach uses the generative design grammar framework Therefore, their use is unsuitable for designing VW and the generative design agent model as tools for designing applications. The use of unsuitable methods and tools for virtual world applications. Preliminary analyses suggest designing VW applications results in poorly designed that, the use of a method and tools created specifically for specifications. Poor design is one of the causes of designing virtual world applications provides a suitable and usability problems in VW applications [2]. Furthermore, robust approach for designing these types of applications. poor design can also adversely affect the adoption and use of VWs [3], [4].
    [Show full text]
  • Understanding the Creative Mechanisms of Design Thinking: an Evolutionary Approach
    !"#$%&'("#)"*+',$+-%$(').$+/$0,(")&1&+23+4$&)*"+5,)"6)"*7+ 8"+9.2:;')2"(%<+8==%2(0,+ Katja Thoring Roland M. Müller Department of Design Faculty of Business and Economics Anhalt University of Applied Sciences Berlin School of Economics and Law Seminarplatz 2a, 06846 Dessau/Germany Badensche Str. 50/51, 10825 Berlin/Germany +49 (0) 340 5197-1747 +49 (0) 30 85789-387 [email protected] [email protected] 8>?5@8-5+ Since generating creative concepts is one of the core aims In this article, we analyse the concept of design thinking of design thinking, we try to analyse how this is actually with its process, the team structure, the work environment, achieved. The first part of this article presents a short the specific culture, and certain brainstorming rules and overview of the design thinking process, as well as the techniques. The goal of this work is to understand how the involved artefacts and team members, and the underlying creative mechanisms of design thinking work and how they principles and guidelines for the process. In the second might be improved. For this purpose, we refer to the idea of section, we present an overview of the evolutionary theory creativity as an evolutionary process, which is determined of creativity. Both sections also cover the analysis of by generation (i.e., recombination and mutation), selection, existing literature in each area. The third section describes and retention of ideas. We evaluate the design thinking the used methodology, while in the fourth section, the main process in terms of its capabilities to activate these part of this article, we draw a comparison between the two mechanisms, and we propose possible improvements.
    [Show full text]
  • Information Systems Foundations: the Role of Design Science
    Information Systems Foundations: The role of design science Information Systems Foundations: The role of design science Dennis N. Hart and Shirley D. Gregor (Editors) THE AUSTRALIAN NATIONAL UNIVERSITY E P R E S S E P R E S S Published by ANU E Press The Australian National University Canberra ACT 0200, Australia Email: [email protected] This title is also available online at: http://epress.anu.edu.au/is_foundations_citation.html National Library of Australia Cataloguing-in-Publication entry Author: Information Systems Foundations (‘The role of design science’) Workshop (2008 : Canberra, A.C.T.) Title: Information systems foundations : the role of design science / edited by Shirley D. Gregor and Dennis N. Hart. ISBN: 9781921666346 (pbk.) ISBN: 9781921666353 (eBook) Notes: Workshop held at the Australian National University in Canberra from 2-3 October, 2008. Includes bibliographical references. Subjects: Management information systems--Congresses. Information resources management--Congresses. System design--Congresses. Other Authors/Contributors: Gregor, Shirley Diane. Hart, Dennis N. Dewey Number: 658.4038 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying or otherwise, without the prior permission of the publisher. Cover design by Teresa Prowse Cover ilustration by Jackson Gable Printed by Griffin Press This edition © 2010 ANU E Press Contents Preface . ix Philosophical Foundations 1 . Identification-interaction-innovation: a phenomenological basis for an information services view . 3 Dirk Hovorka, Matt Germonprez 2 . How critical realism clarifies validity issues in theory- testing research: analysis and case . 21 Robert B. Johnston, Stephen P.
    [Show full text]
  • Uncovering Topological Generativity with a Ck Model of Evolutionary
    INTERNATIONAL CONFERENCE ON ENGINEERING DESIGN, ICED21 16-20 AUGUST 2021, GOTHENBURG, SWEDEN WHAT IS GENERATIVE IN GENERATIVE DESIGN TOOLS? UNCOVERING TOPOLOGICAL GENERATIVITY WITH A C-K MODEL OF EVOLUTIONARY ALGORITHMS. Hatchuel, Armand; Le Masson, Pascal; Thomas, Maxime; Weil, Benoit MINES ParisTech-PSL ABSTRACT Generative design (GD) algorithms is a fast growing field. From the point of view of Design Science, this fast growth leads to wonder what exactly is 'generated' by GD algorithms and how? In the last decades, advances in design theory enabled to establish conditions and operators that characterize design generativity. Thus, it is now possible to study GD algorithms with the lenses of Design Science in order to reach a deeper and unified understanding of their generative techniques, their differences and, if possible, find new paths for improving their generativity. In this paper, first, we rely on C-K ttheory to build a canonical model of GD, based independent of the field of application of the algorithm. This model shows that GD is generative if and only if it builds, not one single artefact, but a "topology of artefacts" that allows for design constructability, covering strategies, and functional comparability of designs. Second, we use the canonical model to compare four well documented and most advanced types of GD algorithms. From these cases, it appears that generating a topology enables the analyses of interdependences and the design of resilience. Keywords: C-K theory, generative design algorithms, Design theory, Computational design methods, Design informatics Contact: Le Masson, Pascal MINES ParisTech-PSL Management Science France [email protected] Cite this article: Hatchuel, A., Le Masson, P., Thomas, M., Weil, B.
    [Show full text]
  • A Set of Systemic Design Tools for the Design of Flourishing Local Fashion Systems Marion Real, Iban Lizarralde
    A set of systemic design tools for the design of flourishing local fashion systems Marion Real, Iban Lizarralde To cite this version: Marion Real, Iban Lizarralde. A set of systemic design tools for the design of flourishing local fashion systems. Relating Systems Thinking and Design 6 (RSD6), Systemic Design Research Network, Birger Sevaldson, Oslo Architecture of School, Oct 2017, Oslo, Norway. hal-01703912 HAL Id: hal-01703912 https://hal.archives-ouvertes.fr/hal-01703912 Submitted on 8 Feb 2018 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. RSD6 Relating Systems Thinking and Design 2017 working paper. www.systemic-design.net A set of systemic design tools for the design of flourishing local fashion systems Working Paper REAL Marion Post-doctoral studies in Systemic Design for the Retrace project dedicated to Circular Economy ESTIA Recherche, ESTIA LIZARRALDE Iban Researcher in Eco-Design and complex system engineering ESTIA Recherche, ESTIA Context and issues Our research is part of a new decentralized vision of the territories and takes part in the construction of new socio-technical models of circular economy, which seek to increase the environmental efficiency of processes, optimize the use of accessible resources and the autonomy of stakeholders in regional ecosystems.
    [Show full text]
  • Contemporary Processes of Text Typeface Design
    Title Contemporary processes of text typeface design Type The sis URL https://ualresearchonline.arts.ac.uk/id/eprint/13455/ Dat e 2 0 1 8 Citation Harkins, Michael (2018) Contemporary processes of text typeface design. PhD thesis, University of the Arts London. Cr e a to rs Harkins, Michael Usage Guidelines Please refer to usage guidelines at http://ualresearchonline.arts.ac.uk/policies.html or alternatively contact [email protected] . License: Creative Commons Attribution Non-commercial No Derivatives Unless otherwise stated, copyright owned by the author Contemporary processes of text typeface design Michael Harkins Thesis submitted for the degree of Doctor of Philosophy Central Saint Martins University of the Arts London April 2018 This thesis is dedicated to the memory of my brother, Lee Anthony Harkins 22.01.17† and my father, Michael Harkins 11.04.17† Abstract Abstract Text typeface design can often be a lengthy and solitary endeavour on the part of the designer. An endeavour for which, there is little in terms of guidance to draw upon regarding the design processes involved. This is not only a contemporary problem but also an historical one. Examination of extant accounts that reference text typeface design aided the orientation of this research (Literature Review 2.0). This identified the lack of documented knowledge specific to the design processes involved. Identifying expert and non-expert/emic and etic (Pike 1967) perspectives within the existing literature helped account for such paucity. In relation to this, the main research question developed is: Can knowledge of text typeface design process be revealed, and if so can this be explicated theoretically? A qualitative, Grounded Theory Methodology (Glaser & Strauss 1967) was adopted (Methodology 3.0), appropriate where often a ‘topic of interest has been relatively ignored in the literature’ (Goulding 2002, p.55).
    [Show full text]
  • Design Science by Aaron Kurosu.Pdf
    DESIGN SCIENCE AN EMPIRICAL AND QUANTITATIVE APPROACH Aaron Kurosu, IDSA Princeton University 1. INTRODUCTION Open up a photo on an iPhone. You’ll see a little icon that looks like a sparkling wand. Press it to ‘enhance’ your photo. Just like magic, the photo will probably look better. Why? Because science has been making progress to demystify preferences and aesthetics (e.g., Brachmann & Redies, 2017; Cela- Conde et al., 2013; Sun, Yamasaki, & Aizawa, 2018; Yeh, Lin, Hsu, Kuo, & Chan, 2015). It’s not just with photos; all the “stuff” that we like are being picked apart. Open up Netflix, there’s some films you might like; open up Spotify, there’s some new music you might like; open up Amazon, there’s some new products you might like. How is this possible? Certainly, these companies are not running focus groups to figure out the preferences of every customer (Stromberg, 2019). Instead, they are building algorithms; they are testing theories; and they are capitalizing on the scientific method (e.g., Linden, Smith, & York 2003; Bennet & Lanning, 2007; Jacobson, Murali, Newett, Whitman, & Yon, 2016). A method, that is providing products which others, who clack clear understanding, are left to interpret as magic. Strickler forewarned in 1999, “if designers do not begin to undertake this important work, others will, and without the benefit of a designer’s perspective.” The purpose of this paper is to inspire a new generation of designers to research their craft using the scientific method. 2. DEFINITIONS A secondary aim of this paper is to clean up jargon in design research.
    [Show full text]
  • Design Science Research in Information Systems
    DESIGN SCIENCE RESEARCH IN INFORMATION SYSTEMS Section Editors: Vijay Vaishnavi, Bill Kuechler, and Stacie Petter Additional Contributors: Gerard De Leoz [Overview of Design Science Research] [Design Science Research Methodology] [Philosophical Grounding of Design Science Research] [Outputs of Design Science Research] [An Exemplar of IS Design Science Research] [Design Science Research Bibliography] WELCOME The intent of the Design Science Research in Information Systems (IS) page is to provide design science researchers in IS as well as others interested in design science research with useful information regarding understanding, conducting, evaluating, and publishing design science research. The goal of this page is to provide the IS community with useful information on design science research, both in and outside of the field of information systems. The page contains numerous citations permitting the interested reader to easily access original cited material on and examples of this unique and dynamic IS research paradigm. If you wish to cite this work, here is the complete citation information. Please send suggestions for improvements to the Section Editors at: [email protected] or [email protected]. INTRODUCTION Design science research is a "lens" or set of synthetic and analytical techniques and perspectives (complementing positivist, interpretive, and critical perspectives) for performing research in IS. Design science research typically involves the creation of an artifact and/or design theory as a means to improve the current state of practice as well as existing research knowledge (Baskerville, et al. 2018). Design science research that focuses on the development of artifacts involves two primary activities to improve and understand the behavior of aspects of Information Systems: (1) the creation of new knowledge through design of novel or innovative artifacts (things or processes) and (2) the analysis of the artifact’s use and/or performance with reflection and abstraction.
    [Show full text]
  • A Survey of Value Sensitive Design Methods
    Full text available at: http://dx.doi.org/10.1561/1100000015 A Survey of Value Sensitive Design Methods Batya Friedman The Information School University of Washington, USA [email protected] David G. Hendry The Information School University of Washington, USA [email protected] Alan Borning Paul G. Allen School of Computer Science & Engineering University of Washington, USA [email protected] Boston — Delft Full text available at: http://dx.doi.org/10.1561/1100000015 Foundations and Trends R in Human-Computer Interaction Published, sold and distributed by: now Publishers Inc. PO Box 1024 Hanover, MA 02339 United States Tel. +1-781-985-4510 www.nowpublishers.com [email protected] Outside North America: now Publishers Inc. PO Box 179 2600 AD Delft The Netherlands Tel. +31-6-51115274 The preferred citation for this publication is B. Friedman, D. G. Hendry and A. Borning. A Survey of Value Sensitive Design Methods. Foundations and Trends R in Human-Computer Interaction, vol. 11, no. 23, pp. 63–125, 2017. R This Foundations and Trends issue was typeset in LATEX using a class file designed by Neal Parikh. Printed on acid-free paper. ISBN: 978-1-68083-290-7 c 2017 B. Friedman, D. G. Hendry and A. Borning All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, mechanical, photocopying, recording or otherwise, without prior written permission of the publishers. Photocopying. In the USA: This journal is registered at the Copyright Clearance Cen- ter, Inc., 222 Rosewood Drive, Danvers, MA 01923.
    [Show full text]
  • Dynamic Software Architectures
    Dynamic Software Architectures A Style-Based Modeling and Refinement Technique with Graph Transformations DISSERTATION in Computer Science submitted to the Faculty of Computer Science, Electrical Engineering, and Mathematics University of Paderborn by Sebastian Th¨one in partial fulfillment of the requirements for the degree of doctor rerum naturalium (Dr. rer. nat.) Paderborn, October 2005 ii Abstract A good architectural design allows to capture the overall complexity of large, distributed systems at a higher level of abstraction. This is especially im- portant for reconfigurable systems where the architectural configuration is subject to (constant) changes at runtime. When designing such a dynamic architecture, the software architect has to bring the functional business re- quirements and the available communication and reconfiguration mechanisms of the intended target platform in line. As it is a complex task to incorporate these often diverging requirements into the architectural model, we propose a stepwise approach similar to the MDA initiative. We start with a platform-independent model capturing the business requirements and add platform-specific details in a later step. For each level of platform abstraction and associated platform, we define an ar- chitectural style which describes the characteristics of the platform. This way, conformance to the architectural style entails consistency between model and the underlying platform. Besides run-time configurations of components and connections, archi- tectural models also comprise the description of processes that control the communication and reconfiguration behavior. To provide operational seman- tics, we formalize architectural models as graphs and architectural styles as graph transformation systems. UML is added as high-level modeling language on top, and profiles are used to adapt UML to certain architectural styles.
    [Show full text]