22 research outputs found
Process Instance Query Language to Include Process Performance Indicators in DMN
Companies are increasingly incorporating commercial
Business Process Management Systems (BPMSs) as mechanisms
to automate their daily procedures. These BPMSs manage
the information related to the instances that flow through the
model (business data), and recover the information concerning
the process performance (Process Performance Indicators).
Process Performance Indicators (PPIs) tend to be used for the
detection of possible deviations of expected behaviour, and help in
the post-mortem analysis and redesign by improving the goals of
the processes. However, not only are PPIs important in terms of
their ability to measure and detect a derivation, but they should
also be included at decision points to make the business processes
more adaptable to the process reality at runtime. In this paper,
we propose a complete solution that allows the incorporation of
the PPIs into decision tasks, following the Decision Model and
Notation (DMN) standard, with the aim of enriching the decisions
that can be taken during the process execution. Our proposal
firstly includes an extension of the decision rule grammar of the
DMN standard, by incorporating the definition and the use of a
Process Instance Query Language (PIQL) that offers information
about the instances related to the PPIs involved. In order to
achieve this objective, a framework has also been developed to
support the enrichment of process instance query expressions
(PIQEs). This framework combines a set of mature technologies
to evaluate the decisions about PPIs at runtime. As an illustration
a real sample has been used whose decisions are improved thanks
to the incorporation of the PPIs at runtime.Ministerio de Ciencia y Tecnología TIN2015-63502-C3-2-
Capability-actor-resource-service : a conceptual modelling approach for value-driven strategic sourcing
This PhD research addresses a problem within strategic sourcing, which is a critical area of strategic management that is centered on decision-making related to procurement. Strategic sourcing is related to two disciplines: (i) procurement and supply management and (ii) strategic management. Sourcing is the strategic part of procurement that refers to tasks like determining cost saving and value-driven opportunities, choosing the most appropriate go-to market strategies, and selecting and evaluating suppliers for building long-term and short-term contractual relationships. Many companies face challenges in obtaining the benefits associated with effective strategic sourcing. Although the concept of strategic sourcing is fairly well recognized, managers are still challenged by many barriers to its implementation. The main problem is the lack of practical instruments (i.e., tools and techniques) to implement the value-driven management approach to strategic sourcing, while at the same time preparing companies for fact-based decision-making by delivering data management and data analytics capabilities. This is the problem which is addressed with this PhD research. To address this problem, the research goal has been defined as “develop a modeling approach that enables companies 1) to drive fact-based decision-making with respect to procurement data management and procurement analytics”; and 2) to implement strategic sourcing toward achieving value-driven targets”. We apply conceptual modeling as our main solution approach to achieve the above research goal. We define three major areas where conceptual modeling can contribute to strategic sourcing decision-making: conceptualization, design and computer support. The proposed conceptual modeling approach is characterized by four different perspectives: (i) a way of thinking (i.e., a conceptual foundation), (ii) a way of modeling (i.e., a modeling language and method to use it), (iii) a way of working (i.e., a model-based analysis approach), and (iv) a way of supporting (i.e., a computer-aided design tool). The scope of PhD research is limited to the first three perspectives, while for the fourth perspective a solution architecture will be proposed as part of future research. This PhD dissertation is a paper-based dissertation consisting of six chapters. Three chapters (chapter 3, 4, 5) of this dissertation have been submitted to international peer-reviewed journals (chapter 4 is published and chapters 3 and 5 are accepted) and one chapter (chapter 2) has been published in the post-conference proceedings of an international workshop
A systematic investigation of risk management and process mining ontologies
Διπλωματική εργασία--Πανεπιστήμιο Μακεδονίας, Θεσσαλονίκη, 2019.This study proposes and examines the ‘’Risk – Process’’ ontology with respect to and in comparison with the Process mining methodology. The ontology consists of Process elements (Process Mining, Business Process Management and Business Process Intelligence) and Risk elements (Governance, Risk Management & Compliance, Internal Audit and Enterprise Risk Management). A two-fold literature review is executed, focusing firstly on the six key elements of the ‘’Risk - Process’’ ontology, and secondly at the “Risk” components of the ontology. Moving on, as an original contribution, the popularity and the coherence of the aforementioned elements in internet searches from 2004 to 2018 is presented and forecasted with the use of the Google Trends tool. As a last step, a statistical analysis of the time series obtained through Google Trends is performed, in order to find relation, correlations, statistical significance and predictors with respect to Process minin
Semantic Model Alignment for Business Process Integration
Business process models describe an enterprise’s way of conducting business and in this form the basis for shaping the organization and engineering the appropriate supporting or even enabling IT. Thereby, a major task in working with models is their analysis and comparison for the purpose of aligning them. As models can differ semantically not only concerning the modeling languages used, but even more so in the way in which the natural language for labeling the model elements has been applied, the correct identification of the intended meaning of a legacy model is a non-trivial task that thus far has only been solved by humans. In particular at the time of reorganizations, the set-up of B2B-collaborations or mergers and acquisitions the semantic analysis of models of different origin that need to be consolidated is a manual effort that is not only tedious and error-prone but also time consuming and costly and often even repetitive. For facilitating automation of this task by means of IT, in this thesis the new method of Semantic Model Alignment is presented. Its application enables to extract and formalize the semantics of models for relating them based on the modeling language used and determining similarities based on the natural language used in model element labels. The resulting alignment supports model-based semantic business process integration. The research conducted is based on a design-science oriented approach and the method developed has been created together with all its enabling artifacts. These results have been published as the research progressed and are presented here in this thesis based on a selection of peer reviewed publications comprehensively describing the various aspects
Understanding service modularity - antecedents, processes, and operationalization
The concept of service modularity has emerged as a promising solution to achieve a sound balance between growing customer requirements for individualization and a companya s necessity to standardize services for cost efficiency reasons. Although service modularity has been on the academic agenda for some time, not many examples of modularized service portfolios can be identified. Therefore, this dissertation aims to examine service modularity in the context of professional services by connecting the decisions made before, during, and after service modularization with a specific focus on the effect on the sales process. The enhanced understanding of the concept is expected to uncover new research gaps in service modularity, as well as promote its application in the context of professional services. Apart from its theoretical contribution, this dissertation will provide practitioners with an improved understanding with respect to what it means to offer a modular service portfolio, what needs to be done for the transformation, as well as what to expect from its completion
The GOALS approach: business and software modeling traceability by means of human-computer interaction: enterprise modeling language and method
The management of an enterprise relies on the continuous organization and development of its business and software systems. A process that requires merging the ideas of the enterprise’ systems managers, targeting the specification of business requirements and the conception and implementation of a supporting information system. This process finds obstacles in the identification and communication of requirements, and also in their transformation in software artefacts, leading to difficulties or loss of traceability between business and software models. Existing methods, languages and techniques are still not sufficiently standardized to ensure that when a business improvement is introduced, the supportive software solution will be implemented within budget and time. Methods are still too closed to the concepts of their original scientific domains, conceiving solutions which are not representative of the business and software conceptual relation and of the complexity concealed in an improvement effort, namely concerning usability and user experience. Moreover, the lack of a common modeling language and method for the conception of holistic and traceable software solutions, also refrains the performance of the enterprise development process. The GOALS Approach presents a solution to surpass these barriers by means of the specification of an enterprise modeling language that relates the business and software conceptual structures using a shared set of concepts, a notation, process, method and techniques, that allow the design of the software as a result of the business organization, ensuring traceability by means of the permanent representation of the business structure in the software structure
Äriprotsesside ajaliste näitajate selgitatav ennustav jälgimine
Kaasaegsed ettevõtte infosüsteemid võimaldavad ettevõtetel koguda detailset informatsiooni äriprotsesside täitmiste kohta. Eelnev koos masinõppe meetoditega võimaldab kasutada andmejuhitavaid ja ennustatavaid lähenemisi äriprotsesside jõudluse jälgimiseks. Kasutades ennustuslike äriprotsesside jälgimise tehnikaid on võimalik jõudluse probleeme ennustada ning soovimatu tegurite mõju ennetavalt leevendada.
Tüüpilised küsimused, millega tegeleb ennustuslik protsesside jälgimine on “millal antud äriprotsess lõppeb?” või “mis on kõige tõenäolisem järgmine sündmus antud äriprotsessi jaoks?”. Suurim osa olemasolevatest lahendustest eelistavad täpsust selgitatavusele. Praktikas, selgitatavus on ennustatavate tehnikate tähtis tunnus. Ennustused, kas protsessi täitmine ebaõnnestub või selle täitmisel võivad tekkida raskused, pole piisavad. On oluline kasutajatele seletada, kuidas on selline ennustuse tulemus saavutatud ning mida saab teha soovimatu tulemuse ennetamiseks.
Töö pakub välja kaks meetodit ennustatavate mudelite konstrueerimiseks, mis võimaldavad jälgida äriprotsesse ning keskenduvad selgitatavusel. Seda saavutatakse ennustuse lahtivõtmisega elementaarosadeks. Näiteks, kui ennustatakse, et äriprotsessi lõpuni on jäänud aega 20 tundi, siis saame anda seletust, et see aeg on moodustatud kõikide seni käsitlemata tegevuste lõpetamiseks vajalikust ajast. Töös võrreldakse omavahel eelmainitud meetodeid, käsitledes äriprotsesse erinevatest valdkondadest. Hindamine toob esile erinevusi selgitatava ja täpsusele põhinevale lähenemiste vahel.
Töö teaduslik panus on ennustuslikuks protsesside jälgimiseks vabavaralise tööriista arendamine. Süsteemi nimeks on Nirdizati ning see süsteem võimaldab treenida ennustuslike masinõppe mudeleid, kasutades nii töös kirjeldatud meetodeid kui ka kolmanda osapoole meetodeid. Hiljem saab treenitud mudeleid kasutada hetkel käivate äriprotsesside tulemuste ennustamiseks, mis saab aidata kasutajaid reaalajas.Modern enterprise systems collect detailed data about the execution of the business processes they support. The widespread availability of such data in companies, coupled with advances in machine learning, have led to the emergence of data-driven and predictive approaches to monitor the performance of business processes. By using such predictive process monitoring approaches, potential performance issues can be anticipated and proactively mitigated.
Various approaches have been proposed to address typical predictive process monitoring questions, such as what is the most likely continuation of an ongoing process instance, or when it will finish. However, most existing approaches prioritize accuracy over explainability. Yet in practice, explainability is a critical property of predictive methods. It is not enough to accurately predict that a running process instance will end up in an undesired outcome. It is also important for users to understand why this prediction is made and what can be done to prevent this undesired outcome.
This thesis proposes two methods to build predictive models to monitor business processes in an explainable manner. This is achieved by decomposing a prediction into its elementary components. For example, to explain that the remaining execution time of a process execution is predicted to be 20 hours, we decompose this prediction into the predicted execution time of each activity that has not yet been executed. We evaluate the proposed methods against each other and various state-of-the-art baselines using a range of business processes from multiple domains. The evaluation reaffirms a fundamental trade-off between explainability and accuracy of predictions.
The research contributions of the thesis have been consolidated into an open-source tool for predictive business process monitoring, namely Nirdizati. It can be used to train predictive models using the methods described in this thesis, as well as third-party methods. These models are then used to make predictions for ongoing process instances; thus, the tool can also support users at runtime
Human Practice. Digital Ecologies. Our Future. : 14. Internationale Tagung Wirtschaftsinformatik (WI 2019) : Tagungsband
Erschienen bei: universi - Universitätsverlag Siegen. - ISBN: 978-3-96182-063-4Aus dem Inhalt:
Track 1: Produktion & Cyber-Physische Systeme
Requirements and a Meta Model for Exchanging Additive Manufacturing Capacities
Service Systems, Smart Service Systems and Cyber- Physical Systems—What’s the difference? Towards a Unified Terminology
Developing an Industrial IoT Platform – Trade-off between Horizontal and Vertical Approaches
Machine Learning und Complex Event Processing: Effiziente Echtzeitauswertung am Beispiel Smart Factory
Sensor retrofit for a coffee machine as condition monitoring and predictive maintenance use case
Stakeholder-Analyse zum Einsatz IIoT-basierter Frischeinformationen in der Lebensmittelindustrie
Towards a Framework for Predictive Maintenance Strategies in Mechanical Engineering - A Method-Oriented Literature Analysis
Development of a matching platform for the requirement-oriented selection of cyber physical systems for SMEs
Track 2: Logistic Analytics
An Empirical Study of Customers’ Behavioral Intention to Use Ridepooling Services – An Extension of the Technology Acceptance Model
Modeling Delay Propagation and Transmission in Railway Networks
What is the impact of company specific adjustments on the acceptance and diffusion of logistic standards?
Robust Route Planning in Intermodal Urban Traffic
Track 3: Unternehmensmodellierung & Informationssystemgestaltung (Enterprise Modelling & Information Systems Design)
Work System Modeling Method with Different Levels of Specificity and Rigor for Different Stakeholder Purposes
Resolving Inconsistencies in Declarative Process Models based on Culpability Measurement
Strategic Analysis in the Realm of Enterprise Modeling – On the Example of Blockchain-Based Initiatives for the Electricity Sector
Zwischenbetriebliche Integration in der Möbelbranche: Konfigurationen und Einflussfaktoren
Novices’ Quality Perceptions and the Acceptance of Process Modeling Grammars
Entwicklung einer Definition für Social Business Objects (SBO) zur Modellierung von Unternehmensinformationen
Designing a Reference Model for Digital Product Configurators
Terminology for Evolving Design Artifacts
Business Role-Object Specification: A Language for Behavior-aware Structural Modeling of Business Objects
Generating Smart Glasses-based Information Systems with BPMN4SGA: A BPMN Extension for Smart Glasses Applications
Using Blockchain in Peer-to-Peer Carsharing to Build Trust in the Sharing Economy
Testing in Big Data: An Architecture Pattern for a Development Environment for Innovative, Integrated and Robust Applications
Track 4: Lern- und Wissensmanagement (e-Learning and Knowledge Management)
eGovernment Competences revisited – A Literature Review on necessary Competences in a Digitalized Public Sector
Say Hello to Your New Automated Tutor – A Structured Literature Review on Pedagogical Conversational Agents
Teaching the Digital Transformation of Business Processes: Design of a Simulation Game for Information Systems Education
Conceptualizing Immersion for Individual Learning in Virtual Reality
Designing a Flipped Classroom Course – a Process Model
The Influence of Risk-Taking on Knowledge Exchange and Combination
Gamified Feedback durch Avatare im Mobile Learning
Alexa, Can You Help Me Solve That Problem? - Understanding the Value of Smart Personal Assistants as Tutors for Complex Problem Tasks
Track 5: Data Science & Business Analytics
Matching with Bundle Preferences: Tradeoff between Fairness and Truthfulness
Applied image recognition: guidelines for using deep learning models in practice
Yield Prognosis for the Agrarian Management of Vineyards using Deep Learning for Object Counting
Reading Between the Lines of Qualitative Data – How to Detect Hidden Structure Based on Codes
Online Auctions with Dual-Threshold Algorithms: An Experimental Study and Practical Evaluation
Design Features of Non-Financial Reward Programs for Online Reviews: Evaluation based on Google Maps Data
Topic Embeddings – A New Approach to Classify Very Short Documents Based on Predefined Topics
Leveraging Unstructured Image Data for Product Quality Improvement
Decision Support for Real Estate Investors: Improving Real Estate Valuation with 3D City Models and Points of Interest
Knowledge Discovery from CVs: A Topic Modeling Procedure
Online Product Descriptions – Boost for your Sales?
Entscheidungsunterstützung durch historienbasierte Dienstreihenfolgeplanung mit Pattern
A Semi-Automated Approach for Generating Online Review Templates
Machine Learning goes Measure Management: Leveraging Anomaly Detection and Parts Search to Improve Product-Cost Optimization
Bedeutung von Predictive Analytics für den theoretischen Erkenntnisgewinn in der IS-Forschung
Track 6: Digitale Transformation und Dienstleistungen
Heuristic Theorizing in Software Development: Deriving Design Principles for Smart Glasses-based Systems
Mirroring E-service for Brick and Mortar Retail: An Assessment and Survey
Taxonomy of Digital Platforms: A Platform Architecture Perspective
Value of Star Players in the Digital Age
Local Shopping Platforms – Harnessing Locational Advantages for the Digital Transformation of Local Retail Outlets: A Content Analysis
A Socio-Technical Approach to Manage Analytics-as-a-Service – Results of an Action Design Research Project
Characterizing Approaches to Digital Transformation: Development of a Taxonomy of Digital Units
Expectations vs. Reality – Benefits of Smart Services in the Field of Tension between Industry and Science
Innovation Networks and Digital Innovation: How Organizations Use Innovation Networks in a Digitized Environment
Characterising Social Reading Platforms— A Taxonomy-Based Approach to Structure the Field
Less Complex than Expected – What Really Drives IT Consulting Value
Modularity Canvas – A Framework for Visualizing Potentials of Service Modularity
Towards a Conceptualization of Capabilities for Innovating Business Models in the Industrial Internet of Things
A Taxonomy of Barriers to Digital Transformation
Ambidexterity in Service Innovation Research: A Systematic Literature Review
Design and success factors of an online solution for cross-pillar pension information
Track 7: IT-Management und -Strategie
A Frugal Support Structure for New Software Implementations in SMEs
How to Structure a Company-wide Adoption of Big Data Analytics
The Changing Roles of Innovation Actors and Organizational Antecedents in the Digital Age
Bewertung des Kundennutzens von Chatbots für den Einsatz im Servicedesk
Understanding the Benefits of Agile Software Development in Regulated Environments
Are Employees Following the Rules? On the Effectiveness of IT Consumerization Policies
Agile and Attached: The Impact of Agile Practices on Agile Team Members’ Affective Organisational Commitment
The Complexity Trap – Limits of IT Flexibility for Supporting Organizational Agility in Decentralized Organizations
Platform Openness: A Systematic Literature Review and Avenues for Future Research
Competence, Fashion and the Case of Blockchain
The Digital Platform Otto.de: A Case Study of Growth, Complexity, and Generativity
Track 8: eHealth & alternde Gesellschaft
Security and Privacy of Personal Health Records in Cloud Computing Environments – An Experimental Exploration of the Impact of Storage Solutions and Data Breaches
Patientenintegration durch Pfadsysteme
Digitalisierung in der Stressprävention – eine qualitative Interviewstudie zu Nutzenpotenzialen
User Dynamics in Mental Health Forums – A Sentiment Analysis Perspective
Intent and the Use of Wearables in the Workplace – A Model Development
Understanding Patient Pathways in the Context of Integrated Health Care Services - Implications from a Scoping Review
Understanding the Habitual Use of Wearable Activity Trackers
On the Fit in Fitness Apps: Studying the Interaction of Motivational Affordances and Users’ Goal Orientations in Affecting the Benefits Gained
Gamification in Health Behavior Change Support Systems - A Synthesis of Unintended Side Effects
Investigating the Influence of Information Incongruity on Trust-Relations within Trilateral Healthcare Settings
Track 9: Krisen- und Kontinuitätsmanagement
Potentiale von IKT beim Ausfall kritischer Infrastrukturen: Erwartungen, Informationsgewinnung und Mediennutzung der Zivilbevölkerung in Deutschland
Fake News Perception in Germany: A Representative Study of People’s Attitudes and Approaches to Counteract Disinformation
Analyzing the Potential of Graphical Building Information for Fire Emergency Responses: Findings from a Controlled Experiment
Track 10: Human-Computer Interaction
Towards a Taxonomy of Platforms for Conversational Agent Design
Measuring Service Encounter Satisfaction with Customer Service Chatbots using Sentiment Analysis
Self-Tracking and Gamification: Analyzing the Interplay of Motivations, Usage and Motivation Fulfillment
Erfolgsfaktoren von Augmented-Reality-Applikationen: Analyse von Nutzerrezensionen mit dem Review-Mining-Verfahren
Designing Dynamic Decision Support for Electronic Requirements Negotiations
Who is Stressed by Using ICTs? A Qualitative Comparison Analysis with the Big Five Personality Traits to Understand Technostress
Walking the Middle Path: How Medium Trade-Off Exposure Leads to Higher Consumer Satisfaction in Recommender Agents
Theory-Based Affordances of Utilitarian, Hedonic and Dual-Purposed Technologies: A Literature Review
Eliciting Customer Preferences for Shopping Companion Apps: A Service Quality Approach
The Role of Early User Participation in Discovering Software – A Case Study from the Context of Smart Glasses
The Fluidity of the Self-Concept as a Framework to Explain the Motivation to Play Video Games
Heart over Heels? An Empirical Analysis of the Relationship between Emotions and Review Helpfulness for Experience and Credence Goods
Track 11: Information Security and Information Privacy
Unfolding Concerns about Augmented Reality Technologies: A Qualitative Analysis of User Perceptions
To (Psychologically) Own Data is to Protect Data: How Psychological Ownership Determines Protective Behavior in a Work and Private Context
Understanding Data Protection Regulations from a Data Management Perspective: A Capability-Based Approach to EU-GDPR
On the Difficulties of Incentivizing Online Privacy through Transparency: A Qualitative Survey of the German Health Insurance Market
What is Your Selfie Worth? A Field Study on Individuals’ Valuation of Personal Data
Justification of Mass Surveillance: A Quantitative Study
An Exploratory Study of Risk Perception for Data Disclosure to a Network of Firms
Track 12: Umweltinformatik und nachhaltiges Wirtschaften
Kommunikationsfäden im Nadelöhr – Fachliche Prozessmodellierung der Nachhaltigkeitskommunikation am Kapitalmarkt
Potentiale und Herausforderungen der Materialflusskostenrechnung
Computing Incentives for User-Based Relocation in Carsharing
Sustainability’s Coming Home: Preliminary Design Principles for the Sustainable Smart District
Substitution of hazardous chemical substances using Deep Learning and t-SNE
A Hierarchy of DSMLs in Support of Product Life-Cycle Assessment
A Survey of Smart Energy Services for Private Households
Door-to-Door Mobility Integrators as Keystone Organizations of Smart Ecosystems: Resources and Value Co-Creation – A Literature Review
Ein Entscheidungsunterstützungssystem zur ökonomischen Bewertung von Mieterstrom auf Basis der Clusteranalyse
Discovering Blockchain for Sustainable Product-Service Systems to enhance the Circular Economy
Digitale Rückverfolgbarkeit von Lebensmitteln: Eine verbraucherinformatische Studie
Umweltbewusstsein durch audiovisuelles Content Marketing? Eine experimentelle Untersuchung zur Konsumentenbewertung nachhaltiger Smartphones
Towards Predictive Energy Management in Information Systems: A Research Proposal
A Web Browser-Based Application for Processing and Analyzing Material Flow Models using the MFCA Methodology
Track 13: Digital Work - Social, mobile, smart
On Conversational Agents in Information Systems Research: Analyzing the Past to Guide Future Work
The Potential of Augmented Reality for Improving Occupational First Aid
Prevent a Vicious Circle! The Role of Organizational IT-Capability in Attracting IT-affine Applicants
Good, Bad, or Both? Conceptualization and Measurement of Ambivalent User Attitudes Towards AI
A Case Study on Cross-Hierarchical Communication in Digital Work Environments
‘Show Me Your People Skills’ - Employing CEO Branding for Corporate Reputation Management in Social Media
A Multiorganisational Study of the Drivers and Barriers of Enterprise Collaboration Systems-Enabled Change
The More the Merrier? The Effect of Size of Core Team Subgroups on Success of Open Source Projects
The Impact of Anthropomorphic and Functional Chatbot Design Features in Enterprise Collaboration Systems on User Acceptance
Digital Feedback for Digital Work? Affordances and Constraints of a Feedback App at InsurCorp
The Effect of Marker-less Augmented Reality on Task and Learning Performance
Antecedents for Cyberloafing – A Literature Review
Internal Crowd Work as a Source of Empowerment - An Empirical Analysis of the Perception of Employees in a Crowdtesting Project
Track 14: Geschäftsmodelle und digitales Unternehmertum
Dividing the ICO Jungle: Extracting and Evaluating Design Archetypes
Capturing Value from Data: Exploring Factors Influencing Revenue Model Design for Data-Driven Services
Understanding the Role of Data for Innovating Business Models: A System Dynamics Perspective
Business Model Innovation and Stakeholder: Exploring Mechanisms and Outcomes of Value Creation and Destruction
Business Models for Internet of Things Platforms: Empirical Development of a Taxonomy and Archetypes
Revitalizing established Industrial Companies: State of the Art and Success Principles of Digital Corporate Incubators
When 1+1 is Greater than 2: Concurrence of Additional Digital and Established Business Models within Companies
Special Track 1: Student Track
Investigating Personalized Price Discrimination of Textile-, Electronics- and General Stores in German Online Retail
From Facets to a Universal Definition – An Analysis of IoT Usage in Retail
Is the Technostress Creators Inventory Still an Up-To-Date Measurement Instrument? Results of a Large-Scale Interview Study
Application of Media Synchronicity Theory to Creative Tasks in Virtual Teams Using the Example of Design Thinking
TrustyTweet: An Indicator-based Browser-Plugin to Assist Users in Dealing with Fake News on Twitter
Application of Process Mining Techniques to Support Maintenance-Related Objectives
How Voice Can Change Customer Satisfaction: A Comparative Analysis between E-Commerce and Voice Commerce
Business Process Compliance and Blockchain: How Does the Ethereum Blockchain Address Challenges of Business Process Compliance?
Improving Business Model Configuration through a Question-based Approach
The Influence of Situational Factors and Gamification on Intrinsic Motivation and Learning
Evaluation von ITSM-Tools für Integration und Management von Cloud-Diensten am Beispiel von ServiceNow
How Software Promotes the Integration of Sustainability in Business Process Management
Criteria Catalog for Industrial IoT Platforms from the Perspective of the Machine Tool Industry
Special Track 3: Demos & Prototyping
Privacy-friendly User Location Tracking with Smart Devices: The BeaT Prototype
Application-oriented robotics in nursing homes
Augmented Reality for Set-up Processe
Mixed Reality for supporting Remote-Meetings
Gamification zur Motivationssteigerung von Werkern bei der Betriebsdatenerfassung
Automatically Extracting and Analyzing Customer Needs from Twitter: A “Needmining” Prototype
GaNEsHA: Opportunities for Sustainable Transportation in Smart Cities
TUCANA: A platform for using local processing power of edge devices for building data-driven services
Demonstrator zur Beschreibung und Visualisierung einer kritischen Infrastruktur
Entwicklung einer alltagsnahen persuasiven App zur Bewegungsmotivation für ältere Nutzerinnen und Nutzer
A browser-based modeling tool for studying the learning of conceptual modeling based on a multi-modal data collection approach
Exergames & Dementia: An interactive System for People with Dementia and their Care-Network
Workshops
Workshop Ethics and Morality in Business Informatics (Workshop Ethik und Moral in der Wirtschaftsinformatik – EMoWI’19)
Model-Based Compliance in Information Systems - Foundations, Case Description and Data Set of the MobIS-Challenge for Students and Doctoral Candidates
Report of the Workshop on Concepts and Methods of Identifying Digital Potentials in Information Management
Control of Systemic Risks in Global Networks - A Grand Challenge to Information Systems Research
Die Mitarbeiter von morgen - Kompetenzen künftiger Mitarbeiter im Bereich Business Analytics
Digitaler Konsum: Herausforderungen und Chancen der Verbraucherinformati
Linguistic Refactoring of Business Process Models
In the past decades, organizations had to face numerous challenges due to intensifying globalization and internationalization, shorter innovation cycles and growing IT support for business. Business process management is seen as a comprehensive approach to align business strategy, organization, controlling, and business activities to react flexibly to market changes. For this purpose, business process models are increasingly utilized to document and redesign relevant parts of the organization's business operations. Since companies tend to have a growing number of business process models stored in a process model repository, analysis techniques are required that assess the quality of these process models in an automatic fashion. While available techniques can easily check the formal content of a process model, there are only a few techniques available that analyze the natural language content of a process model. Therefore, techniques are required that address linguistic issues caused by the actual use of natural language. In order to close this gap, this doctoral thesis explicitly targets inconsistencies caused by natural language and investigates the potential of automatically detecting and resolving them under a linguistic perspective. In particular, this doctoral thesis provides the following contributions. First, it defines a classification framework that structures existing work on process model analysis and refactoring. Second, it introduces the notion of atomicity, which implements a strict consistency condition between the formal content and the textual content of a process model. Based on an explorative investigation, we reveal several reoccurring violation patterns are not compliant with the notion of atomicity. Third, this thesis proposes an automatic refactoring technique that formalizes the identified patterns to transform a non-atomic process models into an atomic one. Fourth, this thesis defines an automatic technique for detecting and refactoring synonyms and homonyms in process models, which is eventually useful to unify the terminology used in an organization. Fifth and finally, this thesis proposes a recommendation-based refactoring approach that addresses process models suffering from incompleteness and leading to several possible interpretations. The efficiency and usefulness of the proposed techniques is further evaluated by real-world process model repositories from various industries. (author's abstract
Vereinigung von detaillierten Teilmodellen in einer flexiblen Enterprise Architecture zur übergreifenden Analyse: Ableitung des Bedarfs an Handlungen für einen durch Kennzahlen beschriebenen Untersuchungskontext
Modelle haben sich zu Dokumentationszwecken bewährt, existieren in der Praxis aber oftmals losgelöst voneinander. Durch die wachsende Komplexität in den Unternehmen reicht jedoch eine getrennte Betrachtung nicht mehr aus. Das Zusammenspiel der Unternehmensbestandteile muss bei Entscheidungen berücksichtigt werden. Eine Enterprise Architecture (EA) eignet sich zur Herstellung einer übergreifenden Sichtweise. Wobei hauptsächlich aggregierte Inhalte enthalten sind, die manuell erstellt werden. Damit ist die EA ein weiteres Datensilo. Durch das Fehlen detaillierter Informationen in der EA sind außerdem die Möglichkeiten einer ganzheitlichen Analyse begrenzt. Die vorliegende Arbeit entwickelt daher ein Gesamtkonzept, um Detailinhalte zu vernetzen und übergreifende Analysen zu ermöglichen. Insbesondere werden auch Datenwerte (z.B. Kosten) einbezogen. Eine Indirektstufe kann die Teilmodelle lose verknüpfen. Zugleich dient ein einfaches EA-Vokabular als neutrale Begriffsschicht. Mithilfe der Technologien des Semantic Web entsteht so eine integrierte Datenbasis. Sie positioniert sich als Ebene oberhalb der Datenquellen. Anschließend kann eine übergreifende Analyse erfolgen, in der alle Inhalte kombiniert werden. Zur Konkretisierung des Ansatzes fokussiert sich die Arbeit auf die Ableitung des Bedarfs an Handlungen. Mit der Importance-Performance-Analyse wird ein Verfahren aus dem Qualitätsmanagement von Dienstleistungen entliehen und auf die EA-Analyse übertragen. Die Berechnung basiert auf flexibel zu beschreibenden Kennzahlen, bei deren Definition das EA-Vokabular verwendet wird. Als Ergebnis werden Gesamtratings für alle Untersuchungsobjekte ausgewiesen. Sie sagen etwas über einen Handlungsbedarf und die Dringlichkeit aus. Auch die Analyse basiert auf Technologien des Semantic Web. Als Nachweis der Realisierbarkeit wurde der Ansatz in einem Prototyp umgesetzt. Außerdem wird ein praxisnaher Anwendungsfall einer Digitalisierungsinitiative bei einer Versicherung skizziert