Business Models and Complexity

　 Purpose: To offer a -necessarily non-exhaustive- analysis of the meaning and significance of the notion of a complex system for research on the Business Model (BM). Design/Methodology/Approach: Conceptual paper Findings: Drawing from early research in complexity and debates that have inspired work in General System Theory, system thinking and cybernetics, we identify four insights, notably i) modeling of complex systems, ii) interdependencies, iii) nested hierarchies and iv) information processing that, we contend, have the potential to shed light on novel possibilities for understanding BMs. We offer an analysis. Research Limitations/Implications: Limitation: exclusive focus on early interpretation of the notion of complexity as referring to a characteristic of a system. The paper does not explore the implications of the more modern understanding of complexity as referring to the ‘behavior’ of a system (complex system vs. complex behavior) Practical Implications: we may be attempting to represent a system which is very complex, the BM and the organization behind it, at the level of the anatomy, only reflecting its main components. This is subject to inherent limitations. Originality/Value: To show that, within the line of inquiry understanding the business model (BM) as some reality existing at the level of the firm, a BM may resemble what students of complexity refer to as a complex system. To explore the meaning and significance of the notion of complexity and of a complex system for research on the BM

Framework for a business interoperability quotient measurement model

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova da Lisboa para obtenção do grau de Mestre em Engenharia e Gestão Industrial (MEGI)Over the last decade the context of Interoperability has been changing rapidly. It has been expanding from the largely technically focused area of Information Systems towards Business Processes and Business Semantics. However, there exists a need for more comprehensive ways to define business interoperability and enable its performance measurement as a first step towards improvement of interoperability conditions between collaborating entities. Through extensive literature reviews and analysis of European Research initiatives in this area, this dissertation presents the State of the Art in Business Interoperability. The objective of this dissertation is to develop a model that closely captures the factors that are responsible for Business Interoperability in the context of Collaborative Business Processes. This Business Interoperability Quotient Measurement Model (BIQMM), developed in this dissertation uses an interdisciplinary approach to capture the key elements responsible for collaboration performance. Through the quantification of the relevance of each element to the particular collaboration scenario in question, this model enables a quantitative analysis of Business Interoperability, so that an overall interoperability score can be arrived at for enhanced performance measurements.Finally, the BIQMM is applied to a business case involving Innovayt and LM Glassfiber to demonstrate its applicability to different collaboration scenarios

Architecture-based Evolution of Dependable Software-intensive Systems

This cumulative habilitation thesis, proposes concepts for (i) modelling and analysing dependability based on architectural models of software-intensive systems early in development, (ii) decomposition and composition of modelling languages and analysis techniques to enable more flexibility in evolution, and (iii) bridging the divergent levels of abstraction between data of the operation phase, architectural models and source code of the development phase

Explainable software systems: from requirements analysis to system evaluation

The growing complexity of software systems and the influence of software-supported decisions in our society sparked the need for software that is transparent, accountable, and trustworthy. Explainability has been identified as a means to achieve these qualities. It is recognized as an emerging non-functional requirement (NFR) that has a significant impact on system quality. Accordingly, software engineers need means to assist them in incorporating this NFR into systems. This requires an early analysis of the benefits and possible design issues that arise from interrelationships between different quality aspects. However, explainability is currently under-researched in the domain of requirements engineering, and there is a lack of artifacts that support the requirements engineering process and system design. In this work, we remedy this deficit by proposing four artifacts: a definition of explainability, a conceptual model, a knowledge catalogue, and a reference model for explainable systems. These artifacts should support software and requirements engineers in understanding the definition of explainability and how it interacts with other quality aspects. Besides that, they may be considered a starting point to provide practical value in the refinement of explainability from high-level requirements to concrete design choices, as well as on the identification of methods and metrics for the evaluation of the implemented requirements

Explainable software systems: from requirements analysis to system evaluation

The growing complexity of software systems and the influence of software-supported decisions in our society sparked the need for software that is transparent, accountable, and trustworthy. Explainability has been identified as a means to achieve these qualities. It is recognized as an emerging non-functional requirement (NFR) that has a significant impact on system quality. Accordingly, software engineers need means to assist them in incorporating this NFR into systems. This requires an early analysis of the benefits and possible design issues that arise from interrelationships between different quality aspects. However, explainability is currently under-researched in the domain of requirements engineering, and there is a lack of artifacts that support the requirements engineering process and system design. In this work, we remedy this deficit by proposing four artifacts: a definition of explainability, a conceptual model, a knowledge catalogue, and a reference model for explainable systems. These artifacts should support software and requirements engineers in understanding the definition of explainability and how it interacts with other quality aspects. Besides that, they may be considered a starting point to provide practical value in the refinement of explainability from high-level requirements to concrete design choices, as well as on the identification of methods and metrics for the evaluation of the implemented requirements

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