Complex Systems Informatics and Modeling Quarterly
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Survey on Organizational Chat Conversation Analysis: Exploring Dialogue Summarization from a Knowledge Discovery Perspective
Get PDFWith the latest advances in natural language processing technologies, multi-participant conversation summarization features are now embedded in the most widely used collaboration platforms offered by industry leaders such as Microsoft, Google, and Zoom. This allows employees to streamline their work and increase efficiency by summarizing long chat threads. In this study, an attempt has been made to perceive summarized chat conversations as a tool for knowledge discovery and reusable information extraction within an organization in general or during projects. To this end, recent scientific articles have been reviewed to identify the most effective techniques and approaches for summarizing chat threads and conversations alongside the challenges and peculiarities of collaborative text-based communication. In addition, significant attention has been paid to the further utilization of the extracted information to represent the knowledge for further reuse
Trustworthiness Requirements in Information Systems Design: Lessons Learned from the Blockchain Community
Get PDFIn modern society, where digital security is a major preoccupation, the perception of trust is undergoing fundamental transformations. Blockchain community created a substantial body of knowledge on design and development of trustworthy information systems and digital trust. Yet, little research is focused on broader scope and other forms of trust. In this study, we review the research literature reporting on design and development of blockchain solutions and focus on trustworthiness requirements that drive these solutions. Our findings show that digital trust is not the only form of trust that the organizations seek to reenforce: trust in technology and social trust remain powerful drivers in decision making. We analyze 56 primary studies, extract and formulate a set of 21 trustworthiness requirements. While originated from blockchain literature, the formulated requirements are technology-neutral: they aim at supporting business and technology experts in translating their trust issues into specific design decisions and in rationalizing their technological choices. To bridge the gap between social and technological domains, we associate the trustworthiness requirements with three trustworthiness factors defined in the social science: ability, benevolence and integrity
Enterprise Evolution: A Discussion from Different Perspectives. Editorial Introduction to Issue 34 of CSIMQ
Get PDFThe current issue provides discussions on different topics that can be summarized as “Enterprise Evolution”. The selected articles continue and elaborate research that was presented in 2022 during workshops at the Perspectives in Business Informatics Research Conference – BIR 2022 in Rostock, Germany. The articles continue the research work presented at the conference, summarize the findings and provide deeper insights and new perspectives. The articles report on research results regarding ethical, social, and environmental accounting; support for post-merger information systems integration; enterprise architecture for inclusion of demand-responsive services in the overall enterprise architecture of transportation companies; and possibilities of SMEs to use robotic solutions for enhancing their processes
Integrating Models of Observing and Observed Activities Based on an Example of Empirical Research in Information Systems Discipline
Get PDFA situation where both observing and observed activities need to be taken into consideration is not uncommon in practice. In Viable System Model (VSM), System 3* is dedicated to making sudden inspections on how the work is done “on the floor”. A typical case in research is an empirical study, where research activities are aimed at understanding the activities of the object under investigation. Though separate models of the observation activity and the observed activity are often presented, having an integrated model that connects both often falls under the radar. This article investigates how the latter model can be built and used in empirical research projects in the Information System (IS) discipline. Articles in the IS field presenting research projects that use data from practice, as a rule, describe the practice and research process, including which research methods have been used for obtaining and analyzing the data. Some articles present models of practice under investigation using appropriate modeling notations. Some articles present a research process in some graphical form. However, to the best of our knowledge, there is no established practice of presenting a model that interconnects practical and research activities. This article tries to fill the gap, and it presents some ideas on how to build a model that integrates observing and observed activities. Such a model can be used for planning a research project and to better understand the limitations of the approaches used or to be used in the project
Design Objectives for Evolvable Knowledge Graphs
Get PDFKnowledge graphs (KGs) structure knowledge to enable the development of intelligent systems across several application domains. In industrial maintenance, comprehensive knowledge of the factory, machinery, and components is indispensable. This study defines the objectives for evolvable KGs, building upon our prior research, where we initially identified the problem in industrial maintenance. Our contributions include two main aspects: firstly, the categorization of learning within the KG construction process and the identification of design objectives for the KG process focusing on supporting industrial maintenance. The categorization highlights the specific requirements for KG design, emphasizing the importance of planning for maintenance and reuse
An Actor-Oriented and Architecture-Driven Approach for Spatially Explicit Agent-Based Modeling
Get PDFNowadays, there is an increasing need to rapidly build more realistic models to solve environmental problems in an interdisciplinary context. In particular, agent-based and spatial modeling have proven to be useful for understanding land use and land cover change processes. Both approaches include simulation platforms often used in several research domains to develop models explaining and analyzing complex phenomena. Domain experts generally use an ad hoc approach for model development, which relies on a code-and-fix life cycle, going from a prototype model through progressive refinement. This adaptive approach does not capture systematically actors’ knowledge and their interactions with the environment. The development and maintenance of resulting models become cumbersome and time-consuming. In this article, we propose an actor and architecture-driven approach that relies on relevant existing methods and satisfies the needs of spatially explicit agent-based modeling and implementation. We have designed an Agent Global Experiment framework incorporating a meta-model built from actor, agent architecture, and spatial concepts to produce an initial model from specifications provided by domain experts and system analysts. An engine is built as a tool to support model transformation. Domain knowledge including spatial specifications is summarized in a class diagram which is later transformed into the agent-based model. Finally, the XML file representing the model produced is used as input in the transformation process leading to code. This approach is illustrated on a hunting and population dynamic model to generate a running code for GAMA, an agent-based and spatially explicit simulation platform
DLT Compliance Reporting
Get PDFToday, local financial institutions are responsible for submitting compliance reporting data to the supervisory authorities. This is commonly referred to as the ‘push model’. The increasing complexity of reporting obligations often results in delayed reporting which delivers a fragmented and incomplete macroeconomic overview of the financial sector. Working with a group of nine representatives from industry and regulatory authorities, we employ the design science research methodology (DSR) in the design of an artefact, enabling the automated collection and enrichment of transactional data from DLT ledgers. Our findings demonstrate how the adoption of DLT in the financial sector will facilitate the automation of compliance reporting through a ‘pull-model’, in which regulators can access compliance data in near real-time and stage aggregate macroeconomic risk exposures for the eurozone. The findings contribute practical insights to the discourse on design-driven research on DLT and blockchain technology
Determining Critical Success Factors of the Digital Transformation Using a Force-Directed Network Graph
Get PDFConducting a digital transformation is one of the major challenges for today’s companies as it is usually associated with a high risk. The reasons for this are manifold. Technologies are still evolving and there is no coherent standard for digital platforms enabling digitalization. Furthermore, it is not only about introducing new technology but also requires a fundamental change in an organization and its culture. Consequently, planning a digital transformation project (or program) requires a careful analysis of the company’s current situation and the envisioned objectives. This article investigates critical success factors for preparing and executing such a transformation. The success factors are identified by conducting a structured literature analysis. 13 scientific papers are identified and then analyzed quantitatively and qualitatively. The quantitative analysis is conducted by using force-directed network graphs. Both methods are then compared and discussed. The result shows that most critical success factors are related to the business change rather than to introducing technology. Leadership, strategy, vision, corporate culture, and customer centricity play a stronger role than a digital platform
Towards an E-Government Enterprise Architecture Framework for Developing Economies
Get PDFThe growth and uptake of e-government in developing economies are still affected by the interoperability challenge, which can be perceived as an orchestration of several issues that imply the existence of gaps in methods used for e-government planning and implementation. To a great extent, various counterparts in developed economies have succeeded in addressing the method-related gaps by developing e-government enterprise architectures, as blueprints for guiding e-government initiatives in a holistic and manageable way. However, existing e-government enterprise architectures are country-specific to appropriately serve their intended purpose, while enterprise architecture frameworks or methods are generic to accommodate several enterprise contexts. The latter do not directly accommodate the unique peculiarities of e-government efforts. Thus, a detailed method is lacking that can be adapted by developing economies to develop e-government enterprise architectures that fit their contexts. To address the gap, this article presents research that adopted a Design Science approach to develop an e-Government Enterprise Architecture Framework (EGEAF), as an explicit method for guiding the design of e-government enterprise architectures in a developing economy. EGEAF was designed by extending the Architecture Development Method of The Open Group Architecture Framework (TOGAF ADM) to address requirements for developing interoperable e-government solutions in a developing economy. EGEAF was evaluated using two scenarios in the Ugandan context, and findings indicate that it is feasible; its design is understandable to enable its adoption and extension to accommodate requirements for developing interoperable e-government solutions in other developing economies
Using Fractal Enterprise Modeling in Strategic Analysis with Focus on Intangibles: Empirical Study in Product Innovation
Get PDFThis article presents a new meta-modeling approach for intangible resources. The method combines Enterprise Modeling (EM) and the resource value innovation model from the knowledge management (KM) field. In particular, fractal enterprise modeling (FEM) language has been used for constructing the intangible resources’ level of development. The practical application of the proposed method deploys a real case example in the strategic analysis of the organizational change within the product innovation activities. The results imply that the proposed method has a good potential to incorporate the intangibles into EM. First, it has been possible to represent the intangible resources’ level of development. Second, the FEM models produced in the study have been useful in the analysis of how tacit knowledge is acquired and appropriated within the organization’s strategic capability building. The study resulted in producing modeling and analyzing patterns that can be reused in similar situations. The research followed the Design Science Research (DSR) methodology