Understanding human factors in the metaverse - an autonomous driving experiment

Research often draws on established research methods such as lab or field experiments to investigate urgent questions about human factors in future autonomous mobility. However, conducting experiments in such a context is either expensive and complex to implement and operate, when the researchers aim for realism, or otherwise entails limitations with regard to the external validity of the experiments. In this work, we propose the use of immersive virtual experiments in emerging game-based ‘metaverse’ platforms as a cost-efficient approach with the potential for high realism. Next to a prototype, we present the setup of an experiment for investigating user behavior in an autonomous driving scenario we want to realize. Finally, we provide an outlook on how we plan to gain novel insights for designing realistic experiments in the metaverse

Towards increased business model comprehension – principles for an advanced business model tool

Business modelling is recognized as an important concept to make company strategies more explicit and to compare alternatives combined with their translation to the operational layer. Typically, busi-ness modelling is performed by a group of experts building on established frameworks like the Busi-ness Model Canvas. In a subsequent step, different stakeholders in a company should build upon and work with the defined business models, thus, comprehension is critical. However, this is challenging from a practical point of view and existing research has not addressed the issue of business model comprehension. In order to close this research gap and to increase users’ business model comprehen-sion, we propose an advanced business model tool and an experimental design in this research-in-progress paper. Following the design science approach, we derive a first set of meta-requirements and design principles and present an advanced business model tool instantiation. The presented tool should contribute to an increased business model comprehension by providing semantic relationships and extended business performance indicators. Finally, we present a set of testable hypotheses and the research design for an experimental tool evaluation. With this research we intend to provide a solu-tion to the problem of business model comprehension and contribute to the design knowledge base of business model tools

Intelligente Geschäftsmodellierung

Globale Herausforderungen und neue Kundenansprüche zwingen Unternehmen heute dazu, ihr Geschäftsmodell an die neuen Gegebenheiten anzupassen. Dieses Modell repräsentiert dabei die Logik, wie ein Unternehmen letztendlich sein Geld verdient. Um langfristig erfolgreich zu bleiben, müssen Firmen diese Logik immer wieder überarbeiten und strategisch richtige Anpassungen treffen. Diesen Prozess soll die Software BM Configuration erleichtern

Design Principles for Business Model Analytics Tools

In this doctoral thesis, a current and widespread approach to business modelling is developed further using findings from data analytics and theories to improve user understanding. The focus is on the goals of an objective business modeling that is comprehensible to all users. Business modelling is an important part of companies to determine their strategy and as a linking element between the strategic and operational level. Different research areas investigate how such business modelling can be supported or applied in different situations (e.g. after disruptive shocks). However, the starting point for these approaches is always a subjective top-down approach, based on the knowledge of the modeler. This involves the challenge that the created business models are incorrect and depend on the knowledge and perspective of the modeler. In addition, they are strongly linked to the strategic level and the abstract management view associated with it. In a design science research approach in this thesis, requirements and design principles for objective and easily understandable business modeling were developed. In addition, these principles were instantiated in a tool that can (semi-)automatically create a business model by using enterprise data. At the same time, the understanding of all users is increased by integrating the relationships between the elements, the value flow and an extension of value capturing. This provides the foundation for a common communication platform, similar to a blueprint in the construction industry. The result of this work is not only the tool but also an extension of the current state of the art of research in the field of business modeling, as well as corresponding principles and findings, which can be used to master individual challenges in practice and science

Acting like a Startup - Using Corporate Startup Structures to Manage the Digital Transformation

Digital transformation is proving to be a significant challenge for firms and companies when it comes to maintaining their market position. It is evident that many companies are struggling to find their particular way through this transformation. A corporate startup structure is one way to find a suitable solution quickly. Therefore, we are presenting a model for corporate startup activities, which we will instantiate in an appropriate tool to support the management of corporate startups by their parent firms. We have derived the first requirements and design principles from a comprehensive problem analysis and literature study. In addition to this,we are presenting a first artifact, which should realize the design principles by implementing a practical tool. Forming a cooperation with an automotive firm has enabled us to gain access to real-world data for the design and evaluation of the artifact

Developing a Business Model Transformation Tool

As promising chance, Industry 4.0 (I4.0) enables companies to defend their position in fast changing markets and to respond on individual customer demands. How-ever, companies have challenges to implement I 4.0 strategies in their current business. We present a research-in-progress design science project with the aim of designing a business model configuration tool enabling company transformation to I 4.0. Based on a comprehensive problem analysis and literature study, we demonstrate a first prototypical instantiation and demonstrate its feasibility in a case study. This tool enables practitioners as well as theorists to observe changes in business models rapidly and support transformations to I 4.0. With the tool, companies can understand their business models better and find a target business model, which is really fitting to the individual way of value creation of the company

Process Mining for Business Process Standardization in ERP Implementation Projects – An SAP S/4 HANA Case Study from Manufacturing

Organizations increasingly build operations on enterprise resource planning (ERP) systems. However, ERP implementation projects require significant process transformation and standardization to successfully use ERP systems. This article presents a case study in a manufacturing corporation to demonstrate how process mining can be used for process decisionmaking in an SAP S/4 HANA implementation project. In particular, the corporation implements process mining for the analysis of the SAP purchase-to-pay (“Purchas-ing”) and the order-to-cash (“Sales”) processes to determine whether the future to-be process should be standardized according to ERP standards, or to be individualized in a corporate-specific template. Further, process mining can be used to select suitable standard process specifications from the SAP Best Practices Explorer, as well as to analyze the required process changes before the launch of the new ERP system and process implementations

DEFINING KEY PERFORMANCE INDICATORS FOR BUSINESS MODELS: DESIGN PRINCIPLES FOR A METHOD AND TOOL SUPPORT

Key Performance Indicators (KPIs) play an important role in guiding the management of business models throughout their lifecycle. However, existing research lacks practical methods to guide the definition of KPIs for business models. Without proper guidance, there may be a mismatch between the intended business model design and its implementation, resulting in many promising business model ideas failing to reach the market. To address this problem, we adopt a design science research approach to design and evaluate a method and supporting IT tool for defining business model KPIs. In this research-in-progress paper, we present a set of meta-requirements and design principles for developing the method and tool support. We instantiate the requirements and principles in a tool prototype and evaluate their validity in semi-structured interviews with five industry experts. Our study contributes to research on KPIs for business models and the development of methods and tools for business model management