Boris Otto | TU Dortmund (original) (raw)

Papers by Boris Otto

The quality of data is critical for enterprises in order to be able to meet a variety of business... more The quality of data is critical for enterprises in order to be able to meet a variety of business requirements, such as compliance with regulatory and legal provisions, integrated customer management ("360°view on the customer"), effective and efficient reporting ("single point of truth"), or integrated and automated business processes. Consumer goods manufacturer Nestlé, for example, is confronted with requirements from the French retail industry to provide "carbon footprint" information on the packaging of each product shipped to stores. The carbon footprint is supposed to inform about the carbon dioxide emitted during the production and distribution of the product along the entire supply chain (AFNOR 2009). This information has to be specified as an attribute of the product data class and has to be made available for the production and packaging process correctly, completely, and in a timely manner. Otherwise, the company risks being fined.

Business & Information Systems Engineering

Digital Twins offer considerable potential for cross-company networks. Recent research primarily ... more Digital Twins offer considerable potential for cross-company networks. Recent research primarily focuses on using Digital Twins within the limits of a single organization. However, Shared Digital Twins extend application boundaries to cross-company utilization through their ability to act as a hub to share data. This results in the need to consider additional design dimensions which help practitioners design Digital Twins tailored for inter-company use. The article addresses precisely that issue as it investigates how Shared Digital Twins should be designed to achieve business success. For this purpose, the article proposes a set of design principles for Shared Digital Twins stemming from a qualitative interview study with 18 industry experts. The interview study is the primary data source for formulating and evaluating the design principles.

Journal of Data and Information Quality, Mar 31, 2022

A Data Ecosystem offers a keystone-player or alliance-driven infrastructure that enables the inte... more A Data Ecosystem offers a keystone-player or alliance-driven infrastructure that enables the interaction of different stakeholders and the resolution of interoperability issues among shared data. However, despite years of research in data governance and management, trustability is still affected by the absence of transparent and traceable data-driven pipelines. In this work, we focus on requirements and challenges that data ecosystems face when ensuring data transparency. Requirements are derived from the data and organizational management, as well as from broader legal and ethical considerations. We propose a novel knowledge-driven data ecosystem architecture, providing the pillars for satisfying the analyzed requirements. We illustrate the potential of our proposal in a real-world scenario. Lastly, we discuss and rate the potential of the proposed architecture in the fulfillment of these requirements.

Digitization is affecting almost all areas of business and society. It brings about opportunities... more Digitization is affecting almost all areas of business and society. It brings about opportunities for enterprises to design a digital business model. While a significant amount of research exist examining the conceptual foundation of business models in general, no comprehensive approach is available that helps enterprises in designing a digital business model. This paper addresses this gap and proposes Digital Business Engineering as a method for digital business model design. The activities are structured into six phases, namely End-to-End Customer Design,

Proceedings of the Annual Hawaii International Conference on System Sciences, 2021

The ever-growing amounts of data offer companies many opportunities to exploit them. Resulting da... more The ever-growing amounts of data offer companies many opportunities to exploit them. Resulting datadriven services hold great potential for creating unique value for customers and the achievement of competitive advantages. Nevertheless, especially companies in the industrial environment struggle to implement successful data-driven service innovations. Surprisingly, there is a lack of scientific research addressing this issue. Thus, our research generates design principles for data-driven services to aid in their development. For this purpose, we present a qualitative interview study with experts in different lines of businesses among the industry sector, holding varying positions and roles in service systems. Through practical examples, we show which challenges exist in the development and use of datadriven services. On this basis, we derive design principles to help understanding data-driven services and to overcome difficulties identified in practice, notably, that allows practitioners to develop new services or redesign existing ones.

CIRED Workshop 2016, 2016

This paper proposes a classification scheme for the different types of flexibilities that are use... more This paper proposes a classification scheme for the different types of flexibilities that are used in electric grids. This classification scheme, which is called a taxonomy, helps to convey the meaning of different concepts of flexibility in research and industrial projects. It also allows to compare the sources and uses of flexibility in conventional vs. smart grid situations to highlight the evolving nature of the power system.

The digitization of the economy and society requires enterprises from all industries to revisit t... more The digitization of the economy and society requires enterprises from all industries to revisit their business models and prepare their organizations for the digital age. The design of "smart" products and services, the involvement of prosumers, and the intensifying interconnection of supply chains are signs of this transformation. Each of these scenarios builds on improved availability and interchangeability of data. In order to successfully transform their business and be able to develop valuable new services, companies require methodological help. To address this need, this paper proposes a service-capability design framework for digital businesses. The framework is developed theoretically based on the literature and earlier research and consists of a meta-model and a high-level reference model. The framework is retroactively applied to a real-world digital use case to demonstrate its validity.

Informatik Spektrum, 2021

ZusammenfassungDaten stellen eine strategische Ressource für die Wettbewerbsfähigkeit von Unterne... more ZusammenfassungDaten stellen eine strategische Ressource für die Wettbewerbsfähigkeit von Unternehmen und die Prosperität der Gesellschaft dar. Von der Nutzung von Daten vieler einzelner Akteure profitieren die Gemeinschaft, aber auch das Individuum. Beispiele hierfür liefern das Gesundheitswesen oder die Mobilität. Dabei sind die Interessen der Individuen in Bezug auf Datenschutz und Datensouveränität über Nutzungsvereinbarungen hinaus zu wahren und bestenfalls technologisch sicherzustellen. Datenräume, basierend auf verteilten Dateninfrastrukturen, stellen Datendienste und Datennutzungsregeln für Individuen und Organisationen bereit. Beispiele hierfür liefern die International-Data-Spaces(IDS)-Initiative oder die Initiative Gaia‑X zur Schaffung einer verteilten Dateninfrastruktur in Europa. Instanziierungen in den Bereichen Mobilität oder Smarthome zeigen Vorteile von Datenökosystemen für Individuen, die Gemeinschaft und die Gesamtheit der Dienstanbieter. Gleichzeitig werden Risik...

Our work develops an archetypical representation of current digital business models of Start-Ups ... more Our work develops an archetypical representation of current digital business models of Start-Ups in the logistics sector. In order to achieve our goal, we analyze the business models of 125 Start-Ups. We draw our sample from the Start-Up database AngelList and focus on platform-driven businesses. We chose Start-Ups as they often are at the forefront of innovation and thus have a high likelihood of operating digital business models. Following well-established methodological guidelines, we construct a taxonomy of digital business models in multiple iterations. We employ different algorithms for cluster analysis to find and generate clusters based on commonalities between the business models across the dimensions and characteristics of the taxonomy. Ultimately, we use the dominant features of the emerging patterns within the clusters to derive archetypes.

ACM Journal of Data and Information Quality (JDIQ), 2022

A data ecosystem (DE) offers a keystone-player or alliance-driven infrastructure that enables the... more A data ecosystem (DE) offers a keystone-player or alliance-driven infrastructure that enables the interaction of different stakeholders and the resolution of interoperability issues among shared data. However, despite years of research in data governance and management, trustability is still affected by the absence of transparent and traceable data-driven pipelines. In this work, we focus on requirements and challenges that DEs face when ensuring data transparency. Requirements are derived from the data and organizational management, as well as from broader legal and ethical considerations. We propose a novel knowledge-driven DE architecture, providing the pillars for satisfying the analyzed requirements. We illustrate the potential of our proposal in a real-world scenario. Last, we discuss and rate the potential of the proposed architecture in the fulfillmentof these requirements.

J. Inf. Technol. Theory Appl., 2018

As cloud computing has become a mature technology broadly being adopted by companies across all i... more As cloud computing has become a mature technology broadly being adopted by companies across all industries, cloud service providers are increasingly turning their attention to retaining their customers. However, only little research has been conducted on investigating the antecedents of service continuance in an organizational context. To address this gap in research, we carried out a quantitative-empirical study. We developed a conceptual model that builds on previous research on organizational level continuance. We tested this model, using survey data gathered from decision makers of companies which have adopted cloud enterprise systems. The data was analyzed using PLS. The results show that continuance intention can be predicted both by socio-organizational and technology-related factors, explaining 55.9% of the dependent variable’s variance. Besides cloud-specific findings, the study also enhances knowledge in organizational level system continuance as well as its connection to ...

The digital and data-driven economy requires enterprises from all industries to revisit their exi... more The digital and data-driven economy requires enterprises from all industries to revisit their existing data management approaches. To address the changing and broader scope of data management activities in the digital economy, this research in progress paper proposes a reference model, that describes the design areas of data management.

Data governance sets standards and guidelines for the major decision areas and tasks in data qual... more Data governance sets standards and guidelines for the major decision areas and tasks in data quality management decision areas and tasks in data quality management Data quality strategy Alignment with business strategy, business benefits of DQM, measurement and control of DQM DQM controlling Measures and metrics scorecards incentive systems Measures and metrics, scorecards, incentive systems Organization and processes Assignment of roles, definition of data management processes

Freight exchanges are central to the logistics industry, as they reduce empty runs and meet spot ... more Freight exchanges are central to the logistics industry, as they reduce empty runs and meet spot demands. To improve their efficiency in terms of automation and enhance trust between the participants, we propose a decentralized freight exchange implemented using public blockchains. With our solution, we also address shortcomings of public blockchains, such as scalability and privacy. We present two artifacts: a general architecture for an electronic logistics marketplace (ELM) and a concrete implementation as the proof of concept for a freight exchange. The solution is implemented using two off-the-shelf public blockchains and a public distributed file system. Additionally, we investigate the implications for the general ELM model and show that an ELM based on a blockchain can be viewed as infrastructure rather than a market participant.

Data Governance defines roles and responsibilities for the management and use of corporate data. ... more Data Governance defines roles and responsibilities for the management and use of corporate data. While the need for Data Governance is undoubted, companies often encounter difficulties in designing Data Governance in their organization. There is no one size fits all solution. As companies are different in terms of their business strategy, their diversification breadth, their industry, IT strategy and application system landscape, Data Governance must take into account this diversity. What works in company A does not necessarily work in company B. An example: A company from the chemical industry organizes data stewardship as a virtual organization with solid reporting lines to the business functions (e.g. supply chain management, financial accounting) whereas a second company of similar size, product range and geographic presence establishes a shared service center to organize data stewards.The presentation introduces a reference model for Data Governance design which was developed b...

Proceedings of the 54th Hawaii International Conference on System Sciences, 2021

Despite being in competitive relations, organizations increasingly engage in data-centric collabo... more Despite being in competitive relations, organizations increasingly engage in data-centric collaborations to utilize access and provision to distributed data sources. Over time, these relations have evolved from dyadic relationships to the emergence of complex ecosystems. These ecosystems are characterized by multiple autonomous organizations that engage in data sharing to leverage data-driven innovation. For value propositions based on data to materialize, the configuration of data governance can provide fundamental control mechanisms that influence the design, dynamics and success of the collaboration. In the context of ecosystems, data governance is considered an under-researched topic. This paper investigates both concepts and identifies the main conceptual characteristics of ecosystem data governance. We develop a taxonomy of ecosystem data governance that comprises eight dimensions and twenty four characteristics to improve the conceptual understanding of data governance in data ecosystems.

Proceedings of the 53rd Hawaii International Conference on System Sciences, 2020

The nature of business conduct is changing due to emerging digital technologies and the ever-incr... more The nature of business conduct is changing due to emerging digital technologies and the ever-increasing role of data as a critical resource. Traditional industry branches such as logistics need to adapt accordingly to keep up with change through digitization and to design adequate business models using data. The present article focuses on investigating the anatomy of these data-driven business models in the logistics sector. In order to achieve this goal, the study develops a taxonomy of data-driven business models in logistics. Start-ups serve as the frame of reference, as they are particularly suitable for deriving explicitly novel and vital business models. The study focuses on two particular types of data-driven business models, namely those offering visibility or optimization services in logistics. The goal of the taxonomy is to uncover the structural composition of such business models and to make the results usable as a morphology for innovation.