Markus Schief

A comprehensive approach towards the structural description of business models

Research on business models has attracted raising consideration among scientists since the burst of the dot-com bubble. However, knowledge on this domain is still quite fragmented which calls for a clarification and in particular a structured conceptualization. Thus, this paper presents a business model ontology that is based on a literature review contrasting and synthesizing eight existing ontologies and extending this knowledge with current understanding and research progress on business models. For sake of clarity, our developed ontology comprises two levels. While the first level focuses on the surrounding of a business model describing the relationships of a business model to its environment, the second level of detail addresses the actual details of the model -- entities and relationships that constitute a business model. Besides describing the proposed ontology by abstract textual and graphical means, the description is underpinned by illustrative examples.

Towards Agile Business Processes Based on the Internet of Things

Though agility is a core demand for firms, software based process modeling and execution approaches realize strict and inflexible formalization. We propose an extension of process modeling and execution based on the integration of real world information as trigger for process variance. As decisions are knowledge-intensive they are propagated to knowledge workers to support the decision process. These activities are again tracked, to identify demand for process redesign. Thus, processes become basis for proactive support and a representation of reality, even in change-ridden domains.

The Relation Between Dynamic Business Models and Business Cases

This paper analyses the relation between two well-known business concepts. It clarifies how business models, as an implementation of a company’s strategy, can be aligned with business cases, as an abstraction of a company’s operations. The relations are analyzed from a static as well as a dynamic point of view by means of inductive reasoning and literature review. Based on the understanding of the relations, a continuous business model-business case alignment approach is proposed. Further, managerial guidelines are presented supporting the approach. Finally, two software tools, business case framework and business model composer, are presented indicating how the proposed conceptual alignment could be implemented. This paper contributes to research and practice. Both can benefit from the conceptual relation between two well-known concepts that have hardly been linked so far. Practitioners can apply the proposed alignment approach and the managerial guidelines to review their business. For research, we contribute to the body of knowledge of business model concepts. Researchers can build upon this fruitful ground by validating the proposed concept in empirical settings or by implementing software solutions supporting this approach. Consequently, the agility of companies can be increased when implementing merged or changed business models in the organization and when using business cases to determine if it is time to change the business model.

The Impact of Software Business Model Characteristics on Firm Performance

Business models have become a topic of increasing academic interest and have emerged as a unit of analysis for performance studies. The software industry has been the source of major business model innovations and is hence of particular interest to researchers and practitioners. In this paper we collect business model data for 120 public U.S. software firms. While some data can be retrieved from Thomson Reuters database, most variables specific to the software firms are obtained from a tedious expert classification of 10-K and 20-F annual reports. The results show that the business model variables under study significantly impact financial performance, but are hardly reflected in market performance. Thus, they determine firm success, but do not necessarily affect investor decisions. Our cross-disciplinary research is rooted in the fields of strategic management and software business. We contribute by providing insights into business model characteristics and the determinants of software firm performance.

Mergers and Acquisitions in the Software Industry Research - Results in the Area of Success Determinants

This paper analyzes approaches investigating success drivers of mergers and acquisitions (M&A) in the software industry. The literature review covers a classification of research papers in the generic and software industry specific M&A research discipline. The results accentuate that the impact of success factors depends on the research context and that many factors have not been examined so far with respect to the software industry. Building on these insights, the resulting areas for research are pointed out. The investigation of software industry specific factors, in particular, promises to contribute to the analysis of variance in M&A performance.

Software Business Model Tool

This section presents a software business model tool incorporating some of the content developed in the previous sections. Section 6.1 introduces the business scenarios and the resulting requirements. Accordingly, Section 6.2 develops the architecture of a software business model tool that addresses the requirements. Section 6.3 then describes the scope and functionalities of the implemented prototype. Additionally, details on the technical scope and mode of realization are summarized. Finally, the tool is evaluated based on empirical usage data and judgments of software firm decision makers in Section 6.4. The evaluation shows that the software business model tool is highly appreciated by practitioners. Nevertheless, being only a first prototype with limited scope, further work is needed to incorporate additional data and functionalities and hence to provide a comprehensive decision support system assisting in the management of software business models.

Software Business Model Characteristics

This section develops the conceptualization of the software business model characteristics. The literature review in Section 2.2 emphasizes value as a business model’s center of gravity. Accordingly, Section 3.1 analyzes how value is generated in the software industry by developing an industry-specific value chain. Morris et al. (2005, p. 728) claim that a firm’s value chain is a major foundation of every business model. The software value chain builds hence a central part of the software business model framework, which is developed subsequently in Section 3.1. Beyond the value chain it builds upon the state-of-the-art in generic and software industry-specific business model concepts as well as upon the software industry’s economic properties. Finally, empirical analyses provide a software industry overview.

The Impact on Firm Performance

This section analyzes the impact of software business model characteristics on firm performance. In this regard, three evaluation models are analyzed based on three different empirical data sets. The first study in Section 4.1 covers the most comprehensive set of business model characteristics. Out of the 25 components introduced in Section 3.2.3, 19 variables are derived that are analyzed based on a sample of 94 software firms. The data stems from the German Software Industry Survey, which is presented in Section 3.3. The subsequent two studies are based on secondary data sources, namely firms’ annual reports and financial databases. For these studies, fewer software business model variables can be analyzed as the information in secondary data sources is limited. The study in Section 4.2 explores the impact of eight software business model variables based on a sample of the global top 100 software firms.

The Impact on M&A Performance

This section analyzes the impact of software business model characteristics on M&A performance. The study builds upon the same sample firms and software business model characteristics as the study in Section 4.3. Accordingly, this study examines the impact of eight software business model variables on M&A performance based on a sample consisting of the 120 largest software firms listed on U.S. stock exchanges. Section 5.1 presents the theoretical background of the M&A study and derives hypothesis for the subsequent analyses. Section 5.2 describes the sample of the study. In this light, both the acquirer and the target selection are defined. Additionally, the software business model characteristics under study and the presented performance variables are described. Section 5.3 reports the results of the study. Descriptive statistics show the overall effect and details on the properties of the takeovers under study.

Fusionen und Unternehmensübernahmen in der Softwareindustrie

ZusammenfassungDer Beitrag untersucht Ansätze zur Bewertung von Erfolgsdeterminanten bei Mergers & Acquisitions (M&A) in der Softwareindustrie. Auf der Basis einer Literaturanalyse und -klassifikation wird der aktuelle Stand der branchenübergreifenden sowie der softwareindustriespezifischen Forschung aufgezeigt. Die Resultate belegen, dass die Wirkung von Erfolgsdeterminanten kontextabhängig ist und dass viele Faktoren bislang nicht hinreichend für die Softwareindustrie untersucht worden sind. Darauf aufbauend wird der weitere Forschungsbedarf aufgezeigt. Dabei verspricht insbesondere die Berücksichtigung software-industriespezifischer Erfolgsdeterminanten einen zusätzlichen Erklärungsbeitrag zu liefern.AbstractThis paper analyzes approaches investigating success drivers of mergers and acquisitions (M&A) in the software industry. The literature review covers a classification of research papers in the generic and software industry specific M&A research discipline. The results accentuate that the impact of success factors depends on the research context and that many factors have not been examined so far with respect to the software industry. Building on these insights, the resulting areas for research are pointed out. The investigation of software industry specific factors, in particular, promises to contribute to the analysis of variance in M&A performance.