Articles

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Business model stress testing: A practical approach to test the robustness of a business model

Business models and business model innovation are increasingly gaining attention in practice as well as in academic literature. However, the robustness of business models (BM) is seldom tested vis-à-vis the fast and unpredictable changes in digital technologies, regulation and markets. The evaluation of the robustness of a BM raises several issues, such as how to describe the business model in a structured way, how to determine a relevant set of changes to test against, how to assess their impact on business model components, and how to use the results of the assessment to strengthen the business model. In this paper, we propose business model stress testing as a practical approach to evaluate the robustness of business model components. The method builds upon concepts from business model innovation and scenario planning. We illustrate our approach using a case example. Our approach enables testing individual business model components as well as the interrelation between components. The approach visualizes challenges and suggests ways to increase the robustness of BM. The stress testing approach is particularly useful in a stage of business model experimentation, i.e. if a company has to choose between alternative business models or still has to implement the business model. The underlying software tool is openly available for reuse and further development. The paper contributes to futures research literature by delivering the first method that allows to test the robustness of business models against future uncertainties.

The Framework of Business Model in the Context of Industrial Internet of Things

The purpose of this article is an attempt to develop the concept of a business model dedicated to companies implementing technologies of the Industrial Internet of Things. The proposed concept has been developed to support traditional companies in the transition to the digital market. The study was based on the available literature on the impact the Industrial Internet of Things has on the economy and business models.

The Cambridge Business Model Innovation Process

Organisations increasingly understand that meeting their sustainability ambitions does not only require new technologies, but innovation on the business model level. To facilitate the design of more sustainable business models, a range of new tools and techniques have been developed. While this resulted in the design of a wide range of promising business models, only very few are successfully implemented. The Cambridge Business Model Innovation Process is a framework developed to guide organisations’ business model innovation efforts and map the necessary activities and potential challenges. In this paper, we introduce the framework and present an exploratory attempt of applying it to a social start-up. The preliminary result of this experience led us to build a comprehensive research agenda that aims at developing tools and processes to help organisations in bridging the design-implementation gap in sustainable business model innovation.

An Explanatory Study on the Co-evolutionary Mechanisms of Business IT Alignment

Business IT Alignment is considered an enduring topic in academic and practitioners’ literature. The interest in the subject is justified by the link, demonstrated by several studies, between alignment and corporate performances. However, alignment research has not yet been translated into practices, theoretically demonstrated in literature and applied to companies. The interpretation of alignment as a function of independent factors and the underestimation of the complex nature of alignment process are considered key barriers in alignment achievement. The present study is based on a multi-case study analysis carried out in two companies that implemented alignment processes. We conceptualise alignment as a co-evolution process and derive four mechanisms and three types of parameters and explain their role in alignment implementation. The contribution is theoretical, since we analyse and describe mechanisms and factors that govern alignment, and for the practitioners, since knowledge of these mechanisms is precondition for an effective alignment implementation.

Analytics, Innovativeness, and Innovation Performance

Based on organizational information processing theory, this paper develops and tests a research model to deepen the understanding about the conditions under which the use of data analytics contributes to innovation performance. This paper suggests that firm innovativeness, as an organization cultural concept, should moderate the relationship between data analytics use and innovation performance. The results of a moderation analysis based on data from cross-sectional survey support this account. The findings indicate a significant inversely U-shaped effect of innovativeness on the relationship between data analytics use and innovation performance. The effect of data analytics use on innovation performance is strongest under medium levels of innovativeness but comparatively weaker when firms have a low or a high level of innovativeness. These insights contribute to the IS literature by clarifying the important role of firm cultural factors in shaping information needs and deployment of information processing capabilities.

Connected Enterprise Meets Connected Customer – A Design Approach

In an increasingly digitized environment, enterprises face new challenges. Enabled by ubiquitous Internet accessibility, people, places, and products have become more interconnected and are gradually merging into the Internet of Everything. Simultaneously, a new generation of connected customers is emerging that is establishing new requirements for the capabilities of enterprises to communicate, interact, and respond to unforeseen events. As customer satisfaction is the central source of future competitiveness, companies must initiate a transformation towards a connected enterprise. By analyzing the characteristics of the connected customer, this paper presents guidelines for enterprises to address customer needs adequately and manage their operations in the Internet of Everything. Building upon established enterprise architecture frameworks, we apply a Design Science Research procedure to derive four practical recommendations. Thus, enterprises must manage their business processes holistically, implement information systems and standards for data exchange, provide mechanisms for real-time business intelligence, and determine their optimal degree of connectivity.