The Evaluation Aspect of Digital Business Model Innovation

Tesch, Jan F.; Brillinger, Anne-Sophie

doi:10.1007/978-3-319-98723-1_4

Cited by 17 publications

(30 citation statements)

References 62 publications

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“…In general, tools and methods, supporting managers and organizations in business model innovation [3,37] through the visualization [42] or the evaluation of business models [44], are available. However, the evaluation of business models should not only focus on the estimation of returns, but also on identifying relevant risk factors, such as knowledge risks, in a business model [5].…”

Section: Background and Related Workmentioning

confidence: 99%

“…To address this gap, in line with the call for more research on managing knowledge risks in strategic Information Systems (IS) settings [31] and the call for research in IS on tooling for risk management in business model innovation based on digital technologies [44], we have developed an artifact to identify knowledge risks in DDBMs in a Design Science Research project within one case organization [15]. The essence of the artifact is a network-based representation of a business model, i.e.…”

Section: Introductionmentioning

confidence: 99%

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A Network-based Tool for Identifying Knowledge Risks in Data-Driven Business Models

Fruhwirth

Pammer-Schindler²,

Thalmann

2021

Proceedings of the Annual Hawaii International Conference on System Sciences

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Data-driven technologies enable organizations to innovate new services and business models and thus hold the potential for new sources of revenue and business growth. However, such new data-driven business models impose new ways for unwanted knowledge spillovers. Current research on datadriven business models and knowledge risks provides little help to identify and discuss such novel risks within the innovation process. We have developed a network-based representation of data-driven business models within one case organization, where it helped to identify knowledge risks in the design process of data-driven business models. In this paper, we further evaluated the artifact through 17 interviews with experts from the domain of business models, data analytics and knowledge management. We found that the network-based representation is suitable to visualize, discuss and create awareness for knowledge risks and see types of data-related value objects and quantification of risks as two recommendations for further research.

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Section: Background and Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Network-based Tool for Identifying Knowledge Risks in Data-Driven Business Models

Fruhwirth

Pammer-Schindler²,

Thalmann

2021

Proceedings of the Annual Hawaii International Conference on System Sciences

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show abstract

“…Dijital dönüşüm işletmelerde yıkıcı bir değişikliğe sebep verdiği için işletmelerin tüm dijital dönüşüm sürecini planlayan, yürüten, kontrol eden ve başarısını ölçen, bütüncül bir dijital dönüşüm stratejisine ihtiyacı vardır (Kofler, 2018 İşletmelerdeki dijital dönüşüm hakkında yapılan kaynak araştırmasında dijital dönüşümü tetikleyen etmenler aranmıştır. Bazı kaynaklar işletmelerdeki dijital dönüşümü genel olarak ele alırken (Chanias, 2017;Ezeokoli vd., 2016;Kane vd., 2015;Kofler, 2018;Liere-Netheler vd., 2018;Morakanye vd., 2017;Pflaum & Schulz, 2018;Tesch & Brillinger, 2017;Verina & Titko, 2019), bazıları sadece iş modellerinin dönüşümü olarak görmektedir (Anderson & Kupp, 2008;Burmeister vd., 2016;Chesbrough, 2010;de Reuver & Bouwman, 2009;Foss & Saebi, 2017;Wirtz & Daiser, 2017).…”

Section: İşletmelerde Dijital Dönüşümü Tetikleyen Etmenlerunclassified

Digital Transformation in Businesses and Its Drivers

Klein¹

2020

Journal of Business in the Digital Age

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In recent years, the digitalization starting with digitizing anolog data proceeding with digitalization of business processes is being replaced by digital transformation. In addition to business models getting value with personalized products, ecosystem partnerships formed by many different companies become widespread and increase the competition in the market. Digital transformation influence and transform the whole operation, organization and even the company culture of businesses. Digital transformation as a disruptive and complex process needs an integrative digital transformation strategy comprising all fields of businesses undergoing the transformation. The aim of this study is to determine those fields of businesses concerned with digital transformation and the drivers of business digital transformation by literature review and to develop a conceptual model displaying the cause and effect relationship among them, in order to support businesses by determining digital transformation scenarios and by developing suitable digital transformation strategies.

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“…Current trends of the so-called New Digital Economy can include: Scientific research of business digitization refers to many areas such as value migration to the sustainable business models of digital economy companies on the capital market (Jabłoński, 2018); transformation of business models of traditional sectors towards the digital economy (Remane, Hanelt, Nickerson, & Kolbe, 2017); evaluation aspect of digital business model innovation (Tesch & Brillinger, 2017); and the Internet of Things (Ng & Wakenshau, 2017). This results in the emergence of new business models.…”

Section: The Influence Of a Digital Economy Paradigm For The Developmmentioning

confidence: 99%

The Critical Aspects of Value Migration from Volatile Business Models in the Digital Economy

Jabłoński

2019

Journal of Creating Value

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Value is interdisciplinary and, in a broader context, is responsible for forming and bonding the expected configuration of the business model. A business model may allow for capturing value or losing it through inconsistency. It can capture value from customers and other stakeholders, such as investors. If a business model is consistent, then stakeholders believe in it and it attracts value. In practice, many business models are volatile, that is, unstable and highly susceptible to many factors, which make them incapable of ensuring success. This issue is an important area of scientific exploration, inasmuch as the issue of the volatility of business models and the associated negative consequences, in particular the migration of value, have been discussed to a limited extent. The article discusses the volatility of business models and its impact on value migration. Research into the volatility of companies operating in the digital economy listed on the alternative market of the Warsaw Stock Exchange has been presented. Key factors responsible for the volatility of business models of the companies surveyed have been shown in the context of value migration.

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The Evaluation Aspect of Digital Business Model Innovation

Cited by 17 publications

References 62 publications

A Network-based Tool for Identifying Knowledge Risks in Data-Driven Business Models

A Network-based Tool for Identifying Knowledge Risks in Data-Driven Business Models

Digital Transformation in Businesses and Its Drivers

The Critical Aspects of Value Migration from Volatile Business Models in the Digital Economy

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