Different patterns in the evolution of digital and non-digital ventures' business models

Konig, Marc; Ungerer, Christina; Baltes, Guido; Terzidis, Orestis

doi:10.1016/j.techfore.2018.05.006

Cited by 73 publications

(52 citation statements)

References 39 publications

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“…In general, the method of hierarchical clustering based on weighted document-term matrices with relevant architecture keywords is an agile statistical approach that can be implemented in similar scenarios, provided a reliable document corpus exists. Last but not least, we contribute to the business model literature that examines business models in their exogenous and environmental context (Bohnsack et al, 2014;König et al, 2019;Magistretti & Dell'Era, 2019;Yun et al, 2019) . Future research may examine larger datasets of firms, also from other sectors, to understand if there are archetypical business model schemes that drive change in their environment.…”

Section: Discussionmentioning

confidence: 99%

“…A broader scope (e.g. multiple products in multiple industries) helps to uncover the latent potential of the technology, creating the possibility to identify underlying needs and application areas that were previously unknown (König, Ungerer, Baltes, & Terzidis, 2019;Magistretti & Dell'Era, 2019;Schmeiss & Friederici, 2019;Trabucchi et al, 2019) .…”

Section: Business Model Researchmentioning

confidence: 99%

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The Business Model as Mediator during Socio-Technical Transitions - Empirical Evidence from Applied AI Technology Startups in the Energy and Transportation Sector

Schmeiss¹,

Stephany²,

Tech³

2019

Preprint

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Firms are an important driver of socio-technical transitions, where a technological innovation moves from a protected niche to a new dominant socio-technical regime. The firm's business model functions as an important mediator during this process, articulating a shared vision of what the technology can do. Following recent calls for a closer examination of the business model’s role during socio-technical transitions, we study 375 startups that develop applied AI technologies. Based on a large-scale semantic analysis of the startup’s website texts, we ran a statistical hierarchical clustering and identified three distinct roles: (1) expansion of the technology in scale and scope, (2) exploration of the technology in-depth, (3) new ways of interacting with technology.

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Section: Discussionmentioning

confidence: 99%

Section: Business Model Researchmentioning

confidence: 99%

The Business Model as Mediator during Socio-Technical Transitions - Empirical Evidence from Applied AI Technology Startups in the Energy and Transportation Sector

Schmeiss¹,

Stephany²,

Tech³

2019

Preprint

View full text Add to dashboard Cite

show abstract

“…There is a distinction between innovative digital and non-digital undertakings. Combining practical management tools with the principles of network theory as well as the theory of organizational learning creates new possibilities for creating business models [30]. The specialist skills that change the existing balance of power in global markets are important for the development of digital business models [31], whereas digital ecosystems should provide companies based on innovative business models with attractive value sources that create new ways to grow [32].…”

Section: Digital Business Models-key Aspectsmentioning

confidence: 99%

Social Factors as a Basic Driver of the Digitalization of the Business Models of Railway Companies

Jabłoński

2019

Sustainability

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The aim of the paper is to present the results of research into the assessment of social factors resulting from the digitalization of railway companies’ business models and building, by means of the AHP method, a ranking of the significance of these criteria in the process of their digital transformation. The results focused on identifying the components of the business models of railway companies that are most affected by social factors and the creation of such factors. Railway companies do not operate within the business environment alone. In the context of processes, they form one common technical and service ecosystem. Digitalization should increase opportunities to create positive social effects which influence the quality of services provided and the safety of rail traffic as well as the increased efficiency of business models.

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“…In the last century, the economic performance and innovation success of countries has increasingly depended on digital technology developments [1]. Digitalization is broadly associated with the changes that relate to big data analytics, the adoption of digital technologies, and an increase in their utilization [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Digital Entrepreneurship and its Role in Innovation Systems: A Systematic Literature Review as a Basis for Future Research Avenues for Sustainable Transitions

2020

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Digital entrepreneurship is an essential driver within the innovation system. It changes the structure, aims, and networking mechanisms of the overall business system and, ultimately, affects the various levels and dimensions of the innovation system. Bringing inevitable changes to the innovation system, digital technologies may not only provide new business opportunities but also be disruptive and cause new vulnerabilities. In order to gain a rigorous understanding of the hybrid concept of digital entrepreneurship and its role within the transformation of the innovation system, we conducted a systematic literature review. The results of 52 core papers allow for the identification of key categories of digital entrepreneurship and also its differentiation from other types of business activities. The analysis leads to the distinction of the determinants of digital entrepreneurship within three core dimensions of the innovation system, which encompass the entrepreneur (including, e.g., behavioral, competence. and mentality patterns, as well as personal outcomes and consequences of entrepreneurial activity), the entrepreneurial process (including activities that concern digitalization in organizational management processes, transformations within strategic and operational activities, and digital start-up establishment), and its relevant ecosystem (which encompasses, among others, the influence that external infrastructure and institutions have on digital entrepreneurship development). The systematization of the existing literature is highly relevant for future research that aims to understand the interrelations between the transformation of entrepreneurial structures within innovation systems as well as the socioeconomic system in general. Such understanding requires further extended research in fields related to method, content, and theory.

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Different patterns in the evolution of digital and non-digital ventures' business models

Cited by 73 publications

References 39 publications

The Business Model as Mediator during Socio-Technical Transitions - Empirical Evidence from Applied AI Technology Startups in the Energy and Transportation Sector

The Business Model as Mediator during Socio-Technical Transitions - Empirical Evidence from Applied AI Technology Startups in the Energy and Transportation Sector

Social Factors as a Basic Driver of the Digitalization of the Business Models of Railway Companies

Digital Entrepreneurship and its Role in Innovation Systems: A Systematic Literature Review as a Basis for Future Research Avenues for Sustainable Transitions

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