Business models, value capture, and the digital enterprise

Teece, David J.; Linden, Greg

doi:10.1186/s41469-017-0018-x

Cited by 232 publications

(224 citation statements)

References 28 publications

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“…Smart products. It is explained by Teece and Linden [69] that smart products, and the services built upon them, can create new business models. Nowadays, simply selling physical products might not be enough in the digital era.…”

Section: Review and Discussionmentioning

confidence: 99%

“…The offering of digital services is primarily based on data and can fit with the overall corporate strategy [49]. "Ultimately, any privately offered digital service must pay its own way, directly or indirectly, by capturing a share of the value it creates if it is to be a sustainable business" [69]. As a result of the importance of services, companies have, across the business landscape, embraced service as an engine of their firms' growth [9].…”

Section: Review and Discussionmentioning

confidence: 99%

“…Business managers have to understand and augment the full range of their organization's capabilities if they design and implement digital business models that track the evolution of technology and consumer demand. These capabilities are embedded in both organizational routines and managerial cognition [69].…”

Section: Target and Basis Of A Digital Business Modelmentioning

confidence: 99%

“…In fact, digitalization impacts entire business models; it not only questions incumbent ways of doing business but also offers opportunities for new start-ups [7]. The pace of technological progress and business innovation seems to have accelerated in recent decades, with the result that sustainably profitable business models are harder than ever to craft [69]. This could be a reason why many companies, such as Blackberry or BenQ, or Nokia, failed.…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

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Behind the Blackbox of Digital Business Models

Ahmad¹,

Botzkowski²,

Klötzer³

et al. 2020

Proceedings of the Annual Hawaii International Conference on System Sciences

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In recent years global competition has undergone significant change as a result of the increasing digitalization or digital transformation of business and society. New forms of value creation have emerged, particularly through the emergence of companies such as Google and Facebook, and other digital disruptors. As a result of these developments, established companies face the challenge of aligning their business model with the new circumstances. One way of doing this is digitalization of the existing business model or designing a completely new digital business model. In this context, however, there is no commonly accepted definition and understanding of the nature of digital business models representing the context of Industry 4.0, cyber-physical systems, and the Internet of Things. So, this work is based on a literature review to help understand the concept of a digital business model. With this contribution, we enable scientific added value for business model research and at the same time help business practice to understand exactly what a digital business model is and which levers of transformation need to be considered.

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Section: Review and Discussionmentioning

confidence: 99%

Section: Review and Discussionmentioning

confidence: 99%

Section: Target and Basis Of A Digital Business Modelmentioning

confidence: 99%

Section: Conclusion and Future Researchmentioning

confidence: 99%

See 2 more Smart Citations

Behind the Blackbox of Digital Business Models

Ahmad¹,

Botzkowski²,

Klötzer³

et al. 2020

Proceedings of the Annual Hawaii International Conference on System Sciences

View full text Add to dashboard Cite

show abstract

“…This is a strong indicator that the way businesses compete, collaborate, and operate is changing. The competition is accelerating and encompasses the next-generation competition (Teece, et al 2017); and big data is part of the driver for this acceleration.…”

Section: Figure 1 -Multiple Sources Of Datamentioning

confidence: 99%

Organizational Design of Big Data and Analytics Teams

Hammerström¹

2018

European Journal of Social Science Education and Research

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Although many would argue that the most important factor for the success of a big data project is the process of analyzing the data, it is more important to staff, structure and organize the participants involved to ensure an efficient collaboration within the team and an effective use of the tool sets, the relevant applications and a customized flow of information. A main challenge of big data projects originates from the amount of people involved and that need to collaborate, the need for a higher and specific education, the defined approach to solve the analytical problem that is undefined in many cases, the data-set itself (structured or unstructured) and the required hard- and software (such as analysis-software or self-learning algorithms). Today there is neither an organizational framework nor overarching guidelines for the creation of a high-performance analytics team and its organizational integration available. This paper builds upon (a) the organizational design of a team for a big data project, (b) the relevant roles and competencies (such as programming or communication skills) of the members of the team and (c) the form in which they are connected and managed.

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Building blockchain‐driven dynamic capabilities for developing circular supply chain: Rethinking the role of sensing, seizing, and reconfiguring

et al. 2023

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Globally, firms face increasing pressure to efficiently utilize resources and minimize costs and may do so through sustainable supply chains and circular economy practices. Emerging technologies, such as blockchain, to enable a circular economy have become a new industrial paradigm. However, firms require building dynamic capabilities through blockchain, which can be key to realizing circular economy model. This study introduces a framework for building blockchain‐driven dynamic capabilities for a circular supply chain. We further use the Decision Making Trial and Evaluation Laboratory (DEMATEL) method to evaluate three major dynamic capabilities and 18 sub‐dynamic capabilities and their interrelationships. The mining industry in Ghana sets the stage for this analysis. The study results show that although blockchain‐driven sensing dynamic capability, seizing dynamic capability, and reconfiguring dynamic capability are crucial for developing a circular supply chain, they do not strictly follow a sequence and overlap. We highlight various cause–effect relationships, providing insights into the role of sensing, seizing, and reconfiguring dynamic capabilities. That information is important to firms, stakeholders, and partners to draft an appropriate strategy to build blockchain‐driven dynamic capabilities for developing a circular supply chain.

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Business models, value capture, and the digital enterprise

Cited by 232 publications

References 28 publications

Behind the Blackbox of Digital Business Models

Behind the Blackbox of Digital Business Models

Organizational Design of Big Data and Analytics Teams

Building blockchain‐driven dynamic capabilities for developing circular supply chain: Rethinking the role of sensing, seizing, and reconfiguring

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