Editorial: Standardization in a Digital and Global World: State-of-the-Art and Future Perspectives

Viardot, Éric; McCarthy, Ian P.; Jin, Chen

doi:10.1109/tem.2020.3006302

Cited by 8 publications

(7 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As mentioned earlier, we assume the context of standardized ES provided by a software vendor as a boundary for our DPs with the goal of supporting an ML solution implementation by a mass market. This assumption is a reasonable one since ES is the de facto standard for enterprise software on the market and ML belongs to the class of enterprise application software used in companies [12]. Because the ML marketplace provides pre-trained ML models, they must be integrated into the corresponding ES of the marketplace participant.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Design Principles for Machine Learning Marketplaces in Enterprise Systems

Hütsch¹,

Wulfert²

2022

Proceedings of the Annual Hawaii International Conference on System Sciences

View full text Add to dashboard Cite

While standardized enterprise systems (ES) have become widely accepted, this is not the case for machine learning (ML) implementations, which are mostly developed individually in company-specific projects. Necessary historical data and rare ML capabilities result in a low cross-market ML utilization. To overcome the high usage barriers of ML, it should be incorporated into ES in a standardized manner. Therefore, we propose to implement an ML marketplace. While marketplaces in ES already exist, this paper proposes a marketplace dedicated to the exchange of ML models in a federated learning approach. Accordingly, this work formulates four meta-requirements based on interviews, which are structured by marketplace governance dimensions. With these meta-requirements, an ML marketplace was implemented in a design science research project, from which eight design principles are derived. The design principles address governance dimensions for making ML accessible to many companies and allow them to integrate ML into existing ES.

show abstract

Section: Discussionmentioning

confidence: 99%

“…Thus, an ML marketplace is helpful in achieving faster market penetration of ML standards across companies. Achieving a de facto standard of ML usage would mean that a large number of companies use ML in a similar way [12]. Probably caused by the minimal standardization of ML in ES, the market penetration of ML in companies is low [13].…”

Section: Introductionmentioning

confidence: 99%

Design Principles for Machine Learning Marketplaces in Enterprise Systems

Hütsch¹,

Wulfert²

2022

Proceedings of the Annual Hawaii International Conference on System Sciences

View full text Add to dashboard Cite

show abstract

“…Layered system architectures and platforms [20] are considered to promote generativity and provide open interfaces for other organizations to contribute to the system. These types of system architectures are connected to platform-based approaches to do business amid a large network of actors in an organizational ecosystem [46], [48] stressing a possibility to achieve market control through standardization [49].…”

Section: B Cops and Digitalizationmentioning

confidence: 99%

“…While platform-based approaches were initially explored as internal or supply chain platforms [24] there is an increasing focus on platforms as a new way of organizing within a large network of actors in an organizational ecosystem [22]. It appears that the main rationale for platforms in IT and mobile technology is the ability to master the combination of market control and generativity [49] while for CoPS industries we find the rationale to be an ability to master the unique combination of system criticality and generativity.…”

Section: A Avenue 1: Generativity In Safety-critical Systemsmentioning

confidence: 99%

Digital Transformation in Complex Systems

Lakemond

Holmberg

Pettersson³

2024

IEEE Trans. Eng. Manage.

View full text Add to dashboard Cite

Complex systems increasingly include embedded digital technologies that interact with and are constrained by physical components and systems. Although these systems play a central role in our society, they have only been scarcely addressed in contemporary research on digital transformation and the organization of innovation. This article explores the digital transformation in complex products and systems and its consequences for organizational design. A longitudinal study of avionics development since the 1950s uncovers the application of digital technologies, first as a sequence of initial experiments, followed by the use as add-on functionality, then as an integral part of achieving critical functionality in systems, and currently combining add-on and critical functionalities enabling generativity. The findings emphasize the evolution of the intricate relationships between the systems architecture and organizational approaches when digital technology enables and enforces increased complexity, expanded functionality, increased systems integration, and continuous development. These nested dependencies are accentuated by the complexity that has emerged beyond human cognition, where increasingly sophisticated boundary objects based on modeling, simulation, and data play an important role in the organization's ability. Boundary objects relate and decouple the multifacetted dynamic relation between organization and architecture. The results also extend existing perspectives on platform strategies by outlining the importance of generativity in combination with criticality control, rather than market control. Criticality control in combination with generativity has become imperative not least as generative digital technologies have become central in achieving critical properties such as safety. Several avenues for further research are outlined.

show abstract

“…Establishing consensus among independent ecosystem participants, standards amplify e-commerce ecosystems by ensuring a proper value proposition (Adner, 2017 ; Papachristos & van de Kaa, 2021 ; Staudenmayer et al, 2005 ). Technical standards are defined as “the characteristics of a product as well as its level of performance, safety, or quality” (Viardot et al, 2021 , p. 11). Standards can be defined generally and within e-commerce ecosystems by standard-setting organizations or competitive market forces that most likely are the platform owners (de facto standard) or enforced by law (de jure standard).…”

Section: Introductionmentioning

confidence: 99%

Developing design principles to standardize e-commerce ecosystems

et al. 2022

View full text Add to dashboard Cite

Platform ecosystems have captured a variety of markets, enabling coordination, transactions, and value co-creation between independent actors. A focal platform constitutes the central nexus of e-commerce ecosystems and fosters the interaction among ecosystem participants through their boundary resources. Standardizing these interfaces simplifies ecosystem entry for developers and increases the number of participants propelling the network effects, and thus the overall value of the ecosystem. Currently, there is a lack of prescriptive design knowledge guiding platform owners in designing successful e-commerce ecosystems. Addressing this issue, we followed a dual approach, reporting on a systematic literature review in which we identified design requirements and complemented these with a multiple-case study on selected e-commerce ecosystems. Aggregating the requirements resulted in six meta-requirements and 19 design principles that foster the standardization of focal e-commerce platforms. Our design principles simplify the development of complements and enable multi-homing for developers due to possible standardization across ecosystems.

show abstract

Editorial: Standardization in a Digital and Global World: State-of-the-Art and Future Perspectives

Cited by 8 publications

References 23 publications

Design Principles for Machine Learning Marketplaces in Enterprise Systems

Design Principles for Machine Learning Marketplaces in Enterprise Systems

Digital Transformation in Complex Systems

Developing design principles to standardize e-commerce ecosystems

Contact Info

Product

Resources

About