Requirement-driven Taxonomy Development – A Classification of Blockchain Technologies for Securities Post-Trading

Notheisen, Benedikt; Willrich, Sven; Diez, Maximilian; Weinhardt, Christof

doi:10.24251/hicss.2019.558

Cited by 7 publications

(4 citation statements)

References 27 publications

(56 reference statements)

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“…Relating to taxonomy research, we have identified several dimensions that stress the potential need for domainspecific taxonomy design. The contribution is similar to adjacent studies proposing novel ways to build taxonomies for a specific purpose -context-specific artifacts, for example, the requirements-driven taxonomy design of Notheisen et al (2019) or the taxonomy design method of Sarkintudu et al (2018). Design decisions, like focusing on a broad or narrow level of conceptual analysis, should be explained in any taxonomy.…”

Section: Implications and Limitationsmentioning

confidence: 88%

Designing business model taxonomies – synthesis and guidance from information systems research

et al. 2021

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Classification is an essential approach in business model research. Empirical classifications, termed taxonomies, are widespread in and beyond Information Systems (IS) and enjoy high popularity as both stand-alone artifacts and the foundation for further application. In this article, we focus on the study of empirical business model taxonomies for two reasons. Firstly, as these taxonomies serve as a tool to store empirical data about business models, we investigate their coverage of different industries and technologies. Secondly, as they are emerging artifacts in IS research, we aim to strengthen rigor in their design by illustrating essential design dimensions and characteristics. In doing this, we contribute to research and practice by synthesizing the diffusion of business model taxonomies that helps to draw on the available body of empirical knowledge and providing artifact-specific guidance for building taxonomies in the context of business models.

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Section: Implications and Limitationsmentioning

confidence: 88%

Designing business model taxonomies – synthesis and guidance from information systems research

et al. 2021

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“…Next to these general activities, other researchers present more specific guidelines for testing taxonomies with conceptual and analytical models (Doty and Glick 1994) or for typical taxonomy building issues (Hambrick 1984). Additional guidance focuses on fields such as requirements-driven taxonomies (Notheisen et al 2019) or business reporting taxonomies (Ojala et al 2018). A detailed overview of related guidance on taxonomy design can be found in Appendix 1 (available online via http://link.springer.com).…”

Section: Taxonomy Development In Information Systems and Adjacent Fieldsmentioning

confidence: 99%

An Update for Taxonomy Designers

et al. 2021

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Taxonomies are classification systems that help researchers conceptualize phenomena based on their dimensions and characteristics. To address the problem of ‘ad-hoc’ taxonomy building, Nickerson et al. (2013) proposed a rigorous taxonomy development method for information systems researchers. Eight years on, however, the status quo of taxonomy research shows that the application of this method lacks consistency and transparency and that further guidance on taxonomy evaluation is needed. To fill these gaps, this study (1) advances existing methodological guidance and (2) extends this guidance with regards to taxonomy evaluation. Informed by insights gained from an analysis of 164 taxonomy articles published in information systems outlets, this study presents an extended taxonomy design process together with 26 operational taxonomy design recommendations. Representing an update for taxonomy designers, it contributes to the prescriptive knowledge on taxonomy design and seeks to augment both rigorous taxonomy building and evaluation.

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“…It has been argued that this lack of a clear positioning of DLT systems leads to a fragmentation in the DLT community and a duplication of effort [76]. The significance of this challenge is reflected in the recent taxonomies of distributed ledgers [55,76,82,[86][87][88].…”

Section: Introductionmentioning

confidence: 99%

Decrypting distributed ledger design—taxonomy, classification and blockchain community evaluation

2021

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More than 1000 distributed ledger technology (DLT) systems raising $600 billion in investment in 2016 feature the unprecedented and disruptive potential of blockchain technology. A systematic and data-driven analysis, comparison and rigorous evaluation of the different design choices of distributed ledgers and their implications is a challenge. The rapidly evolving nature of the blockchain landscape hinders reaching a common understanding of the techno-socio-economic design space of distributed ledgers and the cryptoeconomies they support. To fill this gap, this paper makes the following contributions: (i) A conceptual architecture of DLT systems with which (ii) a taxonomy is designed and (iii) a rigorous classification of DLT systems is made using real-world data and wisdom of the crowd. (iv) A DLT design guideline is the end result of applying machine learning methodologies on the classification data. Compared to related work and as defined in earlier taxonomy theory, the proposed taxonomy is highly comprehensive, robust, explanatory and extensible. The findings of this paper can provide new insights and better understanding of the key design choices evolving the modeling complexity of DLT systems, while identifying opportunities for new research contributions and business innovation.

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Requirement-driven Taxonomy Development – A Classification of Blockchain Technologies for Securities Post-Trading

Cited by 7 publications

References 27 publications

Designing business model taxonomies – synthesis and guidance from information systems research

Designing business model taxonomies – synthesis and guidance from information systems research

An Update for Taxonomy Designers

Decrypting distributed ledger design—taxonomy, classification and blockchain community evaluation

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