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Record W2891744727

Feasibility of Blockchain Applications

2018· article· en· W2891744727 on OpenAlexaff
Mala Kaul, Veda C. Storey, Carson Woo

Bibliographic record

VenueJournal of the Association for Information Systems · 2018
Typearticle
Languageen
FieldComputer Science
TopicBlockchain Technology Applications and Security
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBlockchainComputer scienceComputer security
DOInot available

Abstract

fetched live from OpenAlex

Blockchain has received a great deal of attention due to its inherent and perceived security, as well as its ability to bypass traditional intermediaries and associated transaction costs. Blockchain is a decentralized, distributed network of peer to peer, encrypted public and private ledgers, composed of data records in “blocks,” linked into an immutable chain that is automatically verified and managed. With an initial objective of examining a blockchain use case, we considered the latent value of implementing blockchain within a regional health information exchange. Intrigued by our observations of the lukewarm interest in blockchain for managing the exchange of sensitive information, a difficult problem with high practical significance, we were motivated to examine the feasibility of blockchain applications. From an organizational perspective, there are many unresolved issues related to blockchain because we do not yet understand the impact of the unique features of this technology. Therefore, the objective of this research is: to identify the factors that should be considered when assessing the feasibility of blockchain application. \\ \\ To carry out the research, we examined prior literature and found an extensive number of design documents, opinion pieces (blogs, wikis, and posts), papers, technical reports, conference proceedings, and journal articles. Since the research objective was to examine feasibility, we focused mainly on conference and journal articles. We excluded papers dealing with cryptocurrencies or bit coins, technical papers describing algorithms, or technical developments. We selected all conference proceedings from the AISlibrary with the term “block chain” or “blockchain” within the text. For journal articles, we selected papers using the terms “block chain” or “blockchain” in the Title and Key Terms and the discipline “business” employing a unified search function through an institutional library. In total, 282 papers were retrieved that were related to blockchain. Our review of the literature on systems analysis and design or feasibility studies is not included in this count. \\ \\ From the above literature review, we found that blockchain inherits traditional feasibility concerns: technical, economic, operational/organizational, schedule, legal, governance, and political. However, several attributes are more salient to blockchain: 1) trust, 2) security and privacy, and 3) complexity. Information systems has already dealt with both: the emergence, adoption, and absorption of new technology; and the development of information systems. By examining the characteristics of blockchain from the perspective of the development and adoption of a new technology, we propose that the feasibility aspect of systems analysis should be modified. This leads to a feasibility framework for blockchain applications, that emphasizes trust, security, privacy, and complexity within existing feasibility concerns. \\ \\ Future research will focus on first interviewing senior executives, who are considering adopting and implementing blockchain, to understand how their decision-making process will proceed and, therefore, what additional attributes of feasibility need to be considered. Second, a case study will be used to examine the feasibility of a blockchain application. These will be useful for practitioners and academics in assessing the feasibility of blockchain technology prior to its implementation. \\

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.018
metaresearch head score (Gemma)0.114
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.114
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0060.009
Open science0.0020.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0160.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.260
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2018
Admission routes1
Has abstractyes

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