Enhancing the democratic nature of voting processes within decentralized autonomous organizations

Paper entitled “Enhancing the democratic nature of voting processes within decentralized autonomous organizations” in Digital Policy, Regulation and Governance.

Purpose

This paper aims to explore the problem of power imbalance within decentralized autonomous organizations (DAOs) and propose potential solutions that could contribute to enhancing the democratic nature of DAOs.

Design/methodology/approach

In this paper, the authors apply a qualitative methodology. Using a thematic coding analysis, the authors process data collected from interviews with 11 experts.

Findings

Multiple factors contribute to the perceived lack of democracy within DAOs, such as token concentration and effective stakeholder communication. Next, quadratic voting has the potential to enhance democracy within DAOs, but this mechanism must be implemented mindfully. Finally, the results were nuanced when it comes to the effectiveness of liquid democracy in DAOs to enhance voter participation and representation.

Originality/value

To the best of the authors’ knowledge, this paper is one of the first research contributions to propose recommendations to address the power imbalance within DAOs and to contribute to the advancement of decentralized decision-making structures.

We Are Launching our Own NFT! Characterizing Fashion NFT Transactions-Preliminary Results

Paper presented @BRAINS2023, conference held in Paris (October 2023).

Abstract. Blockchain technology and Non Fungible Tokens (NFTs) have been a hot topic for several years now, as proven by the multitude of brands launching their own NFT projects. In this paper, we will consider some popular fashion NFT collections, namely: adidas Originals Into the Metaverse, AMBUSH OFFICIAL POW! REBOOT, Azuki x AMBUSH IKZ, CULT & RAIN – The Genesis Collection, Dolce& Gabbana: DGFamily, Dolce& Gabbana: DGFamily Glass Box, Chito x Givenchy NFT, MUGLER – We Are All Angel, RTFKT x Nike Dunk Genesis CRYPTOKICK, Prada Timecapsule. First, we will analyze and examine if we can find salient characteristics of transactions pertaining to these collections. Second, we will attempt to propose a first taxonomy of fashion NFT transactions. From the results, we can state that most transactions occur at the NFT launch and that they belong to the Memberships category. Secondly, the results show that we can propose a taxonomy of four transaction groups or clusters. The findings can have practical implications for both researchers and practitioners, indeed the results: (i) can be a stepping stone for future research on (fashion) NFTs, (ii) can help practitioners analyze transactions using our preliminary taxonomy.

Assessing the impact of network factors and Twitter data on Ethereum’s popularity

I recently published a paper entitled “Assessing the impact of network factors and Twitter data on Ethereum’s popularity” in Blockchain: Research and Applications.

Abstract. In March 2021, we witnessed a surge in Bitcoin price. The cause seemed to be a tweet by Elon Musk. Are other blockchains as sensitive to social media as Bitcoin? And more precisely, could Ethereum’s popularity be explained using social media data?

This work aims to explore the determinants of Ethereum’s popularity. We use both data from Etherscan to retrieve the relevant historic Ethereum factors and Twitter data. Our sample consists of data ranging from 2015 to 2022. We use Ordinary Least Squares to assess the relationship between these factors (Ethereum characteristics and Twitter data) and Ethereum’s popularity.

Our findings show that Ethereum’s popularity—translated here by the number of daily new addresses—is related to the following elements: the Ether (ETH) price, the transaction fees, and the polarity of tweets related to Ethereum.

The results could have multiple practical implications for both researchers and practitioners. First of all, we believe that it will enable readers to better understand the technology of Ethereum and its stake. Secondly, it will help the community identify pointers for anticipating or explaining the popularity of existing or future platforms. And finally, the results could help in understanding the factors facilitating the design of future platforms.

bouraga-ethereum-popularityDownload

Feel free to share any comment or question you might have regarding the document itself or the topic in general.

Cheers!

Sarah

When Dashboard’s Content Becomes a Barrier-Exploring the Effects of Cognitive Overloads on BI Adoption

Two colleagues and I recently published and presented a paper entitled “When Dashboard’s Content Becomes a Barrier-Exploring the Effects of Cognitive Overloads on BI Adoption” in International Conference on Research Challenges in Information Science.

Abstract. Decision makers in organizations strive to improve the quality of their decisions. One way to improve that process is to objectify the decisions with facts. Big data, business analytics, business intelligence, and more generally data-driven Decision Support Systems (data-driven DSS) intend to achieve this. Organizations invest massively in the development of data-driven DSS and expect them to be adopted and to effectively support decision makers. This raises many technical and methodological challenges, especially regarding the design of dashboards, which can be seen as the visible tip of the data-driven DSS iceberg and which play a major role in the adoption of the entire system. This paper advances early empirical research conducted on one possible root cause for data-driven DSS dashboard adoption or rejection, namely the dashboard content. We study the effect of dashboards over- and underloading on traditional Technology Adoption Models, and try to uncover the trade-offs to which data-driven DSS interface designers are confronted when creating new dashboards. The result is a Dashboard Adoption Model, enriching the seminal TAM model with new content-oriented variables to support the design of more supportive data-driven DSS dashboards.

Feel free to share any comment or question you might have regarding the paper or the topic.

A taxonomy of blockchain consensus protocols: A survey and classification framework

I recently published a paper entitled “A taxonomy of blockchain consensus protocols: A survey and classification framework” in Expert Systems with Applications.

Abstract. Blockchain, the underlying technology of Bitcoin, refers to the public ledger used in a distributed network. Because blockchain does not rely on a central authority, peers have to agree on the state of the ledger among themselves, i.e., they have to reach a consensus on the state of the transactions. The way nodes reach that consensus has gained incredible attention in the literature. Bitcoin uses the Proof-of-Work (PoW) mechanism, as did Ethereum at first. The latter decided to move from PoW to Proof-of-Stake (PoS) because of the high energy consumption required by PoW. To date, many other consensus protocols have been proposed to address the limitations of the seminal ones.

In this paper, we inform researchers and practitioners about the current state of consensus protocols research. The aim is to provide an analysis of the research introducing new consensus protocols in order to enable a more unified treatment. To that end, we review 28 new consensus protocols and we propose a four-category classification framework: Origin, Design, Performance and Security. We demonstrate the applicability of the framework by classifying the 28 protocols. Many surveys have already been proposed in the literature and some of them will be discussed later in the paper. Yet, we believe that this work is relevant and important for two reasons. Firstly, blockchain being a fast evolving topic, new consensus protocols emerge regularly and improvements are also put forward on a regular basis. Hence, this work aims at reflecting the latest state-of-the-art in terms of consensus protocols. Secondly, we aim to propose a comprehensive classification framework, integrating knowledge from multiple works in the literature, as well as introducing classification dimensions that have not been proposed before.

This work demonstrates that multiple consensus have been proposed in a short period of time, and highlights the differences between these protocols. Furthermore, it is suggested that researchers and practitioners who aim to propose consensus protocols in the future should pay attention to all the dimensions presented in the classification framework.

Feel free to share any comment or question you might have regarding the document itself or the topic in general.

bouraga-2020-taxonomyDownload

BRAINS 2020

The 2nd Conference on Blockchain Research & Applications for Innovative Networks and Services took place in September 2020 (BRAINS2020) was supposed to be held in Paris, but unfortunately due to the COVID-2019 pandemic, the conference had to be held virtually.

In my very first poster session, I’ve presented the poster you can see above which focuses on the prediction of gas for transactions on Ethereum. Obviously, the conditions were not ideal for exchanges with the other attendees, but the organizers did a great job in enabling interactions despite the virtual setting.

Abstract. The author uses data about transactions onEthereum as sources for studying the relationship between thehistoric of transactions for a given address and the amountof gas consumed for a transaction. The author combines dataabout transactions, and blocks to predict the gas usage for atransaction. Specifically, how much gas will be consumed for the next transaction, given the initiator’s transaction history. The results demonstrate the value of considering the transactionhistory for gas usage predictions.

Feel free to leave any comment or question you might have regarding this poster in itself or the topic of the poster.