Magda Pineda, Daladier Jabba, Wilson Nieto, Alfredo J. Pérez
In recent years, consensus algorithms have gained significant importance in the context of blockchain networks. These algorithms play a crucial role in allowing network participants to reach agreements on the state of the Blockchain without needing a central authority. The present study focuses on carrying out a systematic mapping of these consensus algorithms to explore in detail their use, benefits, and challenges in the context of blockchain networks. Understanding consensus algorithms is essential to appreciating how blockchain networks achieve the reliability and integrity of their distributed ledgers. These algorithms allow network nodes to reach agreement on the validity of transactions and the creation of new blocks on the Blockchain. In this sense, consensus algorithms are the engine that drives trust in these decentralized networks. Numerous authors have contributed to the development and understanding of consensus algorithms in the context of blockchain networks. For example, Satoshi Nakamoto's (2008) original paper on Bitcoin introduced proof-of-work (PoW) as a method of achieving consensus on the network. This revolutionary concept paved the way for numerous cryptocurrencies and blockchain systems. Despite advances in this field, significant challenges remain: centralization, fair token distribution, scalability, and sustainability. The energy consumption of blockchain networks, particularly those using algorithms such as Proof of Work, Proof of Stake, Delegated Proof of Stake, Proof of Authority, and hybrid algorithms (Proof of Work/Proof of Stake), has raised concerns about their environmental impact, motivating the scientific and technological community to investigate more sustainable alternatives that promise to reduce energy consumption and contribute to climate change mitigation. Furthermore, interoperability between different blockchains and security in specific environments, such as IoT, are areas that still require significant research attention. This systematic mapping not only seeks to shed light on the current state of consensus algorithms in blockchain, but also their impact on sustainability, identifying those algorithms that, in addition to guaranteeing integrity and security, minimize the environmental footprint, promoting a more efficient use of energy resources, being a relevant approach in a context in which the adoption of sustainable technologies has become a global priority. Understanding and improving these algorithms are critical to unlocking the full potential of blockchain technology in a variety of applications and industry sectors.
Blockchain technology holds the potential to revolutionise the logistics industry by sharing tamper-proof information in a decentralised manner, building trust among parties. However, adoption in the Australian logistics industry lags behind other sectors. This study uses fuzzy DEMATEL to investigate barriers to blockchain adoption, identifying thirteen key barriers within the technology-organisation-environment (TOE) framework. Cost of investment and integration difficulties among partners are the most prominent barriers, particularly within organisational contexts. The findings offer a theoretical foundation and practical insights for overcoming barriers and successfully implementing blockchain in logistics.
Paulo César Galarza-Sánchez, Gerardo Alfredo Solano Gutiérrez
La globalización y la complejidad de las cadenas de suministro han destacado la necesidad de soluciones tecnológicas que mejoren la trazabilidad, transparencia y eficiencia. Este estudio tiene como objetivo comparar las principales plataformas blockchain aplicadas en la gestión de cadenas de suministro, explorando sus características, ventajas, limitaciones y casos de uso. A través de una metodología de análisis bibliográfico, se revisaron fuentes académicas de bases de datos reconocidas, utilizando palabras clave relevantes y criterios estrictos de inclusión y exclusión. Los resultados muestran que plataformas privadas, como Hyperledger Fabric, ofrecen mayor escalabilidad y control de acceso, mientras que plataformas públicas, como Ethereum, priorizan la transparencia, aunque presentan limitaciones en términos de velocidad y costos. Además, la integración de blockchain mejora la trazabilidad y transparencia en las cadenas, permitiendo un seguimiento en tiempo real y fomentando la confianza entre los actores. Sin embargo, factores como la falta de interoperabilidad, los altos costos iniciales y la resistencia al cambio organizacional limitan su adopción. En conclusión, blockchain puede transformar las cadenas de suministro, pero su implementación requiere superar barreras tecnológicas y culturales mediante estrategias colaborativas, estándares comunes y formación.
Kongmanas Yavaprabhas, Mehrdokht Pournader, Stefan Seuring
Existing studies into the roles of trust in blockchain applications within supply chains are fragmented. This paper seeks to address this issue by consolidating current knowledge and identifying various trustors and trust targets in blockchain applications in the supply chain literature. We conduct a bibliometric analysis of 192 relevant journal articles published between 2018 and 2022. We then identify 11 distinct clusters and analyse the trustors and trust targets within these clusters and leverage trust transfer theory to explain how a trustor's trust in one target can be transferred to another associated target in each cluster. We conclude by proposing two prospective research avenues focusing on trust transfer perspectives in blockchain applications in supply chain literature. The first avenue discusses the nuances in the trust transfer processes between voluntary and mandatory contexts of blockchain use. The second avenue highlights the underexplored trust transfer processes of various initial trust targets that can influence blockchain adoption.
Blockchain technology has received increasing attention from academia, practitioners, and policymakers alike for its potential to disrupt business processes and structures of trade in global value chains (GVC). Amidst the ongoing digitization of economies and societies, blockchain holds promise for addressing unresolved challenges. However, current research on this topic primarily consists of either abstract conceptual work or case studies. To bridge this gap, our study conducts a systematic literature review, aiming to comprehensively explore and structure the realm of blockchain and its impact on international trade. Key research questions explored include: What role do blockchain innovations play in facilitating trade within GVC? Additionally, what are the primary barriers hindering the adoption of blockchain innovations in trade within GVC? Our main contribution lies in categorizing these applications into five distinct categories: Trade Documents; Trade Finance; Trusted Real-Time Information Sharing; Provenance; and Sustainable GVC. Contrary to portraying blockchain innovations as a panacea or universal solution, our findings highlight the technologies’ potential rather as a core technological infrastructure when integrated with complementary technologies such as the Internet of Things. Moreover, we identify 11 significant barriers to blockchain adoption in international trade, underscoring the need for concerted efforts to address them. From these insights, we derive implications for policymakers and practitioners, and propose avenues for future interdisciplinary research.
Blockchain technology has promising benefits and provides robust solutions for managing business processes. While prior studies have primarily explored its potential in supporting logistics and supply chain management, many practitioners still lack a clear understanding of how to leverage blockchain technology, hindering its adoption within the industry. Bridging this gap and addressing critical barriers requires further empirical research. This study adopts a comprehensive approach, identifying potential barriers through a literature review and validating their significance through the Index of Item-Objective Congruence (IOC). The study then delves into the interrelationships among the significant barriers, utilising Interpretive Structural Modelling (ISM) and MICMAC methods. The results highlight seven significant barriers within the logistics sector, encompassing a lack of government support, operational standards, top management support, limited public awareness, trust issues, technical challenges, and network collaboration difficulties. Notably, the lack of public awareness and inadequate governmental support form fundamental obstacles that drive various challenges. This research offers insights into the barriers that hinder the successful adoption of blockchain technology in logistics, proposing several mitigation strategies that are in line with the principles of open innovation.
Abstract In the era of emerging technologies, many firms explore the role of blockchain technology and its impact on corporate market value. Past research has shown that companies benefit from executing blockchain projects, but little is known about specific value and risk drivers. Hence, we provide evidence for several conditions under which blockchain provides additional firm market value. Moreover, we test whether blockchain announcements lead to changes in the systematic risk of firms. Theoretically founded on the resource-based view, we utilize the event study methodology, supplemented by a multivariate regression and a firm’s beta analysis. We find that stock markets react positively to corporate blockchain news if the announcement is related to a blockchain consortium or partnership, is declared by a tech company, or if the announcement is a follow-up announcement to initial blockchain news. Moreover, our findings show that blockchain announcements do not lead to significant changes in a firm’s systematic risk.
Maher Alharby, Ali Alssaiari, Saad Alateef, Nigel Thomas · 5 authors
Abstract This study analyzes the security implications of Proof-of-Work blockchains with respect to the stale block rate and the lack of a block verification process. The stale block rate is a crucial security metric that quantifies the proportion of rejected blocks in the blockchain network. The absence of a block verification process represents another critical security concern, as it permits the potential for invalid transactions within the network. In this article, we propose and implement a quantitative and analytical model to capture the primary operations of Proof-of-Work blockchains utilizing the Performance Evaluation Process Algebra. The proposed model can assist blockchain designers, architects, and analysts in achieving the ideal security level for blockchain systems by determining the proper network and consensus settings. We conduct extensive experiments to determine the sensitivity of security to four aspects: the number of active miners and their mining hash rates, the duration between blocks, the latency in block propagation, and the time required for block verification, all of which have been shown to influence the outcomes. We contribute to the findings of the existing research by conducting the first analysis of how the number of miners affects the frequency of stale block results, as well as how the delay in block propagation influences the incentives received by rational miners who choose to avoid the block verification process.
Globalization has transformed the pharmaceutical industry into a vast, interconnected network. However, this complexity has led to inefficiencies in the supply chain, with existing ERP systems struggling to keep up due to their centralized nature, resulting in a lack of transparency and increased errors. This research proposes efficient distributed ledger-based architectures to address these challenges. In Chapter 3, a new transparent supply chain architecture is introduced to eliminate blind spots and enable stakeholders to verify the authenticity of pharmaceutical products. This system creates a secure, single source of truth for the entire lifecycle of medicines, thereby eliminating counterfeits. Chapter 4 focuses on securing the cold pharmaceutical supply chain using IoT and distributed ledgers. The proposed architecture monitors and controls environmental parameters, ensuring safe drug transport. Scalability is addressed with a novel proof of authentication (PoAh) blockchain called EasyChain. In Chapter 5, the serialization of pharmaceutical products is enhanced through digital twinning, providing an efficient and cost-effective solution while complying with regulations. This research aims to create scalable and efficient pharmaceutical supply chains, reducing counterfeits and improving overall security.
Blockchain technology enables innovative financing models in supply-chain finance. This research constructs a tripartite evolutionary game model that includes core enterprises as employers, small- and medium-sized enterprises (SMEs) as contractors, and banks as financial institutions, where they have been simulated for their impact on blockchain technology, especially on the strategic choices of supply-chain financing behavior and the system’s evolutionary path under core enterprises’ guarantee mechanism. The findings show the application of blockchain technology can effectively reduce the regulatory and review costs for financial institutions, thereby enhancing the efficiency of supply-chain financing. Particularly, blockchain technology provides a more reliable credit endorsement platform for SMEs in reducing their tendency to default. The guarantee mechanism of core enterprises is more effective with the support of blockchain technology, which helps to build more solid supply-chain financial cooperation relationships. The research contributes to the theoretical research on the integration of blockchain technology into supply-chain finance, especially for improving the operational efficiency of financial services. It also highlights the need for blockchain-backed guarantees from core enterprises in optimizing supply-chain financial services.
With the widespread adoption of blockchain technology, a novel organizational structure known as Decentralized Autonomous Organizations (DAOs) has attracted considerable attention. DAOs facilitate decision-making through member voting, realizing the governance in a decentralized manner. However, DAOs face unique challenges compared to traditional organization. This paper focuses on two key challenges of governance within DAOs: the whale problem and collusion issue. The whale problem is characterized by the concentration of power among specific members, while for the collusion problem, voting results are distorted by fraudulent collaboration. In terms of voting, we consider Quadratic Voting, a voting system expected to deter the concentration of voting power among a subset of participants, analyzing its resistance to the collusion problem. We show with numerical examples that in comparison to Linear Voting, Quadratic Voting lacks resistance to collusion. Then, we propose a voting mechanism that integrates Quadratic Voting with the Vote escrow tokens, demonstrating the mitigation of the whale problem while acquiring resilience to collusion in the decision-making process. The numerical examples confirm the high efficacy of our proposed model.
Risk and uncertainty are crucial factors in decision-making processes, especially when integrating emerging technologies into essential systems like supply chains. Failing to adequately consider significant risks can disrupt supply chain operations, leading to a loss of competitive edge and causing financial and reputational damage. On the other hand, the complex nature of new technology environments, differing viewpoints among stakeholders, and the challenges of interpreting data introduce a variety of uncertainties in decision-making. In this study, we conduct a thorough examination of how blockchain strategies can be applied within supply chain frameworks. Our analysis utilizes data-driven network decision-making models that are refined to effectively manage uncertainty and risk. These models take into account aspects such as supply chain dynamics and technological factors. Importantly, we meld risk considerations with our models to tackle efficiency shortfalls, while also accounting for uncertainty caused by ambiguous and stochastic data environments. By applying and assessing these models in a real-world case study of the oil and gas industry, our research uncovers insightful observations. Specifically, we find that adopting a localization strategy presents specific risks, while a single-use strategy yields significant efficiency improvements.
This paper investigates the potential of integrating supply chain management with blockchain technology, specifically by implementing smart contracts on the Ethereum network using Solidity. The paper explores supply chain management concepts, blockchain, distributed ledger technology, and smart contracts in the context of their integration into supply chains to increase traceability, transparency, and accountability with faster processing times. After investigating these technologies’ applications and potential use cases, a framework for smart contract implementation for supply chain management is constructed. Potential data models and functions of a smart contract implementation improving supply chain management processes are discussed. After constructing a framework, the effects of the proposed system on supply chain processes are explained. The proposed framework increases the reliability of the supply chain history due to the usage of DLT (distributed ledger technology). It utilizes smart contracts to increase the manageability and traceability of the supply chain. The proposed framework also eliminates the SPoF (Single Point of Failure) vulnerabilities and external alteration of the transactional data. However, due to the ever-changing and variable nature of the supply chains, the proposed architecture might not be a one-size-fits-all solution, and tailor-made solutions might be necessary for different supply chain management implementations.
The BlockSupply project is a pioneering initiative that seeks to redefine supply chain management by leveraging blockchain technology to ensure real-time monitoring of product movements and enhance transparency, security, and traceability. The software offers key functionalities such as creating a private blockchain network, integrating tracking sensors for real-time data collection, secure recording of product data, user authentication, authorization management, and alerts for abnormal events. It is developed using technologies like Web3.js, React.js, Solidity, Ganache, and GitHub, which are integrated into the project’s architecture to create an efficient and secure blockchain-based supply chain solution. Furthermore, the project’s impact is expected to be significant, contributing to scientific advancements in secure and efficient supply chain operations and reshaping the landscape of logistics traceability. As the software gains traction in real-world scenarios, its transformative influence on data reliability, security, and operational efficiency in supply chain research is poised to be showcased in publications. • Blockchain boosts real-time supply monitoring and security. • Utilizes Web3.js, React.js, and Solidity for robust system. • Mitigates fraud and errors in supply chain management. • Streamlines inventory via advanced tracking and sensors. • Open-source, enhances operational efficiency significantly.
Abstract This paper investigates blockchain technology (BT) adoption strategy in a platform dual‐channel supply chain, wherein the supplier establishes a direct selling channel (DC) in addition to the existing reselling channel (RC) of the e‐retailer. Both the supplier and the e‐retailer are risk‐averse, and they have access to consumers through a common online platform. The online platform possesses the capability to introduce BT and can opt to introduce it to neither, one (DC or RC) or both channels. Game models for the four strategies are developed, and the corresponding equilibrium outcomes are obtained using backward induction. Our analysis reveals that when competition intensity is high and both perceived risk aversion level and BT's unit cost are low, the online platform prefers only DC with adopting BT. Otherwise, it prefers both channels with adopting BT. The supplier shares the same preference as the online platform for BT adoption strategy. Interestingly, the e‐retailer prefers only DC with adopting BT only when BT's unit cost is high; otherwise, she prefers solely RC with adopting BT. Furthermore, we enhance the basic model by modifying parameter configurations and the sequence game, and verify that our main findings in these extensions remain robust.
Cristian Valencia-Payan, David Griol, Juan Carlos Corrales
Abstract A sustainable supply chain management strategy reduces risks and meets environmental, economic and social objectives by integrating environmental and financial practices. In an ever-changing environment, supply chains have become vulnerable at many levels. In a global supply chain, carefully tracing a product is of great importance to avoid future problems. This paper describes a self-updating smart contract, which includes data validation, for tracing global supply chains using blockchains. Our proposal uses a machine learning model to detect anomalies on traceable data, which helps supply chain operators detect anomalous behavior at any point in the chain in real time. Hyperledger Caliper has been used to evaluate our proposal, and obtained a combined average throughput of 184 transactions per second and an average latency of 0.41 seconds, ensuring that our proposal does not negatively impact supply chain processes while improving supply chain management through data anomaly detection.
Modern supply chain systems face significant challenges, including lack of transparency, inefficient inventory management, and vulnerability to disruptions and security threats. Traditional optimization methods often struggle to adapt to the complex and dynamic nature of these systems. This paper presents a novel blockchain-based zero-trust supply chain security framework integrated with deep reinforcement learning (SAC-rainbow) to address these challenges. The SAC-rainbow framework leverages the Soft Actor–Critic (SAC) algorithm with prioritized experience replay for inventory optimization and a blockchain-based zero-trust mechanism for secure supply chain management. The SAC-rainbow algorithm learns adaptive policies under demand uncertainty, while the blockchain architecture ensures secure, transparent, and traceable record-keeping and automated execution of supply chain transactions. An experiment using real-world supply chain data demonstrated the superior performance of the proposed framework in terms of reward maximization, inventory stability, and security metrics. The SAC-rainbow framework offers a promising solution for addressing the challenges of modern supply chains by leveraging blockchain, deep reinforcement learning, and zero-trust security principles. This research paves the way for developing secure, transparent, and efficient supply chain management systems in the face of growing complexity and security risks.
Purpose This study analyzes the performance implications of adopting blockchain to support supply chain business processes. The technology holds as many promises as implementation challenges, so interest in its impact on operational performance has grown steadily over the last few years. Design/methodology/approach Drawing on transaction cost economics and the contingency theory, we built a set of hypotheses. These were tested through a long-term event study and an ordinary least squares regression involving 130 adopters listed in North America. Findings Compared with the control sample, adopters displayed significant abnormal performance in terms of labor productivity, operating cycle and profitability, whereas sales appeared unaffected. Firms in regulated settings and closer to the end customer showed more positive effects. Neither industry-level competition nor the early involvement of a project partner emerged as relevant contextual factors. Originality/value This research presents the first extensive analysis of operational performance based on objective measures. In contrast to previous studies and theoretical predictions, the results indicate that blockchain adoption is not associated with sales improvement. This can be explained considering that secure data storage and sharing do not guarantee the factual credibility of recorded data, which needs to be proved to customers in alternative ways. Conversely, improvements in other operational performance dimensions confirm that blockchain can support inter-organizational transactions more efficiently. The results are relevant in times when, following hype, there are signs of disengagement with the technology.
This research aims to develop and optimize an intelligent supply chain framework tailored for the insurance industry by integrating an innovative inventory management policy supported by the Internet of Things (IoT) and blockchain technologies. Through an extensive literature review, key assumptions are established, needs are identified, and objectives are formulated. A multi-objective mathematical planning model is proposed to minimize cost and time within the supply chain, with optimization conducted under deterministic and fuzzy conditions. The model utilizes augmented epsilon constraint and weighted sum methods to address its multi-objectiveness. Noteworthy is the integration of advanced technologies such as Wireless Sensor Networks (WSN), Radio-Frequency Identification (RFID), blockchain, and online sales, distinguishing it from traditional approaches. Initial validation and testing in smaller dimensions demonstrate the model’s adaptability to precise methods, while larger dimensions necessitate the use of meta-heuristic algorithms for efficient problem resolution. Additionally, a comprehensive sensitivity analysis in the insurance industry on objective function coefficients reveals intricate relationships, offering valuable insights into optimization dynamics across diverse conditions.
Ardavan Babaei, Erfan Babaee Tırkolaee, Sadia Samar Ali
Abstract Blockchain Technology (BT) has the potential to revolutionize supply chain management by providing transparency, but it also poses significant environmental and security challenges. BT consumes energy and emits carbon gases, affecting its adoption in Supply Chains (SCs). The substantial energy demand of blockchain networks contributes to carbon emissions and sustainability risks. Moreover, for secure and reliable transactions, mutual authentication needs to be established to address security concerns raised by SC managers. This paper proposes a tri-objective optimization model for the simultaneous design of the SC-BT network, considering a two-step authentication process. The model considers transparency caused by BT members, emissions of BT, and costs related to BT and SC design. It also takes into account uncertainty conditions for participating BT members in the SC and the range of transparency, cost, and emission targets. To solve the model, a Branch and Efficiency (B&E) algorithm equipped with BT-related criteria is developed. The algorithm is implemented in a three-level SC and produces cost-effective and environmentally friendly outcomes. However, the adoption of BT in the SC can be costly and harmful to the environment under uncertain conditions. It is worth mentioning that implementing the proposed algorithm from our article in a three-level SC case study can result in a significant cost reduction of over 16% and an emission reduction of over 13%. The iterative nature of this algorithm plays a vital role in achieving these positive outcomes.
Vinay, Sagar Yadav, Attul Kumar, Prof. Renu Narwal
In the evolving landscape of supply chain management, the integration of blockchain technology and artificial intelligence (AI) stands as a beacon of innovation, promising to address the perennial challenges of efficiency, transparency, and reliability. This paper presents a comprehensive exploration of how AI can revolutionize blockchain supply chains, offering a synthesis of current research, methodologies, and case studies that highlight the transformative potential of this synergy. The supply chain, a complex network that underpins global trade, is often beleaguered by inefficiencies and vulnerabilities. Blockchain technology, with its decentralized and immutable ledger, has emerged as a solution to enhance traceability and trust. However, it is the infusion of AI that has the potential to catalyze a paradigm shift in supply chain management. AI’s capabilities in data analytics, machine learning, and autonomous decision-making can optimize logistics, predict trends, and automate tasks, thereby elevating the blockchain beyond its current utility. This research adopts a mixed-methods approach, drawing on qualitative insights from industry experts and quantitative data from performance metrics to assess the impact of AI on blockchain supply chains. Through a series of case studies, the paper illustrates the practical applications and challenges of this integration, providing a nuanced understanding of its implications. The findings reveal that AI significantly enhances the efficiency and accuracy of blockchain supply chains, leading to improvements in transaction times, data verification processes, and overall supply chain performance. The discussion delves into the strategic advantages of this integration, such as improved compliance and ethical supply chain practices, while also acknowledging the limitations and challenges that organizations must navigate. In conclusion, the paper posits that the convergence of AI and blockchain holds great promise for the future of supply chains. It offers a roadmap for practitioners looking to harness these technologies and sets forth directions for future research, particularly in the development of sophisticated AI algorithms tailored for blockchain applications and the long-term economic impacts on supply chain management. The study contributes to the broader field by providing empirical evidence and a new perspective on the potential of AI to create more resilient, efficient, and transparent supply networks..
In recent years, blockchain technology has attracted substantial interest for its capability to transform supply chain management and finance. This paper employs evolutionary game theory to investigate the application of blockchain in mitigating financial risks within supply chains, taking into account the technology’s maturity and the risk preferences of financial institutions. By modeling interactions among financial institutions, small and medium enterprises (SMEs), and core enterprises within the accounts receivable financing framework, this study evaluates blockchain’s impact on their decision-making and its efficacy in risk reduction. Our findings suggest the transformative potential of blockchain in mitigating financial risks, solving information asymmetry, and enhancing collaboration between financial entities and SMEs. Additionally, we integrate smart contracts into supply chain finance, proposing pragmatic procedures for their deployment in real-world contexts. Via a detailed examination of blockchain’s maturity and financial institutions’ risk preferences, this research demonstrates the primary determinants of strategic decisions in supply chain finance and underscores how blockchain technology fosters system stability using risk mitigation. Our innovative contribution lies in the design of smart contracts for the ARF process, rooted in blockchain’s core attributes of security, transparency, and immutability, thereby ensuring efficient operation and cost reduction in supply chain finance.
Proof-of-stake (PoS) has emerged as a natural alternative to the resource-intensive Proof-of-Work (PoW) blockchain, as was recently seen with the Ethereum Merge. PoS-based blockchains require an initial stake distribution among the participants. Typically, this initial stake distribution is called bootstrapping. This paper argues that existing bootstrapping protocols are prone to centralization. To address centralization due to bootstrapping, we propose a novel game $Γ_\textsf{bootstrap}$. Next, we define three conditions: (i) Individual Rationality (IR), (ii) Incentive Compatibility (IC), and (iii) $(τ,δ,ε)-$ Decentralization that an \emph{ideal} bootstrapping protocol must satisfy. $(τ,δ,ε)$ are certain parameters to quantify decentralization. Towards this, we propose a novel centralization metric, C-NORM, to measure centralization in a PoS System. We define a centralization game -- $Γ_\textsf{cent}$, to analyze the efficacy of centralization metrics. We show that C-NORM effectively captures centralization in the presence of strategic players capable of launching Sybil attacks. With C-NORM, we analyze popular bootstrapping protocols such as Airdrop and Proof-of-Burn (PoB) and prove that they do not satisfy IC and IR, respectively. Motivated by the Ethereum Merge, we study W2SB (a PoW-based bootstrapping protocol) and prove it is ideal. In addition, we conduct synthetic simulations to empirically validate that W2SB bootstrapped PoS is decentralized.