Blockchain Papers

Shuhua Chang, Haiteng Ma, Pengwen Hou, Li Cao

No abstract is available for this record.

sanshao peng, Catherine Prentice, Syed Shams, Tapan Sarker

Purpose Given the cryptocurrency market boom in recent years, this study aims to identify the factors influencing cryptocurrency pricing and the major gaps for future research. Design/methodology/approach A systematic literature review was undertaken. Three databases, Scopus, Web of Science and EBSCOhost, were used for this review. The final analysis comprised 88 articles that met the eligibility criteria. Findings The influential factors were identified and categorized as supply and demand, technology, economics, market volatility, investors’ attributes and social media. This review provides a comprehensive and consolidated view of cryptocurrency pricing and maps the significant influential factors. Originality/value This paper is the first to systematically and comprehensively review the relevant literature on cryptocurrency to identify the factors of pricing fluctuation. This research contributes to cryptocurrency research as well as to consumer behaviors and marketing discipline in broad.

Paul McGivern

Purpose This review aims to provide an overview of research from different academic disciplines to chart some of the key developments in retail cryptocurrency trading against the backdrop of the wider trading landscape, and how it has evolved in recent years. The purpose of this review is to provide researchers with a broad perspective to highlight the complex range of factors that drive cryptocurrency trading among retail investors. Design/methodology/approach Peer-reviewed literature from the social sciences, economics, marketing and branding disciplines is synthesised to explicate influential factors among retail cryptocurrency investors. Findings Online retail trading communities can create narratives that ascribe value to cryptocurrencies leading to consumer herding behaviours. The principles that underpin emotional branding and Fear of Missing Out can promote trading behaviour driven by heuristic processing and cognitive biases. Concurrently, the tenets of controversial marketing and the anti-establishment nature of Bitcoin and other cryptocurrencies serve to bolster in-group out-group categorisations fostering continued investment and market volatility. Consequently, Bitcoin and cryptocurrency trading more broadly offer a powerful combination of excitement from risk-taking akin to gambling buffered by the sanctity of social inclusion. Originality/value A broader, unique perspective on retail cryptocurrency trading which assists in better understanding the complexities that underpin its appeal to retail investors.

Longmei Tian, Benyong Hu

No abstract is available for this record.

Jianghua Wu, Chenchen Zhao

It is often difficult for consumers to predict the greenness of a new green product, reducing their willingness to purchase the product. Numerous companies have recently started adopting blockchain to demonstrate their products' quality. In this study, a market is considered where consumers decide what to buy when they know the greenness of existing products but are unsure about the greenness of new green products. This research presents a game theory model to examine the incumbent's entry-deterrence strategy and the entrant's blockchain adoption strategy. We examine the conditions under which blockchain can help an entrant's market entry, and the impact of blockchain adoption on firms' pricing strategies and profits, consumer surplus, and social welfare. The findings denote that blockchain adoption makes the incumbent more inclined to tolerate the entrant when the blockchain adoption cost is negligible. In addition, blockchain adoption can result in a “win-win” outcome for the two firms when the cost of the green products is low and the proportion of high-type consumers is high. However, blockchain adoption may not always benefit the entrant even if the blockchain adoption cost is negligible, particularly when consumers' perceived greenness of green products is significant enough. Furthermore, blockchain adoption may not be beneficial for consumer surplus and social welfare when green products' cost is moderate. Finally, blockchain adoption may drive the entrant to improve or reduce product greenness, depending on the proportion of high-type consumers and their uncertainty about the greenness.

Baozhuang Niu, Yiyuan Ruan, Haotao Xu

No abstract is available for this record.

Anthony A. Tarr, Julie‐Anne Tarr, Antton Peña

On-demand insurance is growing rapidly with predictions that by 2030 the global insurance market will evolve to contain highly dynamic, usage-based products that are tailored to individual customer behaviours and will transition from an annual renewal model to a continuous cycle, with products that constantly adapt to individual behavioural patterns—driven by application of data and individualised risk models. The availability of “big data” in conjunction with technological advances in artificial intelligence (AI), predictive analytics and blockchain create the foundation and operational capacity for new on-demand insurance products and opens doors to new and exciting opportunities within the insurance industry. Globally, insurtech start-ups have taken the lead in addressing the demand for customisable on-demand insurance, but large institutional insurers are responding to this trend by engaging emerging technologies and delving into transformational options to complement traditional services. Big data in conjunction with AI-driven analytics can be used to more precisely delineate the scope of cover provided. For example, big data and AI analytics enable insurers to monitor an insured&s;s activities in real time (such as motor and health risks) with the data about that insured&s;s behaviour (such as speeding in an insured motor vehicle). In principle, this enables an insurer to vary the scope of the cover or premium payable by way of real-time variations, which could extend to a policy termination or premium increases if certain behaviours occur. This chapter considers on-demand insurance and the associated technological developments supporting its global growth and development, as well as the risks and challenges to be addressed. The fraud implications of on-demand insurance and the potential for distributed ledger technology or blockchain initiatives to assist in fraud detection and risk prevention are also addressed.

Yiheng Tan, Xiying Huang, Wei Li

No abstract is available for this record.

Uma V. Sridharan, Fady Mansour, Lydia Ray, Tobias M. Huning

Purpose This study aims to investigate the effect of risk tolerance on the individual choice of adopting Bitcoin in the form of making and receiving payment and receiving compensation. Design/methodology/approach The study uses data collected from an anonymous survey of 225 undergraduate and graduate students to measure their risk attitude using the general risk-taking propensity scale proposed by Zhang et al. (2018) and the risk-taking index, proposed by Nicholson et al. (2018). After controlling for a variety of personal traits, the study uses logistic regression to identify the predicted probabilities and marginal effects on individual choice of adopting Bitcoin. Findings The findings of this study suggest that individuals with a higher risk-seeking attitude are more likely to choose to receive payment for goods they sell in Bitcoin and more likely to choose to receive a portion of their compensation in cryptocurrency. Individuals in the higher-income groups are more likely to adopt Bitcoin 46% and 65% than their lower 14% and 45% and middle income 4% and 18% counterparts. While there was no statistically significant difference between males and females in adopting Bitcoin, respondents between the age of 26 and 29 were more likely to adopt Bitcoin. The effect on receiving gold was slightly smaller but highly comparable to that of receiving Bitcoin, which highlights a similar perception of risk toward the Bitcoin and gold. Originality/value The study uses a new data set collected by surveying 225 individuals and two different risk measurements to identify the relationship between perceived risk and Bitcoin adoption.

Ferhat Aktaş

Kripto para ve spor arasında çeşitli ilişkiler bulunmaktadır. Kripto para birimleri, spor dünyasında sponsorluk ve reklam fırsatları sunarak önemli bir rol oynamaktadır. Spor takımları, kripto para şirketleriyle anlaşmalar yaparak forma reklamlarında veya stadyum isim haklarında kripto para şirketlerinin markalarını sergileyebilirler. Ayrıca, kripto para birimleri spor etkinliklerinin bilet satışlarında da kullanılabilmektedir. Bazı spor organizasyonları, kripto para birimleriyle bilet satın alma ve ödeme imkânı sunarak, kullanıcıların daha hızlı ve kolay bir şekilde biletlerini temin etmelerini sağlayabilirler. NFT'ler (Non-Fungible Token), kripto para birimleriyle popülerlik kazanan bir konudur ve spor dünyasında da büyük ilgi görmektedir. Bazı çevrimiçi bahis platformları, kripto para birimlerini kabul ederek, kullanıcıların anonimliklerini korumasını ve hızlı işlem yapmalarını sağlayabilirler. Ünlü sporcuların kripto para yatırımlarıyla ilgili açıklamaları veya sosyal medya üzerinden kripto para birimlerini desteklemeleri, kripto para sektöründe ilgi ve bilinirlik oluşturabilir. Kripto para ve spor arasındaki ilişki, spor dünyasına yeni fırsatlar ve finansal yenilikler getirebilirken, aynı zamanda riskleri ve belirsizlikleri de beraberinde getirebilir. Ancak, bu ilişkinin gelecekte daha da gelişmesi ve spor endüstrisinde daha fazla etkileşim sağlaması beklenmektedir.

Thomas Brzustowski, Alkis Georgiadis-Harris, Balázs Szentes

This paper reconsiders the problem of a durable-good monopolist who cannot make intertemporal commitments. The buyer’s valuation is binary and his private information. The seller has access to dynamic contracts and, in each period, decides whether to deploy the previous period’s contract or to replace it with a new one. The main result of the paper is that the Coase conjecture fails: the monopo-list’s payoff is bounded away from the low valuation irrespective of the discount factor. (JEL D42, D82, D86, L12)

Sihang Rao, Fuqiao Chen, Wen Hu, Feng Gao · 6 authors

No abstract is available for this record.

Yu Zhou, Xiang Gao, Jiajia Nie

Abstract In a modern supply chain, the quality of the final product is not determined by a single firm but depends on the joint efforts of multiple firms. When a quality defect happens, it is usually cost‐inefficient to trace the source of quality problems and all firms in the supply chain might incur a loss. New technologies such as blockchain can enable supply chain traceability at an affordable cost. In this paper, we develop a two‐echelon supply chain model including one supplier and one buyer in a competitive market. The quality of the final product depends on the two firms’ quality efforts. The buyer as a leader can set a wholesale price to stimulate the supplier's effort. In the absence (presence) of traceability, the payment of wholesale price is based on the realization of the final product's quality (the supplier's individual quality). Interestingly, we find that supply chain traceability may cause a decrease of the supplier's quality effort, thereby reducing the quality of the final product when market competition is sufficiently intensive. Furthermore, traceability weakly increases the supplier's profit but weakly decreases the buyer's profit. However, the total profit of the supply chain can be increased in the presence of traceability.

Alper Yayla, Ersin Dincelli, Srikanth Parameswaran

No abstract is available for this record.

Soumya Basu, David Easley, Maureen O’Hara, Emin Gün Sirer

Blockchain-based cryptocurrencies must solve the problem of assigning priorities to competing transactions. The most widely used mechanism involves each transaction offering a fee to be paid once the transaction is processed, but this discriminatory price mechanism fails to yield stable equilibria with predictable prices. We propose an alternate fee setting mechanism, StableFees, that is based on uniform price auctions. We prove that our proposed protocol is free from manipulation by users and miners as the number of users and miners increases and show empirically that gains from manipulation are small in practice. We show that StableFees reduces the fees paid by users and reduces the variance of fee income to miners. Data from December 2017 show that, if implemented, StableFees could have saved Bitcoin users $272,528,000 USD in transaction fees while reducing the variance of miner’s fee income, on average, by a factor of 7.4. We argue that our fee protocol also has important social welfare and environmental benefits. This paper was accepted by Agostino Capponi, Special Section of Management Science: Blockchains and Crypto Economics. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4735 .

Jooyoung Kim, Jooyoung Kim, Kyu Hyoung Lee, Jaemin Kim · 5 authors

No abstract is available for this record.

Qiang Guo, Pengfei Zhao, Shengyan Cheng, Mansoora Ahmed

No abstract is available for this record.

Hao Ying, Xiaosong Peng, Xiande Zhao, Zhong Chen

Blockchain‐based track and trace (BCT) is increasingly adopted in the retail supply chain. However, there is little rigorous empirical evidence quantifying the effects of BCT on consumer purchases or examining the heterogeneity of these effects with varying product‐related characteristics. Employing transactional data from a leading global e‐retailer that contains 540 stock keeping units (SKUs), we design a quasi‐natural experiment spanning 80 weeks to estimate the signaling effect of BCT (i.e., disclosure of the BCT to consumers) on consumer purchases. Drawing on the signaling theory, we propose that BCT can serve as an effective and reliable signal of the product quality and trustworthiness of the retailer. Our research uncovers significant positive effects of BCT on the average purchase quantity per buyer, the total number of buyers, the number of new buyers, and the number of unique visitors to the traced products. We also find nuanced moderation effects for two product‐related characteristics—namely, consumer review inconsistency and product origins—on the influence of BCT on consumer purchases. Specifically, the signal effectiveness of BCT is stronger for products with more inconsistent customer reviews that indicate greater information asymmetry. The effect of BCT for products sourced globally is magnified because of the high BCT signal reliability attributed to the unique properties of the blockchain. The heterogeneous effects of BCT by varying product‐related characteristics can inform managers in selecting the right products to implement BCT.

Dominika Bochańczyk-Kupka

The main aim of this article is to present and analyse changes in the global luxury goods market in the 21st century, with particular emphasis on the effects of the supply shock caused by the COVID-19 pandemic. In the part devoted to the period before the pandemic, the following market trends will be described: the democratisation of luxury, brand consolidation process, the emergence of Generation Alpha, the evolution of masstige goods relied on fast-fashion processes, "Chinese bulimia", market ”retailization” processes, the growing importance of mono-brand stores, rejection of online sales by European brands, e-commerce development, and growing environmental awareness. The article’s part, dedicated to the period of the pandemic and the changes immediately after it, presents trends such as the emergence of non-fungible tokens (NFTs) and gaming goods (metaverse gaming), the rebirth of the vintage market and secondhand stores, an increase in sales of casual goods, new multi-brand sales platforms, and the growing importance of local markets. The article is based on literature query and comparative analysis of industry reports prepared by Deloitte, Bain Company, and Luxe Digital.

Senyu Xu, Huajun Tang, Yuxin Huang

Purpose The purpose of this research is to investigate how to introduce a financing scheme to tackle the manufacturer's capital constraint problem, discuss the effects of data-driven marketing (DDM) quality, cross-channel-return (CCR) rate and financing interest rate on the members' pricing and delivery-lead-time decisions and optimal performances, and analyzes `how to achieve the coordination within a dual-channel supply chain (DSC) by contract coordination. Design/methodology/approach This work establishes a DSC model with DDM, and the offline retailer can provide internal financing to the capital-constrained online manufacturer. The demand under the price is determined based on DDM quality, customer channel preference and delivery lead time. Then, combined with the Stackelberg game, the optimal pricing and delivery-lead-time decisions are discussed under the inconsistent and consistent pricing strategies with decentralized and centralized systems. Furthermore, it designs a manufacturer-revenue sharing contract to coordinate the members under the two pricing strategies. Findings (1) The increase of DDM quality will reduce the delivery-lead-time under the inconsistent or consistent pricing strategy and will push the selling prices; (2) The growth of the CCR rate will raise selling prices and extend the delivery-lead-time under the decentralized decision; (3) Under price competition, the offline selling price is higher than the online selling price when customers prefer the offline channel and vice versa; (4) The retailer and the manufacturer can achieve a win-win situation through a manufacturer-revenue sharing contract. Originality/value This paper contributes to the studies related to DSC by investigating pricing and delivery-lead-time decisions based on DDM, CCR, internal financing and supply chain contract and proposes some managerial implications.

Jun Wang, Qian Zhang, Pengwen Hou, Qinghua Li

No abstract is available for this record.

Lang Xu, Yuqi Luo, Xujin Pu

No abstract is available for this record.

Zigui Jiang, Xiuwen Tang, Zibin Zheng, Jinyan Guo · 6 authors

No abstract is available for this record.

Akila Lourdes Miriyala Francis, E. Viswanathan, Dheeksha Jayaraman, Janani Padamanavan Ashokkumar · 5 authors

In this research paper, we'll talk about cryptocurrency with the help and development of deep learning, and AI-assisted trading has gained immense popularity. To regulate the splendid engrossment from the part of cryptology we take the assistance of retailing (Deep learning & AI-support). A specific period of data has been stored on daily bases to receive the outcomes in a company of the help of ultra-modern algos. With the references to various papers, I found out the pros and cons of cryptocurrency price prediction. Some simple algorithms & architectures helped to grow the cryptocurrency market. Crypto trading became popular in 2017 and now more than 1500 cryptocurrencies are proactively trading. Crypto currencies can be smoothly created and used for online settlement. Bitcoin is also known as cryptocurrency and its values keep varying every second. Hence for predicting the rate of bitcoin cost I will use the infrastructure of LSTM. This infrastructure will help us in proving that LSTM will provide more accuracy. RNN is a category of ANN and connectivity for this type of network is made through nodes from the direct nodes along with a time-related progressions. LSTM is a RNN infrastructure which is a part of DL which handles the entire data as well as single data points.