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1,173 results ¡ page 11 of 49
Nenggui Zhao, Jiasen Sun, Qiang Wang
No abstract is available for this record.
Elmira Mohammadhosseini Fadafan, Rudolf Vetschera
Abstract We consider a situation in which two parties have concluded an efficient contract corresponding to one major bargaining solution. After the parties have agreed on one particular contract, an unanticipated shock may change the contract outcomes in a way that benefits one party but harms the other party. If this happens, they have the option to either stay with the original exchange contract or adjust some contract parameters such as the price. We propose a model to perform such adjustments automatically, to obtain the same bargaining solution as in the initial contract under the restriction that the new contract dominates the outcomes of the original contract. We study several bargaining solutions within this general framework. These bargaining solutions offer various sharing rules to distribute the benefit between the parties. To reflect practical considerations, we only consider adjustments made via one contract parameter (the price), while all other parameters result from the original contract and the random shock. To evaluate the efficiency of the proposed approach, we also compare it to a full re-negotiation scenario, in which all parameters can be modified within the boundaries resulting after the random shock. However, waiting and re-negotiation might be costly compared to the situation when the smart contract executes the adjustment automatically. Therefore, the automatic adjustment might be more efficient compared to the other types of contracts. We present several numerical examples and run large random simulations, which we also check statistically.
Minh Ngoc Ta, Tien Quyet
No abstract is available for this record.
Kun Zhang, TsanâMing Choi, SaiâHo Chung, Yue Dai ¡ 5 authors
No abstract is available for this record.
Shang-Ching Kuei, MuâChen Chen
No abstract is available for this record.
Balaji Rao, Yeganeh M. Hayeri
In our study, we propose a novel validator selection mechanism for Proof-of-Stake blockchains that utilizes game theory through a Vickrey auction mechanism to encourage honest staking. The main element of our contribution is to include an auction mechanism that prevents domination by high-stake validators and a weighted random selection process to ensure fairness, and we aim to address a gap in selection methods that advantage nodes with more resources. The rationale for our approach is based on other game-theoretic approaches used in production-grade blockchains like Algorand, Avalanche, and Prism. We introduce a payment mechanism similar to a classic âstag huntâ scenario for mutual benefit through honest bidding. We propose a consensus mechanism that combines a weighted lottery pool and a second-price auction system for candidate selection and cost calculation. Our model incentivizes nodes to bid truthfully, reflecting their true value estimation of validating a block. We set up a PoS blockchain, the initialization of nodes and violators, and proceeded to simulate the addition of new blocks. We record the conditions of the bids and rewards to demonstrate that our mechanism promotes a fairer stake distribution while minimizing disparity among validators. Although a perfectly equitable system is challenging to design, our method offers a significant step towards a more equitable, secure, and efficient blockchain system.
Hongyu Liu, Wang Jia, Yuanyuan Ji
No abstract is available for this record.
Yao Cui, Vishal Gaur, Jingchen Liu
Companies that are investing in blockchain technology to enhance supply chain transparency face challenges in fostering collaborations with others and deciding what information to share. Transparency over the actions of supply chain partners can improve operational decisions, but sharing own data on the blockchain can put firms at a competitive disadvantage. In this paper, we investigate the resulting questions of when blockchain should be adopted in a supply chain and how it should be designed by analyzing two ways that it can enhance supply chain transparency: making the manufacturerâs sourcing cost transparent to the buyers (i.e., vertical cost transparency) and making the ordering status of buyers transparent to each other (i.e., horizontal order transparency). Given such transparency, firms can design a smart contract that automates transactions contingent on the revealed information and enables them to realize better equilibrium outcomes. We find that blockchain increases supply chain profit only when the manufacturerâs capacity is large and decreases supply chain profit otherwise. If the capacity is sufficiently large to eliminate the buyersâ competition, blockchain leads to a winâwinâwin and the incentives of all participants are naturally aligned. If the capacity is only moderately large, the manufacturer needs to compensate the buyers to facilitate a blockchain implementation. However, if the capacity is small, horizontal order transparency enabled by the blockchain mitigates the buyersâ overorder incentive to compete for the manufacturerâs capacity and increases double marginalization. For such cases, we show that a blockchain that only enables vertical cost transparency should (and can) still be adopted in a range of small capacity cases, and we propose an access control layer for the logistics data to implement such a blockchain. This paper was accepted by David Simchi-Levi, operations management. Funding: J. Liu was supported by the National Natural Science Foundation of China [Grant 72101110] and The MOE (Ministry of Education in China) Project of Humanities and Social Sciences [Grant 20YJC630084]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.4851 .
Yi He, Dexia He, Qingyun Xu
No abstract is available for this record.
Songxuan Ma, Bin Dan, Mengli Li, Maosen Zhou
Abstract This study targets a fresh produce supply chain that includes a retailer owning private demand information, a supplier who may adopt blockchain, and a 3PL (Third Party Logistics) engaging in freshness keeping. By developing a multiâstage game model, we study the blockchain adoption strategy and the informationâsharing strategy considering information transmission between the 3PL and the supplier and analyze the interaction of these strategies. We find that under the case of moderate blockchain cost, the retailer could encourage the supplier to adopt blockchain by sharing information strategically. In that case, the retailer would actively share with the supplier and the 3PL for fresh produce with low freshness sensitivity and serious consumer distrust. Otherwise, due to the dominant impact of information transmission, the retailer has to keep private information if consumers are less concerned about freshness, while it has to share information if consumers are more concerned about freshness.
Ubaidullah Mumtaz, Paul Bergey, Nicholas Letch
Technology adoption is vital for improving the efficiency of workflows across value chains. However, technology selection can be challenging, especially for multi-party workflows across different geographical boundaries. The chosen technologies must satisfy the requirements of the tasks at hand and align with international and local laws and regulations. Marine bunkering is a global industry comprising multiple stakeholders with diverse roles and responsibilities that must adhere to global standards and regulations. Through a single case study, we endeavor to understand the role of blockchain technology in marine bunkering, drawing on the Task-Technology Fit theory and Group Support System model to investigate this concept. Our analysis reveals that fit depends on underlying legal norms, task characteristics, and technological properties. Furthermore, we shed light on the blockchain framework used and the role of smart contracts in the value chain. Our research offers insights into an extended Task-Technology Fit theory where stakeholders in a value chain are distributed across multiple geographical boundaries.
Minxue Wang, Bo Li, DongâPing Song
No abstract is available for this record.
Bibhuti Bhusan Dash, Utpal Chandra De, Parthasarathi Pattnayak, Rabinarayan Satapathy ¡ 6 authors
No abstract is available for this record.
Jinting Huang, Biao Xu, Xiangbin Yan
Many e-commerce platforms, such as Amazon and JD.com, consider product information disclosure as a crucial retail strategy. However, due to potential consumer distrust in the disclosed information, these platforms may employ blockchain technology to validate the information and alleviate consumersâ doubts. This study presents a game-theoretical model to investigate the interaction among the manufacturerâs choice of selling mode, the platformâs decision regarding blockchain adoption, and information disclosure strategies in the presence of information asymmetry. Optimal pricing and information disclosure strategies are derived, and the impact of various parameters on the equilibrium results is analyzed. We find that the consumersâ privacy concerns and blockchain implementation costs both have negative effects on the equilibrium retail price, disclosed information amount and profits of the manufacturer and platform. Moreover, we also find that the introduction of blockchain has different effects on a platformâs pricing and information disclosure strategies depending on the market size. In addition, conditions are identified under which the manufacturer selects the optimal selling mode and the platform makes an optimal decision on blockchain adoption. The findings demonstrate that the cost of consumersâ privacy concerns and the commission rate play significant roles in determining the equilibrium selling mode selection and blockchain adoption strategies.
Lifeng Ni, Elnaz Irannezhad
The application of blockchain and smart contracts has been widely acknowledged as essential in digitised logistics, offering improved traceability, transparency, and efficiency. However, concerns regarding performance and implementation limitations persist. To demonstrate the challenges regarding the performance and efficiency of blockchain in logistics use cases, this study presents a proof-of-concept model by leveraging the Hyperledger Fabric blockchain network to emulate the shipping logistics process and illustrate the automated and self-executing nature of smart contracts and transactions among various logistics participants by implementing RAFT consensus mechanism. Utilizing Hyperledger Caliper, this study evaluates the performance by systematically adjusting parameters including the number of clients, the number of concurrent transactions, and transaction rates per second. Then nuanced variations in latency, send rate, and throughput are examined. Preliminary findings indicate significant performance impacts related to client numbers and transaction rates per second. When exceeding the processing capacity, the average latency of transactions experiences an exponential increase due to limited resources. Furthermore, different types of operations are compared, with Read operations exhibiting the lowest latency and Update operations displaying the highest latency due to the complex computations and validations involved. Lastly, the latency measures of the LogisticChain network between fixed-rate and linear-rate controllers are compared, highlighting lower latency with fixed-rate controllers. This research contributes to the advancement of knowledge in this field by developing open-source codes specifically tailored for maritime logistics use cases.
Garud Iyengar, Fahad Saleh, Jay Sethuraman, Wenjun Wang
We examine a supply chain with a single risk-averse manufacturer who purchases from suppliers and sells to consumers. Within this context, we focus on two channels that drive blockchain adoption by the manufacturer: manufacturer risk aversion and consumer information asymmetry. Regarding the first channel, blockchain enables efficient tracing of defective products so that the manufacturer can selectively recall defective products rather than conducting a full recall. This tracing ability reduces the risk involved in the manufacturer purchasing from multiple suppliers and thereby leads the manufacturer to endogenously diversify across suppliers when blockchain is adopted. The diversification enhances the manufacturerâs welfare due to the manufacturerâs risk aversion and thus drives the manufacturer to adopt blockchain. With regard to the second channel, blockchain stores details from the manufacturing process and reveals them to consumers, thereby ameliorating consumer information asymmetry. This reduction in information asymmetry improves consumer decision making that, in isolation, would enhance consumer welfare. However, the manufacturer responds by increasing the consumer price, thereby transferring potential consumer welfare gains to the manufacturer, and consequently serving as a second channel to drive blockchain adoption by the manufacturer. This paper was accepted by Lin William Cong, finance.
Wentao Xu, Wei Yan, Bo Song, Junliang He
Purpose The aim of this study is to examine the influence of consumer preferences for overseas green products and the implementation of blockchain technology on the performance of a supply chain, which comprises an overseas manufacturer and a domestic e-commerce platform. This research endeavors to identify the optimal pricing decisions and strategies for both the manufacturer and the platform in the context of the expanding e-commerce and globalization of the economy. Design/methodology/approach The authors propose and analyze four distinct models based on the selection of selling contracts by the manufacturer and the adoption strategy of blockchain by the platform, using game theory to obtain the optimal solutions for these models. Findings The authors show that consumer migration promotes the manufacturer's green inputs, while the expansion of green consumer proportion is not conducive to it. They also show that blockchain technology has the potential to effectively limit manufacturer cannibalization. Interestingly, the study reveals a cascading effect of advantage where the manufacturer's profit variation trend changes only with the integration of pricing power advantage and blockchain technology inputs. This effect suggests that the equilibrium strategy is achievable under the agency contract with blockchain adoption, while Pareto improvement can be obtained with blockchain technology under both selling contracts. Research limitations/implications This research could be extended in several possible directions. First, future work could explore outsourcing strategies for overseas manufacturers. Second, more types of consumer heterogeneity and different risk preferences could be considered. Third, this study can be extended by further exploring the design of mechanisms under asymmetric demand information to make the model more realistic. Originality/value The authors examine the impact of market segmentation and consumer preferences on green supply chain decisions, and analyze supply chain members' strategic choices for selling contracts and blockchain adoptions. The research also sheds light on the theoretical underpinnings and practical applications of green supply chain development and blockchain applications.
Md Sahabuddin, Qingmei Tan, Maryam Khokhar, Mohammad Amzad Hossain ¡ 6 authors
No abstract is available for this record.
Yongting Tian, Shouxu Song, Dan Zhou, Ruirui Yang ¡ 5 authors
This article underscores the necessity for sustainable and environmentally friendly manufacturing practices in product family configuration (PFC) projects, which are paramount to the global economy. Nevertheless, conventional approaches often fixate solely on design aspects, overlooking downstream supply chain configuration (SCC) considerations and the corresponding environmental benefits. Consequently, there is an escalating demand for an integrated optimisation approach that encompasses both PFC and SCC to realise economic and environmental advantages. This study delves into a methodology that integrates blockchain smart contracts as binary 0â1 variables with waste recycling and utilisation, yielding a comprehensive multi-objective model. The proposed methodology seamlessly incorporates considerations for both PFC and SCC. Furthermore, a nested leader-follower optimisation algorithm, based on the non-dominated sorting genetic algorithm-II (NSGA-II), has been devised with the objective of achieving triple benefits: augmented profits, maintenance revenue, and diminished environmental emissions. In conclusion, this research contributes to the advancement of sustainable collaborative optimisation through the innovative utilisation of blockchain smart contracts and multi-level modelling. To demonstrate the effectiveness of the proposed methodology, it is applied to a 60 KW DC electric vehicle (EV) charging piles, accompanied by a sensitivity analysis to assess its management implications.
Teck Lee Yap, Rajkishore Nayak, Nhung Vu, DuyâTung Bui ¡ 6 authors
Purpose Blockchain-based traceability technology (BTT) is an emerging digital technology that claims to have the potential to fulfil the demand for traceability to safeguard fruit safety. Drawing on the technological, organisational and environmental (TOE) framework, this study aims to investigate the perceived facilitators and barriers that influence the behavioural intentions of multiple stakeholders in the Vietnamese fruit supply chain (i.e., farmers, trading enterprises and consumers) to adopt BTT. Design/methodology/approach This study utilised a qualitative approach of semi-structured in-depth interviews with 60 stakeholders in the Vietnamese fruit supply chain to achieve the research objectives. NVivo 12 was employed to analyse the collected data using content and thematic analysis. Findings The findings identify several perceived facilitators that motivate BTT adoption. These include trust, transparency, business performance, the formation of alliances, consumer awareness of food safety and ethical agricultural practices, fruit branding and the pivotal role of farmers' cooperatives. Meanwhile, the perceived barriers to BTT adoption include a lack of digital literacy amongst the stakeholders, poor organisational culture, the high cost of traceability-enabled products and data privacy and security governance. Practical implications This study suggests that technology awareness and perceived facilitators and barriers should be incorporated into the design and deployment of blockchain-based traceability technology in the agri-food supply chain in developing countries. Originality/value To the best of the authors' knowledge, this study is the first qualitative paper that attempts to fill the research gap of understanding the perceived facilitators and barriers that influence the intentions of multiple stakeholders in the fruit supply chain to adopt BTT in the context of a developing economy.
Yong Wang, Qiong Jiang, Xu Guan, Xiangyang Guan ¡ 6 authors
No abstract is available for this record.
Kaustov Chakraborty, Arindam Ghosh, Saurabh Pratap
No abstract is available for this record.
YongâWu Zhou, Yu-shen Fu, Kunyu Wang, Jie Min ¡ 5 authors
Abstract Consumers typically have a higher preference and trust for traceability products, which makes many online platforms (e.g., JD.com, Tmall Global) and food manufacturers (e.g., BeingMate, Mengniu, Moutai) use blockchainâenabled traceability to improve product transparency and trust. This paper systematically analyzes the effects of constructing blockchainâbased information traceability systems (BITS) on supply chains led by different members in a dualâchannel supply chain consisting of a manufacturer and an online platform. We studied the optimal operational strategy for dualâchannel members in two scenarios without blockchain technology and different members (i.e., manufacturer and online platform) as leaders in building BITS. We find that BITS adoption can effectively improve the performance of supply chain members, but the value added to blockchain depends on the level of consumer goodwill toward BITS, the level of competition, and the proportion of cost sharing. We show that either the manufacturer or the online platform can be more profitable as a leader in building BITS. Further, we showed that either the manufacturer or the online platform, as the leader of BITS construction, should bear more construction costs so that the nonleader builder can gain more profit to achieve a winâwin result. Interestingly, as the leader of BITS construction bearing more construction costs can achieve higher system total profit.
Rejuwan Shamim, Badr Bentalha
Supply chain efficiency relies heavily on being able to accurately predict future demand. In this chapter, the authors offer a machine learning framework for supply chain management demand forecasting that makes use of blockchain technology. The framework improves the precision of demand forecasts while maintaining data integrity and openness through the use of machine learning algorithms and blockchain technologies. Demand data is collected and preprocessed, machine learning models are applied, and blockchain is used to validate and secure the data. Results from experiments show that the framework is useful, with significant gains in accuracy and recall compared to more conventional methods. The results show the promise of merging machine learning with blockchain in demand forecasting, giving supply chain professionals a potent instrument with which to enhance the effectiveness of inventory management and overall operations. To fully reap the benefits of this approach, more study into scalability and implementation difficulties is necessary.