Research on telecommunication resale service supply chain coordination with revenue-sharing contract

The competition and cooperation between traditional telecom operators and resale operators in the supply chain are discussed, when the telecom industry developed telecommunication resale service. Supply chain contract is an effective way to coordinate the supply chain. This paper analyzes the revenue-sharing contract between telecom operators and resale operators. The study shows that by setting up a rational revenue-sharing ratio and wholesale price, a revenue-sharing contract can coordinate this supply chain, and telecom operators and resale operators can achieve a 'win-win' solution.

Revenue-sharing contract to coordinate independent participants within the supply chain

To improve the performance of the supply chain with one supplier and multiple retailers under deterministic price-sensitive customer demand, an optimal strategy is proposed based on knowledge discovery. First the decentralized system in which the supplier and the retailers are independent, profit-maximizing participants with the supplier acting as a Stackelberg game leader is studied. Numerical examples illustrate the importance of the coordination. The conventional quantity discount mechanism needs to be modified to coordinate the supply chain, so a revenue-sharing contract is proposed to coordinate such supply chain. Lastly, a special decision under certain demand rates is studied. The pricing and replenishment policies can be decided sequentially, which yields much less loss comparing with optimal decision when the demand rates are sufficiently large.

Research on two-part revenue-sharing contract under demand disruption

Assuming that the realized demand is determined by the inventory level,a two-part revenue sharing contract of one supplier and one retailer is analyzed under the circumstance of demand disruption(the disruption cost occurs at the supplier).Based on the centralized optimization,the profits of the two members are maximized in sequential optimization though a two-part revenue-sharing contract.The result shows that when the demand disruption occurs,if the degree of disruption is within some range,the ordering and manufacturing plans need not be changed,while only the revenue sharing fraction for the retailer should be diminished;if not,both the plan and the revenue sharing fraction should be changed for the possible coordination of the supply chain.Finally,numerical illustrations of the contract for various scenarios are given.

A Review of Deep Learning-Based Vulnerability Detection Tools for Ethernet Smart Contracts

In recent years,the number of smart contracts deployed on blockchain has exploded.However,the issue of vulnerability has caused incalculable losses.Due to the irreversible and immutability of smart contracts,vulnerability detection has become particularly important.With the popular use of neural network model,there has been a growing utilization of deep learning-based methods and tools for the identification of vulnerabilities within smart contracts.This paper commences by providing a succinct overview of prevalent categories of vulnerabilities found in smart contracts.Subsequently,it categorizes and presents an overview of contemporary deep learning-based tools developed for smart contract detection.These tools are categorized based on their open-source status,the data format and the type of feature extraction they employ.Then we conduct a comprehensive comparative analysis of these tools,selecting representative tools for experimental validation and comparing them with traditional tools in terms of detection coverage and accuracy.Finally,Based on the insights gained from the experimental results and the current state of research in the field of smart contract vulnerability detection tools,we suppose to provide a reference standard for developers of contract vulnerability detection tools.Meanwhile,forward-looking research directions are also proposed for deep learning-based smart contract vulnerability detection.

Preserving Data Secrecy and Integrity for Cloud Storage Using Smart Contracts and Cryptographic Primitives

Cloud computing has emerged as a viable alternative to traditional computing infrastructures,offering various benefits.However,the adoption of cloud storage poses significant risks to data secrecy and integrity.This article presents an effective mechanism to preserve the secrecy and integrity of data stored on the public cloud by leveraging blockchain technology,smart contracts,and cryptographic primitives.The proposed approach utilizes a Solidity-based smart contract as an auditor for maintaining and verifying the integrity of outsourced data.To preserve data secrecy,symmetric encryption systems are employed to encrypt user data before outsourcing it.An extensive performance analysis is conducted to illustrate the efficiency of the proposed mechanism.Additionally,a rigorous assessment is conducted to ensure that the developed smart contract is free from vulnerabilities and to measure its associated running costs.The security analysis of the proposed system confirms that our approach can securely maintain the confidentiality and integrity of cloud storage,even in the presence of malicious entities.The proposed mechanism contributes to enhancing data security in cloud computing environments and can be used as a foundation for developing more secure cloud storage systems.

Mitigating Blackhole and Greyhole Routing Attacks in Vehicular Ad Hoc Networks Using Blockchain Based Smart Contracts

The rapid increase in vehicle traffic volume in modern societies has raised the need to develop innovative solutions to reduce traffic congestion and enhance traffic management efficiency.Revolutionary advanced technology,such as Intelligent Transportation Systems(ITS),enables improved traffic management,helps eliminate congestion,and supports a safer environment.ITS provides real-time information on vehicle traffic and transportation systems that can improve decision-making for road users.However,ITS suffers from routing issues at the network layer when utilising Vehicular Ad Hoc Networks(VANETs).This is because each vehicle plays the role of a router in this network,which leads to a complex vehicle communication network,causing issues such as repeated link breakages between vehicles resulting from the mobility of the network and rapid topological variation.This may lead to loss or delay in packet transmissions;this weakness can be exploited in routing attacks,such as black-hole and gray-hole attacks,that threaten the availability of ITS services.In this paper,a Blockchain-based smart contracts model is proposed to offer convenient and comprehensive security mechanisms,enhancing the trustworthiness between vehicles.Self-Classification Blockchain-Based Contracts(SCBC)and Voting-Classification Blockchain-Based Contracts(VCBC)are utilised in the proposed protocol.The results show that VCBC succeeds in attaining better results in PDR and TP performance even in the presence of Blackhole and Grayhole attacks.

The Impact of Corporate Governance and Fair Value Accounting on Debt Contracts

This paper investigates the theoretical relationship between corporate governance,fair value accounting,and debt contracts.It primarily examines the individual impacts of corporate governance and fair value accounting on debt contracts,while also exploring the influence of corporate governance on fair value accounting.The study emphasizes the importance of considering the interests and legal status of creditors in the context of debt contracts.The findings indicate that strong corporate governance can reduce the likelihood of debt default and that the company’s restructuring costs in the event of a default determine whether improved corporate governance will increase or decrease debt costs.Additionally,the study reveals that the strength of corporate governance affects the value relevance of fair value accounting.However,the impact of fair value accounting on debt contracts is not inherently positive or negative;for instance,companies may use fair value adjustments with manipulative intent to enhance performance.Ultimately,the research highlights that discussions about corporate governance should not prioritize shareholder interests exclusively but also consider the legitimate position of creditors.

OPTIMAL CONTRACTS IN TWO-ECHELON SUPPLY CHAIN UNDER ASYMMETRIC INFORMATION AND NONLINEAR DEMAND

The challenge for supply chain management is to create appropriate supply chain contracts so as to optimize the system performance. To examine the role of asymmetric information in a two-echelon supply chain system and derive supply chain contracts to deal with existing asymmetric information, a two level supply chain model including one Supplier and one retailer under the demand of price elasticity is developed. By using the principalagent principle and the optimal control theory, three types of supply chain contract, i. e. , a wholesale pricing contract, a two-parameter linear and a two-parameter nonlinear contracts are obtained. In these contracts, the Supplier has asymmetric information about the retailer cost structure. Simulation results show that the two-parameter contracts are more effective strategies to achieve supply chain coordination.

The Characteristics of the Prepositions and Prepositional Phrases in Business English Contracts and Translation

A majority of contracts will use many prepositions and prepositional phrases to reflect their preciseness which cause the treaty wording complicated and hard to understand. This paper tends to demonstrate the characteristics of the prepositions and prepositional phrases used in business English contracts and explore the translation strategies used in translating the features of the prepositions and the prepositional phrases in business English contracts. The findings of this paper can provide a reference for the majority of the trade workers, which can help them accurately and effectively draft or translate a contract and avoid unnecessary disputes.

Risks and new transformations of PPP contracts

This paper tries to demonstrate that the principle of the risk allocation based on the balance is the most effective way to resolve the risk allocation problems of public-private partnership （PPP） contracts and presents suggestions how to carry out this principle. For PPP projects, it is necessary to set up a workable and commercially viable risk sharing mechanism to satisfy the different interests and the objectives of both the public sector and the private sector. An effective risk allocation mechanism is not only an important part in preparing project documents, but also an essential part in the success of PPP contracts. Risk allocation can be represented in a risk matrix. The more balanced the risk allocation is, the lower the risk degree of PPP contracts is. Therefore, the most effective risk allocation of PPP contracts is that the public sector and the private sector take part in risk management together in all the stages of the project and allocate the balanced risks. The outcomes of this paper can be used by both the public sector and the private sector to make a good choice of the PPP contract form.

Supply chain coordination mechanisms under flexible contracts

In supply chain management,an important research direction is to coordinate the supply chain through introducing flexible contracts.A supply chain contract is flexible if it can satisfy two conditions at the same time：the supply chain is coordinated,and the total profit of the supply chain can be arbitrarily divided between the supply chain members.This paper puts out two contracts,a flexible return contract and a flexible wholesale price discount contract.In contrast to many of literature,the supply chain contracts with an endogenous wholesale price is specifically considered,and a detailed sensitivity analysis of the contract parameters is given.The paper also discusses the application of the contract in vendor-managed inventory（VMI） mode.The results show that the supply chain＇s performance is improved after introducing above contracts.All the findings are illustrated by numerical examples.

Modeling China's offshore production sharing contracts using meta analysis

Production sharing contracts have been used in the development of China’s offshore petroleum resources since 1982, but the mechanism in which the fiscal terms impact project economics is complicated and not well understood. The purpose of this paper is to model China’s offshore production sharing contracts using a probabilistic approach. Cash flows and economic indicators are used for a typical offshore oilfield development, and meta-models are constructed to analyze the basic features of the fiscal system. Applications of the models in contract negotiation are discussed.

Modeling optimal oil production paths under risk service contracts

Due to the rigorous fiscal terms and huge potential risk of risk service contracts,optimizing oil production paths is one of the main challenges in designing oilfield development plans.In this paper,an oil production path optimization model is developed to maximize economic benefits within constraints of technology factors and oil contracts.This analysis describes the effects of risk service contract terms on parameters of inputs and outputs and quantifies the relationships between production and production time,revenues,investment and costs.An oil service development and production project is illustrated in which the optimal production path under its own geological conditions and contract terms is calculated.The influences of oil price,service fees per barrel and operating costs on the optimal production have been examined by sensitivity analysis.The results show that the oil price has the largest impact on the optimal production,which is negatively related to oil price and positively related to service fees per barrel and operating costs.

Elastic Smart Contracts in Blockchains

In this paper,we deal with questions related to blockchains in complex Internet of Things(IoT)-based ecosystems.Such ecosystems are typically composed of IoT devices,edge devices,cloud computing software services,as well as people,who are decision makers in scenarios such as smart cities.Many decisions related to analytics can be based on data coming from IoT sensors,software services,and people.However,they are typically based on different levels of abstraction and granularity.This poses a number of challenges when multiple blockchains are used together with smart contracts.This work proposes to apply our concept of elasticity to smart contracts and thereby enabling analytics in and between multiple blockchains in the context of IoT.We propose a reference architecture for Elastic Smart Contracts and evaluate the approach in a smart city scenario,discussing the benefits in terms of performance and self-adaptability of our solution.

Mining Bytecode Features of Smart Contracts to Detect PonziScheme on Blockchain

The emergence of smart contracts has increased the attention of industry and academia to blockchain technology,which is tamper-proofing,decentralized,autonomous,and enables decentralized applications to operate in untrustworthy environments.However,these features of this technology are also easily exploited by unscrupulous individuals,a typical example of which is the Ponzi scheme in Ethereum.The negative effect of unscrupulous individuals writing Ponzi scheme-type smart contracts in Ethereum and then using these contracts to scam large amounts of money has been significant.To solve this problem,we propose a detection model for detecting Ponzi schemes in smart contracts using bytecode.In this model,our innovation is shown in two aspects:We first propose to use two bytes as one characteristic,which can quickly transform the bytecode into a high-dimensional matrix,and this matrix contains all the implied characteristics in the bytecode.Then,We innovatively transformed the Ponzi schemes detection into an anomaly detection problem.Finally,an anomaly detection algorithm is used to identify Ponzi schemes in smart contracts.Experimental results show that the proposed detection model can greatly improve the accuracy of the detection of the Ponzi scheme contracts.Moreover,the F1-score of this model can reach 0.88,which is far better than those of other traditional detection models.

Review of Present Collection and Research on Forestry Contracts of Qing Dynasty in Jinping County,Guizhou Province

Forestry contracts of the Qing Dynasty in Jinping County, southwest China’s Guizhou Province, are a unique historical legacy of China. It came into being with the development of society and economy of Jinping. Research on these contracts is becoming widespread domestically and abroad as well. This paper is intended to make a review of the collection and research of forestry contracts in Jinping according to the chronological sequence.

Pareto Optimal Solution for Supply Contracts with Multiple Suppliers

This paper analyzes an electronic procurement （e-procurement） process between a manufacturer and N-supplier in the e-market. We proof that using the general contract based on auction theory, i. e. the wholesale price contract, would not achieve the coordination of channel composed of the manufacturer and the winning supplier. The paper designs a contract mechanism, i.e. the side payment price-restricted contract based on auction theory, which not only ensures Pareto optimal solutions for both, but also coordinates the supply chain. A numerical experiment is provided to compare the performance of different auction mechanisms and to reinforce key managerial insights generated through analysis.

A Review of Deepwater Pipeline Construction in the U.S. Gulf of Mexico-Contracts, Cost, and Installation Methods

The offshore pipeline network in the U.S. Gulf of Mexico is the largest and most transparent system in the world. A review of deepwater projects in the region provides insight into construction cost and installation methods and the evolution of contract strategies. Pipeline projects are identified as export systems, infield flowline systems, and combined export and infield systems, and three dozen deepwater pipeline installations from 1980–2014 are described based on Offshore Technology Conference(OTC) and Society of Petroleum Engineers(SPE) industry publications and press release data. Export lines and infield flowlines are equally represented and many projects used a combination of J-lay, S-lay and reel methods with rigid steel, flexible line, and pipe-in-pipe systems. The average 2014 inflation-adjusted cost for pipeline projects based on OTC/SPE publications was $2.76 million/mi and ranged from $520 000/mi to $12.94 million/mi. High cost pipelines tend to be short segments or specialized pipeline. Excluding the two cost endpoints, the majority of projects ranged from $1 to $6 million/mi. The average inflation-adjusted cost to install deepwater pipelines in the U.S. Gulf of Mexico based on available public data is estimated at $3.1 million/mi.

Incentive Contracts for Venture Capital Syndication

Aiming at the incentive problems of venture capital syndication at the second and later stages, an game model is set up by principal agent and incentive theory, given that the lead venture capitalist has already some knowledge of the project quality from his initial funding of the project. Under symmetric and asymmetric information, the model analyzes how the optimal syndication contracts induce venture capitalists to truthfully reveal their information to each other, and vary with the level of venture capitalists＇ expertise and information in evaluating projects.

Barriers to the Adoption of BOT Contracts System for Infrastructural Development of Technical Universities in Ghana

The study was conducted with the aim of exploring the barriers to the adoption of BOT contract systems for infrastructural development of technical universities in Ghana. In an empirical questionnaire survey with professionals and experts in the construction and education sector, the respondents were invited to rate their perception on the barriers to the adoption of the BOT contracts systems. An interview session to satisfy ways of adopting the BOT contracts for infrastructural development in technical universities was conducted with selected professionals. The study revealed that the major barriers to the adoption of the BOT contract system are: delays in approval, corruption, reliability and credit worthiness of entities and expropriation. The study suggested that detailed policy or framework for implementing BOT contracts;proper planning by technical universities;and adequate protection for lenders is required for successful BOT implementation. Therefore there is a need to explore this concept, using adequate policy initiatives, proper measures and support from government to improve on the proper implementation of the BOT contracts in Technical Universities in Ghana.