Fund Matching between Fund-Raisers and Investors in Financing Platform with Consideration of Default Risk

We construct a stochastic model to study the fund matching between fund-raisers and investors in a financing platform. The raising time is assumed to be a random variable. Then, there is a successful transaction probability that the fund matching is realized. Meanwhile, the interest and the commission rate that the platform earns affect the value of the probability. The platform maximizes its revenue by adjusting the commission rate. We find that the optimal commission rate decreases in investment time. However, when the time interval between two adjacent investments obeys the general distribution, the optimal commission rate increases in the annual interest rate. Besides, we extend the model into a duopoly case in which two fund-raisers compete for customers in the same platform by deciding their own interest rate. Due to lacking competition, the optimal interest rate in the monopoly case is lower than that in the duopoly case. Because the interest rate is the cost for the fund-raiser, the expected profit of the fund-raiser in the monopoly is higher than the expected profit of each fund-raiser in the duopoly case but lower than the total expected profit of two fund-raisers. The platform should choose some small loans as far as possible. The loans with smaller amount are easier for the platform to complete fundraising. For those large loans, the platform should try to ask for higher interest rates or more sufficient time to raise funds.

Supply Chain Performance with Target-Oriented Firms

Problem definition: We study a supply chain in which a supplier sets the wholesale price and a retailer responds with an order quantity. Both of the two firms can be either risk-neutral—maximizing the expected profit—or target-oriented, which is to maximize her or his ability to reach a target profit. Academic/practical relevance: Our work not only sheds light on the benefit/loss of trading with target-oriented decision makers but also, adds new knowledge to the supply chain coordination literature. Methodology: We provide strong support for firms’ target-based preference and the linear target formation model through a survey as well as analyzing company data. With the firms’ target-oriented behavior evaluated by a CVaR-satisficing measure, we apply a game theoretical framework to investigate how the target-based preference affects supply chain performance. Results: A firm, be it a supplier or a retailer, is always hurt by its target-based preference but can benefit from its trading partner’s target-based preference. A risk-neutral supplier, for example, can sometimes reap the whole supply chain’s profit if the retailer is target-oriented, and a target-oriented supplier always performs better with a target-oriented retailer than a risk-neutral one. Furthermore, a target-oriented retailer and/or supplier can help alleviate the double-marginalization effect and with a specific target, can help the supply chain achieve the same efficiency level as in a risk-neutral centralized system, with just a wholesale price contract. Another important finding is that if both firms are target-oriented, then the supply chain can have a higher expected profit under a decentralized system than a centralized one. This contrasts with the case when both firms are risk-neutral. We also investigate the role of outside option and retailer-type misidentification and find that both can alleviate the retailer’s disadvantage of being target-oriented. Managerial implications: (i) The target-based preference can be exploited by the trading partner, and hence, a firm should adopt the target-oriented decision criterion with caution. (ii) A target-oriented retailer can explore strategies such as revealing his outside option or hiding his target-based preference in order to be less manipulated. (iii) Whether a firm (and the supply chain) can benefit from its trading partner’s target-based preference often depends on how ambitious the trading partner (and the firm itself if it is target-oriented) sets the target. (iv) Target-based preference of one or both firms can help the supply chain reach the first-best efficiency. (v) When both firms are target-oriented, decentralization can be preferred to centralization.

Fashion retail competition on product greenness with overconfidence

In this paper, we study the impacts of overconfidence in a competitive retailer setting of green fashion. We model a green fashion supply chain comprising one unbiased manufacturer and two biased retailers, to explore how overconfidence affects greenness level of fashion products and expected profit of retailers. An overconfident retailer has a cognitive bias in which it believes consumers are more sensitive to greenness of fashion products than it really is. Our findings show that the competition between two retailers discourages greenness level of fashion products, while overconfidence can provide a counterbalance to the negative impact caused by competition. We also find, a retailer's overconfidence is not only conducive to the greenness level of its own fashion products, but also can benefit to its rival. Moreover, it shows a low level of overconfidence can be a comparative advantage of the retailer's profit. Even though one of the retailers is unbiased and has an advantage of information, it can still earn less than its overconfident rival.

Gambling Strategies and Prize-Pricing Recommendation in Sports Multi-Bets

A sports multi-bet is a bet on the results of a set of N games. One type of multi-bet offered by the Israeli government is WINNER 16, where participants guess the results of a set of 16 soccer games. The prizes in WINNER 16 are determined by the accumulated profit in previous rounds, and are split among all winning forms. When the reward increases beyond a certain threshold, a profitable strategy can be devised. Here, we present a machine-learning algorithm scheme to play WINNER 16. Our proposed algorithm is marginally profitable on average in a range of hyper-parameters, indicating inefficiencies in this game. To make a better prize-pricing mechanism we suggest a generalization of the single-bet approach. We studied the expected profit and risk of WINNER 16 after applying our suggestion. Our proposal can make the game more fair and more appealing without reducing the profitability.

Maximization of container slot booking profits for carriers in the liner shipping industry

In the liner shipping industry, if a shipper wants to transport its cargo by container ships, it first needs to contact a carrier to book container slots based on the estimated transportation demand. However, one problem in the booking process is that the actual demand is uncertain, resulting in mismatch between the required demand and the booked quantity. To address this issue, this study develops a Newsvendor model to find the optimal order quantity of container slots for the shipper. In addition, uncertainties in the quantity of container slots booking made by the shipper might cause revenue loss to the carrier and low utilization of ship capacity in the daily operations of liner shipping services. Therefore, this study suggests that the shipper should pay reservation fee when booking container slots. This study also aims to find the maximum profit for the carrier under the optimal order quantity of the shipper. In sensitive analysis, how different prices per container slot offered by the carrier would influence the reservation fee, the optimal order quantity of the shipper, and the expected profit of the carrier are explored and discussed. This study can help to manage and promote the online container booking systems in the liner shipping industry.

The Decision-Making Analysis on End-of-Life Vehicle Recycling and Remanufacturing under Extended Producer Responsibility Policy

This research develops a dual-cycle ELV recycling and remanufacturing system to better understand and improve the efficiency of the ELV recycling and remanufacturing businesses. For the flawless operation of this system, the researchers employed evolutionary game theory to establish a game model between original vehicle manufacturers (OVMs) and third-party recyclers with the government involved. This research presents evolutionary stable strategies (ESS) that could promote an ELV recycling and remanufacturing system. Results show that OVMs’ expected profit difference between choosing and not choosing authorization is crucial in their ESS. The licensing fee plays a part of OVMs’ expected profit difference. Based on the results, optimal ESS could be achieved when the OVMs’ expected profit difference between choosing authorization and not choosing authorization and the third-party recyclers’ profit when paying the licensing fee are both positive. Then, the two groups’ involvement in dual-cycle ELV recycling and the remanufacturing system can be ensured. This research implicates the government to devise appropriate reward and punishment strategy to encourage OVMs and third-party recyclers to collaborate for efficient recycling and remanufacturing systems. Particularly, the government is suggested to impose strict restrictions on OVMs to carry ELV recycling and provide support to promote recycling quantity standards. Hence, the ELV recycling and remanufacturing system would be strengthened, thus improving waste management which is crucial for both environmental and resource efficiency.

Research on Financial Hedging Decision Based on Exchange Rate Risk in Transnational Supply Chain

This paper considers a three-echelon manufacturer-retailer-supplier supply chain, the purpose of which is to investigate the influence of the bilateral exchange rate risks of import and export and the leading company’s financial hedging on the decision-makers of the supply chain. Firstly, it constructs the profit function and the financial hedging decision-making model of each member in the decentralized supply chain. Secondly, it introduces the incentive mechanism of exchange rate risk hedging in the centralized supply chain. Thirdly, from the perspective of wholesale price agreements and revenue-sharing contracts, it discusses the impact of financial hedging behavior and bilateral exchange rate risks on the decision-making process of each member through mathematical modeling. Finally, it explores the relationships of decision variables through simulation analysis. The results illustrate that (i) for decentralized and centralized decision-making, the manufacturer’s expected profit and profit variance decrease with the increase of the fluctuations of import and export exchange rates under the hedging strategy for exchange rate risks; (ii) compared with the decentralized supply chain, the manufacturer’s expected profit in the centralized supply chain decreases slightly under the revenue-sharing contract; (iii) in the centralized supply chain, if the manufacturer’s risk hedging ratio is high, its profit variance is smaller than that of the decentralized supply chain and the expected profits of the retailer and the supplier will increase significantly; and (iv) for the members of the transnational supply chain, centralized decision-making is better than decentralized decision-making.

New Product Presale Strategies considering Consumers’ Loss Aversion in the E-Commerce Supply Chain

New product presale is a strategic behavior of manufacturers to transfer inventory risks to consumers. The research purpose of this paper is to examine the presale discount, inventory, and service level decisions in an e-commerce supply chain, where the first period is the presale period and the second is the selling period for the new product. First, consumers were divided into two types—those who are risk averse and those who are not. Then, considering different presale discounts applied for new products, three presale strategy models were discussed: no-presale strategy, presale strategy with a moderate discount, and complete presale strategy, and the optimal decisions of e-commerce supply chain members were obtained under different valuations of the new product by consumers. Finally, the effects of the correlation coefficient between the numbers of the two types of consumers, the loss aversion degree of consumers, and the marginal profit in the sales period on the optimal discounted price and the maximum expected profit were analyzed. The conclusions of this article show that the presale strategy is not always optimal but depends on the parameters of the market and the type of consumers. For example, when the correlation coefficient between the two types of consumers is high, it is more profitable for the suppliers if they choose the presale strategy with a moderate discount, while e-commerce platforms tend to adopt the no-presale strategy. The optimal discounted price in the complete presale case is not necessarily lower than that in the moderately discounted presale case. If the marginal profit is high in the normal sales period or consumers are less averse to losses, suppliers are more likely to adopt the complete presale strategy. The research conclusions provide some theoretical reference for companies in the development of new product presale strategies in the e-commerce supply chain.

A systematic approach to the selection of the optimal capacity for liquid hydrocarbons offloading infrastructure and the sequence of exploration stages of a group of prospects

This paper validates and establishes the concept that the optimality of the decision on the timing of exploration, development and production stages for each field, as well as the performance of the combined transport infrastructure, may depend on the results of a specific scenario at one of the objects under consideration, as exemplified by three individual fields at different stages of development and with individual production and economic parameters. Nevertheless, by varying the values of the required parameters (e.g., shipping terminal capacity), we can determine their values that will result in maximizing expected profit from the project in any of the possible scenarios. The models and methods developed within this research represent a systemic approach to resolving the issue, and can be applied to developing the optimal strategy for additional study and development of the cluster of neighboring fields.