Shipment Frequency of Exporters and Demand Uncertainty

Firms adjust to differences in market size and demand uncertainty by changing the frequency and size of their export shipments. In our inventory model, transportation costs and optimal shipment frequency are determined on the basis of demand as well as inventory and per shipments costs. Using a cross section of monthly firm-product-destination level French export data we confirm that firms adjust on both margins for market size. In a stochastic setting, firms adjust to increased uncertainty by reducing their sales and, for a given export volume, by reducing their number of shipments and increasing their shipment size

Market size and antidumping in duopolistic competition

As an effective measure of demand response programs, interruptible load management has been widely used in electricity markets. This paper addresses the problem of what impacts of interruptible load (IL) contracts will have on the equilibrium outcomes of electricity wholesale markets. First, a market demand model is developed to take considerations of IL contracts. Next, a linear supply function equilibrium model is presented for wholesale markets with IL contracts. The introduction of IL contracts leads to a non-smooth equilibrium problem. To solve this equilibrium problem, a novel solution method is proposed. Finally, numerical examples are presented to verify the effectiveness of the method, in which the uncertainty in market demand is considered to further reflect IL contracts' flexibility. It is shown that with IL contracts, market price and its fluctuation can be lowered. This effect is more obvious when the uncertainty in market demand is relatively large. Furthermore, to achieve the target of lowering market price and its fluctuation, the interruption threshold prices in the IL contracts should be determined carefully.

Recently, several unexpected events of various types (geopolitical, economic, health-related, and weather-related) have had a significant global impact, affecting the lives of millions of people and businesses. Disruptions in supply chains highlight the importance of planning and managing them at various hierarchical levels of decision-making. This paper presents and analyzes supply chain networks (SCNs) for the distribution of soybean and corn in Europe and North Africa, considering the uncertainty of demand and costs along intermodal routes. Transportation and distribution costs for these commodities are minimized by considering the uncertainty of demand and transportation costs. Starting from a deterministic model to establish the SCN, uncertainty is then introduced through stochastic modeling, with the optimization goals redefined accordingly, more specifically in terms of expected cost (EC) and conditional value at risk (CVAR) constraints. The solutions of the bi-objective model, including equivalent average emissions CO2, highlight the strategic positions of the port of Itaqui on the supply side and of the port of Sines as distribution hubs (transshipment) in the design of the networks according to the different objectives. The advantageous position of the port of Sines is analyzed in detail, according to the strategic objective of designing a more efficient intermodal SCN for the distribution of soybean and corn.

Building on recent contributions to the New Economic Geography literature, this paper analyses the relation between asymmetric market size, trade integration, and corporate income tax differentials across countries. First, relying on Ottaviano and Van Ypersele’s (J. Int. Econ. 67:25–46, 2005) foot-loose capital model of tax competition, we illustrate that trade integration reduces the importance of relative market size for differences in the extent of corporate taxation between countries. Then, using a dataset of 26 OECD countries over the period 1982–2004, we provide supportive evidence of these theoretical predictions, i.e., market size differences are strongly positively correlated with corporate income tax differences across countries, but crucially, trade integration weakens this link. These findings are obtained controlling for the potential endogeneity of trade integration and are robust to alternative specifications.

Trade Integration and Business Tax Differentials: Theory and Evidence from OECD Countries

Purpose Blockchain technology (BT) plays an important role in enhancing operational efficiency and consumer trust within the agricultural supply chain (ASC). The purpose of this paper is to investigate how risk-averse attitudes of e-ASC members affect the adoption decision of BT under the consideration of demand uncertainty. Design/methodology/approach This paper simultaneously considers the improvement of consumer trust and concerns of privacy information leakage within the context of BT. We constructed a game model of BT adoption under different risk attitudes consisting of agricultural supplier, third-party logistic (3PL) and e-retailer and introduced the mean-variance theory to analyze the impact of risk attitudes on equilibrium pricing, profits and consumer surplus. We further considered an extended analysis of risk-averse consumers. Findings The equilibrium pricing and equilibrium profit of supply chain members will increase with the heightened consumer trust degree for blockchain products and decrease as the consumer privacy concerns intensify regardless of risk attitudes. In the shift from risk-neutral to risk-averse, supply chain members have an incentive to reduce retail and wholesale prices to maintain their market size, which helps to mitigate the risk of profit volatility associated with demand uncertainty. Suppliers tend to reduce the profit risk from demand uncertainty at the cost of lower expected profits. It is interesting to note that considering risks is beneficial for e-retailer, as it may increase their expected profits. Consumers will also benefit from the risk aversion of supply chain members. Practical implications Practitioners can flexibly adjust pricing strategies based on their own risk preferences and market demand uncertainty to achieve maximum profit and minimum risk. To reduce consumers' privacy concerns, security measures such as digital encryption and digital summarization can be integrated at the technical level to ensure the confidentiality of privacy information. Originality/value This study enriches the research on the application of BT in ASCs and provides insights for practitioners on how to develop effective strategies under different risk attitudes.

Policy competition for foreign direct investment between asymmetric countries

Because of the importance of its products and huge value, the oil and gas industry itself occupies an important position in the national economic system. However, the development of this industry is unbalanced and insufficient, with large differences in market size, liquidity, solvency, profitability, valuation, and growth potential, and few companies have achieved good performance in all of these dimensions. This study delves into the unbalanced development and varied performance metrics among key petrochemical companies listed in the U.S. stock market, utilizing both fundamental analysis and non-financial analysis method, as well as to conduct a specific study on the competitive situation of Diamondback Energy. This study has elucidated that Diamondback Energy lags behind its peers in terms of liquidity and solvency. However, it is worth noting that despite macroeconomic challenges such as economic downturns and industry-wide downturns, its profitability remains relatively strong within the industry. Additionally, it holds a certain advantage over its peers in terms of financial valuation and growth potential, making it a growth-oriented enterprise. The study suggests that investors should consider market volatility and the company's management risk when entering the oil and gas industry in order to maximize returns.

This study develops a mathematical model for a supply chain system with a single supplier and two competing retailers. The selling price and service level are two aspects determining the demand. Investments in service level are also considered to enhance the service environment in the stores. Both parties in the supply chain system employ a periodic review policy to regulate the inventory level in a stochastic setting. This study includes a carbon tax regulation to reduce emissions in the observed system. The proposed model contributes to the current inventory literature by allowing the inclusion of price and service-dependent demand, competition between two retailers, investment in service level, and carbon emissions. The objective of this study is to maximize the joint total profit by optimizing the selling price, service level, safety factor, review period, and number of shipments. An algorithm is developed to solve the proposed problem and its application is validated with a numerical example. The results show that retailers' demand level, selling price, and service are sensitive to emissions and profit. Additionally, investment and carbon tax regulations are effective in raising service levels and reducing emissions, respectively. This research can help decision-makers select the optimal action to improve the effectiveness of the supply chain system, optimize product sales, and emphasize environmental considerations.

Purpose In the hybrid electricity market, renewable energy power generator faces the uncertainty of power market demand and the randomness of the renewable energy generation output. In order to improve the grid-connected quantity of green power, the purpose of this paper is to design the pricing mechanism for renewable energy power generator with revenue-sharing contract in a two-stage “multi-single” electricity supply chain which contains a single dominant power retailer and two kinds of power suppliers providing different power energy species. Design/methodology/approach Considering the dual uncertainties of renewable energy power output and power market demand, the authors design the full-cooperative contract decision-making model, wholesale price contract decision-making model and revenue-sharing contract decision-making model to compare and optimize grid-connected pricing in order to maximize profit of different parties in power supply chain. Then, this paper performs a numerical simulation, discusses the existence of the equilibrium analytical solutions to satisfy the supply chain coordination conditions and analyzes the optimal contract parameters’ variation characteristics and their interaction relationship. Findings The authors find that the expected profits of the parties in the hybrid power supply chain are concave about their decision variables in each decision-making mode. The revenue-sharing contract can realize the Pareto improvement for all parties’ interest of the supply chain, and promote the grid-connected quantity of green power effectively. The grid-connected price will reduce with the increase of revenue-sharing ratio, and this impact will be greater on the renewable energy power. The greater the competition intensity in power supply side, the smaller the revenue-sharing ratio from power purchaser. And for the same rangeability of competition intensity, the revenue-sharing ratio reduction of thermal power is less than that of the green power. The more the government subsidizing green power supplier, the smaller the retailer sharing revenue to it. Practical implications Facing with the dual uncertainties of green power output and market demand and the competition of thermal power in hybrid electricity market, this study can provide a path to solve the problem of renewable energy power grid-connecting. The results can help green power become competitive in hybrid power market under loose regulations. And this paper suggests that the government subsidy policy should be more tactical in order to implement a revenue-sharing contract of the power supply chain. Originality/value This paper studies the renewable energy electricity grid-connected pricing under the uncertainty of power supply and market demand, and compares different contract decision-making strategies in order to achieve the power supply chain coordination. The paper also analyzes the competition between thermal power and renewable energy power in hybrid electricity market.

This project focuses on supply chain coordination model between vendor and buyer with emphasis on transportation cost. The objective is to minimize the supply chain cost which comprises of order cost, setup cost, vendor holding, buyer holding, shortage cost and finally transportation cost. The model developed in this project determines the optimal order size, number of shipments, and reorder point while simultaneously accounting for the uncertainties in diesel price. Uncertainty in price of diesel is also developed using mean reverting process. To date, the impacts diesel price uncertainty and transportation cost in the supply chain policy is not very well known. This report provides an analysis by altering the multiple variables impacting transportation costs such as the truck type, feature, environmental condition, route, weight and driving style. This analysis demonstrates how changes in truck variables impact the expected total cost thereby making it extremely critical for corporations to mitigate costs strategically.

Wang, W.; Ren, Y.; Bian, W., and Jia, X., 2019. Low-carbon marine logistics network design under double uncertainty of market demand and carbon trading price. In: Gong, D.; Zhu, H., and Liu, R. (eds.), Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 94, pp. 30–39. Coconut Creek (Florida), ISSN 0749-0208.This paper discusses the low-carbon marine logistics network design problem under the uncertainty of market demand and carbon emission price, and aims at the minimum cost of shipping logistics network operation (including carbon emission cost), and constructs a three-level marine logistics network site-distribution model based on scenario. The problem is transformed into an unconstrained optimization problem by the penalty function method, and the artificial bee colony algorithm (ABC) is used to solve the model. The study found that the moderate fluctuation of demand is conducive to the integration effect of the marine logistics network, which reduces the total cost of the logistics network. Finally, the validity of the model is verified by an example analysis of a domestic industrial product manufacturer.

This work describes and proposes an two echelon inventory system under supply chain, where the manufacturer offers credit period to the retailer with exponential price dependent demand. The model is framed as demand is expressed as exponential function of retailer’s unit selling price. Mathematical model is framed to demonstrate the optimality of cycle time, retailer replenishment quantity, number of shipments, and total relevant cost of the supply chain. The major objective of the paper is to provide trade credit concept from the manufacturer to the retailer with exponential price dependent demand. The retailer would like to delay the payments of the manufacturer. At the first stage retailer and manufacturer expressions are expressed with the functions of ordering cost, carrying cost, transportation cost. In second stage combining of the manufacturer and retailer expressions are expressed. A MATLAB program is written to derive the optimality of cycle time, retailer replenishment quantity, number of shipments, and total relevant cost of the supply chain. From the optimality criteria derived managerial insights can be made. From the research findings, it is evident that the total cost of the supply chain is decreased with the increase in credit period under exponential price dependent demand. To analyse the influence of the model parameters, parametric analysis is also done by taking with help of numerical example.

Nowadays, due to the increasing complexity of business environment, especially demand uncertainty, supply chain managers need to establish more-effective sourcing and distribution strategies to ensure high customer service and low stock costs. To overcome this challenge multi-echelon network structures and alternative distribution strategies such as lateral transshipments and multiple sourcing should be considered in inventory optimisation models. In this article, we propose a scenario-based modelling approach to solve a two-stage multi-echelon inventory optimisation problem with a non-stationary demand. The model is based on a distribution requirements planning (DRP) approach and minimises the expected total cost that is composed of the fixed allocation, inventory holding, procurement, transportation, and back-ordering costs. Alternative inventory optimisation models, including the lateral transshipment strategy and multiple sourcing, are thus built, and the corresponding stochastic programmes are solved using the sample average approximation method. Through a numerical investigation conducted with several generated instances and an empirical investigation based on the case of a major French retailer’s distribution network, we show the substantial benefit of lateral transshipments and multiple sourcing in reducing the expected total costs of the distribution network.