Price Adjustment Research Articles

Spread Option Pricing Under Finite Liquidity Framework

This work explores a finite liquidity model to price spread options and assess the liquidity impact. We employ Kirk approximation for computing the spread option price and its delta. The latter is needed since the liquidity impact is caused by the delta hedging of a large investor. Our main contribution is a novel methodology to price spread options in this paradigm. Kirk approximation in conjunction with Monte Carlo simulations yields the spread option prices. Moreover, the antithetic and control variates variance reduction techniques improve the performance of our method. Numerical experiments reveal that the finite liquidity causes a liquidity value adjustment in option prices ranging from 0.53% to 2.81%. The effect of correlation on prices is also explored, and as expected the option price increases due to the diversification effect, but the liquidity impact decreases slightly.

Dampak Pembelian Dalam Game Mobile Legend Terhadap Peningkatan Keterampilan dan Keterlibatan Pemain Dengan Pengalaman Game Sebagai Variabel Moderasi

This study aims to investigate the relationship between in-game purchases in Mobile Legends and the improvement of players' playing skills and the extent to which experience factors moderate the relationship between these variables. This study uses a quantitative approach. Data will be collected through an online survey with a research instrument assessment using a Likert scale. The results of the study show that there is a significant relationship between the level of Mobile Legends player involvement and the intensity of in-game purchases. Players who are more involved tend to make in-game purchases with higher frequency and spend more money in the game. The implications of these findings are profound and cover several important aspects of the gaming industry as well as digital consumer behavior research. First of all, the microtransaction pricing adjustments suggested by this study can not only increase player engagement, but also have the potential to change the business paradigm in the gaming industry as a whole. By considering factors such as player price preferences and price sensitivity, developers can design smarter and more responsive pricing strategies. This will not only increase their revenues but also create a more inclusive and sustainable gaming ecosystem.

Resources Price Adjustment in Cloud Computing for Load Balancing and Fairness Between Users and Suppliers

Resource price adjustment is a challenging issue when building a cloud computing system. For this purpose, we present an approach that adopts a market-driven price adjustment model as an economic incentive model and ensures the balance between supply and demand. We show how this model may be adapted and applied to an infrastructure as a service (IaaS) in cloud computing. We place ourselves in the context of the virtual machines market. To achieve competitive equilibrium, prices are adjusted according to a tâtonnement-like process. The prices are computed by a third party, the auctioneer. However, this process requires several assumptions to ensure the existence and stability of competitive equilibrium, not all of which are verified by cloud computing systems. The atomicity and convexity of preferences are not guaranteed by cloud computing systems. These questions will be the subject of our empirical study. We find empirically that the change in the sign of excess demand, indicating the existence of equilibrium, occurs between two similar prices. The experimental results show that the proposed dynamic price adjustment approach is more profitable than fixed-price pricing, allowing dynamic suppliers to become important market agents.

Transfer Pricing End-of-Year Adjustments in Korea

While Korean transfer pricing regulations legally allow year-end transfer pricing adjustments after the filing of a corporate tax return, it is advisable to adjust transfer prices throughout the fiscal year with a well-established business plan and robust transfer pricing documentation.

Cross-border supply chain coordination of low-carbon agricultural products under the risk of supply uncertainty.

The purpose of this paper is to discuss how cross-border e-commerce enterprises can promote the sustainable development of the supply chain by optimizing the risk of supply disruption and product quality control mechanism of the cross-border supply chain of low-carbon agricultural products in the face of the problem of uneven quality and inventory shortage that prevails in the supply chain of low-carbon agricultural products under the framework of low-carbon economy. Methods: A two-level supply chain model consisting of a risk-averse cross-border e-commerce enterprise and two risk-neutral overseas suppliers is constructed to compare the optimal strategies and their coordination effects under the centralized and decentralized decision-making modes, and to deeply analyze the supply chain's operation mechanism. Further, the quality cost factor is introduced and an option contract model is designed to quantitatively analyze the impact of different decision-making scenarios and parameter changes on the overall supply chain performance. The results of the study show that under the coordination of option contract, the profit of cross-border e-commerce companies tends to decrease as the risk of supply disruption increases, while the profit of suppliers rises accordingly. Meanwhile, improving the quality of agricultural products can significantly improve the overall profitability of the supply chain. The cost-sharing mechanism is positively related to the profit of cross-border e-commerce companies, but negatively affects the profit of suppliers. In addition, the adjustment of the option price is directly associated with the increase of the specific supplier's profit and the decrease of the cross-border e-commerce enterprise's profit. Conclusion: By constructing and analyzing the option contract model considering the risk of supply disruption, this study effectively reveals the key influencing factors and their interactions in the cross-border supply chain of low-carbon agricultural products, and provides cross-border e-commerce enterprises with specific strategies to achieve coordination of the supply chain contract, improve product quality, and mitigate the risk of supply disruption, and then promote the sustainable development of the supply chain of low-carbon agricultural products.

VAT pass-through and competition: Evidence from the Greek islands

We examine how competition affects VAT pass-through in isolated oligopolistic markets as defined by the Greek islands. Using daily gasoline prices and a difference-in-differences methodology, we investigate how changes in VAT rates are passed through to consumers in islands with different market structure. We show that pass-through increases with competition, going from 50% in monopoly to around 80% in more competitive markets, but remains incomplete. We also discover a rapid rate of adjustment for VAT changes, as well as a positive relationship between competition and the rate of price adjustment. Finally, we document higher pass-through for products with more inelastic demand.

Dynamics of a Price Adjustment Model with Distributed Delay

This paper deals with the stability and occurrence of Hopf bifurcation of a distributed delay differential cobweb model using the chain trick technique. This is a generalized form of the fixed delay cobweb model to which it is compared using the same parameter values. The results from the delay distribution showed that whenever less weight (γ=0.146) is put on past prices, the current equilibrium price is adjusted upwards while the reverse is observed when a higher weight (γ=0.186) is put on the previous price. It is also observed that if the initial price is set below/above the equilibrium price, the price adjustment either affects the consumers or benefits the suppliers. However, the fixed delay cobweb model does not display the consumers or suppliers benefits of the price dynamics in either direction. These are unique, underlying patterns in price dynamics discovered when using a distributed delay model compared to traditional fixed delay cobweb models. Furthermore, our model challenges the traditional cobweb model’s requirement for divergence, as it is based on the weight assigned to past prices rather than the relationship between the elasticities of supply and demand, which is the determining factor in the classical model. Based on these insights, we recommend that future price adjustment models incorporate distributed delays, as they reveal more intricate price dynamics and provide a more comprehensive understanding of market behavior than fixed delay models.

Rarity, the WTA-WTP disparity, and price adjustments in the NFT market

Non-fungible tokens (NFTs) have become popular and are frequently traded in marketplaces. The current study examines how an NFT’s within-collection rarity influences sellers’ and buyers’ pricing and pricing dynamics. Relying on the pricing history of CryptoPunks, one of the most famous and valuable NFT collections, we find that rarity’s positive impact on willingness to accept is greater than on willingness to pay, which generates a larger pricing disparity. We further examine rarity’s impact on subsequent price adjustments and find that as rarity increases, buyers are more inclined to make greater price concessions, and sellers are reluctant to reduce their prices. Results also show that rarity’s positive impact on pricing is moderated by the NFT’s past ownership, agents’ trading experiences, and agents’ average holding periods for previous NFTs. Finally, an experiment reveals the mediating role of the focus on rarity that sellers tend to consider more about the NFT’s rarity than buyers, and therefore rarity’s positive impact on pricing is more salient for sellers than buyers.

Towards net zero: Comprehensive approach for voluntary carbon trading among microgrids

In the context of growing focus over climate changes and promoting sustainability across a various range of fields, microgrids can play a significant role in global decarbonization endeavors, contributing to carbon neutrality and ultimately attaining net-zero emissions in the energy sector. The objective of this paper is to address the integration of voluntary carbon trading within microgrid communities, in the perspective to mitigate greenhouse gas (GHG) emissions and boost the integration of renewable energy sources (RES). Introducing five modular algorithms managing key aspects of carbon trading, the study engineers a comprehensive framework aiming to optimally orchestrate the Voluntary Carbon Market (VCM) within microgrids. Particularly, the developed algorithms address aspects such as market enrollment decision, optimal energy dispatch, managing the market transactions, sellers-buyers matching as well as the dynamic adjustment of carbon credit prices and emission taxes. The framework has been rigorously tested across three distinct scenarios. Results show that the developed VCM, with adequate configurations, has the potential to incentivize microgrids to curtail their GHG emissions, encourage the integration of more RES into their generation mix, and rewards the more proactive microgrids with substantial financial incentives.

Increased Competitiveness of Indonesia's Rubber Rubber Exports After The Enactment of ACFTA (Asean-China Free Trade Agreement)

The ASEAN-China Free Trade Agreement (ACFTA), which came into effect in January 2010, aims to increase economic cooperation and remove trade barriers. However, the value of Indonesia's rubber exports decreased significantly after the implementation of this agreement. This study uses the gravity model and Revealed Trade Advantage (RCTA) method to analyze the factors affecting the decline in the value of Indonesia's rubber exports. The data used covers the period 2001-2022 and is taken from various sources including TradeMap and interviews with rubber exporters. Findings show that the value of Indonesia's rubber exports to China and ASEAN countries has fluctuated, with a significant decline after 2011. Gravity model analysis shows that ASEAN-China real GDP growth is negatively related to the value of Indonesian rubber exports, while other factors such as exchange rates and commodity prices also play a role. The decline in Indonesia's rubber export competitiveness is not only caused by the implementation of ACFTA, but also by internal factors such as low productivity and underinvestment. Recommendations are given for commodity price adjustments to improve Indonesia's rubber export competitiveness.

Accessibility of Pareto optima

Non-tâtonnement processes and planning procedures have been defined in different economic contexts, as dynamic processes to reach efficient allocations, with or without price adjustment, satisfying the property that, along the process, the utility of every agent is non-decreasing and transactions can occur, thus making a clear distinction with the study of tâtonnement processes whose goal is to reach competitive equilibria with transactions occurring only at equilibrium.In this paper, we provide sufficient conditions guaranteeing that every Pareto optimum which is preferred or indifferent to some given initial situation by every agent is accessible by a monotone efficient dynamic process. The framework considered is general enough to encompass the accessibility of Pareto optima by a non-tâtonnement barter process in an exchange economy, the neutrality of the MDP procedure in an economy with public goods, and other types of planning procedures.

Practical Applications of Asleep at the Wheel? The Risk of Sudden Price Adjustments for Climate Risk

Practical Applications of Asleep at the Wheel? The Risk of Sudden Price Adjustments for Climate Risk

Dynamic pricing for perishable goods: A data-driven digital transformation approach

In supermarkets, rapid pricing adjustments are crucial due to the short shelf life of products. Adopting a multi-case study approach, this study examines the application of dynamic pricing strategies for perishable goods through the lens of a data-driven digital transformation (DD-DT) approach. We introduce a three-phase model of DD-DT for dynamic pricing: initiation, facilitation, and strategic adaptation. In the initiation phase, we identify essential frameworks for robust data collection and analytical processes, which form the backbone of informed pricing decisions. During the facilitation phase, the study integrates sophisticated algorithms and real-time analytics to process and interpret the collected data, facilitating its seamless integration into pricing strategies. The strategic adaptation phase is critical as it focuses on the ongoing refinement and enhancement of pricing strategies, enabling supermarkets to adapt swiftly to market fluctuations and consumer behaviour changes. By presenting a comprehensive DD-DT framework, this research significantly augments the existing literature on dynamic pricing and offers actionable insights for practitioners seeking to optimize pricing strategies in a digitally transforming marketplace.

Forecasting the outcomes of construction contract disputes using machine learning techniques

PurposeThis study aims to develop a predictive model using machine learning techniques to forecast construction dispute outcomes, thereby minimizing economic and social losses and promoting amicable settlements between parties.Design/methodology/approachThis study develops a novel conceptual model incorporating project characteristics, root causes, and underlying causes to predict construction dispute outcomes. Utilizing a dataset of arbitration cases in Türkiye, the model was tested using five machine learning algorithms namely Logistic Regression, Support Vector Machines, Decision Trees, K-Nearest Neighbors, and Random Forest in a Python environment. The performance of each algorithm was evaluated to identify the most accurate predictive model.FindingsThe analysis revealed that the Support Vector Machine algorithm achieved the highest prediction accuracy at 71.65%. Twelve significant variables were identified for the best model namely, work type, root causes, delays from a contractor, extension of time, different site conditions, poorly written contracts, unit price determination, penalties, price adjustment, acceptances, delay of schedule, and extra payment claims. The study’s results surpass some existing models in the literature, highlighting the model’s robustness and practical applicability in forecasting construction dispute outcomes.Originality/valueThis study is unique in its consideration of various contract, dispute, and project attributes to predict construction dispute outcomes using machine learning techniques. It uses a fact-based dataset of arbitration cases from Türkiye, providing a robust and practical predictive model applicable across different regions and project types. It advances the literature by comparing multiple machine learning algorithms to achieve the highest prediction accuracy and offering a comprehensive tool for proactive dispute management.

Trends in drug treatment of benign prostatic hyperplasia in Japan based on the National Database Open Data.

This study examined prescription trends for benign prostatic hyperplasia (BPH) drug therapy in Japan over the past decade, focusing on drugs rated as grade A according to Japanese clinical guidelines. Using the National Database Open Data, this study analyzed prescription data from the fiscal years of 2014 to 2021, tracking α1-blockers, 5α-reductase inhibitors, and phosphodiesterase type 5 inhibitors. We adjusted for demographics and calculated medication costs to determine prescribing patterns and changes in drug utilization. Prescriptions for α1-blockers increased from 9898 per 1000 males in 2014 to 12 613 in 2021. Prescriptions for 5α-reductase inhibitors rose from 1441 per 1000 males in 2014 to 2310 in 2021. Tadalafil prescriptions saw a significant increase, from 900 in 2015 to 2520 in 2021. Despite these increases, the overall market size for BPH drugs decreased from 664 million dollars in 2014 to 279 million dollars in 2021, indicating a shift toward generic medications driven by healthcare policies. Although BPH medication prescriptions are increasing, driven by Japan's aging population and clinical guidelines, market dynamics are shifting owing to generic and government price adjustments. This analysis underscores the changing BPH treatment landscape in Japan, highlighting the importance of continuous evaluation of treatment efficacy and cost-effectiveness in evolving healthcare policies and demographics.

Cost-Effectiveness of Zanubrutinib Versus Bendamustine and Rituximab in Patients With Untreated Chronic Lymphocytic Leukemia

Zanubrutinib, a potent and specific irreversible Bruton's tyrosine kinase inhibitor, has proven to be effective in untreated chronic lymphocytic leukemia (CLL), whether used alone or in combination with other therapies. Here, we compared the cost-effectiveness of zanubrutinib with bendamustine-rituximab (R-bendamustine) to determine its effectiveness as the first-line treatment for Chinese patients with untreated CLL. The evaluation utilized a partitioned survival model, constructed using TreeAge Pro 2011 software, incorporating data from SEQUOIA trial (NCT03336333). Transition probabilities were estimated from the reported survival probabilities in trials using parametric survival modeling. In this analysis, the quality-adjusted life years (QALYs), incremental cost-effectiveness ratio, and lifetime cost were calculated from the Chinese health care system perspective. Sensitivity analyses, including 1-way analysis and probabilistic sensitivity analysis, were carried out to explore the uncertainty of the modeling results. Additionally, several scenario analyses, including different zanubrutinib price calculation and 20-year time horizon, were evaluated. The findings revealed that zanubrutinib had an incremental cost-effectiveness ratio of $58,258.18 per additional QALYs gained compared with bendamustine-rituximab, with zanubrutinib being cost-effective only if its price was reduced by more than 30%. Research indicated that zanubrutinib achieved at least a 3.70% probability of cost-effectiveness at the threshold of $38,223.34/QALY. One-way sensitivity analysis revealed that the results were sensitive to the utility of progressed disease. The study highlighted the importance of considering the cost-effectiveness of zanubrutinib at its current price point for patients with untreated CLL in China, emphasizing the need for further assessment and potential pricing adjustments to enhance its economic viability in clinical practice.

Dynamic Analysis of the Multichannel Supply Chain Under Carbon Subsidy Policy

For achieving the goals of carbon peaking and carbon neutrality, the government will further strengthen subsidies to enterprises for carbon emission reduction. This paper investigates the long-term repeated game behavior of manufacturer and retailer in multichannel supply chains under three different forms of government subsidies. The long-term repeated game behavior of manufacturer and retailer is studied under the manufacturer green innovation subsidy model (IS model), manufacturer production subsidy model (MS model) and retailer sales subsidy model (RS model). Under three situations, excessive price adjustment can easily lead to system instability and sharp fluctuations in profits. Two methods are used for chaos control and management, and the parameter adjustment control method is found having more advantages for system re-stabilization.

MARKETING PRICING POLICY OF A RETAIL BUSINESS ENTERPRISES

Pricing policy is a core element of marketing strategy for any business, especially in the retail sector. In the context of high competition and changing consumer preferences, iterative price adjustments for goods and services become a critical factor for the success of a retail business. Therefore, the article aims to define the basic principles of forming the marketing pricing policy for a retail business. The authors highlight the fact that the marketing pricing policy of a retail business uses price as a tool to achieve specific marketing objectives. It has been proven that such a policy is based on processes and actions involving the continuous analysis and adjustment of prices for goods to balance several core marketing indicators. Future research prospects may focus on analyzing the effectiveness of specific pricing tools and methods of their implementation in the rapidly changing retail market, as well as on developing new approaches for integrating these tools into comprehensive pricing management strategies.

Complexity Analysis of the Interaction between Government Carbon Quota Mechanism and Manufacturers’ Emission Reduction Strategies under Carbon Cap-and-Trade Mechanism

Based on different carbon quota trading mechanisms, the price and emission reduction strategies of oligopoly manufacturers in the low-carbon market and the government carbon quota mechanism are considered. A dynamic game evolution model of the two oligopoly manufacturers with competitive relations is established. The stability of the equilibrium point of the game model, the price adjustment speed of the decision variable, the impact of carbon emission reduction investment, and the government carbon quota on the system are discussed. Through nonlinear dynamics research, it is found that the advantage of the grandfathering method is that it is conducive to maintaining market stability when the government’s carbon quota decision changes; the advantage of the benchmarking method is that when manufacturers formulate price adjustment strategies, the benchmarking method carbon quota mechanism has a stronger stability range for the market, the manufacturer’s profit price adjustment speed is positively correlated, and the government carbon quota decision and emission reduction investment are also positively correlated. Decision makers need to choose appropriate carbon quota mechanisms and manufacturers’ emission reduction strategies according to actual market changes to maintain supply chain stability.

Different effects of carbon pricing and border adjustment in Germany and Spain

This study examines the effects of carbon pricing in Germany, Spain, and the broader European context using the dynamic, three-region environmental multisector general equilibrium model, EMuSe. Our findings indicate that unilateral carbon pricing in Germany or Spain leads to a sustained negative output. The marginal increase in production costs outweighs modest reductions in emissions. However, when Europe collectively adopts carbon pricing, the long-term output effects become positive, although there are more significant transition costs due to close trade relations within Europe. We find evidence of carbon leakage, which is marginally mitigated by a border adjustment mechanism. However, this mechanism mainly protects domestic carbon-intensive sectors and produces inconsistent country outcomes; Germany gains, while Spain loses. Notably, Spain’s energy sector emerges as a long-term beneficiary due to its relatively lower emission intensity. The findings highlight the strategic importance for Europe to engage global partners in carbon pricing as it reduces the economic downturn phase and increases long-term gains.