Pricing Mechanism Research Articles

Climate action and social equity: Mitigation strategies and carbon credits

Carbon taxes are a critical tool in global efforts to reduce greenhouse gas emissions, but they often have regressive effects, disproportionately burdening low-income households. This study examines the economic impact of carbon taxes on different income groups, with a focus on the regressive nature of these policies. Low-income households, which typically spend a higher percentage of their income on energy and carbon-intensive goods, are more adversely affected by carbon taxes. This analysis explores potential mitigation strategies, such as rebates, targeted subsidies, and income-based tax adjustments, to offset these regressive effects. Additionally, the study investigates the role of carbon credits in income distribution, analyzing how the allocation and trading of credits can influence social equity. The research also considers the broader implications of carbon taxes and credits on income distribution, highlighting the need for policies that balance environmental objectives with social equity. By examining the intersection of carbon pricing mechanisms and income inequality, this study provides insights into how policymakers can design carbon taxes and credits that minimize regressive impacts while promoting fair and equitable climate action. The findings underscore the importance of integrating social equity considerations into carbon pricing strategies to ensure that climate policies contribute to sustainable and inclusive economic growth.

Electricity price cross-subsidies and enterprises’ green total factor productivity: Empirical evidence from Chinese industrial listed enterprises

As a kind of electricity price distortion, the effect of electricity price cross-subsidies has always been controversial. From the perspective of the green development effect generated by electricity price cross-subsidies, we estimate the electricity price cross-subsidies in different regions of China using Ramsey’s optimal pricing as a yardstick, and measure the green total factor productivity(GTFP) of enterprises using the SBM-DDF model with the samples of industrial listed enterprises from 2006 to 2020, and then empirically analyze the mechanism of the electricity price cross-subsidies affecting enterprises’ GTFP. The results show that electricity price cross-subsidies affect enterprises’ GTFP through two channels, improving resource allocation efficiency and inhibiting technological progress. However, the effect of electricity price cross-subsidies on improving resource allocation efficiency is more significant than its inhibitory effect on technological advancement, which ultimately enhances the enterprises’ GTFP. At the same time, the impact of electricity price cross-subsidies on enterprises’ GTFP varies significantly across enterprises with different ownership structures, different scales, different energy consumption, and located in different regions, as well as before and after the second round of China’s electricity system reform in 2015. This study provides empirical inspiration for developing countries to steadily advance the reform of electricity price cross-subsidies policies and accelerate the green transformation of economic development mode.

Carbon governance or trade gaming: China's approach to addressing the EU's carbon border adjustment mechanism

The EU's Carbon Border Adjustment Mechanism (CBAM) poses a significant challenge for developing countries, especially China, a key player in the global market and a major carbon emitter. We use the GTAP-E model to evaluate CBAM's impact on China's economy and carbon reduction efforts, and propose two response strategies: carbon governance approaches and international trade gaming. Our findings show that CBAM may lead to a slight decrease of 0.003% in China's GDP and a 0.004% reduction in carbon emissions. It also generates ripple effects across the supply chain, notably affecting energy-intensive upstream industries. We find that the combination of carbon pricing and trade agreements is more effective than trade protection measures in minimizing economic losses from CBAM. This is achieved through mechanisms such as sharing carbon reduction costs and promoting decarbonization on both the supply and demand sides. Furthermore, improving carbon governance can enhance the green competitiveness of Chinese products. Going forward, China should maintain trade agreements with developing countries and enhance its carbon pricing mechanism to better align with global climate governance. Our study offers valuable policy insights for developing countries as they navigate the challenges posed by CBAM.

The impact of reform of medical insurance payment method on medical service pricing—based on empirical analysis of matched medical finance comprehensive data

BackgroundThe medical insurance payment method (MIPM) has an important impact on medical service pricing (MSP) in China. The objective of this study is to examine the impact of medical insurance payment method on medical service pricing with the hope of providing insights into appropriate MSP and resource allocation.MethodFrom the perspective of information asymmetry, using the matched medical finance comprehensive data of Chengdu City, our study empirically analyzed the effect of fixed payment by disease (FPD) on MSP by the difference in difference (DID) model.ResultsThe study found that FPD not only optimizes the allocation of medical resources, saves a large amount of medical insurance funds, but also reduces the personal burden of patients. FPD is adjusted by optimizing the structure of medical expenses and medical insurance compensation, which has certain effects on saving medical insurance funds, improving the quality of medical services, and reducing the burden on patients. It has achieved the goal of medical insurance payment method reform, and make the mechanism of MSP relatively more reasonable.ConclusionThis study provided policy implications for the government to implement multiple and compound medical insurance payment method and establish a more scientific and reasonable pricing mechanism for medical services.

Hybrid game model for electricity trading and pricing among multiple microgrids and consumers based on demand-side complex networks

Local energy markets (LEMs) are pivotal for enhancing renewable energy consumption and facilitating green electricity by linking multiple microgrids (MMGs) and consumers. Existing studies often overlook the evolution of consumer purchasing strategies influenced by social spatial structures and social learning dynamics. This paper addresses this gap by introducing a hybrid game model for LEMs electricity trading and dynamic pricing, integrating demand-side complex network structures. This model encompasses dynamic interactions between MMGs and electricity and carbon markets, employing non-cooperative games among MMGs, complex network evolutionary game among consumers, and Stackelberg games between MMGs and consumers. It promotes efficient transactions and adaptive pricing through distributed algorithms optimizing equilibrium solutions. Key findings include: (1) Compared to Power-to-Grid and Peer-to-Peer models, our model increased MMGs' revenues by 44.10 % and 10.60 %, reduced consumers’ costs by 8.76 % and 1.15 %, and cut carbon emissions by 93.32 % and 77.30 %, significantly boosting economic and environmental benefits. (2) Complex network analysis underscores the importance of social learning in adjusting power consumption strategies and pricing mechanisms. (3) Multidimensional consumer decision-making enhances renewable energy valuation, fosters price competition among MMGs, and accelerates low-carbon transitions in LEMs, providing crucial theoretical support for LEM structure design and policy to enhance renewable energy use.

A Three-Party Dynamic Pricing Mechanism for Customized Data Products Based on the Stackelberg Game and Bargaining Model

In the era of big data, breaking down data silos to enable efficient data transactions has become essential, with the fairness and transparency of pricing mechanisms being paramount. This study addresses these challenges by introducing a novel tripartite pricing model for customized data products that integrates the Stackelberg and bargaining game frameworks. By designing distinct utility functions for buyers, sellers, and the platform, the model effectively aligns the varying objectives of each participant. A dynamic adjustment mechanism further enhances this model by adaptively recalibrating the guidance price and pricing range based on real-time updates to buyer budgets and seller offers, thus ensuring fairness and responsiveness throughout the negotiation process. Experimental simulations comprising 100 transaction rounds across diverse buyer–seller profiles validate the model’s effectiveness, achieving a transaction success rate of 92.70% with an average of 6.86 bargaining rounds. These findings underscore the model’s capacity to optimize transaction outcomes, promote pricing equity, and enhance bargaining efficiency. The proposed model has broad applications in sectors such as finance, healthcare, and e-commerce, where precise data pricing mechanisms are essential to maximize transactional value.

Pricing factors of cryptocurrencies

In recent years, cryptocurrencies have become a significant element of the modern economy, attracting the attention of investors, regulators, and researchers. Despite substantial progress in understanding the factors influencing cryptocurrency pricing, many aspects remain insufficiently studied. This article provides an overview of traditional factors such as fundamental, macroeconomic, financial, behavioral, and infrastructural ones, and introduces two new groups of factors: socio-economic and market manipulators. Socioeconomic factors represent a wide range of influences determined by the state of society and the economy, significantly impacting cryptocurrency pricing. Market manipulators, on the other hand, encompass methods such as pump-and-dump schemes, insider trading, and manipulations using stablecoins, which lead to substantial price fluctuations in cryptocurrencies. The review of existing traditional factors in combination with new ones allows for a more comprehensive assessment of the dynamics of cryptocurrency pricing. The introduction of these new groups of factors underscores the need for further research to gain a fuller understanding of the pricing mechanisms in the cryptocurrency market and to develop risk management strategies. This work provides a review of existing studies and highlights gaps that require researchers’ attention.

Unlocking IPO success in Pakistan: the power of institutional quality, sponsor ownership and smart pricing

PurposeThis study investigates the variables that impact initial public offerings (IPO) initial returns witnessed in Pakistan from 1996 to 2019 using pre-listing information variables, namely country-level institutional quality, sponsor ownership and pricing mechanism. IPO oversubscription is included as a moderating variable.Design/methodology/approachThis research is motivated by the premise that the Pakistani IPO market is characterised by a broad range of institutional and regulatory frameworks. Multiple regression studies, i.e. ordinary least square (OLS) and quantile least square (QLS), were performed on 102 IPOs issued on the Pakistan stock market.FindingsThe present study findings suggest that the quality of public service, the independence of civil service from political influences and the legitimacy of government increase investors’ confidence in the prospects of companies, hence increasing the demand for IPO and initial returns. In addition, good regulatory quality enhances market transparency and lowers uncertainty, hence signalling high-quality IPOs and leading in substantial initial returns. The negative effect of the lock-up ratio on the initial return of an IPO is consistent with the risk-return trade-off theory, which asserts that the lock-up ratio indicates the quality of the IPO.Practical implicationsThe results provide market regulators, policymakers, investors and underwriters with useful data for assuring proper subscriptions of issued shares, as these variables are crucial for company transparency and market efficiency. The findings will also help investors make better IPO subscription decisions.Originality/valueThe present study explains the important influencing factors of IPO initial return in the Pakistani market.

A low-carbon driven price approach for energy transactions of multi-microgrids based on non-cooperative game model considering uncertainties

Under the requirement of improving energy utilization of the grid and the dual-carbon background, balancing the economic and environmental benefits of microgrids (MG) in the competition market has great research significance. To provide reasonable price signals for energy sharing among stakeholders, we propose a new low-carbon driven energy-sharing pricing mechanism based on supply and demand information. The mechanism can incentivize MG to actively participate in non-cooperative games for energy sharing. Specifically, on the one hand, the virtual energy sharing centre (VESC) generates price signals by analysing and integrating the supply-demand information of MG, and then releases them to each MG. On the other hand, each MG receives the latest price signals and accordingly optimizes its own operation. For each MG, a two-stage robust optimization (TSRO) model that considers the uncertainties of the source-load and aims at the economy and environmental friendliness of the MG is established. For the multi-microgrid system, a low-carbon driven energy sharing mechanism is proposed by introducing a low-carbon indicator. Finally, the alternating optimization procedure-looped CCG algorithm (AOP-Looped CCG) is adopted to solve the model effectively. The numerical examples validate that the energy complementarity is promoted and comprehensive benefits are enhanced of the proposed mechanism.

Cybersecurity Challenges in Net Energy Metering: Legal Frameworks and Practical Solutions

Net Energy Metering (NEM) has emerged as a key factor in Modern Energy Management, empowering consumers to produce their own electricity and return Net Excess Generation (NEG) to the grid. However, the increased usage of NEM has introduced significant network security challenges. As millions of electronic devices are interconnected through communication networks across critical power facilities cybersecurity has become a concerning factor, directly affecting the reliability of such extensive infrastructure. This paper gives an insight into the rising cyber offences associated with NEM systems, stipulates the legal framework, e-governance, and liabilities under the Information Technology (IT) Act, 2000. Categorization of potential cyber threats like Access control, database security and encryption, intrusion detection, malicious software, operating system vulnerabilities and security, application security has been highlighted. Evaluation of Time of Day (ToD) pricing mechanism focusing on real time monitoring and energy efficiency during peak and off-peak consumption. Incorporating Virtual Private Networks (VPNs) and other cybersecurity measures to safeguard the integrity and reliability of NEM systems. The paper illustrates the impact of cybercrimes on NEM, by exploring existing applications and case studies. It underscores the necessity of implementing robust cybersecurity practices to protect these systems. The objective of the paper is to raise awareness about the cybersecurity challenges encountered in NEM systems and to propose practical solutions to mitigate these risks, ensuring a safe and regulated environment for the functioning of smart grids in a progressively growing digital world.

Econometrics of Climate Change Research

The econometrics of climate change explores the intricate interplay between economic activity and climate dynamics, offering empirical insights into the causes, impacts, and mitigation of global climate change. This research applies advanced econometric techniques to quantify the economic consequences of environmental changes and evaluate the effectiveness of climate policies. By leveraging panel data models, time-series analysis, and causal inference methods, this study investigates critical topics such as the economic costs of extreme weather events, the efficacy of carbon pricing mechanisms, and the role of renewable energy adoption in mitigating climate risks. Additionally, this research incorporates machine learning techniques to enhance predictive accuracy in modeling future climate-economic interactions. Through rigorous empirical analysis, the study provides actionable recommendations for policymakers to design sustainable strategies that balance economic growth with climate resilience. The findings contribute to a deeper understanding of the socioeconomic dimensions of climate change, emphasizing the importance of evidence-based decision-making in addressing one of humanity’s most pressing challenges.

Synergy-based hydrogen pricing in hydrogen-integrated electric power system: Sensitivity analysis

Hydrogen price significantly impacts its potential as a viable alternative in the sustainable energy transition. This study introduces a synergy-based Hydrogen Pricing Mechanism (HPM) within an integrated framework. The HPM leverages synergy between a Renewable-Penetrated Electric Power System (RP-EPS) and a Hydrogen Energy System (HES). Utilizing the Alternating Direction Method of Multipliers (ADMM), it facilitates data exchange, quantifying integration levels and simplifying the complexities. The study assesses the HPM's operational sensitivity across various scenarios of hydrogen generation, transportation, and storage. It also evaluates the benefits of synergy-based versus stand-alone HPMs. Findings indicate that the synergy-based HPM effectively integrates infrastructure and operational improvements from both EPS and HES, leading to optimized hydrogen pricing.

Analisis Penetapan Harga Jual Beli Makanan pada Sistem Prasmanan Perspektif Prinsip Keadilan Ekonomi Islam

This study examines pricing mechanisms in the buffet system at Wisma Tamu Al Ishlah Restaurant from the perspective of Islamic economic justice principles. This research is crucial given the limited studies that analyze buffet pricing practices from an Islamic economic perspective, particularly in a pesantren (Islamic boarding school) environment. This research adopts a qualitative approach with field research methods, utilizing interviews, observations, and documentation for data collection. The findings indicate that the pricing mechanism at Al Ishlah Restaurant employs a cost-based method, setting prices based on raw material costs, capital, operational expenses, and production services, adjusted according to the types of food selected by customers. Generally, the pricing practices at Wisma Tamu Al Ishlah Restaurant align with Islamic economic justice principles, ensuring that no party is disadvantaged and upholding honesty in transactions. Prices are established through mutual agreement between the restaurant and the customer, ensuring fairness. However, price transparency presents a challenge that could affect consumer perceptions. This research contributes to the development of Islamic economic theory in the culinary business context and provides recommendations to enhance justice in buffet pricing..

Drug pricing models, no 'one-size-fits-all' approach: a systematic review and critical evaluation of pricing models in an evolving pharmaceutical landscape.

Access to new medicines is crucial for patients but increasingly sparks discussion due to high prices. Simultaneously, the growing emphasis on specialized products and uncertainty surrounding the long-term effectiveness of new drug classes brought to the market underscore the need for innovative pricing approaches. A systematic literature review of pharmaceutical pricing models, accompanied by a critical appraisal, was conducted to offer insights contributing to novel approaches balancing sustainable pharmaceutical innovation with affordability and accessibility for patients. Six different pricing models are identified: value based pricing, basic cost-based pricing, and four more comprehensive pricing models incorporating numerous elements: the cancer-drug-pricing model, AIM model, (Nuijtens) discounted cash flow, and the real-option rate of return method. Although there are many similarities among the models, each has unique assumptions for implementation. For instance, all models except for the standard incremental cost-effectiveness ratio and basic cost-based pricing consider the number of eligible patients and the remaining patent period. Only the AIM model and the Nuijtens discounted cash flow model use lump sums. Both the latter and the real-option rate of return method explicitly include the cost of capital as a major cost-based component. Recognizing the diverse applications of each model highlights the need for more differential and dynamic pricing tailored to the characteristics and therapeutic areas of each drug. Additionally, the study underscores the importance of cost transparency in achieving this goal. Consequently, these findings can help stakeholders develop sustainable and affordable drug pricing mechanisms that address the complexities of the ever-changing pharmaceutical landscape.

Pengaruh Konsep Penjualan Syariah Terhadap Minat Beli Konsumen di Toko Emas Sejati Baru Plaza Kebun Sayur Balikpapan Menurut Perspektif Ekonomi Syariah

The application of the sharia sales concept also influences consumer buying interest through the mechanism of fair pricing. The purpose of this study is to determine the effect of the sharia sales concept on consumer buying interest at Sejati Baru Jewelry Store in Plaza Kebun Sayur Balikpapan from an Islamic economic perspective. The method used in this study is descriptive quantitative. The results of this study indicate that the sharia sales variable significantly contributes to variations in consumer buying interest, with an R square value of 0.285, indicating that 28.5% of the variation in buying interest can be explained by this variable. Additionally, the F test and t test also show strong significance, with p-values well below 0.05.

Financial Impacts of Paying for Gene Therapy for Sickle Cell Disease Under Alternate Prices and Financing Mechanisms

ObjectivesThis study aims to understand the role of alternative prices and financing mechanisms on the budget impact for payers and the risks and returns of manufacturers for gene therapies. MethodsThis article uses fundamental economic principles to interpret the implications of alternative pricing mechanisms in terms of the share of value appropriated by the manufacturer and how alternative financing mechanisms alter it. It demonstrates these concepts by studying the financial impacts for a payer and the manufacturer across alternative pricing and financing mechanisms that could be used by the US Centers for Medicare and Medicaid Services to pay for gene therapy for sickle cell disease. ResultsUnlike value-based and manufacturer-set monopoly prices, an effective monopoly price can be derived to guarantee monopoly profits for manufacturers during their exclusivity period, thereby providing a high appropriation share and substantially lowering price and budget impact for a payer. For sickle cell disease gene therapy, the 10-year budget impact for the US Centers for Medicare and Medicaid Services would range from US dollar $8.6 billion to $12.8 billion under a value-based price, to $10.2 billion to $15.2 billion under a monopoly price, but reduce to $7.7 billion under an effective monopoly price. The latter price would still fetch over 50% of the total surplus to the manufacturer while mitigating their risk of sales volume. ConclusionsSignificant budget impacts for funding gene therapy are not mitigated across alternative financing mechanisms at any given price. The price determines most of the budget impact. The option of a patent buyout may help negotiate down prices to effective monopoly prices.

Cost-Effective Dynamic Alliance Pricing Mechanism Based on Distributed Edge Intelligence

Cost-Effective Dynamic Alliance Pricing Mechanism Based on Distributed Edge Intelligence

Agricultural carbon credits: A pathway to environmental sustainability

Climate change and ensuring food security for a rapidly growing global population are two of the biggest challenges in agriculture. To meet the commitments made in the Paris Climate Agreement, it is important to use effective methods for managing soil that can help sequester and stabilise carbon. Conservation agriculture has a huge potential to sequester carbon in plants and soil, making it a viable option for carbon trading despite its significant contribution to global greenhouse gas emissions. Carbon sequestration can be achieved through sustainable practices such as adopting conservation agriculture, crop rotation, cover crop cultivation, crop residue incorporation or mulching, effective management of nutrient supply to crops, and transforming towards organic agriculture and agroforestry. These practices promote food security and environmental improvement and help mitigate global warming. Carbon pricing mechanisms are policies that impose a cost on carbon pollution, encouraging people and organisations to choose low-carbon options and reduce their emissions. Agricultural producers can benefit from carbon trading by earning extra revenue by selling their excess carbon credits to those who emit higher amounts of greenhouse gases. Carbon credit systems in agriculture are still in the early stages, so farmers may have more opportunities to participate in future carbon trading.

Carbon Trading and Environmental Justice: A Juridical Examination of Fairness in Indonesia's Emissions Reduction Initiative

This paper provides a normative juridical analysis of Indonesia's carbon trading regulations, with a focus on environmental justice and fairness. It examines the legal framework established by Presidential Regulation No. 98 of 2021, which governs carbon pricing mechanisms, including carbon taxes and carbon credit trading. The analysis highlights key gaps in the regulation, particularly in terms of equitable benefit distribution and inclusion of vulnerable communities in decision-making processes. While Indonesia's carbon trading system aligns with global trends and its international obligations, significant improvements are needed to ensure that marginalized groups are not further disadvantaged. Recommendations include the redistribution of carbon trading revenues, enhanced public participation, stronger enforcement mechanisms, and alignment with international best practices.

Fair Energy Trading in Blockchain-Inspired Smart Grid: Technological Barriers and Future Trends in the Age of Electric Vehicles

The global electricity demand from electric vehicles (EVs) increased by 3631% over the last decade, from 2600 gigawatt hours (GWh) in 2013 to 97,000 GWh in 2023. The global electricity demand from EVs will rise to 710,000 GWh by 2030. These EVs will depend on smart grids (SGs) for their charging requirements. Like EVs, SGs are a booming market. In 2021, SG technologies were valued at USD 43.1 billion and are projected to reach USD 103.4 billion by 2026. As EVs become more prevalent, they introduce additional complexity to the SG landscape, with EVs not only consuming energy, but also potentially supplying it back to the grid through vehicle-to-grid (V2G) technologies. The entry of numerous independent sellers and buyers, including EV owners, into the market will lead to intense competition, resulting in rapid fluctuations in electricity prices and constant energy transactions to maximize profit for both buyers and sellers. Blockchain technology will play a crucial role in securing data publishing and transactions in this evolving scenario, ensuring transparent and efficient interactions between EVs and the grid. This survey paper explores key research challenges from an engineering design perspective of SG operation, such as the potential for voltage instability due to the integration of numerous EVs and distributed microgrids with fluctuating generation capacities and load demands. This paper also delves into the need for a synergistic balance to optimize the energy supply and demand equation. Additionally, it discusses policies and incentives that may be enforced by national electricity carriers to maintain grid reliability and manage the influx of EVs. Furthermore, this paper addresses emerging issues of SG technology providing primary charging infrastructure for EVs, such as incentivizing green energy, the technical difficulties in integrating diverse hetero-microgrids based on HVAC and HVDC technologies, challenges related to the speed of energy transaction processing during fluctuating prices, and vulnerabilities concerning cyber-attacks on blockchain-based SG architectures. Finally, future trends are discussed, including the impact of increased EV penetration on SGs, advancements in V2G technologies, load-shaping techniques, dynamic pricing mechanisms, and AI-based stability enhancement measures in the context of widespread SG adoption.