Reasonable Price Research Articles

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.

A novel decision-making agent-based multi-objective automobile insurance pricing algorithm with insurers and customers satisfaction

Automobile insurance is essential for customers to obtain an appropriate automobile insurance policy and plays a significant role in the insurance industry. However, pricing a reasonable automobile insurance policy for different customers requires considering several indicators, such as the number of historical accidents, the frequency of long-distance driving, and the mileage driven per month. Therefore, how to make a reasonable automobile insurance pricing policy according to the needs of different customers is an urgent issue. Existing pricing methods often face the challenges of inefficiencies and mispricing, making it difficult to satisfy both insurers and customers. To better address this problem, this paper proposes a decision-making agent-based multi-objective automobile insurance pricing (DMA-MoAIP) algorithm. The DMA-MoAIP algorithm provides a diverse set of pricing strategies that meet various requirements, and considers the satisfaction of both insurers and customers. Firstly, a decision-making agent (DMA) framework is proposed for insurers, which provides an accurate assessment of the risk level for each customer. Secondly, a data-driven scoring (DDS) mechanism is established to better measure the satisfaction of insurers and customers and form a score that corresponds to their satisfaction. Thirdly, a novel multi-objective particle swarm optimization (MoPSO) algorithm is designed to search for effective and diverse solutions in dealing with automobile insurance pricing problem. Experimental results show that DMA-MoAIP outperforms five state-of-the-art multi-objective algorithms (including NSGA-II and so on) in terms of convergence and solution diversity. Specifically, the solution diversity of DMA- MoAIP in automotive pricing has increased by an average of 17%, which can provide more pricing options to meet different customer needs. In practical applications, DMA-MoAIP provides three distinct pricing strategies: insurer-oriented, customer-oriented, and compromise pricing. These strategies underscore the importance of considering relevant driving behavior metrics, rendering them valuable for real-life applications.

Do Farm Service Centers Improve Technical Efficiency of Chickpea Growers in Karak District, Khyber Pakhtunkhwa – Pakistan

The central theme of this research endeavor was to assess the impact of Farm Service Centers (FSCs) on the technical efficiency of chickpea growers in District Karak, Khyber Pakhtunkhwa. Data were collected from chickpea growers, including both members and non-members of FSCs. Primary data were gathered from 120 chickpea growers in three villages of Karak district namely Meerzal Banda, Alam Gulkhel Banda, and Zariwaal Banda by using a multistage stratified random sampling technique. A Stochastic Frontier production function was applied to estimate technical efficiency. The results of the Stochastic Frontier Model indicated that most variables were statistically significant. The mean technical efficiency was calculated at 80%, suggesting that chickpea growers could improve their production by 17%. It is recommended that farmers may be supported with new technologies and essential inputs by the government, as these were significant contributors. Furthermore, Farm Service Centers should enhance their services and provide basic inputs at reasonable prices.

Development of optimal participating strategy for source‐grid‐load‐storage integrated projects in electricity markets with multi‐stage joint optimization

AbstractTo promote peer‐to‐peer trading in a distribution system with the franchise owned by the concerned distribution company respected, a so‐called “source‐grid‐load‐storage” (SGLS) integrated project is promoted in China. Given this background, this paper proposes a multi‐stage joint optimization model to optimize the participating strategy for SGLS‐IPs in electricity energy and ancillary service markets. A multi‐energy flow park model is presented with electricity, gas, and heat included. A two‐stage model for optimal participating strategy of SGLS‐IPs in electricity and ancillary service markets is then presented. Through scenario analysis of a sample system, the attained revenue of an SGLS‐IP in different markets is evaluated. Additionally, a bilevel Stackelberg game model is introduced for internal electric vehicle clusters (EVCs) within an SGLS‐IP, with the upper level representing an SGLS‐IP, and the lower level representing EV users engaging in the game. The effectiveness of the model is validated through case studies. Simulation results demonstrate that reasonable market participation and pricing strategies contribute to the efficient allocation of resources within a SGLS‐IP and a win‐win outcome for both the SGLS‐IP entity and EV users.

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.

A donor-acceptor conjugated bipolar polymer with multielectron redox sites for long-cycle-life and high-rate aqueous zinc dual-ion batteries

Aqueous zinc-ion batteries (AZIBs) have hugely latent advantages in large-scale energy storage due to its innate safety, reasonable price, and sustainability. However, most AZIB cathode materials suffer from short cycling life and poor rate performance. Herein, a bipolar donor-acceptor (D-A) conjugated microporous polymer (PTZ-BDTB), consisting of electron-withdrawing benzo[1,2-b:4,5-b’]dithiophene-4,8-dione (BDTB) units and electron-donating phenothiazine (PTZ) units, is developed as the cathode material of aqueous zinc dual-ion batteries (AZDIBs). The D-A type structure design could reduce the band gap, thus promoting electron transfer in the polymer framework. Therefore, the PTZ-BDTB cathode in a 30 mol/kg (m) ZnCl2 water-in-salt electrolyte exhibits a high reversible capacity of 202 mA h g−1 at 0.05 A g−1 with excellent rate performance (109 mA h g−1 at 15 A g−1), which is far superior to its counterpart polymers PPTZ and PB-BDTB. Impressively, PTZ-BDTB shows ultra-stable cycle performance with capacity retention ratios of 76.2% after 460 cycles at 0.05 A g−1 and 96% after 27000 cycles at 5 A g−1. PTZ-BDTB also exhibits a low self-discharge ability with capacity retention about 76.4% after resting the battery for 28 days. These results demonstrate that D-A type structural design is a promising strategy for constructing high performance cathode materials for AZDIBs.

Application of Linear Programming in Automatic Pricing and Replenishment Strategies for Vegetable Commodities

Vegetable commodities are indispensable parts of the current consumer market. Vegetables possess different characteristics such as seasonality, perishability and so on. Thus, it is critical to formulate reasonable automatic pricing and replenishment strategies for vegetable commodities. However, previous kinds of literature have either ignored some of the attributes of vegetables or restricted their application regions to some specific situations. This review compares the pros and cons of diverse linear programming methods and models in previous research, synthesizes the core method, and finally concludes with two relatively reasonable algorithms for pricing and replenishment strategies. It also gives an evaluation of these two algorithms and proposes suggestions for improvement. The purpose of this review is to provide guidelines for subsequent research to optimize existing methods and models to work out more objective and accurate optimal strategies. Ultimately, vegetable sales and supply can better meet the market demand, which can help rejuvenate economic vitality and bring in higher profits at the same time.

Vegetable Pricing and Replenishment Strategy Based on Multivariate Polynomial Regression and SARIMA Model

Fresh products are one of the important parts of the profitability of superstores, and it is very important for merchants to make effective replenishment and pricing suggestions based on historical data. In order to give a reasonable vegetable pricing and replenishment plan, this paper processes the data and then uses multivariate polynomial regression to regress the sales volume and cost-plus pricing of the category, to obtain the relationship between the sales volume of the category and the cost-plus pricing; and combines with the SARIMA model to further give the recommended replenishment quantity; considering the impact of vegetable freshness on pricing, a freshness-based pricing model is proposed, and the optimal pricing and optimal restocking quantity formula, and proved its correctness in principle. In this study, the pricing and replenishment strategies of reference vegetables are given, and future research can further explore the market forecast of other agricultural products on this basis to broaden the application scope of this model.

The Critical Success Factors Towards Homestay Development in Penang

Since its introduction in 1988, the Homestay Programme in Malaysia has become an iconic rural tourism product. Tourists pay a reasonable price to stay with a host family and experience daily life alongside the local community. The pandemic outbreak in February 2020 severely impacted the tourism industry, causing many homestays to cease operations. In the post-pandemic period, the tourism industry, including homestays, is striving to regain momentum. Studies have been conducted to identify critical success factors influencing homestays' success. This study focuses on identifying these factors for homestays in Penang, Malaysia, considering perspectives from tourists, government agencies, institutions, industry players, and the community. A semi-structured interview and thematic analysis were used to process data collected from eleven informants with varying levels of involvement in homestays, ranging from those directly engaged in their development to those with little or no experience in visiting them. The interviews were conducted mainly in Bahasa Melayu, with the input translated into English. The data was then classified into several themes for further discussion.

Generalized multi-manufacturer multi-retailer production-delivery supply chain model and its minimum cost solution policy

Production of a product at multiple sources and its deliveries to multiple destinations are a common practice in business. Minimization of the integrated total cost of performing operations and transportation considering the relevant factors such as the minimum order quantity contract, capacities of transport vehicles, and times of transportation in this supply chain is essential, in supplying products to customers at reasonable lesser prices. However, such a supply chain has received little attention in terms of minimizing the integrated total cost taking into account these related factors explicitly. So, there lies a research scope on this topic to fulfill the growing need of minimizing the cost of production-deliveries of products to meet customers’ demands fruitfully. Here we develop such a generalized mathematical model to minimize the integrated total cost of carrying out operations at manufacturers and retailers, and transporting batches (sub-lots) of lots from sources to destinations considering the mentioned realistic constraints. The integrated production-delivery flow is synchronized by delivering lots with batches of equal and/or unequal sizes. First without considering transportation costs, we obtain optimal batches to minimize the total cost of the model. Each of these optimal batches is proportionally distributed at manufacturers as supplies and at retailers as demands. Then the minimum transportation cost solution from manufacturers to retailers is incorporated to the earlier solution to obtain the final result. We illustrate this solution policy with numerical example problems. Sensitivity analyses are performed to see the effect of increasing values of parameters on the minimum total cost.

Pricing and Replenishment Decision System Based on LSTM

Fresh supermarket vegetables have a very short shelf life, and the quality of vegetables will also be affected by the storage time. If most of the goods are not sold on that day, they will not be sold on the next day. From the demand side, the sales volume of vegetables is related to the supply side of vegetables from April to October. At the same time, the sales space of the supermarket is limited, which makes a reasonable sales portfolio extremely important. The commercial overpricing replenishment decision system based on LSTM analyzes the relationship between daily sales volume and cost-plus pricing for each vegetable category and single product over three years. It predicts the sales volume and wholesale price of each category for the next week, determining replenishment volume and pricing strategy based on forecasted sales volume and average loss rate. The system considers limited sales space and uses the entropy method to calculate weights for key indicators like total profit. It employs the TOPSIS method to sort items, considering forecasted wholesale prices, to select items for pricing decisions. The system aims to maximize total profit while ensuring the supermarket meets minimum display conditions. By assisting supermarkets in formulating more reasonable pricing strategies, it aims to reduce overstock, backlog, or stock shortages, ultimately improving sales volume and operational efficiency.

Physical information-guided multidirectional gated recurrent unit network fusing attention to solve the Black-Scholes equation

Reasonable option pricing is crucial in the financial derivatives market. Finding analytical solutions for the Black-Scholes (BS) equation, particularly for American options or with fluctuating volatility and interest rates, is challenging. BS equations exhibit strong time-series characteristics, with asset prices typically adhering to geometric Brownian motion. To address the BS equations, we propose a sequence-to-sequence model guided by physical information (PI), called PiMGA. The PiMGA fuses a multidirectional gated recurrent unit (GRU) network with an attention module, where multidirectional GRU enhances the coding performance of the input sequences and the attention module balances the feature weights of the hidden variables. Prior physical knowledge in BS equations is jointly used as a constraint, forming the penalty function for objective optimization. This allows PiMGA to serve as an efficient approximation function in the learning paradigm of physically informed machine learning to solve BS equations. BS equations with various complexities illustrate the accuracy and feasibility of PiMGA for numerical solutions. Furthermore, the out-of-distribution generalization ability of PiMGA is verified by predicting the Nasdaq 100 index.

Cost-effectiveness of finerenone added to standard of care for patients with type 2 diabetes-related chronic kidney disease in the United States.

To examine the cost-effectiveness of adding finerenone to standard of care (SoC) for treating type 2 diabetes mellitus (T2DM)-related chronic kidney disease (CKD) in the United States. Based on the clinical data analysed by FIDELITY, we referenced the validated FINE-CKD model (Markov model) to evaluate the cost-effectiveness of SoC versus SoC + finerenone from the perspective of US payers. The model was cycled for 35 years in 4-month cycles, with cost and utility values derived from the published literature. The primary outcomes were incremental cost-effectiveness ratio (ICER) and quality-adjusted life years (QALYs). Deterministic and probabilistic sensitivity analyses were conducted to assess the robustness of the base-case results. The treatment strategy of finerenone plus SoC led to gains of 6.95 QALYs and had a lifetime cost of $491 745.31. Compared to SoC, that strategy yielded 0.48 more QALYs at an added cost of $65 305.72. The ICER for finerenone was $135 257.06 per QALY, which is below the willingness-to-pay threshold of United States ($150 000/QALY). The results were sensitive to the hazard ratios associated with the efficacy of finerenone and its cost. Probabilistic sensitivity analyses showed that the probability that finerenone plus SoC would be cost-effective was 57.6%. For patients with T2DM-related CKD, adding finerenone to SoC may be a cost-effective option in the United States. Reasonable price reductions for finerenone could potentially benefit more patients.

John R. Commons’s Two-Layered Theory of Reasonable Value

: Broadly speaking, John R. Commons’s theory of reasonable values has been interpreted as either a theory of reasonable prices or reasonable process of policy formation. Comparing newly discovered manuscripts written in 1928–1929 with Institutional Economics, this study shows that Commons’s theory of reasonable value has a two-layered structure consisting of the theory of reasonable price and the theory of reasonable process of policy formation. The essential meaning of reasonableness in the first layer is investigating all facts and giving due weight to each, whereas in the second layer is the voluntary transformation of understandings, leading to the conciliation of conflicting interests through deliberation. In this regard, his theory of reasonable value is related to debates on reasonableness and deliberative democracy in contemporary political philosophy. Then, using the analytical concepts of contemporary political philosophy, this study explains the necessity of a two-layered structure for his theory of reasonable value by clarifying where the two layers overlap and differ.

Research on the Development Strategy of Cultural and Creative Products of Libraries from the Perspective of Consumer Behavior

ABSTRACTIn recent years, there has been a notable trend and exemplary practice among libraries in effectively developing cultural and creative products. This endeavor not only foster the creative transformation and innovative development of culture, but also meets the escalating demand for high‐quality cultural consumption. Focusing on the consumption behavior of library culture and creative products in China, underscores the critical consideration for libraries, including the evolution of the consumption themes, addressing the symbolic consumption demands, creating new consumption scenarios, enhancing product quality, and augmenting consumer service awareness. Our findings highlight the importance of product diversity and aesthetic appeal, the fulfillment of commemorative value and social value, and the balancing of emotional and cognitive satisfaction in consumer demand. Moreover, the effective integration of both online and offline channels and leveraging the influence of Key Opinion Leader (KOL) are recommended marketing strategies. Regarding pricing, consumers are sensitive to price, preferring products of high quality and originality within reasonable price ranges. Finally, the study highlights the significance of enhancing the overall purchase experience and service quality, which significantly influence subsequent consumption behavior.

Design and Implementation of Home Industrial-Based Automatic Granulated Food Weighing Machine

Automation activities are now required in manufacturing processes. This process can provide very effective and efficient performance results, particularly for industrial processes that require a specific standard, such as those used in the granulated food product industry, such as sugar, rice, coffee, and other products. Fast, sanitary packaging processes and standard weights are the main focus of the manufacturing process. This is not a significant barrier at the level of an established industry, whereas, in traditional processes, this is still the main impediment since automated weighing systems at reasonable prices are still challenging to come by in small and medium-sized businesses. This study proposes the development of a prototype weighing mode that can maintain the weight accuracy of powder materials (sugar, rice, and coffee) before they are placed in product packaging. The research employed the experimental method, utilizing a load cell sensor and a screw conveyor to precisely measure the weight of powder raw materials based on the user-specified size and parameters. It is also equipped with a data deviation memory. Some testing was conducted to ensure the accuracy of the prototype. Based on the test results, this system can work with an accuracy rate of 99.693% at parameters 120 grams and 99.677% when testing the weight of powder raw materials of 120 grams, 125 grams, and 175 grams, respectively.

A novel coating layer of mesoporous silica on LiNi0.8Co0.1Mn0.1O2 (NCM811) cathode material for advanced lithium-ion batteries

NCM811 cathode material has many commercial features such as reasonable price, environmental friendliness and high specific capacity, yet it suffers from capacity attenuation during cycling. Silica (SiO2) coating strategy is a valid approach to enhance the capacity retention of NCM811. However, the insulating nature of coating layer reduces the electrochemical performance. Herein, a novel route is developed to alleviate this issue by using a mesoporous layer instead of bulk layer. The mesoporous layer is prepared by condensing a mixture of fine templates (Cetyltrimethylammonium bromide, CTAB) and tetraethyl orthosilicate (TEOS) on NCM811 particles and calcining them to remove templates. The structure, morphology, surface chemical state and electrochemical performance of samples are widely investigated. Results indicate that the mesoporous layer (SiO2–20 wt.% of CTAB) exhibits discharge capacities of 210 and 138 mAh g−1 at 0.1 C and 5C over 2.7–4.3 V, while those of bulk SiO2 coated sample are only 189 and 98 mAh g−1, respectively. This mesoporous layer offers a capacity maintenance of 87.3 % after 100 cycles, compared to only 69.3 % for pure NCM811 at 1 C. The mesoporous layer not only improves the discharge capacity of NCM811 but also reduces its capacity fading.

Sensor Fusion-Based Pulsed Controller for Low Power Solar-Charged Batteries with Experimental Tests: NiMH Battery as a Case Study

Solar energy is considered the major source of clean and ubiquitous renewable energy available on various scales in electric grids. In addition, solar energy is harnessed in various electronic devices to charge the batteries and power electronic equipment. Due to its ubiquitous nature, the corresponding market for solar-charged small-scale batteries is growing fast. The most important part to make the technology feasible is a portable battery charger and the associated controllers to automate battery charging. The charger should consider the case of charging to be convenient for the user and minimize battery degradation. However, the issue of slow charging and premature battery life loss plagues current industry standards or innovative battery technologies. In this paper, a new pulse charging technique is proposed that obviates battery deterioration and minimizes the overall charging loss. The solar-powered battery charger is prototyped and executed as a practical, versatile, and compact photovoltaic charge controller at cut rates. With the aid of sensor fusion, the charge controller is disconnected and reconnects the battery during battery overcharging and deep discharging conditions using sensors with relays. The laboratory model is tested using a less expensive PV panel, battery, and digital signal processor (DSP) controller. The charging behavior of the solar-powered PWM charge controller is studied compared with that of the constant voltage–constant current (CV–CC) method. The proposed method is pertinent for minimizing energy issues in impoverished places at a reasonable price.

The Effect of Product Quality, Price and Sales Location of Nugin Lamping Tofu on Consumer Satisfaction

Tofu lanting nuggets are one type of snack food that is very popular with the public. Along with increasing consumer awareness of product quality, competition in the lanting tofu market is getting tougher. The focus of the study aims to determine the extent to which "the influence of product quality, price and sales location of Tahu Lamping Nugin" plays a role in influencing the level of customer satisfaction. This research was conducted using quantitative as a research method. Meanwhile, data collection was carried out involving questionnaire surveys and other literature studies. After the data was collected, it was analyzed using the regression test using SPSS software. The conclusion from the results of the research analysis shows that product quality, price and sales location of Lamping Nugin Tahu have an effect on customer satisfaction. In an effort to achieve an optimal level of customer satisfaction, companies need to focus on maintaining and improving product quality and determining prices that remain balanced with the value offered. Meanwhile, the sales location is still important to attract consumer interest, but this needs to be balanced by offering products of good quality and reasonable prices.

The Influence Of Facilities And Prices On Tourist Satisfaction At Pantjoran PIK, North Jakarta

This study investigates the influence of facilities and prices on tourist satisfaction at Pantjoran PIK, North Jakarta. The research employed a quantitative approach with 115 respondents who had visited the destination. Using multiple linear regression analysis, the results show that both facilities and prices have a significant and positive effect on tourist satisfaction. Specifically, well-maintained facilities, such as cleanliness, parking availability, and comfort, enhance the overall experience of visitors. Similarly, reasonable prices that align with the quality of services provided also contribute to higher satisfaction levels. The findings suggest that improving facilities and maintaining competitive pricing can lead to increased tourist satisfaction and loyalty. Future research may explore additional factors influencing visitor satisfaction.