Market Demand Analysis Research Articles

Enhancing Business Operations through Strategic Warehouse Location: Methodologies and Implications for Supply Chain Efficiency

For supply chain management to be efficient and productive, a warehouse's ideal location is essential. Here are 10 crucial ideas for a warehouse's introduction and ideal location. The cost and efficiency of product distribution are strongly influenced by the location of a warehouse. A well-placed warehouse speeds up deliveries, improving customer satisfaction. A crucial factor is proximity to transportation networks including highways, railroads, and ports. The availability of transportation infrastructure and access to a skilled labour pool are important considerations. To choose acceptable sites, market demand and client distribution patterns should be examined. The placement of the warehouse should support corporate objectives like cost containment and operational effectiveness Geographical elements such as climate, natural calamities, and local laws should be considered. A centralised position allows for efficient routing and lower transportation expenses. To serve various markets and improve inventory management, several warehouses may be needed. Warehouse location analysis may be performed using cutting-edge technology like geographic information systems (GIS).These bullet points offer a succinct summary of the significance and factors to be taken into account when choosing the best location for a warehouse. The effectiveness of the supply chain and customer satisfaction are directly impacted by the best warehouse location. Proximity to transportation networks and access to skilled labour are crucial factors. Finding ideal sites benefits from analysis of consumer distribution patterns and market demand. It is important to evaluate geographic elements including the climate, laws, and natural catastrophes. Advanced technology and centralised sites can improve routing while lowering costs and optimising inventory control Studying the best place for a warehouse has research implications since it may enhance supply chain management and commercial operations. The importance of the research is highlighted by the following 5 points. Cost cutting Finding the best place for a warehouse may result in savings on labour, transportation, and inventory management, which can boost profitability. Customer satisfaction: Quicker delivery times, improved customer satisfaction, and increased customer loyalty can all contribute to corporate success. Competitive edge: Choosing the best warehouse site might provide you an advantage over rivals by enabling quicker responses to market needs and more effective distribution. Sustainability and environmental impact: Investigating the best warehouse sites may help you make decisions that are good for the environment by lowering transportation costs and emissions, boosting sustainability, and decreasing your ecological imprint. Making strategic choices: Businesses may better align their operations with long-term development objectives by understanding the impact of warehouse location before making choices about distribution centre expansion, consolidation, or the creation of new facilities. Research into the best spot for a warehouse is important overall because it may increase operational effectiveness, cost savings, customer happiness, and sustainable business practices—all of which are necessary for success in a cutthroat market. The following phases are often included in the technique for locating a warehouse in the best possible location:data gathering Obtain pertinent information on market demographics, customer distribution patterns, transportation systems, labour availability, and location-specific costsSite-selection standards: Define the criteria in accordance with the particular requirements of the company, such as closeness to suppliers, consumers, transportation systems, and labour markets. Depending on each criterion's proportional value, give it a weight. Geographic analysis: Use geographic information systems (GIS) to visualise aspects like traffic patterns, population density, and competitor locations while analysing spatial data. To find suitable warehouse locations that match the given requirements, do a geographical analysis. Analyse the costs connected with each prospective site, including the purchase of land or buildings, the price of construction or refurbishment, taxes, utilities, labour, and transportation. Think of long-term elements like scalability and possible growth. Risk assessment: Examine possible hazards and vulnerabilities related to each place, including weather-related catastrophes, political stability, regulatory restrictions, and regulatory restraints. Assess the effects on operations and put risk-reduction plans in place. Decision-making: Compare and order the prospective warehouse sites based on the data that has been gathered, the analysis, and the cost factors. Choose the greatest location for your company, taking into account aspects like cost-effectiveness, market reach, and operational efficiency. Warehouse A, Warehouse B, Warehouse C, Warehouse D. Stock holding capacity (unit) {SHC}, Movement flexibility, Average distance to shops (km), Average distance to main suppliers (km), Unit price {UP} shows the rank of Alternatives Warehouse A, Warehouse B Warehouse C, Warehouse D. In order to achieve supply chain efficiency, customer happiness, and overall business success, a warehouse's ideal location is essential. Businesses may choose the best location for their warehouse operations using a structured technique that includes data collecting, analysis, and decision-making.

Linear Programming and Product Mix of Paint Manufacturing Firms in Port Harcourt

This study examined the relationship between linear programming and product mix of paint manufacturing firms in Port Harcourt. This study adopted a correlational survey research design. The population of the study was 10 selected paint manufacturing firms in Port Harcourt as retrieved from Nigerian business directory (2024). 3 managers were selected from each firm multiplied by 10 firms gives us a total of 30 respondents. Structured questionnaire was used in data collection. The result of the Cronbach's Alpha reliability test indicates .804 which is above .70 which implies that the items are reliable. Pearson product moment correlation was used to test the hypotheses using SPSS (statistical package social sciences). The study revealed that there is a significant relationship between Ellipsoid Linear Programming and Product Mix of paint manufacturing firms in Port Harcourt. There is a significant relationship between Graphical method Linear Programming and Product Mix of paint manufacturing firms in Port Harcourt. There is a significant relationship between Simplex Linear Programming and Product Mix of paint manufacturing firms in Port Harcourt. In conclusion, Linear programming is a powerful mathematical tool that can be effectively utilized by paint manufacturing firms in Port Harcourt to optimize their product mix and maximize profits. The paint manufacturing firms should conduct a thorough analysis of market demand for different types of paint products to identify profitable opportunities for product mix optimization.

A Comprehensive Analysis of Supply Chain Collaboration, Technological Upgrading, and Market Demand as a Framework for Increasing Competitiveness

A Comprehensive Analysis of Supply Chain Collaboration, Technological Upgrading, and Market Demand as a Framework for Increasing Competitiveness

Thinking and Exploration of the Organic Connection between Market Demand and Talent Training of Medical Laboratory Technology Specialty

Background: To explore the reasonable orientation of talent training for medical laboratory technology (MLT) at the vocational undergraduate level, this study has conducted a thorough survey and analysis of the talent market demand in multiple aspects, including the total MLT talent market demand, talent demand changes and expectations, and changes in industry development. Methods: Based on a literature search, this study collected statistics on the number of MLT professionals in China over the past decade. Questionnaires were distributed to 128 employers in 14 provinces nationwide. A survey was conducted on the overall industry development and the requirements of enterprises for the abilities of talent on the market, and 26 doctors and nurses with senior technical titles were interviewed. Another survey was carried out among 17 higher vocational colleges and 8 general undergraduate universities nationwide, focusing on vocational abilities that are highly regarded by teachers. Results: As reflected by the results of this study, the market requires a higher level of educational background for talent, and self-directed learning ability is rated as the most essential vocational ability by enterprises. Moreover, the ability to use information technology and the communication and expression ability are necessary personal abilities in the opinion of enterprises. However, the vocational abilities specially developed by teachers are not always the same as those required by enterprises. The results of this study show that the latest progress of information technology in the industry must be integrated into talent training, and priority should be given to developing innovation ability, self-directed learning ability and interpersonal communication ability to develop talent that precisely meets market demand. Conclusion: Based on a thorough survey and analysis of market demand, this study recommends upgrading traditional teaching thought, focusing on specific market demand, accurately determining talent training and ensuring that talent can better meet market demand.

The Use of Big Data Analysis in Digital Empowerment of Sustainable Technological Innovation Management of Ecological Enterprises.

With the social economy's rapid progress and the popularization of environmental awareness, ecological enterprises have gradually become a crucial trend in the development of modern enterprises. This work intends to promote the development of ecological enterprises to a higher level. This work first analyzes the management mode of ecological enterprises in the context of big data in China. Then, it establishes various indicators to analyze the role of sustainable technological innovation in enterprise development and the impact of digital empowerment on enterprise development. Finally, this work takes China's manufacturing industry and ecological enterprises in Hubei Province as examples to summarize the digital empowerment of sustainable technological innovation management of ecological enterprises under the background of big data. The final result indicates that sustainable technological innovation significantly reduces ecological enterprises' resource consumption and waste emissions. Additionally, it has a significant positive effect on improving enterprise output value and economic benefits. The digital empowerment of enterprises has a significant driving effect on sustainable technological innovation, with a digital driving coefficient of 26. This work provides a feasible scheme for the specific application of big data analysis in the technology innovation management of ecological enterprises, including market demand analysis, environmental monitoring and governance, technology assessment and risk management. This work expounds the role of big data analysis technology in improving decision-making efficiency, optimizing resource allocation and enhancing the competitiveness of enterprises in the digital empowerment of ecological enterprises.

Automated Pricing and Replenishment Decisions for Vegetable Products Based on Data Analysis

This study delves into the critical factors for the successful operation of vegetable products supermarkets: efficient inventory management and accurate market demand analysis. Given the perishability of vegetables, their variety, and the complexity of supply chains, a linear regression model and the method of least squares have been developed to estimate model parameters. Additionally, the ARIMA model is utilized to forecast the unit prices of commodities. In a more comprehensive approach, considering various influencing factors, a combinatorial optimization algorithm (integrating linear regression and greedy algorithm) is employed to determine the optimal replenishment strategy. Based on this, the study forecasts the sales volume and unit prices for various categories over the next seven days, and accordingly, establishes the pricing strategy and predicted replenishment volume for each category. The research underscores the necessity for retailers to precisely analyze sales data and market trends, optimize supply chain management, and formulate effective pricing strategies to cope with seasonal variations and limited sales space. These measures are essential to satisfy consumer demand and enhance profitability.

Automated pricing and replenishment strategies for vegetable products based on SVR and simulated annealing

In fresh supermarkets, the shelf life of general vegetable products is relatively short, and the quality deteriorates with the increase of sales time, and most varieties cannot be sold the next day if they are not sold on the same day. However, due to the fact that the vegetables sold by fresh supermarkets often have a wide variety and different origins, merchants need to make replenishment decisions for each vegetable category on the same day without accurately judging the specific single product and purchase price, and the reliability of market demand analysis is very important for supermarkets to make correct replenishment and pricing decisions. Based on the relevant data of sales details and wholesale prices of six vegetable commodities operated by a supermarket from 2020 to 2023, this paper uses Fourier series and Gaussian function to predict the sales volume of vegetable single products, clarifies the relationship between supermarket revenue and the pricing and replenishment quantity of vegetable products based on multiple linear regression theory, and establishes a pricing strategy model based on simulated annealing algorithm and SVR. On the premise of trying to meet the market's demand for various categories of vegetable products, the supermarket will make the maximum profit, so as to help the supermarket further formulate the pricing and replenishment plan of a single product.

Genetic Algorithms Application for Pricing Optimization in Commodity Markets

The perishable nature of vegetable commodities poses challenges for superstores, as reselling them is often unfeasible due to their short freshness period. Reliable market demand analysis is crucial for boosting revenue. This study simplifies the pricing and replenishment decision-making process by making reasonable assumptions about the selling time, wastage rate, and replenishment time for vegetable commodities. A single-objective planning model with the objective of profit maximization was constructed by fitting historical data using the nonparametric method of support vector regression (SVR). The study reveals a specific relationship between sales volume and cost-plus pricing for each category and predicts future cost changes using an LSTM model. Combining these findings, we substitute the relationship between sales volume and pricing as well as the LSTM prediction data into the model, and solve it using genetic algorithms in machine learning to derive the optimal replenishment volume and pricing strategy. Practical results show that the method can provide reasonable pricing and replenishment strategies for vegetable superstores, and after careful accounting, we arrive at an expected profit of RMB 22,703.14. The actual profit of the supermarket was RMB 19,732.89. The method, therefore, increases the profit of the vegetable superstore by 13.08%. By optimizing inventory management and pricing decisions, the superstore can better meet the challenges of vegetable commodities and achieve sustainable development.

Imperatives and determinants of forming the behavior of agro-traders

In today's dynamic environment, agritraders confront a myriad of intricate challenges and opportunities. Their role necessitates a constant analysis of market trends, supply, and demand, coupled with the ability to engage with diverse stakeholder groups effectively. The behavior of agricultural traders is shaped by a complex interplay of objective and subjective factors, demanding a comprehensive understanding from the perspectives of socio-economic psychology and management practice. In this light, scientific research on the imperatives and determinants of agro-traders' behavior formation assumes paramount importance. This article endeavors to delve into the main factors influencing agro-traders' decision-making, their strategies of action, and their interactions with partners in the agrarian sector. The agricultural sector is essential to the Ukrainian economy, forming up to 20% of the gross domestic product. According to data as of the end of 2021, agribusiness accounted for almost 40% of the country's foreign exchange earnings and had positive development dynamics over the past five years. Ukraine is one of the world's largest grain exporters, producing about 100 million tons annually. Despite the achievements, the agricultural sector faces numerous problems, such as: instability of markets and fluctuations in product prices, difficulties in ensuring effective risk management, high competition on international markets, instability of the economic situation in the country and its impact on the financial support of agriculture, high dependence on climatic conditions and natural disasters, instability of the legislative environment and administrative procedures. For agricultural traders to effectively function in the modern market environment, it is necessary to carefully study and analyze the imperatives and determinants of their behavior, which is the subject of this article. Keywords: agribusiness, agrotrading, risk, development, agrotrading behavior.

Research on supermarket replenishment volume prediction based on LSTM and PSO algorithm

In order to meet people's health needs and reduce economic losses, the new fresh suppliers carried out real, reliable and targeted market demand analysis so that they formulate automatic pricing and replenishment decision of vegetable commodities with the aim of providing fresh and nutritious vegetable commodities. This paper adopts the apriori model to explore the correlation between vegetables and reflects the relationship between total sales and cost plus pricing by the linear fitting method.This paper further uses the LSTM time series prediction model, time sliding sequence and PSO particle swarm algorithm to predict the various vegetable categories of daily supplement and pricing in the next week, so as to maximize the business super profit. The results showed that the price of each vegetable category had a significant negative correlation with the sales volume and the dynamic prediction of replenishment quantity and pricing data had obvious application effect, which effectively helped the supermarket to make pricing and replenishment decisions.

Research on supermarket pricing strategy based on deep learning and optimization model

To carry out reliable market demand analysis and improve the profit of supermarkets, this paper studied the automatic pricing and replenishment decision-making problem of vegetable products in fresh supermarkets. Firstly, the time series-LSTM prediction model is established. Secondly, the parameters of the Adam optimization algorithm and LSTM model are adjusted by grid search, Through the trained model, the daily sales volume, wholesale price, and sales price of each category in the next week are predicted. Finally, the pricing strategy of the total daily replenishment of each vegetable category in the next week is calculated.

Towards Enterprise Business Management Strategy Based on Big Data Technique

A growing number of commercial economic activities are blooming with continuous economic development of China. Therefore, to improve the effectiveness of commercial economic activities, all aspects must be analyzed and managed to ensure that economic decisions are made scientifically and rationally. With the advent of the information era, competition in the market is intensively happened. Big data has substantially boosted the value of technological systems used in commercial and economic administration. In addition to extracting significant information from big data, it also enables analysis and forecasting of market supply and demand as well as current economic trends, helping companies make decisions about their business and economic management strategies. In the digital era, the emerging technologies represented by big data have been seamlessly integrated into Chinese societal and personal realms, playing an increasingly vital role in enhancing productivity and quality of life. As a consequence, big data systems have also shown greater application value in the business and economic management activities, becoming a key technology that is actively developed and utilised by major companies. It can not only improve the efficiency of data processing and economic management benefits, but also provide reference evidence for enterprise leadership to implement decisions, thereby continuously improving the modern commercial economic management mechanism and enhancing the market competitiveness of enterprises.

INNOVATIVE MARKETING IN MARKETING MANAGEMENT SYSTEM OF ENTERPRISES: REASONS AND KEY VECTORS OF DEVELOPMENT

The article considers the issues of terminology, essence and meaning of the concept of “innovative marketing” from the historical and practical points of view, characterizes the main vectors of development and trends in Ukraine. The purpose of the article is to clarify the content and identify the characteristic features of innovative marketing in the marketing management system of enterprises at the current stage, structuring the elements of innovative marketing of the enterprise. Innovative marketing is considered in the article as a component of marketing management which involves the analysis of market changes and demand for goods and services, the study of directions for effective changes (optimization), introduction to the market and sale of products on this basis. At the same time, marketing management, including strategic planning must necessarily include the development of new goods (services) and the strategy of optimizing the product portfolio depending on market changes (based on the analysis of tendencies and trends). The article proves that Innovative marketing covers all areas of marketing activity in aggregate, marketing mixes that are relevant in current conditions and include modern innovative means and tools, including digital marketing. As for “marketing innovations”, they are defined as the introduction of new marketing practices involving significant changes in the design, distribution, promotion or pricing of a product or service. Thus, innovative marketing and marketing innovation are correlated as a whole and a part. The relevance of using innovative marketing in various types of business activity is constantly growing, especially in high-tech industries and the service sector. Innovative marketing includes such key elements as the creation and promotion of an innovative product, innovative service, and innovative technologies. In turn, marketing innovations include place, product, price, promotion and their mix. The proposed classification of marketing innovations covers possible options for the application of innovations by elements of the marketing complex and auxiliary marketing activities, including: the use of the latest marketing research methods based on digital marketing tools; choosing one of the modern marketing concepts with an emphasis on advantages in ecology, social responsibility or building sustainable relationships; choosing a marketing strategy to cover the market and expand the target audience; product positioning and repositioning; changes in the assortment policy of an innovative nature; improvement of sales policy; modification (optimization for the enterprise) of the product life cycle; optimization of pricing policy with the use of innovative approaches in pricing; application of innovative methods of product promotion based on digitization. Conclusions are drawn on the main parameters of the effective use of innovative marketing.

Global strategies: concepts, types and features

Introduction. The paper is devoted to the definition and research of the concept of global strategies, their varieties and features. Different approaches to defining global strategies, proposed by well-known foreign and Ukrainian scientists, are considered. The peculiarities of various types of global strategies are studied, in particular, geopolitical, economic, sociocultural and technological strategies are considered. Specific cases of the application of global strategies are analyzed, namely on the example of the Apple company, and the impact of the chosen strategy on the company's success is described. The purpose of the paper is in a detailed analysis of the concept of global strategies, the definition of their types and features, consideration of conceptual approaches to the definition of global strategies and their classification depending on the goals, field of application, etc., as well as an overview of the role of global strategies in the modern world, their influence on politics, economy and social processes. Results. If we summarize all the information obtained, then the definition of the concept of global strategy can be presented as a plan or approach that establishes the general goal of the organization or company and the ways to achieve this goal at the international level, and which includes setting priorities, developing an action plan and developing policies, which are aimed at ensuring the success of the organization in the conditions of the global economy and competition. The most well-known and used types of global strategies are: cost reduction strategy, differentiation strategy, focus strategy, growth strategy, competitive advantage strategy, sustainable development strategy and digital transformation strategy. Global strategies may differ from company to company, as each company has its own needs and goals. For a deeper understanding of the types and features of global strategies, the purpose is to consider their use and combination on the device of a real organization. The global strategy of the company in question, Apple, is to create and sell products and services that allow users to be constantly connected to the world, which increases their productivity and entertainment. Conclusions. Summarizing all the above information, we can conclude that the global strategy is a long-term plan of action of the company, which determines how it will act in the international market. Each type of global strategy has its advantages and disadvantages, and the choice of the optimal strategy depends on the company's needs and local market conditions. A key feature of global strategies is that they not only contribute to increasing the company's profits, but also allow attracting new customer bases, expanding the geographical coverage of the market and ensuring competitiveness at the international level. Global strategies allow companies to effectively use their resources and capital at the international level, ensure stable production growth and increase their share in the international market. For the successful application of global strategies, it is necessary to conduct an in-depth analysis of market conditions and demand for products, as well as to determine the optimal option for the company's development at the international level.

5G Technology Is Applied to The Market Analysis and Life Impact Research of People with Disabilities

In recent years, the fifth generation of mobile communication system 5G has become a hot topic of discussion in the communication industry and academia.5G is a new generation of broadband mobile communication technology with high speed, low delay and large connection. It is a network infrastructure to realize the interconnection between man-machine and things. For people with disabilities, it is very difficult for them to operate smart phones, and they cannot enjoy the fast and convenient life brought by 5G network to normal people. Therefore, this project wants to study the market demand analysis of the products of 5G technology in front of the disabled, such as "creating" the eyes, ears and other senses of the disabled, and bring them new life experiences. The application of 5G technology in China to people with disabilities should take personal health as the value, and always adhere to the main line of orderly market competition and the development of people with disabilities.

The development of tea tourism in Sochi on the experience of the Chinese tea plantations

According to the characteristics of the economic development of tea garden tourism, this article analyzes the problems of economic development of tourism on tea plantations in Sochi on the experience of Chinese tea plantations, and put forward several measures, according to the analysis of market demand, resource use problems, product development problems for promoting tourism on tea plantations in Sochi and trade cooperation. The RMP statistical analysis model is applicated in this article: resource, market, product, which was put forward by the Chinese scientist Wu Bihu.

Integrating Big Data and Blockchain for Evaluating the Impact of Curriculum Deficiency on Labour Market Preparedness

This research addresses the pressing issue of skills mismatch in Nigeria’s labor market, particularly affecting graduates in science and technology fields. With youth unemployment rates ranging from 11.7% to 36.5%, it is imperative to bridge the gap between educational curricula and industry demands. This study proposed an innovative tool to perform labor market demand analysis and curriculum gap assessments by utilizing blockchain, artificial intelligence, and big data analytics. By collecting and analyzing data from diverse job portals, the tool aims to provide real-time insights into skills required by employers. Additionally, blockchain technology ensures secure and verifiable credentials for graduates. This research seeks to empower graduates and educational institutions, contributing to sustainable economic growth in Nigeria.

Coordinated Development of Urban Intelligent Transportation Data System and Supply Chain Management

With the development of the urban economy, the number of people using various means of transportation is also increasing, resulting in a huge workload of the traffic data system and prone to errors. Supply chain management can formulate a reasonable production plan according to the comprehensive information data generated by the supply chain management system, such as market demand analysis, purchasing demand analysis, and supplier assessment and evaluation. Therefore, this paper proposes the coordinated development of urban intelligent transportation data system and supply chain management, so as to improve the overall efficiency of the logistics system and the level of customer service. This paper aims to study the importance and advantages of the coordinated development of urban intelligent transportation data system and supply chain management. As can be seen from the data in Table 2, the percentage of people using a car increased by 18.2% in 2015, and by 2020, the percentage of people using a car increased by 36.9%. As shown in Figure 10, the traditional urban traffic data management system has the disadvantages of large amount of data and various and complex data types. Among them, the percentage of large amount of data is between 70% and 75%, and the percentage of diverse and complex data is between 62% and 68%. It can be seen that the number of people using cars is increasing, resulting in an increasing workload for the transportation system. On this basis, the intelligent traffic data system should be used to solve this problem and the coordinated development of the intelligent traffic data system and supply chain management can achieve a win-win situation.

Integrated Design Thinking to Improve Pedagogical Practices in Creative Engineering Design

Repeated testing, revision, and verification make products have market value and the commercialization of creative ideas reflected in the product. In the model, product and industrial designs present actual cases so that students are trained from scratch to clarify problems, identify needs, establish functional structures, and evaluate the creative design and engineering design. A good design plan includes market and user demand analysis, creative thinking, concept formation, and actual prototype making. Thus, students need to learn how to simulate the actual product design and development process through design protection and complete design planning. Therefore, taking creative engineering design courses as an example, this study aims to introduce various design methods into interactive teaching by using the problem/project-based learning (PBL) and science, technology, engineering, arts, and mathematics (STEAM) model. In industry, the methods are expected to simulate how a product design engineer faces the market and consumers. The results reveal the following. Students prefer to focus on hands-on practice and ask for examples and supplementary reference materials and a diversified interactive learning model. They like to work in groups and interact with peers and teachers to learn in real-time, hoping to know their levels and thoughts. They hope to apply what they learn for future career development. The education model integrates academic theory and industrial practice to reduce the gap between learning and practice in the industry.

Optimal pricing decision of composite service offered by network providers in E-commerce environment

With the increasing demand of consumers for diversified network services, more and more network service providers are competing fiercely in providing network composite services in order to meet the market demand. Network composition service is the most basic service. According to certain rules, it synthesizes new services and then realizes new functions. At present, the pricing of service composition by network service providers in the market is not scientific, meanwhile random and temporary pricing is still relatively common. In order to scientifically guide network service providers to price composite service scientifically and effectively, improve the profit of service providers, and meet the maximum service demand of consumers. Based on the theory of market demand price, this paper applies the pricing model in supply chain management to the pricing link of composite service network. From the perspective of network service providers, a two-objective competitive pricing model is constructed, and the simulation example analysis and sensitivity test are carried out. The simulation results show that the composite service provided by network service providers satisfy the general market demand price theory. In order to help service providers make scientific decisions on price adjustment of network services, this paper also makes sensitivity analysis of market demand on price changes. The research shows that the composite service provided by network service providers satisfy the general market demand price theory, while adjusting the price can only meet the general market demand price change theory if the original price is less than half of the original price.