The Impact of The Three-Dimensional Cultivation Model on the Development of the Suzhou Tea Industry:Estimating Value of Output Per Acre and Diversified Sales Models

This article explores the impact of the three-dimensional cultivation mode on the development of the Suzhou tea industry,focusing on the diversified estimation of the value of output per acre and sales mode.It introduces the history and traditional cultivation practices of tea in Suzhou,as well as the current challenges and problems faced by the industry.An in-depth analysis was conducted on the overview and improvement plans of the three-dimensional cultivation mode,covering relevant technical methods.Based on this analysis,the impact of the three-dimensional cultivation on the value of output per acre was studied and predicted.Its potential and advantages were explored and compared with the effectiveness of traditional cultivation models.Additionally,the impact of the three-dimensional cultivation mode on sales was analyzed,examining its market adaptability and competitiveness,as well as its advantages in expanding sales channels and market coverage.The study also focused on the promoting effect of diversified sales models on the Suzhou tea industry,including direct consumption market development,tea processing product development and promotion,and the integration of tea culture and the tourism industry.To ensure sustainable development,the article evaluates the environmental impact,economic feasibility,social benefits,and farmer benefits of the three-dimensional cultivation model.Finally,the prospects for the development of the Suzhou tea industry were discussed,and the positioning and response strategies of the threedimensional cultivation model were proposed.

A Study on the Factors Influencing Consumer Purchase Decision Under the Live-Streaming Sales Model

In recent years,with the rapid development and popularization of Internet information technology,many new media platforms have risen rapidly,and major e-commerce companies have begun to explore the mode of livestreaming.Especially during the COVID-19 pandemic,due to the lockdown,live-streaming has become an important means of economic development in many places.Owing to its remarkable characteristics of timeliness,entertainment,and interactivity,it has become the latest and trendiest sales mode of e-commerce channels,reflecting huge economic potential and commercial value.This article analyzes two models and their characteristics of live-streaming sales from a practical perspective.Based on this,it outlines consumer purchasing decisions and the factors that affect consumer purchasing decisions under the live-streaming sales model.Finally,it discusses targeted suggestions for using the live-streaming sales model to expand the consumer market,hoping to promote the healthy and steady development of the live-streaming sales industry.

Did weekly economic index and volatility index impact US food sales during the first year of the pandemic?

We explore the impacts of economic and financial dislocations caused by COVID-19 pandemic shocks on food sales in the United States from January 2020 to January 2021.We use the US weekly economic index(WEI)to measure economic dislocations and the Chicago Board Options Exchange volatility index(VIX)to capture the broader stock market dislocations.We validate the NARDL model by testing a battery of models using the autoregressive distributed lags(ARDL)methodology(ARDL,NARDL,and QARDL specifications).Our study postulates that an increase in WEI has a significant negative long-term effect on food sales,whereas a decrease in WEI has no statistically significant(long-run)effect.Thus,policy responses that ignore asymmetric effects and hidden cointegration may fail to promote food security during pandemics.

The Contribution Margin due to a Limiting Factor in the Presence of Several Sales Options: Actuality Is Not Always As It Appears at the Beginning of the Analysis

The analysis of company data useful for economic decisions,if not interpreted in an overall view of the company situation,can lead to wrong conclusions.This is the case when a company has to choose between several sales options for one or more products in the presence of a limiting factor.The continuation of the investigation often denies the initial analysis.Not everything is as it appears,therefore,at the beginning of the deepening of the data useful for economic decisions.As it is well known,the choices of profitability concerning the planning of the sale of company products take place,at least in the majority of cases,through the determination of the contribution margin,i.e.the profitability margin connected to the individual goods/services sold by the companies(selling price net of variable costs).The contribution margin can be determined with four objectives:(1)Determination of the yield of the single product,net of variable costs only.In this case,the margin defines unitary,from net product yield to unitary contribution margin.(2)Determination of the return on total sales of an individual product,net of variable costs.In this hypothesis,reference is made to the first level(or gross)contribution margin.(3)Determination of the ability of the individual product to contribute to the coverage of fixed costs common to the company.This margin is determined net of special product variable and fixed costs.This aggregate is defined as a Level II(or semi-gross)margin.(4)Determination of the useful value in the planning choices in case of presence of scarce productive factors.In this case,it must identify the so-called unitary margin for low factor.Here we will only deal with the problem of the use of the contribution margin in the presence of rare factors.To complete the analysis,below are some very brief considerations regarding,respectively,the unitary,level I,and level II contribution margin in order to better understand where the problem of the most convenient choice of income is located in the event of the presence of rare production factors,especially in an environment characterized by a plurality of sales options.

Optimization of Electricity Purchase and Sales Strategies of Electricity Retailers under the Condition of Limited Clean Energy Consumption

In the process of my country’s energy transition,the clean energy of hydropower,wind power and photovoltaic power generation has ushered in great development,but due to the randomness and volatility of its output,it has caused a certain waste of clean energy power generation resources.Regarding the purchase and sale of electricity by electricity retailers under the condition of limited clean energy consumption,this paper establishes a quantitative model of clean energy restricted electricity fromthe perspective of power system supply and demand balance.Then it analyzes the source-charge dual uncertain factors in the electricity retailer purchasing and selling scenarios in the mid-to long-term electricity market and the day-ahead market.Through the multi-scenario analysis method,the uncertain clean energy consumption and the user’s power demand are combined to form the electricity retailer’s electricity purchase and sales scene,and the typical scene is obtained by using the hierarchical clustering algorithm.This paper establishes a electricity retailer’s risk decisionmodel for purchasing and selling electricity in themid-and long-term market and reduce-abandonment market,and takes the maximum profit expectation of the electricity retailer frompurchasing and selling electricity as the objective function.At the same time,in themediumand longterm electricity market and the day-ahead market,the electricity retailer’s purchase cost,electricity sales income,deviation assessment cost and electricity purchase and sale risk are considered.The molecular results show that electricity retailers can obtain considerable profits in the reduce-abandonment market by optimizing their own electricity purchase and sales strategies,on the premise of balancing profits and risks.

Comparison of Sales Prediction in Conventional Insights and Machine Learning Perspective

With the integration of global economy development and the rapid growth of science knowledge and technology,the needs of people’s consumption are increasingly personalized and diversified.Such a market background makes sales forecasting become an indispensable part of enterprise management and development.The definition of the sales forecasting is that based on the past few years’sales situation,the enterprises through systematic sales forecasting models estimate of the quantity and amount of all or some specific sales products and services in a specific time in the future.Accurate sales forecasting can promote enterprises to do better in future revenue,and can also encourage enterprises to set and keep an efficient sales management team.This paper will analyze traditional sales forecasting methods and sales forecasting methods based on big data models related to the perspective of machine learning,and then compare them.The research shows that the two sales forecasting methods have their own advantages and disadvantages.In the future,enterprises can adopt the two sales forecasting methods in parallel to maximize the utilization advantage of sales forecasting for enterprises.

Production and sales growth of China's knitting industry slows down,export hits a record high

In 2022,the international economic and trade environment is in turmoil,singed by the pandemic,while domestic sales are weak.In the face of complex and severe situation at home and abroad,China textile industry has shown strong resilience.In 2022,36,000 enterprises in China's textile industry achieved more than 5,200 billion yuan in main business revenue and 200 billion yuan in profit,with operating margin of 3.9 percent.In 2022,China's textile and apparel exports reached a new record high of 340.95 bilion US dollars,up 2.5 percent year-on-year.

Research on the Effect of R&D Investment Intensity and Sales Expense on the Performance of Biomedical Enterprises

Objective To explore the influence of new drug R&D investment and sales expense on the performance of biomedical enterprises.Methods The financial statements of 76 listed biomedical enterprises for 5 consecutive years were selected,and the data were modeled to study the effect of R&D investment and sales expense on the performance of biomedical enterprises by using financial indicators as tools and statistical methods of multiple linear regression.Results and Conclusion Under the premise that the weak related factors such as enterprise scale,life cycle and asset-liability ratio are set as unrelated variables,the R&D investment intensity of biomedical enterprises is negatively correlated with the current performance,which also shows that the R&D of biomedical enterprises has the characteristics of high risk.Besides,the influence of early R&D investment is delayed.However,the sales expense of leading biomedical enterprises with large scales have higher proportion.Meanwhile the greater sales expense of the same enterprise in different periods,the better the enterprise performance is.Biomedical enterprises should consider their own development stage to develop more patented drugs.Besides,they must formulate plans for allocating reasonable sales personnel and cost expense to ensure that enterprises can obtain better benefits.

Product Specification Analysis for Modular Product Design Using Big Sales Data

Big data on product sales are an emerging resource for supporting modular product design to meet diversified customers’requirements of product specification combinations.To better facilitate decision-making of modular product design,correlations among specifications and components originated from customers’conscious and subconscious preferences can be investigated by using big data on product sales.This study proposes a framework and the associated methods for supporting modular product design decisions based on correlation analysis of product specifications and components using big sales data.The correlations of the product specifications are determined by analyzing the collected product sales data.By building the relations between the product components and specifications,a matrix for measuring the correlation among product components is formed for component clustering.Six rules for supporting the decision making of modular product design are proposed based on the frequency analysis of the specification values per component cluster.A case study of electric vehicles illustrates the application of the proposed method.

Design and Implementation of Fresh Vegetable Sales Volume Trend Forecasting System Based on Improved SVR

The forecast of sales volume trend of fresh vegetables has significant referential function for government dominant departments,producers and consumers.In order to evaluate the e-commerce sales information of fresh vegetables scientifically and accurately,the sales volume information of such four common vegetables as baby cabbage,potatoes,bok choy and tomatoes,from Anhui Jinghui Vegetable E-commerce Co.,Ltd.was selected as the research object to establish the sales trend prediction system.Taking the improved SVR as an example,we introduced the overall architecture,detailed design and function realization of the system.The system can reflect the short-term sales volume trend of fresh vegetables,and also can provide guidance for the realization of e-commerce order-oriented management and scientific production.

Retail sales of consumer goods:＞RMB 10 trln

Chinese Academy of Social Sciences(CASS)forecasted the retail sales of consumer goods in 2008 at RMB 10.67 trillion(about US＄1.57 trillion),up 12.8 percent as consumption grows. The figure would reach RMB 12.48 trillion in 2009,up 12.5 percent,said a report released by the CASS.

Correlation Analysis of Fiscal Revenue and Housing Sales Price Based on Multiple Linear Regression Model

This paper selects seven indicators of financial revenue and housing sales price in recent 19 years in China,and uses SPSS and Excel to carry out descriptive statistics,independent sample t-test,correlation analysis and regression analysis to comprehensively study the correlation between financial revenue and housing sales price in China,and establishes the relationship between financial revenue and housing sales price When the average selling price of commercial housing increases by one unit,the fiscal revenue will increase by 27.855 points.

Effect of Rural Social Pension Insurance on Total Retail Sales of Consumer Goods

Based on data of 31 provinces of China in 2019 collected from the National Bureau of Statistics,this paper explores the impact of the number of urban employees’endowment insurance on the total retail sales of social consumer goods in different provinces in China.Taking the population,per capita disposable income,per capita life expectancy,and regional per capita GDP of each province as the variables,this paper establishes regression models to do the empirical research.The results show that:(1)The increase of the number of urban employees’old-age insurance has a significant positive impact on residents’consumption.The wider the coverage of old-age insurance,the more it can enhance the consumption confidence of the residents.(2)Due to the economic development,the level of urbanization has been greatly improved,leading to an increased birth rate and total population,and thus consumption has been driven.Therefore,the increase of the total population has a significant positive effect on the increase of the total retail sales of social consumer goods.(3)The increase of per capita disposable income has insignificant impact on the increase of total retail sales of social consumer goods due to residents’debt,the rise of house prices,the rapid widening of income gap between different groups,and the difficulty of meeting the various needs of people.(4)Although the increase of life expectancy per capita will lead to the decrease of total retail sales of social consumer goods,this decrease is not significant.(5)Per capita GDP will lead to a small increase in the total retail sales of social consumption.Finally,based on the above conclusions,some suggestions to stimulate consumption are given.

THREE EARLY DYNASTIC SUMERIAN SALES CONTRACTS OF IMMOVABLES HOUSED IN THE OKAYAMA ORIENT MUSEUM

Two years ago I had a chance to read four unpublished Sumerian texts newly housed in the Okayama Orient Museum, Okayama-shi, Japan. With the generous permission of Prof. Dr. Taksahi TANIICHI, Director General of the Museum, I offer three of the texts below.

The Variance Analysis on Enterprise of Different Ways of Sales：Based on Analysis of Enterprise Tax Burden and Cash Flows

在目前竞争激烈的市场经济环境中,许多企业为了维持或扩大自己商品的市场份额,往往采取多种多样的销售方式,以达到促销的目的,而且随着经济的发展以及互联网时代的来临,销售形式也越来越多.基于企业税负与现金净流量的基础上对9 种销售方式从企业税负与现金净流量两个方面进行了分析与研究.研究发现税负高的销售方式,可能其现金净流量也比较高,因此企业在经营销售过程中,不能只考虑税负的问题,还要考虑企业现金净流量的问题,甚至是企业的整体发展问题以及顾客对销售方式的接受程度.

Organic Cotton Sales Up-But What’s the Cost?

The latest headline figures on organic cotton retail sales supplied by Organic Exchange (OE)show a healthy 35% growth to a value of US$4.

Clothing Sales Forecast Considering Weather Information: An Empirical Study in Brick-and-Mortar Stores by Machine-Learning

Reliable sales forecasts are important to the garment industry. In recent years, the global climate is warming, the weather changes frequently, and clothing sales are affected by weather fluctuations. The purpose of this study is to investigate whether weather data can improve the accuracy of product sales and to establish a corresponding clothing sales forecasting model. This model uses the basic attributes of clothing product data, historical sales data, and weather data. It is based on a random forest, XGB, and GBDT adopting a stacking strategy. We found that weather information is not useful for basic clothing sales forecasts, but it did improve the accuracy of seasonal clothing sales forecasts. The MSE of the dresses, down jackets, and shirts are reduced by 86.03%, 80.14%, and 41.49% on average. In addition, we found that the stacking strategy model outperformed the voting strategy model, with an average MSE reduction of 49.28%. Clothing managers can use this model to forecast their sales when they make sales plans based on weather information.

Empirical Research on Relationship between Corporate Brand Value and Apparel Market Sales Revenue of Apparel Enterprise

Among the existing researches on brand value,few of them focused on the demands of the companies in the clothing industry to brand value. There were three innovation points as follows: first of all,two key demands of apparel companies to existing brand value were summarized through investigation; then,the concept of rapid brand value evaluation and multi-dimensional factors( MDFs) was presented; finally,the relationship between apparel corporate brand value and the sales revenue in apparel market with the sales revenue was proven by empirical research.During the process of empirical study,the sales revenue data of 66 apparel enterprises domestic and abroad were collected,and the regression analysis has been done on the relationship between the corporate brand value and the apparel market sales revenue of apparel enterprise. The empirical research showed that they were positively correlated to each other. This conclusion presented a method of judging brand value development trend quickly by single indicator.

A New Type of Combination Forecasting Method Based on PLS——The Application of It in Cigarette Sales Forecasting

Cigarette market is a kind of monopoly market which is closed loop running, it depends on the plan mechanism to schedule producing, supplying and selling, but the “bullwhip effect” still exists. So it has a fundamental significance to do sales forecasting work. It needs to considerate the double trend characteristics, history sales data and other main factors that affect cigarette sales. This paper depends on the panel data of A province’s cigarette sales, first we established three single forecasting models, after getting the predicted value of these single models, then using the combination forecasting method which based on PLS to predict the province’s cigarette sales of the next year. The results show that the prediction accuracy is good, which could provide a certain reference to cigarette sales forecasting in A province.