With the advancement of the rural revitalization strategy,preventing poverty recurrence among previously impoverished populations has become a crucial social concern.The application of big data technology in poverty r...With the advancement of the rural revitalization strategy,preventing poverty recurrence among previously impoverished populations has become a crucial social concern.The application of big data technology in poverty recurrence monitoring and agricultural product sales systems can effectively enhance precise identification and early warning capabilities,promoting the sustainable development of rural economies.This paper explores the application of big data technology in poverty recurrence monitoring,analyzes its innovative integration with agricultural product sales systems,and proposes an intelligent monitoring and sales platform model based on big data,aiming to provide a reference for relevant policy formulation.展开更多
This paper reports literature review in the field of pharmaceutical marketing emphasizing problems faced by medical representatives. India after globalization and being the second highest populated country has emerged...This paper reports literature review in the field of pharmaceutical marketing emphasizing problems faced by medical representatives. India after globalization and being the second highest populated country has emerged as major pharmaceutical market in the world. Pharmaceutical marketing in India is highly relied on personal relationship between medical representatives and doctors. In the last decade, many foreign companies have entered in Indian market. This has posed highly competitive and challenging work environment for medical representatives. Therefore, it is indispensable to study the challenges faced by medical representatives in this dynamic environment.展开更多
The development of social economy and the adjustment of enterprises themselves have forced enterprises to keep pace with the times in cost management. Facing the opportunities and challenges, enterprises should establ...The development of social economy and the adjustment of enterprises themselves have forced enterprises to keep pace with the times in cost management. Facing the opportunities and challenges, enterprises should establish the correct concept of cost control, formulate effective cost control management system, and implement scientifically and effectively. Only by doing a good job of cost control can an enterprise be in an invincible position in the market competition and ensure its sustainable development.展开更多
The COVID-19 has brought us unprecedented difficulties and thousands of companies have closed down.The general public has responded to call of the government to stay at home.Offline retail stores have been severely af...The COVID-19 has brought us unprecedented difficulties and thousands of companies have closed down.The general public has responded to call of the government to stay at home.Offline retail stores have been severely affected.Therefore,in order to transform a traditional offline sales model to the B2C model and to improve the shopping experience,this study aims to utilize historical sales data for exploring,building sales prediction and recommendation models.A novel data science life-cycle and process model with Recency,Frequency,and Monetary(RFM)analysis method with the combination of various analytics algorithms are utilized in this study for sales prediction and product recommendation through user behavior analytics.RFM analysis method is utilized for segmenting customer levels in the company to identify the importance of each level.For the purchase prediction model,XGBoost and Random Forest machine learning algorithms are used to build prediction models and 5-fold Cross-Validation method is utilized to evaluate their.For the product recommendation model,the association rules theory and Apriori algorithm are used to complete basket analysis and recommend products according to the outcomes.Moreover,some suggestions are proposed for the marketing department according to the outcomes.Overall,the XGBoost model achieved better performance and better accuracy with F1-score around 0.789.The proposed recommendation model provides good recommendation results and sales combinations for improving sales and market responsiveness.Furthermore,it recommend specific products to new customers.This study offered a very practical and useful business transformation case that assists companies in similar situations to transform their business models.展开更多
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 modula...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.展开更多
Using data from the Economic Advisory Center of the State Information Center(SIC), we examined the spatial patterns of car sales in China at the prefectural level in 2012. We first analyzed the spatial distributions o...Using data from the Economic Advisory Center of the State Information Center(SIC), we examined the spatial patterns of car sales in China at the prefectural level in 2012. We first analyzed the spatial distributions of car sales of different kinds of automakers(foreign automakers, Sino-foreign joint automakers, and Chinese automakers), and then identified spatial clusters using the local Moran's indexes. Location quotient analysis was applied to examine the relative advantage of each type of automaker in the local markets. To explain the variations of car sales across cities, we collected several socioeconomic variables and conducted regression analyses. Further, factor analysis was used to extract independent variables to avoid the problem of multicollinearity. By incorporating a spatial lag or spatial error in the models, we calibrated our spatial regression models to address the spatial dependence problem. The analytical results show that car sales varied significantly across cities in China, and most of the cities with higher car sales were the developed cities. Different automakers exhibit diverse spatial patterns in terms of car sales volume, spatial clusters, and location quotients. The scale and incomes factor were extracted and verified as the two most significant and positive factors that shape the spatial distributions of car sales, and together with the spatial effect, explained most of the variations of car sales across cities.展开更多
Budgeting planning plays an important role in coordinating activities in organizations. An accurate sales volume forecasting is the key to the entire budgeting process. All of the other parts of the master budget are ...Budgeting planning plays an important role in coordinating activities in organizations. An accurate sales volume forecasting is the key to the entire budgeting process. All of the other parts of the master budget are dependent on the sales volume forecasting in some way. If the sales volume forecasting is sloppily done, then the rest of the budgeting process is largely a waste of time. Therefore, the sales volume forecasting process is a critical one for most businesses, and also a difficult area of management. Most of researches and companies use the statistical methods, regression analysis, or sophisticated computer simulations to analyze the sales volume forecasting. Recently, various prediction Artificial Intelligent (AI) techniques have been proposed in forecasting. Support Vector Regression (SVR) has been applied successfully to solve problems in numerous fields and proved to be a better prediction model. However, the select of appropriate SVR parameters is difficult. Therefore, to improve the accuracy of SVR, a hybrid intelligent support system based on evolutionary computation to solve the difficulties involved with the parameters selection is presented in this research. Genetic Algorithms (GAs) are used to optimize free parameters of SVR. The experimental results indicate that GA-SVR can achieve better forecasting accuracy and performance than traditional SVR and artificial neural network (ANN) prediction models in sales volume forecasting.展开更多
One of the most severe problems affecting the efficient operations of gas pipelines is corrosion caused by black powder. According to the literature, the primary source for the existence of black powder is condensed w...One of the most severe problems affecting the efficient operations of gas pipelines is corrosion caused by black powder. According to the literature, the primary source for the existence of black powder is condensed water. In this case study, the temperature (40°C) of the sales gas is much higher than its dew point (9.24°C). The water is therefore in vapor phase. It is then proposed to remove water vapor from the gas at the entrance of the plant using an adsorption process. The recommended technology is the Layered Bed Temperature-Swing Adsorption (LBTSA) with micro-channels with molecular sieve zeolite 4A and activated alumina as adsorbents. In the case of presence of aerosols that could condense water, it is suggested to utilize a RED (Rare Earth Drum) magnetic separator in order to remove black powder from the gaseous feed.展开更多
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 ve...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.展开更多
Chinese traditional sales channels are seriously attacked by the new ones. Household appliances industry will realize the specialized divisions of. development, manufacture, sale and services completely. The model of ...Chinese traditional sales channels are seriously attacked by the new ones. Household appliances industry will realize the specialized divisions of. development, manufacture, sale and services completely. The model of sales channel in marketing is set as the core of this research; the merits and demerits of different sales channels are analyzed; the complicated selective relationship and the conflicts among the manufacturer, middlemen, and ultimate consumers, and the solutions to present multi-channels market and the developments of the sales channels are elaborated in an overall view; the opinion that the only way to develop this industry is raised to establish the competitive sales channels. The aim is to let local household appliances industry use the natural merits to build up a suitable channel rapidly and efficiently, and to speed up the self development and oeffection.展开更多
According to EVsales,a total of 3,124,800 new energy vehicles (NEVs) were sold worldwide in 2020,marking a year-on-year increase of 41%.Besides,battery electric vehicles (BEVs) have gradually become best-selling NEVs....According to EVsales,a total of 3,124,800 new energy vehicles (NEVs) were sold worldwide in 2020,marking a year-on-year increase of 41%.Besides,battery electric vehicles (BEVs) have gradually become best-selling NEVs.According to the White Paper on the Development of China’s New Energy Vehicle Industry (2021),the sales of NEVs around the world are expected to grow to over 4.5 million in 2021,up by about 36% from a year ago.展开更多
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 fundamen...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.展开更多
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 ...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.展开更多
With Internet changing the luxury business landscape,new players have emerged such as the Online Private Sales Retailers(OPSRs).These offer online buyers with a choice of limited-time sales to help companies get rid o...With Internet changing the luxury business landscape,new players have emerged such as the Online Private Sales Retailers(OPSRs).These offer online buyers with a choice of limited-time sales to help companies get rid of their overstocks.Luxury brands are no exception.No research has been conducted about how luxury consumers relate with such websites,hence this paper.In an exploratory fashion,interviews with luxury buyers who also buy online on OPSRs,are conducted to get insights on consumers’perceptions and luxury brand equity that selling through OPSRs may have.We find that appropriate product and brand help consumers forget that they are buying brands’unsold stocks,that transferring the luxury webmospheres would be positively perceived,that consumers from these websites are looking for benefits such as freedom of use and brand discovery,rather than personalized offers,that multiple discounts on several OPSRs may damage the luxury-perception of a brand,that the private sales members consider the service to be good enough for the demanded price,and that personalized invitations can help increase online consumers’feelings of desirability and exclusivity.The paper concludes with practical recommendations for both luxury companies and OPSRs.展开更多
Since the 1980s, China’s commercial housing market has shown an unprecedented rapid development, and the commercial houses still has a high price. This paper studies the sales rate of commercial housing sales to find...Since the 1980s, China’s commercial housing market has shown an unprecedented rapid development, and the commercial houses still has a high price. This paper studies the sales rate of commercial housing sales to find an appropriate model, and it analyzes the volatility of the commercial housing market to describe the sustainable development of the commercial housing market. By selecting month data of China’s commercial housing sales from January 2006 to October 2018, this paper uses EViews7.2 and the ARMA Model as the tool in order to establish EARCH(1,1) through the method of quantitative analysis. It is found that the yield of commercial housing sales has obvious cluster, asymmetry and leverage effect, and the impact of adverse news on the commercial housing market is more significant than the impact of favorable news.展开更多
基金2025 College Students’Innovation Training Program“Return to Poverty Monitoring and Agricultural Products Sales System”2024 College Students’Innovation Training Program“Promoting Straw Recycling to Accelerate the Sustainable Development of Agriculture”(202413207010)。
文摘With the advancement of the rural revitalization strategy,preventing poverty recurrence among previously impoverished populations has become a crucial social concern.The application of big data technology in poverty recurrence monitoring and agricultural product sales systems can effectively enhance precise identification and early warning capabilities,promoting the sustainable development of rural economies.This paper explores the application of big data technology in poverty recurrence monitoring,analyzes its innovative integration with agricultural product sales systems,and proposes an intelligent monitoring and sales platform model based on big data,aiming to provide a reference for relevant policy formulation.
文摘This paper reports literature review in the field of pharmaceutical marketing emphasizing problems faced by medical representatives. India after globalization and being the second highest populated country has emerged as major pharmaceutical market in the world. Pharmaceutical marketing in India is highly relied on personal relationship between medical representatives and doctors. In the last decade, many foreign companies have entered in Indian market. This has posed highly competitive and challenging work environment for medical representatives. Therefore, it is indispensable to study the challenges faced by medical representatives in this dynamic environment.
文摘The development of social economy and the adjustment of enterprises themselves have forced enterprises to keep pace with the times in cost management. Facing the opportunities and challenges, enterprises should establish the correct concept of cost control, formulate effective cost control management system, and implement scientifically and effectively. Only by doing a good job of cost control can an enterprise be in an invincible position in the market competition and ensure its sustainable development.
基金This research is funded by the School of Computer Sciences,and Division of Research&Innovation,Universiti Sains Malaysia,Short Term Grant(304/PKOMP/6315435)granted to Pantea Keikhosrokiani.
文摘The COVID-19 has brought us unprecedented difficulties and thousands of companies have closed down.The general public has responded to call of the government to stay at home.Offline retail stores have been severely affected.Therefore,in order to transform a traditional offline sales model to the B2C model and to improve the shopping experience,this study aims to utilize historical sales data for exploring,building sales prediction and recommendation models.A novel data science life-cycle and process model with Recency,Frequency,and Monetary(RFM)analysis method with the combination of various analytics algorithms are utilized in this study for sales prediction and product recommendation through user behavior analytics.RFM analysis method is utilized for segmenting customer levels in the company to identify the importance of each level.For the purchase prediction model,XGBoost and Random Forest machine learning algorithms are used to build prediction models and 5-fold Cross-Validation method is utilized to evaluate their.For the product recommendation model,the association rules theory and Apriori algorithm are used to complete basket analysis and recommend products according to the outcomes.Moreover,some suggestions are proposed for the marketing department according to the outcomes.Overall,the XGBoost model achieved better performance and better accuracy with F1-score around 0.789.The proposed recommendation model provides good recommendation results and sales combinations for improving sales and market responsiveness.Furthermore,it recommend specific products to new customers.This study offered a very practical and useful business transformation case that assists companies in similar situations to transform their business models.
基金National Key R&D Program of China(Grant No.2018YFB1701701)Sailing Talent Program+1 种基金Guangdong Provincial Science and Technologies Program of China(Grant No.2017B090922008)Special Grand Grant from Tianjin City Government of China。
文摘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.
基金Under the auspices of National Natural Science Foundation of China(No.41301143)
文摘Using data from the Economic Advisory Center of the State Information Center(SIC), we examined the spatial patterns of car sales in China at the prefectural level in 2012. We first analyzed the spatial distributions of car sales of different kinds of automakers(foreign automakers, Sino-foreign joint automakers, and Chinese automakers), and then identified spatial clusters using the local Moran's indexes. Location quotient analysis was applied to examine the relative advantage of each type of automaker in the local markets. To explain the variations of car sales across cities, we collected several socioeconomic variables and conducted regression analyses. Further, factor analysis was used to extract independent variables to avoid the problem of multicollinearity. By incorporating a spatial lag or spatial error in the models, we calibrated our spatial regression models to address the spatial dependence problem. The analytical results show that car sales varied significantly across cities in China, and most of the cities with higher car sales were the developed cities. Different automakers exhibit diverse spatial patterns in terms of car sales volume, spatial clusters, and location quotients. The scale and incomes factor were extracted and verified as the two most significant and positive factors that shape the spatial distributions of car sales, and together with the spatial effect, explained most of the variations of car sales across cities.
文摘Budgeting planning plays an important role in coordinating activities in organizations. An accurate sales volume forecasting is the key to the entire budgeting process. All of the other parts of the master budget are dependent on the sales volume forecasting in some way. If the sales volume forecasting is sloppily done, then the rest of the budgeting process is largely a waste of time. Therefore, the sales volume forecasting process is a critical one for most businesses, and also a difficult area of management. Most of researches and companies use the statistical methods, regression analysis, or sophisticated computer simulations to analyze the sales volume forecasting. Recently, various prediction Artificial Intelligent (AI) techniques have been proposed in forecasting. Support Vector Regression (SVR) has been applied successfully to solve problems in numerous fields and proved to be a better prediction model. However, the select of appropriate SVR parameters is difficult. Therefore, to improve the accuracy of SVR, a hybrid intelligent support system based on evolutionary computation to solve the difficulties involved with the parameters selection is presented in this research. Genetic Algorithms (GAs) are used to optimize free parameters of SVR. The experimental results indicate that GA-SVR can achieve better forecasting accuracy and performance than traditional SVR and artificial neural network (ANN) prediction models in sales volume forecasting.
文摘One of the most severe problems affecting the efficient operations of gas pipelines is corrosion caused by black powder. According to the literature, the primary source for the existence of black powder is condensed water. In this case study, the temperature (40°C) of the sales gas is much higher than its dew point (9.24°C). The water is therefore in vapor phase. It is then proposed to remove water vapor from the gas at the entrance of the plant using an adsorption process. The recommended technology is the Layered Bed Temperature-Swing Adsorption (LBTSA) with micro-channels with molecular sieve zeolite 4A and activated alumina as adsorbents. In the case of presence of aerosols that could condense water, it is suggested to utilize a RED (Rare Earth Drum) magnetic separator in order to remove black powder from the gaseous feed.
基金Supported by Anhui Provincial Science and Technology Major Project(18030701202)General Project of Anhui Provincial Key Research and Development Program(201904a06020056)。
文摘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.
文摘Chinese traditional sales channels are seriously attacked by the new ones. Household appliances industry will realize the specialized divisions of. development, manufacture, sale and services completely. The model of sales channel in marketing is set as the core of this research; the merits and demerits of different sales channels are analyzed; the complicated selective relationship and the conflicts among the manufacturer, middlemen, and ultimate consumers, and the solutions to present multi-channels market and the developments of the sales channels are elaborated in an overall view; the opinion that the only way to develop this industry is raised to establish the competitive sales channels. The aim is to let local household appliances industry use the natural merits to build up a suitable channel rapidly and efficiently, and to speed up the self development and oeffection.
文摘According to EVsales,a total of 3,124,800 new energy vehicles (NEVs) were sold worldwide in 2020,marking a year-on-year increase of 41%.Besides,battery electric vehicles (BEVs) have gradually become best-selling NEVs.According to the White Paper on the Development of China’s New Energy Vehicle Industry (2021),the sales of NEVs around the world are expected to grow to over 4.5 million in 2021,up by about 36% from a year ago.
文摘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.
基金financial interest(such as honorariaeducational grants+2 种基金participation in speakers’bureausmembership,employment,consultancies,stock ownership,or other equity interestand expert testimony or patent-licensing arrangements),or nonfinancial interest(such as personal or professional relationships,affiliations,knowledge or beliefs)in the subject matter or materials discussed in this manuscript.
文摘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.
文摘With Internet changing the luxury business landscape,new players have emerged such as the Online Private Sales Retailers(OPSRs).These offer online buyers with a choice of limited-time sales to help companies get rid of their overstocks.Luxury brands are no exception.No research has been conducted about how luxury consumers relate with such websites,hence this paper.In an exploratory fashion,interviews with luxury buyers who also buy online on OPSRs,are conducted to get insights on consumers’perceptions and luxury brand equity that selling through OPSRs may have.We find that appropriate product and brand help consumers forget that they are buying brands’unsold stocks,that transferring the luxury webmospheres would be positively perceived,that consumers from these websites are looking for benefits such as freedom of use and brand discovery,rather than personalized offers,that multiple discounts on several OPSRs may damage the luxury-perception of a brand,that the private sales members consider the service to be good enough for the demanded price,and that personalized invitations can help increase online consumers’feelings of desirability and exclusivity.The paper concludes with practical recommendations for both luxury companies and OPSRs.
文摘Since the 1980s, China’s commercial housing market has shown an unprecedented rapid development, and the commercial houses still has a high price. This paper studies the sales rate of commercial housing sales to find an appropriate model, and it analyzes the volatility of the commercial housing market to describe the sustainable development of the commercial housing market. By selecting month data of China’s commercial housing sales from January 2006 to October 2018, this paper uses EViews7.2 and the ARMA Model as the tool in order to establish EARCH(1,1) through the method of quantitative analysis. It is found that the yield of commercial housing sales has obvious cluster, asymmetry and leverage effect, and the impact of adverse news on the commercial housing market is more significant than the impact of favorable news.
