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 stimulus to carry out this research is to investigate the relationship between internet advertisement and its features on the total E-commerce sales of the top five countries of Europe. The units of analysis are t...The stimulus to carry out this research is to investigate the relationship between internet advertisement and its features on the total E-commerce sales of the top five countries of Europe. The units of analysis are the individuals of UK, France, Italy, Germany and Netherland. Secondary data are collected from the reports of [1] (ADEX, 2010) and [2] (Eurostats, 2011). To empirically determine the relationship between independent variable and dependent variable in the European context, the study uses various statistical techniques, including OLS regression and correlation analysis techniques. The empirical findings indicate that the Internet advertisement features of search advertisement and classified advertisement have positive significant relationship with the E-commerce sales in Europe. The empirical findings indicate negative significant relationship of display advertisement with the E-commerce sales in Europe. However, this variable is also justified with the help of literature. Findings also demonstrate that search advertisement has strong positive relationship and it generates positive influence for the E-commerce sales as compared to the classified advertisement and display advertisement. Firms and marketers which are investing in online advertisement will find these results useful as they can get better sales and can use these features of online advertisement in order to maximize the sales of their products and services.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
By using the characteristics of the new building in China, this article constructs the virtual repeat sale method to produce virtual repeat data which is similar to the repeat sale model on the house price index. Case...By using the characteristics of the new building in China, this article constructs the virtual repeat sale method to produce virtual repeat data which is similar to the repeat sale model on the house price index. Case-Shiller procedure and OFHEO method are used to calculate the house price index for new building in China. A discussion is given and furthering models are needed to take advantage of the virtual repeat sale data.展开更多
Sale prediction plays a significant role in business management. By using support vector machine Regression （ε-SVR）, a method using to predict sale is illustrated. It takes historical data and current context data ...Sale prediction plays a significant role in business management. By using support vector machine Regression （ε-SVR）, a method using to predict sale is illustrated. It takes historical data and current context data as inputs and presents results, i.e. sale tendency in the future and the forecasting sales, according to the user＇s specification of accuracy and time cycles. Some practical data experiments and the comparative tests with other algorithms show the advantages of the proposed approach in computation time and correctness.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
Cooling, transportation and sale processes of spiced geese were studied, eight spiced geese meat samples with different sampling time, Airborne microorganism samples of three different workplaces and five different en...Cooling, transportation and sale processes of spiced geese were studied, eight spiced geese meat samples with different sampling time, Airborne microorganism samples of three different workplaces and five different environmental contact substance samples were test, measures of special mediums, biochemical identification and DNA sequencing were carried out, then Escherichia coli, Yeast, Mildew, Lactic acid bacteria, Staphylococcus aureus and Janthinobacterium were detected. For spiced geese meat samples, microorganisms were significant (p ) increased with the prolong of sampling time. Lactic acid bacteria, Staphylococcus aureus and Janthinobacterium were detected in each processing operation and the total aerobic counts of each sample was increased or significant (p ) increased with the prolong of sampling time;Escherichia coli, Yeast and Mildew were detected on samples entered into the retail outlet mainly and the total aerobic counts of each sample was increased or significant (p ) increased also. In the household workshop, Mildew and Janthinobacterium were the superior microorganisms. In the transport vehicle, Staphylococcus aureus and Janthinobacterium were the superior microorganisms;Staphylococcus aureus was the superior microorganism in the retail outlet. For environmental contact substances, Cooling platform, pallet, chopping block were the most serious contaminated environmental contact substances and the total bacteria counts were significant (p ) more than stainless steel barrel and chopper;Janthinobacterium was the superior microorganism on pallet, stainless steel barrel and chopper;Lactic acid bacteria was the superior microorganism on chopping block and stainless steel barrel;Staphylococcus aureus was the superior microorganism on cooling platform. Findings indicate that Escherichia coli, Yeast, Mildew, Lactic acid bacteria, Staphylococcus aureus, Janthinobacterium were the main microorganisms;Household workshop and the retail outlet were the main place microorganisms contaminated;Pallet, stainless steel barrel and chopper were the main environmental contact substances.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
In order to make equipment run safely, economically and continuously, some new maintenance models were put forward to improve the equipment after-sale maintenance service, such as E-maintenance, third-party maintenanc...In order to make equipment run safely, economically and continuously, some new maintenance models were put forward to improve the equipment after-sale maintenance service, such as E-maintenance, third-party maintenance, etc. To certain extent, the models solved the problem of the distance between the manufacturer and customer and the dispersion of the maintenance technologies, however, those resources are still widely distributed and do not collaborate efficiently. In this paper, a network-based collaborative maintenance service model was proposed for after-sales equipment to solve the problem of maintenance resources integration. Concretely, equipment designers, maintainers, spare parts suppliers and maintenance experts were grouped together to establish dynamic alliance. The leader of the alliance is the manufacturer under guaranty period or equipment user exceeding the guaranty period. The process of maintenance service was divided into three stages which are fault diagnosis, maintenance decision and maintenance implementation. The sub-alliances were established to carry out maintenance work at each stage. In addition, the business process of network-based collaborative maintenance was analyzed and collaborative business system for equipment＇s after-sales collaborative maintenance service was designed. In the end, an informational economics model of network-based collaborative maintenance was established to demonstrate the effectiveness of this maintenance model.展开更多
Exploring the mechanism for the formation of consumer purchase intentions of geographical indication agricultural products in the context of live-streaming sales can provide an important reference for brand marketing ...Exploring the mechanism for the formation of consumer purchase intentions of geographical indication agricultural products in the context of live-streaming sales can provide an important reference for brand marketing of geographical indication agricultural products.In this study,in-depth interviews were conducted with consumers of geographical indication agricultural products.Based on grounded theory,open coding,axial coding and selective coding were performed for interview text.Finally,21 concepts,7 subcategories and 3 main categories were obtained,and a model of the formation mechanism of the purchase intention of geographical indication agricultural products under the background of live-streaming sales was constructed,that is,"consumer cognition-consumer attitude-consumer behavior".Among them,consumer cognition includes two dimensions:the type of geographical indication agricultural products and the live-streaming appeal strategy,i.e.,the personal cognition of consumer and the promotion of live-streaming host's strategy.Consumer attitude is value perception of consumers,mainly including two dimensions of functional value and emotional value.Consumer behavior is the consumer's willingness to buy.It has been concluded that the types of geographical indication agricultural products interact with the live-streaming appeal strategies.Through the intermediary of consumers'value perception,consumers'purchase intention is generated.Among them,resource-oriented geographical indication agricultural products adopt rational live-streaming appeal strategies,which can enhance the consumer's perception of functional value,thereby promoting their purchase intention;and cultural and creative geographical indication agricultural products brands adopt perceptual live-streaming appeal strategies,which can enhance the emotional value perception of consumers,thereby promoting their purchase intention.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
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
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 stimulus to carry out this research is to investigate the relationship between internet advertisement and its features on the total E-commerce sales of the top five countries of Europe. The units of analysis are the individuals of UK, France, Italy, Germany and Netherland. Secondary data are collected from the reports of [1] (ADEX, 2010) and [2] (Eurostats, 2011). To empirically determine the relationship between independent variable and dependent variable in the European context, the study uses various statistical techniques, including OLS regression and correlation analysis techniques. The empirical findings indicate that the Internet advertisement features of search advertisement and classified advertisement have positive significant relationship with the E-commerce sales in Europe. The empirical findings indicate negative significant relationship of display advertisement with the E-commerce sales in Europe. However, this variable is also justified with the help of literature. Findings also demonstrate that search advertisement has strong positive relationship and it generates positive influence for the E-commerce sales as compared to the classified advertisement and display advertisement. Firms and marketers which are investing in online advertisement will find these results useful as they can get better sales and can use these features of online advertisement in order to maximize the sales of their products and services.
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.
文摘By using the characteristics of the new building in China, this article constructs the virtual repeat sale method to produce virtual repeat data which is similar to the repeat sale model on the house price index. Case-Shiller procedure and OFHEO method are used to calculate the house price index for new building in China. A discussion is given and furthering models are needed to take advantage of the virtual repeat sale data.
基金This project was supported by the National Natural Science Foundation of China (60573159)the Natural Science Foundation of Guangdong Province (05200302).
文摘Sale prediction plays a significant role in business management. By using support vector machine Regression （ε-SVR）, a method using to predict sale is illustrated. It takes historical data and current context data as inputs and presents results, i.e. sale tendency in the future and the forecasting sales, according to the user＇s specification of accuracy and time cycles. Some practical data experiments and the comparative tests with other algorithms show the advantages of the proposed approach in computation time and correctness.
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Cooling, transportation and sale processes of spiced geese were studied, eight spiced geese meat samples with different sampling time, Airborne microorganism samples of three different workplaces and five different environmental contact substance samples were test, measures of special mediums, biochemical identification and DNA sequencing were carried out, then Escherichia coli, Yeast, Mildew, Lactic acid bacteria, Staphylococcus aureus and Janthinobacterium were detected. For spiced geese meat samples, microorganisms were significant (p ) increased with the prolong of sampling time. Lactic acid bacteria, Staphylococcus aureus and Janthinobacterium were detected in each processing operation and the total aerobic counts of each sample was increased or significant (p ) increased with the prolong of sampling time;Escherichia coli, Yeast and Mildew were detected on samples entered into the retail outlet mainly and the total aerobic counts of each sample was increased or significant (p ) increased also. In the household workshop, Mildew and Janthinobacterium were the superior microorganisms. In the transport vehicle, Staphylococcus aureus and Janthinobacterium were the superior microorganisms;Staphylococcus aureus was the superior microorganism in the retail outlet. For environmental contact substances, Cooling platform, pallet, chopping block were the most serious contaminated environmental contact substances and the total bacteria counts were significant (p ) more than stainless steel barrel and chopper;Janthinobacterium was the superior microorganism on pallet, stainless steel barrel and chopper;Lactic acid bacteria was the superior microorganism on chopping block and stainless steel barrel;Staphylococcus aureus was the superior microorganism on cooling platform. Findings indicate that Escherichia coli, Yeast, Mildew, Lactic acid bacteria, Staphylococcus aureus, Janthinobacterium were the main microorganisms;Household workshop and the retail outlet were the main place microorganisms contaminated;Pallet, stainless steel barrel and chopper were the main environmental contact substances.
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 National Natural Science Foundation of China (Grant No. 70301012)National Hi-tech Research and Development Program of China (863 Program, Grant No. 2006AA04Z369-1)Innovative Talent Project of the Third Stage of "211" Project, Chongqing University, China (Grant No. S-09107)
文摘In order to make equipment run safely, economically and continuously, some new maintenance models were put forward to improve the equipment after-sale maintenance service, such as E-maintenance, third-party maintenance, etc. To certain extent, the models solved the problem of the distance between the manufacturer and customer and the dispersion of the maintenance technologies, however, those resources are still widely distributed and do not collaborate efficiently. In this paper, a network-based collaborative maintenance service model was proposed for after-sales equipment to solve the problem of maintenance resources integration. Concretely, equipment designers, maintainers, spare parts suppliers and maintenance experts were grouped together to establish dynamic alliance. The leader of the alliance is the manufacturer under guaranty period or equipment user exceeding the guaranty period. The process of maintenance service was divided into three stages which are fault diagnosis, maintenance decision and maintenance implementation. The sub-alliances were established to carry out maintenance work at each stage. In addition, the business process of network-based collaborative maintenance was analyzed and collaborative business system for equipment＇s after-sales collaborative maintenance service was designed. In the end, an informational economics model of network-based collaborative maintenance was established to demonstrate the effectiveness of this maintenance model.
基金Science and Technology Innovation Activity Program for Undergraduates in Zhejiang Province&Xinmiao Talent Program(2020R412051).
文摘Exploring the mechanism for the formation of consumer purchase intentions of geographical indication agricultural products in the context of live-streaming sales can provide an important reference for brand marketing of geographical indication agricultural products.In this study,in-depth interviews were conducted with consumers of geographical indication agricultural products.Based on grounded theory,open coding,axial coding and selective coding were performed for interview text.Finally,21 concepts,7 subcategories and 3 main categories were obtained,and a model of the formation mechanism of the purchase intention of geographical indication agricultural products under the background of live-streaming sales was constructed,that is,"consumer cognition-consumer attitude-consumer behavior".Among them,consumer cognition includes two dimensions:the type of geographical indication agricultural products and the live-streaming appeal strategy,i.e.,the personal cognition of consumer and the promotion of live-streaming host's strategy.Consumer attitude is value perception of consumers,mainly including two dimensions of functional value and emotional value.Consumer behavior is the consumer's willingness to buy.It has been concluded that the types of geographical indication agricultural products interact with the live-streaming appeal strategies.Through the intermediary of consumers'value perception,consumers'purchase intention is generated.Among them,resource-oriented geographical indication agricultural products adopt rational live-streaming appeal strategies,which can enhance the consumer's perception of functional value,thereby promoting their purchase intention;and cultural and creative geographical indication agricultural products brands adopt perceptual live-streaming appeal strategies,which can enhance the emotional value perception of consumers,thereby promoting their purchase intention.
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.
