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
Accurate sales forecasting is essential in the fast-paced world of business for effective strategic planning and resource allocation. However, traditional forecasting methods often lack precision and flexibility. This...Accurate sales forecasting is essential in the fast-paced world of business for effective strategic planning and resource allocation. However, traditional forecasting methods often lack precision and flexibility. This study aims to address this issue by incorporating machine learning (ML) techniques to improve forecasting accuracy and responsiveness to market changes. The methodology involves gathering extensive sales data and carefully preprocessing it to ensure quality. Various ML algorithms, such as time series analysis, regression models, and neural networks, are utilized to account for the complex and non-linear nature of sales patterns. These models are trained and validated using historical sales data, taking into consideration external factors like economic indicators and consumer trends. The results show a significant enhancement in forecast accuracy compared to traditional methods. The ML models effectively capture underlying trends and seasonal variations, providing reliable predictions that closely match actual sales results. Additionally, the models demonstrate strong adaptability, quickly adjusting to unexpected market shifts.展开更多
The pharmaceutical industry is facing challenges due to various factors such as supply chain disruptions,changing consumer behavior,and regulatory changes.Accurate demand forecasting is essential to ensure an adequate...The pharmaceutical industry is facing challenges due to various factors such as supply chain disruptions,changing consumer behavior,and regulatory changes.Accurate demand forecasting is essential to ensure an adequate supply of drugs.The goal of this work is to forecast paracetamol product demand.For this purpose,we propose a hybrid forecasting model combining two effective forecasting techniques:SARIMA(Seasonal AutoRegressive Integrated Moving Average)and ANFIS(Adaptive Neuro-Fuzzy Inference System).This proposal consists of nonlinear components of time series by ANFIS and adjusting the result by the mean of the residuals of the SARIMA to improve the accuracy and performance of ANFIS predictions.Before the prediction phase,we preprocess our data and detect the anomalies in our dataset with Locally Selective Combination in Parallel Outlier Ensembles(LSCP).Then,by treating these anomalies as missing values,they are imputed using the combination of fuzzy-possibilistic c-means(FCM)with support vector regression(SVR)and a genetic algorithm(GA).Finally,we evaluate the performance of the model and some known models based on MAPE.We choose the hybrid model SARIMA-ANFIS that provides the most accurate and reliable forecasting.展开更多
UK manufacturers experienced a challenging start to 2024,with sales in the first quarter(Q1)down 10 per cent on the previous quarter,according to a report by Unleashed.However,year-on-year growth showed a modest incre...UK manufacturers experienced a challenging start to 2024,with sales in the first quarter(Q1)down 10 per cent on the previous quarter,according to a report by Unleashed.However,year-on-year growth showed a modest increase of 2 per cent,reflecting the Bank of England’s assessment of weak growth in the manufacturing sector.展开更多
Objective To analyze the improvement of the incentive mechanism of sales personnel in pharmaceutical company A,and to promote the smooth operation and further development of the company in a long term.Methods Compensa...Objective To analyze the improvement of the incentive mechanism of sales personnel in pharmaceutical company A,and to promote the smooth operation and further development of the company in a long term.Methods Compensation incentive,performance appraisal,welfare benefit,training incentive,promotion motivation and enterprise cultural inspiration were explored through questionnaires,telephone interviews and in-person interviews.Results and Conclusion This company’s incentive mechanism has problems in two aspects:Material incentives and spiritual incentives.As to the company’s characteristics and strategic development,the optimization countermeasures of incentive mechanism are proposed from the following three aspects:constructing a reasonable incentive system,establishing an efficient spiritual incentive mechanism,and implementing the dynamic incentive and differentiated incentive simultaneously.展开更多
With the rapid advancement of human economic levels and modern civilization,the automobile manufacturing industry is increasingly confronted with challenges related to energy scarcity and environmental pollution.Low c...With the rapid advancement of human economic levels and modern civilization,the automobile manufacturing industry is increasingly confronted with challenges related to energy scarcity and environmental pollution.Low carbon emissions and energy savings have become the main focus of automotive development.Under the influence of government incentives,the sales of household electric vehicles(EVs)have increased significantly,although they still represent a small share of the overall car market.To examine the factors influencing consumer purchases of household EVs,this report integrates both qualitative and quantitative analyses,controlling for single variables.Using linear regression,an empirical analysis was conducted on 18 BYD models with varying ranges and prices.The results indicate a strong positive correlation between driving range,selling price,and EV sales.Looking ahead,the development of new energy vehicles should prioritize longer ranges,high-quality features,and cost-effective performance.展开更多
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 livestreami...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.展开更多
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 introdu...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.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
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Accurate sales forecasting is essential in the fast-paced world of business for effective strategic planning and resource allocation. However, traditional forecasting methods often lack precision and flexibility. This study aims to address this issue by incorporating machine learning (ML) techniques to improve forecasting accuracy and responsiveness to market changes. The methodology involves gathering extensive sales data and carefully preprocessing it to ensure quality. Various ML algorithms, such as time series analysis, regression models, and neural networks, are utilized to account for the complex and non-linear nature of sales patterns. These models are trained and validated using historical sales data, taking into consideration external factors like economic indicators and consumer trends. The results show a significant enhancement in forecast accuracy compared to traditional methods. The ML models effectively capture underlying trends and seasonal variations, providing reliable predictions that closely match actual sales results. Additionally, the models demonstrate strong adaptability, quickly adjusting to unexpected market shifts.
文摘The pharmaceutical industry is facing challenges due to various factors such as supply chain disruptions,changing consumer behavior,and regulatory changes.Accurate demand forecasting is essential to ensure an adequate supply of drugs.The goal of this work is to forecast paracetamol product demand.For this purpose,we propose a hybrid forecasting model combining two effective forecasting techniques:SARIMA(Seasonal AutoRegressive Integrated Moving Average)and ANFIS(Adaptive Neuro-Fuzzy Inference System).This proposal consists of nonlinear components of time series by ANFIS and adjusting the result by the mean of the residuals of the SARIMA to improve the accuracy and performance of ANFIS predictions.Before the prediction phase,we preprocess our data and detect the anomalies in our dataset with Locally Selective Combination in Parallel Outlier Ensembles(LSCP).Then,by treating these anomalies as missing values,they are imputed using the combination of fuzzy-possibilistic c-means(FCM)with support vector regression(SVR)and a genetic algorithm(GA).Finally,we evaluate the performance of the model and some known models based on MAPE.We choose the hybrid model SARIMA-ANFIS that provides the most accurate and reliable forecasting.
文摘UK manufacturers experienced a challenging start to 2024,with sales in the first quarter(Q1)down 10 per cent on the previous quarter,according to a report by Unleashed.However,year-on-year growth showed a modest increase of 2 per cent,reflecting the Bank of England’s assessment of weak growth in the manufacturing sector.
文摘Objective To analyze the improvement of the incentive mechanism of sales personnel in pharmaceutical company A,and to promote the smooth operation and further development of the company in a long term.Methods Compensation incentive,performance appraisal,welfare benefit,training incentive,promotion motivation and enterprise cultural inspiration were explored through questionnaires,telephone interviews and in-person interviews.Results and Conclusion This company’s incentive mechanism has problems in two aspects:Material incentives and spiritual incentives.As to the company’s characteristics and strategic development,the optimization countermeasures of incentive mechanism are proposed from the following three aspects:constructing a reasonable incentive system,establishing an efficient spiritual incentive mechanism,and implementing the dynamic incentive and differentiated incentive simultaneously.
文摘With the rapid advancement of human economic levels and modern civilization,the automobile manufacturing industry is increasingly confronted with challenges related to energy scarcity and environmental pollution.Low carbon emissions and energy savings have become the main focus of automotive development.Under the influence of government incentives,the sales of household electric vehicles(EVs)have increased significantly,although they still represent a small share of the overall car market.To examine the factors influencing consumer purchases of household EVs,this report integrates both qualitative and quantitative analyses,controlling for single variables.Using linear regression,an empirical analysis was conducted on 18 BYD models with varying ranges and prices.The results indicate a strong positive correlation between driving range,selling price,and EV sales.Looking ahead,the development of new energy vehicles should prioritize longer ranges,high-quality features,and cost-effective performance.
文摘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.
基金Suzhou Agricultural Vocational and Technical College Young Teachers Research Ability Enhancement Program“Research and Screening of Bacteria for Fermented Beverages of Vice Tea and Loquat Flower”(Project No.QN[2022]01)。
文摘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.
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.
