The stability of money demand function is an important issue in macroeconomic policy implementation. Money demand of Korean economy was estimated. Cointegration test with time dummy variables results show that there i...The stability of money demand function is an important issue in macroeconomic policy implementation. Money demand of Korean economy was estimated. Cointegration test with time dummy variables results show that there is not only long-run equilibrium relationship between money demand and macroeconomic variables, but also structural breaks in this equilibrium relationships. Least squares, state-space, and Marcov switching methods show that there also has been instability （or regime shifts） of parameters in money demand, especially over 1997 crisis and the early 2000s. This fact implies that monetary policy for stabilization might encounter big problems due to change （instability） of money demand.展开更多
Regional logistics demand forecast is the basis for government departments to make logistics planning and logistics related policies.It has the characteristics of a small amount of data and being nonlinear,so the trad...Regional logistics demand forecast is the basis for government departments to make logistics planning and logistics related policies.It has the characteristics of a small amount of data and being nonlinear,so the traditional prediction method can not guarantee the accuracy of prediction.Taking Xiamen City as an example,this paper selects the primary industry,the secondary industry,the tertiary industry,the total amount of investment in fixed assets,total import and export volume,per capita consumption expenditure,and the total retail sales of social consumer goods as the influencing factors,and uses a combining model least square and radial basis function(LS-RBF)neural network to analyze the related data from years 2000 to 2019,so as to predict the logistics demand from years 2020 to 2024.The model can well fit the training data,and the experimental results obtained from the comparison between the predicted value and the actual value in 2019 show that the error rate is very small.Therefore,the prediction results are reasonable and reliable.This method has high prediction accuracy,and it is suitable for irregular regional logistics demand forecast.展开更多
To address the fuzziness and variability in determining customer demand importance,a dynamic analysis method based on intuitionistic fuzzy numbers is proposed.First,selected customers use intuitionistic fuzzy numbers ...To address the fuzziness and variability in determining customer demand importance,a dynamic analysis method based on intuitionistic fuzzy numbers is proposed.First,selected customers use intuitionistic fuzzy numbers to represent the importance of each demand.Then,the preference information is aggregated using customer weights and time period weights through the intuitionistic fuzzy ordered weighted average operator,yielding a dynamic vector of the subjective importance of the demand index.Finally,the feasibility of the proposed method is demonstrated through an application example of a vibrating sorting screen.展开更多
This paper presents a copula technique to develop time-variant seismic fragility curves for corroded bridges at the system level and considers the realistic time-varying dependence among component seismic demands. Bas...This paper presents a copula technique to develop time-variant seismic fragility curves for corroded bridges at the system level and considers the realistic time-varying dependence among component seismic demands. Based on material deterioration mechanisms and incremental dynamic analysis, the time-evolving seismic demands of components were obtained in the form of marginal probability distributions. The time-varying dependences among bridge components were then captured with the best fitting copula function, which was selected from the commonly used copula classes by the empirical distribution based analysis method. The system time-variant fragility curves at different damage states were developed and the effects of time-varying dependences among components on the bridge system fragility were investigated. The results indicate the time-varying dependence among components significantly affects the time-variant fragility of the bridge system. The copula technique captures the nonlinear dependence among component seismic demands accurately and easily by separating the marginal distributions and the dependence among them.展开更多
This paper explores the use of archived data to calibrate volume delay functions (VDFs) and updates their input parameters (capacity and free-flow speed) for planning applications. The sensitivity analysis of speed to...This paper explores the use of archived data to calibrate volume delay functions (VDFs) and updates their input parameters (capacity and free-flow speed) for planning applications. The sensitivity analysis of speed to change in congestion level is performed to capture functional characteristics of VDFs in modeling specific facility types. Different sensitivity characteristics shown by the VDFs indicate that each function is suitable to a particular facility type. The results of sensitivity analysis are confirmed by the root mean square percent error (RMSPE) values calculated using the Orlando Urban Area Transportation Study (OUATS) model results and observed data. The modified Davidson’s function exhibits remarkable performance in nearly all facility types. The strength of the modified Davidson’s function across a broad range of facilities can be attributed to the flexibility of its tuning parameter, μ. Fitted Bureau of Public Road (BPR) and conical delay functions show lower RMSPE for uninterrupted flow facilities (freeways/expressways, managed lanes) and higher values for toll roads (which might have partial interruptions due to toll booths) and signalized arterials. Akcelik function underperforms on freeways/expressways and managed lanes but shows some improvements for toll roads and superior results for the signalized arterials. This was a desired strength of Akcelik function when modeling link travel speed on facilities where stopped delays were encountered.展开更多
Focused on finding out the relationship between passenger demands of P&R and its influencing factors, a nested-logit mode choice model was developed based on the characteristic of different modes and transfer rule...Focused on finding out the relationship between passenger demands of P&R and its influencing factors, a nested-logit mode choice model was developed based on the characteristic of different modes and transfer rules. The utility functions were given respectively according to the characteristic of each alternative. Passenger demands of different modes between O-D pairs were obtained by making use of the binary logit model. Then an equilibrium model for different modes was proposed. Under this condition, the approximate relationship between passenger demands of different modes and their characteristic indexes was modeled by the sensitivity analysis method. Shift volume among different modes was achieved by utilizing this model when their characteristic indexes were changed. A case study indicates that the model and algorithm presented in this paper are effective.展开更多
The existence of irreversible demand is tested, whereby price increases induce a different absolute magnitude of quantity change than price decreases. Irreversibility is potentially likely in retail food settings for ...The existence of irreversible demand is tested, whereby price increases induce a different absolute magnitude of quantity change than price decreases. Irreversibility is potentially likely in retail food settings for storable products that are consumed regularly and can affect pricing strategy performance. If irreversibility exists, the subsequent research question for storable product demand is whether loss aversion effects dominate stockpiling effects, or vice versa. A two-period theoretical model is developed, which predicts more elastic responses to downward price movements via stockpiling, but empirical tests on secondary data are needed to evaluate offsetting loss aversion effects. A variant of the Rotterdam demand model is developed to allow differential response to price increases and decreases. The model is applied to scanner data of short periodicity （weekly in this case）, which are necessary to measure meaningful demand responses to food price changes. The products selected are U.S. cheeses and table spreads that are storable over multiple weeks. The results suggest that stockpiling dominates loss aversion. One potential cause of this behavior may be that marketers asymmetrically provide consumers with more reference price information when lowering prices, but not when raising prices. When stockpiling effects dominate, given the typically price-elastic store-level demand for food products, high-low pricing strategies should produce higher revenue. Regarding measurement of average demand response, reversible demand models applied to weekly data may overestimate own-price elasticities.展开更多
Forecasting is predicting or estimating a future event or trend.Supply chains have been constantly growing in most countries ever since the industrial revolution of the 18th century.As the competitiveness between supp...Forecasting is predicting or estimating a future event or trend.Supply chains have been constantly growing in most countries ever since the industrial revolution of the 18th century.As the competitiveness between supply chains intensifies day by day,companies are shifting their focus to predictive analytics techniques to minimize costs and boost productivity and profits.Excessive inventory(overstock)and stock outs are very significant issues for suppliers.Excessive inventory levels can lead to loss of revenue because the company's capital is tied up in excess inventory.Excess inventory can also lead to increased storage,insurance costs and labor as well as lower and degraded quality based on the nature of the product.Shortages or out of stock can lead to lost sales and a decline in customer contentment and loyalty to the store.If clients are unable to find the right products on the shelves,they may switch to another vendor or purchase alternative items.Demand forecasting is valuable for planning,scheduling and improving the coordination of all supply chain activities.This paper discusses the use of neural networks for seasonal time series forecasting.Our objective is to evaluate the contribution of the correct choice of the transfer function by proposing a new form of the transfer function to improve the quality of the forecast.展开更多
文摘The stability of money demand function is an important issue in macroeconomic policy implementation. Money demand of Korean economy was estimated. Cointegration test with time dummy variables results show that there is not only long-run equilibrium relationship between money demand and macroeconomic variables, but also structural breaks in this equilibrium relationships. Least squares, state-space, and Marcov switching methods show that there also has been instability （or regime shifts） of parameters in money demand, especially over 1997 crisis and the early 2000s. This fact implies that monetary policy for stabilization might encounter big problems due to change （instability） of money demand.
基金Social Science Research Project of Education Department of Fujian Province,China(No.JAS160571)Key Project of Education and Teaching Reform of Undergraduate Universities in Fujian Province,China(No.FBJG20190130)Educational Research Project of Social Science for Young and Middle Aged Teachers in Fujian Province,China(No.JAS19371)。
文摘Regional logistics demand forecast is the basis for government departments to make logistics planning and logistics related policies.It has the characteristics of a small amount of data and being nonlinear,so the traditional prediction method can not guarantee the accuracy of prediction.Taking Xiamen City as an example,this paper selects the primary industry,the secondary industry,the tertiary industry,the total amount of investment in fixed assets,total import and export volume,per capita consumption expenditure,and the total retail sales of social consumer goods as the influencing factors,and uses a combining model least square and radial basis function(LS-RBF)neural network to analyze the related data from years 2000 to 2019,so as to predict the logistics demand from years 2020 to 2024.The model can well fit the training data,and the experimental results obtained from the comparison between the predicted value and the actual value in 2019 show that the error rate is very small.Therefore,the prediction results are reasonable and reliable.This method has high prediction accuracy,and it is suitable for irregular regional logistics demand forecast.
文摘To address the fuzziness and variability in determining customer demand importance,a dynamic analysis method based on intuitionistic fuzzy numbers is proposed.First,selected customers use intuitionistic fuzzy numbers to represent the importance of each demand.Then,the preference information is aggregated using customer weights and time period weights through the intuitionistic fuzzy ordered weighted average operator,yielding a dynamic vector of the subjective importance of the demand index.Finally,the feasibility of the proposed method is demonstrated through an application example of a vibrating sorting screen.
基金Natural Science Foundation of China under Grant No.51808376
文摘This paper presents a copula technique to develop time-variant seismic fragility curves for corroded bridges at the system level and considers the realistic time-varying dependence among component seismic demands. Based on material deterioration mechanisms and incremental dynamic analysis, the time-evolving seismic demands of components were obtained in the form of marginal probability distributions. The time-varying dependences among bridge components were then captured with the best fitting copula function, which was selected from the commonly used copula classes by the empirical distribution based analysis method. The system time-variant fragility curves at different damage states were developed and the effects of time-varying dependences among components on the bridge system fragility were investigated. The results indicate the time-varying dependence among components significantly affects the time-variant fragility of the bridge system. The copula technique captures the nonlinear dependence among component seismic demands accurately and easily by separating the marginal distributions and the dependence among them.
文摘This paper explores the use of archived data to calibrate volume delay functions (VDFs) and updates their input parameters (capacity and free-flow speed) for planning applications. The sensitivity analysis of speed to change in congestion level is performed to capture functional characteristics of VDFs in modeling specific facility types. Different sensitivity characteristics shown by the VDFs indicate that each function is suitable to a particular facility type. The results of sensitivity analysis are confirmed by the root mean square percent error (RMSPE) values calculated using the Orlando Urban Area Transportation Study (OUATS) model results and observed data. The modified Davidson’s function exhibits remarkable performance in nearly all facility types. The strength of the modified Davidson’s function across a broad range of facilities can be attributed to the flexibility of its tuning parameter, μ. Fitted Bureau of Public Road (BPR) and conical delay functions show lower RMSPE for uninterrupted flow facilities (freeways/expressways, managed lanes) and higher values for toll roads (which might have partial interruptions due to toll booths) and signalized arterials. Akcelik function underperforms on freeways/expressways and managed lanes but shows some improvements for toll roads and superior results for the signalized arterials. This was a desired strength of Akcelik function when modeling link travel speed on facilities where stopped delays were encountered.
基金Sponsored by the National Project from Ministry of Science and Technology,China(Grant No.2006BAJ18B03)
文摘Focused on finding out the relationship between passenger demands of P&R and its influencing factors, a nested-logit mode choice model was developed based on the characteristic of different modes and transfer rules. The utility functions were given respectively according to the characteristic of each alternative. Passenger demands of different modes between O-D pairs were obtained by making use of the binary logit model. Then an equilibrium model for different modes was proposed. Under this condition, the approximate relationship between passenger demands of different modes and their characteristic indexes was modeled by the sensitivity analysis method. Shift volume among different modes was achieved by utilizing this model when their characteristic indexes were changed. A case study indicates that the model and algorithm presented in this paper are effective.
文摘The existence of irreversible demand is tested, whereby price increases induce a different absolute magnitude of quantity change than price decreases. Irreversibility is potentially likely in retail food settings for storable products that are consumed regularly and can affect pricing strategy performance. If irreversibility exists, the subsequent research question for storable product demand is whether loss aversion effects dominate stockpiling effects, or vice versa. A two-period theoretical model is developed, which predicts more elastic responses to downward price movements via stockpiling, but empirical tests on secondary data are needed to evaluate offsetting loss aversion effects. A variant of the Rotterdam demand model is developed to allow differential response to price increases and decreases. The model is applied to scanner data of short periodicity （weekly in this case）, which are necessary to measure meaningful demand responses to food price changes. The products selected are U.S. cheeses and table spreads that are storable over multiple weeks. The results suggest that stockpiling dominates loss aversion. One potential cause of this behavior may be that marketers asymmetrically provide consumers with more reference price information when lowering prices, but not when raising prices. When stockpiling effects dominate, given the typically price-elastic store-level demand for food products, high-low pricing strategies should produce higher revenue. Regarding measurement of average demand response, reversible demand models applied to weekly data may overestimate own-price elasticities.
文摘Forecasting is predicting or estimating a future event or trend.Supply chains have been constantly growing in most countries ever since the industrial revolution of the 18th century.As the competitiveness between supply chains intensifies day by day,companies are shifting their focus to predictive analytics techniques to minimize costs and boost productivity and profits.Excessive inventory(overstock)and stock outs are very significant issues for suppliers.Excessive inventory levels can lead to loss of revenue because the company's capital is tied up in excess inventory.Excess inventory can also lead to increased storage,insurance costs and labor as well as lower and degraded quality based on the nature of the product.Shortages or out of stock can lead to lost sales and a decline in customer contentment and loyalty to the store.If clients are unable to find the right products on the shelves,they may switch to another vendor or purchase alternative items.Demand forecasting is valuable for planning,scheduling and improving the coordination of all supply chain activities.This paper discusses the use of neural networks for seasonal time series forecasting.Our objective is to evaluate the contribution of the correct choice of the transfer function by proposing a new form of the transfer function to improve the quality of the forecast.
