Multivariable Linear Regression Model for Promotional Forecasting:The Coca Cola - Morrisons Case

This paper describes a promotional forecasting model, built by linear regression module in Microsoft Excel. It intends to provide quick and reliable forecasts with a moderate credit and to assist the CPFR between the Coca Cola Enterprises (CCE) and the Morrisons. The model is derived from previous researches and literature review on CPFR, promotion, forecasting and modelling. It is designed as a multivariable linear regression model, which involves several promotional mix as variables including percentage discount, display, and holidays. Before modelling, all data and variables have been tested for their validity by two tests: the trend test and the up/downlift-average test. The model has also been conducted twice: the first time is to use a part of the data to define the structure of the model and the second time is to use all the data to finalize the model by deciding its coefficients. The model is capable to make forecast for 26 products and to forecast for several new promotions. The performance of this model is satisfactory in terms of the adjusted R2 (over 80%) and the MAPE (lower than 20%). A user-friendly interface is also provided to facilitate the use of the model in the actual forecasting. However, the model can be further improved both from the modelling method and the variable refining

Identification of Baicalin as an Immunoregulatory Compound by Controlling TH17 Cell Differentiation

TH17 cells have been implicated in a growing list of inflammatory disorders. Antagonism of TH17 cells can be used for the treatment of inflammatory injury. Currently, very little is known about the natural compound controlling the differentiation of TH17 cells. Here, we showed that Baicalin, a compound isolated from a Chinese herb, inhibited TH17 cell differentiation both in vitro and in vivo. Baicalin might inhibit newly generated TH17 cells via reducing RORγt expression, and together with up-regulating Foxp3 expression to suppress RORγt-mediated IL-17 expression in established TH17 cells. In vivo treatment with Baicalin could inhibit TH17 cell differentiation, restrain TH17 cells infiltration into kidney, and protect MRL/lpr mice against nephritis. Our findings not only demonstrate that Baicalin could control TH17 cell differentiation but also suggest that Baicalin might be a promising therapeutic agent for the treatment of TH17 cells-mediated inflammatory diseases

Multivariable Linear Regression Model for Promotional Forecasting:The Coca Cola - Morrisons Case

This paper describes a promotional forecasting model, built by linear regression module in Microsoft Excel. It intends to provide quick and reliable forecasts with a moderate credit and to assist the CPFR between the Coca Cola Enterprises (CCE) and the Morrisons. The model is derived from previous researches and literature review on CPFR, promotion, forecasting and modelling. It is designed as a multivariable linear regression model, which involves several promotional mix as variables including percentage discount, display, and holidays. Before modelling, all data and variables have been tested for their validity by two tests: the trend test and the up/downlift-average test. The model has also been conducted twice: the first time is to use a part of the data to define the structure of the model and the second time is to use all the data to finalize the model by deciding its coefficients. The model is capable to make forecast for 26 products and to forecast for several new promotions. The performance of this model is satisfactory in terms of the adjusted R2 (over 80%) and the MAPE (lower than 20%). A user-friendly interface is also provided to facilitate the use of the model in the actual forecasting. However, the model can be further improved both from the modelling method and the variable refining

How does internal migration affect the emotional health of elderly parents left-behind?

The ageing population resulting from the one-child policy and massive flows of internal migration in China pose major challenges to elderly care in rural areas where elderly support is based on a traditional inter-generational family support mechanism. We use data from the China Health and Retirement Longitudinal Study to examine how migration of an adult child affects the emotional health of elderly parents left-behind. We identify the effects using fixed effects and IV approaches which rely on different sources of variation. We find that migration reduces happiness by 6.6 percentage points and leads to a 3.3 percentage points higher probability of loneliness. CES-D scores of elderly parents are severely increased pushing average scores close to the cut-off indicating clinical levels of depressive symptoms. As emotional health is a key determinant of the overall health status, our findings have significant impacts on economic development in China