According to the more severe competition and uncertain of economic environment, the corporate enterprise is to try to overcome them through advertising and sales promotion. As a result, the consumer may choose a new brand or can enhance the loyalty of the existing brands. If the sales promotion is implemented, the consumer purchase more quantity, buy earlier and stockpile in advance for future consumption.
This study is analysis of forwarding which occurred in case of sales promotion and estimating price increase. Additionally the transfer effect of forward buying is analyzed through intervention model. For this analysis the sales data of two product of automotive lubricant <Figure 1> are used. An Intervention model used for the study is a special kind of ARIMA model. The intervention is a series of indicator variables that represent the occurrence of event that affect the output variable.
For ARIMA model building, a regression analysis is performed. <Table 1> shows the result regression and 6 intervention event for premium product and 5 intervention are all statistically significant(<.05). Identification of both product based on ACF and PACF, several models are available as <Table 2>. Among the models, ARIMA(1,0,1)(0,0,0) for Premium product and ARIMA(1,0,0)(0,0,0) for Mass product are selected as the lower value of BIC is more suitable. According to ARIMA model procedure, both model evaluated and parameter estimation is <Table 3> and residual of ACF and PACF for both product is met the criteria accordingly the model is accepted.
After diagnosis of both intervention model, outlier is checked by plot of residuals. In case of premium product 2 outlier is observed as <Table 4>. These outlier is considered transfer effect of forwarding buying by mass product and additional intervention analysis is performed. <Table 5> shows new intervention model considering transfer effect and among 2 models ARIMA(1,0,1)(0,0,0) is selected by comparing BIC value. <Table 6> presents the parameters estimations of intervention model reflected transfer effect from mass product and all accepted. For diagnosis ACF and PACF of residual is plotted as <Figure 2> and criteria is met. Finally <Table 7> shows that applying transfer effect is most suitable model comparing accuracy by MAPE.
As a result of ARIMA intervention analysis, forward buying is come true before end of trade sales promotion in lubricants market. Also when the price increase is expected, forward buying on a large scare is implemented.
Comparing forward buying of premium products and mass products, transfer effect of forward buying is found when prices increase forecasted. It can be the additional cause of forward buying.
Based on the findings of this study, it is suggested that consumer sales promotion or retail sales promotion combined with trade promotion by manufacture. And immediate price increase is more effective considering forward buying effect. To prevent forward buying manufacturer can make use of average sales data from distribution channel. Especially when the price increment of limited product is executed, strategic approach must be developed to prohibit transfer of forward buying.
크라우드소싱 플랫폼의 디자인이 웹사이트 지각요소를 통해 소비자의 창의성에 미치는 영향
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