【摘要】：服裝市場(chǎng)是典型的供遠(yuǎn)大于需的買方市場(chǎng),在激烈的市場(chǎng)競(jìng)爭(zhēng)中,屬于短生命周期產(chǎn)品的服裝,具有較長(zhǎng)提前期、較短銷售期、較低期末殘值、快速需求變化等特點(diǎn),使得服裝供應(yīng)商難以準(zhǔn)確預(yù)測(cè)市場(chǎng)需求和銷量走勢(shì),我國(guó)傳統(tǒng)的訂貨會(huì)模式也無法快速響應(yīng)服裝流行趨勢(shì)和消費(fèi)者喜好的變換。很多服裝企業(yè)在進(jìn)行市場(chǎng)預(yù)測(cè)時(shí),往往缺乏科學(xué)周密的計(jì)劃方案,憑借個(gè)人經(jīng)驗(yàn)和主觀想法作出定性判斷,預(yù)測(cè)準(zhǔn)確性低,盲目地訂貨和補(bǔ)貨使得產(chǎn)量與未來銷售狀況不匹配,可能產(chǎn)生缺貨風(fēng)險(xiǎn)。然而更多的情況是服裝企業(yè)將面臨庫存積壓,增加了運(yùn)營(yíng)成本,減少了利潤(rùn)收入,影響自身的長(zhǎng)遠(yuǎn)發(fā)展。本文的研究對(duì)象是國(guó)內(nèi)某家一線品牌的時(shí)尚休閑服裝公司,生命周期短的特點(diǎn)在時(shí)尚類服裝上顯得更為突出。本文結(jié)合該服裝公司的產(chǎn)品特征和銷售數(shù)據(jù),通過數(shù)學(xué)方法來解決其銷量預(yù)測(cè)方面的難題,尋找可靠的預(yù)測(cè)方案提高時(shí)尚服裝銷售的預(yù)測(cè)精度。本文主要的研究成果,是運(yùn)用MATLAB作為編程工具,為服裝公司產(chǎn)品的生命周期進(jìn)行階段劃分,以及設(shè)計(jì)非參數(shù)核密度估計(jì)模型進(jìn)行預(yù)測(cè)。利用非參數(shù)核估計(jì)函數(shù)預(yù)測(cè)該公司各個(gè)品類服裝進(jìn)入生命期后的日銷量和總銷量,并對(duì)預(yù)測(cè)結(jié)果的準(zhǔn)確性進(jìn)行了檢驗(yàn)。在結(jié)果有效的基礎(chǔ)上,根據(jù)預(yù)測(cè)值對(duì)公司訂貨決策提出建議。本文的研究可以幫助服裝公司建立和完善預(yù)測(cè)系統(tǒng),為企業(yè)合理安排生產(chǎn)補(bǔ)貨計(jì)劃提供參考。
[Abstract]:Clothing market is a typical buyer's market. In the fierce market competition, clothing belongs to short life cycle products. It has the characteristics of longer lead time, shorter sales period, lower end-of-life residual value, rapid demand change, and so on, and the clothing market has the characteristics of long lead time, shorter sales period, lower end-of-term residual value and rapid demand change. It makes it difficult for clothing suppliers to accurately predict the market demand and sales trend, and the traditional order meeting pattern in China can not respond quickly to the change of fashion trend and consumer preference. When making market forecast, many garment enterprises often lack scientific and careful planning scheme, make qualitative judgment by virtue of personal experience and subjective thought, forecast accuracy is low, blindly order and replenish make output and future sales situation not match, There may be a risk of out-of-stock. However, more clothing companies will face a backlog of inventory, increased operating costs, reduced profits and income, affecting their long-term development. The research object of this paper is a fashion leisure clothing company with a first-line brand in China. The short life cycle is more prominent in fashion clothing. Combined with the product characteristics and sales data of the clothing company, this paper solves the difficult problems in the forecast of the sales volume of the clothing company by mathematical method, and looks for a reliable forecast scheme to improve the forecast precision of fashion clothing sales. The main research achievement of this paper is to use MATLAB as a programming tool to divide the life cycle of clothing company products and to design a non-parametric kernel density estimation model to predict the product life cycle. The non-parametric kernel estimation function is used to predict the daily and total sales of clothing in each category of the company, and the accuracy of the forecast results is tested. On the basis of the effective result, the paper puts forward some suggestions on the decision-making of the company's order according to the forecast. The research in this paper can help garment companies to establish and perfect the forecasting system, and provide reference for enterprises to arrange the production replenishment plan reasonably.
【學(xué)位授予單位】：浙江工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：F274;F426.86;F224

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