【摘要】：生鮮電商發(fā)展越來越成熟,生鮮冷鏈配送市場也隨之興起,引領物流產(chǎn)業(yè),在眾多生鮮電商的發(fā)展中,運輸配送環(huán)節(jié)備受關注,不僅關乎配送成本,也影響到末端消費者的時間滿意度。所以線下社區(qū)店布局,利用O2O的優(yōu)勢來發(fā)展維護現(xiàn)有消費客戶,提升用戶體驗的做法被越來越多的專家和企業(yè)所認同,甚至已經(jīng)開始了市場探索和嘗試。而在生鮮電商O2O模式的探索過程中,線下社區(qū)店的布局選址則變成了最重要的問題。本文研究生鮮電商社區(qū)店的布局選址問題,針對傳統(tǒng)商業(yè)設施選址問題研究成果在需求覆蓋程度和服務時間體現(xiàn)的不足,文章利用最大覆蓋選址模型和服務覆蓋路徑概念解決需求覆蓋和服務時間的問題。生鮮電商社區(qū)店的選址問題和傳統(tǒng)商業(yè)設施選址及公共服務設施選址存在差異,通過對比傳統(tǒng)選址方法中各類影響因素分析,部分影響因素存在關聯(lián)性,總結出本文社區(qū)店選址內(nèi)外部影響因素,主要考慮影響因素為人口規(guī)模、人口結構、收入水平,通過具體數(shù)據(jù)分析得到對應影響系數(shù)α、β、m,每個影響因素在計算各社區(qū)電商需求量時起決定作用,根據(jù)影響系數(shù)計算出每個需求點的需求量。需求量是最終的目標最優(yōu)決策依據(jù),同時社區(qū)店選址考慮到建設成本和建設數(shù)量等約束條件,使用最大覆蓋模型滿足所有需求點被社區(qū)店覆蓋,同時滿足覆蓋的需求量最大。本文在建模的過程中考慮到生鮮電商的特性和消費者需求,融入了消費者的時間滿意度,在判斷社區(qū)覆蓋與否時提出覆蓋路徑概念。由于提供配送服務速度和距離已知,根據(jù)配送速度和配送距離來確定每個點之間的配送時間,以時間為消費者服務滿意的判斷標準,時間越短滿意度越高,當時間超出預定的范圍,判定該區(qū)域不在覆蓋范圍內(nèi)。本文通過定性分析和定量分析相結合,給出了適用該領域的最大覆蓋選址模型,從時間和覆蓋路徑角度重新定義了該模型,并通過具體案例求解,給出最優(yōu)方案。
[Abstract]:The development of fresh e-commerce is becoming more and more mature, and the fresh cold chain distribution market is also rising, leading the logistics industry. in the development of many fresh e-commerce, transportation and distribution links have attracted much attention, which is not only related to the cost of distribution. It also affects the time satisfaction of end consumers. Therefore, the offline community store layout, using the advantages of O2O to develop and maintain existing consumer customers, improve the user experience has been recognized by more and more experts and enterprises, and has even begun to explore and try the market. In the process of exploring the O2O model of fresh e-commerce, the layout and location of offline community stores has become the most important problem. In this paper, the layout and location of fresh ecommerce community stores is studied, and the research results on the location of traditional commercial facilities are insufficient in the degree of demand coverage and service time. In this paper, the maximum coverage location model and the concept of service coverage path are used to solve the problem of demand coverage and service time. There are differences between the location problem of fresh e-commerce community store and the location of traditional commercial facilities and public service facilities. By comparing all kinds of influencing factors in the traditional location method, some of the influencing factors are related. This paper summarizes the internal and external factors of community store location, mainly considering the population size, population structure, income level, through the specific data analysis to obtain the corresponding influence coefficients 偽, 尾, m, Each influencing factor plays a decisive role in calculating the demand of e-commerce in each community, and the demand of each demand point is calculated according to the influence coefficient. Demand is the final goal of the optimal decision-making basis, at the same time, considering the construction cost and construction quantity and other constraints, the maximum coverage model is used to meet all the demand points covered by the community store, and the demand to meet the coverage is the largest. In the process of modeling, considering the characteristics of fresh e-commerce and consumer demand, the time satisfaction of consumers is integrated, and the concept of coverage path is put forward when judging whether the community is covered or not. Since the speed and distance of providing distribution service are known, the distribution time between each point is determined according to the distribution speed and distribution distance, and the shorter the time is, the higher the satisfaction is. When the time exceeds the predetermined range, it is determined that the area is not covered. In this paper, through the combination of qualitative analysis and quantitative analysis, the maximum coverage location model suitable for this field is given, the model is redefined from the point of view of time and coverage path, and the optimal scheme is given by solving a concrete case.
【學位授予單位】：浙江工商大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：F326.6

【參考文獻】

相關期刊論文 前10條

1 紀漢霖;周金華;張深;;生鮮電商行業(yè)眾包模式研究[J];物流工程與管理;2016年01期

2 王小軍;蔣與峰;;電商時代傳統(tǒng)社區(qū)便利店經(jīng)營模式創(chuàng)新研究[J];中國集體經(jīng)濟;2016年01期

3 關穎;許評;王聞環(huán);;O2O的特點及模式探析[J];現(xiàn)代商業(yè);2015年30期

4 張良;班慧;宮談飛;王浩;;生鮮電商的社區(qū)物流共同配送模式研究[J];赤峰學院學報(自然科學版);2015年17期

5 肖建華;王飛;白煥新;李永開;;基于非等覆蓋半徑的生鮮農(nóng)產(chǎn)品配送中心選址[J];系統(tǒng)工程學報;2015年03期

6 褚玉婧;馬良;張惠珍;;時間滿意逐漸覆蓋電動汽車充電站選址及算法[J];數(shù)學的實踐與認識;2015年10期

7 王敬;方馨;;我國生鮮農(nóng)產(chǎn)品電子商務發(fā)展的研究[J];智富時代;2015年03期

8 艾格帆;張曉紅;張寧;潘婉瑩;尹世元;;構建基于O2O模式的長春市果蔬體驗館[J];物流工程與管理;2015年02期

9 張傳杰;李圓穎;;我國B2C生鮮電商供應鏈模式比較研究[J];當代經(jīng)濟;2015年03期

10 林建成;;中國石化易捷便利店打造O2O運營模式幾個關鍵問題的探索[J];石油庫與加油站;2014年06期

相關碩士學位論文 前6條

1 劉曉紅;中國電子商務O2O運營模式研究[D];吉林大學;2015年

2 陳明;基于空間連續(xù)需求的最大覆蓋模型在銀行業(yè)選址的應用[D];天津大學;2014年

3 楊向紅;基于GIS的最大化區(qū)域覆蓋的連續(xù)設施選址問題研究[D];清華大學;2013年

4 劉鵬;020本地生活服務電子商務模式研究[D];北京郵電大學;2012年

5 王天夫;消費者網(wǎng)絡團購消費偏好對O2O意向影響研究[D];東北大學;2012年

6 高建平;電動汽車充電站網(wǎng)絡規(guī)劃優(yōu)化研究[D];山東大學;2012年

，

本文編號：2495040