本文關(guān)鍵詞： 決策模型 前景理論 B2C電子商務(wù) 網(wǎng)絡(luò)口碑　出處：《華南理工大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著電子商務(wù)的蓬勃發(fā)展,網(wǎng)絡(luò)消費者表現(xiàn)出了愈來愈多的與以往不同的行為特征。如:隨著“雙11”活動越來越被消費者期待和認同,在活動開展的過程中,存在大量網(wǎng)絡(luò)消費者熬夜刷單、沖動消費(“剁手族”)、節(jié)后大量退貨等行為。這些行為在一定程度上反映了網(wǎng)絡(luò)消費者行為決策過程中的“有限理性”甚至是“非理性”的特點。因此,針對當(dāng)前網(wǎng)絡(luò)消費者的行為特征,本研究的目的在于:能夠合理地對網(wǎng)絡(luò)購物消費者“有限理性”或“非理性”行為決策過程進行正確的建模,從而為企業(yè)開展運營管理及服務(wù)營銷管理提供切實可行的建議。本研究主要內(nèi)容包括:(1)網(wǎng)絡(luò)購物情境下的消費者行為決策研究及建模。運用服務(wù)藍圖法確定服務(wù)流程各階段,將B2C電子商務(wù)服務(wù)流程分為決策、通達、交易、支付、物流和售后6個子流程階段;針對各個流程中的顧客行為決策建立價值函數(shù)、權(quán)重函數(shù)及前景函數(shù);通過引入直覺模糊數(shù)以完善數(shù)學(xué)模型;最后,通過定義多屬性決策問題,確定了京東、1號店和當(dāng)當(dāng)為備選方案集及相對應(yīng)的決策指標(biāo)屬性的結(jié)構(gòu)。(2)基于網(wǎng)絡(luò)口碑的決策模型定量化。在已建立的行為決策模型的基礎(chǔ)上,通過挖掘網(wǎng)絡(luò)口碑定量表示決策模型。首先,使用java編程語言,按照服務(wù)流程進行網(wǎng)絡(luò)口碑的分類,實現(xiàn)了基于SVM算法的網(wǎng)絡(luò)口碑服務(wù)流程分類模型;分類完成后,調(diào)用weka數(shù)據(jù)分析工具,對類內(nèi)的網(wǎng)絡(luò)口碑進行聚類分析。主要運用EM算法,確定了類內(nèi)聚類的簇數(shù)(即指標(biāo)數(shù)),并輔助QFD調(diào)研方法確定各個類中子決策指標(biāo)權(quán)重。經(jīng)過聚類后,各個子流程共得到13個決策指標(biāo);進一步使用ROST情感分析工具對網(wǎng)絡(luò)口碑進行情感評分,依據(jù)打分結(jié)果,按照情感正負極性分為兩類評價結(jié)果,并按照情感傾向程度的不同轉(zhuǎn)化為直覺三角模糊數(shù),從而實現(xiàn)模型的定量化。(3)基于前景理論的B2C消費者行為決策模型算例分析。對決策模型進行計算,主要應(yīng)用了直覺三角模糊數(shù)的相關(guān)運算性質(zhì),求出各個屬性下的前景值并得出綜合前景值。通過與期望效用理論構(gòu)建的決策行為模型進行比較,發(fā)現(xiàn)本文構(gòu)建的基于前景理論的行為決策模型能更貼近實際情況。此外,通過對結(jié)果進行排序分析,討論各個備選方案的優(yōu)劣程度,得到各個備選方案的管理啟示。研究結(jié)果表明:(1)總體上,京東商城綜合前景得分最高,1號店次之,當(dāng)當(dāng)網(wǎng)最低。但分析累積綜合得分發(fā)現(xiàn),1號店在前期服務(wù)水平落后于當(dāng)當(dāng)網(wǎng)的情況下,通過后階段高水平的服務(wù)提供,在總得分上超過了當(dāng)當(dāng)網(wǎng),這對企業(yè)如何實現(xiàn)服務(wù)補救具有參考價值;(2網(wǎng)絡(luò)口碑的聚類分析得到了13個評價指標(biāo),在這些指標(biāo)中,京東商城在其中7個指標(biāo)上前景值最優(yōu),1號店有4個前景值最優(yōu)。京東商城雖然得分最高,但其售后服務(wù)階段的得分卻低于其余兩者,導(dǎo)致總得分差距亦被縮小。而1號店最初得分較低,但通過出色的服務(wù)補救,最終得分排名第二。這充分說明,良好的服務(wù)補救策略對提升企業(yè)服務(wù)質(zhì)量具有重要的作用。
[Abstract]:With the rapid development of e-commerce, online consumers show different behavior characteristics more and more. Such as: with the "double 11" activities, more and more consumers expect and accept, in the course of activities carried out, there are a large number of network consumers stay single brush, impulsive consumption (chop hand family), after a large number of return behavior. These behaviors in a certain extent reflects the network consumer behavior in the decision-making process of "limited rationality" and "irrational" characteristics. Therefore, according to the behavior characteristics of the current network of consumers, the purpose of this research is to reasonably correct modeling of the decision making process of the online shopping consumer "limited rationality" or "irrational" behavior, so as to provide feasible suggestions for enterprises to carry out operations management and service marketing management. The main contents of this research include: (1) the network shopping situation Consumer behavior research and decision modeling. To determine the stage of service process by using service blueprint, B2C e-commerce service process is divided into decision-making, access, transaction, payment, logistics and customer service of 6 sub process; the decision of customer behavior in the process of establishing the value of each function, weight function and function by introducing the prospect; hundreds of perfect intuitionistic fuzzy mathematical model; finally, through the definition of multiple attribute decision making problems, determine the structure of Jingdong, and the corresponding decision attribute and Dangdang Shop No. 1 set for alternatives. (2) quantitative decision model based on the word-of-mouth network. Based on the behavior decision model has been established on the mining IWOM quantitative representation decision model. Firstly, using the Java programming language, the classification of word of mouth network according to the service process, the realization of the SVM algorithm of network flow classification model based on reputation service points; The class is completed, call the Weka data analysis tools, internet word-of-mouth on intra class cluster analysis. The main use of EM algorithm to determine the number of clusters within class clustering (i.e. index number), and make sure each kind of neutron decision index weight assisted QFD research methods. After clustering, the sub process there are 13 decision ROST index; the further use of sentiment analysis tools emotional score on the network reputation, according to evaluation results, according to the polarity of the emotion is divided into two categories according to the evaluation results, and different degree of transformation sentiment intuitionistic triangular fuzzy number, so as to realize the quantitative model. (3) cases based on the B2C consumer behavior decision model prospect theory. The decision model is calculated, the main application of the correlation algorithm of triangle intuitionistic fuzzy number, calculated each attribute the prospect value and the result of comprehensive prospect value. With the expected utility theory Compare the decision behavior model, found the behavior decision model of prospect theory based on more practical built in this paper. In addition, sorting through analysis of the results, discuss the extent of the various alternatives, get the management implications of various options. The results show that: (1) overall, the Jingdong mall comprehensive prospect the highest score, 1 stores and the lowest dangdang.com. But analysis of cumulative score, shop No. 1 in the pre service level behind the dangdang.com case, by providing a high level of service after the stage, in the total score more than that of dangdang.com, enterprise how to implement service recovery has the reference value; (cluster analysis of 2 online word-of-mouth got 13 evaluation indexes in these indicators, the 7 indicators in the mall Jingdong to view the optimal value, shop No. 1 has 4 prospect value optimization. Although most score mall Jingdong High, but its customer service service stage is lower than that of the rest of the two scores, resulting in a total score gap was also reduced. The No. 1 shop was originally a low score, but through excellent service recovery, the final score ranked second. This shows that the good service recovery strategy plays an important role in promoting enterprise service quality.

【學(xué)位授予單位】：華南理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：F713.55

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