本文選題：知識 + 客戶隱性知識��； 參考：《鄭州大學(xué)》2017年碩士論文

【摘要】：21世紀是知識經(jīng)濟時代,知識成為價值創(chuàng)造的核心來源。電子商務(wù)的迅速普及與發(fā)展,帶給企業(yè)的不僅是機遇,還有挑戰(zhàn)。在電子商務(wù)背景下,“買方市場”特征進一步凸顯。及時、準確、系統(tǒng)、深入地認知客戶,迅速而高效地滿足客戶需求,成為企業(yè)生存與發(fā)展的關(guān)鍵所在。通過電子商務(wù)平臺與渠道,企業(yè)可獲得大量有關(guān)客戶及其消費特征的數(shù)據(jù),其中蘊含了有關(guān)客戶消費行為與潛能的隱性知識,能為企業(yè)開展精準營銷、有效提升客戶滿意度以及培育客戶忠誠度奠定堅實基礎(chǔ)。有鑒于此,基于電子商務(wù)背景,在獲得企業(yè)大量客戶相關(guān)數(shù)據(jù)的基礎(chǔ)上,本文謀求通過對前述相關(guān)數(shù)據(jù)的甄別與預(yù)處理,設(shè)計客戶隱性知識獲取的完備機制,以此指導(dǎo)電子商務(wù)企業(yè)開展精準客戶細分、有針對性地制定并落實客戶關(guān)系維系與改進的措施和方案,從而重塑企業(yè)核心競爭力,實現(xiàn)可持續(xù)發(fā)展。首先,本文分析了論文的選題背景,主要體現(xiàn)在四個方面:產(chǎn)品同質(zhì)化嚴重;“買方市場”形成;企業(yè)營銷壓力增大;電子商務(wù)帶來機遇和挑戰(zhàn)�；跇I(yè)內(nèi)現(xiàn)存問題與未來發(fā)展趨勢,提出了本文研究的出發(fā)點以及相關(guān)研究內(nèi)容與方法。而后,對知識、隱性知識、客戶知識管理等相關(guān)理論進行了綜述研究,并對粗糙集的理論與方法進行了簡要探討。其次,在客戶知識的基礎(chǔ)上,本文對“客戶隱性知識”的內(nèi)涵進行了分析與界定,在此基礎(chǔ)上討論并歸納了客戶隱性知識的類型與特征。而后,分析了電子商務(wù)背景下獲取客戶隱性知識的基本過程,綜合應(yīng)用Spearman非參數(shù)統(tǒng)計方法、信息熵法、遺傳算法以及粗糙集相關(guān)理論與方法,分析并設(shè)計了對客戶隱性知識源數(shù)據(jù)的預(yù)處理、屬性離散化以及屬性集約簡的算法模型,并基于此設(shè)計、提出了客戶隱性規(guī)則的提取方法。最后,本文采用實證研究方法,基于××電子商務(wù)公司客戶相關(guān)數(shù)據(jù),通過SPSS和Rosetta兩套工具軟件,完成對前述相關(guān)模型與方法的實證分析。
[Abstract]:The 21st century is the era of knowledge economy, knowledge has become the core source of value creation.The rapid popularization and development of e-commerce bring not only opportunities but also challenges to enterprises.In the background of e-commerce, the characteristics of buyer's market are more prominent.Timely, accurate, systematic, in-depth understanding of customers, quickly and efficiently to meet customer needs, become the key to the survival and development of enterprises.Through e-commerce platforms and channels, enterprises can obtain a lot of data about customers and their consumption characteristics, which contains tacit knowledge about customer consumption behavior and potential, and can carry out accurate marketing for enterprises.Effectively improve customer satisfaction and cultivate customer loyalty to lay a solid foundation.In view of this, based on the background of electronic commerce, and on the basis of obtaining a large number of customer related data, this paper seeks to design a complete mechanism of customer tacit knowledge acquisition by discriminating and preprocessing the aforementioned relevant data.In order to guide e-commerce enterprises to carry out accurate customer segmentation, targeted development and implementation of customer relationship maintenance and improvement measures and programs, so as to reshape the core competitiveness of enterprises to achieve sustainable development.First of all, this paper analyzes the background of the thesis, mainly reflected in four aspects: product homogeneity; "buyer's market" formation; increased marketing pressure; e-commerce brings opportunities and challenges.Based on the existing problems and the future development trend, this paper puts forward the starting point of this study and related research contents and methods.Then, the theories of knowledge, tacit knowledge and customer knowledge management are summarized, and the theory and method of rough set are discussed briefly.Secondly, on the basis of customer knowledge, this paper analyzes and defines the connotation of "customer tacit knowledge", and then discusses and summarizes the types and characteristics of customer tacit knowledge.Then, the paper analyzes the basic process of obtaining customer's tacit knowledge under the background of electronic commerce, and synthetically applies Spearman non-parametric statistical method, information entropy method, genetic algorithm and rough set related theory and method.The algorithm model of preprocessing attribute discretization and attribute set reduction of customer tacit knowledge source data is analyzed and designed. Based on this design a customer implicit rule extraction method is proposed.Finally, this paper uses the empirical research method, based on the customer data of 脳 脳 E-commerce company, through the SPSS and Rosetta two sets of tools software, completed the empirical analysis of the above relevant models and methods.
【學(xué)位授予單位】：鄭州大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F724.6;F274

【參考文獻】

相關(guān)期刊論文 前10條

1 湯超穎;丁雪辰;;創(chuàng)新型企業(yè)研發(fā)團隊知識基礎(chǔ)與知識創(chuàng)造的關(guān)系研究[J];科學(xué)學(xué)與科學(xué)技術(shù)管理;2015年09期

2 李金海;梅長林;張紅英;張曉;;基于遺傳算法的決策形式背景的屬性約簡方法及其在決策分析中的應(yīng)用[J];小型微型計算機系統(tǒng);2015年08期

3 王鷗;;隱性知識對提升企業(yè)核心能力的研究[J];生產(chǎn)力研究;2015年03期

4 楊晨暉;張德鵬;;創(chuàng)新顧客研發(fā)團隊的隱性知識傳播[J];企業(yè)經(jīng)濟;2014年10期

5 侯榮濤;史鑫明;路郁;;一種基于粗糙集和信息熵理論的屬性離散化算法[J];計算機應(yīng)用與軟件;2014年03期

6 范鈞;郭立強;聶津君;;網(wǎng)絡(luò)能力、組織隱性知識獲取與突破性創(chuàng)新績效[J];科研管理;2014年01期

7 游達明;朱思文;;突破性技術(shù)創(chuàng)新中隱性知識吸收過程及規(guī)律研究[J];科技進步與對策;2014年06期

8 李柏洲;趙健宇;蘇屹;;團隊知識共享意愿、非正式隱性知識交流與知識創(chuàng)造的關(guān)系研究[J];情報理論與實踐;2013年09期

9 王舉范;陳卓;;基于信息熵的粗糙集連續(xù)屬性多變量離散化算法[J];青島科技大學(xué)學(xué)報(自然科學(xué)版);2013年04期

10 張樹中;;知識創(chuàng)新過程的隱性知識轉(zhuǎn)移機理研究[J];圖書情報工作;2013年04期

相關(guān)碩士學(xué)位論文 前2條

1 周凡程;粗糙集理論在數(shù)據(jù)離散化中的應(yīng)用研究[D];國防科學(xué)技術(shù)大學(xué);2012年

2 張永明;基于電子商務(wù)活動的客戶知識管理及客戶價值挖掘研究[D];南京理工大學(xué);2007年

，

本文編號：1755896