基于在线评论的消费者非理性购买行为模糊推理研究
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摘要
在市场经济条件下,消费者不是像经济学中假设的一样完全理性,而是常常做出非理性的购买决策。随着互联网和信息技术的高速发展,越来越多的消费者采用网络消费形式进行购买并在网上发表相关评论。这些在线评论不但蕴含了大量有关产品和服务的信息,而且蕴含了有关消费者个人情感和心理特质的信息。运用情感计算和文本挖掘技术,可以从在线评论中获取与网络消费者非理性购买行为相关的信息。在线评论中的情感语义资源具有模糊属性,借助模糊数学理论,可以更好的深入了解消费者,预测其购买行为。在此基础上,本文将模糊数学理论方法应用于网络消费者的非理性购买行为研究。具体内容如下：
首先,介绍本研究的背景、现状及意义。通过研究已有的文献发现,目前消费者非理性研究主要集中在对影响消费者非理性因素的研究上,比较琐碎,缺乏系统性的研究框架。另外,大多数对消费者非理性行为的研究集中在传统购物环境中,对网络环境中的消费者非理性购买研究较少。
其次,综合已有的文献,借鉴已有的研究成果并分析研究中的不足,设计出新的研究方法对网络消费者非理性购买行为进行研究。本文通过对在线评论的内容进行分析处理,结合模糊数学理论对在线评论中的情感词汇和评价词汇构建模糊语义模型,给出了消费者综合情感和评价模糊集的计算方法。本文根据认知语言学和消费心理学等理论,依据情感程度的高低将消费者非理性程度分为7个等级,并用模糊集对各个级别进行表不。
本文采用模糊模式识别方法,计算消费者综合情感模糊集与非理性程度模式的接近度,对消费者的非理性程度进行识别。本文构建了消费者非理性购买的模糊推理模型,以外部诱导因素,内部诱导因素,消费者非理性程度作为前件,消费者非理性购买倾向作为后件,构建推理规则库,对网络消费者非理性购买行为进行模糊推理。
最后,选取两个商家,互联网上获取消费者对二者的在线评论,并结合二者的实际网络营销情况,得到两个商家在特定营销策略下消费者的非理性购买行为倾向,证明了所提方法的可行性。
本文将在线评论文本处理技术和模糊数学计算和推理方法应用到网络消费者的非理性购买研究之中,是对网络消费者非理性购买进行的一种有益的探索。采用的模糊模式识别方法,实现了由在线评论中的主观性信息来识别消费者的非理性程度。构建网络消费者非理性购买行为模型和模糊推理规则库,更好地适应了网络环境特点,对消费者在网络环境中的非理性购买行为预测提供了可能。同时,本文对于消费者指导自身消费行为,对于营销者了解市场行情和产品动态,实现个性化营销对策选择、个性化产品推荐具有重要现实意义。
Under the conditions of market economy, consumers are not perfectly rational as the same as the hypothesis in economics, but often make irrational buying decision. With the Internet and the information technology developing at high speed, more and more consumer choice to consume and to publish relevant comments online. These online comments contain not only the information of consumers' personal emotional and psychological characteristics, but also the information about relevant products and services. Using sentiment calculation and text mining technology, the information about consumers' irrational buying behavior can be got from online comments. The semantic resources of online comments have fuzzy attributes, and with the aid of the fuzzy mathematical theory, consumers'buying behavior can be better understood and predicted. On this basis, this thesis applied fuzzy mathematics method to the analysis of online consumers' irrational buying behavior. Specific contents are shown as follows.
Firstly, this thesis introduces the background, the research status and the meaning of the analysis of consumers'irrational purchasing behaviors. Through existing literatures, it was found that most research focused on the factors that influence consumers'irrational, which are trivial and lack of the systematic research framework. In addition, most studies focused on consumers' irrational buying in the way of traditional shopping, but fewer studies focused on it in the network environment.
Secondly, taking the existing results as reference and analysis problems in existing literatures, the new method on analyzing the online consumers' irrational buying behavior was designed. The content of online comments was analyzed with the help of Fuzzy semantic model of emotional words based on fuzzy mathematics knowledge, and the method of calculating consumers'comprehensive sentiment fuzzy sets was given. Base on the consumer psychology and cognitive linguistics theory, consumers'irrational degree is divided into seven levels according to their sentiment degree, and each level was expressed by fuzzy set. This thesis adopted the fuzzy pattern recognition method, and calculated the approach degree between the fuzzy sets of consumers'comprehensive sentiment and irrational degree, which enforce consumers'irrational degree reorganization. The thesis established the fuzzy reasoning model and rules base of consumers'irrational buying, which take external cues, internal cues and the consumer characteristics as former antecedents, consumers'irrational buying tendency as later antecedents and realize the fuzzy reasoning of online consumers' irrational buying behavior.
Finally, two companies were selected, and online comments on the two companies by their consumers on Internet were accessed. Combined with actual situation of network marketing of the two companies, the tendency of consumers'irrational buying behavior in certain marketing strategy was got. In this way, the feasibility of the proposed method was proved.
This thesis applied online review text processing technology and fuzzy mathematics calculation and reasoning method to the research of consumers'irrational buying behavior, which is an advanced exploration of consumers'irrational theory. Using the fuzzy pattern recognition method, the irrational buying behavior model and reasoning rules base was established, which is adapt to the characteristics of the online comments, and the consumers' irrational level can be identified through the emotional information contained by the online comments, which makes the forecast of consumers'irrational buying behavior. At the same time, this article has great advantage for consumers to instruct their own consumption behavior, and has important practical significance for marketers to understand trends of market and product and to choose personalized marketing countermeasures and realize personalized products recommendation.
首先,介绍本研究的背景、现状及意义。通过研究已有的文献发现,目前消费者非理性研究主要集中在对影响消费者非理性因素的研究上,比较琐碎,缺乏系统性的研究框架。另外,大多数对消费者非理性行为的研究集中在传统购物环境中,对网络环境中的消费者非理性购买研究较少。
其次,综合已有的文献,借鉴已有的研究成果并分析研究中的不足,设计出新的研究方法对网络消费者非理性购买行为进行研究。本文通过对在线评论的内容进行分析处理,结合模糊数学理论对在线评论中的情感词汇和评价词汇构建模糊语义模型,给出了消费者综合情感和评价模糊集的计算方法。本文根据认知语言学和消费心理学等理论,依据情感程度的高低将消费者非理性程度分为7个等级,并用模糊集对各个级别进行表不。
本文采用模糊模式识别方法,计算消费者综合情感模糊集与非理性程度模式的接近度,对消费者的非理性程度进行识别。本文构建了消费者非理性购买的模糊推理模型,以外部诱导因素,内部诱导因素,消费者非理性程度作为前件,消费者非理性购买倾向作为后件,构建推理规则库,对网络消费者非理性购买行为进行模糊推理。
最后,选取两个商家,互联网上获取消费者对二者的在线评论,并结合二者的实际网络营销情况,得到两个商家在特定营销策略下消费者的非理性购买行为倾向,证明了所提方法的可行性。
本文将在线评论文本处理技术和模糊数学计算和推理方法应用到网络消费者的非理性购买研究之中,是对网络消费者非理性购买进行的一种有益的探索。采用的模糊模式识别方法,实现了由在线评论中的主观性信息来识别消费者的非理性程度。构建网络消费者非理性购买行为模型和模糊推理规则库,更好地适应了网络环境特点,对消费者在网络环境中的非理性购买行为预测提供了可能。同时,本文对于消费者指导自身消费行为,对于营销者了解市场行情和产品动态,实现个性化营销对策选择、个性化产品推荐具有重要现实意义。
Under the conditions of market economy, consumers are not perfectly rational as the same as the hypothesis in economics, but often make irrational buying decision. With the Internet and the information technology developing at high speed, more and more consumer choice to consume and to publish relevant comments online. These online comments contain not only the information of consumers' personal emotional and psychological characteristics, but also the information about relevant products and services. Using sentiment calculation and text mining technology, the information about consumers' irrational buying behavior can be got from online comments. The semantic resources of online comments have fuzzy attributes, and with the aid of the fuzzy mathematical theory, consumers'buying behavior can be better understood and predicted. On this basis, this thesis applied fuzzy mathematics method to the analysis of online consumers' irrational buying behavior. Specific contents are shown as follows.
Firstly, this thesis introduces the background, the research status and the meaning of the analysis of consumers'irrational purchasing behaviors. Through existing literatures, it was found that most research focused on the factors that influence consumers'irrational, which are trivial and lack of the systematic research framework. In addition, most studies focused on consumers' irrational buying in the way of traditional shopping, but fewer studies focused on it in the network environment.
Secondly, taking the existing results as reference and analysis problems in existing literatures, the new method on analyzing the online consumers' irrational buying behavior was designed. The content of online comments was analyzed with the help of Fuzzy semantic model of emotional words based on fuzzy mathematics knowledge, and the method of calculating consumers'comprehensive sentiment fuzzy sets was given. Base on the consumer psychology and cognitive linguistics theory, consumers'irrational degree is divided into seven levels according to their sentiment degree, and each level was expressed by fuzzy set. This thesis adopted the fuzzy pattern recognition method, and calculated the approach degree between the fuzzy sets of consumers'comprehensive sentiment and irrational degree, which enforce consumers'irrational degree reorganization. The thesis established the fuzzy reasoning model and rules base of consumers'irrational buying, which take external cues, internal cues and the consumer characteristics as former antecedents, consumers'irrational buying tendency as later antecedents and realize the fuzzy reasoning of online consumers' irrational buying behavior.
Finally, two companies were selected, and online comments on the two companies by their consumers on Internet were accessed. Combined with actual situation of network marketing of the two companies, the tendency of consumers'irrational buying behavior in certain marketing strategy was got. In this way, the feasibility of the proposed method was proved.
This thesis applied online review text processing technology and fuzzy mathematics calculation and reasoning method to the research of consumers'irrational buying behavior, which is an advanced exploration of consumers'irrational theory. Using the fuzzy pattern recognition method, the irrational buying behavior model and reasoning rules base was established, which is adapt to the characteristics of the online comments, and the consumers' irrational level can be identified through the emotional information contained by the online comments, which makes the forecast of consumers'irrational buying behavior. At the same time, this article has great advantage for consumers to instruct their own consumption behavior, and has important practical significance for marketers to understand trends of market and product and to choose personalized marketing countermeasures and realize personalized products recommendation.
引文
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