消费者决策网络及应用研究
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摘要
消费环境的快速变化,使得消费者决策行为呈现出越来越明显的关联效应,消费者决策愈发“嵌入”到由各种各样关联关系构成的系统中,并涌现出各类复杂的市场现象。因此,研究消费者决策的关联性和嵌入性问题,对于解释日益复杂的消费行为和市场现象便具有了重要的意义。
基于此,文章提出从“关系”视角,来研究和剖析消费者决策的“关联性”和“嵌入性”,并提出了描述这一问题的消费者决策关联关系和消费者决策网络的概念。消费者决策关联关系是消费者决策“关联性”以及“嵌入性”发生的基础,在微观层面,决策关联关系作为属性影响个体消费者的决策,使得决策呈现“关联性”；在宏观层面消费者被“嵌入”到由大量错综复杂决策关联关系的消费者构成的系统当中,进行关联决策并涌现出各类复杂的市场现象。因此,只有厘清消费者决策关联关系,才能透彻研究消费者决策的“关联性”,只有描述清楚消费者决策关联而成的系统,才能分析消费者决策的“嵌入性”
而消费者决策网络是对消费者决策时嵌入的复杂系统的拓扑和描述,它首先是一个整体的概念,用来描述消费者决策的关联关系集合,体现了由纵横交错决策关联关系构成的系统对消费者决策的整体影响；其次是一种结构化的分析工具,用来研究不同的网络结构对消费者决策的影响。基于消费者决策网络研究消费者决策问题,不仅可以分析微观层面消费者决策的关联性,还可以分析微观层次个体消费者决策与宏观层面涌现的复杂市场现象之间的动态关联,进而可以有效的将微观层面的消费者决策问题研究与宏观层面的消费者决策问题研究以及复杂市场现象研究联系起来。在实践当中,消费者决策网络的研究,一方面可以帮助企业透视不同产品的消费者决策时如何相互关联,新产品如何在这个关联的网络中扩散,进而指导企业基于消费者决策网络做出更有效地营销决策；另一方面也可为政府部门规范和制定各种消费政策提供建议。
综述目前国内外学者相关方面的研究,发现消费者决策关联关系和消费者决策网络研究还存在几个问题：1)缺乏关于消费者决策网络形成基础的分析,即缺乏对消费者决策关联关系的分析；2)忽视消费者决策网络结构特征特殊性的研究；3)忽视消费者决策网络的情境性；4)对消费者决策网络动态演化分析不足。这些问题要求我们对消费者决策关联关系和消费者决策网络进行更加深入细致的研究和界定,从而为消费者决策网络及其应用提供更加坚实的理论基础和分析方法。
因此,文章在这一研究主旨之下,着重研究以下问题：
第一,界定清楚消费者决策关联关系的内涵和性质。消费者决策关联关系是消费者决策网络研究的基础,只有界定清楚消费者决策关联关系,才能为后续的研究提供基础。
第二,对消费者决策网络进行分析研究,包括概念、特征和分类等。对消费者决策网络的研究,文章从个体网络研究和整体网络研究两个方面展开,个体网络研究以特定消费者为中心的网络,而不研究除此消费者之外的其他消费者之间的关系；整体网络研究的是相对闭合集合内部由消费者之间所有关联关系构成的网络。
第三,界定清楚消费者决策个体网络的概念和性质。从理论上界定消费者决策个体网络的内涵和特征,并提出描述消费者决策个体网络的结构指标,以实例说明。
第四,界定清楚消费者决策整体网络的概念和性质,并提出描述整体网络的结构指标。进一步通过研究设计区别于经典的小世界网络和无标度网络算法的、具有消费者决策特性的消费者决策网络构造算法。通过这一算法,可以设计出更加切合实际的消费者决策整体网络模型。
第五,消费者决策网络的应用研究。基于消费者决策网络的内涵以及消费者决策网络的构造算法,模拟研究网络结构恒定和网络结构动态变化两种情境下,企业进行创新产品扩散时,如何基于消费者决策网络,或基于消费者之间的关联,选取有效的赠样目标,进而保证赠样策略的成功。
针对以上问题,文章进行了研究,并得出如下的研究结论：
第一,对消费者决策关联关系进行了理论界定和实例描述。消费者决策关联关系是指消费者在购买决策过程中与能够影响其决定是否购买某种产品的其他人之间形成的,以实现满意决策为目的关系。进一步,文章对它的类型、性质进行了理论研究,并通过特定的实例对特定消费群体的决策关联关系类型及其影响,决策关联关系的性质及其影响等进行了统计分析。
第二,对消费者决策网络进行了基础研究。首先界定了消费者决策网络的概念,它是用于描述和映射消费者决策过程关联而成的关系及其表现出来的不同网络结构,即描述特定时刻特定产品购买决策关联关系的“总和”。进一步从概念本质分析了它的基本特征：1)嵌入性,2)网络价值性,3)结构效应性,4)动态复杂性,并提出可从决策主体、客体两个方面对消费者决策网络进行分类,其中按照决策主体研究范围,可以将消费者决策网络分为消费者决策个体网络和消费者决策整体网络。基于这一分类,后续研究重点针对消费者决策个体网络和整体网络进行了研究。
第三,对消费者决策个体网络的内涵、特征进行了理论界定,提出了描述消费者决策个体网络的指标,并通过实例进行说明。消费者决策个体网络描述了由特定消费对象决定的以研究对象消费者为中心形成的相对稳定的决策关联关系体系,它具有与消费者决策网络同样的特征。并提出了描述消费者决策个体网络的指标：平均网络规模、关系构成比例、相似性程度、关系亲密性程度、决策趋同性程度、网络演化特征以及度分布特征。在此基础上通过设计问卷,对特定对象的消费者决策个体网络进行了实例研究,并从7类网络指标上,对其进行了统计分析。
第四,对消费者决策整体网络的内涵、特征进行了理论研究,消费者决策整体网络是指由特定消费对象决定的相对闭合集合内的消费者及其决策关联关系集合,它不仅是消费者决策关联关系集合的描述工具,更是研究消费者决策网络结构对消费者决策行为影响的一种有效的分析工具。以此为基础,文章设计了一类具体的,能够反映消费者决策特殊性的消费者决策整体网络算法,这一算法设计考虑了消费者决策整体网络的增长性、优先连接机制,同时考虑了消费者决策网络的特殊性,如局域世界特性、新节点的异质性、网络的动态演化特性等；进-步,结合消费者决策整体网络特征,提出了一系列描述消费者决策整体网络的结构指标。在此基础上,模拟了基于消费者决策整体网络算法的四个网络,并对模型的结构特征等进行了描述和研究。
第五,消费者决策网络应用研究。基于消费者决策网络的构造算法,模拟了两类具有不同结构特征的网络,一是网络结构恒定的网络,一是网络结构随着消费者决策行为不断变化的网络。研究了在这两种网络下,企业在进行创新产品扩散时,该如何选取有效的赠样目标,以保证赠样策略的成功。
据此,本文的创新点可以归纳为以下三个方面：
第一,对消费者决策的“关联性”和“嵌入性”进行了“关系”视角的研究,提出了描述消费者决策“关联性”的决策关联关系的概念,并提出了描述和拓扑消费者决策“嵌入”的决策关联系统的消费者决策网络的概念。从而为系统研究消费者决策的这两种属性及其效用,提供了基础的概念体系和分析方法。
第二,对消费者决策关联关系和消费者决策网络进行了系统的研究。提出了描述消费者决策网络的结构化指标体系,设计了区别于经典网络构造算法的新的、基于消费者决策独特性的消费者决策网络构造算法,且通过模拟证明了该算法能够在一定程度上反映现实消费者决策网络的基本特征。
第三,基于消费者决策网络的结构恒定和演化两种情境,研究了企业如何基于消费者决策网络进行有效的赠样目标选择,以促进产品在市场中的快速扩散。此处消费者决策网络的演化,即动态性研究是对前文消费者决策网络研究的扩展和补充,其演化的规则是基于消费者决策行为的,体现了行为和结构的协同演化。
The decision-making behavior of consumers shows more and more obvious correlation, due to rapid changing in consumer environment. So the Consumer's decision-making increasingly "embedded" into the complex system, which is constituted by various correlative relationships, and it emerges in various types of complex market phenomena. Therefore, it is very important to interpret the increasingly complex consumer behavior and complex market phenomena, from the study of correlation and embedded of the consumers'decision-making.
Thus, this paper presents to research the "correlative" and "embedded" of consumers'decision-making from the perspective of "relationship", and presents the consumer decision-making relationship and the consumer's decision-making network to describe it. The consumer decision-making relationship is The Foundation of the "correlative" and "embedded" of consumers'decision-making. At the micro level, the consumer decision-making relationship affect the individual consumer's decision-making as attributes, and making it to appear "correlative"; at the macro, the consumer is "embedded" into the system, which is composed of large number of Complicated consumer decision-making relationships. Consumers make correlative decision in the system and emerge in various types of complex market phenomena. Therefore, only to clarify the nature of the consumer decision-making relationship, we can study the "correlative" of consumers'decision making thoroughly. Only to descript the associated system clearly, we can analyze the "embedded" of consumers'decision making
The consumer's decision-making network is the topology and description of the complex system which the consumers embedded in. firstly it is an overall concept to describe the collection of consumer decision-making relationships, and it reflects the overall impact of the system on consumer's decision-making, which is constituted by the crisscrossing relationships. Secondly, it is a structured analysis tool used to study the effects of different network structures on consumer's decision-making. Application of the consumer's decision-making network to study consumer's decision-making problems, not only can analyze the "correlative" of consumer's decision-making in micro-level, but also can analyze the dynamic link between the individual consumer's decision-making and the emerging complex market phenomena in macro-level. In turn, it also can correlate the individual consumer and the study of consumer decision-making problems with macro-level and the complex market phenomena research effectively. In practice, the research on consumer decision-making network, On the one hand, can help companies to understand how consumers relate to each other when they make decisions to buy different products, and How new product diffuse in this network. Then it can guide enterprises to make more effective marketing decisions based on consumer network characteristics. On the other hand, it can also provide advice to government departments to regulate and develop a variety of consumer policy.
Research on the current relevant study, we can find there are several network research questions on these studies, which lacking of the analysis on the basis of consumer decision-making network formation, namely the consumer decision-making relationship,lacking of the research of the particularity of consumer decision-making structure, ignoring the situation of consumer decision-making network, and are inadequate on the analysis of the dynamic evolution of the consumer's decision-making and other aspects of network analysis. These issues require us to study and definition consumer decision-making relationship and consumer decision-making networks more intensive, thus providing a more solid theoretical basis and analysis methods for the research on the consumer decision-making network and it application.
Therefore, under the guidelines, this article mainly researches the following key questions:
First, we define the content and nature of the consumer decision-making relationship clearly. It is the foundation of the study on consumer decision-making network. Only clearly define consumer decision-making relationship, which can provide a basis for further research.
Second, we analysis and study of consumer decision-making networks, including basic concepts, characteristics and classification, etc. the research on consumer decision network is mainly in two fields, the consumer decision-making individual networks and the consumer decision-making whole networks.:the individual network research on the specific consumer-centric network, rather than the relationship between other consumers outside the specific consumers. The whole network research on the network, which is constitute by all relationship between consumers in a relatively closed set.
Third, we define the concept and the nature of the consumer decision-making individual network clearly. We theoretically define the meaning and characteristics of the consumer decision-making individual network, and propose the structure indicators to describe it, and then we use an example to descript and illustrate it.
Fourth, we define the concept and the nature of the consumer decision-making whole network, and proposed structure indicators to describe it. Further, we need to study and design new algorithm of the consumer decision-making network, which is able to distinguish with small-world network design and scale-free network algorithm, and can reflect the characteristics of the consumers'decision-making. With this algorithm, we can design a more realistic model of consumer decision-making network.
Fifth, the application of consumer decision research network. Based on the content of Consumer decision-making network and its construction algorithm, we simulation two scenarios, the constant structure network and the dynamic structure network, in which we study how the enterprises select a valid Sampling Targets for New Product, based on the consumer decision-making network, or the consumer decision-making relationship, to ensure the success of sampling strategy.
Combining these analyzes content, this paper draw the following conclusions:
First, we define the consumer decision-making relationship theoretically and description it with empirical examples. The consumer decision relationship is formed between the consumer and other people, which can influence the consumer's decision-making, and to achieve a satisfactory purpose of decision-making. And further we theoretically analyze the content and nature of consumer decision-making relationship. We also statistical analyze the types and nature of the consumer decision-making relationship and their effects on decision making, through an empirical example of specific consumer groups.
Second, we study the consumer decision-making network basically, including the concept, characteristics and classification of consumer decision-making networks, First, we define the concept of consumer decision-making network, which is used to describe and mapping the relationship between the consumer decision-making process and different network structures they performance, namely to describe "sum" of the consumer decision-making relationship with given moment and particular product. Further we analysis its basic characteristics:1) embeddedness;2) the value of the network;3) the effect of the structure;4) dynamic complexity; And put forward to classify it from two aspects of the subject and the object of decision-making. In accordance with the scope of the subject studied, we can divide the consumer decision-making network into consumer decision-making individual network and consumer decision-making whole network. Further, based on this classification, the follow-up study will focus on these two networks.
Third, this paper theoretically analyzes the content and features of consumer decision-making individual network, and design indices system to reflect the network characteristics, and use an empirical example to illustrate it. The consumer decision-making individual network describes a relatively stable system of decision-making relationship, which is consumer-centric and determined by specific consumer object. It has the same characteristics with consumer decision-making network. Then we proposed the structure indicators to describe it:average network size, relationship structure, similarity, relationship intimacy, decision-making convergence, network evolution characteristics and the degree distribution. Based on this, we make an empirical study on a specific consumer decision-making individual network, and analysis statistical it from the seven categories indicators, through the design of the questionnaire.
Fourth, this paper research on the content and features of consumer decision-making whole network theoretically. The consumer decision-making whole network is a set of consumers and their decision-making relationships in a relatively closed set, which is determined by specific consumer objects. It is not only a tool to describe the set of consumer decision-making relationships, but also a tool to analyze to research the effects of the structure of the consumer decision-making network on the consumer's decision-making.
Based on this we design a particular class of algorithm to construct consumer decision-making whole network, which reflect the special nature of the consumer decision-making. This algorithm is designed to consider the growth and the preferential attachment mechanism of consumer decision-making whole network, but also to consider the particularity of it, such as the local world properties, the heterogeneity of the new node and the dynamic evolution of the network. Further, combined the characteristics of consumer decision-making whole network, we propose a series of structure indices to describe it. On this basis, we simulate four networks, according to the algorithm of consumer decision-making whole network, and describe and study the structure and characteristics of them.
Fifth, the application of consumer decision research network. Based on the construction algorithm of consumer decision-making network, we simulation two network, the constant structure network and the dynamic structure network with the consumer's behavior. And we study in the two networks how the enterprises select a valid Sampling Targets for New Product to ensure the success of sampling strategy.
Accordingly, the innovation of this paper can be summarized as the following three aspects:
First, we research on the "correlative" and "embedded" of consumers' decision-making from the perspective of "relationship", and presents the consumer decision-making relationship to describe the "correlative" and The consumer's decision-making network to topology and describe of the complex economic system which the consumers "embedded" in. So we provide a basic conception system and analytical methods to study the two properties of consumer decision-making and their effectiveness.
Second, we research on the consumer decision-making relationship and the consumer decision-making network systematically, and propose the structure indicators to describe the consumer decision-making network, and design new algorithm of the consumer decision-making network, which is able to distinguish with classic network algorithm, and can reflect the characteristics of the consumers' decision-making. Through simulation, we prove that the algorithm can reflect the reality of the basic characteristics of consumer decision-making networks to some extent.
Third, based on the two scenarios, the constant structure network and the dynamic structure network, we study how the enterprises select valid sampling targets for new product to ensure the success of sampling strategy. Here, the dynamic study of consumer decision-making networks is to extend and complement of earlier studies, the rules of the evolution of the consumer decision-making network is based on its decision-making behavior and reflecting the cooperative evolution of behavior and structure.
基于此,文章提出从“关系”视角,来研究和剖析消费者决策的“关联性”和“嵌入性”,并提出了描述这一问题的消费者决策关联关系和消费者决策网络的概念。消费者决策关联关系是消费者决策“关联性”以及“嵌入性”发生的基础,在微观层面,决策关联关系作为属性影响个体消费者的决策,使得决策呈现“关联性”；在宏观层面消费者被“嵌入”到由大量错综复杂决策关联关系的消费者构成的系统当中,进行关联决策并涌现出各类复杂的市场现象。因此,只有厘清消费者决策关联关系,才能透彻研究消费者决策的“关联性”,只有描述清楚消费者决策关联而成的系统,才能分析消费者决策的“嵌入性”
而消费者决策网络是对消费者决策时嵌入的复杂系统的拓扑和描述,它首先是一个整体的概念,用来描述消费者决策的关联关系集合,体现了由纵横交错决策关联关系构成的系统对消费者决策的整体影响；其次是一种结构化的分析工具,用来研究不同的网络结构对消费者决策的影响。基于消费者决策网络研究消费者决策问题,不仅可以分析微观层面消费者决策的关联性,还可以分析微观层次个体消费者决策与宏观层面涌现的复杂市场现象之间的动态关联,进而可以有效的将微观层面的消费者决策问题研究与宏观层面的消费者决策问题研究以及复杂市场现象研究联系起来。在实践当中,消费者决策网络的研究,一方面可以帮助企业透视不同产品的消费者决策时如何相互关联,新产品如何在这个关联的网络中扩散,进而指导企业基于消费者决策网络做出更有效地营销决策；另一方面也可为政府部门规范和制定各种消费政策提供建议。
综述目前国内外学者相关方面的研究,发现消费者决策关联关系和消费者决策网络研究还存在几个问题：1)缺乏关于消费者决策网络形成基础的分析,即缺乏对消费者决策关联关系的分析；2)忽视消费者决策网络结构特征特殊性的研究；3)忽视消费者决策网络的情境性；4)对消费者决策网络动态演化分析不足。这些问题要求我们对消费者决策关联关系和消费者决策网络进行更加深入细致的研究和界定,从而为消费者决策网络及其应用提供更加坚实的理论基础和分析方法。
因此,文章在这一研究主旨之下,着重研究以下问题：
第一,界定清楚消费者决策关联关系的内涵和性质。消费者决策关联关系是消费者决策网络研究的基础,只有界定清楚消费者决策关联关系,才能为后续的研究提供基础。
第二,对消费者决策网络进行分析研究,包括概念、特征和分类等。对消费者决策网络的研究,文章从个体网络研究和整体网络研究两个方面展开,个体网络研究以特定消费者为中心的网络,而不研究除此消费者之外的其他消费者之间的关系；整体网络研究的是相对闭合集合内部由消费者之间所有关联关系构成的网络。
第三,界定清楚消费者决策个体网络的概念和性质。从理论上界定消费者决策个体网络的内涵和特征,并提出描述消费者决策个体网络的结构指标,以实例说明。
第四,界定清楚消费者决策整体网络的概念和性质,并提出描述整体网络的结构指标。进一步通过研究设计区别于经典的小世界网络和无标度网络算法的、具有消费者决策特性的消费者决策网络构造算法。通过这一算法,可以设计出更加切合实际的消费者决策整体网络模型。
第五,消费者决策网络的应用研究。基于消费者决策网络的内涵以及消费者决策网络的构造算法,模拟研究网络结构恒定和网络结构动态变化两种情境下,企业进行创新产品扩散时,如何基于消费者决策网络,或基于消费者之间的关联,选取有效的赠样目标,进而保证赠样策略的成功。
针对以上问题,文章进行了研究,并得出如下的研究结论：
第一,对消费者决策关联关系进行了理论界定和实例描述。消费者决策关联关系是指消费者在购买决策过程中与能够影响其决定是否购买某种产品的其他人之间形成的,以实现满意决策为目的关系。进一步,文章对它的类型、性质进行了理论研究,并通过特定的实例对特定消费群体的决策关联关系类型及其影响,决策关联关系的性质及其影响等进行了统计分析。
第二,对消费者决策网络进行了基础研究。首先界定了消费者决策网络的概念,它是用于描述和映射消费者决策过程关联而成的关系及其表现出来的不同网络结构,即描述特定时刻特定产品购买决策关联关系的“总和”。进一步从概念本质分析了它的基本特征：1)嵌入性,2)网络价值性,3)结构效应性,4)动态复杂性,并提出可从决策主体、客体两个方面对消费者决策网络进行分类,其中按照决策主体研究范围,可以将消费者决策网络分为消费者决策个体网络和消费者决策整体网络。基于这一分类,后续研究重点针对消费者决策个体网络和整体网络进行了研究。
第三,对消费者决策个体网络的内涵、特征进行了理论界定,提出了描述消费者决策个体网络的指标,并通过实例进行说明。消费者决策个体网络描述了由特定消费对象决定的以研究对象消费者为中心形成的相对稳定的决策关联关系体系,它具有与消费者决策网络同样的特征。并提出了描述消费者决策个体网络的指标：平均网络规模、关系构成比例、相似性程度、关系亲密性程度、决策趋同性程度、网络演化特征以及度分布特征。在此基础上通过设计问卷,对特定对象的消费者决策个体网络进行了实例研究,并从7类网络指标上,对其进行了统计分析。
第四,对消费者决策整体网络的内涵、特征进行了理论研究,消费者决策整体网络是指由特定消费对象决定的相对闭合集合内的消费者及其决策关联关系集合,它不仅是消费者决策关联关系集合的描述工具,更是研究消费者决策网络结构对消费者决策行为影响的一种有效的分析工具。以此为基础,文章设计了一类具体的,能够反映消费者决策特殊性的消费者决策整体网络算法,这一算法设计考虑了消费者决策整体网络的增长性、优先连接机制,同时考虑了消费者决策网络的特殊性,如局域世界特性、新节点的异质性、网络的动态演化特性等；进-步,结合消费者决策整体网络特征,提出了一系列描述消费者决策整体网络的结构指标。在此基础上,模拟了基于消费者决策整体网络算法的四个网络,并对模型的结构特征等进行了描述和研究。
第五,消费者决策网络应用研究。基于消费者决策网络的构造算法,模拟了两类具有不同结构特征的网络,一是网络结构恒定的网络,一是网络结构随着消费者决策行为不断变化的网络。研究了在这两种网络下,企业在进行创新产品扩散时,该如何选取有效的赠样目标,以保证赠样策略的成功。
据此,本文的创新点可以归纳为以下三个方面：
第一,对消费者决策的“关联性”和“嵌入性”进行了“关系”视角的研究,提出了描述消费者决策“关联性”的决策关联关系的概念,并提出了描述和拓扑消费者决策“嵌入”的决策关联系统的消费者决策网络的概念。从而为系统研究消费者决策的这两种属性及其效用,提供了基础的概念体系和分析方法。
第二,对消费者决策关联关系和消费者决策网络进行了系统的研究。提出了描述消费者决策网络的结构化指标体系,设计了区别于经典网络构造算法的新的、基于消费者决策独特性的消费者决策网络构造算法,且通过模拟证明了该算法能够在一定程度上反映现实消费者决策网络的基本特征。
第三,基于消费者决策网络的结构恒定和演化两种情境,研究了企业如何基于消费者决策网络进行有效的赠样目标选择,以促进产品在市场中的快速扩散。此处消费者决策网络的演化,即动态性研究是对前文消费者决策网络研究的扩展和补充,其演化的规则是基于消费者决策行为的,体现了行为和结构的协同演化。
The decision-making behavior of consumers shows more and more obvious correlation, due to rapid changing in consumer environment. So the Consumer's decision-making increasingly "embedded" into the complex system, which is constituted by various correlative relationships, and it emerges in various types of complex market phenomena. Therefore, it is very important to interpret the increasingly complex consumer behavior and complex market phenomena, from the study of correlation and embedded of the consumers'decision-making.
Thus, this paper presents to research the "correlative" and "embedded" of consumers'decision-making from the perspective of "relationship", and presents the consumer decision-making relationship and the consumer's decision-making network to describe it. The consumer decision-making relationship is The Foundation of the "correlative" and "embedded" of consumers'decision-making. At the micro level, the consumer decision-making relationship affect the individual consumer's decision-making as attributes, and making it to appear "correlative"; at the macro, the consumer is "embedded" into the system, which is composed of large number of Complicated consumer decision-making relationships. Consumers make correlative decision in the system and emerge in various types of complex market phenomena. Therefore, only to clarify the nature of the consumer decision-making relationship, we can study the "correlative" of consumers'decision making thoroughly. Only to descript the associated system clearly, we can analyze the "embedded" of consumers'decision making
The consumer's decision-making network is the topology and description of the complex system which the consumers embedded in. firstly it is an overall concept to describe the collection of consumer decision-making relationships, and it reflects the overall impact of the system on consumer's decision-making, which is constituted by the crisscrossing relationships. Secondly, it is a structured analysis tool used to study the effects of different network structures on consumer's decision-making. Application of the consumer's decision-making network to study consumer's decision-making problems, not only can analyze the "correlative" of consumer's decision-making in micro-level, but also can analyze the dynamic link between the individual consumer's decision-making and the emerging complex market phenomena in macro-level. In turn, it also can correlate the individual consumer and the study of consumer decision-making problems with macro-level and the complex market phenomena research effectively. In practice, the research on consumer decision-making network, On the one hand, can help companies to understand how consumers relate to each other when they make decisions to buy different products, and How new product diffuse in this network. Then it can guide enterprises to make more effective marketing decisions based on consumer network characteristics. On the other hand, it can also provide advice to government departments to regulate and develop a variety of consumer policy.
Research on the current relevant study, we can find there are several network research questions on these studies, which lacking of the analysis on the basis of consumer decision-making network formation, namely the consumer decision-making relationship,lacking of the research of the particularity of consumer decision-making structure, ignoring the situation of consumer decision-making network, and are inadequate on the analysis of the dynamic evolution of the consumer's decision-making and other aspects of network analysis. These issues require us to study and definition consumer decision-making relationship and consumer decision-making networks more intensive, thus providing a more solid theoretical basis and analysis methods for the research on the consumer decision-making network and it application.
Therefore, under the guidelines, this article mainly researches the following key questions:
First, we define the content and nature of the consumer decision-making relationship clearly. It is the foundation of the study on consumer decision-making network. Only clearly define consumer decision-making relationship, which can provide a basis for further research.
Second, we analysis and study of consumer decision-making networks, including basic concepts, characteristics and classification, etc. the research on consumer decision network is mainly in two fields, the consumer decision-making individual networks and the consumer decision-making whole networks.:the individual network research on the specific consumer-centric network, rather than the relationship between other consumers outside the specific consumers. The whole network research on the network, which is constitute by all relationship between consumers in a relatively closed set.
Third, we define the concept and the nature of the consumer decision-making individual network clearly. We theoretically define the meaning and characteristics of the consumer decision-making individual network, and propose the structure indicators to describe it, and then we use an example to descript and illustrate it.
Fourth, we define the concept and the nature of the consumer decision-making whole network, and proposed structure indicators to describe it. Further, we need to study and design new algorithm of the consumer decision-making network, which is able to distinguish with small-world network design and scale-free network algorithm, and can reflect the characteristics of the consumers'decision-making. With this algorithm, we can design a more realistic model of consumer decision-making network.
Fifth, the application of consumer decision research network. Based on the content of Consumer decision-making network and its construction algorithm, we simulation two scenarios, the constant structure network and the dynamic structure network, in which we study how the enterprises select a valid Sampling Targets for New Product, based on the consumer decision-making network, or the consumer decision-making relationship, to ensure the success of sampling strategy.
Combining these analyzes content, this paper draw the following conclusions:
First, we define the consumer decision-making relationship theoretically and description it with empirical examples. The consumer decision relationship is formed between the consumer and other people, which can influence the consumer's decision-making, and to achieve a satisfactory purpose of decision-making. And further we theoretically analyze the content and nature of consumer decision-making relationship. We also statistical analyze the types and nature of the consumer decision-making relationship and their effects on decision making, through an empirical example of specific consumer groups.
Second, we study the consumer decision-making network basically, including the concept, characteristics and classification of consumer decision-making networks, First, we define the concept of consumer decision-making network, which is used to describe and mapping the relationship between the consumer decision-making process and different network structures they performance, namely to describe "sum" of the consumer decision-making relationship with given moment and particular product. Further we analysis its basic characteristics:1) embeddedness;2) the value of the network;3) the effect of the structure;4) dynamic complexity; And put forward to classify it from two aspects of the subject and the object of decision-making. In accordance with the scope of the subject studied, we can divide the consumer decision-making network into consumer decision-making individual network and consumer decision-making whole network. Further, based on this classification, the follow-up study will focus on these two networks.
Third, this paper theoretically analyzes the content and features of consumer decision-making individual network, and design indices system to reflect the network characteristics, and use an empirical example to illustrate it. The consumer decision-making individual network describes a relatively stable system of decision-making relationship, which is consumer-centric and determined by specific consumer object. It has the same characteristics with consumer decision-making network. Then we proposed the structure indicators to describe it:average network size, relationship structure, similarity, relationship intimacy, decision-making convergence, network evolution characteristics and the degree distribution. Based on this, we make an empirical study on a specific consumer decision-making individual network, and analysis statistical it from the seven categories indicators, through the design of the questionnaire.
Fourth, this paper research on the content and features of consumer decision-making whole network theoretically. The consumer decision-making whole network is a set of consumers and their decision-making relationships in a relatively closed set, which is determined by specific consumer objects. It is not only a tool to describe the set of consumer decision-making relationships, but also a tool to analyze to research the effects of the structure of the consumer decision-making network on the consumer's decision-making.
Based on this we design a particular class of algorithm to construct consumer decision-making whole network, which reflect the special nature of the consumer decision-making. This algorithm is designed to consider the growth and the preferential attachment mechanism of consumer decision-making whole network, but also to consider the particularity of it, such as the local world properties, the heterogeneity of the new node and the dynamic evolution of the network. Further, combined the characteristics of consumer decision-making whole network, we propose a series of structure indices to describe it. On this basis, we simulate four networks, according to the algorithm of consumer decision-making whole network, and describe and study the structure and characteristics of them.
Fifth, the application of consumer decision research network. Based on the construction algorithm of consumer decision-making network, we simulation two network, the constant structure network and the dynamic structure network with the consumer's behavior. And we study in the two networks how the enterprises select a valid Sampling Targets for New Product to ensure the success of sampling strategy.
Accordingly, the innovation of this paper can be summarized as the following three aspects:
First, we research on the "correlative" and "embedded" of consumers' decision-making from the perspective of "relationship", and presents the consumer decision-making relationship to describe the "correlative" and The consumer's decision-making network to topology and describe of the complex economic system which the consumers "embedded" in. So we provide a basic conception system and analytical methods to study the two properties of consumer decision-making and their effectiveness.
Second, we research on the consumer decision-making relationship and the consumer decision-making network systematically, and propose the structure indicators to describe the consumer decision-making network, and design new algorithm of the consumer decision-making network, which is able to distinguish with classic network algorithm, and can reflect the characteristics of the consumers' decision-making. Through simulation, we prove that the algorithm can reflect the reality of the basic characteristics of consumer decision-making networks to some extent.
Third, based on the two scenarios, the constant structure network and the dynamic structure network, we study how the enterprises select valid sampling targets for new product to ensure the success of sampling strategy. Here, the dynamic study of consumer decision-making networks is to extend and complement of earlier studies, the rules of the evolution of the consumer decision-making network is based on its decision-making behavior and reflecting the cooperative evolution of behavior and structure.
引文
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