消费者行为意向的前因与作用机理研究述评
2014-11-26刘春济
刘春济
摘要:在消费者行为研究领域,行为意向的前因及其作用机理研究一直备受关注。通过对典型研究成果的回顾发现,既有研究呈现出了一定的动态发展特征,且围绕三条主要线索展开:即以质量、价值、满意为主要前置变量;以理性行为等理论为基础;引入新变量或重塑既有模型。基于上述分析,提出了完善相关研究的建议。
关键词:消费者行为意向;前因;作用机理
中图分类号:F713
文献标识码:A文章编号:1001-8409(2014)11-0107-04
Antecedents and Effect Mechanism of Behavioral Intention
LIU Chunji
(School of Business, Shanghai Normal University, Shanghai 200234;
School of Business, East China Normal University, Shanghai 200241)
Abstract:
Antecedents and effect mechanism of consumer behavioral intention has received considerable attention in the field of consumer behavior. This paper reviews a series of typical studies, and research shows that the main approach of current studies including: taking quality, value and satisfaction as main antecedents; studying based on the theory of reasoned action and so on; using new variables or refining the existing models. It analyzes the main viewpoints and puts forward some proposals for future study.
Key words: consumer behavioral intention; antecedent; effect mechanism
意向是行为表现的必须过程,该变量对行为具有重要的预测作用,大量的实证研究均已证明了这一点[1];同时,行为意向的多维度性也基本上成了一种共识[2]。但学术界对影响行为意向的前因性变量及其作用机理的认知则一直处于动态发展过程中。整体来看,当前研究主要是围绕三条线索展开的:第一,以质量、价值、满意为主要前置变量;第二,以理性行为理论模型(Theory of Reasoned Action,TRA)、科技接受理论模型(Theory of Acceptance Model,TAM)、计划行为理论模型(Theory of Planned Behavior,TPB)及解构式计划行为理论模型(Decomposed Theory of Planned Behavior,DTPB)为主线;第三,以“质量、价值、满意”,或以“TRA、TAM、TPB及DTPB理论”为基础的模型拓展或模型整合。
1以质量、价值、满意为主要前置变量的行为意向研究
质量、价值和满意变量对行为意向具有重要的影响,由此也推动了全面质量管理(Total Quality Management)、顾客满意度测量(Customer Satisfaction Measurement)和顾客价值管理(Customer Value Management)理论及实践的发展[3]。上述三个变量与行为意向的关系,曾经历了单一前因变量研究(图1)、两前因变量研究(图2),以及以质量、价值和满意为主的多前因变量研究的发展阶段[4]。
而根据Cronin等[3]的梳理,在1995年以后多前因变量研究逐渐增多,且质量、价值和满意多在其中位居主导地位,但三个变量在“前因—中介—结果变量”链条中的作用却颇受争议,也由此发展出了多个竞争模型(图3)。在实证检验中,Cronin 等[3]得出了竞争模型E对行为意向解释力最强的结论,并重点讨论了质量对行为意向的直接显著作用,同时认为如果忽略质量、价值等变量对行为意向的直接影响效应会导致模型的偏估。但后期多次研究则表明质量对行为意向的直接影响效应是不显著的[5,6],质量对行为意向的显著影响往往是通过价值、满意变量间接发生的[5]。因此,虽然以质量、价值和满意为主要前置变量的多前因变量模型受到了越来越多的重视,但在不同研究情境下,部分变量的作用机制仍有较大差异。此外,在多前因变量模型中,以“质量—满意”、“价值—满意”、“质量—价值”为主要传递机理的研究也受到了较多关注。
2以TRA、TAM、TPB及DTPB理论为主线的行为意向研究
TAM、TPB与DTPB理论模型均来源于Fishbein和Ajzen于1975年提出来的TRA理论。TRA理论认为人的行为是由行为意向决定的,而行为意向则受态度和主观规范的影响(图4),此理论提出后,其适用性已经在多个领域获得了验证。但TRA理论关于个体行为主要受个体意志控制的假定,限制了该理论的适用范围并受到了一定的质疑[7]。此后,基于TRA理论对行为意向或行为进行解释与预测的模型不断得以重构,TAM、TPB与DTPB模型即是其中的代表并获得了国外学术界的高度认可[8]。其中TAM模型由Davis[9]于1986年提出(图5);TPB模型由Ajzen[7]于1985年提出(图6),DTPB模型由Taylor 和Todd[10]于1995年发展而来(图7)。
Huh 等[11]曾归纳了TAM、TPB和DTPB模型的异同点,认为三个模型的共同点在于:①均是根植于社会心理学、以意向为基础而建立的,并被用于推定用户使用信息技术或信息系统决定要素的模型;②每个模型均可预测或解释用户对信息技术或信息系统的接受度。区别在于:①TAM与TRA、TPB与TRA、DTPB与TPB模型间有一定的根植性;②前置变量有差别;③由于信念结构的差异,TPB和DTPB模型比TAM模型适用性更强;④模型中涵盖社会变量(如主观规范)的情况或对社会变量维度多少的界定有别;⑤对行为控制变量的理解有差异。
但事实上,上述模型特别是TRA、TPB和DTPB模型的应用范围早已不再局限于信息技术或信息系统领域[12];同时,在一定的研究情境下,TPB和DTPB模型的预测力或解释力未必比TAM模型大[13]。
3以前两条线索为基础建立拓展模型或整合模型的行为意向研究
近年来,行为意向研究除了继续遵循“质量、价值、满意”与“TRA、TAM、TPB及DTPB理论”两条主要线索演进外,相关的拓展模型或整合模型也逐渐兴起。而模型拓展或整合的具体方式通常有三种:第一,新变量的引入(表1);第二,对原变量的重新解构或对前置变量的重构(表2);第三,对原变量间关系的重塑。
此外,对原变量间关系的重塑则通常表现为两种形式:第一,变量间关系路径的增加或因果关系的变化,如把主观规范作为态度和感知行为控制的前置变量[24]、将主观规范作为知觉有用性的前置变量[25]、将感知行为控制作为知觉易用性的前置变量[25];第二,模型中增加新变量以后,原变量间直接或间接关系的变化,如把涉入作为质量与行为意向中介变量的间接效应模型[19]、把公平性作为质量与满意度中介变量的间接效应模型[5]、把信任作为满意与行为意向中介变量的间接效应模型[21]等。
4对行为意向影响因素、作用机理研究的评价
第一,以“质量、价值、满意”和“TRA、TAM、TPB及DTPB理论”为主线的两类模型均获得了良好发展,但两类模型对同一行为意向的解释力如何?两类模型是否有融合的可能性及其预测力如何?对上述问题尚缺乏分析。笼统看,“质量、价值、满意”模型更多是从外在感知因素角度探讨各变量对个体意向的影响,“TRA、TAM、TPB及DTPB理论”关注的重点则主要是个体意志变量对其意向的影响,而外在因素与个体意志变量发挥作用的时间差及其稳定性是有差异的,这种差异可能会导致其解释力的不同。当然,个体意志变量的形成往往会受到外在感知变量的影响,这可能为“质量、价值、满意”和“TRA、TAM、TPB及DTPB理论”模型中部分变量的整合提供了理论依据,这也可能是在近期大量研究中(表2),把质量、风险、成本、不确定性、满意、经历等变量作为前置变量引入到TRA、TAM、TPB及DTPB模型中的部分原因。
第二,虽然行为意向的影响因素与作用机理有一定的共通性,既有模型也可以在相当程度上预测相关意向,但研究背景与情境的差异使得模型结构改良成为行为意向研究的核心。其成因在于:①研究对象存在的情境、背景往往是特定的,此种情况下行为意向的发生机制往往受特定因素的影响。如Gu等[23]归纳发现传统的TAM模型对行为意向的解释力多介于40%~60%之间,而在模型中引入信任变量后研究手机银行时,解释变异量则达到了727%。②把特定研究情境下创立的理论模型应用于新的研究情景时,模型往往会出现解释力不足的情况。如Hung和Chang [26]在研究无线协议服务时比较了TAM、TPB和DTPB模型的解释力,结果却发现三个模型对人们使用无线协议服务意向的解释力均不足40%,而对行为的解释力则均不到10%。上述情况的发生也可能与相关研究中凸显信念(salient beliefs)表达的恰适性有关。
第三,新变量的引入丰富了既有的以“质量、价值、满意”和“TRA、TPB及DTPB理论”为主线的行为意向研究,但所引入的变量绝大多数是作为前置变量或中介变量使用的,为明晰研究对象的组间差异,尚需要结合研究情境引入更多的调节变量。事实上,在部分研究中,已经关注了经历、感知价格、转换成本、熟悉度等变量的调节作用,并发现了其价值,但关注度还远远不足。
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(责任编辑:王惠萍)
[20]Han H, Back K J, Barrett B. Influencing Factors on Restaurant CustomersRevisit Intention: The Roles of Emotions and Switching Barriers[J]. International Journal of Hospitality Management, 2009, 28(4): 563-572.
[21]Chiu C M, Hsu M H, Lai H, et al. Re-examining the Influence of Trust on Online Repeat Purchase Intention: The Moderating Role of Habit and Its Antecedents[J]. Decision Support Systems, 2012, 53(4): 835-845.
[22]Hutchinson D, William W J, Mohammed S, et al. Refining Value-Based Differentiation in Business Relationships: A Study of the Higher Order Relationship Building Blocks that Influence Behavioral Intention[J]. Industrial Marketing Management,2011,40(3): 465-478.
[23]Gu J C, Lee S C, Suh Y H. Determinants of Behavioral Intention to Mobile Banking[J]. Expert Systems with Applications, 2009,36(9): 11605-11616.
[24]Quintal V A, Lee JA, Soutar G N. Risk, Uncertainty and the Theory of Planned Behavior: A Tourism Example[J].Tourism Management,2010, 31(6): 797-805.
[25]Gumussoy C A, Calisir F. Understanding Factors Affecting E-reverse Auction Use: An Integrative Approach[J]. Computers in Human Behavior, 2009, 25(4): 975-988.
[26]Hung S Y, Chang C M. User Acceptance of WAP Services: Test of Competing Theories[J]. Computer Standards & Interfaces, 2005, 27(4):359-370.
(责任编辑:王惠萍)
[20]Han H, Back K J, Barrett B. Influencing Factors on Restaurant CustomersRevisit Intention: The Roles of Emotions and Switching Barriers[J]. International Journal of Hospitality Management, 2009, 28(4): 563-572.
[21]Chiu C M, Hsu M H, Lai H, et al. Re-examining the Influence of Trust on Online Repeat Purchase Intention: The Moderating Role of Habit and Its Antecedents[J]. Decision Support Systems, 2012, 53(4): 835-845.
[22]Hutchinson D, William W J, Mohammed S, et al. Refining Value-Based Differentiation in Business Relationships: A Study of the Higher Order Relationship Building Blocks that Influence Behavioral Intention[J]. Industrial Marketing Management,2011,40(3): 465-478.
[23]Gu J C, Lee S C, Suh Y H. Determinants of Behavioral Intention to Mobile Banking[J]. Expert Systems with Applications, 2009,36(9): 11605-11616.
[24]Quintal V A, Lee JA, Soutar G N. Risk, Uncertainty and the Theory of Planned Behavior: A Tourism Example[J].Tourism Management,2010, 31(6): 797-805.
[25]Gumussoy C A, Calisir F. Understanding Factors Affecting E-reverse Auction Use: An Integrative Approach[J]. Computers in Human Behavior, 2009, 25(4): 975-988.
[26]Hung S Y, Chang C M. User Acceptance of WAP Services: Test of Competing Theories[J]. Computer Standards & Interfaces, 2005, 27(4):359-370.
(责任编辑:王惠萍)