网络营销参与与消费者行为外文翻译本科毕业论文设计外文翻译原文Internet Marketing Involvement and Consumer BehaviorIntroductionOne of the most stunning aspects of the past few years has been the speed at which the Internet market has expanded and matured This rapid rate of Internet adoption has resulted in an extraordinary pace of change in the marketing landscape- and opened up a variety of opportunities for marketers All across Taiwan and around the world shopping centers are closing their doors as consumers turn to the Internet for all of their shopping needs The Internet as the primary on-line marketing channel is now overtaking the commercial on-line servicesIn fact all of the on-line service firms now offer Internet access as a primary service Users can send e-mails exchange views shop for products and access newsfood recipes art and business information As the Internet establishes its position as a mainstream marketing channel consumer criticism regarding Internet marketing strategies have increased as well Critics worry about information privacy including issues related to the acquisition and disseminationof consumer data Thus though over half of all American adults use the Internet approximately only half of the current Internet users have purchased products or services onlineThis poses a serious obstacle for Internet marketers as 75 of American adults do not spend money in web storesThe percentage of online money-spenders is generally less in countries outside the United StatesA key factor that decides the success of Internet marketing is user involvement The level of consumer involvement in a product category or service is a major determinant of online purchase or usage behavior Different involvement clusters produce different responses Thus the degree of user involvement in an Internet marketing effort will determine consumer behavior The response dimension is a function of the type of involvement generated and the situations confronted The response dimension characterizes how a consumer will behave under different involvement conditions There are three response factors 1 search 2 information processing and 3 decision persuasionHowever a variety of variables are thought to precede and influence the user involvementThese so-called antecedents interact with each other to determine the degree of involvement a consumer will experience at any particular timeThese variables can be grouped into 1 person 2 stimulusobject and 3 situation categoriesThe purpose of this paper is to propose a framework that candetermine the relationship among involvement antecedents of Internet marketing measured involvement degree related constructs and consequences of consumer behavior The framework first establishes the factors that affect the degree of Internet marketing involvement and then presents the different involvement degree clusters according to the measured involvement degrees Finally consumer behavior consequences of Internet marketing are established With the findings this paper then discusses the implications for Internet marketers and recommends Internet strategies for a variety of involvement degree clustersInvolvement identificationInvolvement identification Involvement result is the customers ultimate concern with a purchaseconsumption experienceHolbrook and Hirschman 1982 proposed that involvement included experiencing a number of positive results such as the rewards inherent in the product and the products expressive values Rothschild 1984 defined involvement as an unobservable state ofmotivation arousal or interest Involvement is evoked by a particular stimulus or situation and has drive properties Its consequences are searching information processing and decision making Hansen 1985 suggested that involvement is nothing more than a consumers interest for a product category Moreover some researchers proposed frameworks for conceptualizing the involvement construct Zaichkowsky1986 outlined prior studies that have shown involvement antecedents to be due to personal characteristics object characteristics andor situation characteristics Earlier researchers posited that one or more of these factors influenced the consumers level of involvement in advertising products and purchase decision Andrews Durvasula and Akhter 1990 designed a framework that closely scrutinizes the involvement constructs antecedents state properties measures related constructs and consequences The framework provided a nomological network of relationships among involvement antecedents state properties related constructs and consequences The antecedents to involvement were grouped into personal and situationaldecision factors The related construct factors such as ones opportunity to process and ability to process can limit the impact of these antecedents on the level of involvement Numerous consequences of manipulated involvement levels have also been determined including search behavior information processing and persuasionInvolvement measuring methodologyAndrews Durvasula and Akhter 1990 distinguished involvement measurement scales into two types One scale measures enduringproduct involvement For example Buchanan 1964 Zinkhan and Fornells 1989 method for measuring product interest was developed based on their research respondents relative preferences for watching short films regarding the products in question Each product was presented four times for a possiblerange of 0 to 8 a higher result indicating Bowen and Chaffee 1974 and Tyebjee 1979 used seven product-involvement measures to differentiate product class Vaughn 1980 distinguished product class by product categorization and thinkfeel dimensions Else Block 1981 used a 17-item product involvement scale for car enthusiasts Laurent and Kapferer 1985 used a 19-item consumer involvement scale Zaichkowsky 1985 1987 used a 20-item bipolar adjective scale while Wells 1986 used a 10-item relevance scale The second scale measures information manipulation with a focus on advertising messages This second method studies three topics 1 attentionprocessing strategies 2 personalsituational involvementand 3 audienceprocess involvementIn marketing involvement has often been equated with perceived product importance Traylor 1981 Lastovicka and Bonfield 1982 Zaichkowsky 1985 proposed a bipolar adjective scale the Personal Involvement Inventory PII to capture the concept of involvement in products The scale successfully complied with standards for internal reliability reliability over time content validity criterion - related validity and construct validity The PII offers researchers an easily administered tool that can be applied across product categories used as a covariate to other research questions By using twenty items the scale allowed an adequate sampling of possible items that represented product involvement was long enough to ensure a high level of reliability This scale used semanticdifferential that consists of a series of bipolar items each measured ona seven-point rating scale It is easy to administer and score takes only a few minutes to complete and is applicable to a wide array of objects Thus this study used PII as the measuring scale for Internet marketing involvement and to segment the market clustersThe FrameworkAccording to Andrews Durvasula and Akhter 1990 this studys conceptualization of the relationship construct is shown in Figure 1 This framework for identifying consumer involvement is influenced by four antecedents that included a personal characteristics b lifestyle c perception needs and d situations that directly affect the shopping decision The consumer behaviors affected were a purchase decision b items purchased c amount of money spent d volume of purchase and e trade mode Based on this framework the four antecedents influenced the consumers involvement in Internet marketing and consumption behaviors These involvement antecedents are significantly related with the degree of Internet marketing involvement which in turn has a significant relationship with consumer behaviors The following hypotheses are offered regarding the relationship among the degree of Internet marketing involvement influence variables and consumer behaviorH1The degree of Internet marketing involvement is significantly related with consumers personal characteristicsH2The degree of Internet marketing involvement changes significantly with different consumers lifestylesH3The degree of Internet marketing involvement changes significantly with different consumers perception needsH4The degree of Internet marketing involvement is significantly related with situationsH5Consumer behavior is significantly related with the degree of Internet marketing involvementThe study Focus groupsThis study interviewed a focus group of ten potential customers to collect original consumer perception needs associated with Internet marketing In total 122 descriptions of perception needs were collected All nonredundant needs obtained from the first focus group were recorded as primary needs The study then interviewed a second focus group of ten different customers to consolidate and reduce the number of primary needs This process generated 20 representative items regarding the respondents perception needs and attitudes toward Internet marketing A third focus group composed of ten Internet users was formed to verify the descriptions about perception needs so a questionnaire on perception needs and attitudes for Internet marketing could be designed Finally 17 items concerning perception needs and attitudes were obtained and incorporated into a questionnaire for a random sampling survey Concurrently the SRI Value and Lifestyles Program was used to design and acquire 18 lifestylequestions Lifestyle was defined as a persons living patterns Lifestyle questions measured consumers major AIO dimensions Activities Interests and Opinions In this study consumer perception needs and lifestyles were measured using a five-point Likert scale Consumer purchase behavior personal characteristics data and the situations were assessed using a nominal scaleData collectionThe primary data from this research were collected through personal interviews with 620 Internet users selected by quota sampling throughout Taiwan After rejecting 20 unusable responses this research collected a sample of 600 respondents for an effective response yield of 9677 percent Respondent ages ranged from sixteen to fifty years old Gender was almost equally balanced 435 male 565 female Respondent occupations included engineers students business professionals laborers and service workers Educational levels ranged from junior high school to post-graduate degrees Monthly individual gross income ranged from under US550 to US2850 Of the 600 respondents 138 were married and the others were either never married or divorced These demographic characteristics were similar to those of Taiwan Internet usersThe first purpose of this study is to measure a persons involvement in Internet marketing Using the PII measure to total the 20 items gives a range from a low of 20 to a high of 140 This study divided consumers into three involvement degree clusters by quartiles An involvement scorewithin the first quartile25th percentile was considered the low involvement cluster An involvement score between the first quartile25th percentile and the third quartile 75th percentile was considered the intermediate involvement cluster An involvement score on the third quartile75th percentile or above was considered the high involvement cluster To decide the cut off points for low intermediate and high involvements on the scale an overall distribution was tabulated and presented in Table 1 The resulting distribution was used to classify scores into low intermediate or high involvement clusters when the study needed a comparison among individuals A low score were defined as one ranging from 20 to 69 Intermediate scores were defined as those ranging from 70 to 86 High score were defined as those in the top quartile of the distribution ranging from 87 to 140 Because some involvement scores were similar the respondent sample could not be divided perfectly into three groups by quartiles The resulting three clusters were 151 252 285 475 and 164 273 for low intermediate and high scores respectively Result analysisThis study first sought to determine the influence of antecedents on Internet marketing involvement By the Chi-square test this research found that the degree of Internet marketing involvement was significantly related with three items of consumer personal characteristics p000 Education occupation and income This result supports H1 Most members ofthe low involvement degree cluster had low levels of education were laborers or service workers and were in the middle-income level Most in the intermediate involvement degree cluster were college students with low incomes Members in the high involvement degree cluster had the highest education level most of whom with graduate or college degrees Those in the high involvement cluster were mostly students or business professionals and exhibited the highest average income among the three clustersSource Shwu-Ing Wu Asia Pacific Journal of Marketing and Logistics Volume 14 Issue4 2002译文网络营销参与与消费者行为简介对过去数十年来最惊人的一个方面是哪个互联网市场的不断扩大和成熟速度这种互联网采用不同寻常的步伐导致了市场迅速增长的景观开辟了营销机会在台湾在世界各地商场关门大吉因为消费者转向了他们的互联网购物的所有需求作为主要的网上营销渠道互联网现在是超车商业在线服务事实上上线服务的公司现在都提供互联网为主要服务的访问用户可以发送电子邮件交换意见对产品车间并获得新闻食品配方艺术和商业信息随着互联网的确立其作为主流营销渠道的地位消费者的批评有关互联网营销策略也增加了批评人士担心隐私信息包括有关收购和消费者数据传播的问题因此虽然超过半数的美国成年人使用互联网但目前大约只有一半的互联网用户在购买产品或在线服务这将成为互联网营销的严重障碍有75的美国成年人不花钱在网络商店在网上赚钱花钱的比例一般比在美国以外的国家少一个关键因素决定了网络营销的成功就是用户的参与消费者参与产品类别或服务水平是网上购买或使用行为的主要决定因素不同涉入集群产生不同的反应因此用户在网络营销的努力将决定消费者的参与程度方面的行为这反应是生成的参与和面临的形势类型的函数消费者的行为特征如何在不同的参与条件中相应反应的因素有三个1搜索2信息处理3决定或说服力然而各种变量被认为是影响用户的参与这些所谓的前置因素相互影响以确定消费者的参与程度将经历在任何特定时间这些变量可以分为1人2刺激或对象3类别的情况本文的目的是提出一个框架可以决定在参与互联网市场的前因关系测量的参与程度相关结构和消费行为的后果该框架首先确立因素影响了网络营销的参与程度然后提出了不同的参与程度集群根据实测的参与度最后通过网络营销建立消费者行为的后果随着发现本文则探讨了互联网营销的影响并建议对集群的参与程度进行不同的互联网战略参与鉴定参与鉴定的结果是参与客户的消费经验与购买的终极关怀在1982年霍尔布鲁克和赫希曼提出的参与包括遇到的奖励如在产品和产品的内在价值表现了积极成果在1984年罗斯柴尔德所界定的参与一个不可观测的状态觉醒和利益涉入是由一个特定的刺激诱发或情况并驱动的属性其后果是搜索信息处理和决策在1985年汉森建议参与只不过是一个消费者对产品类别的兴趣此外一些学者提出的概念化的参与构建框架在1986年Zaichkowsky概述了显示参与来路是由于个人的特点对象特性或以前的研究情况特点早期研究者假定有一个或多个这些因素影响了消费者的广告产品和购买决策的参与程度安德鲁斯Durvasula和Akhter在1990年设计了一个框架密切负责审查参与建设的先例国有财产措施相关结构和后果该框架提供了一个涉入前因国有财产关系的法理网络相关结构和后果参与前因被分为个人和情境因素相关建设为一体的机会和能力来处理工艺因素可以限制这些前因对参与程度的影响涉入程度的许多操纵后果也已确定包括搜索行为信息处理和劝导参与的测量方法安德鲁斯Durvasula和Akhter在1990年将不同的参与分为两种类型测量尺度一个为大规模产品涉入持久措施例如布坎南在1964年以及Zinkhan和Fornells在1989年的测量方法开发产品的兴趣建立于他们的研究受访者观看相对喜欢的产品短片提出了产品的第四代范围可以为0到8表明了一个较高的结果鲍文和查菲在1974年以及Tyebjee在1979年都用了七个产品参与措施来区分产品类别沃恩在1980年按产品分类区分产品的类别和想法或感觉尺寸另外用汽车爱好者的17项产品涉入规模 Laurent和Kapferer在1985年使用了19项消费者参与的规模 Zaichkowsky在1985年和1987年使用了20项规模双极形容词而韦尔斯在1986年使用了10项相关的规模第二个措施是对大型广告信息和焦点信息的操纵第二种方法的研究有三个议题1注意处理策略2个人情境的参与3观众进程的参与在市场营销里特雷勒在1981年以及 Lastovicka和邦菲尔在1982年都认为经常参与等同于知觉产品的重要性 Zaichkowsky在1985年提出了一个双极形容词规模个人涉入量表PII以捕捉产品中参与的概念规模成功地遵守内部的可靠性可靠性随着时间的推移内容效度效标准 - 相关效度和结构效度研究人员的PII提供一个易于管理的工具它可以跨越作为其他研究问题帮助用过的产品分别应用通过使用二十项规模允许对可能的项目是代表产品抽样充分参与是足够长以确保高可靠性这种规模的使用语意差异是一个两极的项目在七点评定量表测量每个系列组成这是易于管理和评分只需几分钟即可完成广泛地适用于一组对象因此本研究以作为衡量网络营销的参与规模细分市场集群的PII 框架据安德鲁斯Durvasula和Akhter研究的关系所构造的是概念化这种对消费者参与确定的框架是由四个前因影响其中包括一个人特征二生活习惯三认知的需要四状况直接影响到购物决定消费者行为的影响分别为一购买决策二购买的物品三所花费的钱四购买量以及五贸易方式在此框架基础上四个来路影响着消费者对网络营销和消费行为的参与这些参与前因有显着相关的网络营销与参与程度这反过来又与消费行为有显著的关系下面的假说提供了关于网络营销之间的参与影响变量消费行为的程度关系H1互联网营销的参与程度与消费者的个人特征显著相关H2互联网营销的参与程度的变化与不同消费者的生活方式显著相关H3互联网营销的参与程度的变化与不同消费者的认知需求显著相关H4互联网营销的参与程度相关情况H5消费者行为与网络营销的参与程度显著相关研究的重点群体这项研究访问了10个潜在客户聚焦小组收集原始消费者认知需求与相关的网络营销总共有122个需要说明获得收集从第一个焦点小组所得的全部低使用率数据需要被记录为主要需求这项研究随后采访了十个不同的客户群的第二个重点是巩固和减少基本需求数量这个过程中产生的20个代表性项目有关受访者的认知需求和对网络营销的态度第三个焦点团体由十个互联网用户组成成立了有关描述验证知觉感知的需要以便对需求和网络营销的态度可以设计问卷最后17项有关的看法和态度需要获得和转化为一个随机抽样调查问卷中同时SRI的价值和生活方式程序是用于设计和获得18生活方式的问题生活方式被定义为一个人的生活模式生活方式的问题衡量消费者的AIO的主要方面活动兴趣和意见在这项研究中消费者认知需求和生活方式测定采用李克特的五点对消费者购买行为个人特性的数据以及使用情况进行了评估数据收集本研究的主要数据是经由互联网与620配额的抽样方式以及台湾各地用户的个人访谈在拒绝了20种与众不同的反应本研究收集了有效的反应率为9677的600受访者的样本答辩人年龄介于1650岁性别435为男性565为女性答辩人的职业包括工程师学生商务人士劳工和服务工作教育水平从初中到研究生学位个人每月总收入介于550美元至2850美元在这600名受访者中138为已婚其他人不是未婚就是离婚这些人口特征相似于台湾互联网用户本研究的第一个目的是要衡量一个人在网络营销的参与使用的PII措施共20个项目提供了从一组地范围20个到140个本研究分为三个集群参与四分度的消费者第一25参与评分的被认为是低涉入集群25到75参与评分的被认为是中间参与集群75以上参与评分的被认为是高涉入集群要决定关闭的规模低中高涉入分切总体分布列于表1所列由此产生的分布是用来分为低中高涉入群或研究时需要一个比较个人之间的分数一个低分被定义为一个由20至69人不等中间分数被定义为从70至86人高分被定义为在分配前四分之一范围从87至140人由于一些参与评分相近样本不能被申请人完全划分为三个组由此产生的三组分别为151占252164占273和285占475为低中高分数结果分析本研究首先试图在参与的网络营销确定前因的影响本研究发现由卡方检定互联网营销的参与程度和个人消费特征有显著关联教育职业和收入这一结果支持H1的表达低涉入程度集群的多数成员教育水平低是劳动者或服务工作并在中等收入水平在中间的参与程度集群大多是低收入的大学生高涉入程度集群的成员是教育程度最高的其中大部分为研究生或大学本科学历在高涉入集群内大多是学生或商务人士体现出三组之间的最高收入水平出处安泰武《亚太区市场营销及物流期刊》第14卷2002436-53。