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中国管理科学 ›› 2018, Vol. 26 ›› Issue (9): 158-169.doi: 10.16381/j.cnki.issn1003-207x.2018.09.016

• 论文 • 上一篇    下一篇

多渠道零售环境下消费者渠道选择意愿形成机理研究——产品类别特征的调节作用

郭燕1, 吴价宝1, 王崇2, 卢珂3   

  1. 1. 淮海工学院商学院, 江苏 连云港 222005;
    2. 南京审计大学工商管理学院, 江苏 南京 211815;
    3. 南京大学工程管理学院, 江苏 南京 210093
  • 收稿日期:2017-03-14 修回日期:2018-04-23 出版日期:2018-09-20 发布日期:2018-11-23
  • 通讯作者: 郭燕(1980-),女(汉族),山西长治人,淮海工学院商学院,副教授,管理学博士,研究方向:营销工程,E-mail:guoyangongzuo@126.com E-mail:guoyangongzuo@126.com
  • 基金资助:

    国家自然科学基金面上资助项目(71571085);江苏省社会科学基金后期资助项目(16HQ013);淮海工学院博士人才基金资助项目(KQ17002)

The Formation Mechanism of Consumer Channel Selection Intention during Multi-channel Retailing Environment——Moderating Role of Product Categories Characteristics

GUO Yan1, WU Jia-bao1, WANG Chong2, LU Ke3   

  1. 1. School of Business, Huaihai Instititute of Technology, Lianyungang 222005, China;
    2. School of Business Administration, Nanjing Audit University, Nanjing 211815, China;
    3. School of Management & Engineering, Nanjing University, Nanjing 210093, China
  • Received:2017-03-14 Revised:2018-04-23 Online:2018-09-20 Published:2018-11-23

摘要: 传统与网络结合的多渠道正成为零售业的标准模式,多渠道零售环境下,消费者渠道决策发生了根本变化,在不同购买决策过程阶段运用不同渠道的行为日益普遍,但尚未有文献基于搜索信息和产品购买两个阶段,引入产品类别特征对消费者渠道选择意愿形成机理展开研究。运用感知价值理论、信任转移理论构建了消费者搜索意愿和购买意愿形成机理概念模型,分析了渠道属性、渠道内锁定、渠道间协同对消费者搜索与购买意愿的影响及产品搜索性与风险性对其的调节作用,运用联立方程建模并求解发现:渠道属性、渠道内锁定、渠道间协同显著影响消费者搜索意愿和购买意愿;购买高风险搜索产品(如计算机、手机)、低风险搜索产品(如书、文具)、高风险体验产品(如服装、化妆品)、低风险体验产品(如玩具、零食)时,渠道属性、渠道内锁定、渠道间协同对消费者渠道选择意愿的影响存在明显差异;渠道搜索属性如信息有效性、搜索便利性、品种丰富性、社会互动性正向影响消费者搜索意愿,搜索努力负向影响消费者搜索意愿,渠道购买属性如服务质量、购买便利性、享乐性正向影响消费者购买意愿,购买努力、购买风险负向影响消费者购买意愿;传统渠道具有锁定性,网络渠道缺乏锁定性,但购买低风险搜索产品时,网络渠道具有锁定性;购买高风险产品时,传统渠道与网络渠道存在协同性,对于高风险搜索产品,消费者网络渠道搜索意愿正向影响其传统渠道购买意愿,而对于高风险体验产品,还存在消费者传统渠道搜索意愿正向影响其网络渠道购买意愿的协同性,但对于低风险产品,传统渠道与网络渠道缺乏协同性。

关键词: 多渠道零售, 消费者搜索意愿, 消费者购买意愿, 渠道属性, 产品类别特征

Abstract: Nowadays, "touch the Internet" is becoming a key word for the Chinese brick-and-mortar retail industry, with dramatic changes of people's consumption lifestyle brought about by the Internet technology. Multi-channel retail model combined with traditional channel and Internet has become a standard mode for the retail industry. Under multi-channel retailing environment, consumer channel decision-making has changed fundamentally. The behavior that using different channels to buy becomes more and more popular. However, in the process of cross-channel buying, companies may also lose potential customers. For example, a consumer may enjoy the fitting service and personalized recommendations provided by a physical store, but end up purchasing clothes from the Internet, which seriously hurt the enthusiasm of traditional channel service personnel. Therefore, "how to guide consumers to migrate to the channel benefitting enterprises" becomes one of the important problems for multi-channel customer management. Firstly, a concept model of consumer channel selection mechanism including both search period and purchase period is established, based on the perceived value theory and trust transfer theory, specifically bringing products' search and risk characteristics into the model, channel-attributes, channel lock-in and cross-channel synergy's effects on consumer search intention and buying intention, and also, product search and risk characteristics' moderating functions to them are analyzed. Secondly, four simultaneous equations including consumer searching intention for traditional channel are listed, consumer searching intention for Internet channel, consumer buying intention for traditional channel and consumer buying intention for Internet channel are listed. Based on literature review, each variable of the equations is measured. Then data is collected by questionnaire survey. After the analysis of data's reliability and validity, parameters of consumer channel selection intention models are respectively estimated by 3SLS estimation using Stata12.0. Thirdly, consumer channel selection intentions about overall product categories and high-risk search product, low-risk search product, high-risk experience product, low-risk experience product are respectively analyzed. At last, conclusions and implications are put forward.
Some interesting results have been found. Firstly, channel-attributes, channel lock-in and cross-channel synergy affect consumer search intention and buying intention significantly. Secondly, for high-risk search products (such as mobile phones and personal computers), low-risk search products (such as books and stationery), high-risk experience products (such as clothing and cosmetics) and low-risk experience products (such as toys and snacks), there are obvious differences in channel search and buying attributes, traditional channel and Internet channel lock-in and cross-channel synergy's effects on consumer channel selection intention. Channel search attributes such as information availability, search convenience, assortment and social interactive affect consumer search intention positively, but search effort affects it negatively. Channel buying attributes such as service quality, purchase convenience and enjoyment affect consumer search intention positively, but purchase effort, purchase risk affects it negatively. Traditional channel has lock-in, but Internet channel hasn't. Otherwise for low-risk search products, Internet channel also has lock-in. For high-risk products, traditional channel and Internet channel has cross-channel synergy. For high-risk search products, there is some positive cross-channel synergy from Internet search to store purchase. For high-risk experience products, there is some positive cross-channel synergy both from Internet search to store purchase and from store search to Internet purchase. For low-risk experience products, there is no significant cross-channel synergy between the Internet and the store.
All of these throw lights on practical implications for enterprises' channel construction, increasing customer stickiness and managing multi-channel customer effectively.

Key words: multi-channel retailing, consumer searching intention, consumer buying intention, channel attributes, product categories characteristics

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