地理研究  2017 , 36 (5): 957-971 https://doi.org/10.11821/dlyj201705012

研究论文

南京市居民购物行为的影响因素和空间效应——基于四种商品的对比研究

杜晓娟1, 甄峰23, CAO Jason4

1. 南京大学地理与海洋科学学院,南京 210093
2. 南京大学建筑与城市规划学院,南京 210093
3. 南京大学人文地理研究中心,南京 210093
4. 美国明尼苏达大学公共事务学院,双子城 55455,美国

Influential factors and spatial effects of individuals' shopping behavior in Nanjing: A comparative study on four types of goods

DU Xiaojuan1, ZHEN Feng23, CAO Jason4

1. School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210093, China
2. School of Architecture and Urban Planning, Nanjing University, Nanjing 210093, China
3. Human Geography Research Center, Nanjing University, Nanjing 210093, China
4. Humphrey School of Public Affairs, University of Minnesota, Twin Cities 55455, USA

通讯作者:  通讯作者:甄峰(1973- ),男,陕西汉中人,教授,博士生导师,研究方向为城市地理与区域规划、智慧城市。E-mail:zhenfeng@nju.edu.cn

收稿日期: 2016-11-23

修回日期:  2017-03-10

网络出版日期:  2017-05-20

版权声明:  2017 《地理研究》编辑部 《地理研究》编辑部

基金资助:  国家自然科学基金项目(41571146,41371149)国家科技支撑计划课题(2015BAJ08B01)

作者简介:

作者简介:杜晓娟(1989- ),女,重庆丰都人,硕士,研究方向为城市地理与区域规划。E-mail:mg1427024@smail.nju.edu.cn

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摘要

信息技术的发展和使用不断改变着居民的购物方式和行为,并对城市交通和城市商业空间布局等产生了一系列影响。采用2015年南京市居民购物行为问卷调查数据,通过联合有序probit模型,探讨南京市居民购物行为影响因素和空间效应,并对四种商品进行对比研究。研究表明:① 家庭生命周期、城市建成环境、居民购物态度、机动车保有状况和社会经济人口因素均对居民购物行为有显著影响,且存在产品类型差异;② 不同类型人群对城市交通出行和商业布局的影响不同,且特征人群分布存在空间分异;③ 居民对不同产品类型购物的空间偏好存在差异,且这种偏好受居民主观决策和客观环境共同影响。基于以上发现,对城市交通和商业布局提出相关建议。

关键词: 居民购物行为 ; 网络购物 ; 影响因素 ; 空间效应 ; 南京

Abstract

The development of information and communication technology has changed individuals' shopping mode and behavior, which in turn affects urban travel and the spatial distribution of retail businesses. This paper explored the influencing factors of shopping behavior and discussed spatial effects of the shopping behavior by using a comparative study of four types of goods, i.e., clothing, book, daily goods and electronic device. Joint ordered probit models have been applied based on a survey conducted in Nanjing city from April to June in 2015. The survey presents the shopping behavior of 963 residents from 42 residential development and eight metropolitan districts of Nanjing city.The result reveals that: (1) the built environment, shopping attitudes, and demographic characteristics have significant impacts on individual's shopping behavior. At different stages of family life cycle, individuals tend to increase or decrease the frequency of purchasing different types of goods. All these impacts vary in the four types of goods; (2) both substitution effect and complementarity effect of online shopping have been identified. However, the complementarity effect is applied on all the four types of goods and the substitution effect only applied on clothing. Individuals have been categorized into some specific sub-populations to identify and predict the two effects. There is only one sub-population whose online shopping behavior has substitution effect and many others have complementarity effect. The spatial distribution of these specific sub-populations is heterogeneous so that it has great impacts on urban transportation and commercial planning. (3) In terms of different types of goods, individuals have different spatial preferences, which are subject to their desire and the built environment. They prefer purchasing non-daily goods at shopping mall miles away from home and purchasing daily goods at small stores nearby. These preferences would affect the effect of urban commercial zoning. For example, when the density of shopping malls increases, the individuals' travel distance of clothing shopping will decrease but the frequency will increase. The overall travel magnitude is determined by the combined effect of the two models. Based on the results, we proposed some suggestions on urban transportation and commercial land use planning.

Keywords: shopping behavior ; e-shopping ; influencing factors ; spatial effects ; Nanjing

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杜晓娟, 甄峰, CAO Jason. 南京市居民购物行为的影响因素和空间效应——基于四种商品的对比研究[J]. , 2017, 36(5): 957-971 https://doi.org/10.11821/dlyj201705012

DU Xiaojuan, ZHEN Feng, CAO Jason. Influential factors and spatial effects of individuals' shopping behavior in Nanjing: A comparative study on four types of goods[J]. 地理研究, 2017, 36(5): 957-971 https://doi.org/10.11821/dlyj201705012

1 引言

随着ICT技术和互联网技术的飞速发展,网络购物快速崛起。根据《2015年度电子商务市场数据监测报告》,2015年中国网络零售市场交易规模达到3.83万亿元,同比增长35.7%;占社会消费品零售总额的12.7%,同比增长2.1%。网络购物的发展带来了居民购物行为的改变,在一些特定的商品交换领域改变较明显[1]。同时,网络购物对实体购物的冲击和影响,带来一系列城市商业空间、交通出行等方面的变化[2-4]。因此,居民购物行为特征、影响因素、网购与实体购物的关系及其对交通出行和土地利用等方面的影响,成为城市规划、交通规划者和城市、交通领域的学者关注的主要议题。

国外学者对居民购物行为的研究相对较早和成熟。实体购物行为研究主要集中在影响因素[5,6]和决策机制[7]等方面。影响因素的探讨涵盖客观购物环境(商业中心的面积、距离等)[8]、消费者属性[7]、主观态度(冲动购买、时间压力等)[9]等方面。网络购物行为影响因素方面,早期主要从移动交易平台建设[10]、互联网设备使用[11]、网络购物的优劣势以及性别、收入、年龄、网络使用经验[12]等角度进行探讨。随着行为视角的增强,学者们开始关注消费者主观态度的影响[13]。同时,空间因素作为城市和地理领域关注的重点,其影响作用逐渐成为研究热点。Anderson等[14]基于新技术起源和扩散规律,互联网技术对时间和空间障碍的消减等前提条件,提出了两种假设:创新扩散假设和效率假设。基于两种假设,已有成果通过网购消费者居住地城市化水平、购物可达性等变量对这两种假设进行了实证研究,两种假设均得到验证[13,15-18]。国内对居民购物行为影响因素探讨主要集中在经济、市场营销等领域,地理视角的研究相对较少,仅有少量研究对主观决策与客观物质空间[19]、消费者居住地类型、交通方式、网络使用情况[3, 20]等因素进行了探讨。

规划、交通和地理领域对购物行为的研究最终均会落到时空间特征或者对规划、土地利用和交通出行的影响层面。国外研究主要通过探讨实体购物与网络购物的关系,进而提出对规划和交通的启示。已有研究成果将实体购买与网购的关系概括为四种:替代、补充、修正和中立[21-24]。其中,替代作用是规划和交通研究中关注的焦点。网络购物替代传统购物,即网络购物具有减少实体购物出行的潜力,对缓解交通拥堵等问题有显著意义,同时也带来实体商业空间布局的变化。但由于研究单位(家庭或个人)和商品种类不同,研究结果存在一定差异[25-27]。国内研究主要包括对时空间特征[19]以及空间等级结构[28, 29]的描述,或者通过问卷设计得出对交通出行的影响[3]

综合来看,国内外均未探讨家庭生命周期(family life cycle)对居民购物行为的影响。但是,这是影响居民购物行为的重要因素[30],居民购物频率以及购买商品的类型与居民所处的家庭生命周期息息相关。家庭生命周期是反映一个家庭从形成到解体的过程。美国学者Glick[31]最早从人口学角度进行了比较完整的家庭生命周期阶段的划分,之后家庭生命周期在人口学、社会学、消费者行为学等领域被广泛应用,但是较少被用于地理学领域。其次,国内从家庭生命周期、客观建成环境、主观购物态度、机动车拥有情况以及社会经济人口等方面进行全面研究的成果相对不足,且缺少多种产品类型的对比研究。第三,居民购物行为的空间特征、空间效应、以及对土地利用和交通出行的影响方面,研究成果仍然较少。第四,本文采用的联合有序probit模型(joint ordered probit model),相较于单个模型,考虑了多个因变量同时被未观察到因素影响的情形,估计结果更准确[32]。因此,本文采用联合有序probit模型,全面探讨包括家庭生命周期、客观建成环境、主观购物态度等在内的南京居民购物行为影响因素和空间效应,并进行四种类型产品对比,以期从地理视角进一步完善居民购物行为方面的研究。

2 研究方法与数据来源

2.1 数据来源

本文基于2015年4-6月开展的南京市居民购物行为问卷调查,调查内容主要包括购物过程、网络使用经验、购物态度、购物行为习惯、社会经济人口信息五部分。根据南京市人口分布现状,综合考虑交通便利性和购物可达性,通过多阶段抽样,调研组选择南京的8个区(鼓楼、玄武、秦淮、建邺、栖霞、浦口、江宁、雨花台),从每个区抽取两个街道,再从每个街道抽取2~3个小区,共抽取42个小区进行随机入户调查(图1)。最终1032位受访者完成问卷,有效问卷963份,有效率为93.3%。调研样本基本情况统计如表1所示。

图1   南京市调研地分布图

Fig. 1   Map of samples in Nanjing

表1   南京市调研样本基本情况统计

Tab. 1   Descriptive statistics of samples in Nanjing

样本属性样本量均值或比例
年龄年龄92331.48(均值)
性别40442.1%
55557.9%
学历小学及以下50.5%
初中434.5%
高中/中专10410.8%
大专22623.5%
本科44846.6%
研究生及以上13514.1%
家庭平均月收入(元)<100040.4%
1000~1999272.8%
2000~2999757.9%
3000~499920421.5%
5000~699920621.8%
7000~999916817.7%
10000~1499913514.2%
15000~19999687.2%
>200000626.5%
居住地市区53455.5%
郊区42944.5%

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不同类型商品购物频率分布情况如表2所示。

表2   居民网络购物和实体店购物频率

Tab. 2   Frequency of online and store shopping

购物频率衣服书籍日用百货电子产品
网络实体网络实体网络实体网络实体
很少25.92%29.04%55.39%70.66%30.58%16.21%79.68%83.12%
二个月一次19.94%25.37%21.56%14.30%13.97%12.92%12.06%11.01%
一个月一次19.41%24.00%13.42%8.73%26.03%21.29%8.26%5.87%
一个月两次14.06%12.37%9.62%6.31%13.97%21.29%
一个月三次及以上20.67%9.23%15.45%28.29%
样本量953954946951945944945954

注:书籍购物频率分类包括很少、二个月一次、一个月一次、一个月二次及以上;电子产品购物频率分类包括很少、二个月一次、一个月一次及以上。

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2.2 研究方法

2.2.1 联合有序probit模型 本文采用联合有序probit模型对南京市居民购物频率进行探讨。Roodman[32]提出用Stata 12.0软件中的“cmp”模块联合多个有序probit模型,用以修正多个因变量同时被未测度到的因素影响的情形。单个有序probit模型不能对这些共同的影响因素进行有效估计,因此需要进行模型联合。Zhen等构建了一个包含4个变量的有序probit模型(quadruple-variate ordered probit model),用于探讨衣服、书籍、日用百货和电子产品四种商品网购与实体购物之间的关系,从实证层面证明了此方法的科学性[30]。本文借鉴Zhen等的研究[30,32],采用Stata 14.0软件中的“cmp”模块,针对衣服、书籍、日用百货和电子产品的网络购买频率和实体店购买频率,分别构建二变量有序probit模型。模型检测结果显示,4个模型的网络购买频率和实体店购买频率的残差项显著相关。即网络购买频率和实体店购买频率以及各类商品购买频率之间存在未测度到的共同影响因素,联合模型估计结果优于单个模型。

模型计算公式为:

Yi*=βiXi+εi(1)

式中:Xi为解释变量; βi为估计参数值; εi为残差;Yi*是潜在变量,无法观测到具体值。但是Yi为可观测变量,表示在(0, 1, …, m)上取值的有序响应,假设YJ个取值O1, O2, …, OJ,用一个升序序列 α0, α1, …, αJ定义Y*会落入的区间,其中 α0=-, αJ=+

Yi=O1,α0<Yi*α1Oj,αj-1<Yi*αjOJ,αj-1<Yi*αJ(2)

本文联合网络购物频率和实体购物频率,针对四种商品类型,模型构建如下:

Y网购ij*=βijXij+εijY实体ij*=βjXij+εij(3)

式中:j取值为衣服、书籍、日用百货、电子产品。

2.2.2 统计分析和空间分析 结合解居民购物行为的影响因素,本文将采用统计分析的方法,分析网络购物和实体购物的不同关系以及各种关系对应的不同特征人群和商品种类。同时,通过空间分析的方法将不同生命周期的人口比率定位到各行政区划,讨论居民网络购物对实体购物影响的空间差异。

图2   模型概述

Fig. 2   Model overview

同时,通过统计居民购买各类商品的出行距离,可以得到居民对于各类商品的空间偏好,同时结合影响因素分析的结果,以探讨不同偏好对于城市规划效果的影响。

3 居民购物行为的影响因素

家庭生命周期对购物行为具有重要影响[30],因而本文引入家庭生命周期进行探讨。根据已有文献[33-36]和样本实际情况,综合受访者婚姻、子女年龄和受教育阶段等指标,本文将家庭生命周期划分为6个阶段(表3)。居住地类型和购物出行时耗代表空间因素对购物行为影响的两类主要变量:地理区位和购物可达性[15]。随着ICT的不断发展和深入渗透,居民在通勤途中通过智能手机、ipad等移动设备进行ICT活动已成为常态,其中购物是主体活动之一。购物态度是影响居民购物行为最直接的因素之一,对居民购物行为影响较大[37]。网络使用经验会直接影响居民的网络购物行为,进而影响实体购物行为。因此,本文选取家庭生命周期、居住地类型(城区/郊区)、购物出行时耗、通勤类型(工作和居住在同一行政区/工作和居住在不同行政区)、购物态度(采用Zhen等[30]因子分析结果)、网络使用经验、社会人口等因素进行探讨。

表3   家庭生命周期阶段划分

Tab. 3   Criteria for the classification of family life cycle

家庭生命周期定义比例(%)
单身成年之后到结婚29.78
新婚从结婚到孩子出生26.41
满巢I孩子学龄前阶段(0~5岁)17.07
满巢II孩子小学阶段(6~11岁)13.04
满巢III孩子中学阶段(包括初中和高中)(12~17岁)5.98
空巢孩子上大学或者参加工作(18岁及以上)7.72

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衣服、书籍、日用百货、电子类产品联合有序probit模型拟合结果如表4表5所示。为了获得简洁有效的模型,本文剔除了模型中显著性大于0.1的变量。

表4   联合有序probit回归结果(1)

Tab. 4   Regression result of joint ordered probit model (1)

衣服书籍
网络实体网络实体
性别(以男性为参照)0.507***(5.87)0.39***(4.82)0.162**(-2.01)
收入0.05**(2.06)0.057**(2.39)0.055**(2.25)
教育水平-0.076*(-1.84)0.246***(5.58)
家庭生命周期(以单身为参照)
新婚0.12(1.09)-0.172*(-1.67)-0.202*(-1.77)-0.395***(-3.18)
满巢I0.219*(1.74)-0.213*(-1.81)0.042(0.34)-0.251*(-1.86)
满巢Ⅱ0.038(0.28)-0.225*(-1.78)0.400***(3.03)0.063(0.45)
满巢Ⅲ-0.119(-0.67)-0.025(-0.15)0.193(1.03)0.144(0.77)
空巢-0.404*(-2.34)0.088(0.58)0.299*(1.76)0.286*(1.72)
居住地类型(以城区为参照)0.201**(2.44)
通勤类型(以工作和居住在同一行政区为参照)0.166**(2.02)
购物出行时耗-0.108***(-3.88)-0.053**(-2.03)-0.059**(-2.27)
上网时长0.098**(2.44)
求新心理0.081*(1.95)0.086**(2.19)0.078**(1.96)
成本节约意识-0.072*(-1.92)
冲动消费心理0.123***(2.88)0.077*(1.95)-0.075*(-1.86)
时间节约意识0.089**(2.13)0.157***(3.98)
机动车数量0.117***(2.65)0.105**(2.59)0.102**(2.33)0.127***(2.79)
驾照0.186**(2.07)0.265***(3.14)
ε网络ε实体相关性0.242***(5.42)0.511***(9.34)
似然比(LR)检验LR chi2(31)=208.24***LR chi2(18) =113.58***
对数似然值-2217.742-1549.9871
样本量801814

注:括号内为Z值;***表示P<0.01;**表示P<0.05;*表示P<0.1。

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表5   联合有序probit回归结果(2)

Tab. 5   Regression result of joint ordered probit model (2)

日用百货电子类产品
网络实体网络实体
性别(以男性为参照)0.198**(2.52)0.273***(3.6)-0.353***(-3.51)-0.280***(-2.7)
收入0.042*(1.78)0.068***(3.17)
教育水平0.120***(2.76)
家庭生命周期
(以单身为参照)
新婚0.116(1.13)0.222**(2.31)0.036(0.28)0.210*(1.65)
满巢I0.350***(2.94)0.260**(2.34)0.118(0.8)-0.278*(-1.68)
满巢Ⅱ0.129(1.01)0.250**(2.08)-0.027(-0.16)-0.044(-0.26)
满巢Ⅲ-0.163(-0.94)0.088(0.56)-0.109(-0.48)-0.088(-0.39)
空巢-0.223(-1.34)0.037(0.26)-0.06(-0.28)0.164(0.83)
居住地类型(以城区为参照)0.212***(2.75)
通勤类型(以工作和居住在同一行政区为参照)0.149*(1.92)0.259***(2.83)
购物出行时耗-0.163***(-6.1)
求新心理0.215***(5.29)0.129***(3.51)0.15***(3.09)0.203***(4.09)
购物享受心理0.083**(2.21)-0.115**(-2.38)
成本节约意识-0.129***(-2.98)
冲动消费心理0.092**(2.32)
时间节约意识0.109**(2.26)
驾照0.229**(2.1)0.252**(2.33)
ε网络ε实体相关性0.256***(5.86)0.718***(9.55)
似然比(LR)检验LR chi2(22)=185.74***LR chi2(20)=95.47***
对数似然值-2511.8594-923.34061
样本量905913

注:括号内为Z值;***表示P<0.01;**表示P<0.05;*表示P<0.1。

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3.1 家庭生命周期因素

模型结果显示,家庭生命周期对衣服、书籍、日用百货类商品的网络购买频率和实体店购买频率均有显著影响,对电子类产品实体店购买频率有影响。已有研究显示,不同的家庭生命周期阶段,家庭消费具有倾向性,同时在消费总量上存在差异[38]。在本研究中,与单身阶段相比,新婚阶段的受访者将减少衣服、书籍的购买频率,增加日用百货和电子类产品的购买频率。通常组建新的家庭会添置一些电器类家具以及日常用品。在孩子0~5岁阶段,会增加网络购买衣服的频率,减少实体店购买衣服、书籍、电子类产品的频率,同时增加日用百货的网络和实体店购买频率。此阶段照顾孩子需要花费大量时间,将会挤占去实体店购物的时间,对衣物等必需品通过网络购买替代实体购买。同时此阶段对日用百货需求量大,而超市一般布置在居住区附近,因此日用品的网络购买频率和实体店购买频率均增加。在孩子6~11岁阶段,仍然要花时间照顾孩子,同时工作较忙,因此实体店购买衣服频率减少,对日用百货需求量仍然较大,因此日用百货购买频率增加。此外,此阶段需要给孩子购买教辅书籍和课外读物,因此书籍网络购买频率增加。在孩子12~17岁阶段,家庭发展成熟,购买频率趋于稳定,倾向性较弱。空巢阶段受访者一般年龄较大,对网络购买熟悉度较低,因而网络购买衣服频率减少,同时需求量下降,实体店购买频率并未显著增加。此外,书籍购买频率增加,老年人空闲时间较多,可能会通过阅读一些老年读物打发时间。

3.2 空间因素

空间因素方面,居住地类型、购物出行时耗和通勤类型,均显示出对购物频率有影响。Anderson等[14]提出两种空间假设:一方面他认为城区居民更可能进行网购或者网购频率更高,因为网络作为一种新技术发源于城市,由城市中心区向郊区扩散,即创新扩散假设。另一方面,他提出网络可以消减时间和空间的阻隔,因而购物可达性较差地区的居民更倾向于进行网购,即效率假设。本文研究结果支持效率假设,研究结果显示,与居住在城区的受访者相比,居住在郊区的受访者网络购买衣服和日用百货的频率较大,这与已有研究结果支持创新扩散假设不同[13,15]。随着城镇化速度加快,郊区的网络基础设施得到完善,居民的受教育水平不断提高,以及移动网络购物的快速发展,创新扩散假设的前提已经发生变化,因而网购优势更多的表现为可以随时随地进行购物。购物出行时耗代表购物可达性,已有研究显示,居民实体店购物频率随购物可达性降低而减少[13,17]。本文研究结果显示,随着购物出行时间增加,受访者网络和实体店购买衣服频率均减少,书籍和日用百货仅实体店购买频率减少。衣服属于体验型商品,需要进行试穿才能确定合适性,不同于书籍等搜索型商品,可以通过网络等渠道获得确切信息。因此,衣服购物可达性降低,居民网络购买和实体店购买频率均下降。此外,通勤距离增加,居民网络购买衣服、书籍和日用百货频率增加。长距离通勤会挤占居民实体店购物时间,因此,与短距离通勤居民相比,通勤距离较长的居民倾向于用便利网购替代实体店购物。同时,通勤途中也可以进行网络购物。

3.3 居民购物态度因素

居民的购物态度直接影响其购物频率。本文购物态度通过因子分析得出求新心理、购物享受心理、成本节约意识、冲动消费心理、时间节约意识五个因子。研究结果显示,具有求新心理的居民四种商品的购买频率均增加。追求潮流、新奇的居民,会乐于购买新出现的商品,购买渠道包括网络和实体。享受购物的消费者趋向于去实体店购买日用百货和电子类产品。成本意识较强的居民倾向于减少实体店购买衣服和电子类产品的频率。因为无门店租金或者批发商直销等原因,网上价格通常低于实体店价格,对于单价较高的衣服和电子类产品具有更明显的价格差。喜欢冲动消费的居民,衣服和日用百货购买频率增加。对于衣服和日用百货类可囤积的商品,冲动消费者较容易受打折信息影响产生购买。时间节约意识较强的消费者对衣服和电子产品等需要体验的商品类型,实体店购买频率增加。去实体店进行体验之后进行购买更可能买到合意的商品,减少退货/换货花费的时间。

3.4 社会经济属性因素

机动车数量和是否拥有驾照对衣服、书籍和电子类产品购物频率有影响,机动车数量较多和拥有驾照的受访者购物频率增加。对日用百货购买频率没有影响,通常居住区步行范围内均有超市。上网频率影响较弱,仅对网络购买衣服频率有促进作用。

此外,性别、受教育水平、收入等社会人口变量对购物频率也有影响。对于衣服、书籍、日用百货女性购物频率高于男性,电子类产品男性高于女性。居民受教育水平越高,网络购买频率增加,实体店购买频率减少。收入较高的居民,购物频率较高。

3.5 四种商品影响因素对比

四种商品对比来看,影响四种商品购物频率因素存在差异。家庭生命周期在不同的阶段对产品类型存在不同的需求和偏好,新婚对电子产品和日用百货需求较大,满巢Ⅰ对日用百货需求量大,满巢Ⅱ对书籍和日用百货有需求,空巢阶段对书籍类商品需求较大。空间因素方面,除电子类产品外,均受空间因素影响,其中衣服和日用百货购买频率受购物便利性等空间因素影响较大,书籍受影响最小。这与四种商品的购买频率有关。按照数据统计结果,四种商品的购买频率均值由大到小依次为:日用百货、衣服,书籍、电子类产品。购物态度对书籍购物频率影响较小,对衣服、日用百货和电子类产品购买频率影响较大。机动车保有量对需要进行体验和长距离出行的商品类型影响较大,对日用百货购买影响较小,日用百货店铺通常步行可达。

4 居民购物行为的空间效应

居民购物行为决定了其购物出行模式,对城市交通规划、城市实体商业布局等的影响在空间上具有以下效应(以下简称“空间效应”):

首先,居民网络购物对实体购物具有替代、补充等效应,这种效应也存在空间差异,从而影响居民购物出行以及城市交通和商业空间布局。通过影响因素分析界定特征人群,能更系统准确地预测不同群体的居民购物行为倾向,从而讨论居民购物行为对于城市交通和商业布局的影响及其空间差异。

其次,居民对实体购物空间也存在主观偏好,即居民实体购物行为受到客观购物空间和主观偏好的双重制约。利用影响因素模型结果和居民空间偏好,可以进一步对城市空间布局进行敏感性分析,更好地服务于城市决策。

4.1 居民网络购物的替代效应、补充效应及其空间差异

网络购物通过影响实体购物活动进而影响居民交通出行[3]及实体商业布局。居民的自身属性、主观态度、购买的商品类型、购物设施客观环境不同,居民交通出行以及对实体空间的影响均存在差异。从网络和实体购物行为影响因素对比看,一些特定类型的人群或进行特定商品类型购买时具有网络购买替代实体购买、网络购买激发实体购买或网络购买和实体购买均减少的特征(表6)。但是从整体来看,Zhen等[30]基于相同数据的研究结果显示,四种类型的商品均显示出网络购买对实体购买具有补充效应,即网络购买会激发实体购买活动。

表6   网购与实体店购物关系及对出行的影响总结

Tab. 6   Summary of the relation between online and store shopping and their impact on travel

关系特征描述对出行的影响
人群特征商品类型
网络购物增加,实体购物减少(替代)满巢Ⅰ衣服减少出行
网络购物和实体购物均增加(补充)女性、高收入者、具有求新心理、冲动消费心理、时间节约意识、机动车保有数量多、拥有驾照衣服增加出行
空巢、拥有驾照书籍
女性、高收入者、满巢I、具有求新心理日用百货
男性、具有求新心理、拥有驾照电子类产品
网络购物和实体购物均减少新婚书籍减少出行
购物出行时耗增加衣服

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在城市空间中,上述特征人群的空间分布可能是不均匀的。特征人群在空间上的不均衡分布对城市交通出行和商业空间的需求存在一定差异。本文以家庭生命周期为例,图3显示了其在不同行政区的分布情况。结合表6图3可知:建邺区和江宁区处于新婚阶段的受访者比例较高,则其购买书籍的出行减少,对书籍类商业空间需求减少;玄武区和江宁区处于满巢I阶段的受访者比例较高,则其可能增加购买日用品的出行而减少购买衣服的出行,对日用品商业空间的需求增加,对衣服类商业空间的需求减少;雨花台区和鼓楼区空巢比例较高,其购买书籍的出行可能增加,对书店需求可能增加。

图3   家庭生命周期在不同行政区的分布

Fig.3   Spatial distribution of family life cycle among administrative districts

4.2 居民购物空间偏好特征

本次问卷调查了居民距其购买频率最高的衣服店、书店、日用百货店和电子类产品店的距离。此问题的调研结果不仅呈现了购物配套设施便利性的客观情况,同时也反映了居民对购物设施的主观选择。居民购物的空间选择倾向由居民主观偏好和客观环境共同决定。因而,居民在某一空间距离上呈现的选择倾向,事实上是因为居民主观偏好的店铺或品牌“恰好”位于该距离上。因此,本文对居民购物出行时耗作进一步分析,探究居民在客观购物环境制约下的主观空间选择,以期对城市商业空间规划提出相关建议。

图4来看,不同类型的商品空间选择倾向存在差异。居民在选购衣服、书籍、电子类产品时,出行时耗分布大致相同,50%左右的人集中在11~30 min出行时间范围内。表明,居民在进行非日用品购买时,均显示出去最近的城市商业中心或者副中心的偏好,对社区周边配套的衣服、电子产品等专卖店选择的频率较低。按照《南京市城市总体规划(2011-2020)》中对城市商业设施的布局显示:社区周边配套有相关专卖店配套;其次,居民到最近商业中心或者副中心的距离基本均在11~30 min公共交通可达范围内。与非日用品购买行为相反,居民购买日用百货倾向选择社区周边的超市和百货店,较少选择去大型综合超市。调研数据显示,49.95%的人选择了10 min内可达的店铺。究其原因,人们对日用品的需求量大,产品本身价值较低,居民对产品的要求也较低,因而空间倾向选择以便利性为主。相反,对衣服和电子类产品的质量、适合性等要求较高,因而倾向于选择品牌集中、商品种类集中、质量和售后保障均较好的商业中心进行购买活动,放弃社区周边便利的零散店铺。

图4   居民购买四种商品的出行时耗折线图

Fig.4   Travel time spend on shopping, by type of goods

4.3 居民购物行为的空间效应对城市交通规划、商业布局的启示

4.3.1 网络购物的替代和补充效应及其空间差异影响城市交通和商业布局 基于特征人群的空间分析可以用于预测区域内购物出行带来的交通压力以及实体商业需求。在实际应用中,可以利用城市大数据库将该分析深入到小区层级。居民普遍使用的社交媒体(如微博、微信等)是搜集个人情况、位置和购物态度的理想渠道。通过大数据分析,可以得出上述特征人群在城市空间上的具体分布情况,进而进一步研究居民购物行为对交通出行和城市商业空间的影响在空间上的特点和规律。从而针对不同区域内居民的需求进行城市交通空间和商业空间布局的合理调整和优化。

此外,网购主要呈现出对实体购物的促进作用显示:网购对南京市居民整体交通出行压力的缓解作用较小,同时网购并不会对实体零售业带来较大冲击,打破了网购导致购物中心空置率上升[39],导致实体商业空间萎缩,甚至实体店消亡的担忧[40]

4.3.2 居民购物空间偏好将影响城市商业空间规划的效果 一方面,当居民偏好店铺的空间分布发生变化,居民出行的空间选择倾向会相应发生变化。例如,当城市决策者计划增加大型商业中心的密度,居民距离他们偏好购买衣服的店铺更近,则居民购物空间偏好曲线将平移,如图5所示,原有空间偏好向更近距离移动。在第3部分的讨论中,了解到居民实体店购衣频率随着出行距离的增大而有减少的倾向(图5)。因此,当增加商业中心的密度,总体上会减少居民购物出行的距离,但同时可能增大他们购物出行的频率。

图5   居民购物空间选择倾向变化(以衣服为例)注:出行频率倾向由衣服实体店购物模型中购物出行时耗的回归系数(表4)计算得到,计算公式为:出行频率倾向=购物出行时耗回归系数×购物出行时耗分类变量值。

Fig. 5   Change of shopping spatial preference (taking clothing as an example)

另一方面,若居民不偏好店铺的空间分布发生变化,则对城市交通空间的影响较小。例如,在社区内增加零散的服装店,居民仍会前往大型购物中心购买衣服。

表4表5的结果看,出行距离对于居民前往实体店购买衣服、书籍、日用品的频率具有显著影响,而日用品系数的绝对值(0.163)明显大于衣服(0.053)和书籍(0.059)。这表明,日用品商业空间布局的改变对居民出行频率的影响大于衣服和书籍,在规划该类商业空间布局时需要更加谨慎考量。另外,当控制其他影响因素不变时,利用本模型中出行距离变量的变化,可以对城市商业空间布局进行敏感性分析(sensitivity analysis),进而讨论居民购物出行频次、距离、商业空间利用局部热点等方面的变化趋势。本文并未进行定量的敏感性分析,相关内容将在以后的研究中进一步探讨。

5 结论与讨论

5.1 结论

互联网技术以及移动信息技术的飞速发展和ICT的广泛使用,不断改变着居民购物方式和行为,并随之产生了一系列空间效应,包括对交通出行、商业用地布局等方面的影响。因而,逐渐成为城市地理学等领域关注的重点。本文通过对比四种不同类型的商品,引入联合有序probit模型,探讨了南京居民购物行为影响因素和空间效应。主要结论如下:

居民购物行为影响因素研究结果显示,居民购物行为除了受到性别、收入、受教育水平等社会人口因素影响外[3,12],家庭生命周期、客观建成环境、主观购物态度以及机动车拥有情况也是主要影响因素。对四种商品对比研究发现,不同类型商品的居民购物行为影响因素存在差异。其中,空间是地理学领域关注的重点[41],本文空间因素的研究结果发现,客观购物环境影响居民购物行为,同时,存在产品类型差异。衣服和日用百货等高频购买商品的购物行为受实体购物空间影响较大,而书籍、电子类产品等低频购买商品受空间影响较小。研究结果显示,居民处于不同家庭生命周期的购物行为以及处于同一家庭生命周期的居民在不同产品购买上均存在差异。

居民购物行为的空间效应研究结果显示,不同特征的人群以及购买不同类型的产品时在对出行和商业空间的影响上存在不同,且具有明显的空间分异。因而在未来城市和交通规划中应结合不同特征居民的空间分布规律,优化交通空间,合理分配商业用地。其次,网购对居民购物出行的替代作用较小,主要为补充作用。该结果表明,网络购买对减少实体出行、缓解交通压力作用较小,更可能产生额外的购买需求和出行需求。这有利于实体零售业的持续发展,特别是郊区实体购物设施完善等。同时,将进一步促进线上+线下的商业模式发展,使其逐渐成为互联网经济时代实体商业发展的主要方向。但是,这也对城市商业中心的合理布局和交通系统的优化提出了更高的要求。

此外,针对不同类型的商品,居民购物存在空间选择偏好。首先,对于非日用品(如衣服/书籍/电子产品),居民更倾向于前往距离较远但商品集中的大型购物中心购买,反映出非日用品可能存在联合购买的可能;对于日用百货,则更倾向于就近购买。居民对于商品的差异化购物空间偏好,将使得不同类型商品在商业分布格局(分布密度/位置/辐射范围等)上产生分化。其次,居民购物的空间选择倾向受居民主观偏好和客观环境共同影响。因此城市决策者需结合大数据分析等方法,充分考量两者的相互作用机制和结果,使城市交通和商业空间布局更加便民、合理。

5.2 讨论

在互联网经济时代,居民购物行为发生了较大变化。而国内地理学领域关于居民购物行为,特别是网络购物的研究尚处于起步阶段,研究成果较少。本文从一定程度上弥补了已有研究仅针对某类商品或者单种购物模式(网络购物或者实体购物)进行研究,以及地理领域对居民购物行为及其空间影响关注较少[2,42]等不足。但是本文对信息时代的城市空间变化趋势、行为空间引导和城市零售业未来的发展方向等方面探讨尚不够深入,选取的建成环境因素也相对简单,在未来研究中需要进一步加强。

The authors have declared that no competing interests exist.


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以信息技术进步为核心的信息革命已经成为推动国家、区域与城市社会经济发展及其快速转型的重要动力,并持久、深刻地冲击和改变着工业革命以来人类对社会经济及其空间结构形成的固有认识。当前,移动通信技术的进步及其应用,与高速铁路的加快建设、城市区域化的加速和智慧城市的建设一起,正将世界带入一个全新的移动信息时代。由于时间和空间概念的重新定义,全新时空观的出现,使得以空间问题为核心内容的城市地理学面临着根本性的变革。在移动信息技术的支撑下,城市地理学的研究范式、方法和内容都开始发生巨大的变化,传统的理论框架已逐渐不能满足当前研究的需要。本文重点分析了移动信息技术影响下的地理空间与网络信息空间的变化,提出了基于移动信息技术的移动社会理论框架。进而对移动信息时代城市地理学的研究方法、研究重点进行了探讨,希望运用城市地理学的研究更好地服务于移动信息时代的城市与区域的发展、规划与管治。
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Travel, like many other aspects of daily life, is being transformed by the information technology revolution. Accessibility can no longer be measured only in terms of travel time, distance or generalized travel cost. Information technology gives people virtual accessibility to a rapidly growing range of activities. E-commerce has become a catalyst for structural changes in the freight transportation industry and is changing where freight moves, the size of typical shipments and the time within which goods must be delivered. In this paper we explore some of the potential effects of information technology on transportation, both personal and freight.
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The proliferation of Internet shopping has imposed enormous pressure on traditional stores. Few studies have examined the geographic distribution of online buyers and its implications on retail development and transportation. Using 585 Internet users in the Minneapolis and Saint Paul, Minnesota, metropolitan area, this study develops structural equation models to test two competing hypotheses regarding the connections between spatial attributes and e-shopping: diffusion of innovation and efficiency. The results demonstrate that the influence of shopping accessibility on e-shopping is not uniform and depends on the locations in metropolitan areas. Specifically, Internet users living in urban areas, areas with greater shopping accessibility, or both tend to purchase online more often than their counterparts in other areas because the former are better educated and use the Internet more than the latter. However, low shopping accessibility in exurban areas does promote the use of e-shopping as compared with exurban areas with relatively high shopping accessibility.
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Information and communications technologies (ICTs) are affecting an ever-increasing array of household activities. Although considerable research has documented patterns of ICT use and sociodemographic profiles of ICT users, surprisingly little research has examined the role of spatial attributes such as accessibility, ICT availability, and levels of congestion in ICT-related activities. This paper aims to answer questions related to the propensity of residents in metropolitan areas to use the Internet for e-commerce, e-banking, and other financial transactions and how such use is affected by spatial attributes of retail and bank accessibility and traffic congestion. First, a snapshot of aggregate patterns of ICT use in the United States is provided, and past theories are described. Next, the methodology is described for administering a mail-out and mail-back survey of households in the spring of 2003 (including Seattle, Washington; Kansas City, Kansas and Missouri; and Pittsburgh, Pennsylvania). The survey measured participation in ICT-based activities in the form of shopping on the Internet (referred to as e-shopping), electronic banking, and other financial transactions. Finally, analyses are presented that focus on the degree to which the use of such activities is shaped by factors of accessibility, ICT availability, and traffic congestion. Contrary to expectations, the results suggest that, for the most part, spatial attributes do not appear to play a significant or substantive role in affecting rates of ICT use.
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Environment and Planning B: Planning and Design, 2009, 36(2): 262-278.

https://doi.org/10.1068/b34014t      URL      [本文引用: 1]      摘要

Recent studies have examined what factors affect the adoption of e-shopping (electronic shopping), why people adopt e-shopping, and what changes in activity – travel patterns will occur as a response to e-shopping. Very few studies to date, however, have investigated the impact of geographic context on people’s e-shopping behavior. This study reexamines the explanatory factors that are related to people’s e-shopping patterns through a study of the Columbus Metropolitan Area, OH. It focuses on the effect of accessibility to local shops and the residential context on the adoption of e-shopping and the frequency of buying online. Using an activity – Internet diary dataset, the results suggest that people with lower levels of accessibility to local shopping opportunities are more likely to engage in e-shopping, since the Internet enhances the efficiency of shopping by providing more product information and by eliminating the need of travel in the physical world. Further, people who live in areas with a white majority are more likely to adopt e-shopping. The magnitude of the impact of these context factors on e-shopping, however, is quite small.
[18] Zhai Q, Cao X, Mokhtarian P L, et al.

The interactions between e-shopping and store shopping in the shopping process for search goods and experience goods.

Transportation, 2016, doi:10.1007/s11116-016-9683-9.

URL      [本文引用: 1]      摘要

When exploring the interactions between e-shopping and store-shopping, most empirical studies regarded shopping as a transaction, but did not consider internet use in other stages of the shopping process, which has transportation implications. Few studies have conducted comparative analyses between different types of products. Using 952 internet users in two cities in Northern California, this study explores the interactions in the shopping process for two types of products: search goods and experience goods. We find that for internet buyers, clothing is more likely than books to be associated with store visiting for both information search and product trial. Online pre-purchase behaviors were more likely to facilitate cross-channel shopping than those at a store. A comparison with an earlier study shows more similarities than differences between the two studies, suggesting a certain amount of spatio-temporal generalizability of relationships.
[19] 柴彦威, 沈洁, 翁桂兰.

上海居民购物行为的时空间特征及其影响因素

. 经济地理, 2008, 28(2): 221-227.

URL      [本文引用: 2]      摘要

基于上海市居民购物行为的问卷调查数据,研究居民购物行为的时空间特征,并从主观决策和客观物质空间的两个方面探讨其影响因素.结果表明,上海市居民购物行为表现出低频率、夜间化、短距离以及非机动与公交出行方式为主的一般特征;商品购物出行的时空间等级明显,但具有分散化和扁平化的特征.其中,不同商品购物活动空间选择因素的不同导致其购物出行范围的等级性差异,而城市商业物质环境和空间分布更多地决定了居民购物行为的具体方式、空间大小和集中程度.

[Chai Yanwei, Shen Jie, Weng Guilan.

A study on activity space of shopping of shanghai residents: Temporal and spatial characteristics and relative influencing factors.

Economic Geography, 2008, 28(2): 221-227.]

URL      [本文引用: 2]      摘要

基于上海市居民购物行为的问卷调查数据,研究居民购物行为的时空间特征,并从主观决策和客观物质空间的两个方面探讨其影响因素.结果表明,上海市居民购物行为表现出低频率、夜间化、短距离以及非机动与公交出行方式为主的一般特征;商品购物出行的时空间等级明显,但具有分散化和扁平化的特征.其中,不同商品购物活动空间选择因素的不同导致其购物出行范围的等级性差异,而城市商业物质环境和空间分布更多地决定了居民购物行为的具体方式、空间大小和集中程度.
[20] 焦华富, 韩会然.

中等城市居民购物行为时空决策过程及影响因素: 以安徽省芜湖市为例

. 地理学报, 2013, 68(6): 750-761.

URL      Magsci      [本文引用: 1]      摘要

购物决策过程是居民根据自身需求进行购物信息搜寻、购物目的地选择等方面的完整过程,是居民购物行为发生与实施的前提和基础,已经成为城市地理学研究的热点之一。本文利用2011 年芜湖市居民购物行为调查问卷数据,通过构建居民购物出行的嵌套Logit 模型,从购物出行模式决策、购物初始时间决策、购物目的地决策、购物出行交通方式决策等四个层面对芜湖市居民购物行为的决策过程及影响因素进行了探讨。结果表明:① 居民属性特征对购物出行模式决策具有显著影响,男性居民选择单纯购物出行的概率较大,而女性居民、有家人陪伴的居民更倾向多目的出行;在中心城区居住及出行距离远的居民偏好中午进行多目的购物概率较大,出行距离集中在1~2 km的范围内,而近郊区居民则避开下班高峰期进行购物,倾向选择2~5 km的购物空间范围;② 具有私家车的男性居民在晚上进行购物的概率比较大,其出行概率是上午的2.94 倍,更加偏好远距离出行;居民上下班途中购物大多发生在下班时间,偏好5~8 km范围的远距离;有朋友陪伴的居民更倾向上午依赖公共交通进行远距离出行;③ 以家为购物出发地点的居民的购物更倾向19:00 之后并且偏好远距离出行,公交车依然是芜湖市居民购物出行的主要载体。

[Jiao Huafu, Han Huiran.

Research on temporal and spatial decision-making process and influencing factors of residents' shopping behavior in medium-sized cities: A case study of Wuhu city in Anhui province.

Acta Geographica Sinica, 2013, 68(6): 750-761.]

URL      Magsci      [本文引用: 1]      摘要

购物决策过程是居民根据自身需求进行购物信息搜寻、购物目的地选择等方面的完整过程,是居民购物行为发生与实施的前提和基础,已经成为城市地理学研究的热点之一。本文利用2011 年芜湖市居民购物行为调查问卷数据,通过构建居民购物出行的嵌套Logit 模型,从购物出行模式决策、购物初始时间决策、购物目的地决策、购物出行交通方式决策等四个层面对芜湖市居民购物行为的决策过程及影响因素进行了探讨。结果表明:① 居民属性特征对购物出行模式决策具有显著影响,男性居民选择单纯购物出行的概率较大,而女性居民、有家人陪伴的居民更倾向多目的出行;在中心城区居住及出行距离远的居民偏好中午进行多目的购物概率较大,出行距离集中在1~2 km的范围内,而近郊区居民则避开下班高峰期进行购物,倾向选择2~5 km的购物空间范围;② 具有私家车的男性居民在晚上进行购物的概率比较大,其出行概率是上午的2.94 倍,更加偏好远距离出行;居民上下班途中购物大多发生在下班时间,偏好5~8 km范围的远距离;有朋友陪伴的居民更倾向上午依赖公共交通进行远距离出行;③ 以家为购物出发地点的居民的购物更倾向19:00 之后并且偏好远距离出行,公交车依然是芜湖市居民购物出行的主要载体。
[21] Choo S, Lee T, Mokhtarian P.

Do transportation and communications tend to be substitutes, complements, or neither? U.S. consumer expenditures perspective, 1984-2002.

Transportation Research Record: Journal of the Transportation Research Board, 2007. doi: 10.3141/2010-14.

URL      [本文引用: 1]      摘要

With aggregate data from the U.S. Consumer Expenditure Survey for 19 years, 1984 through 2002, this study analyzes relationships between expenditures on transportation and communications. Several classification schemes for expenditure categories were used, from the most aggregate [two categories (transportation and communications)] to the most disaggregate [nine transportation categories (new vehicle purchases, used vehicle purchases, vehicle finance charges, gasoline and motor oil, vehicle maintenance and repairs, vehicle insurance, public transportation, out-of-town lodging, and other entertainment including bikes and recreational vehicles) and five communications categories (telephone service; miscellaneous household equipment including phones and computers; television, radio, and sound equipment; postage and stationery; and reading)]. Aggregate demand system modeling (in particular, the linear approximate almost ideal demand system) was then used to determine the relationships between expenditures on transportation and those on communications, again for several different classifications. The model results indicate that transportation and communications categories have substitution and complementarity relationships, often not symmetric. However, a dominant effect of complementarity can be found in the influence of communications on transportation.
[22] Mokhtarian P L.

A typology of relationships between telecommunications and transportation.

Transportation Research Part A: General, 1990, 24(3): 231-242.

https://doi.org/10.1016/0191-2607(90)90060-J      URL      摘要

This paper defines the relationship between telecommunications and transportation, by expanding on linkages already identified in the literature, by identifying additional relationships, and by putting these relationships into a robust conceptual framework. There are conceptual, physical, analytical, and regulatory parallels between telecommunications and transportation. Telecommunications affects the demand for, and supply of, transportation — and vice versa. In the broadest sense, all communication requires transportation in order to occur: transportation either of people, of objects, or of electronic impulses. In other words, communication takes place via one or more of those three modes. It is suggested that “communication breeds communication.” That is, the easier it is to communicate (whether through travel or communications), or the more that one or another form of communication takes place, the more that communication as a whole is stimulated. The relative shares of each of the three modes of communication may vary as one mode partially substitutes for another, but the absolute amounts of communication via each mode are likely to increase. Two empirical studies are summarized, one illustrating that teleconferencing increased travel, the other illustrating that telecommuting decreased travel. Other implications for transportation planning are highlighted.
[23] Pendyala R M, Goulias K G, Kitamura R.

Impact of telecommuting on spatial and temporal patterns of household travel.

Transportation, 1991, 18(4): 383-409.

[24] Salomon I.

Telecommunications and travel relationships: A review.

Transportation Research Part A: General, 1986, 20(3): 223-238.

https://doi.org/10.1016/0191-2607(86)90096-8      URL      [本文引用: 1]      摘要

No abstract provided.
[25] Farag S, Krizek K J, Dijst M.

E-shopping and its relationship with in-store shopping: Empirical evidence from the Netherlands and the USA.

Transport Reviews, 2006, 26(1): 43-61.

https://doi.org/10.1080/01441640500158496      URL      [本文引用: 1]      摘要

Despite considerable examination of the impact of telecommunications on travel, little empirical evidence sheds light on the impact of e‐shopping on travel—a recent and increasingly popular form of telecommunications. This paper analyses determinants of online buying and their relationship with in‐store shopping, using empirical data obtained from Minneapolis, USA, and Utrecht, the Netherlands. Based on chi‐square tests and logistic and ordinary least‐squares regressions, the results indicate that online buying is affected by sociodemographics and spatial characteristics of people, their Internet experience, and their attitudes towards in‐store shopping. US respondents who prefer to see products in person are less likely to buy online. Dutch respondents are more likely to buy online as travel times to shops are shorter. At first sight, this counterintuitive result might be related to an urban, innovative lifestyle that supports e‐shopping. A more detailed analysis of Dutch online buyers reveals that they make more shopping trips than non‐online buyers and have a shorter shopping duration. The results indicate that the relationship between online buying and in‐store shopping is not one of substitution but of complementarity.
[26] Ferrell C.

Home-based teleshoppers and shopping travel: Do teleshoppers travel less?

Transportation Research Record: Journal of the Transportation Research Board, 2004, 1894: 241-248.

https://doi.org/10.3141/1894-25      URL      摘要

Some have assumed that teleshopping will become a functional substitute for traditional retail shopping and thereby reduce physical shopping trips and vehicle miles traveled. More recent studies have painted a far more complex picture, in which a combination of lifestyle, shopping opportunities, and the costs of travel all play a role in a person's choice of shopping modes. In this study, data from an activity-diary survey collected by the Metropolitan Transportation Commission, California, were analyzed to gain insights into the degree to which teleshopping substitutes for traditional out-of-home shopping trips, person miles traveled for shopping, and shopping-trip chains. A two-step linear regression model was used to estimate the effects of home-based teleshopping. Results indicate that teleshopping households engage in more shopping trips and chain more of their shopping trips. It is hypothesized that teleshopping has a complementary effect on out-of-home shopping and leads to more shopping trip making and that the time for these additional trips and home teleshopping activities is enabled through efficiencies gained from increased trip chaining. Time saved through increased trip chaining and teleshopping may provide the additional time needed to shop more--both from within the home and outside the home.
[27] Ferrell C.

Home-based teleshopping and shopping travel: Where do people find the time?

Transportation Research Record: Journal of the Transportation Research Board, 2005, 1926: 212-223.

https://doi.org/10.3141/1926-25      URL      [本文引用: 1]      摘要

Structural equation modeling techniques were used to explore the trade-offs that people make when teleshopping from home. Early in the development and growth of online shopping, many assumed that it would become a direct substitute for traditional retail (out-of-home) shopping and thereby reduce shopping trips and vehicle miles traveled. A growing body of research on the interplay between the use of information and communications technologies suggests that people shop and travel for a multitude of reasons that depend on the interplay between lifestyle, availability and convenience of shopping opportunities and the demands of other activities during the day. Using the San Francisco Bay Area Travel Survey 2000 from California, this paper performs an activities analysis to investigate these relationships. Time use variables predict the amount of time each individual spends during the day on work, maintenance, discretionary, and shopping activities both inside and outside the home. These activities are used to predict the amount of shopping travel each person undertook. Results suggest that people substitute home teleshopping time for shopping travel time and that teleshoppers take fewer shopping trips and travel shorter total distances for shopping purposes. Variables constructed to represent the degree to which people are "time-starved" from the demands of their work and maintenance activities revealed that female heads of households tend to teleshop more, make more shopping trips and shopping trip chains, do more out-of-home shopping, and shop travel for longer periods than the rest of the survey population.
[28] 韩会然, 杨成凤, 宋金平.

芜湖市居民购物出行空间的等级结构演变特征及驱动机制

. 地理研究, 2014, 33(1): 107-118.

https://doi.org/10.11821/dlyj201401010      URL      Magsci      [本文引用: 1]      摘要

居民购物出行空间是城市内部空间结构的重要组成部分。在对芜湖市居民问卷调查和访谈的基础上,分析了居民购物出行空间等级结构的演变特征及驱动机制。结果表明:① 芜湖市居民购物出行的空间距离具有减小的趋势,变化幅度最大的是家用电器与服装衣饰类等高等级商品,从中心区与郊区来看,中心城区居民的出行距离变化不大,郊区居民的购物出行距离明显缩短,反映了城市商业空间格局的分散化趋向。② 芜湖市居民购买不同类型商品出行的空间等级层次分明,基本符合中心地理论中的等级关系,购物地点逐渐从高级中心地向相对较低级中心地转移;日常用品类商品购物地等级下降最为明显,由2001年的介于三、四级中心地下降到2011年的四、五级中心地之间,下降了1个空间等级,具有明显的就近居住地购买趋向。③ 从政府政策作用、零售商供给、居住主体偏好等三方面剖析了居民购物出行空间演变的驱动机制,认为商业网点发展规划、新业态的集聚与扩散、职住分离与居住-消费空间错位、交通条件的改善、居民购物需求偏好等因素影响着居民购物出行空间的等级结构演变。

[Han Huiran, Yang Chengfeng, Song Jinping.

The evolutoin of the hierarchy of shopping trip space for residents in Wuhu city and its driving mechanism.

Geographical Research, 2014, 33(1): 107-118.]

https://doi.org/10.11821/dlyj201401010      URL      Magsci      [本文引用: 1]      摘要

居民购物出行空间是城市内部空间结构的重要组成部分。在对芜湖市居民问卷调查和访谈的基础上,分析了居民购物出行空间等级结构的演变特征及驱动机制。结果表明:① 芜湖市居民购物出行的空间距离具有减小的趋势,变化幅度最大的是家用电器与服装衣饰类等高等级商品,从中心区与郊区来看,中心城区居民的出行距离变化不大,郊区居民的购物出行距离明显缩短,反映了城市商业空间格局的分散化趋向。② 芜湖市居民购买不同类型商品出行的空间等级层次分明,基本符合中心地理论中的等级关系,购物地点逐渐从高级中心地向相对较低级中心地转移;日常用品类商品购物地等级下降最为明显,由2001年的介于三、四级中心地下降到2011年的四、五级中心地之间,下降了1个空间等级,具有明显的就近居住地购买趋向。③ 从政府政策作用、零售商供给、居住主体偏好等三方面剖析了居民购物出行空间演变的驱动机制,认为商业网点发展规划、新业态的集聚与扩散、职住分离与居住-消费空间错位、交通条件的改善、居民购物需求偏好等因素影响着居民购物出行空间的等级结构演变。
[29] 仵宗卿, 柴彦威, 戴学珍, .

购物出行空间的等级结构研究: 以天津市为例

. 地理研究, 2001, 20(4): 479-488.

URL      Magsci      [本文引用: 1]      摘要

<p>以天津市为例,通过大量问卷调查,总结出城市居民购物出行的空间圈层结构,为国际间相关问题的横向对比奠定了基础。在中地论的基础上,创建了系统描述和详细分析购物出行空间等级结构的新模式,为今后的相关研究提供一种制度和方法。在市场细分的基础上,总结出天津市三种不同收入阶层的购物出行空间等级结构类型,并对其进行了尝试性解释。</p>

[WuZongqing, Chai Yanwei, Dai Xuezhen, et al.

On hierarchy of shopping trip space for urban residents: A case study ofTianjing city.

Geographical Research, 2001, 20(4): 479-488.]

URL      Magsci      [本文引用: 1]      摘要

<p>以天津市为例,通过大量问卷调查,总结出城市居民购物出行的空间圈层结构,为国际间相关问题的横向对比奠定了基础。在中地论的基础上,创建了系统描述和详细分析购物出行空间等级结构的新模式,为今后的相关研究提供一种制度和方法。在市场细分的基础上,总结出天津市三种不同收入阶层的购物出行空间等级结构类型,并对其进行了尝试性解释。</p>
[30] Zhen F, Cao X, Mokhtarian P L, et al.

Associations between online purchasing and store purchasing for four types of products in Nanjing, China.

Transportation Research Record: Journal of the Transportation Research Board, 2016, 2566: 93-101.

https://doi.org/10.3141/2566-10      URL      [本文引用: 6]     

[31] Glick P C.

The family cycle.

American Sociological Review, 1947, 12(2): 164-174.

[本文引用: 1]     

[32] Roodman D M.

Fitting fully observed recursive mixed-process models with CMP.

Stata Journal, 2011, 11(2): 159-206.

Magsci      [本文引用: 3]      摘要

At the heart of many econometric models are a linear function and a normal error. Examples include the classical small-sample linear regression model and the probit, ordered probit, multinomial probit, tobit, interval regression, and truncated-distribution regression models. Because the normal distribution has a, natural multidimensional generalization, such models can be combined into multiequation systems in which the errors share a multivariate normal distribution. The literature has historically focused on multistage procedures for fitting mixed models, which are more efficient computationally, if less so statistically, than maximum likelihood. Direct maximum likelihood estimation has been made more practical by faster computers and simulated likelihood methods for estimating higher-dimensional cumulative normal distributions. Such simulated likelihood methods include the Geweke-Hajivassiliou-Keane algorithm (Geweke, 1989, Econometrics 57: :1317-1339; Hajivassiliou and McFadden, 1998, Econometrics 66: 863-896; Keane, 1994, Econometrics 62: 95-116). Maximum likelihood also facilitates a generalization to switching, selection, and other models in which the number and types of equations vary by observation. The Stata command cmp fits seemingly unrelated regressions models of this broad family. Its estimator is also consistent for recursive systems in which all endogenous variables appear on the right-hand sides as observed. If all the equations are structural, then estimation is full-inforrnation maximum likelihood. If only the final stage or stages are structural, then estimation is limited-information maximum likelihood. cmp can mimic a score of built-in and user-written Stata commands. It is also appropriate for a panoply of models that previously were hard to estimate. Heteroskedasticity, however, can render cmp inconsistent. This article explains the theory and implementation of cmp and of a related Mata function, ghk 2 (), that implements the Geweke-Hajivassiliou-Keane algorithm.
[33] Carter B E, McGoldrick M E. The Changing Family Life Cycle: A Framework for Family Therapy. New York: Gardner Press, 1988.

[本文引用: 1]     

[34] Lansing J B, Kish L.

Family life cycle as an independent variable.

American Sociological Review, 1957, 22(5): 512-519.

https://doi.org/10.2307/2089474      URL      摘要

Abstract The abstract for this document is available on CSA Illumina.To view the Abstract, click the Abstract button above the document title.
[35] 桂晶晶, 柴彦威.

家庭生命周期视角下的大都市郊区居民日常休闲特征

. 地域研究与开发, 2014, 33(2): 30-35.

Magsci      摘要

在郊区化和休闲大众化的背景下,休闲成为衡量郊区生活方式、提升郊区居民生活质量的重要侧面。从家庭生命周期的视角出发,将居民划分为单身、新婚、满巢Ⅰ、满巢Ⅱ和空巢5个阶段,通过对2012年北京市上地—清河地区居民的问卷调查数据的方差分析,剖析家庭生命周期对日常休闲行为的影响。乘坐公共交通与朋友一起进行购物、KTV和看电影等娱乐活动是单身阶段的主流休闲方式;家庭成员成为婚后阶段休闲的主要同伴;孩子出生以后,私家车出行成为满巢Ⅰ阶段的主要交通方式,每次休闲的平均时间变长;满巢Ⅱ阶段,参与体育锻炼的郊区居民变多;空巢阶段的居民以自然型休闲活动为主,在社区内休闲的比例上升,与家庭成员一起休闲的比例降低。

[Gui Jingjing, Chai Yanwei.

Suburban daily leisure activities from the perspective of family life cycle: Case of Shangdi-Qinghe Area in Beijing.

Areal Research and Development, 2014, 33(2): 30-35.]

Magsci      摘要

在郊区化和休闲大众化的背景下,休闲成为衡量郊区生活方式、提升郊区居民生活质量的重要侧面。从家庭生命周期的视角出发,将居民划分为单身、新婚、满巢Ⅰ、满巢Ⅱ和空巢5个阶段,通过对2012年北京市上地—清河地区居民的问卷调查数据的方差分析,剖析家庭生命周期对日常休闲行为的影响。乘坐公共交通与朋友一起进行购物、KTV和看电影等娱乐活动是单身阶段的主流休闲方式;家庭成员成为婚后阶段休闲的主要同伴;孩子出生以后,私家车出行成为满巢Ⅰ阶段的主要交通方式,每次休闲的平均时间变长;满巢Ⅱ阶段,参与体育锻炼的郊区居民变多;空巢阶段的居民以自然型休闲活动为主,在社区内休闲的比例上升,与家庭成员一起休闲的比例降低。
[36] 许春晓, 田媛, 姜漫, .

家庭生命周期与旅游态度的关联研究: 以长沙市居民为例

. 旅游学刊, 2012, 27(9): 65-72.

URL      [本文引用: 1]      摘要

家庭是旅游态度形成的最重要环境背景,也一直是旅游活动的重要组 织单元,探究家庭生命周期与旅游态度的关系意义重大.文章依据已有研究成果,建立家庭生命周期模型,制定旅游态度量表,以问卷工具面向长沙市居民进行调 查,获得基础数据,运用因子分析得到了追求享受、强调卫生、看重设施、向往体验、关注身心健康等5个方面的旅游态度主成分,通过验证性因子分析后,再用相 关分析、多元回归分析探究家庭生命周期与旅游态度5个主成分的关系.结果表明,随着家庭生命周期的演进,人们愈发追求享受、看重设施、关注身心健康.无巢 期人群看重设施和关注身心健康的表现低于其他阶段人群,空巢期人群追求享受的表现高于其他阶段人群,空巢期、鳏寡期人群关注身心健康的表现高于其他阶段人 群,满巢期人群向往体验的表现高于其他阶段人群.

[Xu Chunxiao, Tian Yuan, Jiang Man, et al.

Study on the correlation between famiiy life circle and travel attitude: Taking residents in Changsha for example.

Tourism Tribune, 2012, 27(9): 65-72.]

URL      [本文引用: 1]      摘要

家庭是旅游态度形成的最重要环境背景,也一直是旅游活动的重要组 织单元,探究家庭生命周期与旅游态度的关系意义重大.文章依据已有研究成果,建立家庭生命周期模型,制定旅游态度量表,以问卷工具面向长沙市居民进行调 查,获得基础数据,运用因子分析得到了追求享受、强调卫生、看重设施、向往体验、关注身心健康等5个方面的旅游态度主成分,通过验证性因子分析后,再用相 关分析、多元回归分析探究家庭生命周期与旅游态度5个主成分的关系.结果表明,随着家庭生命周期的演进,人们愈发追求享受、看重设施、关注身心健康.无巢 期人群看重设施和关注身心健康的表现低于其他阶段人群,空巢期人群追求享受的表现高于其他阶段人群,空巢期、鳏寡期人群关注身心健康的表现高于其他阶段人 群,满巢期人群向往体验的表现高于其他阶段人群.
[37] Farag S, Dijst M, Lanzendorf M.

Exploring the use of e-shopping and its impact on personal travel behavior in the Netherlands.

Transportation Research Record: Journal of the Transportation Research Board, 2003, 1858: 47-54.

https://doi.org/10.3141/1858-07      URL      [本文引用: 1]      摘要

The Internet makes it possible to conduct activities such as working and shopping without traveling to activity places. As e-shopping becomes popular, it can fundamentally change travel behavior. The presented study uses a literature review, an Internet survey of e-shoppers, and the Netherlands National Travel Survey to analyze the possible impact of e-shopping on travel behavior. The findings indicate that people living in areas with relatively many shopping opportunities buy online as often as do people who live in areas with relatively few shopping opportunities. People who spend a lot of time on in-store shopping typically are women, are more than 60 years old, have a low level of education, are on a low income, and live in a more urbanized area. Online buyers can be characterized as men between ages 25 and 40 who are highly educated, have a high income, and live in a less urbanized area. Four hypotheses were derived to describe the future impact of e-shopping on travel. First, some shopping time will be saved and used for other maintenance or leisure activities instead. Second, the enlargement and fragmentation of an individual's action spaces will be fostered and so lead to increased travel distances. Third, e-shopping will affect travel behavior most in the urbanized western part and in the less urbanized parts of the Netherlands. Finally, a reduction in car travel in the less urbanized areas of the Netherlands and a reduction in walking and cycling in the more urbanized areas of the Netherlands are expected.
[38] 李志兰, 江林.

家庭生命周期对我国居民消费意愿的影响研究

. 上海经济研究, 2014, (2): 126-132.

URL      [本文引用: 1]      摘要

家庭是一个动态的消费主体,每个生命周期阶段中的家庭,其消费意向、消费结构和水平都具有独特的特点。与此前主要关注家庭消费行为结果的研究不同,本研究重点关注家庭消费行为的心理倾向,致力于从消费行为学的角度来探索家庭生命周期对消费意愿不同层面的影响。研究结果表明,不同生命周期阶段的家庭在消费总量、消费档次、借贷消费、奢侈品消费及不同产品和服务的消费意愿上会呈现不同的偏好,在特定产品和服务消费意愿的作用强度也具有明显差异。满巢2阶段家庭是当前我国社会消费的中坚力量,单身和新婚阶段的家庭是社会消费趋势的引领者,而满巢3、空巢2和孤寡阶段家庭的消费驱动力则明显不足。本研究对于国家消费政策和企业的营销决策的制定都有重要的启示意义。

[Li Zhilan, Jiang Lin.

The impact of family life cycle on willingness to pay in China.

Shanghai Econmic Review, 2014, (2): 126-132.]

URL      [本文引用: 1]      摘要

家庭是一个动态的消费主体,每个生命周期阶段中的家庭,其消费意向、消费结构和水平都具有独特的特点。与此前主要关注家庭消费行为结果的研究不同,本研究重点关注家庭消费行为的心理倾向,致力于从消费行为学的角度来探索家庭生命周期对消费意愿不同层面的影响。研究结果表明,不同生命周期阶段的家庭在消费总量、消费档次、借贷消费、奢侈品消费及不同产品和服务的消费意愿上会呈现不同的偏好,在特定产品和服务消费意愿的作用强度也具有明显差异。满巢2阶段家庭是当前我国社会消费的中坚力量,单身和新婚阶段的家庭是社会消费趋势的引领者,而满巢3、空巢2和孤寡阶段家庭的消费驱动力则明显不足。本研究对于国家消费政策和企业的营销决策的制定都有重要的启示意义。
[39] 岳彩周.

商业布局乱象求解

. 中国连锁, 2013, (S1): 36-43.

[本文引用: 1]     

[Yue Caizhou.

How to solve the chaos of commercial layout.

China Chain Store, 2013, (S1): 36-43.]

[本文引用: 1]     

[40] 陆亦琦.

实体店:生存还是死亡?

销售与市场: 评论版, 2014, (8): 16-17.

URL      [本文引用: 1]      摘要

类似“双11”的“超级销售日”规模越来越惊人,很多人相信,实体店被其取而代之只是一个时间问题,事实真的如此吗?

[Lu Yiqi.

Stores: Survival or death?

Sales and marketing: Comments Edition, 2014, (8): 16-17.]

URL      [本文引用: 1]      摘要

类似“双11”的“超级销售日”规模越来越惊人,很多人相信,实体店被其取而代之只是一个时间问题,事实真的如此吗?
[41] 曾思敏, 陈忠暖.

国外网上零售商业空间及其影响效应研究综述

. 人文地理, 2013, 28(1): 36-42.

URL      [本文引用: 1]      摘要

基于可获得的国外文献,文章回顾了1990年代中期以来,国外地理学科关于网上零售引发的商业空间和其他活动空间的响应以及改变的探讨。目前,国外地理学者主要致力于以下几个方面的研究:(1)网上商店的区位问题及其空间扩散过程;(2)网上零售对购物模式的组织和空间的影响;(3)城市交通空间结构对网上零售的响应;(4)网上零售产业渗透对居住空间的影响。相关研究基本涉及了在网上零售产业背景下可能出现的各类地理问题,值得刚开始致力于这一领域的其他国家学者(例如中国)参考和借鉴。此外,文章从研究尺度、研究对象以及研究内容等方面评价了国外已有研究。

[Zeng Simin, Chen Zhongnuan.

A review on spatial organization of e-retail and its impact abroad.

Human Geography, 2013, 28(1): 36-42.]

URL      [本文引用: 1]      摘要

基于可获得的国外文献,文章回顾了1990年代中期以来,国外地理学科关于网上零售引发的商业空间和其他活动空间的响应以及改变的探讨。目前,国外地理学者主要致力于以下几个方面的研究:(1)网上商店的区位问题及其空间扩散过程;(2)网上零售对购物模式的组织和空间的影响;(3)城市交通空间结构对网上零售的响应;(4)网上零售产业渗透对居住空间的影响。相关研究基本涉及了在网上零售产业背景下可能出现的各类地理问题,值得刚开始致力于这一领域的其他国家学者(例如中国)参考和借鉴。此外,文章从研究尺度、研究对象以及研究内容等方面评价了国外已有研究。
[42] 章雨晴, 甄峰, 张永明.

南京市居民网络购物行为特征: 以书籍和衣服为例

. 地理科学进展, 2016, 35(4): 476-486.

https://doi.org/10.18306/dlkxjz.2016.04.008      URL      [本文引用: 1]      摘要

随着信息通讯技术(ICT)的飞速发展,网络购物日益成为当今社会经济生活的重要组成部分,深刻影响了居民的购物消费行为和传统零售业的发展.不同国家、不同人群、不同商品类型的居民购物行为具有一定差异.本文在问卷调查的基础上,分析南京市居民网络购物行为特征,并区分不同商品类型的居民网购行为特征差异,对理解网络购物和实体购物相互作用关系及网购对于交通出行和城市零售业空间的影响具有重要意义.结果表明:居民网络购物行为是一个复杂的过程,不同类型商品、不同频率网购人群在社会经济属性、空间特征、网络使用及购物习惯、购物态度上有明显差异,其中不同频率网购衣服的人群在特征上的差异更为显著,体验型商品对网络购物这一新型购物方式的响应更为强烈.

[Zhang Yuqing, Zhen Feng, Zhang Yongming.

Characteristics of e-shopping behavior of Nanjing residents: A case of books and clothes.

Progress in Geography, 2016, 35(4): 476-486.]

https://doi.org/10.18306/dlkxjz.2016.04.008      URL      [本文引用: 1]      摘要

随着信息通讯技术(ICT)的飞速发展,网络购物日益成为当今社会经济生活的重要组成部分,深刻影响了居民的购物消费行为和传统零售业的发展.不同国家、不同人群、不同商品类型的居民购物行为具有一定差异.本文在问卷调查的基础上,分析南京市居民网络购物行为特征,并区分不同商品类型的居民网购行为特征差异,对理解网络购物和实体购物相互作用关系及网购对于交通出行和城市零售业空间的影响具有重要意义.结果表明:居民网络购物行为是一个复杂的过程,不同类型商品、不同频率网购人群在社会经济属性、空间特征、网络使用及购物习惯、购物态度上有明显差异,其中不同频率网购衣服的人群在特征上的差异更为显著,体验型商品对网络购物这一新型购物方式的响应更为强烈.

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