Journal of Textile Research ›› 2022, Vol. 43 ›› Issue (06): 157-164.doi: 10.13475/j.fzxb.20210700208

• Apparel Engineering • Previous Articles     Next Articles

Empirical study on Beijing residents' emotion of green consumption of clothing

NING Jun1(), SHI Jia2   

  1. 1. Beijing Philosophy and Social Sciences Capital Costume Culture and Clothing Industry Research Base, Beijing Institute of Fashion Technology, Beijing 100029, China
    2. School of Business,Beijing Institute of Fashion Technology, Beijing 100029, China
  • Received:2021-07-01 Revised:2022-01-11 Online:2022-06-15 Published:2022-07-15

Abstract:

In order to explore the relationship among Beijing residents' perceptions, attitudes, intention and behavior of green clothing consumption, and to help achieve the goals of carbon peak and carbon neutrality from the consumer perspective, a survey including clothing green consumption perceptions was conducted based on 1 005 questionnaires, involving structured equations on knowledge, attitude, consumption intention of five green clothing brands(material, producting packaging, transportation, post-sales) and five green clothing consumption behaviors(collection, purchase, use, care, disposal). The results show that consumers' cognition of green clothing consumption significantly affects their consumption attitudes, which in turn influences their intention to consume green clothing brands, and their attitudes to transform green consumption behaviors to a certain extent. The consumption intention of green packaging and post-sales clothing brands consumption intention have a positive and significant impact on consumers' collection, use, care and disposal of clothing green information, but it is difficult to influence green purchasing behavior. The consumption intention of green materials, production and transportation clothing brands does not have a significant impact on consumers' five green clothing consumption behaviors. On this basis, strengthening the government's popular education on green clothing consumption knowledge, promoting the green development of enterprises and actively taking social responsibilities, and guiding consumers to practice a variety of green clothing consumption behaviors will help promote green clothing consumption.

Key words: clothing green consumption, consumption cognition, consumption attitude, green brand behavior intention, consumption behavior

CLC Number: 

  • F713.52

Fig.1

Logical framework diagram"

Tab.1

Basic statistics of survey sample"

潜变量 符号 测量题项
服装绿色
消费认知
C
C1 R-关于服装生产和穿着使用中对环境产生的负面影响,我知道的很少
C2 我可以正确识别服装上的环保标识
C3 R-购买服装时我没有查看吊牌环保标识的习惯
C4 我相信厂商的服装环保标识
服装绿色
消费态度
A
A1 R-我认为保护环境、节能减排是政府和企业的责任,与我关系不大
A2 去超市购物时,我会自带购物袋
A3 为了保护环境,我愿意放弃一些个人利益和生活便利
A4 我会主动向朋友家人宣传环保知识和技巧
绿色材料
服装品牌
消费意愿
IMR
IMR1 优选品牌:它会追踪和检测服装生产中使用的原料和化学制品
IMR2 优选品牌:它会提供第三方实验室检测结果来证实服装产品不含违禁成分
IMR3 优选品牌:它会使用对环境影响小的原料生产
绿色包装
服装品牌
消费意愿
IPK
IPK1 优选品牌:它会在有效保护产品的前提下使用更小、更轻的包装
IPK2 优选品牌:它会检测包装物所使用的原料
IPK3 优选品牌:它会在包装上减少黏合剂、标签、着色剂、油墨等的使用
IPK4 优选品牌:它会使用可回收包装物
绿色生产
服装品牌
消费意愿
IPD
IPD1 优选品牌:它会对外包的制造商提供环保指导:比如法律要求、最佳做法等
IPD2 优选品牌:它会在生产环节减少水资源使用
IPD3 优选品牌:它会在生产过程中减少产生纺织品固体废料
IPD4 优选品牌:它会鼓励供应商不断改善环保成效
绿色运输
服装品牌
消费意愿
ITP
ITP1 优选品牌:它会优化运输方案,减少运输中的碳排放
ITP2 优选品牌:它会选择注重环保的运输公司
绿色售后
服装品牌
消费意愿
IAS
IAS1 优选品牌:它与慈善机构或二手商店有合作伙伴关系
IAS2 优选品牌:它会提供服装使用后的处理方法指导
服装绿色
信息搜集
BIA
BIA1 R-我不关注与服装生产、穿着使用、废弃处置等有关的环保信息
BIA2 我会主动搜索、查询与服装生产、穿着使用、废弃处置等有关的环保信息
BIA3 我会留意阅读与服装生产、穿着使用、废弃处置等有关的环保信息
BIA4 我会转发分享与服装生产、穿着使用、废弃处置等有关的环保信息给大家
潜变量 符号 测量题项
服装绿色
购买BP
BP1 我总是买很多衣服,享受买买买的乐趣
BP2 我通常购买较少数量、更加经久耐穿的衣服
BP3 我会购买布料自己动手、或找人帮忙制作衣服
BP4 我会购买二手服装
服装绿色
使用BWU
BWU1 R-我喜欢穿新衣服,已有衣服穿几次就不穿了
BWU2 我尽量多穿已有的衣服
BWU3 我会尽量延长衣服的使用寿命
服装绿色
护理BIPC
BIPC1 我在不影响穿着的情况下尽量减少衣服的洗涤熨烫频率
BIPC2 使用洗衣机时,我让洗衣机满负荷工作
BIPC3 使用洗衣机时,我用适量洗涤剂以较低温度进行洗涤
BIPC4 我购买提供清楚的“产品护理”信息的衣服
BIPC5 我购买提供清楚的“维修服务”信息的衣服
服装绿色
处置BIDP
BIDP1 R-我把确定不要的旧衣物直接扔到垃圾箱里
BIDP2 对于过时或部分破损的衣服,我自己动手或送到改衣店修改成别的衣服或物品,重新使用
BIDP3 我把穿过的衣物直接送给亲戚、朋友或熟人
BIDP4 我参与旧衣捐赠活动
BIDP5 我把旧衣物投放到旧衣物回收箱里
BIDP6 我会将衣物交给提供旧衣回收服务的品牌
人口统计
变量
GEND 性别
AGE 年龄
HEDU 最高学历
MS 婚姻状况
PRO 职业
FMI 家庭月收入
PRN 常住人口

Tab.2

Basic statistics of the survey sample"

统计指标 分类指标 样本数 比例/%
性别 376 37.4
629 62.6
24岁及以下 354 35.2
年龄 25~44岁 477 47.5
45~54岁 147 14.6
55岁及以上 27 2.7
教育程度 高中/技校及以下 154 16.3
大专/高职 117 11.7
大学本科 505 49.7
硕士及以上 229 22.3
未婚 484 48.3
婚姻状况 已婚 499 49.3
离异 22 2.4
国有性质单位工作人员 90 8.7
专业技术人员 164 16.5
办事人员和有关人员 132 13.0
商业、服务业人员 122 12.6
农、林、牧、渔、水利业生产人员 17 1.7
生产、运输设备操作人员 26 2.5
职业 警察及军人 8 1.0
自由职业者 60 5.9
个体户、小摊主 31 3.1
不便分类的其他从业人员 27 2.5
学生 296 29.4
离退休人员 19 1.8
无业、待业 13 1.2
家庭
月收入
1万元以下 296 29.7
1万~3.9万元 574 57.1
4万~7.9万元 96 9.4
8万元及以上 39 4.3
常住
人口数
1~2人 146 14.4
3~4人 726 72.3
5人及以上 133 13.3

Tab.3

Reliability analysis results of scale"

分量表 Cronbach's
Alpha
系数
观察
变量
CITC 删除CICT
值较低项
目后整体
Cronbach's
Alpha系数
C 0.539 C1 0.457 0.348
C2 0.457 0.345
C3 0.256 0.533
C4 0.154 0.588
A 0.548 A1 0.327 0.484
A2 0.120 0.738
A3 0.513 0.357
A4 0.543 0.321
IMR 0.928 IMR1 0.859 0.889
IMR2 0.839 0.906
IMR3 0.858 0.891
IPK 0.932 IPK1 0.824 0.916
IPK2 0.846 0.909
IPK3 0.848 0.908
IPK4 0.840 0.911
IPD 0.964 IPD1 0.907 0.953
IPD2 0.904 0.954
IPD3 0.907 0.953
IPD4 0.921 0.949
ITP 0.957 ITP1 0.918 -
ITP2 0.918 -
IAS 0.831 IAS1 0.710 -
IAS2 0.710 -
BIA 0.822 BIA1 0.431 0.875
BIA2 0.729 0.737
BIA3 0.746 0.728
BIA4 0.706 0.748
BP 0.359 BP1 0.174 0.317
BP2 0.334 0.110
BP3 0.134 0.356
BP4 0.130 0.358
BWU 0.690 BWU1 0.361 0.789
BWU2 0.642 0.433
BWU3 0.541 0.550
BIPC 0.771 BIPC1 0.553 0.726
BIPC2 0.332 0.798
BIPC3 0.556 0.726
BIPC4 0.651 0.689
BIPC5 0.642 0.692
BIDP 0.743 BIDP1 0.040 0.743
BIDP2 0.408 0.594
BIDP3 0.422 0.590
BIDP4 0.599 0.528
BIDP5 0.444 0.578
BIDP6 0.523 0.547

Tab.4

Post item reliability analysis scale"

分量表 Cronbach's
Alpha系数
观察变量 CITC 删除CICT
值较附项
目后整体
Cronbach's
Alpha系数
C 0.588 C1 0.510 0.319
C2 0.357 0.545
C3 0.335 0.583
A 0.738 A1 0.463 0.770
A3 0.633 0.573
A4 0.602 0.604
BIA 0.875 BIA2 0.761 0.821
BIA3 0.744 0.836
BIA4 0.771 0.812
BP 0.674 BP1 0.509 -
BP2 0.509 -
BWU 0.789 BWU2 0.654 -
BWU3 0.654 -
BIPC 0.798 BIPC1 0.533 0.783
BIPC3 0.548 0.776
BIPC4 0.684 0.708
BIPC5 0.682 0.710
BIDP 0.743 BIDP2 0.462 0.714
BIDP3 0.448 0.718
BIDP4 0.603 0.666
BIDP5 0.454 0.722
BIDP6 0.585 0.667

Tab.5

KMO and Bartlett's test results"

取样足够的Kaiser-
Meyer-Olklin度量
Bartlett的球形度检验
近似卡方 df Sig.
0.955 2 8458.402 666 0.000

Tab.6

SEM fit index and results"

统计指标 X2/df RMSEA CFI GFI NFI IFI
判断标准 3~5 <0.5 >0.9 >0.9 >0.9 >0.9
模型一值 5.458 0.067 0.905 0.832 0.887 0.906
拟合评价 接近 接近 理想 接近 接近 理想
模型二值 4.469 0.059 0.909 0.846 0.886 0.909
拟合评价 理想 接近 理想 接近 接近 理想

Tab.7

Descriptive statistical results"

变量 C IMR IPK IPD ITP ISA
均值 4.210 4.773 5.092 4.985 4.740 5.050
4.928
变量 A BIA BP BWU BIPC BIDP
均值 6.733 4.295 5.475 7.070 6.095 5.770
5.741

Tab.8

Estimation results of SEM"

假设 实际估值 近似标
准误差
临界值 结论
H1:C→A 0.281*** 0.002 3.722 支持
H2a:A→IMR 0.881*** 11.493 5.486 支持
H2b:A→IPD 0.966*** 12.794 5.514 支持
H2c:A→IPK 0.952*** 11.523 5.498 支持
H2d:A→ITP 0.937*** 13.064 5.510 支持
H2e:A→IAS 0.852*** 9.657 5.454 支持
H3a:IMR→BIA 0.052 0.063 0.639 拒绝
H3b:IMR→BP 0.092 0.033 1.240 拒绝
H3c:IMR→BWU -0.058 0.049 -0.672 拒绝
H3d:IMR→BIPC -0.012*** 0.032 9.839 支持
H3e:IMR→BIDP -0.021 0.050 1.214 拒绝
H4a:IPD→BIA -0.032 0.097 -0.253 拒绝
H4b:IPD→BP 0.155 0.051 1.328 拒绝
H4c:IPD→BWU -0.053 0.076 -0.392 拒绝
H4d:IPD→BIPC 0.124 0.040 1.467 拒绝
H4e:IPD→BIDP -0.113 0.046 -1.333 拒绝
H5a:IPK→BIA 0.213* 0.106 1.689 支持
H5b:IPK→BP 0.121 0.057 1.028 拒绝
H5c:IPK→BWU 0.485*** 0.085 3.543 支持
H5d:IPK→BIPC 0.322*** 0.046 3.690 支持
H5e:IPK→BIDP 0.102 0.050 1.214 拒绝
H6a:ITP→BIA -0.084 0.073 -0.833 拒绝
H6b:ITP→BP -0.302*** 0.043 -2.940 支持
H6c:ITP→BWU -0.229* 0.057 -2.156 支持
H6d:ITP→BIPC -0.079 0.030 -1.179 拒绝
H6e:ITP→BIDP -0.170** 0.034 -2.566 支持
H7a:IAS→BIA 0.218*** 0.065 3.020 支持
H7b:IAS→BP -0.050 0.038 -0.670 拒绝
H7c:IAS→BWU 0.229*** 0.057 2.667 支持
H7d:IAS→BIPC 0.563*** 0.032 9.839 支持
H7e:IAS→BIDP 0.139 0.050 1.214 拒绝

Fig.2

SEM path analysis"

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