基于技术接受度模型的模块化服装使用意愿分析

doi:10.13475/j.fzxb.20220809301

Abstract

Abstract:

Objective Modular clothing has become an important form of clothing transformation to green and low-carbon with its detachable and reconfigurable characteristics. At present, there are few related studies on modular clothing, and domestic related research mainly focuses on computer clothing system, modeling, and pattern design. There are few studies on the acceptance and attitude of modular clothing. The influencing factors for use intention need additional analysis.

Method Based on the technology acceptance model, the clothing functionality is introduced as an external variable in the model to construct a modular clothing user willingness model. Through the 'questionnaire star' software, 141 young people aged from 18 to 26 were surveyed online and the collected data were analyzed, and seven hypotheses were proposed (Fig. 1). SPSS software was used to test the reliability and validity of the data. After passing the reliability and validity test, the questionnaire was analyzed and hypothesis tested in combination with the structural equation model.

Results Among the 141 respondents to the questionnaire, 37.6% are male and 62.4% are female. After evaluating the five important elements of modular clothing (fabric selection, color matching, style and structure, pattern, and overall design style) by 1-5 points, it is concluded that the highest score is 'color matching' with a score of 4.49, and the lowest score is 'pattern' with a score of 3.38 (full score of 5 ) (Tab. 5). The reliability test shows that the Cronbach's α value of the total sample data is 0.930, the validity test shows that the Kaiser-Meyer-Olkin (KMO) value of the total sample data is 0.915 > 0.9, and the significance level is 0.000 < 0.01, indicating that the sample data has good reliability and validity (Tab. 6). The results of model fitness analysis show that chi square divided by degrees of freedom (CMIN/DF) is 1.711 < 3, root mean square error of approximation (RMSEA) is 0.071 < 0.08, goodness-of-fit index (GFI) is 0.868 > 0.8, comparative fit index (CFI) is 0.945 > 0.9, incremental fit index (IFI) is 0.946 > 0.9 (Tab. 7). The results of model path coefficient analysis show that the P values of Hypotheses 1 to 4 and 7 are all less than 0.001, and they are consistent with the prediction direction, so these hypotheses are accepted (Tab. 8). The P values for hypotheses 5 and 6 are greater than 0.05, so Hypotheses 5 and 6 are rejected. The functionality of modular clothing has a significant positive impact on perceived usefulness and perceived ease of use. Perceived ease of use has a significant positive impact on perceived usefulness. Perceived usefulness has a significant positive impact on attitude. Attitude has a significant positive impact on behavioral intention. Perceived ease of use of modular clothing has no significant effect on attitude. Perceived usefulness has no significant effect on behavioral intention.

Conclusion Young people aged from 18 to 26 pay the most attention to the color matching of modular clothing, followed by the style and structure, overall design style and fabric selection. While,they pay less attention to the pattern. The establishment of Hypotheses 1 and 2 means improving the functional performance of modular clothing can improve the perceived usefulness and perceived ease of use. The establishment of Hypothesis 4 and the non-establishment of Hypothesis 6 indicate that the perceived ease of use of modular clothing can directly and positively affect people's positive attitude towards modular clothing, but the direct impact on the purchase decision is not significant. The establishment of Hypothesis 3 and the non-establishment of Hypothesis 5 indicate that the perceived ease of use of modular clothing can indirectly affect the use attitude through perceived usefulness. The establishment of Hypothesis 7 indicates that people's positive attitude towards modular clothing can positively promote purchase behavior. Therefore, the functionality, perceived usefulness, perceived ease of use, interest and other aspects of modular clothing are the main influencing factors that affect users' willingness to use. Corresponding measures can be taken to promote consumers to make purchase decisions on modular clothing.

Key words: technology acceptance model, modular garment, use intention, structural equation model, sustainable design

CLC Number:

TS941.75

SONG Huihui, LU Yehu. Analysis of use intention of modular garment based on technology acceptance model[J].Journal of Textile Research, 2023, 44(10): 157-163.

Figures/Tables 10

Fig. 1

Tab. 1

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Tab. 5

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Fig. 2

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Tab. 8

References 22

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序号	基本问题题项
1	性别(男/女)
2	职业(学生/上班族/自由职业者/其它)
3	穿衣风格(休闲运动/时尚前卫/成熟干练/温柔可爱/其它)

序号	重要元素量表问题题项
1	面料选择对模块化服装很重要
2	颜色搭配对模块化服装很重要
3	款式版型对模块化服装很重要
4	有图案对模块化服装很重要
5	整体设计风格对模块化服装很重要

潜变量类别	测量问题题项
功能性 FUN	FUN1:这种模块化服装比较经济实用 FUN2:这种模块化服装比较绿色环保 FUN3:这种模块化服装收纳、清洗很方便 FUN4:穿着这种模块化服装可以让我看起来更时髦
感知有用性 PU	PU1:这种模块化服装可有助于提高我的生活质量 PU2:这种模块化服装可能解决我选衣难的问题 PU3:这种模块化服装可有助于减少服装购买量,进而减少环境污染 PU4:穿着这种模块化服装可有助于提高我的工作效率
感知易用性 PE	PE1:这种模块化服装搭配起来很简单 PE2:穿着这种模块化服装不会很复杂 PE3:穿着这种模块化服装不会花费我太多时间
使用态度 ATT	ATT1:模块化服装是有趣的 ATT2:模块化服装是有用的 ATT3:购买模块化服装是可行的
行为意向 PI	PI1:我愿意尝试这种模块化服装 PI2:模块化服装值得一试 PI3:如果这种模块化服装可行的话,我可能会购买

类别	样本分类	样本数	比例/%
性别	男女	53 88	37.6 62.4
职业	学生上班族自由职业者其它	113 25 2 1	80.1 17.7 1.4 0.7
穿衣风格(多选)	休闲运动时尚前卫成熟干练温柔可爱其它	107 40 27 44 12	75.9 28.4 19.1 31.2 8.5

变量	均值	标准差	偏度	峰度
面料选择对模块化服装很重要	4.26	0.907	-1.011	0.037
颜色搭配对模块化服装很重要	4.49	0.733	-1.397	1.518
款式版型对模块化服装很重要	4.46	0.761	-1.298	1.002
有图案对模块化服装很重要	3.38	1.012	-0.116	-0.332
整体设计风格对模块化服装很重要	4.43	0.709	-1.072	0.723

Analysis of use intention of modular garment based on technology acceptance model

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变量	问题项	删除项后的 Cronbach's α值	变量的 Cronbach's α值	总数据的 Cronbach's α值	KMO值	因子载荷	总数据的方差累计贡献率/%
功能性 FUN	FUN1 FUN2 FUN3 FUN4	0.602 0.541 0.645 0.657	0.678			0.523 0.614 0.559 0.547
感知有用性 PU	PU1 PU2 PU3 PU4	0.790 0.795 0.823 0.775	0.839			0.726 0.711 0.699 0.736
感知易用性 PE	PE1 PE2 PE3	0.880 0.783 0.710	0.853	0.930	0.915	0.686 0.660 0.689	74.203
使用态度 ATT	ATT1 ATT2 ATT3	0.847 0.690 0.686	0.817			0.677 0.791 0.763
行为意向 PI	PI1 PI2 PI3	0.857 0.869 0.914	0.917			0.817 0.833 0.760

拟合指数	拟合指数含义	指标值	拟合情况
CMIN	卡方	191.605
DF	自由度	112
P	绝对拟合指数	0.000
CMIN/DF	卡方自由度比	1.711	<3,可接受
GFI	拟合优度指数	0.868	>0.8,可接受
CFI	比较拟合指数	0.945	>0.9,拟合很好
TLI	非规范拟合指数	0.933	>0.9,拟合很好
IFI	增值拟合指数	0.946	>0.9,拟合很好
RMSEA	近似误差均方根	0.071	<0.08,可接受

假设	路径	非标准化估计值	标准化估计值	验证结果
H1	FUN→PU	0.978^***	0.678	接受
H2	FUN→PE	0.965^***	0.545	接受
H3	PE→PU	0.310^***	0.381	接受
H4	PU→ATT	0.698^***	0.758	接受
H5	PE→ATT	0.048	0.064	拒绝
H6	PU→PI	0.005	0.005	拒绝
H7	ATT→PI	1.124^***	0.909	接受

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