智能服装购买意愿影响机制实证研究

With the improvement of people s living standards and the growth demand for personalization and intelligence, smart clothing, as a combination of clothing and cutting-edge technology, has attracted attention from an increasing number of clothing technology enterprises and ordinary consumers. Many organizations predict that smart clothing will develop rapidly in the future and occupy a certain share of the clothing market. As an ideal wearable device, smart clothing is gradually shifting its target consumers from professional fields such as sports and healthcare to ordinary consumers. While meeting the basic wearable functions,smart clothing also uses science and technology to add special functions related to daily life. As a result, smart clothing is no longer unattainable and is becoming more and more relevant to the lives of ordinary consumers. At present, there arc many studies on smart clothing technology, while there is relatively little research on consumers' willingness to purchase smart clothing in China. Researching consumers' purchase intentions for smart clothing is conducive to the development of the smart clothing industry. Based on the technology acceptance model and the characteristics of smart clothing, the FEA ( functionality, expressiveness, and aesthetics) model was introduced as an external variable to construct the structural equation model (SEM) of consumers' purchase intentions of smart clothing, and we put forward 11 research hypotheses. Based on the scale proposed and verified by many scholars at home and abroad, and combined with the characteristics of smart clothing, six independent variables of functionality, expressiveness, aesthetics, perceived usefulness, perceived ease of use, and attitudes were extracted to design the research questionnaire, which were measured with 5-point Likert scale. Then, the research questionnaire was employed to collect data, and the SPSS 24.0 software was used to conduct descriptive statistical analysis of the basic individual information. Next, in order to assess the model using the PLS-SEM, the SmartPLS 3.2.9 software was applied to test the reliability and validity, and the results indicated that the reliability and validity of the variables greatly exceeded the recommended threshold, which was of statistical significance. Finally, the bootstrapping method was used to empirically verify the hypotheses of the model, and a total of nine hypotheses were supported. The results of the empirical analysis show that: i ) From the perspective of the FEA model, expressiveness has a significantly positive impact on perceived usefulness and ease of use; functionality positively and significantly affects the perceived ease of use, while the effect on perceived usefulness is not significant. Aesthetics positively and significantly affects consumer attitudes, while it has no impact on purchase intentions, ii ) From the perspective of the TAM model, it indicates that the hypotheses between the variables have positive and significant effects on each other, which can well explain consumers' willingness to purchase smart clothes, iii) Among all the hypotheses, consumers' attitudes have the greatest influence on purchase intentions.Based on the above results, we propose some suggestions for the smart clothing: i ) From the perspective of the functionality of smart clothing, it is necessary to meet the needs of comfort, protection, and practicality when consumers wear smart clothing, and satisfy their different functional needs, so as to improve the perceived usefulness of smart clothing, ii ) From the perspective of expressiveness, smart clothing should conform to consumers' lifestyles, iii) From the perspective of aesthetic performance, the design of smart clothing should follow the current fashion trends in order to make smart clothing he better integrated into daily life, iv ) From the perspective of ease of use, the future design of smart clothing can improve consumers' wearing proficiency, work efficiency, and quality of life by enhancing the interaction between consumers and smart clothing, and then make consumers form the willingness to purchase by influencing their attitudes. Through this study, a certain theoretical foundation is laid for the subsequent research on the purchase intentions of different kinds of smart clothing.