Attitudes and Purchase Intentions for Smart Clothing

Abstract

This research extends the technology acceptance model with apparel design attributes and examines factors influencing consumers’ attitudes and purchase intentions of smart clothing, specifically, solar-powered clothing. A random sample of college students and faculty (N = 720) participated in this study. Results from structural equation modeling reveal that perceived usefulness is the strongest predictor of attitude and purchase intention. Perceived compatibility is the strongest predictor of perceived usefulness, and along with perceived comfort, it determines perceptions of usefulness, ease of use, and performance risk. Perceived performance risk, aesthetic attributes, and environmental concern are significant predictors of attitude. This research validates the technology acceptance model in explaining new technology adoption in clothing and confirms the importance of multiple dimensions of smart clothing. Retailers can emphasize the shift from a technical concern to a user-centered one by highlighting utilitarian aspects of clothing and providing compatible and aesthetically appealing design features that interconnects functionality, expressiveness, and aesthetics (FEA) consumer needs.

Keywords

TAM FEA smart clothing solar-powered clothing

The integration of smart technology with textiles and clothing continues to develop in industry and academic literature. The function of clothing has evolved from a means of protecting human beings to an “instrument of augmenting human capabilities,” as modern digital lifestyles demand ubiquitous connectedness (Jeong & Yoo, 2010, p. 89). This market continues to expand into the military, health and medical care, and leisure industries (Cho, 2010). According to NanoMarkets (2014), smart clothing will grow from about US$212 million in 2014 to more than US$1.8 billion by 2021. However, while smart clothing offers convenience and competitive advantages to wearers, the newer an innovation, the higher the uncertainty associated with this newness among users (Rogers, 2003).

Despite increasing attention to the development and commercialization of smart clothing, few studies on consumer response have been conducted (Chae, 2009; Ko, Sung, & Yun, 2009). The authors found few published studies, in which smart clothing was examined with regard to characteristics of technological devices and garments. Thus, additional research is needed to fill a gap in the literature on consumers’ acceptance of the multidisciplinary nature, especially clothing perspectives, of smart clothing. Particularly, it is important to gain knowledge on potential adopters’ perceptions and attitudes toward solar-powered clothing, since it is expected to be a major item for the future fashion industry (Cho, 2010).

Solar-powered clothing was chosen for this study since it shares characteristics with other smart clothing and is used to provide other smart functions. For instance, Ko, Sung, and Yun (2009) used iPod Nike+ shoes, a Burton’s Bluetooth-enabled Audex jacket, and an outdoor jacket to examine consumers’ attitudes toward smart clothing; all these items provide entertainment functions attached to the clothes (e.g., sensors and MP3 players). Unlike specific types of smart clothing, solar-powered clothing can support various entertainment functions. Solar-powered clothing, within the context of smart clothing, uses a solar cell as an alternative energy source to generate electricity. It is “the first long-term energy source for human beings” and one of the most potentially important energy sources recognized by present scientists (Jeon & Cho, 2010, p. 251). Most solar-powered clothing on the market now offers a universal socket for portable electronic devices, such as mobile phones and MP3 players, ultimately a solution to the constant problem of limited battery life. This functionality is especially impactful when electronic device usage has become an integral part of digital activity among consumers of all ages. For instance, mobile subscribers increased from 5.4 billion in 2010 to almost 7 billion in 2014, and users have expressed numerous complaints about limited battery life when using mobile phones (International Telecommunication Union, 2014).

Even though solar-powered clothing intrigues researchers and the industry because of its functionality and proenvironmental attributes, it is unknown how consumers perceive such clothing. Unlike other technological devices, smart clothing is complex because it is considered both a device and a garment, integrating characteristics of clothing (e.g., aesthetics and comfort), and electronic devices (e.g., usability and safety); at the same time, technological aspects often interfere with the features of clothing such as aesthetic attributes and comfort (Sonderegger, 2013). To better serve consumers, researchers working from a multidisciplinary approach, including the disciplines of computer science, engineering, and design, have actively dealt with textile development, commercialization possibilities, and product development (Jeon & Cho, 2010).

Thus, the purpose of this study was to examine factors affecting consumers’ attitudes toward and purchase intentions for smart clothing, specifically solar-powered clothing, based on the technology acceptance model (TAM). Although Ko et al. (2009) examined perceived risks and perceived attributes (e.g., relative advantage, compatibility, triability, and observability) of smart clothing with regard to attitude and purchase intention, we further extend the study by distinguishing attributes of technology and clothing separately and identifying antecedents contributing to the acceptance of solar-powered clothing from a perspective of apparel functionality, expressiveness, and aesthetics (FEA). In this study, the researchers address the gap in the literature by investigating the clothing attributes of smart clothing and aiding the future development and promotion of solar-powered clothing, which inherently require both technological and clothing attributes. Determining factors affecting consumers’ adoption of solar-powered clothing is imperative in light of increasing technology and the sustainability movement in the apparel industry.

Literature Review

Smart Clothing

As a form of wearable technology, which refers to “many different forms of body mounted technology, including wearable computers, smart clothing, and functional clothing,” smart clothing distinguishes itself from other worn accessories like fitness bracelets and emphasizes the importance of clothing attributes (Dunne, 2004, p. 5). Technology and computer science have partnered with fashion, allowing clothing attributes and technological functions to coexist in apparel. Since the late 1990s, the amount of technology-integrated clothing available on the market has increased dramatically and includes garments such as Levi Strauss’ jacket with an embedded MP3 player and mobile phone (Fenn, 2000), the North Face’s MET5 jacket that generates heat (Best Inventions of 2001, 2001), and the Hug Shirt with electronic sensors that gauge body temperature and heart rate (Voigt, 2007). The development of smart clothing takes into consideration many factors and thus must be “collaborative between end-users, textile specialists, electronics, fashion and clothing designers and manufacturers all the way from the concept for new garment or wearable device through to point of sale” (McCann, 2009, p. 28). The convergence of technology and clothing has brought both opportunities and challenges for designers and product developers, as it requires great knowledge from various fields.

User Acceptance of Technology: Technology Acceptance Model (TAM)

TAM (Davis, Bagozzi, & Warshaw, 1989) is considered the most validated model to explain the acceptance and usage intention for information technology. The model explains users’ technology adoption behavior based on perceived usefulness and perceived ease of use as the key determinants; these are the most frequently validated factors that influence consumers’ attitudes toward and purchase intentions of technology and innovative products (Davis et al., 1989). Researchers have validated TAM as a parsimonious framework for understanding the user’s adoption of technology in a variety of contexts, including smartphones (Park & Chen, 2007) and smart clothing (Chae, 2009).

According to Davis (1989), consumer perception of usefulness directly influences attitudes toward technology adoption. Perceived usefulness is defined as “the degree of which a person believes that using a particular system would enhance his or her job performance” (Davis, 1989, p. 320). Perceived usefulness has consistently been suggested as the most powerful predictor for intention to use and adopt technology (Venkatesh, Morris, Davis, & Davis, 2003). Concepts similar to perceived usefulness include relative advantage and outcome expectation relating to users’ perceived value of improving their performance (Venkatesh et al., 2003).

Prior to the work of Davis (1989), researchers have found that perceived usefulness provided a reliable prediction for using technology and confirmed that a high correlation existed between perceived usefulness and system usage (Chuttur, 2009). Based on TAM (Davis et al., 1989), Chae (2009) viewed smart clothing as “innovative technology” and found that perceived usefulness was a key variable that influenced consumer attitudes, a person’s positive or negative feelings about performing that behavior (Ajzen & Fishbein, 1980). Based on diffusion theory (Rogers, 2003), Ko et al. (2009) further confirmed that relative advantage, interchangeable with perceived usefulness, influences purchase intention, the cognitive representation of a person’s readiness to perform a given behavior (Ajzen, 1991) of smart clothing. Thus, based on the previous findings, it is proposed that perceived usefulness positively affects attitude and purchase intention of solar-powered clothing:

Hypothesis 1a: Perceived usefulness positively affects attitude toward purchasing solar-powered clothing.

Hypothesis 1b: Perceived usefulness positively affects purchase intention of solar-powered clothing.

The second original TAM variable is perceived ease of use, “the degree to which a person believes that using a particular system would be free of effort” (Davis, 1989, p. 320). In regard to smart clothing, Chae (2009) found that perceived ease of use positively influences consumers’ attitudes. Ko et al. (2009) used complexity in reverse of perceived ease of use and found an insignificant relationship between complexity and purchase intention of smart clothing. Further, TAM assumes that perceived usefulness is related to perceived ease of use (Davis et al., 1989) because “the easier the system (technology) is, the more useful it can be” (Venkatesh & Davis, 2000, p. 187). Researchers have found that perceived ease of use positively influences perceived usefulness (Park & Chen, 2007). Thus, it can be expected that perceived ease of use positively affects perceived usefulness and attitude toward purchasing solar-powered clothing:

Hypothesis 2a: Perceived ease of use positively affects perceived usefulness.

Hypothesis 2b: Perceived ease of use positively affects attitude toward purchasing solar-powered clothing.

Perceived Performance Risk

Along with the two original TAM variables, perceived risk, defined as “the uncertainty consumers face when they cannot foresee the consequences of their purchase decisions” (Schiffman & Kanuk, 2000, p. 153), may influence user acceptance of technology. Apparel has been regarded as a product category having multidimensional risks (e.g., performance risk, sociopsychological risk, aesthetic/fashion risk, product care risk, time-related risk, and financial risk), and in general, perceived risk has a negative influence on attitudes toward adopting innovative technology (Ko et al., 2009). Rogers (2003) states that the newer an innovation and the higher the uncertainty associated with this newness, the more likely consumers are hesitant to adopt the product. Thus, uncertainty related to an innovation can be conceptualized by perceived risk, and it plays an important role in the formation of an attitude toward new products and the purchase intention for those products (Park & Stoel, 2005; Sjöberg, 2000).

Specifically, product performance risk is “the possibility that the product will not function as expected and/or will not provide the desired benefits” (Grewal, Gotlieb, & Marmorstein, 1994, p. 145). Perceived performance risk can be a significant obstacle preventing consumers from selecting a product, and previous researchers have indicated that perceived performance risk negatively affects purchase intention (Park, Lennon, & Stoel, 2005). Thus, negative relationships between perceived performance risk and attitude along with purchase intention of solar-powered clothing are hypothesized:

Hypothesis 3a: Perceived performance risk negatively affects attitude toward purchasing solar-powered clothing.

Hypothesis 3b: Perceived performance risk negatively affects purchase intention of solar-powered clothing.

Antecedents to TAM: FEA Consumer Needs

Davis (1989) proposed that external stimulus of a system’s features and design characteristics influences user motivation to use the system. Researchers examined antecedents to the perceived usefulness and ease of use in relation to various contexts such as websites and smartphones (Lee, Fiore, & Kim, 2006; Venkatesh & Davis, 2000). Specifically, some researchers have examined utilitarian aspects of products as the external stimuli. For example, Ahn, Ryu, and Han (2004) found significant positive relationships between the quality (e.g., appearance and technical adequacy) of Internet shopping mall products and TAM variables; Lee, Fiore, and Kim (2006) found significant relationships between the utilitarian and hedonic shopping orientations of a website with TAM variables. However, antecedents of TAM related to clothing attributes have not been examined given their possible influence in the context of smart clothing.

The complex nature of smart clothing must satisfy user needs with clothing attributes, such as FEA (Lamb & Kallal, 1992). Lamb and Kallal (1992) proposed the three-dimensional model for multiple purposes in apparel design and suggest that all three dimensions should be taken into consideration when addressing consumer wants and needs for innovative design. In the FEA model, the functional dimension of clothing includes fit, mobility, protection, and comfort that relates to its utility. The expressive clothing dimension proposes symbolic communicative characteristics that establish identity, such as values, roles, and self-esteem. Aesthetic considerations, in regard to clothing, deal with the use of elements such as design principles and the body–garment relationship. In the current study, the researchers consider FEA attributes as external stimuli to TAM that influence early user motivation to adopt solar-powered clothing. Interrelating FEA considerations can be helpful in assessing the suitability of smart clothing as an apparel product. Along with viewing solar-powered clothing as an innovation and technology-integrated product, the three dimensions of clothing would provide a full spectrum of consumer needs. Thus, each dimension of FEA (discussed as perceived comfort, compatibility, and aesthetic) is discussed below as antecedents to TAM.

Perceived comfort (functionality)

Functionality is a utilitarian aspect of clothing from the FEA model that influences user acceptance of technology. Lamb and Kallal (1992) state that functional considerations for an apparel product relate to its utility and physical comfort. Fit and ease of movement are examples of functional requirements that might be sought. Specifically, according to Sontag (1985), physical comfort is “a mental state of physical well-being expressive of satisfaction with physical attributes of a garment such as air, moisture, heat transfer properties, and mechanical properties such as elasticity, flexibility, bulk, weight, texture, and construction” (p. 10). Thus, the demands of the body were highlighted for functional clothing, and physical comfort results in subjective assessments of garment fit along with tactile properties resulting from skin contact (Sontag, 1985). As the focus of technology-integrated clothing has shifted from a technical concern to a user-centered one for marketability, researchers and designers have tried to achieve greater mobility and comfort in smart clothing.

Researchers have shown that physical comfort, as recognized in the FEA model, is an important factor influencing overall evaluation of the product (Frith & Glesson, 2004; Sontag, 1985). Suh, Carroll, and Cassill (2010) suggested that smart clothing should maintain the comfort and usability of ordinary clothes, since uncomfortable clothing will not be worn by consumers (Shanley, Slaten, & Shanley, 1993). Unlike conventional clothing, smart clothing may add extra weight and pressure on the human body when integrating music or heart rate devices, sensors, or solar panels and chips which have additional features to support smart functions (Dunne, Ashdown, & Smyth, 2005). The wearer should not be limited in comfort as a result of intelligent adaptation in clothing (Dunne et al., 2005; Suh et al., 2010); thus, the utilitarian aspect of clothing would influence user acceptance of technology. Logically, if a product is perceived to be comfortable in terms of fit and mobility, it may reduce risks of having unfamiliarity of the usage of products and be perceived to be more useful, since consumers do not have to worry about clothing being uncomfortable. As such, the utilitarian aspect of perceived comfort as an external stimulus of smart clothing is proposed to influence user acceptance of technology (perceived usefulness, ease of use, and performance risk):

Hypothesis 4a: Perceived comfort positively affects perceived usefulness.

Hypothesis 4b: Perceived comfort positively affects perceived ease of use.

Hypothesis 4c: Perceived comfort negatively affects perceived performance risk.

Perceived compatibility (expressiveness)

According to the FEA model, consumers are concerned about expressive considerations of clothing (Stokes & Black, 2012). Expressive considerations relate to the “communicative, symbolic aspects” of clothes and are based on the sociocultural and psychological aspects of a garment (Lamb & Kallal, 1992, p. 43). Thus, the product should be compatible with the wearer’s status and self-image, as the garment communicates various messages about the wearer and makes visual statements about their individuality (Damhorst, 1990). This leads to the importance of compatibility, also mentioned in perceived attributes of an innovation from Rogers (2003), where compatibility is defined as “the degree to which the innovation is perceived as consistent with the existing values, needs, and past experiences of [the] potential adopter” (p. 240).

In terms of smart clothing, Ko et al. (2009) defined compatibility as “the degree to which the innovation is perceived consistent with the existing values, needs, and past experiences of a potential adopter” (p. 261) and found that it influences user acceptance of smart clothing.

Consumers’ “past experiences” of using similar technology can lower the risk of the technology’s malfunctioning due to lack of confidence and knowledge to use it; they may also indicate that using the new technology requires less effort to learn. Their past experiences of feeling the “needs” of similar technology to solve problems can increase the product being viewed as more useful. Thus, if the product is compatible and consistent with consumers’ current needs and lifestyles, it will positively influence user acceptance of technology. Hence, it is proposed that perceived compatibility positively affects the technology acceptance variables of perceived usefulness and ease of use and negatively affects performance risk:

Hypothesis 5a: Perceived compatibility positively affects perceived usefulness.

Hypothesis 5b: Perceived compatibility positively affects perceived ease of use.

Hypothesis 5c: Perceived compatibility negatively affects perceived performance risk.

Perceived aesthetic attributes

Aesthetic criteria from the FEA model are important criteria for consumers’ evaluations of apparel because apparel is an important means of visual communication (Chattaraman & Rudd, 2006; Eckman, Damhorst, & Kadolph, 1990). The aesthetic criteria take into account the human desire for beauty. Specifically, researchers have used product attributes related to textiles and apparel (e.g., fiber content, style, color, design, and appearance) to investigate overall judgments made by consumers.

Unlike the other two FEA variables, perceived compatibility and perceived comfort, no researchers found a significant relationship of aesthetic attributes on TAM variables. Thus, it can be inferred that even if a product is perceived to be aesthetically pleasing, it does not necessarily influence consumers’ acceptance of technology, such as perceived ease of use toward the product. Rather, previous researchers suggest that perceived aesthetic attributes may directly influence consumers’ attitudes toward purchasing the clothing (Eckman et al., 1990; McCann, 2009). Researchers have shown that aesthetic attributes of apparel such as color, styling, and fabric were the most important criteria for women when purchasing clothing (Eckman et al., 1990). In terms of smart clothing, Malmivaara (2009) argued that aesthetic considerations are vital factors influencing the acceptability and wearability of the final product. Such clothing should have “an appropriate balance of aesthetic concerns” (e.g., color, fabrication, cut, proportion, and detail) that contributes to the satisfaction of the wearer (McCann, 2009, p. 49). Thus, the distinct aesthetic features of smart clothing with electronic devices may be perceived as “awkward in style” and may not attract users’ attention, since consumers prefer using advanced technology without losing their fashion sense (Suh et al., 2010, p. 10). As such, it is proposed that perceived aesthetic attributes positively affect attitude and purchase intention:

Hypothesis 6a: Perceived aesthetic attributes positively affect attitude toward purchasing solar-powered clothing.

Hypothesis 6b: Perceived aesthetic attributes positively affect purchase intention of solar-powered clothing.

Environmental Concern

Environmental concern refers to a general attitude or value orientation toward protecting the environment (Ajzen, 1991). According to Antil (1984), consumers’ environmental attitudes are expressed through their concerns for the environment, and these attitudes are likely to be an important motive influencing consumers’ behavior and purchase decisions. Kim and Damhorst (1998) argued that individuals with positive environmental attitudes are more likely to engage in environmentally responsible behaviors in general. Environmental attitudes were found to influence intentions to behave responsibly in apparel consumption and have shown that an individual’s concern for the environment influences decisions related to apparel consumption (Yan, Hyllegard, & Blaesi, 2012).

Specifically, clothing with proenvironmental attributes such as organic or recycled materials is shown to attract consumers with environmental concerns (Yan et al., 2012). In the case of smart clothing, an innovative way to support smart functions is solar cells, since they generate electricity for many devices and sensors. There is increasing focus on the development of innovative smart clothing with sustainable and environmental-friendly functions (Cho, 2010). Thus, environmental concern is an important factor that cannot be ignored in the development of smart clothing and is a vital addition to the theoretical model. Based on the previous literature and solar-powered clothing’s proenvironmental attributes, it is proposed that environmental concern positively affects attitude and purchase intention of solar-powered clothing:

Hypothesis 7a: Environmental concern positively affects attitude toward purchasing solar-powered clothing.

Hypothesis 7b: Environmental concern positively affects purchase intention of solar-powered clothing.

Attitude and Purchase Intention

According to the theory of reasoned action (TRA), an individual’s behavior is determined by one’s intention to perform the behavior, and this intention is influenced by one’s attitude (Ajzen & Fishbein, 1980). Empirical research supports this attitude–behavioral intention relationship—the more positive attitudes consumers hold toward a behavior, the more likely they are to perform the given behavior (Shaw & Shiu, 2003). Researchers have found positive effects of attitude on purchase intention in the context of apparel products (Shaw & Shiu, 2003; Yan et al., 2012). Thus, based on TRA, Hypothesis 8 is proposed as:

Hypothesis 8: Attitude toward purchasing solar-powered clothing positively affects purchase intention.

Method

Sample and Procedure

An online survey was conducted with a convenience sample of college students and faculty at a large Midwestern university. After receiving institutional review board approval, 31,190 college students and 6,400 faculty received an invitation e-mail to participate in the study. The e-mail contained consent elements and a link to the survey. To give participants a clear understanding of solar-powered clothing, a detailed information page describing solar-powered clothing was provided at the beginning of the survey. As shown in Figure 1, this page included images of commercially available solar-powered clothing (e.g., Zegna’s Ecotech solar jacket and SCOTTeVEST) with a description of solar cells, a price range, and instructions on how to use the product. A pretest that asked about the clarity of the stimuli in representing current solar-powered clothing was conducted with 20 graduate students in the areas of textiles, clothing, and merchandising; the results indicated that the stimuli clearly represented the function and aesthetic of solar-powered clothing.

Figure 1.

Examples of stimuli used in the study.

Instrument Development

All scales, except perceived comfort, perceived performance risk, and attitude, employed 7-point Likert-type items, ranging from strongly disagree (1) to strongly agree (7). Perceived usefulness was measured by 3 items adapted from Davis (1989). Another 3 items were used to assess consumers’ perceived ease of use based on Davis’ (1989) scales. Perceived performance risk was measured by adapting 3 items with a 7-point scale from Grewal, Gotlieb, and Marmorstein (1994), and these items measured uncertainty and consequences. Three items measuring perceived compatibility were adapted from Ko et al. (2009). Attitude toward purchasing the product was measured with 7-point semantic differential scales (MacKenzie, Lutz, & Belch, 1986), and purchase intention was assessed by adapting three 7-point Likert-type items from Bower and Landreth (2001).

Since there is no validated measurement for perceived comfort and perceived aesthetic attributes, items were developed from a previous study (Eckman et al., 1990), and face validity on the instrument was examined and confirmed by several researchers in the areas of textiles, clothing, and merchandising to confirm the clarity of the items. The scales were developed to fit the context of solar-powered clothing as criteria for evaluating the product. For perceived comfort, four semantic differential scales were developed, each measured on a 7-point scale. The scales were adapted from a wearer acceptability scale developed by Huck, Maganga, and Kim (1997). The 4 items were uncomfortable (1)/comfortable (7), rigid (1)/flexible (7), hard to move in (1)/easy to move in (7), and heavyweight (1)/lightweight (7). For perceived aesthetic attributes, three 7-point Likert-type items were developed based on a study by Eckman, Damhorst, and Kadolph (1990), ranging from strongly disagree (1) to strongly agree (7).

Results

Sample Profile

A total of 870 participants responded to the survey, out of which 720 responses were usable. Based on the results, 67.9% of the respondents were female and 32.1% were male. Age ranged from 18 to 68 years old with 52.9% between 20 and 24 years old. The majority of the respondents were White/European American (84.5%), followed by Asian (7.8%) and Hispanic American or Latino (2.9%). Nearly 60% of respondents earned less than US$25,000 annually and 3.2% earned over US$100,000 annually. In terms of participants’ awareness of solar-powered clothing, 233 (32.5%) of the 718 participants indicated they had heard about solar-powered clothing previously.

Measurement Validity and Reliability

A confirmatory factor analysis (CFA) using maximum likelihood estimation was conducted. The CFA for the full measurement model provided a good fit, χ² = 679.361, degrees of freedom (df) = 288, p < .001, comparative fit index (CFI) = .975, Tucker–Lewis index (TLI) = .969, standardized root mean square residual (SRMR) = .035, and root mean square error of approximation (RMSEA) = .044. All indicators loaded significantly (p < .001) and substantively (standardized coefficient > .5) on their respective constructs, providing evidence of convergent validity. Construct reliability and average variance extracted (AVE) estimates in the sample met the recommended threshold levels of .60 and .50, respectively, providing evidence of internal consistency and convergent validity (Hair, Anderson, Tatham, & Black, 2010). As shown in Table 1, the square root of AVE of each construct was greater than the correlations between constructs, evidencing discriminant validity (Fornell & Larcker, 1981). Internal consistency for each construct was assessed using Cronbach’s α. Cronbach’s α coefficients for all nine constructs were acceptable, as they ranged from .82 to .95. Results of CFA are summarized in Table 2.

Table 1.

Correlation Coefficients Between Constructs and Construct Average Variances Extracted (AVE).

Constructs	1	2	3	4	5	6	7	8	9	AVE	Square Root of AVE
1. Perceived usefulness	1									.74	.86
2. Perceived ease of use	0.37	1								.61	.78
3. Perceived performance risk	−0.38	−0.34	1							.79	.89
4. Perceived comfort	0.33	0.34	−0.48	1						.72	.85
5. Perceived compatibility	0.70	0.32	−0.39	0.45	1					.67	.82
6. Perceived aesthetic attributes	0.32	0.21	−0.04	0.44	0.42	1				.83	.91
7. Environmental concerns	0.16	0.25	−0.14	0.15	0.15	0.19	1			.79	.89
8. Attitude	0.54	0.32	−0.04	0.43	0.50	0.36	0.31	1		.75	.86
9. Purchase intention	0.65	0.23	−0.39	0.40	0.67	0.52	0.23	0.64	1	.87	.93

Note. All correlations are significant at .01 level (two-tailed test).

Table 2.

Factor Loading and Reliability of Measurement Items and Average Variances Extracted (AVE).

Constructs and Measurement Items	Standardized Factor Loading	Cronbach’s α	AVE
Perceived usefulness		.90	.74
Wearing solar-powered clothing would improve the quality of my life.	.87
Wearing solar-powered clothing would increase my productivity.	.85
Overall, I find solar-powered clothing useful.	.86
Perceived ease of use		.82	.61
The use of solar-powered clothing is clear and understandable.	.70
Overall, I find solar-powered clothing easy to use.	.75
Using solar-powered clothing would not require a lot of mental effort.	.89
Perceived performance risk		.92	.79
How confident are you that the product/clothing will perform as described?	.89
How certain are you that the product/clothing will work satisfactorily?	.91
Do you feel that the product/clothing will perform the functions that were described in the information page?	.85
Perceived comfort		.89	.72
Wearing this product would be uncomfortable/comfortable.	.82
Wearing this product would be rigid/flexible.	.87
Wearing this product would be difficult to move in/easy to move in.	.86
Perceived compatibility		.86	.67
This product would coordinate well with the other clothing I own.	.70
This product would be more compatible with my current needs than clothing I already have.	.83
This product would be appropriate for my lifestyle.	.90
Perceived aesthetic attributes		.94	.83
The appearance of the solar panels is aesthetically appealing to me.	.86
The designs of solar-powered clothing are aesthetically appealing to me.	.91
The overall style of solar-powered clothing is appealing to me.	.97
Environmental concern		.91	.79
I think environmental problems are very important.	.90
I think environmental problems cannot be ignored.	.80
I think we should care about environmental problems.	.95
Attitude		.92	.75
Purchasing solar-powered clothing is bad/good.	.89
Purchasing solar-powered clothing is unfavorable/favorable.	.90
Purchasing solar-powered clothing is foolish/wise.	.87
Purchase intention		.95	.87
I intend to try this type of product.	.90
It is likely that I will buy this product when it becomes available.	.95
I would purchase this product.	.93

Hypotheses Testing

To test the hypotheses, a structural equation model with a maximum likelihood estimation procedure was conducted using Mplus version 7 (Muthén & Muthén, 2000) (Figure 2). The fit indices of the structural model test revealed an acceptable model fit, χ² = 798.269, df = 298, RMSEA = .049, CFI = .966, TLI = .962, and SRMR = .045. The χ² to df ratio was 2.68, which falls within the acceptable range of 1–3 suggested by Carmines and McIver (1981). Other fit indices were also evaluated to determine how well the model fits the data: CFI and TLI were considered and found to be within the acceptable range.

Figure 2.

Structural equation model path coefficients and model fits for the proposed model.

Hypotheses 1a and 1b proposed that perceived usefulness positively affects attitude toward and purchase intention of solar-powered clothing. The results supported both hypotheses (β = .45, p < .001; β = .44, p < .001). Hypotheses 2a and 2b posited that perceived ease of use positively affects perceived usefulness and attitude toward purchasing solar-powered clothing. The results supported Hypothesis 2a (β = .14, p < .001); however, there was no relationship between perceived ease of use and attitude toward purchasing solar-powered clothing (β = .02, p > .05), rejecting Hypothesis 2b. Perceived performance risk negatively influenced attitude (β = −.17, p < .01), supporting Hypothesis 3a, but it did not significantly influence purchase intention (β = −.01, p > .05), rejecting Hypothesis 3b.

Hypotheses 4a, 4b, and 4c posited that perceived comfort positively affects perceived usefulness and perceived ease of use and negatively affects perceived performance risk. Hypothesis 4a was not supported (β = −.10, p < .01), and Hypotheses 4b and 4c were supported (β = .26, p < .001; β = −.40, p < .001). Hypotheses 5a, 5b, and 5c proposed that perceived compatibility positively affects perceived usefulness and perceived ease of use and negatively affects perceived performance risk. The results supported all of the hypotheses (β = .86, p < .001; β = .28, p < .001; β = −.26, p < .001). Perceived aesthetic attributes significantly influenced both attitude (β = .10, p < .001) and purchase intention (β = .27, p < .001), supporting Hypotheses 6a and 6b. Hypothesis 7a was supported because environmental concerns positively influenced attitude toward purchasing solar-powered clothing (β = .21, p < .001) but did not significantly influence purchase intention (β = .00, p > .05), rejecting Hypothesis 7b. Lastly, the relationship between attitude and purchase intention of solar-powered clothing was positive (β = .31, p < .0010), supporting Hypothesis 8.

Conclusions and Implications

The phenomenon of smart clothing from a consumer perspective is not well understood, and a very limited number of researchers have examined how consumers perceive smart clothing (Macguire, 2011). We propose that the effects of various antecedent factors from the FEA model influence the acceptance of smart clothing, specifically solar-powered clothing. Solar-powered clothing was chosen as the topic for this study due to an increasing focus by researchers and development by designers (Cho, 2010); few researchers have examined consumer acceptance of certain types of technology-integrated clothing (Ko et al., 2009). Based on the extended TAM, we examined the effects of technology acceptance variables, FEA variables, and environmental concerns on consumers’ attitude toward purchasing solar-powered clothing. The findings are useful to current researchers and apparel industry members who promote products that inherently require both technology and clothing attributes.

The results of this study indicated that the technology acceptance variables are important factors influencing the acceptance of the clothing. Perceived usefulness is the strongest predictor of attitude and also directly influence purchase intention, confirming the findings from previous studies (Chae, 2009; Ko et al., 2009). Thus, when consumers perceive the clothing to be useful, it would directly influence their purchase intentions. This has practical implications for retailers and product developers in terms of emphasizing apparel functionalities (e.g., comfort, fit, mobility, etc.) when integrating certain technological functions into clothing, highlighting the usefulness of the product and benefits that would enrich consumers’ daily lifestyles. However, perceived ease of use did not have a significant effect on attitude but rather an indirect effect: The indirect effects of ease of use to both attitude and purchase intention tested using bootstrapped standard errors were significant (β = .078, SE = .016, p < .001; β = .085, SE = . 018, p < .001), indicating that perceived ease of use indirectly influences both attitude and purchase intention through perceived usefulness. Previous researchers also found mixed results regarding the effect of perceived ease of use on consumer attitude toward using technology, where some found a positive effect (Moon & Kim, 2001) and others a nonsignificant effect on attitude (Lu, Yu, Liu, & Yao, 2003). In the case of solar-powered clothing, the effect of perceived ease of use was found to be insignificant. This may be due to the fact that clothing items in general are considered “easy to use” objects; however, this result warrants further investigation. It is also confirmed that perceived performance risks negatively influence consumers’ attitudes and indirectly influence purchase intention through attitude (β = −.052, SE = .014, p < .001), indicating that consumers’ perception that a product would not function as expected is a significant obstacle preventing consumers from selecting the technology-integrated product.

When examining antecedents of TAM related to clothing attributes, it was confirmed that the external stimuli of FEA dimensions significantly influence consumer attitude to use solar-powered clothing. Specifically, perceived compatibility is the strongest predictor of perceived usefulness and also significantly influences perceived ease of use and performance risk. Thus, researchers have confirmed the perceived attributes of smart clothing from the study of Ko et al. (2009) are important factors influencing attitude and further specify the term “perceived attributes” to each FEA and TAM variables. Further, perceived comfort significantly influences perceived ease of use and performance risk, confirming the importance of utilitarian aspects of how a garment interacts with the body. The finding of the negative coefficient implies contradictions between perceived comfort and usefulness, but the correlation coefficient between the two variables is positive (.33), indicating a positive association. A possible explanation of the negative coefficient in Hypothesis 4a may be the lack of variance in perceived usefulness, since perceived compatibility is such a strong predictor (β = .86). This indicates the complexity of clothing attributes coexisting with technology, and consumers may suffer the lack of comfort such as fit and durability. Thus, retailers should balance the design of the smart clothing to be comfortable and promote usefulness. It also emphasizes the shift from a technical concern to a user-centered one for marketability and requires greater mobility and comfort. Lastly, perceived aesthetic attributes significantly influenced attitude toward purchasing solar-powered clothing, confirming this as an important criteria in consumers’ apparel selection decisions. Thus, the distinct aesthetic features of smart clothing should be attractive and compatible with current fashion styles, so that consumers can use advanced technology without losing their fashion sense. Lastly, confirming previous findings (Yan et al., 2012), environmental concerns positively influence attitude and indirectly influence purchase intention. Thus, manufactures may consider integrating proenvironmental attributes when developing smart clothing, such as solar cells to support smart functions as well as organic or recycled materials, to increase positive attitude toward purchasing smart clothing.

The theoretical and practical implications of this study contribute to the growing body of research on the development of smart clothing, especially solar-powered clothing. The researchers confirmed the salient influences of multiple dimensions on wearable technology. The complexities underlying smart clothing and the multiple factors involved in solar-powered clothing from both consumer and apparel industry perspectives are highlighted. Wearable technology is currently at the forefront of consumer products; therefore, it is critical to understand the interconnections of technological and clothing attributes in developing and marketing products that meet the needs of consumers. Further, this validates the TAM model in explaining new technology adoption in clothing and the importance of the FEA model for solar-powered clothing. The results provide a foundation for future research related to adopting wearable technology and the effects of both clothing and technology attributes.

Limitations and Future Research

There are several limitations to this study. The first limitation relates to sampling: The convenience sampling method limits the generalizability of the findings since the sample is comprised of consumers in a university, where the age, education, and income levels of the participants are skewed. Thus, a more heterogeneous group in terms of geographic location, age, and social economic background should be examined to further support the research findings. Other types of technology-integrated clothing should be examined, with both TAM and FEA variables and compared with the results of solar-powered clothing. Considering the nascent field of the topic, future studies may employ qualitative research methods with in-depth interviews to identify the most important perceived attributes considered by consumers in adopting wearable technology in general. Other factors such as price, psychological implication of wearing technology, and the proliferation of new products in the marketplace over the last year should be considered as well. Lastly, focus group interviews may be also conducted, where consumers can touch, feel, and wear test the actual technology-integrated clothing.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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