The antecedents of perceived value in the Airbnb context

Aubrey Stollery (Keimyung University, Daegu, Republic of Korea)
Soo Hyun Jun (College of Business Administration, Department of Tourism Management, Keimyung University, Daegu, Republic of Korea)

Asia Pacific Journal of Innovation and Entrepreneurship

ISSN: 2398-7812

Publication date: 4 December 2017

Abstract

Purpose

This study aims to examine the antecedents of perceived value in the Airbnb context using the variables of perceived benefits (i.e. monetary saving, hedonic benefit, novelty and social interaction) and perceived risks (i.e. performance, physical, psychological and time).

Design/methodology/approach

The study population was Airbnb users in South Korea. This study applied a survey research method using a questionnaire. A link to the survey was sent via e-mail to panel members of a multinational research company.

Findings

The results revealed the positive influence of monetary saving, hedonic benefit and novelty on perceived value and the negative influence of psychological risk on perceived value.

Research limitations/implications

The results of this study, which identified the specific factors that influence Airbnb users’ perception of value, can assist Airbnb managers and Airbnb hosts in developing appropriate marketing plans and strategies to enhance the value of their offerings.

Originality/value

This study provided empirical support to the inclusion of affective factors and risk in determining perceived value. Moreover, while previous Airbnb studies focused on consumers from Western countries (e.g. USA and Canada), this study used a sample of South Korean consumers.

Keywords

Citation

Aubrey Stollery and Soo Hyun Jun (2017) "The antecedents of perceived value in the Airbnb context", Asia Pacific Journal of Innovation and Entrepreneurship, Vol. 11 No. 3, pp. 391-404

Download as .RIS

DOI

: https://doi.org/10.1108/APJIE-12-2017-040

Publisher

:

Emerald Publishing Limited

Copyright © 2017, Aubrey Stollery and Soo Hyun Jun.

License

Published in the Asia Pacific Journal of Innovation and Entrepreneurship. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode


Introduction

The concept of perceived value has long been used by researchers and marketers to understand the purchase decision-making behavior of consumers. Many studies have shown that perceived value influences consumer behavior such as purchase intentions (Bajs, 2015; Cronin et al., 2000; Oh, 2000; Petrick, 2004). Although the literature is clear in indicating the consequences of perceived value, its antecedents have not been as well developed (Zauner et al., 2015). One explanation for this could be that the factors that influence perceived value can change depending on the context (Chen and Dubinsky, 2003). Gallarza et al. (2011) also suggested that the factors which affect perceived value are determined by the product or service being studied. Thus, it is important that research should be conducted to identify the antecedents of perceived value in different contexts. Petrick (2004, p. 29) suggested that a better understanding of the antecedents of perceived value would enable managers to “cater experiences to their various markets in a way to maximize perceptions of value and inevitably future purchase behaviors”.

This study focuses on the context of the sharing economy, specifically Airbnb. Airbnb is an online platform that connects travelers looking for a place to stay, with people that have space to rent out (Guttentag, 2015). Since 2008, Airbnb has served around 150 million guests and offers more than three million listings (i.e. spaces available for rent) in 191 countries (Airbnb, 2017). Given that industry reports predict the number of Airbnb users to continue rising (Ting, 2017; Verhage, 2016), it seems ideal and timely to identify and understand the factors that contribute to the perception of value among Airbnb users.

Accordingly, the aim of this study is to examine the antecedents of perceived value in the Airbnb context. As noted earlier, the factors that may affect perceived value are context-dependent. Hence, this study seeks to analyze the variables that have been identified in the literature as associated with the use of the sharing economy and Airbnb. Specifically, we propose a model of perceived value using perceived benefits (i.e. gains from use of a product or service) and perceived risks (i.e. potential loss from use of a product or service) as antecedents in the Airbnb context. In addition, this study focuses on a sample of South Korean consumers as travelers from Asian countries using Airbnb are gradually increasing (Iyer, 2014). For instance, Asian travelers make up seven of the top ten countries that visited Japan using Airbnb with the most users coming from South Korea (Nikkei Asian Review, 2016). Findings from this study will assist Airbnb managers and Airbnb hosts develop appropriate strategies to enhance the value of their offering.

Literature review

Perceived value

Perceived value has been defined in various ways within the literature. For instance, Woodruff (1997, p. 142) referred to it as:

[…] a customer’s perceived preference for and evaluation of those product attributes, attribute performances, and consequences arising from use that facilitate (or block) achieving the customer’s goals and purposes in use situations.

whereas Chen and Dubinsky (2003, p. 326) described it as “a consumer’s perception of the net benefits gained in exchange for the costs incurred in obtaining the desired benefits”. However, the most commonly cited definition of perceived value is from Zeithaml (1988, p. 14) – “the consumer’s overall assessment of the utility of a product based on perceptions of what is received and what is given”.

The value concept has been suggested as theoretically based on the utility theory of microeconomics (Sanchez-Fernandez and Iniesta-Bonillo, 2006). One application of the utility theory is the weighing of pros and cons of the alternatives to help decision makers determine the “best” (most preferred) course of action for the situation (Fishburn, 1968). Scholars generally conceptualize perceived value in the same way – a trade-off between benefits or what the consumer receives and sacrifices or what the consumer gives up (Chen and Dubinsky, 2003; Woodruff, 1997). Zeithaml (1988) proposed that the benefit component of value is composed of intrinsic attributes, extrinsic attributes, perceived quality and other relevant high level abstraction, whereas the sacrifice component is composed of monetary prices and nonmonetary price (e.g. time, energy and effort). It is assumed that the benefit component has a positive influence on perceived value and that the sacrifice component has a negative influence (Bajs, 2015; Gallarza and Gil Saura, 2006).

Early studies on perceived value were based on a cognitive perspective. That is, these studies have mainly used quality and price as antecedents of perceived value (Sanchez-Fernandez and Iniesta-Bonillo, 2006; Sweeney et al., 1999), which led to a value-for-money conceptualization (Sweeney and Soutar, 2001). However, this had been suggested as being too simple (Bolton and Drew, 1991; Sweeney and Soutar, 2001) and may force consumers to assess tourism services more on their functional and utilitarian dimensions (Otto and Ritchie, 1996).

Recent studies, however, have taken a broader approach by incorporating affective components and non-monetary costs such as effort and risks. For example, Gallarza and Gil Saura (2006) used the factors of efficiency, play, aesthetics, social value, perceived risk and time and effort spent in a travel-behavior context. Sparks et al. (2008) applied relaxation, gift, status, flexibility, fun and new experience as dimensions of value in the timeshare industry. The inclusion of affective factors has been argued as more appropriate due to the importance of experiential aspects in consumption (Holbrook and Hirschman, 1982) especially in tourism (Otto and Ritchie, 1996).

Following the suggestion that perceived value is context-dependent, the specific antecedents examined in this study are based on factors associated with the use of the sharing economy and Airbnb. Specifically, factors that consumers may gain or lose when using sharing economy services and Airbnb are taken into consideration. A review of the current literature reveals factors that are grouped as perceived benefits and perceived risks.

Perceived benefits

Benefit is defined as the advantages enjoyed by the consumer from the use of a product or service (Gutman, 1982). In an online context, Forsythe et al. (2006) referred to perceived benefit as the consumer’s subjective perception of gain. On the basis of existing literature (Carlson Wagonlit Travel, 2015; Folger, 2016; Guttentag, 2015; Tussyadiah and Pesonen, 2016), we suggest that benefits associated with Airbnb use are monetary saving, hedonic benefit, novelty and social interaction.

Monetary saving refers to spending less and saving money (Mimouni-Chaabane and Volle, 2010). Tussyadiah and Pesonen (2016) indicate that use of peer-to-peer accommodations (e.g. Airbnb) is driven by its lower costs in comparison to hotels. This reduced cost allows guests to save money (Folger, 2016). Moreover, Finley (2013) reported that compared to using traditional accommodations, Airbnb users feel they obtain more value from the Airbnb experience as they are able to get a better place for a lower price.

Hedonic benefit relates to the need for enjoyment, fun or pleasure during consumption (Lai, 1995). As argued by Holbrook and Hirschman (1982), consumption is not only limited to solving a problem but also includes seeking fun, amusement and enjoyment. Bellotti et al. (2015) indicated that users of sharing economy services are attracted to experiences that are interesting, engaging and amusing. PricewaterhouseCoopers (2015) also reported that consumers think it is fun participating in the sharing economy. In addition, the study of Satama (2014) found that hedonic motivations have a positive influence in the adoption of Airbnb.

Novelty is generally viewed as the difference between the past and present experience of an individual (Lee and Crompton, 1992; Pearson, 1970). According to Hirschman (1980), the concept of novelty has two related aspects: the first aspect related to searching for new information, and the second aspect related to searching for variety. Several authors (Kim et al., 2012; Petrick, 2002) also related this concept to uniqueness. For the purpose of this study, novelty refers to doing or experiencing something new, different and unique. A desire for novelty is one of the frequently reported motives for travel (Lee and Crompton, 1992). According to Tussyadiah and Pesonen (2016), novelty is present to a certain degree when using peer-to-peer accommodations (e.g. Airbnb). Moreover, they suggested that travelers looking for variety in their experiences may be attracted to peer-to-peer accommodations because they are located outside of the usual tourist areas.

Social interaction refers to a feeling of connection and group identity with local people (Kim et al., 2012). One of the motivations in pleasure travel is the desire to connect with local people (Crompton, 2004). According to Williams and Soutar (2009), interaction with other people creates social benefit in the tourism context. As Airbnb accommodations are homes of ordinary people, it gives travelers the opportunity to interact with the host or neighbors (Guttentag, 2015). Bellotti et al. (2015) suggested that social connections may be a way to enhance the overall value of sharing economy services that offer accommodations.

Perceived risks

Stone and Winter (1985, p. 2) defined perceived risk as “one’s expectation of loss associated with an exchange”. In an online context, Forsythe et al. (2006) refers to perceived risk as the consumer’s subjective perception of potential loss. Previous studies on the sharing economy and Airbnb have suggested that consumers perceive risks in terms of performance, physical, psychological and time (Carlson Wagonlit Travel, 2015; Finley, 2013; Folger, 2016; Guttentag, 2015; Mun, 2013).

Performance risk is defined as the possibility of not getting what is expected or the service not performing as expected (Horton, 1976). This risk may be a result of consumers’ limited ability to accurately determine the quality of offerings online as it cannot be touched, felt or tried beforehand (Forsythe and Shi, 2003). Mun (2013) indicated that there were some worries about the quality and misrepresentation of what was being offered in the sharing economy. In the case of Airbnb, this may translate to the photos, location and description of the listings posted online not matching the ones in real life (Finley, 2013). Furthermore, as there are no specific hospitality standards implemented among Airbnb listings, risks were also noted regarding cleanliness and noise levels (Finley, 2013; Guttentag, 2015).

Physical risk refers to “the chances that (brand) may not be safe, may be (or become) harmful or injurious to health” (Jacoby and Kaplan, 1972, p.11). Compared to hotels or traditional bed and breakfasts, Airbnb listings are unregulated (Stone, 2015), and there seems to be no health and safety regulations that they have to follow (Bonnington, 2015). As such, security and personal safety is one of the concerns in the use of Airbnb (Carlson Wagonlit Travel, 2015; Finley, 2013). Additionally, several “horror” stories in the use of Airbnb exist online. There was a host who locked a guest in and sexually assaulted him (Lieber, 2015) and another who drugged his guests (Jose, 2013). In 2013, a Canadian woman died in an Airbnb listing in Taiwan as it had a broken heater which filled the room with poisonous gas (Hill, 2015).

Psychological risk refers to the possibility that using Airbnb will have a negative effect on a person’s peace of mind (Garner, 1986). Psychological risks are dominant in purchase situations, wherein the item or service is expensive, complex and difficult to judge (Kim et al., 2009; Stone and Grønhaug, 1993). The study of Pires et al. (2004) found that psychological risks were ranked the highest for services purchased online. As there are no hospitality standards implemented among Airbnb listings and guests do not know what to expect, it becomes troubling for users (Finley, 2013).

Time risk means the possibility of wasting time, taking too much time or effort in using a service (Garner, 1986). Mitchell and Greatorex (1993) found that for hotel services, time risk was the second most important risk for consumers. In the case of Airbnb, as they provide a wide variety of accommodation choices, it may be time-consuming looking for offers that are trustworthy (Carlson Wagonlit Travel, 2015). Additionally, as not all Airbnb listings have an instant book feature, it would require more time and effort to send messages to the host before being able to reserve a room (Guttentag, 2015).

Hypotheses

Several studies in different contexts provide support for the positive relationship between the specific benefits used in this study and perceived value. Han and Hwang (2013), in their study of medical hotels, found that financial saving was a significant predictor of perceived value. In a cruise services context, Duman and Mattila (2005) showed the strong positive relationship between hedonics and perceived value. Sparks et al. (2008) reported that timeshare owners acquired value from novelty (operationalized in their study as new experiences). In the travel context, Gallarza and Gil Saura (2006) showed that social interaction (operationalized in their study as social value) was a positive antecedent of perceived value. On the basis of the previous discussion, it is proposed that

H1.

Monetary saving positively influences perceived value.

H2.

Hedonic benefit positively influences perceived value.

H3.

Novelty positively influences perceived value.

H4.

Social interaction positively influences perceived value.

Several scholars (Agarwal and Teas, 2001; Zauner et al., 2015) have suggested that perceived risk is a variable that may affect consumers’ value perception. Day and Crask (2000, p. 57) also proposed a relationship between perceived value and risk as this will reframe value “in terms consistent with the manner in which consumers evaluate and choose among alternatives”. Furthermore, they posit that when risk is reduced, value is provided to the consumer.

Some empirical studies (Chen and Dubinsky, 2003; Kwun and Oh, 2004) have already been conducted to analyze the relationship between perceived risk and value. However, most of these studies have mainly used a general risk measure in their model. Only a few studies have explored the relationship between the individual dimensions of risk and perceived value. For example, the study of Sweeney et al. (1999) and Agarwal and Teas (2001) used performance and financial risks. They found that performance and financial risks have a negative effect on perceived value. The present study proposes the same negative effect as risks represent the sacrifice component of value. Accordingly, it is hypothesized that

H5.

Performance risk negatively influences perceived value.

H6.

Physical risk negatively influences perceived value.

H7.

Psychological risk negatively influences perceived value.

H8.

Time risk negatively influences perceived value.

Methodology

The target population of this study was Airbnb users in South Korea. The study sample was drawn from the panel of a multinational research company. Data were gathered by means of a questionnaire. The questionnaire was distributed online to panel members through e-mail messages that contained a link to the survey. There were a total of 4,688 panel members invited to participate in the study. On the basis of a filter question, only panel members who had previous Airbnb use experience were included in the final sample.

In developing the questionnaire, items were adopted from scales used by previous researchers and modified to fit the Airbnb context. Four items under monetary saving (i.e. lowers my travel costs, saves me money, makes travel more affordable and benefits me financially), five items under hedonic benefit (i.e. exciting, enjoyable, fun, interesting and pleasant) and four items under social interaction (i.e. know people from the local neighborhoods, develop social relationships, connect with locals and have a meaningful interaction with locals) were from the study of Tussyadiah (2016). To measure novelty, six items (i.e. different types of accommodations, various experiences, wide assortment of experiences, new places, new experiences and innovativeness) were adopted and modified from Vogt and Fesenmaier (1998) and four items (unique places, something one-of-a-kind, unusual places and unique experiences) came from Folger (2016) and the Airbnb website. Four items in the performance risk scale (not matching the photos posted online, not matching the descriptions posted online, would not be clean and host would treat me unkindly) were developed from the study of Finley (2013), Folger (2016), Guttentag (2015) and Mun (2013). To form the scale for physical risk, items (i.e. something bad happening, host may do something bad and may not be safe staying at an Airbnb place) were taken from Jose (2013), Lieber (2015) and Stone (2015). Psychological risk items (i.e. feeling of unwanted anxiety, feeling psychologically uncomfortable and experiencing unnecessary tension) were from Kim et al. (2009). Four items to measure time risk (i.e. waste of time, a lot of effort, take too much time and inefficient use of time) were from the study of Guttentag (2015) and Kim et al. (2009). Perceived value was measured using a three-item scale (i.e. The Airbnb experience has satisfied my wants, Overall, the value of the Airbnb experiences is high, Compared to what I gave up, what I received from Airbnb was high) from Gallarza and Gil Saura (2006). All responses to the items were measured using a seven-point Likert type scale with “1” being “strongly disagree” and “7” being “strongly agree”. Demographic information and Airbnb use behavior of the respondents were also collected.

Results

Out of 4,688 panel members who were invited to participate in the study, 1,393 members responded, which represents a 29.7 per cent response rate. The filter question that was included to select Airbnb users only resulted in the collection of 416 complete responses. After data cleaning, six responses were removed due to the use of similar internet protocol (IP) address, leading to a total of 410 responses being used for further analysis.

Table I presents the demographic profile and Airbnb use behavior of the respondents. The respondents were predominantly female (65.6 per cent). Nearly half (44.9 per cent) of the respondents were aged between 20 and 29 years. Most of the respondents (70.0 per cent) had a university or college degree and the highest number of respondents came from Seoul (44.9 per cent). Almost half of the respondents found out about Airbnb from the internet (44.6 per cent). During their most recent Airbnb use, 41.2 per cent of the respondents stayed in Asia (excluding South Korea). In terms of the number of Airbnb use, 27.8 per cent of the respondents have used it twice, while 26.8 per cent of the respondents have used it four times or more.

The data were factor-analyzed using principal component analysis with Varimax rotation. Table II summarizes the results of the factor and reliability analyses. Four factors emerged for both perceived benefits and perceived risks, which explained 75.024 and 84.613 per cent of the variance, respectively. Except for three items under perceived benefits, all items loaded on their intended factor. These three items were removed and excluded from further analysis. All factor loading scores were 0.60 and higher, while the Cronbach’s alpha scores for all factors were equal to or greater than 0.80.

The hypotheses were tested with a regression model using the enter method. The dependent variable, perceived value was regressed against the factors that emerged from the factor analysis. Multicollinearity was not a concern for the data as the variance inflation factor (VIF) values were all below the cut-off value of 5 (Hair et al., 2011). Table III reports the results of the regression analysis. With an adjusted R2 value of 0.437, this model accounts for 43.7 per cent of the variance in perceived value.

In terms of perceived benefits, monetary saving (β = 0.128, p < 0.01), hedonic benefit (β = 0.177, p < 0.01) and novelty (β = 0.353, p < 0.001) were significantly and positively associated with perceived value. Thus, H1, H2 and H3 were supported. Unexpectedly, social interaction was not significantly related to perceived value. Therefore, support for H4 was not found.

With regard to perceived risks, only psychological risk (β = −0.226, p < 0.001) was significantly and negatively associated with perceived value, which lends support for H7. The proposed negative effect of performance risk, physical risk and time risk on perceived value was not found. Thus, H5, H6 and H8 were not supported.

On the basis of the regression coefficients, novelty had the greatest impact on the perceived value of Airbnb users. This was followed by psychological risk, hedonic benefit and monetary saving.

Conclusion

The results revealed the significant positive effects of monetary saving, hedonic benefit and novelty on perceived value. These findings suggest that South Korean Airbnb guests find value in using Airbnb because it allows them to have different and unique experiences, have fun and excitement and save money. Novelty was found to be the strongest predictor of perceived value, which implies the importance of providing experiences to guests that are different from the usual. These results support previous studies, which show that affective factors (i.e. hedonics and novelty) influence perceived value (Duman and Mattila, 2005; Sparks et al., 2008). It was also found that social interaction does not influence perceived value despite many studies highlighting this specific benefit in using Airbnb. This result suggests that the opportunity to interact and form relationships with locals does not enhance the value of using Airbnb among South Korean guests.

Results further reveal the significant negative effect of psychological risk on perceived value. This finding is in line with the study of Stone and Grønhaug (1993) and Kim et al. (2009) regarding the presence of psychological risks on items that are complex and hard to judge. This result indicates that guests have feelings of anxiety when using Airbnb, which influences their value perception of the service. The other types of risk (i.e. performance, physical and time) were found to have no influence on perceived value. A possible reason for this result may be attributed to the nature of the study sample. Almost 75 per cent of the respondents had used Airbnb twice or more and this experience could have reduced their risk perception. Previous studies have indicated that less risk is perceived as consumers gain more experience (Kim et al., 2009; Sonmez and Graefe, 1998). If this study had been conducted with non-users of Airbnb, the presence of the other risk types might have been more salient. Further studies, however, are needed to support this explanation.

Theoretical and managerial implications

This study broadens the application of the perceived value concept into the sharing economy context, specifically Airbnb. The results of the study also contribute to the literature by identifying the specific antecedents of perceived value in the Airbnb context. Moreover, it provides empirical support to the inclusion of affective factors as antecedents of perceived value. Specifically, the importance of novelty and hedonics in the Airbnb experience were highlighted in this study despite the focus of the sharing economy and Airbnb literature on the economic aspect. Although this study found that only one risk type (i.e. psychological risk) had a significant effect on perceived value, it implies that it is still worthwhile to include the different risk dimensions as antecedents of perceived value. As this study showed, even if consumers have experience with the service, certain risk types may still be present which can subsequently affect their value perceptions.

The study results also have a significant implication in the management and promotion of Airbnb. The study results indicate the importance of novelty and hedonics to guests of Airbnb. Airbnb management should continue to emphasize the different, unique and fun experiences to be had when using Airbnb in their marketing strategies. Additionally, Airbnb hosts should pay attention on providing guests with experiences that are enjoyable and unusual. It is also important to make guests feel that they are able to save money when they use Airbnb as opposed to using hotels or motels in the area they will be staying at. A key issue to resolve is the presence of psychological risks in the use of Airbnb. A suggestion would be for Airbnb managers and hosts to identify the sources of worry and anxiety for guests and find ways to address them. For example, Airbnb management may provide guarantees to their guests (e.g. by sending an email message and providing contact numbers) that they will be taken care of in case of any eventualities during their stay.

Limitations and future studies

Several limitations were identified in the study. First, this study is limited to a sample of Airbnb users from one country, South Korea. Therefore, caution must be taken in generalizing the results. Further studies should be undertaken with Airbnb users from different countries to further validate the results. Second, this study only examined the perception of Airbnb users. Additional research is needed to analyze the perceptions of non-users as the factors that influence their perceived value of Airbnb may be different from those with experience. As mentioned previously, risk perceptions may be more salient for consumers who have no Airbnb use experience. Third, the variables used in the study were limited to the ones identified in the literature as associated with the sharing economy and Airbnb. This model accounted for a significant amount of variance (44 per cent); however, it also indicates that there are other possible antecedents of perceived value in the Airbnb context. Quality and price are two such factors that have been shown to significantly affect value perceptions but were not included in this study. Hence, future research should include price, quality and other variables in their model of perceived value. Finally, while this study is exploratory in nature and applied regression analysis, future studies are encouraged to apply a more powerful statistical approach for a richer understanding of the antecedents and additionally the consequences (e.g. intention and repurchase intention) of perceived value.

Demographic profile and Airbnb use behavior of respondents

Characteristics Frequency (%)
Gender
Male 141 34.4
Female 269 65.6
Age
20-29 184 44.9
30-39 125 30.5
40-49 77 18.8
50-59 24 5.9
Level of education
High school graduate 48 11.7
University/college graduate 287 70.0
Masters or PhD graduate 75 18.3
Others
Monthly household income
under ₩ 2,000,000 25 6.1
₩ 2,000,001 to ₩ 4,000,000 105 25.6
₩ 4,000,001 to ₩ 6,000,000 102 24.9
₩ 6,000,001 to ₩ 8,000,000 94 22.9
₩ 8,000,001 to ₩ 10,000,000 54 13.2
₩ 10,000,001 and over 30 7.3
Place of residence
Seoul 184 44.9
Incheon, Gyeonggi 113 27.6
Busan, Gyeongnam 48 11.7
Daegu, Gyeongbuk 30 7.3
Daejeon, Chungcheong, Gangwon 18 4.4
Gwangju, Jeolla, Jeju 17 4.1
How they found out about Airbnb
Internet 183 44.6
Friends and acquaintances 133 32.4
Homepage (www.airbnb.com) 50 12.2
SNS 20 4.9
Mobile app 14 3.4
TV or radio 9 2.2
Others 1 0.2
Area recently stayed at using Airbnb
Asia (except South Korea) 169 41.2
South Korea 100 24.4
Europe 100 24.4
North America 33 8.0
Oceania 5 1.2
South America 3 0.7
Number of Airbnb use
Twice 114 27.8
Four times or more 110 26.8
Once 106 25.9
Thrice 80 19.5

Results of exploratory factor analysis and reliability analysis

Factor Items Factor loading Eigenvalue Variance (%) Alpha
Monetary saving MS2
MS1
MS3
MS4
0.835
0.832
0.817
0.737
3.213 16.066 0.894
Hedonic benefit HB2
HB1
HB4
HB3
HB5
0.807
0.804
0.796
0.774
0.751
4.024 20.118 0.937
Novelty N6
N3
N7
N5
N4
N2
N1
0.763
0.749
0.720
0.691
0.665
0.664
0.625
4.275 21.376 0.914
Social interaction SI3
SI4
SI2
SI1
0.886
0.877
0.816
0.676
3.493 17.464 0.902
KMO = 0.932; Bartlett’s χ2 = 6771.811; Total variance = 75.024%
Performance risk PR2
PR1
PR3
PR4
0.894
0.880
0.866
0.748
3.348 23.916 0.906
Physical risk PHYR2
PHYR3
PHYR1
0.842
0.816
0.727
2.336 16.687 0.914
Psychological risk PSYR1
PSYR2
PSYR3
0.829
0.825
0.805
2.516 17.971 0.932
Time risk TR3
TR2
TR1
TR4
0.871
0.865
0.864
0.864
3.646 26.039 0.946
KMO = 0.894; Bartlett’s χ2 = 5446.767; Total variance = 84.613%
Perceived value PV3
PV1
PV2
0.876
0.859
0.827
2.188 72.945 0.809
KMO = 0.708; Bartlett’s χ2 = 424.074; Total variance = 72.945%

Results of multiple regression analysis on perceived value

Beta t
Perceived benefits
Monetary saving 0.128 2.691**
Hedonic benefit 0.177 3.082**
Novelty 0.353 5.862***
Social interaction 0.070 1.378
Perceived risks
Performance risk 0.008 0.173
Physical risk 0.026 0.478
Psychological risk −0.226 −4.064***
Time risk 0.069 1.276
Adjusted R2 0.437
ANOVA regression F ratio 40.610***
Notes:

*p < 0.05;

**

p <0.01;

***

p < 0.001

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Corresponding author

Soo Hyun Jun can be contacted at: soohjun@kmu.ac.kr