Abstract
This paper examines the relationship between consumer loneliness, boredom, telepresence, influencer-brand image congruence and purchase intention by investigating consumers of live commerce during the COVID-19 period. With the help of an online survey website, survey data was gathered on 550 Chinese customers who experienced live commerce shopping in China. Although previous studies have shown that consumer boredom and loneliness have an impact on purchase intention, the mechanism of influence remains unclear. As a result, additional research is needed to study the link between boredom and loneliness and customer purchase intention. Consumers’ purchase intention was influenced by their feelings of loneliness and boredom. Telepresence played a mediating role in the impact of loneliness and boredom on purchase intention. Influencer-brand image congruence played a moderating role in the impact of consumers’ boredom on purchase intention. The study results contribute to the research of factors impacting consumers’ purchase intention. In addition, this study can help live commerce merchants better understand the impact factors of consumers’ purchase intention and contribute to the development of live commerce.
Introduction
Live commerce has been booming in China in recent years and has been welcomed by the market as a new type of shopping (Andronie et al., 2021; Liu et al., 2022). With the attributes of social business and the unique live streaming attributes, live commerce is rapidly improving its position in the consumer market. According to data, China’s live commerce market size exceeds RMB 1.2 trillion in 2020, with an annual growth rate of 197%, and is expected to exceed RMB 4.9 trillion in 2023. Live commerce is rapidly taking over China’s consumer market (iresearch, 2021). Meanwhile, on March 11, 2020, the World Health Organization (WHO) announced the emergence of the COVID-19 outbreak, which has now affected more than 223 countries and territories (Priyadarshini et al., 2020). Studies have shown that COVID-19 can cause physical and mental health damage (Moreno et al., 2020; Xiang et al., 2020; Meda et al., 2021). Preliminary research suggests that the pandemic’s mental challenge will continue to impact society and people for some time (Ahmed et al., 2020; Brenner, 2020). And because people fear that COVID-19 will threaten their lives, they reduce social activities to protect themselves and spend a lot more time at home, resulting in issues like feelings of loneliness and boredom (Brooks et al., 2020). Studies have shown that consumer emotions are closely related to purchase intention (Ma and Wang, 2021; Watson and Popescu, 2021; Zhou et al., 2021; Kliestik et al., 2022). When people feel negative psychological emotions, they buy products to relieve negative emotions and escape from reality (Hoffner and Lee, 2015; Gong et al., 2022). It is worth noting that people would alleviate their loneliness and boredom by purchasing through live commerce (Snyder and Newman, 2019). However, the literature on live commerce research during COVID-19 is insufficient. The mechanisms by which consumers’ feelings of loneliness and boredom impact purchase intention remain unclear. Therefore, there is a need for further research on the mechanisms of how loneliness and boredom generated by consumers during the COVID-19 period affect purchase intention.
This study contributes to the body of knowledge about the factors that influence the purchasing intentions of online shoppers. First, this study enriches the research in related fields by illustrating how consumers’ loneliness and boredom impact purchase intention during the COVID-19 period based on media compensation theory. Specifically, the effects of loneliness, boredom, and telepresence on purchase intention are identified. The study explored the mediating role of telepresence between boredom and purchase intention and loneliness and purchase intention. Second, our study reveals that influencer-brand image congruence moderates the effects of loneliness and boredom on purchase intention. The results show that influencer-brand image congruence enhances the positive impact of loneliness and boredom on purchase intention. Our study also provides practical suggestions for live commerce platforms and merchants to promote live commerce’s sustainable and healthy development. Therefore, this work is crucial since it will provide new information for future consumer psychology and live commerce during the COVID-19 pandemic. Figure 1 shows the research model established in this paper.
FIGURE 1
Literature Review and Hypothesis Development
The Impact of Loneliness on Boredom
The COVID-19 pandemic has made it more difficult for individuals to go outside due to fears of infection, death and other threats from the outbreak. And, as time spent at home increases dramatically, people reduce social and recreational activities, increasing consumer isolation (Bu et al., 2020; Elran-Barak and Mozeikov, 2020; Ausín et al., 2021). When people experience emotions of loneliness, they generally wish to take action to interact via online media to compensate for real social interaction (Smith et al., 2021). Therefore, when people feel lonely during the pandemic, they reduce their loneliness by using smartphones and other methods of entertainment to relieve their negative inner feelings (Kardefelt-Winther, 2014; Killgore et al., 2020a). As an essential factor affecting people’s mental health, loneliness is closely related to negative emotions such as boredom and anxiety (Beutel et al., 2017). Some studies show that loneliness leads to higher levels of boredom (Chen, 2020; Li et al., 2021). In the COVID-19 period, boredom increases when people feel lonely at home due to the inability to satisfy their inner social needs. Based on this, the following hypothesis is proposed:
H1: Loneliness during the COVID-19 period has an impact on boredom.
The Impact of Loneliness on Purchase Intention
Loneliness is a subjective state of social isolation, a painful experience of the individual’s lack of contact with others (Russell et al., 1978). Loneliness is often described as a negative emotion associated with isolation and dissatisfaction (Rokach, 2004). As a negative emotion, loneliness can make people feel unhappy and even lead to illnesses such as depression because loneliness can make people’s perceived social status and socialization inconsistent with reality (Russell, 1996). With the rise of loneliness, people often want to take steps to alleviate this negative feeling and, if necessary, even need intervention therapy (Park et al., 2015; Rajendran and Arun, 2020; Yang et al., 2021). Loneliness increases during COVID-19 pandemic when people cannot engage inadequate social and recreational activities due to social distance restrictions and other reasons (Killgore et al., 2020b; Li and Wang, 2020). In this case, people will alleviate their loneliness by purchasing goods. When people feel lonely, they increase their purchase intention and use shopping consumption as a coping means to relieve loneliness (Mandel et al., 2017; Yang et al., 2021). Therefore, this study hypothesized that:
H2: Loneliness during the COVID-19 period can have an impact on purchase intention.
The Impact of Boredom on Purchase Intention
Boredom can be seen as a state of difficulty in concentrating due to constant fatigue while awake (Mikulas and Vodanovich, 1993). COVID-19 causes many people to stay at home for their protection, making people safer and objectively limiting their social activities. People staying at home every day can reduce individual arousal levels and create boredom (van Tilburg and Igou, 2017). People’s reduced social activities and social isolation can increase boredom and reduce people’s life satisfaction (Chao et al., 2020). Studies have shown that boredom is closely related to shopping behavior, and people’s intention and behaviors increase when they feel bored (Lidholm et al., 2017; Bae et al., 2019; Bozaci, 2020; Pelegrín-Borondo et al., 2020). As a result of the common idea that going shopping may both ease boredom and put importance into otherwise mundane events (Sundström et al., 2019). Therefore, to compensate for the lack of social interaction in real life, people increase their purchase intention and even develop an addiction to excessive shopping (El Hedhli et al., 2016; Lidholm et al., 2017; Vinerean et al., 2022). Therefore, this study hypothesized that:
H3: Consumer boredom in the COVID-19 period can have an impact on purchase intention.
The Mediating Effect of Telepresence
Telepresence is an immersive online experience that is a combination of imagined accessibility and immersion, in which consumers are very focused and engaged (Novak et al., 2000; Hopkins et al., 2004; Hyun and O’Keefe, 2012; Beuckels and Hudders, 2016; Cowan and Ketron, 2019). In telepresence, the individual is unaware that they are in a virtual environment created by media such as television or computers at the time (Coyle and Thorson, 2001; Faiola et al., 2013). Telepresence is a standard variable for studying consumer behavior in online environments (Algharabat, 2018). People increase their use of media to compensate for social deficits such as loneliness, boredom, and anxiety (Hollenbaugh and Ferris, 2014; Lim and Kim, 2017). In this process, individuals who feel more lonely may watch media programs and do online shopping to relieve their inner loneliness (Lather and Moyer-Guse, 2011; Minnebo et al., 2014). The emergence of television shopping programs, in particular, has addressed the entertainment and shopping demands of customers (Fritchie and Johnson, 2003). Shopping on television allows consumers to become immersed in the show and engage with the host and other shoppers (Gudelunas, 2002). Consumers can alleviate feelings of loneliness and boredom when shopping on television since they are able to forget about the real world around them (Mollen and Wilson, 2010; Bellman et al., 2014). Through communication and interaction with the hosts of TV shopping programs, individuals can reduce boredom and have a positive psychological experience (Chory-Assad and Yanen, 2005; Derrick et al., 2009; Lim and Kim, 2011). Interacting and shopping with TV hosts help individuals reduce negative emotions, and consumers become immersed in the shopping environment provided by the seller, creating a sense of telepresence. Thus, feelings of loneliness and boredom enhance the telepresence experience. Telepresence could convince customers that they can completely comprehend the goods, allowing them to boost their enjoyment of the occurrence and thus create higher purchase intention (Gao and Li, 2019; Ongsakul et al., 2020; Ye et al., 2020). During the COVID-19 period, less research has been done on the factors influencing consumer purchase intention in TV buying. Customers can communicate with influencers and others more easily in person than they do on television. Customers who see influencers and other consumers market things are more likely to make a buy themselves (Yu and Kim, 2020; Wang et al., 2021). There are just a few options for customers to connect with the host when buying on TV, such as making phone calls or writing letters rather than using multiple communication channels. But the live commerce environment is real-time communication using cell phones face-to-face, and consumers and participants of other live platforms also form multiple communication fields. Therefore, live commerce is more accessible for consumers to feel telepresence than TV shopping, and the interaction methods are more diverse. Based on the above study, these hypothesis was formulated:
H4: Loneliness in the COVID-19 period influences purchase intention in live commerce through telepresence.
H5: Boredom in the COVID-19 period has an impact on purchase intention in live commerce through telepresence.
Moderating Role of Influencer-Brand Congruence
In live commerce, influencers play the role of merchandise advocates in the sales process. Many social media influencers have enormous followings, and their fans trust the things they advocate, which is regarded to be the marketing value of the influencers to the companies in these social media industries (De Veirman et al., 2017; Kemp et al., 2019; Lou and Yuan, 2019). Influencers significantly impact consumers’ shopping decisions as product advocates and opinion leaders (Casaló et al., 2020). In previous studies, spokesperson-brand image congruence is an important influencing factor for consumers’ purchase intention. Product spokespersons represent corporate culture and image and are of great significance in the consumer shopping process (Escalas and Bettman, 2005; Shan et al., 2020). When customers believe the spokesperson’s image matches the product’s image, the product commercial and the brand’s image are more positively received by customers, the research revealed (Akbar, 2019; Lee et al., 2019; Haobin Ye et al., 2021). When consumers feel that the spokesperson’s brand image is inconsistent, it decreases the consumer’s favorability of the product and can reduce their willingness to purchase the product (Paul and Bhakar, 2018; Deska et al., 2022). Although consumers’ feelings of loneliness and boredom can have an impact on purchase intention, when influencer images are less consistent with brand images, it may reduce consumers’ trust in the product and decrease the shopping experience. Consumers are less likely to have purchase intention for products with low influencer-brand image congruence. Spokesperson-brand image congruence strengthens consumers’ willingness to shop, but research exists primarily in television shopping or in social shopping (Skupski, 2019; Arora et al., 2021). Fewer studies have been conducted in the COVID-19 period on the influencers’ brand image congruence in live commerce. Consumers in social media will trust influencers more than traditional celebrities and show more positive attitudes toward products endorsed by influencers (Jin et al., 2018; Kim and Kim, 2021; Li and Peng, 2021; Pop et al., 2022). Whether influencer-brand image congruence enhances the effect of loneliness and boredom on shopping intention is a question worthy of further study. Therefore, this study hypothesized that:
H6: Influencer-brand image congruence enhances the positive effect of loneliness on purchase intention in live commerce.
H7: Influencer-brand image congruence enhances the positive effect of boredom on purchase intention in live commerce.
Materials and Methods
Participants
In order to test the research model and related hypotheses, this paper adopts a questionnaire survey method to collect data. 550 Chinese live commerce consumers participated in this study and completed an informed consent form before completing the questionnaire. Using the WENJUANXING data website, a questionnaire was employed to gather information. It was gathered between February 10, 2022 and February 25, 2022.
Variable Measurement
Loneliness
The measure of loneliness was modified from the revised Loneliness Scale by Tian et al. (2012). The scale consists of 20 items (e.g., “Do you feel isolated?”). The response options on the questionnaire ranged from 1 (strongly disagree) to 5 (strongly agree). Higher scores reflect higher levels of individual loneliness. Cronbach’s α = 0.835.
Boredom
The boredom scale revised by Lee and Zelman was used in this study (Lee and Zelman, 2019). The scale contains 12 items (e.g., “Usually, I am less able to find things that interest me”). The scale has shown good reliability and validity in previous studies (Elhai et al., 2018). The response options for the questions ranged from 1 (strongly disagree) to 5 (strongly agree). Higher scores reflect higher levels of individual boredom. In our study, the internal rate of reliability of the questionnaire was high with a Cronbach’s α = 0.867.
Telepresence
As revised by Kim and Biocca the telepresence scale was used in this study (Kim and Biocca, 1997). The scale contains nine measures (e.g., when I use live commerce, I forget the reality of my environment). Cronbach a = 0.815.
Influencer-Brand Image Congruence
The study was adapted from a scale developed by Haobin Ye et al. (2021). The scale contains 3 measures (e.g., do you think the influencer’s image is consistent with the image of the company). The questionnaire response options range from 1 (strongly disagree) to 5 (strongly agree). Cronbach’s α = 0.884.
Purchase Intention
The questionnaire was based on a questionnaire developed by Li et al. (2002). The scale contained four measures (e.g., how likely you think it is to buy the product) (Li et al., 2002). The response options of the questionnaire ranged from 1 (strongly disagree) to 5 (strongly agree). Cronbach’s α为0.759.
Procedure
The Academic Research Ethics Committee of Linyi University approved the study (No. LYU20220105). The study questionnaire was answered anonymously, and they were instructed on how to complete the survey. Informed consent was obtained from all participants before the study, and participants could withdraw during the response process.
Data Analyses
Statistical analyses were performed using SPSS 26.0 software. Specifically, first, descriptive statistics and correlation analyses were conducted for the main variables. Second, the effect of loneliness on boredom was analyzed by regression using SPSS. In addition, the mediating and moderating roles of telepresence in loneliness, boredom, and purchase intention were analyzed using model 5 of SPSS PROCESS macro (Preacher and Hayes, 2008). SPSS PROCESS macro can provide several models to perform analysis of processes such as mediation and moderation effects.
Results
Descriptive Statistics
In the 550 valid survey samples, there are a total of 273 females and 277 males. Sample loneliness mean = 3.52, skewness = –6.38, kurtosis = –0.855. sample boredom mean = 3.43, skewness = –8.56, kurtosis = –0.534. More than 65.82% are people aged 18–32, 75.09% of the samples have a junior college degree or above. Most people spent an average of less than 1 h on live commerce every day. The descriptive statistics of our survey samples are shown in Table 1.
TABLE 1
| Characteristics | Frequency | The percentage | |
| Gender | Male | 277 | 50.36 |
| Female | 273 | 49.67 | |
| Age | 18 Years old and below | 103 | 18.73 |
| 18–25 Years old | 169 | 30.73 | |
| 26–32 Years old | 193 | 35.09 | |
| 33–40 Years old | 29 | 5.27 | |
| 40 Years old and above | 56 | 10.18 | |
| Education | High school and below | 137 | 24.91 |
| Junior college degree | 208 | 37.82 | |
| Bachelor’s degree | 176 | 32.00 | |
| Master’s degree or above | 29 | 5.27 | |
| Frequency of use (hours) | Less than 0.5 | 248 | 45.09 |
| 0.5–1 | 260 | 47.28 | |
| 1–3 | 24 | 4.36 | |
| Above 5 | 18 | 3.27 | |
Descriptive characteristics of the sample (N = 550).
Table 2 summarizes the descriptive statistical results and correlations between the main variables. Correlation analysis showed that loneliness was positively correlated with boredom, telepresence, and the purchase intention process. Boredom was positively correlated with telepresence and purchase intention, and Purchase intention was positively correlated with endorser influencer-image congruence.
TABLE 2
| Variables | M | SD | 1 | 2 | 3 | 4 | 5 |
| Loneliness | 3.5156 | 0.96004 | 1 | ||||
| Boredom | 3.428 | 0.99126 | 0.382** | 1 | |||
| Telepresence | 3.4986 | 1.02513 | 0.358** | 0.321** | 1 | ||
| PI | 3.4232 | 0.83204 | 0.290** | 0.205** | 0.292** | 1 | |
| IBC | 3.1085 | 1.32318 | 0.044 | –0.013 | 0.002 | 0.103* | 1 |
Correlations between variables.
*p < 0.05; **p < 0.01.
N = 550. M, mean; SD, standard deviation; PI, Purchase Intention; IBC, Influencer-brand image congruence.
Table 3 depicts the relationship between consumer loneliness, boredom, and purchase intention during COVID-19. Specifically, loneliness had an impact on boredom (β = 0.382, SE = 0.035, t = 9.669). In addition, loneliness had an impact on purchase intention (β = 0.183, SE = 0.037, t = 4.961). Boredom has an impact on purchase intention (β = 0.106, SE = 0.036, t = 2.964). Hypothesis 1 and Hypothesis 2 and Hypothesis 3 are supported.
TABLE 3
| Relationship | β | SE | 95% CI | Results | |
| Lower | Upper | ||||
| Direct effect | |||||
| Loneliness→boredom | 0.382 | 0.035 | 0.314 | 0.474 | Supported |
| Loneliness→PI | 0.183 | 0.037 | 0.111 | 0.256 | Supported |
| Boredom→PI | 0.106 | 0.036 | 0.036 | 0.176 | Supported |
| Indirect effect | |||||
| Loneliness→TP→PI | 0.067 | 0.016 | 0.038 | 0.100 | Supported |
| Boredom→TP→PI | 0.068 | 0.016 | 0.040 | 0.101 | Supported |
Standardized parameter estimates for the direct and indirect effects of the hypothesized model.
n = 550, bootstrapping randomly sampled 5,000 times.
Mediation analysis was performed to test the mediating role of telepresence in the association between loneliness, boredom, and purchase intention. To test the mediating role of escape motivation between loneliness, boredom and purchase intention, we ran the PROCESS macro, model 5, in SPSS with 5,000 bootstrapping samples (Preacher and Hayes, 2008). All data were standardized. Telepresence exhibited a significant mediating effect (Table 3). We suggested that telepresence plays a mediating role between loneliness and purchase intention (β = 0.067, 95% confidence interval of bootstrapping = 5,000 is [0.038, 0.100], excluding 0). Moreover, telepresence exerts a mediating effect on boredom and purchase intention (β = 0.068, 95% confidence interval of bootstrapping = 5,000 is [0.040, 0.101], excluding 0). Thus, telepresence partially mediates the relationship between loneliness, boredom and purchase intention.
To test the moderating roles of influencer-brand congruence, we ran the PROCESS macro (PROCESS Model 5; Preacher and Hayes, 2008). Influencer-brand congruence had a significant moderating effect on the relationship between boredom and purchase intention, results shown in Table 4 (β = 0.049, t = 2.024). To illustrate the moderating effect presented above, we conducted a simple slope test. We divided telepresence into high (M + 1 SD) and low (M –1 SD) groups to better explain telepresence in moderating boredom and purchase intention (Figure 2). The results revealed that when the influencer-brand congruence was high (mean + 1 SD), boredom exerted a significant influence on the purchase intention of live commerce consumers (b = 0.171, t = 3.534, p < 0.001). When the influencer-brand congruence was low (mean –1 SD), boredom exerted no significant negative impact on the purchase intention of live commerce consumers (b = 0.040, t = 0.842, p = 0.40). Therefore, We found that influencer-brand congruence exerts a significant moderating effect on boredom and purchase intention (β = 0.049, 95% confidence interval of bootstrapping = 5,000 is [0.072, 0.157], excluding 0). Hence, Hypothesis 4 and Hypothesis 5 and Hypothesis 6 are supported.
TABLE 4
| Relationship | β | SE | 95% CI | t | Results | |
| Lower | Upper | |||||
| Loneliness × IBC → PI | 0.047 | 0.025 | –0.002 | 0.096 | 1.868 | Not supported |
| Boredom × IBC → PI | 0.049 | 0.024 | 0.001 | 0.098 | 2.024 | Supported |
Moderation analysis.
PI, Purchase Intention; IBC, Influencer-brand image congruence.
FIGURE 2
Discussion
This study was constructed to explore the potential mechanisms between loneliness, boredom and consumer shopping intention during COVID-19. Telepresence is a potential mediator of loneliness, boredom and shopping intention, while influencer-brand congruence is a potential moderator to explain the influence of loneliness on purchase intention. Loneliness is a factor in boredom for live commerce customers in particular. To put it another way, loneliness has an effect on boredom. Therefore, the study is consistent with the previous findings (Bu et al., 2020; Elran-Barak and Mozeikov, 2020; Killgore et al., 2020a; Ausín et al., 2021; Li et al., 2021). Consumers’ loneliness and boredom positively predicted purchase intention in live commerce. When consumers feel loneliness and boredom, they are motivated to shop through live commerce, consistent with previous research findings (Lidholm et al., 2017; Jiang et al., 2018; Lee and Zelman, 2019; Yang et al., 2021; Vinerean et al., 2022). Telepresence mediates consumer loneliness, boredom and purchase intention (Lim and Kim, 2017; Gao and Li, 2019; Ongsakul et al., 2020). Loneliness and boredom affect consumers’ willingness to shop through telepresence. When consumers are lonely, if telepresence increases, it makes them more likely to have purchase intention. Consumers have reduced their social behavior during the COVID-19 period for various reasons, so they need to compensate for the lack of interpersonal behavior through the Internet and other means. A high influencer-brand image congruence is more likely to make consumers willing to purchase intent, consistent with previous research findings (Ruiz-Equihua et al., 2020; Kim and Kim, 2021; Pop et al., 2022). In other words, when consumers are bored, interesting live commerce can provide a way to eliminate boredom and make consumers feel interesting, which is inseparable from the influencer’s charm. The statistics show that influencer-brand congruence has a moderating effect on the relationship between boredom and purchase intention. However, influencer-brand image congruence did not act as a moderator between loneliness and purchase intention, possibly since, during the pandemic, consumers sought other social outlets to alleviate their loneliness when they felt lonely.
Implications
When it comes to customers’ purchase intention, previous research has neglected to take into account COVID-19’s results on emotions of loneliness, boredom, telepresence, and influencer-brand congruence. The findings of this study provide important insights for live commerce platforms and merchants. First, given the importance of consumer loneliness and boredom in purchase intention during the COVID-19 period, live commerce platforms and anchors should develop new features that reduce consumer loneliness and boredom to promote consumers’ purchase intention. Second, current research has found that consumers’ telepresence mediates feelings of loneliness, boredom and purchase intention, so live commerce platforms need to improve picture and sound quality to ensure consumers’ telepresence. In addition, influencer-brand image congruence can strengthen the influence of boredom on purchase intention. Especially, retailers using live commerce should focus on enhancing their brand image in order to boost the likelihood that customers will make a purchase during the COVID-19 period. Therefore, when consumers are bored, merchants in live commerce should choose products with high influencer-brand image congruence to sell and promote the sales of products.
Conclusion
This research sheds light on the psychological underpinnings of consumer purchasing behavior during the COVID-19 period and sheds light on the elements that influenced consumers’ buying intentions. If we want to build the live commerce business, we need to understand the psychology of consumers. This study constructed a moderated mediation model of the relationship between loneliness, boredom, telepresence, influencer-brand congruence and purchase intention during the COVID-19 pandemic and verified the mechanism of loneliness and boredom on the customer purchase intention during the COVID-19 pandemic through empirical methods. Research in the subject of live commerce is enriched by this study, which gives a novel viewpoint on the investigation of customer purchase intention.
Although this study can provide some insight into the factors influencing consumers’ purchase intention, this study has some limitations. First, all data in the study were filled in by consumers themselves, which may lead to bias in consumers’ recall. Second, COVID-19 is still very severe in some areas of China, but the outbreak is under control in other places, which may affect the data’s accuracy. Third, a cross-sectional study cannot determine a causal relationship between loneliness, boredom and purchase intention. This study only examined the regulatory impact of influencer-brand congruence, but it may also be utilized as an antecedent variable to affect purchase intention. Thus future research can further deepen and expand on this. Using a longitudinal survey to evaluate the influence of additional characteristics such as resilience on consumer purchase intention is recommended in future research.
Publisher’s Note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Statements
Data availability statement
The original contributions presented in this study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.
Ethics statement
The studies involving human participants were reviewed and approved by the Academic Research Ethics Committee of Linyi University. The patients/participants provided their written informed consent to participate in this study.
Author contributions
All authors listed have made a substantial, direct, and intellectual contribution to the work, and approved it for publication.
Funding
This work was supported by the Shandong Provincial Social Science Planning Research Project, “Research on the negative emotion and guidance mechanism in short video communication.” The project funding number was 21DXWJ01; 2021–2023.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
References
1
AhmedM. Z.AhmedO.AibaoZ.HanbinS.SiyuL.AhmadA. (2020). Epidemic of COVID-19 in China and associated psychological problems.Asian J. Psychiatr.51102092. 10.1016/j.ajp.2020.102092
2
AkbarW. (2019). The Effect of Consumers’ Self-Congruence with Brand Endorsers on Consumer Responses.dissertation/master’s thesis, Montreal: Concordia University.
3
AlgharabatR. S. (2018). The role of telepresence and user engagement in co-creation value and purchase intention: online retail context.J. Internet Commerce171–25. 10.1080/15332861.2017.1422667
4
AndronieM.LăzăroiuG.ŞtefănescuR.IonescuL.CocoşatuM. (2021). Neuromanagement decision-making and cognitive algorithmic processes in the technological adoption of mobile commerce apps.Oeconomia Copernicana121033–1062. 10.24136/oc.2021.034
5
AroraN.PrasharS.TataS. V.ParsadC. (2021). Measuring personality congruency effects on consumer brand intentions in celebrity-endorsed brands.J. Consum. Mark.38251–261. 10.1108/JCM-02-2020-3634
6
AusínB.González-SanguinoC.CastellanosM. ÁMuñozM. (2021). Gender-related differences in the psychological impact of confinement as a consequence of COVID-19 in Spain.J. Gender Stud.3029–38. 10.1080/09589236.2020.1799768
7
BaeJ.KimS. J.KimK. H.KooD.-M. (2019). Affective value of game items: a mood management and selective exposure approach.Internet Res.29315–328. 10.1108/INTR-12-2017-0477
8
BellmanS.KempA.HaddadH.VaranD. (2014). The effectiveness of advergames compared to television commercials and interactive commercials featuring advergames.Comput. Hum. Behav.32276–283. 10.1016/j.chb.2013.12.013
9
BeuckelsE.HuddersL. (2016). An experimental study to investigate the impact of image interactivity on the perception of luxury in an online shopping context.J. Retail. Consum. Serv.33135–142. 10.1016/j.jretconser.2016.08.014
10
BeutelM. E.KleinE. M.BrahlerE.ReinerI.JungerC.MichalM.et al (2017). Loneliness in the general population: prevalence, determinants and relations to mental health.BMC Psychiatry17:97. 10.1186/s12888-017-1262-x
11
BozaciI. (2020). The effect of boredom proneness on smartphone addiction and impulse purchasing: a field study with young consumers in Turkey.J. Asian Finance Econ. Bus.7509–517. 10.13106/jafeb.2020.vol7.no7.509
12
BrennerM. H. (2020). Will there be an epidemic of corollary illnesses linked to a COVID-19-Related Recession?Am. J. Public Health110974–975. 10.2105/AJPH.2020.305724
13
BrooksS. K.WebsterR. K.SmithL. E.WoodlandL.WesselyS.GreenbergN.et al (2020). The psychological impact of quarantine and how to reduce it: rapid review of the evidence.Lancet395912–920. 10.1016/S0140-6736(20)30460-8
14
BuF.SteptoeA.FancourtD. (2020). Who is lonely in lockdown? Cross-cohort analyses of predictors of loneliness before and during the COVID-19 pandemic.Public Health18631–34. 10.1016/j.puhe.2020.06.036
15
CasalóL. V.FlaviánC.Ibáñez-SánchezS. (2020). Influencers on instagram: antecedents and consequences of opinion leadership.J. Bus. Res.117510–519. 10.1016/j.jbusres.2018.07.005
16
ChaoM.ChenX.LiuT.YangH.HallB. J. (2020). Psychological distress and state boredom during the COVID-19 outbreak in China: the role of meaning in life and media use.Eur. J. Psychotraumatol.11:1769379. 10.1080/20008198.2020.1769379
17
ChenI.-S. (2020). Turning home boredom during the outbreak of COVID-19 into thriving at home and career self-management: the role of online leisure crafting.Int. J. Contemp. Hosp. Manag.323645–3663. 10.1108/IJCHM-06-2020-0580
18
Chory-AssadR. M.YanenA. (2005). Hopelessness and loneliness as predictors of older adults’ involvement with favorite television performers.J. Broadcast. Electron. Media49182–201. 10.1207/s15506878jobem4902_3
19
CowanK.KetronS. (2019). A dual model of product involvement for effective virtual reality: the roles of imagination, co-creation, telepresence, and interactivity.J. Bus. Res.100483–492. 10.1016/j.jbusres.2018.10.063
20
CoyleJ. R.ThorsonE. (2001). The effects of progressive levels of interactivity and vividness in web marketing sites.J. Advert.3065–77. 10.1080/00913367.2001.10673646
21
De VeirmanM.CaubergheV.HuddersL. (2017). Marketing through Instagram influencers: the impact of number of followers and product divergence on brand attitude.Int. J. Advert.36798–828. 10.1080/02650487.2017.1348035
22
DerrickJ. L.GabrielS.HugenbergK. (2009). Social surrogacy: how favored television programs provide the experience of belonging.J. Exp. Soc. Psychol.45352–362. 10.1016/j.jesp.2008.12.003
23
DeskaJ. C.HingstonS. T.DelVecchioD.StenstromE. P.WalkerR. J.HugenbergK. (2022). The face of the brand: spokesperson facial width-to-height ratio predicts brand personality judgments. Psychol. Mark.1–17. 10.1002/mar.21666[Epub ahead of print].
24
El HedhliK.ZourrigH.ChebatJ.-C. (2016). Shopping well-being: Is it just a matter of pleasure or doing the task? the role of shopper’s gender and self-congruity.J. Retail. Consum. Serv.311–13. 10.3389/phrs.2021.1603960
25
ElhaiJ. D.VasquezJ. K.LustgartenS. D.LevineJ. C.HallB. J. (2018). Proneness to boredom mediates relationships between problematic smartphone use with depression and anxiety severity.Soc. Sci. Comput. Rev.36707–720. 10.1177/0894439317741087
26
Elran-BarakR.MozeikovM. (2020). One month into the reinforcement of social distancing due to the COVID-19 outbreak: subjective health, health behaviors, and loneliness among people with chronic medical conditions.Int. J. Environ. Res. Public Health17:5403. 10.3390/ijerph17155403
27
EscalasJ. E.BettmanJ. R. (2005). Self-construal, reference groups, and brand meaning.J. Consum. Res.32378–389. 10.1086/497549
28
FaiolaA.NewlonC.PfaffM.SmyslovaO. (2013). Correlating the effects of flow and telepresence in virtual worlds: enhancing our understanding of user behavior in game-based learning.Comput. Hum. Behav.291113–1121. 10.1016/j.chb.2012.10.003
29
FritchieL. L.JohnsonK. K. (2003). Personal selling approaches used in television shopping.J. Fashion Mark. Manag. Int. J.7249–258. 10.1108/13612020310484807
30
GaoW.LiX. (2019). Building presence in an online shopping website: the role of website quality.Behav. Inf. Technol.3828–41. 10.1080/0144929X.2018.1509127
31
GongJ.SaidF.TingH.FirdausA.AksarI. A.XuJ. (2022). Do privacy stress and brand trust still matter? implications on continuous online purchasing intention in China.Curr. Psychol.10.1007/s12144-022-02857-x[Epub ahead of print].
32
GudelunasD. (2002). QVC: television retail & ritual.J. Am. Cult.25105-11810.1111/1542-734X.00017
33
Haobin YeB.FongL. H. N.LuoJ. M. (2021). Parasocial interaction on tourism companies’ social media sites: antecedents and consequences.Curr. Issues Tour.241093–1108. 10.1080/13683500.2020.1764915
34
HoffnerC. A.LeeS. (2015). Mobile phone use, emotion regulation, and well-being.Cyberpsychol. Behav. Soc. Netw.18411–416. 10.1089/cyber.2014.0487
35
HollenbaughE. E.FerrisA. L. (2014). Facebook self-disclosure: examining the role of traits, social cohesion, and motives.Comput. Hum. Behav.3050–58. 10.1016/j.chb.2013.07.055
36
HopkinsC. D.RaymondM. A.MitraA. (2004). Consumer responses to perceived telepresence in the online advertising environment: the moderating role of involvement.Mark. Theory4137–162. 10.1177/1470593104044090
37
HyunM. Y.O’KeefeR. M. (2012). Virtual destination image: testing a telepresence model.J. Bus. Res.6529–35. 10.1016/j.jbusres.2011.07.011
38
JiangQ.LiY.ShypenkaV. (2018). Loneliness, individualism, and smartphone addiction among international students in China.Cyberpsychol. Behav. Soc. Netw.21711–718. 10.1089/cyber.2018.0115
39
JinS. V.RyuE.MuqaddamA. (2018). Dieting 2.0!: moderating effects of Instagrammers’ body image and Instafame on other Instagrammers’ dieting intention.Comput. Hum. Behav.87224–237. 10.1016/j.chb.2018.06.001
40
Kardefelt-WintherD. (2014). A conceptual and methodological critique of internet addiction research: towards a model of compensatory internet use.Comput. Hum. Behav.31351–354. 10.1016/j.chb.2013.10.059
41
KempA.Randon, McDougalE.SyrdalH. (2019). The matchmaking activity: an experiential learning exercise on influencer marketing for the digital marketing classroom.J. Mark. Educ.41141–153. 10.1177/0273475318803415
42
KillgoreW. D. S.CloonanS. A.TaylorE. C.DaileyN. S. (2020a). Loneliness: a signature mental health concern in the era of COVID-19.Psychiatry Res.290:113117. 10.1016/j.psychres.2020.113117
43
KillgoreW. D. S.CloonanS. A.TaylorE. C.LucasD. A.DaileyN. S. (2020b). Loneliness during the first half-year of COVID-19 Lockdowns.Psychiatry Res.294:113551. 10.1016/j.psychres.2020.113551
44
KimD. Y.KimH.-Y. (2021). Trust me, trust me not: a nuanced view of influencer marketing on social media.J. Bus. Res.134223–232. 10.1016/j.jbusres.2021.05.024
45
KimT.BioccaF. (1997). Telepresence via television: two dimensions of telepresence may have different connections to memory and persuasion.J. Comput. Mediated Commun.3:JCMC325. 10.1111/j.1083-6101.1997.tb00073.x
46
KliestikT.KovalovaE.LăzăroiuG. (2022). Cognitive decision-making algorithms in data-driven retail intelligence: consumer sentiments, choices, and shopping behaviors.J. Self Governance Manag. Econ.1030–42. 10.22381/jsme1012022
47
LatherJ.Moyer-GuseE. (2011). How do we react when our favorite characters are taken away? an examination of a temporary parasocial breakup.Mass Commun. Soc.14196–215. 10.1080/15205431003668603
48
LeeC. J. B.LamJ. M.NgS. K.OoiS. Y.TaiY. S. (2019). The Impact of Branding Towards Cosmetics Products: a Comparison Study Between Generation Y and Generation Z. UTAR. Avaliable at: http://eprints.utar.edu.my/3466/(accessed April 10, 2022).
49
LeeF. K.ZelmanD. C. (2019). Boredom proneness as a predictor of depression, anxiety and stress: the moderating effects of dispositional mindfulness.Pers. Individ. Differ.14668–75. 10.1016/j.paid.2019.04.001
50
LiH.DaughertyT.BioccaF. (2002). Impact of 3-D advertising on product knowledge, brand attitude, and purchase intention: the mediating role of presence.J. Advert.3143–57. 10.1080/00913367.2002.10673675
51
LiL. Z.WangS. (2020). Prevalence and predictors of general psychiatric disorders and loneliness during COVID-19 in the United Kingdom.Psychiatry Res.291:113267. 10.1016/j.psychres.2020.113267
52
LiX.FengX.XiaoW.ZhouH. (2021). Loneliness and mobile phone addiction among Chinese college students: the mediating roles of boredom proneness and self-control.Psychol. Res. Behav. Manag.14:687. 10.2147/PRBM.S315879
53
LiY.PengY. (2021). Influencer marketing: purchase intention and its antecedents.Mark. Intell. Plan.39960–978. 10.3389/fpsyg.2022.853168
54
LidholmS. H.RadonA.SundströmM.BalkowJ. (2017). “Understanding on-line fashion buying behavior on impulse: feelings nothing more than feelings,” in Advanced Fashion Technology and Operations Management, ed.AlessandraV. (Pennsylvania: IGI Global).
55
LimC. M.KimY. K. (2011). Older consumers’ TV home shopping: loneliness, parasocial interaction, and perceived convenience.Psychol. Mark.28763–780.
56
LimC. M.KimY.-K. (2017). Older consumers’ TV shopping: emotions and satisfaction.Int. J. Retail Distrib. Manag.45292–307.
57
LiuX.YuanY.HeJ.LiZ. (2022). Framing the travel livestreaming in China: a new star rising under the COVID-19.Curr. Issues Tour.251–20.
58
LouC.YuanS. (2019). Influencer marketing: how message value and credibility affect consumer trust of branded content on social media.J. Interact. Advert.1958–73.
59
MaR.WangW. (2021). Smile or pity? examine the impact of emoticon valence on customer satisfaction and purchase intention.J. Bus. Res.134443–456.
60
MandelN.RuckerD. D.LevavJ.GalinskyA. D. (2017). The compensatory consumer behavior model: how self-discrepancies drive consumer behavior.J. Consum. Psychol.27133–146.
61
MedaN.PardiniS.SlongoI.BodiniL.ZordanM. A.RigobelloP.et al (2021). Students’ mental health problems before, during, and after COVID-19 lockdown in Italy.J. Psychiatric Res.13469–77. 10.1016/j.jpsychires.2020.12.045
62
MikulasW. L.VodanovichS. J. (1993). The essence of boredom.Psychol. Record433–12.
63
MinneboJ.EggermontS.VandenboschL. (2014). Neuroticism, extraversion, perceived social support, and escape television viewing as determinants of psychological distress in crime victims.J. Aggress. Maltreat. Trauma23249–267.
64
MollenA.WilsonH. (2010). Engagement, telepresence and interactivity in online consumer experience: reconciling scholastic and managerial perspectives.J. Bus. Res.63919–925.
65
MorenoC.WykesT.GalderisiS.NordentoftM.CrossleyN.JonesN.et al (2020). How mental health care should change as a consequence of the COVID-19 pandemic.Lancet Psychiatry7813–824. 10.1016/S2215-0366(20)30307-2
66
NovakT. P.HoffmanD. L.YungY.-F. (2000). Measuring the customer experience in online environments: a structural modeling approach.Mark. Sci.1922–42. 10.1186/s13054-016-1208-6
67
OngsakulV.AliF.WuC.DuanY.CobanogluC.RyuK. (2020). Hotel website quality, performance, telepresence and behavioral intentions.Tour. Rev.76681–700.
68
ParkS.KimI.LeeS. W.YooJ.JeongB.ChaM. (2015). “Manifestation of depression and loneliness on social networks: a case study of young adults on Facebook,” in Proceedings of the 18th ACM Conference On Computer Supported Cooperative Work & Social Computing.New York, NY: ACM.
69
PaulJ.BhakarS. (2018). Does celebrity image congruence influences brand attitude and purchase intention?J. Promot. Manag.24153–177.
70
Pelegrín-BorondoJ.Olarte-PascualC.OruezabalaG. (2020). Wine tourism and purchase intention: a measure of emotions according to the PANAS scale.J. Wine Res.31101–123.
71
PopR.-A.SăplăcanZ.DabijaD.-C.AltM.-A. (2022). The impact of social media influencers on travel decisions: the role of trust in consumer decision journey.Curr. Issues Tour.25823–843.
72
PreacherK.HayesA. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models.Behav. Res. Methods40879–891.
73
PriyadarshiniI.MohantyP.KumarR.SonL. H.ChauH. T. M.NhuV.-H.et al (2020). Analysis of outbreak and global impacts of the COVID-19.Healthcare8:148.
74
RajendranR. P.ArunC. J. (2020). The effect of loneliness and nostalgic advertising on mobile shopping intention: a conceptual framework.Int. J. Bus. Econ.542–55.
75
RokachA. (2004). Loneliness then and now: reflections on social and emotional alienation in everyday life.Curr. Psychol.2324–40.
76
Ruiz-EquihuaD.RomeroJ.CasalóL. V. (2020). Better the devil you know? the moderating role of brand familiarity and indulgence vs. restraint cultural dimension on eWOM influence in the hospitality industry.J. Hosp. Mark. Manag.29310–328.
77
RussellD.PeplauL. A.FergusonM. L. (1978). Developing a measure of loneliness.J. Pers. Assess.42290–294. 10.1207/s15327752jpa4203_11
78
RussellD. W. (1996). UCLA loneliness scale (Version 3): reliability, validity, and factor structure.J. Pers. Assess.6620–40. 10.1207/s15327752jpa6601_2
79
ShanY.ChenK.-J.LinJ.-S. (2020). When social media influencers endorse brands: the effects of self-influencer congruence, parasocial identification, and perceived endorser motive.Int. J. Advert.39590–610.
80
SkupskiI. M. (2019). Making the Commercial Non-Commercial: Traditional Ad Effects on TV Billboards.Baton Rouge: Louisiana State University.
81
SmithD.LeonisT.AnandavalliS. (2021). Belonging and loneliness in cyberspace: impacts of social media on adolescents’ well-being.Aust. J. Psychol.7312–23.
82
SnyderD. G.NewmanK. P. (2019). Reducing consumer loneliness through brand communities.J. Consum. Mark.36337–347.
83
SundströmM.Hjelm-LidholmS.RadonA. (2019). Clicking the boredom away–exploring impulse fashion buying behavior online.J. Retail. Consum. Serv.47150–156.
84
TianL.-M.ChenG.-H.WangS.-Q.LiuH.-J.ZhangW.-X. (2012). Effects of parental support and friendship support on loneliness and depression during early and middle adolescence.Acta Psychol. Sin.44944–956.
85
van TilburgW. A.IgouE. R. (2017). Boredom begs to differ: differentiation from other negative emotions.Emotion17309–322. 10.1037/emo0000233
86
VinereanS.BudacC.BaltadorL. A.DabijaD.-C. (2022). Assessing the effects of the COVID-19 pandemic on M-Commerce adoption: an adapted UTAUT2 approach.Electronics11:1269. 10.3390/electronics11081269
87
WangL.WangZ.WangX.ZhaoY. (2021). Assessing word-of-mouth reputation of influencers on B2C live streaming platforms: the role of the characteristics of information source.Asia Pacific J. Mark. Logistics.Online ahead of print.10.1108/APJML-03-2021-0197
88
WatsonR.PopescuG. H. (2021). Will the COVID-19 pandemic lead to long-term consumer perceptions, behavioral intentions, and acquisition decisions?Econ. Manag. Financial Markets1670–83. 10.22381/emfm16420215
89
XiangY. T.JinY.CheungT. (2020). Joint international collaboration to combat mental health challenges during the coronavirus disease 2019 Pandemic.JAMA Psychiatry77989–990. 10.1001/jamapsychiatry.2020.1057
90
YangS.HuangL.ZhangY.ZhangP.ZhaoY. C. (2021). Unraveling the links between active and passive social media usage and seniors’ loneliness: a field study in aging care communities.Internet Res.312167–2189. 10.1108/INTR-08-2020-0435
91
YeS.LeiS. I.ShenH.XiaoH. (2020). Social presence, telepresence and customers’ intention to purchase online peer-to-peer accommodation: a mediating model.J. Hosp. Tour. Manag.42119–129. 10.1016/j.jhtm.2019.11.008
92
YuI. H.KimH. (2020). The effect of influencer factors in personal media contents on purchase intention.J. Korea Contents Assoc.2045–59.
93
ZhouY.ZhengD.ChenX.YuY. (2021). A study on the influence of the facial expressions of models on consumer purchase intention in advertisements for poverty alleviation products.Pers. Individ. Differ.172:110578. 10.1016/j.paid.2020.110578
Summary
Keywords
loneliness, boredom, telepresence, influencer-brand image congruence, purchase intention, live commerce
Citation
Peng C, Liu Z, Lee J-Y, Liu S and Wen F (2022) The Impact of Consumers’ Loneliness and Boredom on Purchase Intention in Live Commerce During COVID-19: Telepresence as a Mediator. Front. Psychol. 13:919928. doi: 10.3389/fpsyg.2022.919928
Received
14 April 2022
Accepted
06 June 2022
Published
23 June 2022
Volume
13 - 2022
Edited by
Hiroshi Kadotani, Shiga University of Medical Science, Japan
Reviewed by
Gianpaolo Maggi, University of Campania Luigi Vanvitelli, Italy; Aurel Pera, University of Craiova, Romania; Maria Kovacova, University of Žilina, Slovakia
Updates
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© 2022 Peng, Liu, Lee, Liu and Wen.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Fang Wen, w1311311@naver.com
This article was submitted to Personality and Social Psychology, a section of the journal Frontiers in Psychology
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