Source credibility theory refers “a source is perceived as possessing expertise relevant to the communication topic and can be trusted to give an objective opinion on the subject” (Ohanian, 1990). Previous research has widely accepted that source credibility consists of three dimensions, namely trustworthiness, expertise, and attractiveness (Ohanian, 1990). However, as the realities of consumption emerge, perhaps some other new elements are relevant to the components of source credibility. Ismagilova et al. (2020); Halder et al. (2021) suggested that celebrity credibility needs multiple dimensions, rather than just trustworthiness, expertise, and attractiveness. In live streaming consumption, Meng et al. (2020) introduced that interaction, as one of the online celebrity factors of streamers' credibility, has a positive impact on purchase intention. In the food O2O consumption context, Kang and Namkung (2019) considered reputation as one of the source credibilities of the O2O platform in customers' evaluation. Besides, according to signaling theory, the sender can manipulate the information to influence decisions in the exchange relationship and to indicate quality and trustworthiness (Wagner et al., 2011; Rokonuzzaman et al., 2021). Rokonuzzaman et al. (2021) studied how retailers' reopening policies can reduce perceived risk and improve store image and retain patronage intention. In this study, based on signaling theory, we propose that the marketing stimuli (guarantee, authenticity, and money-saving) provided in the ELS can serve as the signal for consumers to indicate the credibility of the ELS. In the online shopping context, studies have classified internal and external stimuli affecting online consumption (Lim and Yazdanifard, 2015). Studies have classified individual characteristics as internal factors (Chan et al., 2017) and classified marketing stimuli as one of the external factors (Kimiagari and Malafe, 2021). In the ELS, unlike other streamers, entrepreneur streamers can not only showcase their products but also decide the marketing stimuli in the live streaming. Based on the philosophy behind the internal and external stimuli of online shopping (Kimiagari and Malafe, 2021), we propose that the characteristics of entrepreneur streamers (reputation, expertise, and interactivity) as internal factors and the marketing stimuli (guarantee, authenticity, and money-saving) provided in the ELS as external factors of the ELS's credibility.

Previous literature on live stream E-commerce mainly focused on online celebrities (Liu et al., 2020; Park and Lin, 2020) and professional streamers (Addo et al., 2021; Chen et al., 2021). Studies on online celebrities have mainly focused on (1) trustworthiness, attractiveness, and live streaming content (Wanghong vs. self)-product fit (Park and Lin, 2020), (2) online celebrities' image and product consistency (Liu et al., 2020), (3) celebrity characteristics (i.e., credibility, professionalism, skill, interaction, and attraction) (Meng et al., 2020) on purchase intention. Studies on professional streamers have mainly dedicated to (1) user stickiness affected by technical factors (synchrony and alternative expressions) and social factors (interaction and identification); (2) purchase intention affected by social capital and negative event (Xu et al., 2022); consumer engagement (Addo et al., 2021), interpersonal factors (perceived expertise, perceived similarity, perceived familiarity and perceived likeability) (Chen et al., 2021), crosss-border E-commerce live streaming features (Guo et al., 2021); social status (Hou et al., 2020), IT affordability (Sun et al., 2019); (3) intention to watch influenced by interactivity and top streamers' personal traits (Guo et al., 2022); sense of community, interactivity, and emotional support (Chen and Liao, 2022); (4) tipping and gift-giving intention affected by audience (Lu et al., 2021), live streamers' personal traits (trustworthiness, expertise, attractiveness) and live scene characteristics (telepresence, instant feedback, interactivity, entertainment) (Li and Peng, 2021); (5) consumer engagement influenced by interactivity (Kang et al., 2021), trust (trust in community members, trust in broadcasters, trust in products) (Guo et al., 2021), streamers' emotion (Lin et al., 2021), perceived values (Wongkitrungrueng and Assarut, 2020), financial bonds, and social bonds structural ties (Hu and Chaudhry, 2020), and live interaction (Xue et al., 2020). A recent study on celebrity streamers has investigated that interactivity has a positive effect on purchase intention through social presence and flow experience. Related studies are given in Table 1.

The existing literature related to live streaming is increasingly focused on consumer engagement. Consumer engagement is an important factor in predicting and explaining consumer repurchase intention and preference for brands (Xue et al., 2020). With the emphasis on the importance of engagement in social commerce, engagement has transpired in live E-commerce recently (Guo et al., 2021; Kang et al., 2021). In the live streaming context, according to Guo et al. (2021), we define consumer engagement as consumers' behavioral engagement toward entrepreneur streamers, including purchase behavior and non-transaction behavior (e.g., sharing, like, and giving tips). Live streaming literature on consumer engagement mostly focused on live streaming activities hosted by professional streamers from third-party companies (e.g., MCN) and overlooked the live streaming activities hosed by the enterprises themselves. There are two types of live streaming activities hosted by the enterprises themselves: ELS and employees' live streaming. In this study, we aim to figure out the factors behind the ELS-driven consumer engagement, which is significantly higher than employees' live streaming.

Guarantee means that consumers have higher services/products evaluation (Ostrom and Iacobucci, 2016). Desmet (2014) noted that retailers can normally offer two types of guarantee: the manufacturer's quality guarantee required by law and the money-back guarantee. The former is provided by suppliers (repair, exchange, and refund due to the quality issue in a certain time) while the latter provides consumers a chance to return products purchased without any condition within a certain period of time. Professional streamers and online celebrities are the third parties to promote products, while entrepreneur streamers represent the manufacturers/brand owners, and their products are legally obligated to provide the guarantee from manufacturers. Once consumers have product quality issues in live broadcast, they need to seek support from product suppliers or manufacturers. Rokonuzzaman et al. (2021) illustrated that retailers' reopening policy of retailers enhances store image and retains patronage intention via decreasing perceived risk. Moreover, some entrepreneur streamers provide a money-back guarantee. For example, Jianzhang Liang, founder of Ctrip, promised that consumers can get a refund if they want to return the products (e.g., hotel booking and sightseeing tickets) in a year. The guarantee provided by entrepreneur streamers gives consumers faith in their products and the whole live broadcast activity. Thus, we propose that:

Authenticity refers to “a multidimensional structure variously consisting of claims that an entity is consistent in its internal values and external behaviors; it conforms to relevant social norms, and the person, time, or place it claims to be” (Lehman et al., 2019). In the ELS, we defined authenticity as that consumers' perception of the products, information, and activity provided by the live streaming activity conforms to the information claimed by the entrepreneur streamers. Eggers et al. (2013) noted that brand authenticity is important for gaining trust. Moreover, Matthews et al. (2020) found that the frontline service employees' authenticity can enhance consumers' perceived trust, which in turn affects their purchase intention. Although live streaming activities have grown rapidly in recent years, some live streamers sell fake products for chasing high profits without market supervision. However, entrepreneur streamers who represent their organizations and brands will not deceive consumers in the live streaming activities that they can ensure the authenticity of the products, which will allow them to gain more trust from consumers. Thus, we propose that:

Chandon et al. (2000) noted that due to the lower price, live streaming activities bring the impression of money-saving to consumers. Previous studies have examined that saving money is one of the vital factors for consumers to engage in their relationships and behaviors (Park et al., 2012; Hu and Chaudhry, 2020). In live streaming, discounts, gifts, and special prices can be offered by streamers to help customers save money (Hallanan, 2019; Hu and Chaudhry, 2020). However, in reality, consumers sometimes complain that they receive a false price discount or higher price compared with other marketing activities. Different from other streamers, entrepreneur streamers have the power to offer the “ex-factory price”—the lowest product price for consumers. It can make consumers save the largest amount of money, which is expected to greatly improve consumers' trust in live streaming activity. Thus, we propose that:

Schindler et al. (2013) defined admiration as “respect for someone or something considered praiseworthy or excellent.” Admiration has an impact on consumer emotional and behavioral consequences (Aaker et al., 2012). In terms of admiration for something, existing research has examined the effect of brand admiration on purchase intention (Trivedi and Sama, 2020; Gupta et al., 2021). Gupta et al. (2021) examined the mediating role of brand admiration in the influence of CSR communication via social media on consumers' purchase intention. Trivedi and Sama (2020) have pointed out that preference for a brand has a positive effect on online purchase intentions. In terms of admiration for someone, some scholars have examined the positive effect of admiration for employees on engagement (He et al., 2019) and the positive effect of consumer admiration for entrepreneurs on brand attitude (Liu et al., 2018). In the ELS, we assume that consumer admiration for entrepreneur streamers has a positive influence on consumer engagement.

The psychological distance can be defined as “the extent to which individuals mentally perceive the entrepreneur streamers as being distant from themselves at that moment” (Liberman and Trope, 2008). Xue et al. (2020) suggested that psychological distance negatively affects social commerce engagement in live streaming. Hernández-Ortega (2018) noted that shortening the social–psychological distance results in increased purchase intention. Additionally, Edwards et al. (2009) illustrated that the reduction of psychological distance will reduce individuals' sense of danger and crisis, barriers, and self-defense, and will provide real, genuine, more inclusive, and trusting feelings (Edwards et al., 2009). Thus, we propose that:

Trust has a positive effect on consumer engagement in live streaming (Wongkitrungrueng and Assarut, 2020; Guo et al., 2021). Wongkitrungrueng and Assarut (2020) examined that trust in sellers and products has a positive relationship with consumer engagement in live broadcasts. Extending the studies of Wongkitrungrueng and Assarut (2020), and Guo et al. (2021) have examined that trust in community members, trust in broadcasters, and trust in products have a positive effect on consumer engagement through quickly established social bonds. However, due to the negative news that some live streamers provide false information about products/services, consumers still have concerns about the credibility of live streaming activity (iResearch, 2020). In online/offline commerce, consumers trust the following several entities: the company, the agent (seller, salesperson, and website), the product, and the market/channel (Komiak and Benbasat, 2004). In the ELS, based on the ideas of Komiak and Benbasat (2004), we defined trust as trust toward the whole live streaming activity, including products, entrepreneur streamer, and information provided in live streaming. Friedrich et al. (2019) examined that trust positively affects website stickiness. We assume that consumers who have trust in live streaming activity will actively engage in the ELS.

We first conducted a quasi-experiment to examine the effect of entrepreneur live streaming on consumer engagement. The quasi-experimental approach was a good approximation of a randomized experiment, especially when a randomized experiment is not available. We collected our data from Tik Tok, which is one of the biggest live streaming and short video platforms in China. According to the Annual Data Report of 2020 (Tik Tok, 2021), the amount of daily active users of Tik Tok was more than 6 billion at the end of August 2020. The data contain details of the live streaming activity anchored by the entrepreneur streamers on 1st January and the live broadcast activity anchored by the employee streamers on 5th January from the Tik Tok platform. Each live streaming activity was operated from 20:00 to 22:00. For the consumer engagement, we collected the number of viewers in the peak, the total amount of viewers, the number of viewers' likes, the total amount of rewards, and the increased number of fans every 2 min.

We used an independent sample method, t-test to examine differences in consumer engagement between the entrepreneur streamers and the employee streamers. The results showed that consumer engagement driven by the entrepreneur streamers is higher than the employee streamers. In detail, the peak amount of viewers in the entrepreneur live streaming [M_EPS = 505539.15] is significantly higher than that of the employee live streaming [M_EMS = 7144.91, t₍₅₃₎ = 29.198, p < 0.001]; the total amount of viewers in the entrepreneur live streaming (M_EPS = 12472506.83) is significantly higher than that of the employee live streaming [M_EMS = 1460674.81, t₍₅₃₎ = 12.344, p < 0.001]; the number of viewer's likes in the entrepreneur live streaming [M_EPS = 17267900.89] is significantly higher than that of the employee live streaming [M_EMS = 325758.96, t₍₅₃₎ = 20.994, p < 0.001]; the total amount of tips in the entrepreneur live streaming (M_EPS = 1452402.54) is significantly higher than that of the employee live streaming [M_EMS = 13183.83, t₍₅₃₎ = −32.056, p < 0.001]; the increased number of fans in the entrepreneur live streaming (M_EPS = 302424.54) is significantly higher than that of the employee live streaming [M_EMS = 28068.87, t₍₅₃₎ = 11.871, p < 0.001]. Descriptive statistics are shown in Table 2.

Study 1 shows that ELS has a more significant impact on consumer engagement in corporate live streaming environments than employees' live streaming. The next study aims to uncover the success factors behind consumer engagement and the mechanisms in the ELS.

Since we collected data via questionnaire, common method bias (CMB) could be a potential problem. First, we used Harman's single-factor test to check the method variance in the data. The results show that 10 factors with eigenvalues >1.0 are formed. The largest factor accounted for 29.879%, below 50% of the variance of subjects indicating that CMB did not pose a threat in our study (Fornell and Bookstein, 1982). Second, we built a technique for fine-grained CMB testing using unmeasured latent methods (Podsakoff et al., 2003). The results show that the average variance explained by the substantive structure (0.568) is much higher than that explained by the common method factor (0.005), implying that CMB is not a serious problem in this research, as shown in Table 4.

We used factor analysis to verify the reliability and validity of the constructs. According to the results, Cronbach's α of all the constructs was between 0.712 and 0.838, higher than 0.7, indicating that the constructs had relatively good reliability. The composite reliability (CR) of each structure was >0.8, which indicates that the internal consistency of the constructs was relatively good. The minimum item loading is 0.707, larger than 0.7, so the internal consistency of the structure was good. The average variance extracted (AVE) of each construct was between 0.500 and 0.664, indicating that these constructs show relatively good convergent validity. The statistical analysis results are listed in Table 5.

We test discriminant validity by three methods (Sun et al., 2019): (1) we compared the relationship between the square root of the AVE of the variable and the correlation coefficients. It can be seen from the analysis results that the square root of the AVE of the variable is greater than the correlation coefficients, see Table 5. Therefore, the constructs also have relatively sound discriminant validity; (2) we utilized cross-loadings to confirm discriminant validity (George, 1998). The results show that all indicator loadings exceed the cross-loadings, verifying discriminant validity, see Table 6; (3) we employed the heterotrait-monotrait (HTMT) ratio to test for discriminant validity. The results show that HTMT values ranged from 0.426 to 0.842, and were lower than 0.85, indicating that the discriminative validity was confirmed (Sun et al., 2019), see Table 7. By utilizing three methods to test discrimination validity, we find that this study satisfies the criteria of discriminant validity.

Figure 3 shows the results of the SmartPLS analysis that reputation (β = 0.216, p < 0.001), expertise (β = 0.203, p < 0.001), interactivity (β = 0.141, p < 0.01), guarantee (β = 0.111, p < 0.05), authenticity (β = 0.249, p < 0.001), money-saving (β = 0.112, p < 0.05) positively affect trust in activities, and trust in activities, positively affects consumer engagement (β = 0.383, p < 0.001); reputation (β = 0.407, p < 0.001), expertise (β = 0.162, p < 0.05) positively affect admiration, and admiration positively affect consumer engagement (β = 0.269, p < 0.001); interactivity (β = −0.474, p < 0.001) and expertise (β = −0.137, p < 0.05) negatively affect psychological distance, and psychological distance negatively affects consumer engagement (β = −0.215, p < 0.001). The R² for admiration, trust in activities, psychological distance, and consumer engagement is 0.242, 0.584, 0.300, and 0.491, respectively. Thus, H1a–b, H2a–c, H3a–b, H4, H5, H6, H7, H8, and H9 are all supported, as shown in Table 8.

H10a–b posits that admiration mediates the effect of (a) entrepreneur reputation, (b) expertise on consumer engagement; H11a–b posits that psychological distance mediates the effect of (a) expertise and (b) interactivity on consumer engagement; H12a–f posits that trust in activities mediates the effects of (a) reputation, (b) expertise, (c) interactivity, (d) guarantee, (e) authenticity, and (f) money-saving on consumer engagement. A bootstrapping procedure with 5,000 bootstrapped samples was employed to test the mediating effects. If 95% bootstrapped confidence intervals (CI), for the estimates of indirect effect that do not include zero, the mediation effect is statistically significant (Zhao et al., 2010). Table 9 reports the estimates of indirect pathways with their respective 95% CI. The results show that except for H11b and H12f, the indirect effect of H10a–b, H11a, and H12a–e are all significant. Thus, H10a–b, H11a, and H12a–e are supported.

This research first examined that consumer engagement (i.e., the peak number of viewers, the total amount of viewers, number of viewer's likes, the total amount of tips, and the increased number of fans) of the ELS is significantly higher than that of the employees' live streaming in the enterprise live streaming based on a quasi-experiment. Furthermore, we confirmed the effect of success factors on consumer engagement in the ELS through the online survey. Our findings confirm the effects of internal factors (i.e., reputation, expertise, and interactivity) and external factors (i.e., guarantee, authenticity, and money-saving) of the ELS's credibility on consumer engagement and the mechanisms underlying those effects.

First, we found that factors of ELS's credibility positively affect trust in activities. In terms of internal factors: (1) reputation positively affects trust in activities, which is consistent with the study of Kim and Peterson (2017) illustrated that reputation is an important antecedent of trust. The result reveals that when consumers engage the ELS, they prefer to engage entrepreneur streamers with reputation. (2) Expertise positively affects trust in activities, which is consistent with the study of Guo et al. (2022) suggested that expertise is one of the top streamers' characteristics that can influence consumer behavior. Entrepreneur streamers are the experts on their products that they have rich knowledge about the products. Mingzhu Dong, the chairwoman of the GREE, said that compared with other live streamers, no one is more experiential than her in the air conditioner industry. (3) Interactivity positively affects trust in activities, which is consistent with the study of Arghashi and Yuksel (2022) suggested interactivity has a positive effect on consumer trust. In terms of external factors: (1) guarantee positively affects trust in activities. The finding extends the previous study of Rokonuzzaman et al. (2021) and illustrates that the return policy of retailers can enhance store image and patronage intentions from offline context to live streaming context. In live streaming activity, consumers are worried about after-sales services, thus, the promise and guarantee provided by the entrepreneur streamers is an important prerequisite for consumer trust. (2) Authenticity positively affects trust in activities. In the live streaming activity, consumers worried about false products and misinformation. Authenticity can enhance consumer trust in activities, which is consistent with the study of Matthews et al. (2020). (3) Money-saving positively affects trust in activities. Entrepreneur streamers can offer “entrepreneur price,” the lowest price compared with other promotion channels, which can help gain consumers' trust in activities.

Second, we found the effects of reputation and expertise on admiration. In detail, reputation positively affects admiration, which is consistent with previous studies that the preference originates from an appreciation of excellent behavior and character (Haidt, 2003). Expertise positively affects admiration. This finding is consistent with a previous study that admiration is derived from skills and actions (Algoe and Haidt, 2009). Meanwhile, we found expertise and interactivity negatively affect psychological distance. Expertise negatively affects psychological distance because professional information can reduce information asymmetry (Dimoka et al., 2012). Interactivity negatively affects psychological distance, which is consistent with the study of Xue et al. (2020) for live streaming.

Third, we found the effect of admiration, psychological distance, and trust in activities on consumer engagement. (1) Admiration positively affects consumer engagement and mediates the effect of reputation and expertise on consumer engagement. This finding extends the previous study, showing that consumer admiration for entrepreneurs positively affects brand attitude (Liu et al., 2018). (2) Psychological distance negatively affects consumer engagement, which is consistent with the study of Xue et al. (2020). This point indicates that psychological distance harms social commerce engagement in live streaming. (3) Trust in activities positively affects consumer engagement. This finding is consistent with a previous study, which revealed that trust has a positive relationship with consumer engagement in live streaming (Wongkitrungrueng and Assarut, 2020).

Fourth, this study examined the mediation effect of admiration, psychological distance, and trust in activities on the relationship between the ELS' credibility and consumer engagement. (1) Admiration meditates the effect of reputation and expertise on consumer engagement. The findings show that watching entrepreneur streamers with reputation and skills in live streaming activity can lead to consumer admiration for the entrepreneur and in turn increases consumer engagement. (2) Psychological distance mediates the effect of interactivity on consumer engagement. The finding tells us that consumers feel closer when entrepreneur streamers interact with them and then increase consumer engagement. However, the mediation effect of psychological distance on the relationship between expertise and consumer engagement is not significant. The possible reason is that the psychological distance shortened by expertise came from the decreased information asymmetry (Dimoka et al., 2012), which cannot increase consumer engagement in the ELS. Furthermore, the gender distribution of the sample may be one reason. (3) Trust in activities mediates the effects of reputation, expertise, interactivity, guarantee, and authenticity on consumer engagement. Nevertheless, the effect of money-saving on consumer engagement is not mediated by trust in activities. The likely reason is that money-saving may directly affect consumer engagement.

The findings of this paper provide insights with theoretical and practical implications.

This study provides four implications from a theoretical perspective by investigating the impact of ELS credibility factors on consumer engagement and its underlying mechanisms.

First, we extend source credibility theory in the live streaming literature by providing the credibility of the ELS. Previous live streaming studies based on source credibility mainly were dedicated to the streamers' credibility (Liu et al., 2020; Meng et al., 2020; Park and Lin, 2020). The streamers are one of the important components in live streaming (Guo et al., 2022), but those studies failed to grasp the whole live streaming system. In this study, we extended the study of source credibility in live streaming by studies to examine the factors of ELS's credibility and the effects on consumer engagement based on source credibility theory and signaling theory.

Second, we provided a novel perspective to discuss the ELS-driven consumer engagement from the perspective of internal and external factors of the ELS's credibility. In live streaming, streamers, live streaming platforms, and consumers are important. Previous studies have examined the relationship among streamers, live streaming platforms, and consumers (Wongkitrungrueng and Assarut, 2020; Chen et al., 2021; Guo et al., 2021, 2022), which overlooked another important factor, marketing stimuli in the live streaming. In this study, we extended the live streaming literature by introducing marketing stimuli as external factors of the ELS's credibility.

Third, this study examined the mediating roles of admiration, psychological distance, and trust in activities on the relationship between the factors of the ELS's credibility and consumer engagement. Previous studies have suggested the effect of quickly established social ties and perceived value on consumer engagement (Wongkitrungrueng and Assarut, 2020; Guo et al., 2021). However, few studies have illustrated that admiration, psychological distance, and trust in activities are driven by the ELS's credibility in consumer engagement. This study enriched the live streaming literature on the antecedents of consumer engagement.

Fourth, this study employed a portfolio of methods such as a quasi-experiment and an online survey to confirm our findings. Previous studies on live streaming mainly only used an online survey to examine the effects of factors on purchase intention, consumer engagement, and viewing intention. This study utilized a quasi-experiment to confirm that the effect of the ELS is significantly higher than the employees' live streaming, which brings our study a solid foundation to examine the factors of the ELS's credibility on consumer engagement in the enterprise live streaming context. It is suggested that future studies can take advantage of this approach.

This study provides a deep understanding of the ELS and can offer actionable guidance to practitioners. Our findings can offer insights not only for the marketers in China where live streaming e-commerce is booming but also for the marketers outside China where live streaming e-commerce is emerging. We highlight the importance of internal factors (i.e., reputation, expertise, and interactivity) and external factors (i.e., guarantee, authenticity, and money-saving) of the ELS' credibility in promoting consumer engagement.

First, based on our findings on the effect of reputation, we suggest that entrepreneurs should pay attention to their reputation in the business field, especially in terms of competency and charisma. With the development of social media, marketing managers can share short clips in live streaming apps before the ELS to show entrepreneurial competence and charismatic reputation-related content. For instance, Mi's official account on Tik Tok provided several interviews of Jun Lei, founder of Xiaomi, for consumers before he participated in live streaming to share his achievement and display his charisma.

Second, based on our findings on the effect of interactivity, we suggest that entrepreneur streamers should pay attention to the interaction with the viewers. Normally, there are other live streamers to help entrepreneur streamers in the ELS, we suggest that other live broadcast streamers should give more time and encourage entrepreneur streamers to interact with consumers. Besides, we suggest that entrepreneur streamers can not only display the features of their product but also illustrate the inner concept of the products and share their entrepreneurial experience, because many consumers who admire the entrepreneur may want to learn about the entrepreneurial experience through the ELS.

Third, based on our findings on the effect of guarantee and authenticity, we suggest that entrepreneur streamers should emphasize the authenticity and guarantee policies of their products. Besides, entrepreneurs can show the manufacturing process of their products through live streaming, which will enhance consumers' trust and engagement. For example, Mingzhu Dong, Chairwoman of Gree, invited online consumers to visit her factories in live streaming activities. However, other types of live streamers cannot ensure the authenticity of the products and provide guarantees to consumers. For instance, 27,270 consumers purchased false bird's nests through a famous internet celebrity live streaming in November 2020. A couple of days later, the news reported that more than 20,000 consumers purchased the low-quality sweater in another famous online celebrity's live streaming activities.

Fourth, based on our findings on the effect of money-saving, it is suggested that entrepreneur streamers should bring various price incentive activities for consumers in the ELS. On the one hand, entrepreneurs can decide the prices of products so that they can give the “entrepreneur price,” which means the lowest price, in the ELS; on the other hand, they can provide some enjoyable promotion activities, such as the special price for certain products/services. For example, Jun Lei, founder of Xiaomi, sold 1,000 pieces of mouse pads for only 1 RMB, which attracted a huge number of consumers.

There are some limitations to this study, which also provide directions for future research. First, although this study has discussed the effect of reputation on consumer engagement, further moderators (e.g., power distance belief) may provide valuable insights for managerial decisions. For instance, power distance beliefs (Jain and Jain, 2018) may influence the effect of reputation on consumer engagement. Besides, some variables, such as interactivity, authenticity, admiration, and trust, are multi-dimensional. Future research can examine the effect of multi-dimensions of those variables on consumer engagement. Second, we meet difficulties in collecting samples. We collaborated with the professional data collection institution to collect valuable samples with the audience's viewing experience in the ELS. Third, this study investigated live streaming engagement through secondary data and questionnaires, future studies can use a field study to measure consumer engagement. Thus, the effects of other interesting factors affecting consumer engagement may be examined. According to Appendix A1 in Supplementary material, there are many industries in which entrepreneur live streaming has been applied. As the industry is very important and can affect consumer engagement. For instance, smart device companies, such as Xiaomi vs. real estate companies, e.g., Kaisa. Future studies can test factors behind consumer engagement from the perspective of an industry. Besides, as there are several live-streaming platforms, future research can compare the differences in consumer attitudes toward the ELS across live-streaming platforms.