Abstract
Along with the economic and technological development in Indonesia, one of the innovations is in the field of social media commerce and it has managed to attract the attention of Indonesian consumers. Different from other social media, TikTok offers a new feature, namely TikTok Live, participants can use this social media for their entertainment as well as a buying and selling platform. At the same time, live streaming also faces several factors where consumers are not yet sure about buying it. However, the marketing strategy has recently become a hot topic of discussion. Therefore, this empirical research aimed to investigate why Indonesian consumers buy on live streaming using perceived trust as a mediating variable, such as trust in the products and trust in the sellers. The factors used to analyse the influence on consumers' purchase intention include utilitarian value, hedonic value and social value. This study collected data in a questionnaire created in Google Forms and performed data analysis using SPSS 26 and SPSS Amos software, using structural equation models to analyse validation and theoretical hypotheses. The results of this analysis are expected to provide knowledge to social commerce providers, especially in the area of live streaming.
This study shows that perceived values such as utilitarian, hedonic and social values have a significant positive impact on purchase intention. Utilitarian value and social value both have a significant and positive influence on both consumer trust in the products and consumer trust in the platform, but not on hedonic value, where hedonic value only has a significant positive influence on trust in the platform, but an insignificant effect on trust in the product. Even though hedonic value has no influence on the product, sellers still need to provide a more pleasant atmosphere to attract the attention of users or consumers. And for further research, this study hopes to uncover additional elements that influence consumer behaviour on the TikTok live streaming platform.
Keywords: Indonesian consumers, Social commerce, Live streaming, Consumer perceived value, Consumer trust, Consumer buying intentions
1. Introduction
On 11 December, Chinese social media platform TikTok officially announced a strategic e-commerce partnership with Indonesia's GoTo Group. This means that two months after the ban was lifted, TikTok social e-commerce is back in the Indonesian market by taking a controlling stake in Tokopedia, a local Indonesian e-commerce platform. On the surface, it is TikTok that needs Indonesia as a market, but in fact Indonesia is already inextricably linked to social e-commerce [1].
In recent years, the number of people using social media for shopping in Indonesia has grown rapidly [2]. After the massive growth of the e-commerce sector during the COVID-19 pandemic, social commerce has become the next popular business phenomenon in the Indonesian market. Although this emerging shopping method is relatively small in Indonesia, it is expected to grow rapidly in the coming years, with a total goods value (GMV) of approximately US$22 billion by 2028 [3]. Currently, Indonesians spend an average of over 3 h a day on social media, and with the growing number of new influencers, social media will continue to play an important role in the shopping process for most Indonesian consumers. According to a recent social commerce survey, 40 % of Indonesian consumers frequently shop on social media [4].
TikTok has gained popularity in Indonesia since its launch in September 2017. It has become a goal for TikTok's head of marketing to focus on the Indonesian market because Indonesia has the fourth largest number of internet users in the world after China, India and the US [5]. According to Statista (2023), the total number of internet users in Indonesia reached 212 million people, which means that 83 % of Indonesians are currently using the internet. TikTok launched its new features of TikTok Shop with live streaming in mid-April 2021. It turns out that the vision of TikTok's marketing director has been achieved [Fig. 1]. By early 2023, the number of TikTok users in Indonesia had reached 110 million. Indonesia has the second most users in the world after the United States of America, which has reached 113 million people [5]. Although TikTok is the fourth most popular platform in Indonesia after WhatsApp, Instagram and Facebook, its year-on-year growth has increased dramatically in a short period of time compared to other platforms [6]. According to a social commerce survey conducted by Rakuten Insight in Indonesia in 2023, around 56 percent of respondents said they had used TikTok to make purchases in the past 12 months. The same survey found that around 40 percent of Indonesian consumers regularly shop on social media [7].
Fig. 1.
Live streaming platform in Indonesia.
Why do Indonesian consumers shop on the live streaming platform? As an emerging market country, there are certainly differences from developed market countries (e.g. the US market), and even within the same emerging market country, there may be differences between Indonesia and other markets (e.g. the Chinese market). However, despite the growing popularity of social commerce through live streaming, there is little research on the motivations and behaviours of Indonesian consumers who shop through live streaming in social commerce. This research paper aims to explore the phenomenon of Indonesian consumers' purchase intention during live streaming on social media. It examines the utilitarian value, hedonic value, social value and trust of consumers who intend to buy products and services through live streaming on social media platforms and conducts structural equation modeling to analyse the validity of the hypothesis and theoretical framework.
Based on the Consumer Perceived Value Theory, this study aims to provide recommendations for related businesses in Indonesia to help them capitalise on this growing trend in the social commerce industry. The research questions of this study are (1) to analyse why Indonesian consumers buy on live streaming platforms and (2) to identify the factors that may influence consumer behaviour on live streaming.
2. Literature review
2.1. Live streaming commerce
One of the most significant trends to emerge from social media is the rise of live streaming. Not only has live streaming changed the way people consume and create content, it has also created new ways for businesses to connect with their customers. Live streaming has become a popular way for businesses to showcase their products and interact with customers in real time. By integrating shopping functionality into live streams, businesses can now offer their customers a seamless shopping experience, allowing them to make purchases without leaving the social media platform [8]. Live streaming commerce differs from traditional e-commerce in three ways: First, in traditional e-commerce sites, the interactive activity is primarily between the customer and the site features, but in live streaming, broadcasters can clearly describe the products and services and even try on the products, such as clothes and makeup [9]. Second, live streaming can provide consumers with a more social and authentic experience than traditional e-commerce sites. Third, live streaming can facilitate real-time interactions between consumers and sellers, which can attract consumers and increase consumers' online purchase intentions. Live streaming commerce contributes to direct mutual awareness between presenters and consumers through real-time audio and video delivery technology, enabling conversations that resemble direct interactions. Live streaming commerce is essentially an extension and enhancement of TV shopping in the traditional media era, reflecting the real-time nature and interactivity of communication in the new media era, making it more internalised than traditional media production [10].
In recent years, with the gradual penetration of live streaming commerce in many countries, a considerable body of literature in the academic community has begun to examine this phenomenon, resulting in a substantial corpus of research results. These studies have explored live streaming commerce from a variety of perspectives. From the perspective of research objects, they can be divided into consumer, anchor, seller, and platform perspectives. From the perspective of research content, they can be divided into experiential products and functional products. From the perspective of research methods, there are consumer perception models, technology acceptance models, S–O-R models, and so forth. From the perspective of data sources, there are research data, experimental data, real transaction data, and so on. We have classified and summarised the literature, and highlighted the focus of our study, as shown in Table 1 [[11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24]].
Table 1.
Comparison with the relevant literature（Last 5 years）.
| References | research object | theoretical foundation/methodology | Data sources | product categories |
|---|---|---|---|---|
| Wongkitrungrueng and Assarut (2018) | Consumers' engagement | consumer perceived value/structural equation modeling | survey data | fashion products |
| Ang et al., 2018 | consumers' motivations/trust | social impact theory/structural equation modeling | Experiment data | smartphone |
| Cai et al. (2018) | Consumers' motivations | Technology Acceptance Model (TAM)/structural equation modeling | survey data | General Products |
| Zhang et al. (2019) | customers | construal level theory | experiment data | General Products |
| Hou et al., 2019 | celebrity | Uses and Gratification Theory partial least squares-structural equation modeling | semi-structured interview survey data | experience goods |
| Sun et al. (2019) | consumer engagement | IT affordance/structural equation modeling（SEM） | survey data | General Products |
| Wongkitrungrueng et al., 2020) | seller | Principal Component Analysis Qualitative content analysis |
real data | – |
| Hu and Chaudhry (2020) | consumer engagement | S–O-R model/structural equation modeling（SEM） | online survey data | General Products |
| Park and Lin (2020) | celebrity endorsement | S–O-R framework/structural equation modeling (SEM). | Online survey data | fashion products |
| Gao et al. (2021) | streamer/Consumer | Elaboration likelihood model SEM |
survey data | General Products |
| Meng et al. (2021) | celebrities' emotion | The emotional contagion theory SEM + ICTCLAS text |
survey data/real data | food products |
| Zhang et al., 2022 | Consumer trust | socio-technical system theory/structural equation modeling（SEM） | survey data | General Products |
| Zhong et al., 2022 | college students | S–O-R model/PLS -SEM | survey data | General Products |
| Juju et al. (2023) | consumer | Structural Equation Model | survey data Google Forms |
fashion products |
| Our work | Consumer trust | consumer perceived value | survey data | General Products |
A significant proportion of users of live streaming are concerned about the trustworthiness of the seller and the platform, as well as the satisfaction they can expect from the online store and the products they will purchase. Consequently, numerous previous researchers have analyzed the perceived value of customers, which encompasses utilitarian and hedonic values. In parallel with the growth of the internet and the emergence of numerous online retailers offering their products via live streaming, this study is broadening the scope of its research by incorporating social value. This analysis aims to ascertain the impact of social interaction between sellers and buyers on consumer trust and purchasing intentions [8].
2.2. Consumer perceived value
Perceived value is an important concept in marketing strategy because it helps companies understand how their customers make purchasing decisions and how to improve their products and services to meet customer needs and preferences. By understanding the factors that contribute to perceived value, businesses can develop marketing strategies focused on highlighting the benefits and value of their products and services rather than just lowering their prices. This allows businesses to differentiate themselves from their competitors and attract and retain customers over the long term.
The perceived values that will be analyzed in this study are utilitarian value, hedonic value, and social value. The utilitarian value indicates the perception of functional benefits like “ease of use” or “convenience.” The previous literature [25] indicated that the functioning of online shops can be seen from two consumer perspectives: the utilitarian dimension and the hedonic dimension. A utilitarian consumer is a rational thinker whose shopping motivation is driven by the information and navigational design of the features of the online store. They purchase action-motivated and rational. While hedonic value indicates the perception of emotional benefits like “enjoyment” or “fun” and hedonic consumers' online shopping motivations are directed toward the visual design of online store features. The hedonic value of store features reflects the potential entertainment and playful enjoyment value that customers derive from their online shopping experience. In terms of visual design, the store shows aesthetic beauty, graphics, colors, and fonts improve the look and feel of your website. It can appeal to the emotions of online shoppers and influence their shopping behaviour [25]. The social value indicates the intangible benefits such as “emotional” and “psychological” benefits. These benefits are not necessarily related to the functional characteristics of the product, but rather to the meaning and symbolism that the product represents to the customer [9]. It is more likely to show the status and self-esteem of the consumers. The higher level of consumer social value will increase consumer satisfaction with online shopping and strengthen consumers' purchase intentions. By introducing live streamers, interacting with consumers and providing a comfortable live streaming atmosphere will also really help for consumers' decision-making [26].
2.3. Consumer trust
Trust is seen as a factor that assists customer decision-making and reduces customer-perceived risk. Compared to traditional stores, consumers perceive more risk as they cannot physically see the presence of a store and cannot touch or examine products before making a purchase decision. As such, trust plays a more important role for e-commerce merchants. Instead, consumers turn to the merchant's website for information about products. The previous research about consumer online shopping behaviour found that electronic trust has a significant positive impact on consumer online purchase intention [27]. They also stated that no users or consumers will buy products from untrusted e-commerce merchants even though they may feel satisfied with the products and services provided. This result is in line with Fadhillah et al. (2021) In a study of Shopee in Indonesia, it was also found that trust has a positive and significant effect on customer online shopping [28].
A study by Dang et al. (2023) stated that customer trust plays the most important role in e-commerce marketing strategies for online consumer shopping decisions [29]. They found that to build customer trust in e-commerce, one must first improve the e-commerce platform's effectiveness for users to feel the ease of use. Secondly, e-commerce has to provide quality information, and lastly, a secure payment system has to be developed by professionals who can support customers in their purchasing decisions. Trust is the most effective way to reduce risk perception and is essential for online customers' real buying decisions in e-commerce. This result is in line with Mosunmola et al. (2019) who suggest that online merchants be more concerned about consumer trust in online shopping and how it impacts consumer purchase intentions [25]. because consumers will be concerned about not sharing their private data to develop a sense of trust in the e-commerce platform they use for shopping. Therefore, online merchants need to ensure that their online store features consist of interactive information and visual and navigational designs. This might increase the confidence of online shopping buyers and increase their willingness to use live online shopping.
Based on previous analysis, consumer trust is a very important thing that online shop sellers must pay attention to. Therefore, this study uses the trust variable as a mediating variable, which is a factor that is influenced by perceived value, and also identifies the existence of an influence or relationship to the dependent variable, namely consumer buying behaviour, which uses the purchase intentions factor. The trust variables used in this analysis are trust in the product and trust in the vendor.
2.4. Purchase intentions
One of the primary objectives for companies is to attract consumer attention, as this can lead to increased sales. This is consistent with the definition of Zong et al. (2023), which posits that external factors can influence customer purchase intentions for a specific product. Furthermore, consumer behaviour in the choice of a product occurs.
In the Ali et al. (2021) study, purchase intentions are defined as the willingness of consumers to engage in online transactions. The manner in which consumers choose to purchase products and services online has a significant impact on their online purchasing behaviour. Moreover, purchase intentions can be assumed to be the probability level at which a consumer will purchase a product. Furthermore, the study by Fadhillah et al. (2021) indicated that consumer trust can enhance consumer purchasing intentions. The findings are consistent with those of Dewi et al. (2022), who demonstrated that consumer trust acts as a mediating variable between ease of use and consumer repurchase intention. Consequently, it is of paramount importance to gain an understanding of and assess consumer purchase intentions in order to achieve superior performance compared to competitors.
3. Hypothesis development
3.1. The utilitarian value and customer trust
The utilitarian value in live streaming e-commerce refers to the satisfaction level of the features, prices, and quality offered by a product and service that match the consumer's expected utility [30], it also refers to the instrumental dimension such as convenience and cost reduction [9] and when the consumers satisfied on the products and services features, prices, and quality they get, it is the time when consumers experience the utilitarian value [30]. It can refer to one of the risks of online shopping, in which the goods purchased cannot be physically touched by the customer.
Customers who buy products online often find that the quality of the products does not meet their expectations [31]. Therefore, the live streaming feature allows potential buyers to see the actual condition of the item without going through a Photoshop-like editing process. They also stated that when the presenter or influencer presents the products via live streaming, the consumer can easily see the details of the products and get accurate information about them; this proves that the perceived utilitarian value affects consumer trust in the presenter as well as the platform. Consumers tend to lose confidence in using technology when they find it difficult to use it [27].
When an online vendor can provide accurate, relevant, and clear information for consumers, it tends to increase the consumer's trust in the seller [25]. They found out that utilitarian value has a significant and positive relationship with consumer trust. This result is in line with the study of [32] who also found that the quality of information provided will meet the consumer's utilitarian needs as well. According to the prior research, this study generates the hypothesis as follows:
H1a
The utilitarian value of live streaming has a significant and positive impact on customer trust in products.
H1b
The utilitarian value of live streaming has a significant and positive impact on customer trust in the platform.
3.2. The hedonic value and customer trust
Hedonistic value is more subjective and personal than utilitarian value, and it derives more from the feeling of enjoyment and playfulness than task completion [33]. It refers to non-functional benefits and emotional benefits such as enjoyment and happiness [9]. The aesthetic beauty of the platform will attract consumers' perceived hedonic value, these emotions may increase the consumer's intention to buy products on the vendor's platform [25]. It will lead to a better user experience, reduce ambiguity, and increase customer trust in the online merchant. Based on the study of Halim et al. (2022), they believe that the consumer who has feelings of enjoyment, pleasure, and satisfaction has higher impulsive buying behaviour [32].
In contrast, the study of Dewobroto & Enrica (2021) found that perceived hedonic value has no impact on consumer trust in a platform or seller, but it has an impact on consumer trust in products because the research respondents showed mostly younger respondents idolized an artist [31], therefore, when the live streamer is one of their idols, the consumers may believe the product can meet their expectations. Activities such as asking questions to the audiences and distributing awards such as gifts, discount vouchers, etc. will increase the consumer's hedonic value as well as the likelihood that they will buy the products [27]. The literature above has found that perceived hedonic value is a strong determinant of attitude toward live streaming shopping, therefore, the hypothesis of this study is as follows:
H2a
The hedonic value of live streaming has a significant and positive impact on customer trust in products.
H2b
The hedonic value of live streaming has a significant and positive impact on customer trust in the platform.
3.3. The social value and customer trust
Social value is defined as the perception of social self-concept that arises from the use of social networks in commerce, it occurs when the products and services reach the consumer's social needs [32]). Social value is realized through enhancing one's social status or connections. Live streaming occurs in the interactions between consumers and sellers, through this feature, consumers can feel like they are interacting with humans, not only with technology. The result of Wu & Huang (2023) also found that social value has a significant and positive relationship with consumer trust in products because, on live streaming platforms, the streamer can deepen their trust by giving a sense of belonging and showing interest in the platforms [30]. The social value also has a significant and positive impact on trust in the products because, through the product's brand image, consumers can increase their favorable perceptions and their trust in the products. But in contrast to the study of Dewobroto & Enrica (2021) they found no significant impact of social value on consumer trust in products since the live streaming activity is planned by the presenter, so it has no relation to the products they present [31].
According to previous research, perceived social value is an important function of social commerce sites. By gaining social recognition and acceptance and making a favorable impression on others, consumers might increase their satisfaction with live streaming shopping and increase their purchase intentions. Therefore, the author generates this study hypothesis as follows:
H3a
The social value of live streaming has a significant and positive impact on customer trust in products.
H3b
The social value of live streaming has a significant and positive impact on customer trust in the platform.
3.4. The perceived value and consumer buying intention
The study by Gan &Wang (2017) found utilitarian value has a significant and positive relationship with consumer buying intention, they stated that users will feel more satisfied and tend to purchase the products and services when they feel more convenience and ease of use on the platforms [9]. The result is in line with the study of Dewobroto & Enrica (2021) and Dewi et al. (2022) who also found there is a positive impact on utilitarian value for consumer buying intentions [27,31]. They stated that the easy and convenient way for the consumer to interact with the seller just by chatting in the live room may encourage consumer engagement during the live streaming.
In addition, when the consumer feels like shopping in live streaming e-commerce, they will perceive higher hedonic value, feel more satisfied, and increase their buying intention. The studies of Mosummola et al. (2019) and Dewobroto & Enrica (2021) believe that enjoyment shopping has a positive effect on consumer buying intentions [25,31].
The study by Gan & Wang (2017) stated that perceived social value is not focused only on the quality and characteristics of the products, it is more likely to pursue the consumers’ shopping experience [9]. Their results indicate that perceived social value has a significant and positive influence on consumer buying intentions. They also define social value as the process of interaction and sharing between sellers and consumers, or sharing between fellow consumers during live streaming, which will increase consumer satisfaction and purchase intention. While consumers can exchange opinions and share information with sellers and other audiences in the live room, it will increase their social value as well as their buying intentions. This study generates the following hypothesis:
H4
Utilitarian value has a significant and positive impact on consumer buying intentions.
H5
Hedonic value has a significant and positive impact on consumer buying intentions.
H6
Social value has a significant and positive impact on consumer buying intentions.
3.5. The customer trust and consumer buying intention
Trust is a key factor in consumer behaviour and decision-making as it reduces the uncertainty and perceived risks associated with purchases [17]. In the context of live streaming, consumers rely on the trustworthiness of the platform and the trustworthiness of the hosts or influencers promoting their products. When a consumer wants to reduce the perceived risk, trust is a mental shortcut for the consumer because it is more critical when consumers purchase products on e-commerce when they cannot physically touch and feel the real products [34].
From the study of Falahat et al. (2019), they give some suggestions on how to increase consumer trust on their online platform, such as that the vendor needs to promote their brand to become well recognized by the public [34]. Service quality is important for a vendor to ensure consumer trust in the vendor platform. Sellers need to provide professional feedback to consumers, and to gain consumer trust, e-commerce vendors must emphasize the security and protection of consumer information by clearly explaining and displaying such commitments on their e-commerce platform.
The study by Mosunmola et al. (2019) found that consumer trust has a strong impact on consumer buying intention [25]. They indicate that customer trust in online shopping leads to an increase in consumer buying intentions. This result is in line with the study of Wu & Huang (2023), who found that trust in the products and trust in the seller both have a significant and positive impact on consumers' continuous buying intentions [30]. In contrast, the result of Dewobroto & Enrica (2021) stated that the trust of the seller has no impact on consumer buying intentions because the seller is not the producer of the products, they are just a reseller [31]. Consumers who do not trust e-commerce applications are less loyal and will not shop again, even if they are satisfied with the products and services offered [35].
Therefore, the author formulated the following hypothesis.
H7a
Customer trust in products has a significant and positive impact on consumer buying intentions.
H7b
Customer trust in platforms has a significant and positive impact on consumer buying intentions.
Based on the hypothesis applied in this study, one can see the conceptual framework analyzed in this study in Fig. 1. Utilization value, hedonic value, and social value are variables of perceived value that will be used to analyse the relationship with consumer buying intention. Meanwhile, trust in the product and trust in the platform are mediating variables in this study that are influenced by perceived value and its relationship with consumer buying intentions. Therefore, this study's research model has been generated in the following sections (Fig. 2).
Fig. 2.
Conceptual model.
4. Research methodology
In this research, the author considered TikTok Live, one of the newest live streaming platforms in Indonesia, as research content. TikTok Live is a platform that has direct mutual awareness between presenters and consumers through real-time audio and video delivery technology, enabling conversations that resemble direct interactions [5]. In a live streaming room, a broadcaster can create a video stream to display and start introducing products (such as clothing or cosmetics) to customers. Customers can interact with broadcasters and other customers through chatting in the live room. Fig. 3 shows an example screenshot of a TikTok user's homepage and a live streaming e-commerce site running on TikTok Live from the customer's screen. The interactive interaction and contact in this enhanced live-streaming e-commerce can easily increase the impulsive buying behaviour of customers.
Fig. 3.
Screenshot of live streaming commerce in TikTok.
4.1. Measurements
All the question items were generated using prior research, with only minor modifications made in accordance with the research context of this paper, in order to ensure the scale's validity. The specific design of the scale questions is presented in Table 2. For the utilitarian value dimensions and hedonic value dimensions, please refer to Refs. [9,30]. For the social value dimensions, please refer to the design of [19,30]. For the mediation variable, such as trust in products, dimensions are taken from the designs of Wongkitrungruenga & Assarut (2020) and Wu & Huang (2023). For trust in platforms, dimensions are taken from the designs of Falahat, Lee, Foo, & Chia (2019). Finally, the dimensions of the purchase intention variables are referenced in the designs of Wongkitrungruenga & Assarut (2020) and Wu & Huang (2023) [17,30].
Table 2.
Measurement scales.
| Construct | Code | Items | |
|---|---|---|---|
| Utilitarian Value (UV) | UV1 | The way a product is presented via TikTok Live helps me to visualize the appearance of the product on a real figure. | Gan & Wang, （2017) Wu & Huang, （2023） |
| UV2 | The way a product is presented online gives me as much sensory information about the product as I would experience in a store. | ||
| UV3 | I feel that I can ask the seller via TikTok Live to find products I want. | ||
| UV4 | Products sold through TikTok Live tend to be up-to-date and on-trend. | ||
| UV5 | Compared to other ways, I think shopping through that TikTok live room is a better value and better deal. | ||
| Hedonic value (HV) | HV1 | The process of shopping on the TikTok Live Streaming made me feel relaxed. | Gan & Wang, （2017) Wu & Huang, （2023） |
| HV2 | I enjoy TikTok live shopping | ||
| HV3 | I am able to do a lot of fantasizing while watching TikTok Live. | ||
| HV4 | Using this TikTok Live for shopping is one that I would feel interesting. | ||
| HV5 | Using this TikTok Live for shopping would give me pleasure. | ||
| Social value (SV) | SV1 | By TikTok shopping live, I feel very fashionable. | Wongkitrungruenga & Assarut, 2020) Wu & Huang, 2023 |
| SV2 | Shopping via TikTok Live Streaming can make a good impression on others. | ||
| SV3 | When shopping via TikTok Live Streaming, I can find products that match my style. | ||
| SV4 | I would love to tell my friends/acquaintances about this live shopping. | ||
| SV5 | I can infer social acceptance of products from other customers' comments during the live stream. | ||
| Trust in product (TIP) | TIP1 | I believe the products I order from TikTok Live will be as I imagined. | Wongkitrungruenga & Assarut, （2020) Wu & Huang, （2023) |
| TIP2 | I believe that I will be able to use products like those demonstrated on TikTok Live. | ||
| TIP3 | I believe I will be very happy with the product I receive. | ||
| Trust in Platform (TPL) | TPL1 | I believe this vendor's platform provides reliable information | Falahat, Lee, Foo, & Chia, （2019） |
| TPL2 | I believe this vendor's platform keeps promises and commitments. | ||
| TPL3 | I believe this vendor's behaviour meets my expectations | ||
| Intention to Buy (IB) | IB1 | I would consider buying this product after watching the TikTok live stream. | Wongkitrungruenga & Assarut, （2020) Wu & Huang, （2023) |
| IB2 | When I need it, I am willing to buy it directly from the TikTok live room. | ||
| IB3 | In the future I will be watching more TikTok Live e-commerce to purchase items. | ||
| IB4 | I am likely to revisit the seller's page to watch their new live videos in the near future |
The measurement of utilitarian value is informed by a number of factors, including efficiency, convenience, reliability, effectiveness, and cost-effectiveness. The measurement of hedonic value involves factors such as the degree of enjoyment, the aesthetic appeal, and the overall emotional experience associated with the product or service. The measurement of social value encompasses factors such as community involvement and environmental sustainability. Consumer trust in the products is gauged by the extent to which consumers repose confidence in the quality, reliability, and performance of the products or offerings. Consumer trust on the platform is gauged by the extent to which consumers repose confidence in the platform or marketplace where the products are being offered.
Consumer behaviour is the process by which consumers make decisions when purchasing products in e-commerce. Consumer purchasing behaviour is the process of seeking, selecting, purchasing, using, evaluating, and disposing of products and services to satisfy needs and desires. It is the mental, emotional, and observable process of how consumers search, buy, and consume, how they buy, what they buy when they buy, and why they buy in a particular time period [35]. The consumer behaviour in this study is measured by the factor of consumer buying intentions. The measurement is measured by the likelihood of consumers purchasing products and services.
4.2. Questionnaire distribution and data collection
The population of the questionnaire is required for Indonesian and is not limited to the respondent's gender, age, occupation, monthly income, and education as the first part of the questionnaire. The second part is to understand the attitude of respondents toward online shopping, and considering that live streaming e-commerce is still a relatively new kind of marketing strategy in Indonesia, I may exclude respondents who have never used live streaming e-commerce before. The last part of the questionnaires is a specific scale that measures the variables of utilitarian value, hedonic value, social value, trust in products and platforms, and intention to buy. The scale used in this study is a five-point Likert scale, with the number value from 1 to 5 representing “strongly disagree” to “strongly agree."
Before formally distributing the questionnaire, we first conducted a pre-test. We invited 30 customers who had made purchases on the TikTok live streaming platform in the past six months. Based on the results of the pretest, we made appropriate changes to the questionnaire.
The questionnaires were distributed through the Google Form that spread out through WhatsApp, email, Instagram, and WeChat for hypothesis testing and this research objective. To collect more accurate data, this study will only collect Indonesians who are using live streaming s-commerce and have ever shopped in e-commerce. After distributing the questionnaire in the form of a Google Form, the researcher got 204 respondents who completed the questionnaire.
4.3. Common method bias
The primary objective was to implement procedural measures to prevent the occurrence of common methodological biases. Prior to administration, the questionnaire was pre-tested to ensure that respondents could comprehend the questions. Secondly, the order of the questionnaire was adapted in order to establish temporal intervals. Thirdly, the data collection process was designed to ensure anonymity and confidentiality. Finally, respondents were informed that there is no correct or incorrect response to the questions, as the tone of the items was designed to be neutral. Furthermore, Harman's one-factor test was employed to ascertain the presence of biases. The results of the test indicated that there was no single factor or general factor that could be identified as explaining the majority of the covariance between the measures.
5. Analysis results
5.1. Sample description
Table 3 presents the respondent information and attitudes towards online shopping, based on the data collected. The table includes a total of 204 respondents. It can be observed that in Indonesia, the majority of respondents are women who use live streaming for shopping. Among those aged between 26 and 35, the percentage reaches 52.45 %, while among those aged between 36 and 45, it reaches 56.37 %. The majority of live shopping shoppers are self-employed individuals with a monthly income of 5 million to 10 million rupiah. Their average monthly expenditure on live streaming is less than 500,000 rupiah. The majority of TikTok users make purchases via live streaming, with a percentage of 44.12 %. This is followed by Shopee and Instagram, with respondents citing the attractive promotions on TikTok and the more acceptable prices applied on TikTok as the reasons for this.
Table 3.
Information of respondent.
| Variable | Category | Frequency | Percentage (%) |
|---|---|---|---|
| Gender | Male | 97 | 47.55 |
| Female | 107 | 52.45 | |
| Age | Between 18 and 25 | 71 | 34.80 |
| Between 26 and 35 | 115 | 56.37 | |
| Between 36 and 45 | 16 | 7.84 | |
| Above 45 | 2 | 0.98 | |
| Educational Level | High school | 26 | 12.75 |
| Diploma | 12 | 5.88 | |
| Bachelor's degree | 147 | 72.06 | |
| Master's degree | 17 | 8.33 | |
| Phd | 2 | 0.98 | |
| Monthly Income | Less than IDR 3.000.000 | 40 | 19.61 |
| Between IDR 3.000.000-IDR5.000.000 | 32 | 15.69 | |
| Between IDR 5.000.000-IDR10.00.000 | 89 | 43.63 | |
| Between IDR 10.000.000-IDR15.000.000 | 29 | 14.22 | |
| More than IDR15.000.000 | 14 | 6.86 | |
| Occupations | Government Employee | 28 | 13.73 |
| Private Sector | 71 | 34.80 | |
| Self-Employed | 52 | 25.49 | |
| Student | 44 | 21.57 | |
| Unemployed | 9 | 4.41 | |
| Monthly Spend | Less than IDR 500.000 | 108 | 52.94 |
| IDR 500.000 - IDR 1.000.000 | 81 | 39.71 | |
| IDR 1.000.000 - IDR 2.000.000 | 8 | 3.92 | |
| More than IDR 2.000.000 | 7 | 3.43 | |
| Why Using LS | Price | 67 | 32.84 |
| Product Quality | 50 | 24.51 | |
| Promotion | 85 | 41.67 | |
| Others | 2 | 0.98 | |
| Used Platform | 28 | 13.73 | |
| Shopee | 84 | 41.18 | |
| TikTok | 90 | 44.12 | |
| Others | 2 | 0.98 | |
| Total of Respondents | 204 | 100.00 | |
5.2. Reliability and validity analysis
In this study, the SPSS AMOS software will be employed to analyse the validation, reliability, and hypothesis testing. A confirmatory factor analysis test is employed to test and explain the validity of existing constructs. Therefore, the confirmatory factor analysis test is suitable for testing one variable on the indicators in it and can also be used to determine whether the measurement model was constructed in accordance with the proposed theory.
In terms of analysing the validity of the study, the concept of convergent validity is employed in order to test the hypothesis put forth by Ref. [30]. All variables demonstrated sufficient levels of convergent validity, as evidenced by the results of the validity and reliability tests. The findings demonstrate that the data collection instrument accurately captured each variable, with all items exhibiting satisfactory factor loading, average variance extraction (AVE) and composite reliability values (CR). The results of validity testing show that all research indicators have a loading factor value of >0.5 and an average variance extracted (AVE) value of >0.5. Furthermore, the reliability assessment is evident from the construct reliability value, which is greater than 0.7. As a result, all variables were considered reliable. Consequently, no indicators were taken out of the research model.
Table 4 also shows that the data distribution is normal, indication that the research model meets the assumptions of multivariate normality. Therefore, the analysis process can use the Maximum Likelihood (ML) method.
Table 4.
Reliability and validity.
| Variables | Indicator | loading factor | Error | CR | AVE | Skewness | Kurtosis |
|---|---|---|---|---|---|---|---|
| Utilitarian Value | UV1 | 0.825 | 0.175 | 0.83 | 0.74 | −0.704 | −0.679 |
| UV2 | 0.785 | 0.215 | −0.605 | 0.126 | |||
| UV3 | 0.751 | 0.249 | −0.591 | −0.157 | |||
| UV4 | 0.795 | 0.205 | −0.623 | 0.032 | |||
| UV5 | 0.771 | 0.229 | --0.521 | 0.040 | |||
| Hedonic Value | HV1 | 0.871 | 0.129 | 0.93 | 0.87 | −0.475 | −0.314 |
| HV2 | 0.894 | 0.106 | −0.513 | −0.404 | |||
| HV3 | 0.855 | 0.145 | −0.398 | −0.392 | |||
| HV4 | 0.896 | 0.104 | −0.623 | −0.053 | |||
| HV5 | 0.887 | 0.113 | −0.450 | −0.476 | |||
| Social Value | SV1 | 0.879 | 0.121 | 0.91 | 0.84 | −0.489 | −0.350 |
| SV2 | 0.824 | 0.176 | −0.549 | −0.328 | |||
| SV3 | 0.873 | 0.127 | −0.645 | −0.112 | |||
| SV4 | 0.898 | 0.102 | −0.798 | 0.205 | |||
| SV5 | 0.821 | 0.179 | −0.649 | 0.092 | |||
| Intention to buy | IB1 | 0.807 | 0.193 | 0.84 | 0.78 | −0.788 | 0.827 |
| IB2 | 0.821 | 0.179 | −1.031 | 0.992 | |||
| IB3 | 0.813 | 0.187 | −0.737 | 0.363 | |||
| IB4 | 0.821 | 0.179 | −0.921 | 1.067 | |||
| Trust in Product | TIP1 | 0.822 | 0.178 | 0.82 | 0.80 | −0.429 | 0.291 |
| TIP2 | 0.858 | 0.142 | −0.389 | −0.215 | |||
| TIP3 | 0.801 | 0.199 | −0.416 | −0.170 | |||
| Trust in Platform | TPL1 | 0.832 | 0.168 | 0.84 | 0.82 | −0.616 | 0.066 |
| TPL2 | 0.848 | 0.152 | −0.524 | 0.312 | |||
| TPL3 | 0.858 | 0.142 | −0.480 | 0.057 |
The AVE is also employed to assess discriminant validity. In accordance with the criteria established by Fornell and Larcker (1981) [36], it is expected that each construct will exhibit a higher degree of correlation with its own construct than with other constructs. Table 5 demonstrates that all variables are significantly correlated (p < 0.001) and less than the square root of the corresponding AVE, indicating that the discriminant validity of the scale is optimal (see Table 6).
Table 5.
Discriminant validity.
| Item | UV | HV | SV | IB | TIP | TPL |
|---|---|---|---|---|---|---|
| UV | 0.8602 | |||||
| HV | 0.842a | 0.9327 | ||||
| SV | 0.533a | 0.436a | 0.916 | |||
| IB | 0.504** | 0.942** | 0.532a | 0.8831 | ||
| TIP | 0.577a | 0.656a | 0.417** | 0.520a | 0.8944 | |
| TPL | 0.572** | 0.6150a | 0.317a | 0.561a | 0.564a | 0.9055 |
Represents p-values less than 0.001, and the diagonal line is the extracted AVE mean-variance.
Table 6.
Regression model.
| Hypotheses | Estimate | S.E. | C.R. | P | VIF |
|---|---|---|---|---|---|
| Trust in Product → Utilitarian Value | 0.624 | 0.111 | 5.62 | *** | 1.8460 |
| Trust in Platform → Utilitarian Value | 0.538 | 0.090 | 5.992 | *** | 1.7860 |
| Trust in Product → Hedonic Value | −0.017 | 0.087 | −0.19 | 0.849 | 2.6410 |
| Trust in Platform → Hedonic Value | 0.202 | 0.071 | 2.842 | 0.004 | 1.3476 |
| Trust in Product → Social Value | 0.252 | 0.107 | 2.345 | 0.019 | 2.7110 |
| Trust in Platform → Social Value | 0.232 | 0.087 | 2.669 | 0.008 | 1.4621 |
| Intention to buy → Utilitarian Value | 0.186 | 0.091 | 2.038 | 0.042 | 2.8925 |
| Intention to buy → Hedonic Value | 0.176 | 0.057 | 3.105 | 0.002 | 1.8930 |
| Intention to buy → Social Value | 0.209 | 0.069 | 3.009 | 0.003 | 1.9230 |
| Intention to buy → Trust in Product | 0.283 | 0.064 | 4.442 | *** | 1.2290 |
| Intention to buy → Trust in Platform | 0.195 | 0.078 | 2.495 | 0.013 | 2.0163 |
5.3. SEM and hypothesis test
Once the measurement model has been subjected to confirmatory factor analysis (CFA), and it has been established that each variable can be used to define a latent variable, a full structural equation model (SEM) can be analyzed. The results of the SPSS AMOS processing are presented in Fig. 4.
Fig. 4.
Path coefficients of SEM.
The preceding tests of validity, reliability, and multivariate variables indicate that the study model is fit for the next analysis, namely the hypothesis test. The hypothesis test is designed to ascertain whether there is a statistically significant relationship between the independent and dependent variables. The analysis process employs the Maximum Likelihood (ML) method.
The relationship between utilitarian value and trust in the product based on the above Table 4 results is positively significant, while H1a is accepted. This is because the probability value is less than 0.05, namely 0.000. It indicates that if you increase the utilitarian value of customers in TikTok live streaming, you are also increasing customers' trust in the products. This result is in line with the studies of Wongkitrungruenga & Assarut (2020) and Wu & Huang (2023) who also found that there is a significant and positive relationship between utilitarian value and trust in the products. This study found that the influence of utilitarian value on trust in products is in terms of perceived value, while at the same time, the product displayed by the streamer can be seen clearly by customers. The second is in terms of transparency, which means that live streaming allows customers to directly witness the product being displayed so that they understand more about the use of the product, and if the streamer answers customer questions informatively, they tend to believe that the product will meet their expectations. Lastly, it is about better value and better deals that attract customers' attention when they make purchases on the TikTok platform.
The relationship between utilitarian value and trust in the platform based on the hypothesis test results showed a significant and positive relationship, while H1b is accepted. This is because the probability value is less than 0.05, namely 0.000. It indicates that if you increase the utilitarian value of customers in TikTok live streaming, meanwhile there is also increasing customers' trust in the platform. This study result is in line with the studies of (Dewobroto & Enrica, 2021), (Sarah & Nurdin, 2022), and (Wu & Huang, 2023) [8,17,23]. In terms of efficiency, where customers can buy a product by seeing the physical product, getting the information they want, and making purchases in an easy way, it tends to increase trust in platforms that provide efficient and practical facilities. In order to increase consumer trust, the live streaming platform has to put more emphasis on offering clear, efficient, and high-quality utilitarian value to consumers. As a result, consumers will feel secure and confident using the platform for their shopping.
The relationship between hedonic value and trust in the product based on the above results shows that there is an insignificant relationship, while H2a is rejected. The result shows an insignificant relationship between hedonic value and trust in the products because hedonic value is more concerned with the sentimental and experiential aspects of a product and might not directly affect a customer's level of trust in the item when making a live streaming purchase. Hedonic value may not be a reliable indicator of trust for all customers, even though trust is typically based on more objective and concrete elements like product quality, transparency, and dependability. According to this theory, consumers may place a greater value on the objectivity of useful information and product specifications than on the subjective nature of emotional experiences. In contrast to emotional appeals, they might be more inclined to believe facts, specifications, and demonstrations, which are typically linked to utilitarian value. This analysis's result is in line with the study of Wu & Huang (2023).
The relationship between hedonic value and trust in the platform based on the analysis results above indicates that there is a significant and positive relationship, while H2b is accepted. This result indicates that positive feelings like joy, willingness, or contentment are frequently linked to hedonic value. Customers may be more likely to trust a platform when they relate these favorable feelings to their online buying experience. The positive experiences offered by hedonic value might also increase platform credibility. Customers can be more willing to trust a platform that offers a pleasurable experience because they think the platform is reputable and trustworthy. This result is in line with the studies of Sarah & Nurdin (2022) and Wu & Huang (2023). But in contrast with the results of (Dewobroto & Enrica, 2021) and (Wongkitrungruenga & Assarut, 2020) who stated that there is an insignificant relationship between hedonic value and consumer trust in the platform.
The relationship between social value and trust in the products based on the hypothesis test result in this study is significant and positively related, while H3a is accepted. This result is in line with the studies of Sarah & Nurdin (2022) and Wu & Huang (2023). This study indicates that increasing the consumer's social value tends to increase their trust in the products in live streaming shopping experiences. Positive user reviews that customers see or hear during live broadcasts or in comments left by other viewers serve as social evidence in favor of the product. In the view of consumers, the positive comments from consumers in the live room might tend to increase the trust of products that are influenced by other viewers. People frequently take the beliefs and actions of others into consideration, especially when they identify with that group.
The relationship between social value and trust in the platform based on the hypothesis test result in this study is significant and positively related, while H3b is accepted. Live broadcasting definitely leads to direct interactions, and if the streamer is kind and engaging during this interaction, viewers are likely to develop trust in the platform as a welcoming and reliable online shopping destination. Customers who shop online via live streaming will also feel as though they have made a good impression on others, and live streaming users will feel very fashionable and want to tell people about this live shopping.
The relationship between utilitarian value and intention to buy based on the hypothesis test result in this study is significant and positively related, while H4 is accepted. This study's result indicates that the more utilitarian value of live streaming will tend to increase consumer buying intentions. This study result is in line with the studies of Dewobroto et al. who also found that there is a positively significant relationship between utilitarian value and consumer buying intentions [2,8,9]. The practical advantages and utility value that consumers derive from the product are referred to as “utilitarian value.” Customers are more likely to feel satisfied and inspired to make purchases when the products given in live broadcasts address their requirements or concerns. In order to make the viewer feel more valuable, as if they are getting a better deal, live broadcasts frequently include special offers, discounts, or purchase bonuses. This actually creates additional value and gives buyers the impression that they are receiving a good deal, which encourages them to shop more in live streaming.
The relationship between hedonic value and intention to buy based on the hypothesis test result in this study is significant and positively related, while H5 is accepted. This result indicates that the more hedonic value consumers receive, the more likely they are to make a purchase. Hedonic value is related to the emotional and shopping experience, when consumers feel enjoyment when purchasing live streaming, they will tend to consider purchasing the products. Live streaming platforms must design a satisfying and emotionally engaging shopping experience. This can involve engaging in enjoyable communication and interaction while creating a strong desire to buy. This result is in line with the study of Gan et al [[2], [8], [23]]. [8,23] [][[2], [8], [23]][].
The relationship between social value and intention to buy based on the hypothesis test result in this study is significant and positively related, while H6 is accepted. It indicates that the more social value arises from consumers, the higher the percentage of consumers buying products. In the context of live shopping, creating positive interactions between the streamer and the viewers or consumers, allowing them a space for recommendations, and developing an engaged community can strengthen social value and raise purchase intent. This study's result is in line with the study of Gan et al [[2], [23]]. [23] [][[2], [23]][].
The relationship between trust in the product and trust in the platform with intention to buy based on the hypothesis test result in this study is significant and positively related, while H7a and H7b is accepted. This result indicates that trust in products can be influenced by product quality, if consumers believe that the quality matches their expectations, they will consider making a purchase. With the trust of the platform, consumers will feel more comfortable when they can contact the seller and get a quick response. And when the platform has a high enough reputation, customers will automatically trust it. The results also found that trust in the products has a significant and positive relationship to consumer buying intentions, while only the study of Wongkitrungruenga & Assarut (2020) found that trust in platforms has a significant and positive relationship to consumer buying intentions [17,19,23].
6. Discussions, conclusions, and limitations
6.1. Research conclusions
Using perceived value factors such as utilitarian value, hedonic value and social value, as well as two types of consumer trust such as trust in the product and trust in the platform. This study examines why Indonesians choose to transact on the live streaming platform TikTok. The findings of this study are discussed below.
First, based on the significant findings of this study, it is confirmed that utilitarian value plays a significant role in influencing consumer trust in products and platforms. In order to increase consumer trust in both products and platforms, sellers need to be able to use utilitarian value effectively, and platforms also need to continue to improve and maintain the utilitarian value they provide, such as accurate product and service information, responsiveness to consumer needs, and transparency policies.
Second, this study found that the hedonic value of perceived value has a significant and positive effect on consumers' purchase behaviour on the TikTok live streaming platform. Therefore, it is important for streamers to present a pleasant and emotional shopping experience to increase consumers' intention to make a transaction via live streaming. However, since the hedonic value is insignificant for product trust, since the entertainment activities in LS e-commerce are primarily planned by the streamer, the hedonic value has no direct effect on product trust. As a result, the emotional trust generated by the hedonic value perceived by viewers during the live stream is often directed towards the streamer rather than the product itself.
Third, like utilitarian value, social value also has a significant and positive relationship with consumer trust in products, consumer trust in platforms, and consumer purchase intention on live streaming platforms. This is because the use of live streaming supports social interaction between streamers and users, creating community formations that can increase consumer trust and purchase intention. Therefore, implementing strategies that increase social value can help users or consumers increase their trust and purchase intent, while supporting platform growth.
Consumer trust is a successful foundation that has a significant and positive impact on purchase intent on the TikTok live streaming platform. Consumer trust should be valued and prioritised by platforms in today's competitive e-commerce market. In order to build and maintain long-term relationships with customers, it is important to understand that consumer trust plays an important role in their purchase intent. Believe that trust can create loyal and engaged customers who not only make a single purchase, but also recommend the platform to others.
6.2. Theoretical implications
This study makes two key contributions to the existing body of research. One of the study's principal contributions is that it is one of the few to employ Indonesian consumers as a sample. The majority of existing literature is based on Chinese or American consumers. This is the largest sample of mainly Chinese consumers, and in these literatures, there is a clear focus on the particular context of Chinese culture. Nevertheless, although Southeast Asian cultures are part of the same Oriental culture, there are also differences between them. This study contributes to the existing body of research on Southeast Asian culture, thereby enhancing the generalisability of the theory.
Secondly, the theory of perceived value was first developed in Western culture. Despite the growing number of empirical studies in this area, there are still some conflicting conclusions. In particular, research in the nascent field of live streaming commerce has demonstrated that consumers' perceived value is complex and multidimensional. This study examines the joint role of product trust and platform trust and their mediating role between customer perceived value and purchase intention. In light of the above, the objective of this study is to contribute to a more comprehensive understanding of the nature and measurement of perceived value.
6.3. Practical and managerial implications
This research can assist business owners and company management in comprehending consumers' perspectives (in terms of functional, emotional, and social) towards live streaming. This can facilitate the identification of market targets and the development of strategies to enhance sales and achieve optimal performance.
The findings of this research are of significant value to online shop entrepreneurs and marketers when selecting marketing strategies for their businesses. The findings can be employed by company management in the formulation of strategies designed to facilitate the growth of their businesses and to achieve the objectives set by their superiors. In particular, this research can be of benefit to new micro, small and medium-sized enterprises (MSMEs) that are considering entering the online commerce industry. It can provide them with insights into the most appropriate strategies and platforms for their products, thus enabling them to operate their businesses more effectively.
For the streamer, this study can assist in the enhancement of utilitarian value by providing quality information about the services and products offered and the capacity of customer service to respond to the inquiries of consumers. Secondly, in order to optimise the utility of social value, the streamer must be able to encourage users or consumers to interact with one another in order to foster a sense of community. Thirdly, there is a weak correlation between hedonic value and trust in the product. Users may find it more enjoyable if the streamer provides content that is more entertaining, such as stories and interesting material.
For policymakers and governments, it is imperative to establish and maintain transparency policies and data security in order to maintain consumer trust. Furthermore, it is crucial to provide training and guidance to sellers or hosts so that they can better understand and meet consumer expectations. This could enhance the overall quality of live broadcasts. This will subsequently have a beneficial impact on the Indonesian economy, enabling micro, small and medium-sized enterprises (MSMEs) to enhance their business operations and, consequently, ensuring the continued viability of not only large corporations but also MSMEs.
6.4. Limitations and future research directions
This study is subject to several limitations. Firstly, the sample size of respondents in this study is relatively small, with only 204 individuals. Furthermore, the majority of respondents are young people. Consequently, the sample size needs to be expanded at a later stage to verify the conclusions drawn, including the experiences of middle-aged and older consumers who engage with live streaming commerce, as well as those who purchase offline. Secondly, this study employed a single research method, namely a questionnaire survey. However, given the digitisation of live e-commerce, real data will be used for analysis at a later stage. Alternatively, a combination of methods will be employed to conduct a comparative study. Thirdly, the variables employed remain limited. While the related research on perceived value is well-developed, combining different samples of its dimensions remains a topic worthy of further investigation. In addition to trust, other variables such as loyalty and product type can be further investigated.
Although the results of this study demonstrate that perceived value has a positive impact on purchase intention, further research is recommended to assist the platform or seller in increasing the number of users who utilise the platform and make purchases. This could be achieved by including perceived risk as a factor influencing consumers' purchase intention, analysing whether there is a repeat purchase in the next purchase, and developing new strategies to enhance the shopping experience and purchase intention.
Data availability
The data are available upon reasonable request.
Funding statement
This work was supported by the Humanities and Social Sciences project of the Ministry of Education (granted numbers 21YJA630088).
CRediT authorship contribution statement
Hao Zhang: Visualization, Validation, Supervision, Resources, Methodology, Funding acquisition, Formal analysis. Sinta Zheng: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Peifeng Zhu: Writing – review & editing, Conceptualization.
Declaration of competing interest
The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Hao zhang reports financial support was provided by Nanjing University of Aeronautics and Astronautics. Hao zhang reports a relationship with Nanjing University of Aeronautics and Astronautics that includes: board membership. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Contributor Information
Hao Zhang, Email: Zhanghao0216@nuaa.edu.cn.
Sinta Zheng, Email: Sintazheng19@gmail.com.
Peifeng Zhu, Email: 280702@njucm.edu.cn.
Appendix A.
Appendix 1Attitudes towards online shopping by the respondents
| Questions | Categories |
|---|---|
| Have you ever used live streaming platform ? | Very often (more than 5 times/month) |
| Regularly (3–5 times/month) | |
| Sometimes (1–2 times/month) | |
| Never been used | |
| How much money did you spend monthly on live streaming ? | Less than IDR 500.000 |
| IDR 500.000 - IDR 1.000.000 | |
| IDR 1.000.000 - IDR 2.000.000 | |
| More than IDR 2.000.000 | |
| What is the most important issue for you when shopping on live streaming ? | Price |
| Delivery time | |
| Promotion | |
| Product Quality | |
| Others | |
| Live streaming platforms mostly preferred | TikTok |
| Shopee | |
| Others |
Source: Data that has been processed by the author (2023)
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Data Availability Statement
The data are available upon reasonable request.