Streamer Trust in Livestreaming Commerce: History
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Contributor:
Bowen Tian
,
Jinye Chen
,
Jie Zhang
,
Wei Wang
,
Leibao Zhang

Livestreaming commerce has become the mainstream of e-commerce. The key difference between livestreaming commerce and traditional e-commerce lies in the presence of the streamer.

  • livestreaming commerce
  • cognitive-affective-conative (C-A-C) framework
  • streamer trust

1. Introduction

Livestreaming commerce has developed into a field that promises major investment potential. Compared with traditional e-commerce, livestreaming commerce, which shows products through real-time live video, has various advantages [1], such as timely interactions between consumers and streamers, straightforwardness, and vitality. The industry report of iMedia Research shows that the total scale of China’s livestreaming commerce industry is expected to reach RMB 2137.3 billion by 2025. Realizing the great potential of livestreaming commerce, researchers have been starting to pay attention to this field and dig into the great value of this new business model.
Several research topics could be identified from the current literature, such as pricing strategies [2], newly launched products, sales strategies under the contexts of long vs. short cooperation between retailer and MCN [3], manufacturers’ decisions regarding the open of livestreaming channel [4], optimal online channel structure for firms considering livestreaming shopping [5], impacts of streamers’ linguistic styles on sales performance [6], as well as the product brand extension [7]. 

2. Livestreaming Commerce

As an increasingly important part of the livestreaming industry, livestreaming commerce is characterized by real-time interaction between the streamer, the audience, vivid product demonstration, and purchase behavior [1][8][9][10]. The interaction between the streamer and the audience plays a key role in the user experience because it promotes the flow of cognition and affection, making it possible to establish a solid and stable interpersonal relationship between the streamer and the audience [11][12]. Some previous studies have studied the characteristics of consumers and the impact of psychological factors in the shopping process from consumers’ perspective [13], and some studies have discussed the characteristics of streamers and the interaction between streamers and audiences from the perspective of streamers [9]. However, the current research has not yet thoroughly studied the antecedents and consequences of streamers. This provides a new perspective for the research of livestreaming commerce.
Some research focuses on the impact of consumers’ personal characteristics on purchasing behavior. For example, Zhang et al. [14], upon investigating impulse buying behavior in livestreaming commerce, added personal impulse as a control variable and demonstrated that, in livestreaming commerce environments, impulsive buying is driven by affective state (i.e., emotional intensity) rather than cognitive state (i.e., perceived risk). Wu et al. [15] found that when consumers make purchases online, although personal impulse had a positive impact on their impulse purchases, it did not moderate the impact of perceptual arousal. In the study of Chen et al. [16], habits are found to reinforce the impact of product uncertainty on purchase intention precisely because the convenience of product search meets consumers’ preferences, and their interaction during livestreaming yields an overall happy experience. Eventually, a habitual dependence is formed, and this habit then regulates the relationship between product quality uncertainty and purchase intention.
External influences comprise the focus of most prior research. In the work of Wongkitrungrueng and Assarut [17], it was found that sellers can provide consumers with cognitive value by providing livestreaming content and services that consumers are interested in [10]. Consumers may, therefore, be grateful and exhibit reciprocal behavior with sellers because of the non-sales content provided by livestreaming for free. An empirical study by Kang et al. [18] found that interactivity has a curved relationship with audience participation behavior in livestreaming and that it, more precisely, increases the interaction between audiences and streamers will promote audiences’ willingness to purchase and actively send gifts. Chen et al. [16] also found that information is the core element that drives consumers’ product purchases; thus, if the product information is ambiguous, it will create a complex shopping process for consumers.
The concept of trust also comprises an important research direction, and studies have found that when consumer trust in streamers increases, sellers are capable of expanding their product portfolio [10]. Zhang et al. [19] found that trust (including trust in streamers and products) is key to audiences’ continued livestreaming; the study also found that social and technological drivers have a positive impact on consumer trust in livestreaming and that trust in streamers mediates between interactivity, IT delivery and trust in products.
Research on livestreaming commerce is still in its infancy, as most studies thus far have offered descriptions of livestreaming and consumer behavior (see Table 1). Based on the C-A-C framework, this paper examines consumers’ purchase intentions by studying their internal influences and external influences, both of which generate trust in streamers.
Table 1. Literature review and summary related to livestreaming commerce.
Literature Internal Impact External Influence Attitude Trust Theory Context
Zhang et al. [14] √ √ × × Affective-cognitive framework Livestreaming
Wu et al. [15] √ √ × × Competitive arousal model Online shopping
Chen et al. [16] √ √ × × Dual-process theory Livestreaming
Wongkitrungrueng et al. [17] × √ × × Sales orientation and online relationship marketing Livestreaming
Kang et al. [18] × √ × × S-O-R theory Livestreaming
Wongkitrungrueng and Assarut [10] × √ × √   Social commerce
Lu et al. [20] × √ × √ Social presence theory Social commerce
Lu and Chen [9] × √ × √ Signaling theory Livestreaming
Park and Lin [21] × √ √ √ Match-up hypothesis Livestreaming
Zhang et al. [19] √ √ × √ Socio-technical system theory Social commerce
This Study √ √ √ √ C-A-C framework Livestreaming

3. C-A-C Framework

Research in the field of psychology can be categorized into three segments: cognition, affection, and conation [22][23][24]. McDougall argues that the purest instinctive behavior can be adequately described through the lens of these three aspects of the mental process, each of which relates to the behavior of something, from the realization of feelings to the execution of the act. Cognition is the process of knowing and understanding; it encompasses the reception of information and its processing [25]. Affection refers to the emotional interpretation of information or things; in other words, it pertains to how people feel about the information they perceive [25]. Meanwhile, conation is the connection to behavior on a cognitive and affective basis; it can be described as a person’s behavioral intention or the subjective probability that they will use an information system [25][26]. The progression from cognition to affection to conation is connected in a universal way to the outside, the system, and the senses. An important marker of cognition is its representation, and although the senses that provide this characteristic are mostly external, personal traits can also process emotions in different cognitions [27].
The C-A-C framework has been used as a basic theory in numerous past studies across different contexts. Dai et al. [28] developed the applicability of the C-A-C framework to the behavior of social media users from a cognitive-affective-conative perspective; Hsiao [29] used the C-A-C framework to investigate online content sharing behavior, describing Internet users’ perception of the internet, their emotions about the internet, and the intentions of these users when using the technology (i.e., online content sharing).
The present study applies a cognitive-affective-conative framework to explain the relationship between interactivity, product information, personal impulse, attitude towards livestreaming shopping, trust in the streamer, and purchase intention in the context of livestreaming commerce (see Figure 1).
Behavsci 13 00308 g001 550
Figure 1. Conceptual framework.
Consumer behavior typically consists of cognitive, affective, and conative aspects [30], although there are many studies that adopt a cognitive-affective-conative framework in the context of e-commerce [31][32][33]. Nonetheless, studies that account for consumers’ consumption behavior in livestreaming scenarios are rare. In the context of livestreaming shopping, cognitive factors are made up of consumers’ internal influences (personal impulses and attitudes towards livestreaming shopping) and external influences (interactivity and product information). Based on the fact that trust is related to affective factors, trust in the streamer is used as an effective factor. Conative factors consist of purchase intention.

This entry is adapted from the peer-reviewed paper 10.3390/bs13040308

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