Research on the return of e-commerce live broadcast

: This paper introduces the current situation of high return rate in live broadcasts, then analyzes the reverse logistics articles of related e-commerce platforms, and finds that only a small number of authors focus on the return problem in live broadcasts. In order to reduce the return rate of live broadcasts, this paper starting with consumers, enterprises, and live broadcast anchors, analyzes their problems of returning goods in live broadcasts and then stands in their perspective to solve the problem of high return rate in live broadcasts.


Introduction
In the post-epidemic era, more and more people choose to shop online without leaving their homes. Live ecommerce, an online shopping model that minimizes the risk of people contracting the virus, is widely used. Unlike traditional e-commerce sales, live e-commerce is mainly used to attract customers' purchases through herd behaviour and celebrity effects [1] [2]. The herd behaviour comes from the biological study of animal flocking characteristics. A flock is a dispersed organization that usually stumbles blindly together, but once one head sheep moves, the others will move without thinking, regardless of whether there are wolves ahead or better grass not far away [3]. For example, when Little Red Book users see that a very influential blogger they follow has recommended a product, they tend to scramble to buy it. The celebrity effect is a means of using the social influence of celebrities to leverage marketing. Because of the influence and appeal of celebrities to the public, it has a subtle impact on the psychology of the audience, and the effect is often more effective and direct [4]. In live streaming, the celebrity effect is equivalent to a new branding effect that can drive crowds, especially attracting those who follow celebrities. The close interaction between the celebrity and the consumer, the detailed explanation of the celebrity on the goods sold, and the high trust and blind following of the celebrity on the brand greatly stimulate and enhance the consumers' desire to buy. These two effects tend to drive consumers to irrational consumption, triggering them to make returns due to regretful impulsive consumption. Many articles focus on the benefits of live e-commerce or explore this new e-commerce marketing model. They see live e-commerce as a new platform to connect shopping with user consumption scenarios. Nevertheless, there are many problems with live e-commerce, for example, the experience of buying products on-site is not as good as in offline shops. The poor experience leads to a high return rate for users. The return rate even reaches 60% to 70% [5], so this article wants to explore why such a high return rate for live e-commerce and suggest solutions accordingly. By focusing on a series of reverse logistics services in live e-commerce, this paper hopes to address the issue from three perspectives: consumers, sales anchors, and enterprises, to improve the return reverse logistics services across e-commerce platforms and solve the problem of high return rates. The remainder of the paper is organized as follows. Section 2 is the literature review, while section 3 presents the discussion of solutions.

Literature Review
E-commerce is booming under the epidemic, but returns are becoming increasingly important for merchants. Many scholars have studied the problems related to the reverse logistics of e-commerce platforms. ( [6][7] [10]). For example, Zhang and Hu [6] studied the shortcomings of the reverse management model of a wide range of ecommerce platforms and proposed optimization strategies. Using JD.com as an example, Yuan [7] investigated reverse logistics distribution and labour cost control. When e-commerce needs new tools to attract traffic and realize cash to break bottlenecks, live streaming has emerged to empower traditional e-commerce, enabling the integration of live streaming and e-commerce. It has shaped an intuitive "online + offline" virtual shopping experience, breaking the bottleneck that has constrained the development of traditional e-commerce. This paper is also related to reverse logistics under the ecommerce platform. The development of e-commerce reverse logistics in China is not stable enough. First, ecommerce enterprises generally do not pay enough attention to reverse logistics. In the daily management of e-commerce enterprises, how to attract customer traffic and increase sales through marketing means is the focus of attention, much time and various resources are invested in this, while reverse logistics is a part of the enterprise to ensure regular operation only when there are quality problems with the goods or errors in the delivery [8]. Secondly, the reverse logistics caused by the return and exchange behaviour is unpredictable. As the consumer is the initiator of the return behaviour, and there are many consumers in online shopping, it is unpredictable whether the product can meet the consumer's needs, and therefore the return behaviour is unpredictable. Moreover, consumers are located in different regions and use different logistics methods, resulting in unpredictable development of return reverse logistics and unpredictable use of logistics resources, bringing obstacles to the coordinated development of return reverse logistics. Finally, the e-commerce business competition is fierce, and logistics resource allocation is duplication. Ecommerce economic prosperity can not be separated from all walks of life, large and small businesses, however, in the e-commerce industry, commodities are often homogenized seriously, the number of businesses of the same product, and thus the competition between businesses is fierce. In the fierce competition, merchants put more money and effort into publicity and invest less in the allocation of logistics resources. And the logistics resources allocation between different merchants is not effectively integrated, resulting in duplication of reverse logistics resource allocation and low operational efficiency [9]. Currently, research on live returns is not carried out on a large scale, and people still focus on the traditional ecommerce returns problem, but some people have started to explore the reasons behind the high rate of live ecommerce returns, with the paper by Wu and Yan [10] being the closest to ours. Based on the SOR (Stimulus-Organism-Response) model, Wu and Yan [10] found through a questionnaire study that live-streaming interactions enhanced consumer identification with their high degree of visibility and emotional experience which led to impulsive buying behaviour. Furthermore, the likelihood of consumers' return behaviour using live streaming return services was greatly enhanced due to the fear of making a wrong choice and regretting it. Notably, their article explores the reasons for the high return rate from the consumer's perspective. Most previous articles have examined the flaws in the reverse logistics process of e-commerce platforms, so this article will continue to explore the causes of high return rates in live e-commerce and propose solutions from the company, the anchor, and the consumer.

Discussion of solutions
In order to solve the problem of high return rates in live streaming, the next step is to think about how to reduce the return rate in live streaming from the perspective of three subjects: consumers, companies and anchors.

Target group: Consumers
Consumers tend to spend irrationally and impulsively and follow the trend because of the substantial discounts on live goods and trust in the anchor/celebrity. However, after getting the item, consumers will return it because the online experience is so different from how it feels in person that consumers will have regrets and want to return it [11]. For consumers, most returns are at their own expense, except for some merchants who offer a "seven-day noquestions-asked return" service. Consumers can return goods by courier or at a post, but whichever method they use, they need to plan their own return time, which in effect has a time cost. Finally, consumers must wait for the merchant to confirm that they have received the goods in good condition and are ready for secondary sale. For example, if a consumer wants to return a fresh product purchased live, it is difficult to guarantee that the goods returned to the merchant will be the same as those bought at the time. Consumers should maintain essential judgement when shopping on the spot, don't follow the crowd, develop their ability to think independently, gather information, judge keenly, reduce blind obedience behaviour and use more of their rational thinking and judgement. For example, when buying a piece of clothing, it is important to consider not only the price of the clothing and whether the clothing is necessary, but also careful considerations such as whether the fabric is exquisite, whether it suits your figure and whether you will regret getting it in your hands. What's more, if you need to return the goods, the potential time cost of logistics, such as their need to take time to go to the post or need to wait at home for a series of process times such as courier door-to-door. So consumers need to ask themselves questions in their minds before considering whether or not to buy goods in the live room.

Target group: Companies
The live-streaming industry has become a significant avenue for consumers to shop and, as a result, an important channel for companies to sell. Live streaming is a new form of face-to-face communication with audiences, and an excellent live stream not only brings objective sales to brands but also allows consumers to experience the unique appeal of a product visually and indepth. However, companies often focus only on the flow economy of their products, spending much money on celebrities and anchors while neglecting the quality control of their products. For businesses, live returns, let the business sales profits affected, would have sold the goods now returned, of course, affect the revenue. Secondly, the consumer to the enterprise returns more, the enterprise return rate increases, and the enterprise ranking will fall, leading to collapse of the enterprise live search volume. And, consumers who make returns will give a bad conclusion and evaluation on the business, affecting the subsequent purchase of potential consumers. Live returns will also affect the business's judgement of its own products, such as selling out and adding some inventory and returning them to find that there is too much inventory pressed into the warehouse, thus incurring additional inventory costs. Finally, there are some potential losses to the business from live-streaming returns, such as advertising expenses, courier costs, manual operation costs and some other losses that are difficult to calculate. Companies must first do a good job of controlling the quality of their goods, especially in the production process. It is only after a short period of traffic gathering that consumers will continue to buy high-quality goods. Secondly, companies should live within their means, choose quality anchors and hire spokespeople who fit the comprehensive image of the brand, rather than just pursuing traffic. Enterprises should discard those anchors who falsify data and evade taxes in the live broadcast, choose those with strong live business ability and legal compliance, and take some measures to circumvent the act of swiping. For example, enterprises should state at the beginning of the contract with the anchor that all falsification is prohibited and bundle the final sales result of the live broadcast with the commission of the anchor. Finally, companies should seize the market trend and choose high-quality and suitable spokespersons, not necessarily traffic stars, such as the sponsor of Mengniu in the Beijing Winter Olympics, who chose skiers who have won glory for their country as spokespersons [12].

Target group: Anchors
In addition to providing some advice for consumers and businesses, this paper has also considered how to discipline the lead anchors in the live stream to reduce the return rate of products. The income of the anchor is mainly based on the "entrance fee", and the commission fee of the actual transaction amount, which depends on the popularity of the live broadcast and the number of orders placed [13]. The amount of money ordered and other data. Some anchors choose to sell fake products and take advantage of legal loopholes to make more money [14]. More than consumers, anchors need to remain rational. Firstly anchors should not bid in bad faith. When invited by a brand to bring in goods, there is an 'entry fee', and anchors should be reasonably clear about their ability to bring in goods. Anchors who offer sky-high "entry fees" but end up with low volumes will start to falsify order volumes, leading to high return rates, and this behaviour can disrupt the live market. For this reason, the first unique self-regulatory code on online video marketing activities issued by the China Advertising Association -the "Code of Conduct for Live Webcast Marketing" -stipulates several prohibited behaviours in live broadcast, does not stipulate the consequences of non-compliance, and its implementation relies mainly on the self-discipline of the subjects in the industry and is not mandatory [15]. Secondly, anchors should put themselves in consumers' shoes, rejecting fake goods and focusing on improving their ability to bring in goods. When choosing goods for live streaming, anchors should do their research to avoid quality testing problems with the goods they bring. Finally, anchors should cut themselves to improve their ability to bring goods and should be comprehensive and practical when introducing goods, rather than just praise.

Conclusion
Focusing on the high return rate in live streaming, this study has analyzed the reasons behind the high return rate in live streaming and explored solutions to the high return rate from consumers and anchors in addition to the widely discussed enterprise perspective. This paper has addressed three questions, including the phenomenon of high return rate in live streaming, the reasons for high return rate research in e-commerce studied by scholars in the past, and the solutions to high return rate in live streaming summarized from three parties: consumers, enterprises, and e-commerce anchors. This study has several limitations, as it does not use some data models to explain how the herd effect and the celebrity effect specifically work for e-commerce live streams. Although my findings provide ideas to address the high returns of live streaming, more empirical research on the psychology of consumers in live streaming is needed, and in the future, I will use crawlers to mine the data and conduct questionnaires on live streaming consumers to further test and refine these findings.