Optimal live streaming strategy of online retailer considering online reviews

Live streaming selling strategies of online retailers with spillover effects

Accepted by: Aris Syntetos The rapid expansion of e-commerce has led many businesses to adopt live streaming as a means to enhance product sales. This paper investigates two adoption strategies: one involving manufacturers implementing the live streaming, and the other where retailers utilize the live streaming. Additionally, we also consider two live streaming modes: live streaming agency mode and self-built live streaming mode. Based on different introducers and live streaming modes, there exist four scenarios: (i) the manufacturer introduces the live streaming agency mode; (ii) the retailer introduces the live streaming agency mode; (iii) the manufacturer establishes his own live streamer and (iv) the retailer establishes her own live streamer. We build theoretical models to derive and analyze the equilibrium outcomes across four distinct scenarios. Our results show that consumers may not always benefit from the live streaming since the retail price under this channel may be higher than that under the traditional channel. Given the introducer of the live streaming, the manufacturer and the retailer can achieve a win–win situation. From the perspectives of the entire supply chain and consumer surplus, the optimal strategy is that the manufacturer implements the self-built live streaming mode. These primary findings remain the same in the presence of spillover effects. Our study is of significant value to business practices.

With the rising popularity of live video streaming in recent years, it has begun to attract interest from both e-commerce practitioners and the research community. However, there is scarce academic research in understanding whether and how live video streaming affects the landscape of e-commerce. In this paper, we seek to understand the effects of the adoption of live video streaming strategy by online retailers and their online product sales. Leveraging multiple archival data sources, we combine econometrics with deep learning to test the hypotheses. The results indicate that adopting live video streaming strategy significantly boosts online product sales. Furthermore, we propose a novel deep learning framework to address the challenge of identifying product-oriented live video streaming, and find that the adoption of a product-oriented live video streaming strategy increases online product sales, whereas there is no significant impact for adopting non-product-related live video streaming strategy. In the meanwhile, the impact of product-oriented live videos is attenuated as the buyers’ uncertainty decreases. These results provide empirical support that reduction in product uncertainty via information provision is the main mechanism through which live video streaming increases online sales.

Strategic live streaming choices for vertically differentiated products

The adoption of live streaming channel considering impulse buying and product returns

Live streaming strategy under multi-channel sales of the online retailer

We investigate strategy choice of sales format considering online reviews and the spillover effect in a dual-channel supply chain. Generally, online and offline consumers read online reviews before purchasing, and thus offline retailers will be subjected to the spillover effect of online reviews. We develop joint product quality and service level decision models in reselling and agency selling with online reviews and the spillover effect. There are some interesting findings: first, the optimal service level and product quality increase with online reviews and spillover effect. Second, counterintuitively, the spillover effect of online reviews benefits not only the offline retailer and manufacturer but also the online retailer in some circumstances. Moreover, the win-win sales format for the manufacturer and online and offline retailers exists in some circumstances. Finally, it is interesting to find that consumers’ channel preference in the agency sales format is more important than in the resales.

Abstract: With the rapid development of e-commerce, an increasing number of companies, such as Huawei, Apple, and Adidas, are no longer confined to offline physical stores for product sales. They leverage third-party e-commerce platforms or establish online stores on their official websites. Modern consumers have access to various purchasing channels, including e-commerce platforms, offline stores, and manufacturer direct sales. In recent years, a new e-commerce model, live streaming sales, has emerged. In live streaming sales, professional salespersons or key opinion leaders (KOLs) showcase product performance, aiming to sell products online. Unlike traditional online channels, live streaming sales alleviate new consumers' uncertainty about product information through real-time interaction or comments from KOLs. Live streaming has been adopted by e-commerce giants worldwide, such as Taobao, JD.com, and Amazon, due to its significant sales revenue potential. Additionally, channels with KOLs may generate negative or positive spillover effects on other channels. These effects are crucial parameters for exploring the impact of seller profits in the multi-channel supply chain under live streaming conditions. Both domestic and international research have focused on live streaming sales, multi-channel sales, and spillover effects, with many studies yielding significant economic and social benefits. However, challenges faced by multi-channel supply chains, including complex channel management, difficulty in information synchronization, brand consistency issues, and increased costs, need to be addressed. To overcome these challenges, recommendations include integrating channel resources, optimizing channel experience, establishing cross-channel data analysis systems, strengthening supply chain coordination, continuous innovation and improvement, and strengthening brand building.

In the context of virtual anchors as a supplement to human anchors in live streaming e-commerce. In this paper, for the first time, virtual anchors are included in the live streaming mode selection strategy, combined with the characteristics of the live streaming anchor and the cost of live streaming, constructed a model of the four live streaming modes, and used the Stackelberg game method to study. The results show that: (1) live streaming prices are positively correlated with cross price elasticity coefficient, market share of live streaming channels and consumer sensitivity to live streaming e-commerce. (2) When the cross price elasticity coefficient or market share of live streaming channels is small, the influence of influencer anchors can attract more consumers to purchase products, and the influencer anchor live streaming mode is the optimal choice; When the cross price elasticity coefficient or market share of live streaming channels is large, the merchant combined with virtual anchors live streaming mode is the optimal choice due to the low cost of live streaming for merchant staff anchors, as well as the advantage of continuous live streaming for virtual anchors. (3) When the consumer sensitivity to live streaming e-commerce is small, due to the low cost of live streaming for merchant staff anchors, the merchant live streaming mode is the optimal choice; When the consumer sensitivity to live streaming e-commerce is large, based on the influence of influencer anchors and the advantage of continuous live streaming for virtual anchors, the influencer anchor combined with virtual anchors live streaming mode is the optimal choice.

In recent years, live streaming is becoming a popular channel to sell products all over the world. Compared to traditional e-commerce channel, live streaming channel may not only bring consumers more shopping convenience, but also pose consumers more privacy concern. This paper considers a supply chain consisting of a manufacturer and an e-tailer who sells through dual channels (i.e., live streaming and traditional e-commerce) to explore how shopping convenience and privacy concern affect the optimal decisions. We build game models of two pricing (exogenous and endogenous) and two incentive contracts (wholesale price and two-part tariff). We find that the optimal promotion efforts are decreasing in shopping convenience while increasing in privacy concerns under the wholesale price contract, and independent of them under the two-part tariff contract when pricing is not a decision (such as iPhone); the optimal promotion efforts are increasing in shopping convenience while decreasing in privacy concern when pricing is a decision (such as the seasonal products). Whether the retail pricing is a decision or not, supply chain coordination can be achieved by the two-part tariff contract, but not through the wholesale price contract. Further, the two-part tariff contract is more favorable to the manufacturer if the exogenously given retail price is low, and the wholesale price contract is more favorable to the manufacturer if the retail price is high; the two-part tariff contract is always more beneficial for the supply chain than the wholesale price contract. Finally, we extend our analysis to relax a more realistic form with a variable effort elasticity and verify the robustness of the theoretical results.

Consumers increasingly rely on online reviews to help them make consumption decisions. Meanwhile, online reviews also facilitate the comparison of product information. Consumers typically pick one from a bunch of similar products by comparing available product information rather than only consider the items they finally purchase. Therefore, the information about one product could affect consumers’ perception of related products, which is known as information spillover. Understanding the spillover effect is significant for businesses to have a full picture of the influence of online reviews. Although recent research has shown significant interest in exploring the spillover effect, especially those from marketing campaigns, little has been known on the spillover effect caused by online reviews. This research aims to study the spillover effect of online WOM among competitive products and the moderating effect of brand strength and brand relationship based on the accessibility-diagnosticity theory. Using the cutting-edge Bayesian dynamic linear model, this empirical analysis disassembles the influence of reviews into a two-stage dynamic process. At the first stage, online reviews of different valence influence consumers’ latent interest in products, which can be seen as online WOM from the perspective of product providers. Consumers’ latent interests in different products influence each other, during which the spillover effect occurs. At the second stage, the change of such latent interests affects the performance of a product in the end. Using the check-in data of the catering industry provided by a location-based service company, this research finds that online reviews have a negative WOM spillover effect among competitive brands. In other words, the increase of online WOM of one product will damage the performance of its competitors. This negative spillover is asymmetric among products with different brand strength. Products with higher brand strength have a larger spillover effect on products with lower brand strength, while they get less affected by other brands. Products sharing the same brand name could generate value transfer and have a positive spillover effect among each other. What’s more, despite of the resistance to the negative spillover from competitive brands, strong brands suffer more loss from their negative WOM. Therefore, it is especially important for them to maintain positive online WOM. This study makes three main theoretical contributions. Firstly, previous studies tend to focus only on the direct effect of online reviews on product performance, while this research discusses its spillover effect based on the accessibility-diagnosticity framework, expanding the perspectives on the effect of online reviews. Secondly, this research emphasizes the important role that brands play in the online environment and provides a new angle to analyze the interaction of traditional business characteristics and the online environment. Although social media has dramatically changed the way how a business reaches its customers, building a strong brand is still crucial to gain competitive advantages. Thirdly, this research examines and discusses how reviews of different valence affect online WOM and how this effect differs among brands, contributing new empirical evidence to the usefulness of online reviews.

Content providers in online social media platforms, particularly live streaming, often switch content categories. Despite the uniqueness and importance, there is a dearth of academic research examining the unintended effects of providers’ content switching. We study the direct and indirect spillover effects of content switching for live streamers--individuals who broadcast content through live streaming platforms. We propose a framework based on theories related to viewer flow and network effects to conceptualize the direct and indirect spillover effects of entrant streamers’ content switching on the incumbent streamers. Contrary to conventional wisdom which concerns about the negative effects on the incumbent’s viewership due to network congestion, we propose two positive spillover effects that are unique to the social media platform setting: a) the entrant streamers not just increases network congestion, but they also bring their own viewers to the new category, which benefit the incumbent streamers due to a streaming flow effect (direct spillover); and (b) the entrant streamers influences incumbent streamers’ viewer size by boosting category visibility through indirect network effects (indirect spillover). We also propose that the two spillover effects are contingent on the size of the entrant streamers’ follower base. Based on a unique observational dataset from the leading live streaming platform (Twitch.tv), particularly with viewer flows data at the streamer-session level, we first estimate that an average content switching is associated with a 1.3% net increase in direct net viewer flow from the entrant to an incumbent. And this direct spillover effect is attenuated by the size of entrant streamers’ follower base. We also estimate that an average content switching is associated with a 2.1% net increase in (indirect) net viewer flow from outside categories to an incumbent streamer. And this indirect spillover effect is reinforced by the entrant streamers’ follower base size. This study contributes to the emerging literature on the dynamics of content switching on social media platforms in the emerging context of live streaming. We discuss the managerial implications of this study for streaming strategies and platform management.

PurposeThe rapid growth of live streaming has intensified competition among streamers. A key challenge lies in aligning live-streaming sales strategies with consumer needs to cultivate positive consumer attitudes.Design/methodology/approachDrawing on theories of the types of consumer–live streamer interaction strategies, the uses and satisfaction theory, the channel complementarity theory and the congruence hypothesis of live streaming content and online reviews, this study employs quantitative research to investigate how to effectively integrate genuine product feature preferences, as reflected in online reviews, with key messages conveyed by live streamers. To achieve the objective, this paper synthesizes machine learning techniques – including information quantity calculation and BERT – with statistical analysis methods such as difference testing and scenario experiments.FindingsThe results demonstrate that the proposed predictive model of perceived useful information, which relies on information quantity, provides notable advantages. Specifically, there is a significant disparity between consumer feature preferences derived from useful information and those identified through traditional methods that consider all available data. Moreover, feature preferences extracted from useful information diverge from the focal points of the live streamer’s actual explanations. The proposed method, which aligns consumer preferences with the live streamer’s explanations, markedly enhances consumers’ purchase intentions.Originality/valueThis study introduces a novel metric of information quantity to distinguish useful reviews from the broader dataset, integrating it with sentiment analysis and feature extraction techniques. Unlike traditional methods that treat all reviews as equally valuable, this approach prioritizes comments based on informational value, emotional tone and relevance to product features, providing a nuanced and precise understanding of consumer preferences. By aligning these preferences with live streamers’ explanations, the study offers a data-driven, consumer-centric strategy for improving product recommendations and engagement in live commerce. This comprehensive framework represents a significant advancement over traditional models reliant on data volume alone.

PurposeAs live streaming commerce becomes increasingly growing in the e-retailing environment, it is crucial to explore its role in enriching and expanding the e-servicescape model within e-retailing platforms. This paper seeks to enhance and extend the online retailing e-servicescape by integrating the dimensions specific to live-streaming e-commerce.Design/methodology/approachThis research employed a qualitative approach through in-depth interviews with 15 participants, focusing on their e-retail live-streaming experiences in China. This method provided valuable insights into the perceptions and experiences of individuals engaged in live streaming as an extension of the e-servicescape. Through thematic analysis, six dimensions of live streaming were identified as enrichments to the e-servicescape framework.FindingsThis paper proposes enriching the live-streaming dimension by introducing six sub-dimensions: attractiveness and authenticity, reliability and credibility, responsive lively interactions, social connectivity, celebrity influence and community consciousness. These sub-dimensions expand the e-servicescape within online retail platforms.Research limitations/implicationsIt is anticipated that the findings will offer significant perspectives on how online consumers evaluate the importance of live-streaming attributes in the changing dynamics of the e-servicescape.Practical implicationsBy exploring the importance of live-streaming and online purchasing experiences for customers, this insight can help create an online retail environment that is more engaging.Originality/valueTo the best of the authors’ knowledge, this is the first study that thematically enriches the e-servicescape by integrating the live-streaming dimension based on e-retailing. It provides a structured framework for future research to employ a quantitative approach to test the effectiveness of the enriched e-servicescape resulting from the integration of live-streaming commerce with consumers’ behavioural responses.

Purpose Live streaming e-commerce is an emerging e-commerce model within the realm of the mobile Internet, based on video-centric social media interaction. However, there is currently a lack of in-depth research on live streaming from a business perspective and the impact of product selection in live streaming on firm performance. To fill these gaps, the current study investigated how brand – consumer congruence moderates the influence of product selection in live streaming on firm performance and how this effect varies across retailers. Methodology/approach The model and hypotheses were tested by applying partial least squares regression to data collected from 302 online retailers in the Chinese live streaming market. Findings Product selection in live streaming had a significant positive impact on firm performance. Brand – consumer congruence in live rooms partially mediated the relationship between product selection and firm performance. Live room scenario matching and live room interaction had significant positive moderating effects on the main effect of product selection in live streaming on firm performance. Research implications The literature has focused on the impact of live streaming on customer purchase behavior. Few studies have explored the value of live streaming from a business-to-business marketing perspective. Our findings offer theoretical insights into the relationship between product selection and firm performance. Originality/value/contribution This is the first study to examine the value of product selection in live streaming. In addition, it reveals how product selection affects firm performance through brand – consumer congruence. Practical implications This study has implications for online retail managers based on the effect of product selection in live streaming on firm performance and the roles of brand – consumer congruence, interaction, and scenario in live streaming of business-to-business marketing.