Xiaoling Li, Zongshu Wu, Qing Huang and Juanyi Liu
This study develops an empirical framework to address how large third-party sellers (TPSs) can apply customer acquisition strategies to improve their performance in consumers’…
Abstract
Purpose
This study develops an empirical framework to address how large third-party sellers (TPSs) can apply customer acquisition strategies to improve their performance in consumers’ person-goods matching process and how the platform firm’s similar strategies moderate the effects of TPSs’ strategies.
Design/methodology/approach
Using data collected from the top ten TPSs from a Chinese e-commerce platform, the fixed effect model is used to validate the conceptual model and hypotheses.
Findings
The study results show that both market detection strategy and matching optimization strategy can help large TPSs improve their sales performance. Moreover, the similar market detection strategy applied by the platform firm weakens the effect of large TPSs’ customer acquisition strategies, while the similar matching optimization strategy applied by the platform firm strengthens the effect of large TPSs’ customer acquisition strategies.
Originality/value
This study provides firsthand evidence on the performance of large TPSs’ and the platform firm’s strategies. It demonstrates the effectiveness of large TPSs’ market detection strategy and matching optimization strategy, which can be adopted to meet consumers’ search and evaluation motivations in their person-goods matching process respectively. Moreover, it identifies the role of platform firms by showing the moderating effect of similar strategies adopted by the platform firm on the effect of large TPSs’ customer acquisition strategies.
Details
Keywords
The profound impact of the COVID-19 pandemic on the film industry has underscored the growing significance of online movies. However, there is limited research available on the…
Abstract
Purpose
The profound impact of the COVID-19 pandemic on the film industry has underscored the growing significance of online movies. However, there is limited research available on the factors that influence the viewership of online films. Therefore, this study aims to use the signaling theory to investigate how signals of varying qualities affect online movie viewership, considering both signal transmission costs and prices.
Design/methodology/approach
This study uses a sample of 1,071 online movies released on the iQiyi from July 2020 to July 2022. It uses OLS regression and instrumental variable method to examine the impact of various quality indicators on the viewership of online movies, as well as the moderating effect of price.
Findings
After conducting a thorough analysis of this study, it can be deduced that the varying impacts on online movie viewership are attributed to disparities in signal transmission costs. Specifically, star influence and rating exhibit a positive effect on the viewership of online movies, whereas the number of raters has a detrimental impact. Furthermore, there exists an “inverted U-shaped” relationship between the number of reviews and online movie viewership. Additionally, within the consumer decision-making process, both price-cost and price-quality relationships coexist. This is evident as prices negatively affect online movie viewership but positively moderate the relationship between rating, number of reviews and online movie viewership.
Originality/value
The research findings of this study offer valuable insights for online film producers to effectively leverage quality signals and pricing, thereby capturing market attention and enhancing film profitability.