Jia Chen, Gang Kou, Yi Peng, Xiangrui Chao, Feng Xiao and Fawaz E. Alsaadi
Social media commerce provides a convenient way for users to share information and interact with each other. Few studies, however, have examined the effect of marketing messages…
Abstract
Purpose
Social media commerce provides a convenient way for users to share information and interact with each other. Few studies, however, have examined the effect of marketing messages and consumer engagement behaviors on the economic performance of marketing. This study, therefore, explored the economic performance of social media in terms of marketing messages and consumer engagement.
Design/methodology/approach
Using ordinary least squares regression and data collected from Weibo and Maoyan, this study analyzed the effects among marketing messages, consumer engagement and movie ticket sales.
Findings
The results indicated that marketing messages on Weibo had a positive effect on box office revenues, while consumer engagement behavior (whether personal or interactive) did not affect box office revenues. The results suggested that marketing messages on social media have more salient effects for predicting economic performance than consumer engagement behaviors.
Originality/value
This study underscores the importance of social media in consumer purchasing behavior. The findings also extend the literature related to commerce and product message design on social media platforms.
Details
Keywords
Zhongwen Cao, Liang Zhang, Adil M. Ahmad, Fawaz E. Alsaadi and Madini O. Alassafi
This paper aims to investigate an adaptive prescribed performance control problem for switched pure-feedback non-linear systems with input quantization.
Abstract
Purpose
This paper aims to investigate an adaptive prescribed performance control problem for switched pure-feedback non-linear systems with input quantization.
Design/methodology/approach
By using the semi-bounded continuous condition of non-affine functions, the controllability of the system can be guaranteed. Then, a constraint variable method is introduced to ensure that the tracking error satisfies the prescribed performance requirements. Meanwhile, to avoid the design difficulties caused by the input quantization, a non-linear decomposition method is adopted. Finally, the feasibility of the proposed control scheme is verified by a numerical simulation example.
Findings
Based on neural networks and prescribed performance control method, an adaptive neural control strategy for switched pure-feedback non-linear systems is proposed.
Originality/value
The complex deduction and non-differentiable problems of traditional prescribed performance control methods can be solved by using the proposed error transformation approach. Besides, to obtain more general results, the restrictive differentiability assumption on non-affine functions is removed.