Chuang Wei, Zhao-Ji Yu and Xiao-Nan Chen
This paper aims to solve the problem of information overload and reduce search costs. It proposes a social e-commerce online reputation formation model and community…
Abstract
Purpose
This paper aims to solve the problem of information overload and reduce search costs. It proposes a social e-commerce online reputation formation model and community state-introduced model. A system dynamics trend simulation has been run to capture the relationship among the sellers, buyers, social e-commerce platforms and external environment to obtain an online reputation.
Design/methodology/approach
Empirical research relating to social e-commerce reputation has been used to confirm the influencing factors in social e-commerce, and a conceptual framework is developed for social e-commerce reputation formation. Thereafter, a trend simulation is generated to classify the relationship among the factors based on system dynamics. Also, the improved algorithm for community detection and a state-introduced model based on a Markov network are proposed to achieve better network partition for better online reputation management.
Findings
The empirical model captures the interaction effect of social e-commerce reputation and the state-introduced model to guide community public opinion and improve the efficiency of social e-commerce reputation formation. This helps minimize searching cost thereby improving social e-commerce reputation construction and management.
Research limitations/implications
There is no appropriate online reputation system to be constructed to test the relationship proposed in the study for a field experiment. Also, deeper investigation for the nodes’ attributes in social networks should be made in future research. Besides, researchers are advised to explore measurement for the reputation of a given seller by using social media data as from Twitter or micro blogs.
Originality/value
Investigations that study online reputation in the social e-commerce are limited. The empirical research figured out the factors which can influence the formation of online reputation in social e-commerce. An SD model was proposed to explain the factors interaction and trend simulation was run. Also, a state-introduced model was proposed to highlight the effect of nodes’ attributes on communities’ detection to give a deeper investigation for the online reputation management.
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Min Lin, Yi Wang and Guisheng Wu
The purpose of this paper is to find the specific competitive industries in emerging industries of strategic importance of each province in China in order to provide references…
Abstract
Purpose
The purpose of this paper is to find the specific competitive industries in emerging industries of strategic importance of each province in China in order to provide references for industrial cultivation and development.
Design/methodology/approach
This paper uses quantitative analysis methods on RCA and R&D efficiency.
Findings
Different provinces have specific competitive emerging industries of strategic importance. Taking biotechnology, equipment manufacturing, and new generation of information technology industry as examples, this paper finds: for the advanced equipment manufacturing industry, Shaanxi, Sichuan, Guizhou, Tianjin, Liaoning, Heilongjiang and Jiangxi provinces have obvious characteristics and relatively high R&D efficiency; for bio‐technology, Jiangsu, Henan, Jiangxi, Hunan, Zhejiang and Shandong provinces have obvious characteristics and relatively high R&D efficiency; and for the next generation of the information technology industry, Jiangsu, Guangdong, Fujian, Beijing, Tianjin and Shanghai provinces have obvious characteristics and relatively high R&D efficiency.
Research limitations/implications
This study is limited by lack of industrial comprehensiveness so that more statistical data about emerging industry of strategic importance is needed for more in‐depth analysis.
Practical implications
The identification of specific competitive emerging industry of strategic importance of each province will give managers and policy makers train of thought for the cultivation and development of strategic emerging industry and make future policies more targeted.
Originality/value
The paper contributes to the research on the differentiated cultivation and development tactics of strategic emerging industry by, respectively, finding out the specific competitive emerging industries of each province in China.