Influence Mechanism of Mobile Social Network Users’ Product Recommendation Information on Consumers’ Intention to Participate Sharing Economy

2021 ◽  
pp. 106-112
Author(s):  
Ying Dong ◽  
Li Dong
Keyword(s):  
Social Network ◽  
Sharing Economy ◽  
Mobile Social Network ◽  
Product Recommendation ◽  
Influence Mechanism ◽  
Intention To Participate

scholarly journals Young Consumers’ Intention to Participate in the Sharing Economy: An Integrated Model

2021 ◽  
Vol 13 (1) ◽  
pp. 430
Author(s):  
José Alberto Martínez-González ◽  
Eduardo Parra-López ◽  
Almudena Barrientos-Báez
Keyword(s):  
Social Norm ◽  
Structural Model ◽  
Causal Model ◽  
Sharing Economy ◽  
Internal Variables ◽  
Critical Variable ◽  
Generation Z ◽  
External Variables ◽  
Young Consumers ◽  
Intention To Participate

This paper aims to analyze the external and internal drivers of young consumers’ intention to participate in the sharing economy in tourism. From previous findings, a causal model (PLS) is designed to generate an integrated, practical, and novel structural model that significantly predicts the intention to participate. The model, consisting of nine dimensions, includes consumers’ external and internal variables. Separately, these variables have all been considered relevant in the literature, though they have not been studied jointly before. The descriptive results show the excellent attitude and predisposition of young people toward the tourism sharing economy, which facilitates their participation. Through the model, the importance of all internal and external consumer variables in the formation of intention are proven; however, attitude and social norm are most notable among them. Trust is also a critical variable that serves as the link between internal and external variables. The study provides managers of sharing economy platforms with knowledge to encourage young consumers’ participation in a communication and market orientation context. The generational approach (Generation Z) used also allows the conclusions and implications to be transferred to other regions and sectors.

scholarly journals PRUB: A Privacy Protection Friend Recommendation System Based on User Behavior

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Wei Jiang ◽  
Ruijin Wang ◽  
Zhiyuan Xu ◽  
Yaodong Huang ◽  
Shuo Chang ◽  
...  
Keyword(s):  
Social Network ◽  
Recommendation System ◽  
User Behavior ◽  
Network Services ◽  
Mobile Social Network ◽  
Fine Grained ◽  
Friend Recommendation ◽  
Social Applications ◽  
Browsing Behavior ◽  
Behavioral Information

The fast developing social network is a double-edged sword. It remains a serious problem to provide users with excellent mobile social network services as well as protecting privacy data. Most popular social applications utilize behavior of users to build connection with people having similar behavior, thus improving user experience. However, many users do not want to share their certain behavioral information to the recommendation system. In this paper, we aim to design a secure friend recommendation system based on the user behavior, called PRUB. The system proposed aims at achieving fine-grained recommendation to friends who share some same characteristics without exposing the actual user behavior. We utilized the anonymous data from a Chinese ISP, which records the user browsing behavior, for 3 months to test our system. The experiment result shows that our system can achieve a remarkable recommendation goal and, at the same time, protect the privacy of the user behavior information.

scholarly journals Examining Cross-Industry Collaboration in Sharing Economy Based On Social Exchange and Social Network Theories

2020 ◽  
pp. 29-41
Author(s):  
Cheng-Wen Lee ◽  
Hao-Yuan Yu
Keyword(s):  
Content Analysis ◽  
Social Network ◽  
Social Exchange ◽  
Service Providers ◽  
Secondary Data ◽  
Sharing Economy ◽  
Jel Classification ◽  
Industry Collaboration ◽  
Multiple Case ◽  
The Cost

Information technology and advanced online environments have reduced the cost of these exchange activities and triggered the emergence of the sharing economy. Con-sequently, public attitude toward the sharing economy has gradually shifted from re-luctance to acceptance. Moreover, the sharing economy has revolutionized the busi-ness models and viewpoints of conventional industries, and sharing service providers have gradually shifted from an independent to a collaborative stance, thereby affect-ing conventional economies. This study interprets the phenomenon of cross-industry collaboration in the sharing economy through social exchange and social network the-ories. A multiple-case research framework is used to examine tourism and service in-dustries. Secondary data of service providers and users on sharing platforms are ana-lyzed using content analysis, supplemented with a content analysis of the interview data of three hotel executives. The varying phenomena of the conventional and shar-ing economies on social exchange and social network were compared. Finally, this paper proposes conclusions and practical recommendations according to the analytical results. JEL classification numbers: D85, M31, L14. Keywords: Cross-Industry Collaboration, Sharing Economy, Social Exchange, Social Network.

scholarly journals Cooperation Dynamics on Mobile Crowd Networks of Device-to-Device Communications

2016 ◽  
Vol 2016 ◽  
pp. 1-10
Author(s):  
Yong Deng ◽  
Guiyi Wei ◽  
Mande Xie ◽  
Jun Shao
Keyword(s):  
Social Network ◽  
Resource Sharing ◽  
Evolutionary Game ◽  
Influence Factors ◽  
Smart Devices ◽  
Mobile Social Network ◽  
Crowd Density ◽  
Cooperation Rate ◽  
Cooperative Behaviors ◽  
Mobile Crowd

The explosive use of smart devices enabled the emergence of collective resource sharing among mobile individuals. Mobile users need to cooperate with each other to improve the whole network’s quality of service. By modeling the cooperative behaviors in a mobile crowd into an evolutionary Prisoner’s dilemma game, we investigate the relationships between cooperation rate and some main influence factors, including crowd density, communication range, temptation to defect, and mobility attributes. Using evolutionary game theory, our analysis on the cooperative behaviors of mobile takes a deep insight into the cooperation promotion in a dynamical network with selfish autonomous users. The experiment results show that mobile user’s features, including speed, moving probability, and reaction radius, have an obvious influence on the formation of a cooperative mobile social network. We also found some optimal status when the crowd’s cooperation rate reaches the best. These findings are important if we want to establish a mobile social network with a good performance.

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