scholarly journals The Effect of Social Network Services Determinants on Word Of Mouth

2015 ◽  
Vol 24 (1) ◽  
pp. 1-25
Author(s):  
Hua Wei ◽  
Kyungmin Kim
2020 ◽  
Vol 12 (11) ◽  
pp. 4339 ◽  
Author(s):  
Taesoo Cho ◽  
Taeyoung Cho ◽  
Guosong Zhao ◽  
Hao Zhang

Today, social network services (SNS) advertising is frequently utilized by enterprises to communicate with consumers as it provides the best marketing effect using low-cost media. Since the value of SNS is increasing, managers need to look for more effective methods of utilizing the existing SNS channels. This study aims to provide suggestions for attracting customers and gaining an advantage amid the stiff competition among similar golf courses. To achieve the goal of this study, a questionnaire-based survey was conducted at six golf resorts in South Korea where SNS advertising has been used to enhance consumer experiences. The study found that SNS advertising and online word of mouth regarding golf resorts have a positive effect on emotive, social, and price values. Moreover, SNS advertising for golf resorts had a positive effect on the quality function value, while online word of mouth had no effect.


Kybernetes ◽  
2013 ◽  
Vol 42 (8) ◽  
pp. 1149-1165 ◽  
Author(s):  
Jorge Arenas-Gaitan ◽  
Francisco Javier Rondan-Cataluña ◽  
Patricio Esteban Ramírez-Correa

KBM Journal ◽  
2020 ◽  
Vol 4 (2) ◽  
pp. 147-165
Author(s):  
Nam-Goo Park ◽  
Jung-Min Lee

2021 ◽  
Vol 11 (6) ◽  
pp. 2530
Author(s):  
Minsoo Lee ◽  
Soyeon Oh

Over the past few years, the number of users of social network services has been exponentially increasing and it is now a natural source of data that can be used by recommendation systems to provide important services to humans by analyzing applicable data and providing personalized information to users. In this paper, we propose an information recommendation technique that enables smart recommendations based on two specific types of analysis on user behaviors, such as the user influence and user activity. The components to measure the user influence and user activity are identified. The accuracy of the information recommendation is verified using Yelp data and shows significantly promising results that could create smarter information recommendation systems.


2014 ◽  
Vol 71 (6) ◽  
pp. 2035-2049 ◽  
Author(s):  
Feng Jiang ◽  
Seungmin Rho ◽  
Bo-Wei Chen ◽  
Xiaodan Du ◽  
Debin Zhao

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