scholarly journals Peran Viral Marketing Terhadap Kepercayaan Konsumen dan Keputusan Pembelian Melalui Media Promosi Akun Instagram @kuliner lampung

2021 ◽  
Vol 9 (4) ◽  
pp. 839
Author(s):  
Eka Yulianti ◽  
Herani Putri ◽  
Vicky F Sanjaya
Keyword(s):  

Penelitian ini bertujuan untuk menguji dan menganalisa Peran Viral Marketing Terhadap Kepercayaan Konsumen dan Keputusan Pembelian Melalui Media Promosi Akun Instagram @kuliner lampung. Penelitian ini menggunakan metode pendekatan kuantitatif Sampel yang digunakan dalam penelitian ini menggunkan pengisian kuesioner sebagai pengumpulan data, dengan jumlah responden yang bepartisipasi dalam penelitian ini sebanyak 66 responden Data yang terkumpul kemudian dianalisis dan diuji validitas, reabilitas dan uji hipotesis menggunakan program SmartPLS Hasil penelitian ini menunjukun bahwa viral marketing berpengaruh signifikan tehadap kepercayaan konsumen, viral marketing berpengaruh signifikan terhadap keputusan pembelian.

2019 ◽  
Vol 5 (5) ◽  
Author(s):  
Elena Gerasikova ◽  
Milena Ischenko ◽  
Olga Saenkova ◽  
Nataliya Yasenkova

2019 ◽  
Vol 118 (6) ◽  
pp. 97-99
Author(s):  
Arockia Jeyasheela A ◽  
Dr.S. Chandramohan

This study is discussed about the viral marketing. It is a one of the key success of marketing. This paper gave the techniques of viral marketing. It can be delivered word of mouth. It can be created by both the representatives of a company and consumer (individuals or communities). The right viral message with go to right consumer to the right time. Viral marketing is easy to attract the consumer. It is most important advertising to consumer. It involves consumer perception, organization contribution, blogs, SMO (Social Media Optimize), SEO (Social Engine Optimize). Principles of viral marketing are social profile gathering, Proximity Market, Real time Key word density.


2019 ◽  
Vol 7 (1) ◽  
pp. 103-107
Author(s):  
Yani Restiani Widjaja ◽  
Ruth Alexandra

2020 ◽  
Vol 31 (5) ◽  
pp. 231-247
Author(s):  
Kang Jun Choi ◽  
Soon Pyeong Kim ◽  
Jae Young Lee ◽  
Tae Hyung Pyo

2021 ◽  
Vol 54 (2) ◽  
pp. 1-36
Author(s):  
Fan Zhou ◽  
Xovee Xu ◽  
Goce Trajcevski ◽  
Kunpeng Zhang

The deluge of digital information in our daily life—from user-generated content, such as microblogs and scientific papers, to online business, such as viral marketing and advertising—offers unprecedented opportunities to explore and exploit the trajectories and structures of the evolution of information cascades. Abundant research efforts, both academic and industrial, have aimed to reach a better understanding of the mechanisms driving the spread of information and quantifying the outcome of information diffusion. This article presents a comprehensive review and categorization of information popularity prediction methods, from feature engineering and stochastic processes , through graph representation , to deep learning-based approaches . Specifically, we first formally define different types of information cascades and summarize the perspectives of existing studies. We then present a taxonomy that categorizes existing works into the aforementioned three main groups as well as the main subclasses in each group, and we systematically review cutting-edge research work. Finally, we summarize the pros and cons of existing research efforts and outline the open challenges and opportunities in this field.


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