Internet Word-Of-Mouth on Consumer Online Purchasing Behavior Analysis in China

2013 ◽  
Vol 5 (1) ◽  
pp. 747-757 ◽  
Author(s):  
Jie Gao ◽  
Weiling Ye
Keyword(s):  
Behavior Analysis ◽  
Word Of Mouth ◽  
Purchasing Behavior

Destination Image Components and Word-of-Mouth Intentions in Urban Tourism: A Multigroup Approach

2015 ◽  
Vol 42 (4) ◽  
pp. 503-527 ◽  
Author(s):  
Dimitra Papadimitriou ◽  
Kyriaki (Kiki) Kaplanidou ◽  
Artemisia Apostolopoulou
Keyword(s):  
Behavior Analysis ◽  
Behavioral Intentions ◽  
Word Of Mouth ◽  
Urban Tourism ◽  
Destination Image ◽  
Future Behavior ◽  
Structural Relationships ◽  
Local Residents

The purpose of this study was to explore differences among three distinct groups, namely local residents, past tourists, and prospective tourists, in their perceptions of cognitive, affective, and overall image of a city destination and their future behavior. Analysis of data generally confirmed previously established structural relationships of cognitive and affective image, overall destination image, and word-of-mouth intentions. However, differences were identified among the three groups in terms of their destination image perceptions and their behavioral intentions to engage in word-of-mouth communications. Specifically, residents who engaged in word-of-mouth were primarily influenced by the cognitive and affective destination image components, while tourists relied on overall image perceptions.

Pengaruh Tingkat Kepercayaan Berkomunikasi di Jejaring Sosial Internet (Social Media) Terhadap Perilaku Beli Mahasiswa

2012 ◽  
Vol 4 (1) ◽  
pp. 1-12
Author(s):  
Ilham Prisgunanto
Keyword(s):  
Social Media ◽  
Interpersonal Communication ◽  
Word Of Mouth ◽  
Private University ◽  
Semantic Differential ◽  
Communication Model ◽  
Purchasing Behavior ◽  
Buying Behavior ◽  
Keywords Internet ◽  
Survey Results

The research examines effect of the confidence level of students in social media to communicate to their buying behavior. The theories used in this research are impersonal interpersonal communication model develop by Miller DeVito continuum of interpersonal and Word of Mouth model’s Ian Safko. This is a quantitative study using associative effects among variables Knowing, Confidence, and Buying behavior. Thus research uses semantic differential scale with a student population of information technology at a private university in Jakarta with a simple sample about 92 people as the random sampling model. From this survey results that there is influence between the level of confidence to communicate in social media purchasing behavior student, but very small. Equation that there is a Y (buying behavior) = 0.136 + 1.16 X1 (Confidence) + 0.049 X2 (Knowing). Keywords: internet, social media, interpersonal communication, word of mouth

WEB FARMING WITH CLICKSTREAM

2008 ◽  
Vol 07 (02) ◽  
pp. 291-308 ◽  
Author(s):  
JIA HU ◽  
NING ZHONG
Keyword(s):  
Behavior Analysis ◽  
Web Mining ◽  
User Interaction ◽  
Purchasing Behavior ◽  
Web Content ◽  
Related Data ◽  
Web Usage ◽  
Proposed Model ◽  
The Web ◽  
Usage Data

In a commercial website or portal, Web information fusion is usually from the following two approaches, one is to integrate the Web content, structure, and usage data for surfing behavior analysis; the other is to integrate Web usage data with traditional customer, product, and transaction data for purchasing behavior analysis. In this paper, we propose a unified model based on Web farming technology for collecting clickstream logs in the whole user interaction process. We emphasize that collecting clickstream logs at the application layer will help to seamlessly integrate Web usage data with other customer-related data sources. In this paper, we extend the Web log standard to modeling clickstream format and Web mining to Web farming from passively collecting data and analyzing the customer behavior to actively influence the customer's decision making. The proposed model can be developed as a common plugin for most existing commercial websites and portals.

scholarly journals Ill Consequences of Social Media in Intepreting Customers Buying Opinion

2019 ◽  
Vol 9 (2S4) ◽  
pp. 178-180
Keyword(s):  
Social Media ◽  
Word Of Mouth ◽  
Vital Role ◽  
Demographic Variables ◽  
Brand Awareness ◽  
Purchasing Behavior ◽  
Buying Behavior ◽  
Result Show ◽  
The Impact ◽  
Consumer Buying Behavior

This research aims to study the interaction between the companies and the consumers directly. Now a day’s social media is playing a vital role for the marketers. It creates curiosity, brand awareness. Social media is the fastest way to get in touch with the consumers. The traditional word-of-mouth publicity has been replaced by word-of-web as consumers are increasingly referring to social media sites before making a purchase, greatly influencing buying behavior. This Study is focusing on the factors which influence the impact of social media on consumer buying behavior. To analyse the impact of demographic variables on purchasing behavior using social media. The survey has been conducted by randomly selecting 50 respondents who are using Social Media. Result show that Social Media influences consumer buying behavior.

WORD-OF-MOUTH VERSUS EXPERTS AND REPUTATION IN THE INDIVIDUAL DYNAMICS OF WINE PURCHASING

2011 ◽  
Vol 14 (06) ◽  
pp. 871-885 ◽  
Author(s):  
TATIANA BOUZDINE-CHAMEEVA ◽  
SERGE GALAM
Keyword(s):  
Social Interactions ◽  
Word Of Mouth ◽  
Specific Problem ◽  
Opinion Dynamics ◽  
Practical Implementation ◽  
Purchasing Behavior ◽  
Sample Distribution ◽  
Individual Preferences ◽  
Market Shares ◽  
The Individual

The dynamics of wine purchasing behavior is studied focusing on the respective impacts of the word-to-mouth versus wine expert judgements and reputations. To investigate the problem we apply the Galam model of opinion dynamics to agents who have to select a preference about which type of wine to buy given expert judgements, individual preferences and wine reputations. It could be, for instance, a preference between Bordeaux and Burgundy. The main novelty of the work is not about the building of a new model but indeed the construction of a scheme to confront the Galam model to a specific problem of the real world. Accordingly we design a commercial strategy to hold on to a share of the wine market. It provides a novel understanding on how, given some established reputation, the competitive interplay between social interactions and expert judgments affects the market shares distribution. The financial implications of the practical implementation of these results are discussed. In particular it is found that sample distribution of bottles could be drastically reduced from the usual levels practiced by producers. We hope our results will convince some wine producers to test our predictions.

scholarly journals Responding to Negative Electronic Word of Mouth to Improve Purchase Intention

2021 ◽  
Vol 16 (6) ◽  
pp. 1945-1959
Author(s):  
Robert Zinko ◽  
Angela Patrick ◽  
Christopher P. Furner ◽  
Shalanda Gaines ◽  
Mi Dya Kim ◽  
...  
Keyword(s):  
Purchase Intention ◽  
Word Of Mouth ◽  
Online Review ◽  
Electronic Word Of Mouth ◽  
Purchasing Behavior ◽  
Negative Outcomes ◽  
Simulation Based ◽  
Growing Body ◽  
Online Conversation ◽  
Fake Reviews

Retailers have little control over what their customers say about their products and services online. Review platforms (e.g., Yelp and Travelocity) are rife with negativity, from both real customers with bad experiences and from fake reviews created by competitors. These negative reviews have been shown to influence the purchasing behavior of future consumers. Many platforms do afford companies some control by including them in the online conversation about their products or services. Crafting a response to a poor review which appeals to future consumers may mitigate some of the negative outcomes associated with that review. This study advances our knowledge of responding to negative reviews by adding to the growing body of research, using a simulation-based experiment to test the influence of three elements of a review response on purchase intention (i.e., an apology, an explanation and a pledge to correct the problem identified in the review). In doing so, the data show that purchase intention increases only when a response contains all three elements. Implications for e-commerce researchers and review platform developers are discussed.

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