• Journal of Service Research and Studies
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• v.1 no.1
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• pp.49-60
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• 2011

Recently, with the growing of social network sites, people's choice is also getting more and more. So the notion of loyalty has become an important construct within the Social Network framework because of member is easy switching on the social networking sites. Despite the increasing importance of social network sites loyalty question, there's very little research in this area. In electronic commerce, the website loyalty development process is based on both website satisfaction and website trust toward the net-enabled business. But how to target the members with high or low loyalty in the social network sites is still a question. In this paper we propose one improved RFM model to evaluate the member loyalty to find the potential members for improving the service quality of the social network site. In addition, an empirical case study is performed to demonstrate how this procedure works. Moreover, further applications of this research are provided for improved social network sites experiences and how to use the model to practice.

• Journal of Fashion Business
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• v.21 no.2
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• pp.30-44
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• 2017

The purposes of this study were to (a) identify dimensions of relational benefits in the social commerce market, (b) predict the effects of relational benefits on satisfaction, repurchase intention, and word of mouth (WOM) intention, (c) examine the mediating effects of satisfaction, and (d) compare the differences in the effects of relational benefits on satisfaction, repurchase intention, and WOM intention between the two groups of market mavenism. For collecting data, a self-administered questionnaire was undertaken by an online research agency. A total of 490 usable responses were obtained from consumers who have used social commerce sites. The sample included a slightly higher number of females (50.8%) than males and age was ranged from 20 years to 40 years. An exploratory factor analysis generated four factors of relational benefits such as confidence, convenience, special treatment, and information. Multiple regression models showed that confidence, convenience, and special treatment benefits were significant predictors of satisfaction and repurchase intention; the confidence and convenience benefits were significant for WOM intention. Satisfaction significantly mediated the relationship between relational benefits and repurchase intention, and the relationship between relational benefits and WOM intention. The group with high level of market mavenism more highly perceived the relational benefits than the other groups. Confidence benefit had a significant effect on repurchase intention regardless of the level of market mavenism, while convenience benefit had a significant effect on repurchase intention in the non-market maven group. This study discussed the managerial implications for customer relationship management in the social commerce marketplace.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.115-120
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• 2017

Online reputation systems for social network services(SNS) aggregate users' feedback and estimate the reputation of contents or providers. The aim of this research is to enhance credibility of the online reputation system on the SNS based e-Commerce(we called it as social commerce). SNS users usually refer to evaluations from other users who bought the products before. Most social commerce sites provide reputation system to help their customer make a decision, but sometimes we can't believe the reputation because the reputation is too subjective and the seller can deceive the customer for sales promotion. Threrefore, we usually use just the average value to show the general customer's evaluation result. We applied collaborative filtering method to give more weighting to the users who have evaluated correctly in the past. As a result, we could get more accurate evaluation results by considering each customers' credibility value that was computed by collaborative filtering.

• Journal of Convergence for Information Technology
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• v.9 no.2
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• pp.75-84
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• 2019

The purpose of this paper is to examine the factors influencing on loyalty in US online shopping malls. The study proposed a model to investigate the relationship among quality of sites, satisfaction, attitude, and loyalty. The hypotheses were examined by analyzing a structural equation model. 280 US samples were used for the final analysis. The results show that this model demonstrates good fit for the samples. The ease of use was found to be a significant variable in their satisfaction, while it did not have the direct effect on attitude toward the sites. The information quality was found to be a crucial variable in consumers' satisfaction and attitude toward the site. Satisfaction directly affected attitude as well as loyalty, and attitude also directly affected loyalty. Thus, the structural relationship among the variables of customers' loyalty was verified. This research provides practical insights into US consumer behaviors that would be beneficial to marketers when they make decisions for the US e-commerce market.

• Journal of the Korea Society of Computer and Information
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• v.25 no.10
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• pp.255-260
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• 2020

In this paper, I propose an efficient brand identity strategy by topic modeling the Instagram posts, one of SNS(Social Network Service) having more than 1billion world-wide and 500 million daily users. Since the 92% age groups of the Instagram is 18~50 years old (59% 18~29y and 33% 30~49), I set research analysis target three mobile commerce sites to dress and cosmetics sales sites that sale apparels cosmetics and gadgets that recently opened and have operated marketing on diverse channel including SNS. By topic modeling SNS posts for 6 months after launching the site that tagged each m-commerce site brand name or company name, I validate companies' brand identity strategy works effectively and suggest moderation of strategy for brand image. As a result, I found one of three mobile commerce site has different brand image by users and need different identity set up.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.4
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• pp.2048-2061
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• 2014

This paper redefines the concept of social shopping as the part of social commerce and identifies the significant factors to the customer satisfaction and repurchase intention for the social shopping using the factor analysis based on the selected elements from the previous research results. Structural equation modeling(SEM) result shows that 3 significant factors to the customer satisfaction are price, convenience of web site use and fun. But Security, reliability, diversity did not affect significantly satisfactorily. From the resulting factors to the customer satisfaction, users of social shopping seems to be satisfied with site entertainment like looking around and comparison shopping. The main purpose of visiting social shopping sites is considered as not only purchase of goods or services but also entertainment in the community and cyberspace. The results of this study, it provides an indication of the aspects of marketing that can be used in social shopping practice.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.1-6
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• 2023

Text mining (TM) is most widely used to process the various unstructured text documents and process the data present in the various domains. The other name for text mining is text classification. This domain is most popular in many domains such as movie reviews, product reviews on various E-commerce websites, sentiment analysis, topic modeling and cyber bullying on social media messages. Cyber-bullying is the type of abusing someone with the insulting language. Personal abusing, sexual harassment, other types of abusing come under cyber-bullying. Several existing systems are developed to detect the bullying words based on their situation in the social networking sites (SNS). SNS becomes platform for bully someone. In this paper, An Enhanced text mining approach is developed by using Ensemble Algorithm (ETMA) to solve several problems in traditional algorithms and improve the accuracy, processing time and quality of the result. ETMA is the algorithm used to analyze the bullying text within the social networking sites (SNS) such as facebook, twitter etc. The ETMA is applied on synthetic dataset collected from various data a source which consists of 5k messages belongs to bullying and non-bullying. The performance is analyzed by showing Precision, Recall, F1-Score and Accuracy.

• The Journal of Information Systems
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• v.15 no.3
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• pp.131-157
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• 2006

A lack of trust in the technical and institutional environments surrounding the web can hinder e-commerce adoption, because Internet social cues are minimal and trust is difficult th establish. Web vendors must act purposefully to overcome consumer perceptions of uncertainty and risk by building trust-both in their own web sites and in the broader Internet environments. Trust makes consumers comfortable by sharing personal information making purchases, and acting on web vendor advice-behaviors essential to wide-spread adoption of e-commerce. Understanding the nature and antecedents of trust is, therefore, a major issue for both Internet researchers and practitioners. Prior research on e-commerce trust has used diverse, incomplete, and inconsistent definitions of trust therefore, making it difficult to compare results across studies. This study tried to and the empirical relationships among the trust-related factors on the usage of Internet shooing mall. The model includes five high-level constructs-disposition to trust institution-based trust trusting beliefs, trusting intention and environmental factors. The results showed that the disposition to trust and the environmental factors had a significant effect on the web site trust however, their effect was not consistent Moreover, the model suggested in this study need to be extended including with the more sociological factors and results in this study required to be verified with those extended model.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.206-211
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• 2021

Internet users are increasingly invited to express their opinions on various subjects in social networks, e-commerce sites, news sites, forums, etc. Much of this information, which describes feelings, becomes the subject of study in several areas of research such as: "Sensing opinions and analyzing feelings". It is the process of identifying the polarity of the feelings held in the opinions found in the interactions of Internet users on the web and classifying them as positive, negative, or neutral. In this article, we suggest the implementation of a sentiment analysis tool that has the role of detecting the polarity of opinions from people about COVID-19 extracted from social media (tweeter) in the Arabic language and to know the impact of the pre-processing phase on the opinions classification. The results show gaps in this area of research, first of all, the lack of resources when collecting data. Second, Arabic language is more complexes in pre-processing step, especially the dialects in the pre-treatment phase. But ultimately the results obtained are promising.

• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.177-185
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• 2024

Web science, a general discipline of learning is presently at high demand of expertise with ideas to develop software-based WebApps and MobileApps to facilitate user or customer demand e.g. shopping etc. electronically with the access at their smartphones benefitting the business enterprise as well. A worldwide-computerized reservation network is used as a single point of access for reserving airline seats, hotel rooms, rental cars, and other travel related items directly or via web-based travel agents or via online reservation sites with the advent of social-web, e-commerce, e-business, from anywhere-on-earth (AoE). This results in the accumulation of large and diverse distributed databases known as big data. This paper describes a novel intelligent web-based electronic booking framework for e-business with distributed computing and data mining support with the detail of e-business system flow for e-Booking application architecture design using the approaches for distributed computing and data mining tools support. Further, the importance of business intelligence and data analytics with issues and challenges are also discussed.