• Asia pacific journal of information systems
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• v.32 no.4
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• pp.945-963
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• 2022

With the widespread use of social media, online social platforms like Twitter have become a place of rapid dissemination of information-both accurate and inaccurate. After the COVID-19 outbreak, the overabundance of fake information and rumours on online social platforms about the COVID-19 pandemic has spread over society as quickly as the virus itself. As a result, fake news poses a significant threat to effective virus response by negatively affecting people's willingness to follow the proper public health guidelines and protocols, which makes it important to identify fake information from online platforms for the public interest. In this research, we introduce an approach to detect fake news using deep learning techniques, which outperform traditional machine learning techniques with a 93.1% accuracy. We then investigate the content differences between real and fake news by applying topic modeling and linguistic analysis. Our results show that topics on Politics and Government services are most common in fake news. In addition, we found that fake news has lower analytic and authenticity scores than real news. With the findings, we discuss important academic and practical implications of the study.

• Journal of Information Technology Applications and Management
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• v.25 no.2
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• pp.53-72
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• 2018

This empirical study explored characteristics that affect the usefulness of online reviews, in the China e-commerce platform, and implemented multiple regressions to find factors that significantly influence on product sales, ultimately. Till now, prior studies have continuously revealed what factor affects usefulness of online review or product sales, only in respective terms. The point of our study is that we built two-level regression models, thereby being able to comprehensively analyze these two different targets. Before plunging into running regressions, we carefully collected 192,764 online review data for 200 products extracted from the Jingdong, the second biggest e-commerce platform in China. Also, we gathered "review sentimental scores" variable from each review and used that one as a core variable in our regression model, thus we were able to implement both quantitative and qualitative research. The evidences from the two-level regression models showed that the extent to which a product is experience good positively affects both usefulness of a review and product sales, again the usefulness of a review contributes to product sales in sequence. Also, the property of experience good has interaction effect on both for two-level regression models. Our main findings highlight the importance of role of online review to business performance of e-commerce firms.

• The Journal of Society for e-Business Studies
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• v.3 no.1
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• pp.95-115
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• 1998

The growth of the internet shopping mall has led to a critical mass of consumers and firms participating in a global online marketplace. This study is devoted to providing a conceptual framework for describing and analyzing the characteristics of internet shopping mall. We proposed a model which classifies internet shopping mall into four types, including (1) general intermediary (2) general direct-sales (3) specialized intermediary (4) specialized direct-sales. Our framework facilitates greater understanding of the internet shopping mall as commercial medium and allows examination of internet shopping mall in terms of the opportunities and challenges firms facing online business.

• Information Systems Review
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• v.19 no.1
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• pp.123-145
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• 2017

This study empirically examines the effects of regulation on online gaming. Going beyond ad hoc heuristic approaches on individual behavior, we investigate the effects of regulation on dynamic changes of games or service providers. In particular, we propose three theoretical perspectives: social influence to investigate the regulation effect, the role of prior experience to determine the difference in the regulation effect size through users' prior experience, and network externalities to discover the difference in the regulation effect size according to the number of users on an online gaming platform. We use the vector autoregression methodology to model patterns of the co-movement of online games and to forecast game usage. We find that online gamers are heterogeneous. Therefore, policy makers should make suitable regulations for each heterogeneous group to effectively avoid generating gaming addicts without interrupting the economic growth of the online gaming industry.

• Journal of Fashion Business
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• v.14 no.2
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• pp.81-94
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• 2010

The online shopping environment has radically changed consumer shopping behavior. Without the actual physical shopping experience in a brick-and-mortar store, consumers make purchasing decisions over the Internet. They make an effort to obtain product information not only from online merchants, but also from previous purchasers in order to make an informed decision. Accordingly, customer comments are expected to have a significant impact on decisions to purchase goods and services online. This paper focuses on one type of electronic word-of-mouth, the online consumer review. It derives several motivations why customers post product reviews on shopping mall sites. Customer motives were identified through an in depth one-on-one interview with twenty female respondents conducted twice from June $17^{th}$ to September $11^{th}$, 2009. The interviews lasted between 40 and 60 minutes. The results showed that consumers write product reviews based on six motivations: to receive a reward or remuneration for writing a product review, to share information with other customers, to improve the quality of goods and services, to reduce customer dissatisfaction, to recommend products and services, and to derive pleasure.

• Knowledge Management Research
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• v.15 no.2
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• pp.107-128
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• 2014

From old times, companies have created profits by developing business models utilizing their friendship with customers, so the relationships can be connected to the activity giving a gift. This activity of giving a gift is developed as the service of giving gifts via social network services (SNS) as the use of SNS and smart phones is recently increased in relation to that, this study set the online friendship desire and the SNS gift convenience as the intrinsic motive and the extrinsic motive of the SNS gift behavior, respectively. This study identified how the interactivity's sub factors influenced on the online friendship desire/SNS gift convenience by reorganizing the interactivity's sub factors in the mobile context. As the results of this study, it was found that the connectedness, the synchronicity and playfulness positively influenced on the online friendship desire for the SNS gift convenience, the only connectedness positively influenced on it. And it was identified that the SNS gift convenience and the online friendship desire positively influenced on the SNS gift intention. This study is academically meaningful in that it conducted an empirical research by focusing on the friendship desire in relation to the SNS gift. Besides, through the results of this study, the online friendship desire and the SNS gift convenience will have to be considered as providing any SNS gift service, and that is expected to create knowledge for SNS business model to companies.

• The Journal of Society for e-Business Studies
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• v.3 no.2
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• pp.57-71
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• 1998

In this paper, we describe the approaches of shopping agents and directory services for online comparison shopping on the web, and propose an information indexing and retrieval system, named InfoEye, with a new method for automatic extraction of product information. The developed method is based on the knowledge about presentation of the product information on the Web. The method from the knowledge about presentation of the product information is derived from both the point that online stores display their products to customers in easy-to-browse ways and heuristics made of analyses of product information look-and-feel of domestic online stores. In indexing process, the method is applied to product information extraction from Hypertext Markup Language (HTML) documents collected by a mirroring robot from online stores. We have made InfoEye to a readily usable stage and transferred the technology to Webnara commercial shopping engine. The proposed system is a cutting-edge solution to help customers as a shopping expert by providing information about the reasonable price of a product from dozens of online stores, saving customers shopping time, giving information about new products, and comparing quality factors of products in a same category.

• Journal of Fashion Business
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• v.22 no.3
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• pp.39-56
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• 2018

Since trusting in other consumers may refer to having similar needs and preferences on fashion goods with them, interpersonal trust can be a reliable and practical criterion for market segmentation online. Therefore, this study aims to identify fashion online consumers based on interpersonal trust. This study segments fashion consumers based on interpersonal trust and experience and describes characteristics of each segment by examining demo-psychographic and behavioral variables as well as clothing consumption values. An online survey was conducted to collect data from 426 adult consumers who had bought fashion goods from their patronized e-tailer in the past one month. They completed a self-administered questionnaire inquiring about interpersonal trust, trust in e-tailers, purchase intentions, clothing consumption values, and their purchasing behavior online. Two-step cluster analysis generated four segments: distrustful doers, trusting doers, inactive trusters, and distrusters. They exhibited different characteristics in gender, online experiences, interpersonal trust, clothing consumption values, trust in the e-tailers, and attitude toward the e-tailers. Providing a new effective segmentation base, this study suggests that fashion marketers identify customers with a high level of trust in other customers and develop an encouraging environment that customers can interact with others in order to increase the effectiveness of trust. Because customers with a higher level of interpersonal trust are likely to have stronger trust in e-tailers with, more favorable attitude and purchase intention, and highly perceive the value of clothing consumption than those who have a lower level of interpersonal trust.

• Journal of Fashion Business
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• v.21 no.6
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• pp.31-46
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• 2017

This study views the people's propensity to rely on others' evaluations as the interpersonal trust online despite a lack of personal interactions. Therefore, this study explores the underlying dimensions of interpersonal trust and examines how interpersonal trust influences trust in the e-tailer and behavioral intent. Data of 395 adults who had purchased apparel goods online were collected nationwide using an online questionnaire. Exploratory and confirmative factor analysis identified five underlying constructs of interpersonal trust online such as peer identification, ability, integrity, shared lifegoals, and benevolence. A structural equation modeling test was conducted to examine the relationships between interpersonal trust, trust in the e-tailer, and behavioral intent. Interpersonal trust influenced on trust in the e-tailer, specifically on trust in the e-tailer's competence which subsequently increased a customer's behavioral intent such as attitude toward the e-tailer and shopping intention. Although no direct effect of interpersonal trust on the behavioral intent was found, interestingly, the effects of the interpersonal trust on the e-tailer trust which derived the behavioral intent to purchase. This result suggests that marketers devise a more effective system and environment that can encourage the interpersonal trust between customers to build a strong trust in e-tailers. It also provides a theoretical framework of online trust in the way of classifying interpersonal trust and trust in e-tailers.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.9
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• pp.131-141
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• 2021

With the rapid development of the Internet, online shopping has grown so fast that almost any good or service can be sold online today. The popularity and rapid growth of e-commerce signal a huge market opportunity for e-retailers. From the organizational perspective, it is necessary to evaluate and explore what drives customers to buy their products or to use their services. This study, therefore, aims to explain the online purchase intention and its determinants of Vietnamese customers for cosmetics and personal care products. Quantitative data was collected from an online survey conducted among university students, then was put into SPSS and AMOS for further analysis. Descriptive statistics, Cronbach's alpha test, exploratory factor analysis (EFA), regression analysis, and SEM were used to examine data from 434 valid answers. The research findings reveal that four factors positively affect purchase intention: Shopping enjoyment has the most significant impact, followed by trust, benefit, and website quality. On the other hand, perceived risk negatively influences purchase intention. While the cosmetics and personal care industry is thriving with a huge number of producers and consumers throughout the world, this study contributes to the existing literature in terms of capturing customers' needs and developing effective strategies to attract more online users.