• Information Systems Review
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• v.25 no.1
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• pp.213-231
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• 2023

With the rapid development of live streaming commerce, online host as an information source plays a critical role in affecting live streaming performance. However, the impact of different product types on the relationship between online hosts and live streaming has been less studied. Based on the elaboration likelihood model (ELM) and information source theory, this study aims to empirically investigate what factors influence the sales of live streaming commerce and how product type moderates the relationship between them. The analysis of 11,422 live streaming commerce data collected for four months from October 10, 2021 to February 10, 2022 shows that, among the factors related to source credibility and attractiveness, multi-channel networks (MCN) and the number of followers positively affect the sales volume of live streaming commerce, whereas the reputation score harms the sales. Moreover, the moderating effect of the product type (i.e., ratio of involvement products) on the relationships is confirmed. The findings enrich the literature on live streaming commerce performance. The limitations and future research directions are also discussed.

• Journal of Information Technology Applications and Management
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• v.11 no.1
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• pp.83-100
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• 2004

Understanding characteristics of Internet businesses from a cross-cultural perspective could offer valuable insights on developing business strategies and policies. This work is concerned with revealing divergence and convergence of Internet businesses in their financial performance, given organizational conditions and cultural context. For this, we studied the association between static organizational attributes (core activity, origination, firm age, and industry type) and a firms financial performance (gross revenue and net income). Relevant data was gathered from representative Internet firms in Korea and U.S. Data analysis indicated that, besides industry type, overall connection between selected organizational variables and financial performance was weak. Cross-national comparison showed that Korean firms financial performance was comparable to U.S firms during the period of economic turbulence. A noticeable difference was that Korean Internet firms and their business models were more service-oriented than U.S. counterparts.

• The Journal of Society for e-Business Studies
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• v.9 no.2
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• pp.1-16
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• 2004

This study evaluates the factors of e-commerce websites using a Kano model. In this study, especially the Kano model is applied to both business-to-customer(B2C) and business-to-business(B2B) websites in order to reveal how factors are different between the two types, while previous research is limited to mainly evaluation of B2C websites. In addition, the factors on product types supported from websites are defined, which resulted in discovering the differences among the websites by product types. The contribution of this paper is as follows. Firstly, it reveals the actual B2B website evaluation as well as evaluation by product types such as physical and service product. Secondly, it reviews the B2B e-Commerce that will play a key role in the near future.

• Proceedings of the Technology Innovation Conference
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• 2002.02a
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• pp.133-149
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• 2002

This study aims to investigate the impact of wide use of digital technology, in particular, the Internet, on innovation process and corporate strategy in electronics industry. The introduction of digital technology has changed innovation process, business model and organizational structure of the electronics companies. With the introduction of digital technology, the entire value chain of electronics industry from procurement, sales, and marketing to R&D and manufacturing has been restructured. E-commerce has been a major agenda for e-business. Recently, collaboration among electronics companies through e-marketplace has emerged as an important issue. A web-based e-commerce standard, so called RosettaNet, has been developed for facilitating e-transactions of electronics firms. The development of digital technology has dramatically increased the processing speed and sophisticated the virtual reality technology. As simulation becomes easier and more effective, the uncertainty and risk involved in R&D has decreased significantly. Another positive impact is closer cooperation between R&D and manufacturing functions. Taking advantage of automated and flexible production technology, has a new type of firm, so called, EMS (Electronics Manufacturing Services) emerged, whose strategic focus is on manufacturing only. The EMS can be seen as a kind of innovative organization, that is, a modular organization for production function. Digital technology has made convergence of computer and communication possible at early years but right now the convergence has been accelerated in extensive areas of communication, broadcasting, information appliances, software, contents, and services. Firms' effort for an innovative product and service has been intensified and the competition for a new standard product and service has become severe in electronics industry. Business activities are always realized in a specific organizational context. Accordingly building up innovation-friendly organization has emerged as a critical concern. Due to the striking decrease of transaction cost, a network type of organization has proliferated, and a business function turns into a modular organization. As a whole, digital technology has pushed electronics firms into developing their own business model, which takes consideration of standardization of business platform and their core competency.

• Journal of Digital Contents Society
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• v.15 no.6
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• pp.711-719
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• 2014

Along with the advent of ubiquitous computing environment, it is becoming a part of our common life style that the demands for enjoying the wireless internet using intelligent portable device such as smart phone and iPad, are increasing anytime or anyplace without any restriction of time and place. The recommending service becomes a very important technology which can find exact information to present users, then is easy for customers to reduce their searching effort to find out the items with high purchasability in e-commerce. Traditional mining association rule ignores the difference among the transactions. In order to do that, it is considered the importance of type of merchandise or service and then, we suggest a new recommending service using mining sequential pattern based on weight to reflect frequently changing trends of purchase pattern as time goes by and as often as customers need different merchandises on e-commerce being extremely diverse. To verify improved better performance of proposing system than the previous systems, we carry out the experiments in the same dataset collected in a cosmetic internet shopping mall.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.187-206
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• 2007

The development of computer and information technology has been combined with the information superhighway internet infrastructure, so information widely spreads not only in special fields but also in the daily lives of people. Information ubiquity influences the traditional way of transaction, and leads a new E-commerce which distinguishes from the existing E-commerce. Not only goods as physical but also service as non-physical come into E-commerce. As the scale of E-Commerce is being enlarged as well. It keeps people from finding information they want. Recommender systems are now becoming the main tools for E-Commerce to mitigate the information overload. Recommender systems can be defined as systems for suggesting some Items(goods or service) considering customers' interests or tastes. They are being used by E-commerce web sites to suggest products to their customers who want to find something for them and to provide them with information to help them decide which to purchase. There are several approaches of recommending goods to customer in recommender system but in this study, the main subject is focused on collaborative filtering technique. This study presents a possibility of pre-evaluation for the prediction performance of customer's preference in collaborative filtering before the process of customer's preference prediction. Pre-evaluation for the prediction performance of each customer having low performance is classified by using the statistical features of ratings rated by each customer is conducted before the prediction process. In this study, MovieLens 100K dataset is used to analyze the accuracy of classification. The classification criteria are set by using the training sets divided 80% from the 100K dataset. In the process of classification, the customers are divided into two groups, classified group and non classified group. To compare the prediction performance of classified group and non classified group, the prediction process runs the 20% test set through the Neighborhood Based Collaborative Filtering Algorithm and Correspondence Mean Algorithm. The prediction errors from those prediction algorithm are allocated to each customer and compared with each user's error. Research hypothesis : Two research hypotheses are formulated in this study to test the accuracy of the classification criterion as follows. Hypothesis 1: The estimation accuracy of groups classified according to the standard deviation of each user's ratings has significant difference. To test the Hypothesis 1, the standard deviation is calculated for each user in training set which is divided 80% from MovieLens 100K dataset. Four groups are classified according to the quartile of the each user's standard deviations. It is compared to test the estimation errors of each group which results from test set are significantly different. Hypothesis 2: The estimation accuracy of groups that are classified according to the distribution of each user's ratings have significant differences. To test the Hypothesis 2, the distributions of each user's ratings are compared with the distribution of ratings of all customers in training set which is divided 80% from MovieLens 100K dataset. It assumes that the customers whose ratings' distribution are different from that of all customers would have low performance, so six types of different distributions are set to be compared. The test groups are classified into fit group or non-fit group according to the each type of different distribution assumed. The degrees in accordance with each type of distribution and each customer's distributions are tested by the test of ${\chi}^2$ goodness-of-fit and classified two groups for testing the difference of the mean of errors. Also, the degree of goodness-of-fit with the distribution of each user's ratings and the average distribution of the ratings in the training set are closely related to the prediction errors from those prediction algorithms. Through this study, the customers who have lower performance of prediction than the rest in the system are classified by those two criteria, which are set by statistical features of customers ratings in the training set, before the prediction process.

• Journal of Digital Convergence
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• v.19 no.4
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• pp.73-88
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• 2021

The development of modern industry is changing the consumption pattern of consumers. With the advent of COVID-19, consumers' consumption using online e-commerce has begun to become more active. Online shopping malls where e-commerce takes place have four types of platforms: stand-alone, rental, open market and store farm. Among them, by comparing the stand-alone and store farm types, this study was conducted how the platform type affects consumers' purpose of using the online shopping mall and their intention to revisit the online shopping mall. This study analyzed 202 surveys within the last six months. According to the results of the study, reliability and information had a significant impact on psychological benefits. In addition, promotion and convenience have had a significant impact on economic benefits. The psychological and economic benefits, have been found to have a significant impact on the intention of revisit. However, there is no difference depending on the platform type.

• Management & Information Systems Review
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• v.21
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• pp.99-114
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• 2007

According as Internet based EC(Electronic Commerce) has been activated, More requirements for exchanging digital documents are being proposed in B2B(Business to Business) and B2G(Business to Government) environments. However, the documents can not be processed automatically, because the structures of documents in each site(companies, central/local governments) do not match. Therefore, W3C(World Wide Web Consortium) has proposed XML(eXtensible Markup Language) DTD(Document Type Declaration) technology to support structuring documents. The XML DTD technology can support interoperability between EC sites. And, XML DTD based documents can be processed automatically in every sites. They will improve efficiency of services in B2B and B2G environments. In this paper, we propose interoperable DTD architecture and IDEP(Interoperable DTD Exchange Protocol) protocol which supports searching DTDs and exchanging DTDs. This technology can popularize DTDs and digital documents.

• Proceedings of the Technology Innovation Conference
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• 2002.02a
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• pp.269-296
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• 2002

This paper is an exploitative research on the types of B2B e-business model. The research method adopted is a literature review of academic articles, reports of consulting firms, technical papers and seminar materials. This paper presents an integrated business model of business to business electronic commerce. The B2B business model comprises of four dimensions:1) type of operators 2) Product scope(industry scope) 3) transaction method 4) revenue source.

• Journal of the Korea Society of Computer and Information
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• v.28 no.5
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• pp.49-56
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• 2023

Currently, e-commerce is changing from a digital twin to a metaverse world. The metaverse world is an intermediate form between virtual and real worlds and is operated as a coin-based meta-commerce. In this meta-commerce world, blockchain-based NFT coins are used when trading items (contents). In this study, we studied how to issue a large number of NFT coins (certification) rather than issuing a single type of NFT. The research method was designed to produce content layer-based and automatically create the desired quantity using a mass NFT index and automatic generation method. In this study, a layer overlap method (background, body, etc.) was used with a Phyton-based program for mass minting. As a result, it can be used as a blockchain-based certificate that can prove a group of many people. In addition, the content created with the NFT index was registered on the NFT sales site to confirm its utilization and value.