• Asia pacific journal of information systems
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• v.32 no.3
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• pp.477-495
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• 2022

This paper proposes how to design and implement data-driven strategies by investigating how a firm can increase its value using data science. Drawing on prior studies on architectural innovation, a behavioral theory of the firm, and the knowledge-based view of the firm as well as the analysis of field observations, the paper shows how data science is abused in dealing with meso-level data while it is underused in using macro-level and alternative data to accomplish machine-human teaming and risk management. The implications help us understand why some firms are better at drawing value from intangibles such as data, data-science capabilities, and routines and how to evaluate such capabilities.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1135-1143
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• 2007

The singular value decomposition and the spectral decomposition are the useful methods in the area of matrix computation for multivariate techniques such as principal component analysis and multidimensional scaling. These techniques aim to find a simpler geometric structure for the data points. The singular value decomposition and the spectral decomposition are the methods being used in these techniques for this purpose. In this paper, the singular value decomposition and the spectral decomposition are compared.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.763-774
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• 2006

The purpose of this study is to identify relationship among service quality, service value and customer satisfaction of food service industries. The respondents included 120 customers of K-restaurant in the survey. Data were analyzed by confirmatory factor analysis and cause-effect analysis among the constructs. After research model testing, the following results was obtained : Service Value was influenced directly and positively by the service quality. And customer satisfaction was influenced directly and positively by the service value. But customer satisfaction was not influenced directly and positively by the service quality.

• Journal of Korea Trade
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• v.25 no.7
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• pp.19-40
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• 2021

Purpose - This paper's purpose is to investigate how foreign ownership and innovation affect firm value. Design/methodology - Firm innovation is defined as operational efficiency, which is calculated by adopting data envelopment analysis (DEA). Additionally, R&D intensity is included as a measure of innovation in the analysis. We used firm-level data from manufacturing companies in Korea. The sample comprised 3,753 firm-year observations for every year in the period 2003-2017. Findings - We found that foreign ownership and innovation are positively related to firm value (Tobin's Q). Foreign ownership moderates innovation's contribution to firm value, implying that foreign ownership may enhance the value relevance of firm innovation. In addition, we found that firm innovation partially mediates the relationship between foreign ownership and firm value. Originality/value - This highlights the important role of foreign investors' monitoring; wherein foreign investors enhance firm value by facilitating firm innovation. Our results suggest that foreign ownership can be crucial for innovation and may serve to address weak ownership structures.

• Journal of Information Technology Services
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• v.11 no.3
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• pp.39-48
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• 2012

It is essential that firm makes a rational and scientific decision making and creates a news value for the future direction. To do so, many firms attempt to collect meaningful data and find the filtered and refined implication for the better customer relationship and the active market drive through the various analytic tools. Among the possible IT solutions, utilization of 'Big Data' is becoming more attractive and necessary in such a way that it would help firms obtain the systemized and demanding information and facilitate their decision making process to keep up with the market needs. In this paper, it introduces the concepts and development of 'Big Data' recognized as a IT resource and solution under the rapidly changing firm environment. This study also presents the several firm cases using Big Data' and the Oracle's total data management and analytic solutions in order to support the application of 'Big Data'. Finally this paper provides a holistic viewpoint and realistic approach on use of 'Big Data' to create a new value.

• Journal of Integrative Natural Science
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• v.13 no.4
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• pp.147-151
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• 2020

In this paper, we propose a method to detect concept drift by applying Convolutional Neural Network (CNN) in a data stream environment. Since the conventional method compares only the final output value of the CNN and detects it as a concept drift if there is a difference, there is a problem in that the actual input value of the data stream reacts sensitively even if there is no significant difference and is incorrectly detected as a concept drift. Therefore, in this paper, in order to reduce such errors, not only the output value of CNN but also the probability vector are used. First, the data entered into the data stream is patterned to learn from the neural network model, and the difference between the output value and probability vector of the current data and the historical data of these learned neural network models is compared to detect the concept drift. The proposed method confirmed that only CNN output values could be used to reduce detection errors compared to how concept drift were detected.

• Journal of Distribution Science
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• v.18 no.10
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• pp.25-38
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• 2020

Purpose: Traditional markets have served as important locations for social-cultural and economic activities. It is a hub of economic transactions and where people gather and exchange information and goods, while also serving as the center of social activities, including commercial exchanges. Accordingly, this study aimed to contribute to the studies on the perceived value in traditional markets for customers in different aspects. Research design, data, and methodology: To analyze the proposed model, data was collected from 456 respondents and analyzed with SPSS 21.0 and AMOS 21.0. The data was analyzed with structural equation modeling (SEM) using path analysis. Results: According to the results of the analysis, the perceived value comprises utilitarian value, emotional value, economic value, and social value, all of which had a positive impact on attitude. Emotional value and social value had a positive impact on subjective norms, while utilitarian value and economic value did not have an impact on subjective norms. Also, attitudes and subjective norms were found to have a positive impact on behavioral intention. Conclusions: Through this study, the value that the traditional markets need to provide to consumers have been identified. Traditional markets should develop into places that can provide value for their consumers.

• The Korean Journal of Franchise Management
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• v.8 no.1
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• pp.43-53
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• 2017

Purpose - The coffee market in Korea has been dramatically developed and coffee chains dominate the Korean coffee market recently. Customer's perceived value is one of the marketing tools to get competitive advantages of coffee chains, and plays a critical role to study on coffee franchise industry. Thus, this study is to identify the effect of customer's perceived value (price, brand, service, and quality) on revisit intentions and word-of-mouth(WOM). Research design, data. and methodology - Customer's perceived values consists of four dimensions. 253 samples of 320 were used for data analyses excluding unusable responses. The data were analyzed with SPSS 21.0 and SmartPLS 3.0. Result - First, customer's perceived brand value and service value have a significant, positive effect on revisit intentions. Second, Price value and brand value have a positive influence on WOM. Third, gender difference plays a moderating role in the relationship between brand value and price value and WOM, and between brand value and revisit intentions. Conclusions - Males tend to focus more on their perceived brand value of coffee shops for revisit and recommendation, otherwise females consider price value to give an advice to others. Based on the results of this study, the marketers of coffee chains can develop effective strategies regarding gender difference as well.

• The Journal of Information Systems
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• v.32 no.1
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• pp.1-21
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• 2023

Purpose The purpose of this study is to investigate the intention of early application users in consideration of the characteristics of digital finance-based MyData service users. It is expected that user characteristics will affect the intention to use MyData service, which has not yet been advanced, and accordingly, it will examine how the characteristics of the initial users of MyData service and the intention to use it are connected. Design/methodology/approach The model used in this study is a value-based adoption model (VAM), and a lot of research has been conducted on information technology and online user acceptance and continuous use intention of online users. VAM has been proven useful through empirical analysis in many studies. The value-based acceptance model is a method of analyzing the intention to use Benefits and Sacrifices as the main elements of perceived value. It can be said to be a model that can analyze the benefits of use and the sacrifices to be made. Findings According to the analysis results of this study, it was found that usefulness, enjoyment, and reliability, which are the benefits of MyData service apps, had a positive effect on perceived value, which is partially consistent with existing research results. However, it was found that complexity, which is the sacrifice of MyData service apps, negatively affects perceived value and security has no negative impact. The results of security are considered to be complementary to financial institutions because MyData service deals with financial data based on personal information, and the research hypothesis is rejected because users' demands are relatively low. Therefore, MyData service apps should do more to increase benefits (usefulness, enjoyment, and reliability) than to reduce sacrifice (complexity) to users.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3966-3991
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• 2018

Due to the lack of visualization services and organic combinations between public and private buildings data, the usability of the basic map has remained low. To address this issue, this paper reports on a solution that organically combines public and private data while providing visualization services to general users. For this purpose, factors that can affect building prices first were examined in order to define the related data attributes. To extract the relevant data attributes, this paper presents a method of acquiring public information data and real estate-related information, as provided by private real estate portal sites. The paper also proposes a pretreatment process required for intelligent machine learning. This report goes on to suggest an intelligent machine learning algorithm that predicts buildings' value pricing and future value by using big data regarding buildings' spatial information, as acquired from a database containing building value attributes. The algorithm's availability was tested by establishing a prototype targeting pilot areas, including Suwon, Anyang, and Gunpo in South Korea. Finally, a prototype visualization solution was developed in order to allow general users to effectively use buildings' value ranking and value pricing, as predicted by intelligent machine learning.