• Journal of Venture Innovation
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• v.5 no.2
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• pp.101-110
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• 2022

It is easy for first movers of platform business model to monopolize the market due to the platform's own characteristics such as network effect and flywheel strategy. Accordingly, the regulations on platform operators are constantly being discussed in the recent monopoly regulation arguments, but the concrete regulations have not been settled worldwide. This is because there is no clear consensus on the valuation method which can objectively identify dominant platform firms from the others. This study suggested a platform valuation method based on the Tobin's Q theory, by measuring the moderating effect of the existence of specific scale of platform on the relationship between replacement cost and market valuation. Our method can not only be a standard for settling monopoly regulation by converging the regulation targets, but also contribute to active investment on the new platform firms by evaluating their potential growths quantitatively.

• Journal of Smart Tourism
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• v.3 no.4
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• pp.23-31
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• 2023

This paper explores the concept of enhanced smart tourism as a response to the challenges and opportunities arising in the post-pandemic tourism landscape. The COVID-19 pandemic has not only halted the global tourism industry but also prompted a reevaluation of its sustainability, technological integration, and impact on local communities. The need for a paradigm shift in tourism is emphasized, focusing on digitalization, innovation, and resilience. Enhanced smart tourism is characterized by a shift from traditional practices to innovative governance models, increased emphasis on sustainability, and the integration of technology for better management and visitor experiences. The paper discusses the four pillars of enhanced smart tourism - Technology, Sustainability, Accessibility/Mobility, and Innovation/Creativity, and their expansion in the post-pandemic era. Furthermore, the significant role of data in smart tourism is examined, highlighting the importance of data valuation, management, and ethics. The paper proposes frameworks and methods for data valuation and emphasizes the necessity of a comprehensive approach to data within the smart tourism ecosystem. The conclusion points to the need for further empirical and conceptual research to fully realize the potential of enhanced smart tourism.

• Knowledge Management Research
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• v.23 no.1
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• pp.133-148
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• 2022

In an ever-changing tourism environment, we need to think about how to successfully attract tourists and provide them with memorable experiences. Smart tourism content is considered as a useful tourism resource for converting into an attractive tourist destination by providing new values in various tourist destinations as well as the changed tourism patterns due to COVID-19. However, there are still few successful cases of smart tourism contents that have secured economic sustainability. Accordingly, this study applied the Contingent Valuation Method (CVM) to estimate the economic value perceived by tourists for smart tourism contents based on augmented reality to develop a smart tourism content development plan that can secure economic sustainability. As a results, it was confirmed that the lower the offered amount, the higher the awareness of the new value, the higher the likelihood of willingness to pay. Based on these research results, this study presented academic and practical implications for the development of smart tourism content that secured economic sustainability.

• Journal of Industrial Convergence
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• v.22 no.7
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• pp.1-13
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• 2024

Among e-government services, the intelligent CCTV control platform is a screening control service that utilizes artificial intelligence to display major objects such as people, cars, etc. to control personnel when they appear on CCTV. The operation of an intelligent CCTV control platform is expected to improve the quality of life of citizens by enabling rapid response in the event of an emergency and increasing the resolution of complaints. In this study, the benefits of the intelligent CCTV control platform, a non-market good, were estimated by applying the contingent valuation method (CVM), a choice experiment technique, to estimate the average willingness to pay per household and calculate the social benefits. As a result of the analysis, the average willingness to pay per household was estimated to be KRW 6,908 per year, and the economic benefits for the country as a whole were estimated to be about KRW 150.4 billion per year. This study is of academic significance as it extends the application of CVM to the field of intelligent e-Government services. The Intelligent CCTV control platforms is being actively discussed, this study has practical implications in that the benefits were estimated in monetary value.

• Journal of Technology Innovation
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• v.15 no.2
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• pp.153-176
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• 2007

DMB data broadcasting has recently come into the spotlight as a platform for a new business opportunity and an application of various contents. This paper estimates the willingness to pay for the DMB data broadcasting services and explains the demand characteristics for TPEG, BIFS and BWS services, using the Double-bounded dichotomous choice Contingent Valuation Method. Consumers are willing to pay 2,039 Korean won for TPEG service and 1,612 Korean won for BIFS and BWS services per month, which corresponds to the market size 87.6 billion Korean won for TPEG and 195.2 billion Korean won for BWS and BIFS a year respectively. It is also found that the more consumers show usage intentions, have experiences in the similar services, and know of the DMB data broadcasting services, the more they are likely to pay for the DMB data broadcasting services.

• Journal of Software Assessment and Valuation
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• v.15 no.1
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• pp.11-24
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• 2019

Using cross-platform development frameworks, mobile app developers can easily implement mobile apps for multiple platforms in one step. The frameworks also provides adversaries with the ability to write malicious code once, and then run it anywhere for other platforms. In this paper, we analyze the ratio of benign and malicious apps written by cross-platform development frameworks for Android apps collected from AndroZoo's site. The analysis results show that the percentage of benign apps written in the frameworks continues to increase, accounting for 45% of all benign apps in 2018. The percentage of malicious apps written in the frameworks accounted for 25% of all malicious apps in 2015, but that percentage has declined since then. This study provides useful information to make a suitable choice when app developers face several challenges in cross platform app development.

• Journal of Software Assessment and Valuation
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• v.13 no.2
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• pp.9-17
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• 2017

Software compliance is an essential process when Open Source Software is included in software development to avoid such as license violation issue. However, analyzing quite big software which involves many developers requires enormous time and hard difficulty. To resolve these kinds of problem, SPDX formalizes and standardize the metadata about the software package. When the use of SPDX is activated, software package analysis would be simple and could contribute fair Open Source Software distribution. In this paper, we develop blockchain based SPDX distribution platform which fulfills the requirement of SPDX lifecycle to provide SPDX database which does not depend on particular centralized service but serve as distributed ledger and control by user's certification and their purpose. Moreover, to contribute invigoration of blockchain based SPDX distribution platform, we develop SPDX document generation plug-in for integrated development environment such as Visual Studio.

• Information Systems Review
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• v.26 no.1
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• pp.57-71
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• 2024

There are several ways to assess the value of personal data, but there is no standard for evaluating data value. In the case of medical my data utilization platform services, it was found that when the platform company received the user's consent and received data for the purpose of data utilization, an average of about 4,000 credits was paid per user as compensation. As in the previous case, the value of personal information is mainly measured based on the value of each individual, not on specific items of personal information. However, as the number and type of personal information increases, the value of personal information must be measured by type. This study focuses on measuring the value of unstructured personal information, especially images, and proposes standards for unstructured personal information. By measuring the value of images, we will be able to help platform companies set credit standards for compensation per person when providing data and support objective and reasonable pricing when selling B2B data.

• Journal of Software Assessment and Valuation
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• v.17 no.1
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• pp.59-66
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• 2021

Recently, conceptual information model is changing fast, and these changes are coming about as a result of individual tendency, social cultural, new circumstances and societal shifts within big data environment. Despite the data is growing more and more, now is the time to commit ourselves to the development of renewable, invaluable information of social/live commerce. Because we have problems with various insoluble data, we propose about deep learning prediction model-based object classification in social commerce of big data environment. Accordingly, it is an increased need of social commerce platform capable of handling high volumes of multiple items by users. Consequently, responding to rapid changes in users is a very significant by deep learning. Namely, promptly meet the needs of the times, and a widespread growth in big data environment with the goal of realizing in this paper.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.187-193
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• 2021

In February 2020, Gyeonggi-do paid the world's first Data Dividend to local residents of Gyeonggi Province who produced data using local currency. Currently, Data Dividend is being paid to consumers who have produced data, but this paper studied the expansion of Data Dividend qualifications according to the contribution to creating added value. First, it raised the question of whether it is right for the recipient of Data Dividend to have only the consumers who produced the data. Second, by analyzing the four elements of data valuation criteria that influenced the creation of added value identified the objects that influence the creation of added value. The 4 factors were divided into productivity, effectiveness, concreteness, and usability, and the objects corresponding to each factor were analyzed. Accordingly, it was determined whether platform workers contributed to the creation of added value. In conclusion, it was confirmed that not only consumers, who were the first data producers, but also platform workers who contributed to the concreteness of data valuation to create added value can qualify for Data Dividend. Since this paper focuses on the necessity of data allocation centered on platform workers among the objects, the validity of objects that influence added value other than platform workers are excluded.