• Asia-Pacific Journal of Business
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• v.12 no.3
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• pp.1-36
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• 2021

Purpose - This empirical study, aims to identify the determinants of adoption and acceptance of mobile payment as to understand why it is successful in some countries in Sub-Saharan Africa but failing in others. A comparative study of a successful mobile payment service and a purported failed one was done as to have some insights to the factors affecting acceptance of the technology. Design/methodology/approach - The strength of three notable theories: theory of diffusion of innovation (DOI), the extended unified theory of user acceptance of information technology (UTAUT2) and self-efficacy theory were use. The self-efficacy of government support inclusion as, a moderating variable in the form of infrastructure, securing transaction and price value revealed the relevance of government in the success of mobile payment service. By means of a field survey of 705 subjects in two separate regions of Africa (East and West), the data was collected and use to test the research model. Findings - The study result shows the importance of the moderating factor of government support to the success of mobile payment of any nation. The result also shows the importance of the perception of relative advantage, compatibility, complexity, social influence as already revealed by other studies. Research implications or Originality - Mobile payment success in some part of Sub-Saharan Africa is well known but also suggested to fail in some Sub-Saharan African countries. Buttressing the need for understanding of the factors affecting mobile payment acceptance. This article empirically examined the factors influencing the success of mobile payment, and we implicated that if the implementation of mobile payment is to be successful for mobile commerce in any nation, adoption, acceptance and use by its citizen is imperative.

• The Journal of Industrial Distribution & Business
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• v.8 no.2
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• pp.33-38
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• 2017

Purpose - The objective of the current research is to explore success factors of the 'Night Markets' in Korea. Unlike other countries, where the markets are culturally established based upon various socioeconomic factors, the night markets are relatively new phenomena in Korea and are created by the government's support. Since the first introduction in 2011, now there are 34 Night Markets that are operating or are in the process of operation. Some of them attract nearly 100,000 customers a day, while some are discontinued shortly after the introduction due to lack of visitors. Its influence on the customers' behavioral motives of engaging in various activities in the night markets is increasing. However, because of its brief history in Korea, not much of research has cast attention on them. It is imperative to figure out the success factors of the night markets, so that other night markets can learn the secret of successful operation of the markets. Research design, data, and methodology - The research is based upon both qualitative and quantitative data. Data are collected from multiples levels of the night market related parties. Four groups are chosen: customers, night market sellers, sellers' union and government officers who are in charge of the market. Conventional survey formats are employed for customers and night market sellers. For night market union and government officers, survey and in-depth focus group interview methods are applied. Of the night markets in operation, commonalities of successful or well established ones are elaborated. Results - Night Market operation success factor are sought utilizing Porter's The Competitive Advantage of Nations model (1990). Results are shown that successful night markets commonly have satisfactory 'Factor Conditions.' Specifically, established night markets have either nearby big cities or tourist attractions in common. While these have fair 'Firm Strategy/structure/rivalry,' and 'Related and supporting industries,' they commonly demonstrate weakness in 'Demand conditions.' Conclusions - A successful night market incurs new customers not only to the market itself but also to the traditional periodical market the night markets are within. Government support to the night market can be justified where the circulation of new customer to the night market and the night market to the periodical market mechanism is in effective.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.2
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• pp.223-230
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• 2019

The study aims to contribute to the improvement of project management in Vietnam. It focuses on developing new critical success factors (CSFs) which can be used to assess the success of project management in the country. This is a promising issue considering the rapid changes occurring within the business environment. The reason is because CSFs carry great consequences on project management issues, particularly in the context of Vietnam, which is currently experiencing many big scale projects involving both local and foreign investors. Two applications are utilised. One is to adapt the business model of Belassi and Tukel (1996) to observe the transitional and emerging economy of Vietnam. The other is to examine the data collected from a survey to examine the new CSFs which can then be used to assess the success of its projects and project management in Vietnam. The research results showed some remarkable differences between CSFs of Vietnam and foreign countries in both number of success factors and its impact levels which should be paid attention by foreign project managers/owners when doing investment and project management in Vietnam. The outcome generated can be useful to project owners/managers as well as policy makers in Vietnam's business environment.

• Informatization Policy
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• v.26 no.1
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• pp.25-45
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• 2019

With the advent of the data economy, interest in using big data has increased, but conflicts with protecting personal information have been also steadily raised. In this regard, major countries are accelerating use of big data by exempting de-identified, pseudonymous personal information from protection. However, these policies have been made without the understanding that the economic value of personal information has been actually changing slowly. This paper presents the concept of 'collected information' and defines it as having public interest and therefore, not the exclusive property of the collector of such information. The paper shows the collected information has public interest in terms of personal information protection, connectivity, and universal service and public goods. It also specifies that the 'data governance' cannot be applied to the current data utilization framework that depends upon the holder's consent; rather, it raises the need to improve the practices of information provision consent or provide the beneficiary right of information use to the information holder in order to ensure the proper 'data governance' that will turn market failure into success.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.384-392
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• 2019

Big data-related research that deals with the amount of explosive information in the era of the Fourth Industrial Revolution is actively underway. Big data is an essential element that promotes the development of artificial intelligence with a wide range of data that become learning data for machine learning, or deep learning. The use of deep learning and big data in various fields has produced meaningful results. In this paper, we have investigated the use of Big Data in the cultural arts industry, focusing on video contents. Noteworthy is that big data is used not only in the distribution of cultural and artistic contents but also in the production stage. In particular, we first looked at what kind of achievements and changes the Netflix in the US brought to the OTT business, and analyzed the current state of the OTT business in Korea. After that, Netflix analyzed the success stories of 'House of Cards', which was produced / circulated through 'Deep Learning' cinematique, which is a prediction algorithm, through accumulated customer data. After that, FGI (Focus Group Interview) was held for cultural and artistic contents experts. In this way, the future prospects of Big Data in the domestic culture and arts industry are divided into technical aspect, creative aspect, and ethical aspect.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.823-830
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• 2022

The risk of project execution increases due to the enlargement and complexity of Engineering, Procurement, and Construction (EPC) plant projects. In the fourth industrial revolution era, there is an increasing need to utilize a large amount of data generated during project execution. The design is a key element for the success of the EPC plant project. Although the design cost is about 5% of the total EPC project cost, it is a critical process that affects the entire subsequent process, such as construction, installation, and operation & maintenance (O&M). This study aims to develop a system using machine-learning (ML) techniques to predict risks and support decision-making based on big data generated in an EPC project's design and construction stages. As a result, three main modules were developed: (M1) the design cost estimation module, (M2) the design error check module, and (M3) the change order forecasting module. M1 estimated design cost based on project data such as contract amount, construction period, total design cost, and man-hour (M/H). M2 and M3 are applications for predicting the severity of schedule delay and cost over-run due to design errors and change orders through unstructured text data extracted from engineering documents. A validation test was performed through a case study to verify the model applied to each module. It is expected to improve the risk response capability of EPC contractors in the design and construction stage through this study.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.25-40
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• 2019

Many companies are executing big data analysis and utilization projects to legitimize the development of new business areas or conversion of management or technical strategies. In Korea and abroad, however, such projects are failing because they are not completed within specified deadlines, which is not unrelated to the current situation in which the knowledge base for big data project risk management from an engineering perspective is grossly lacking. As such, the current study analyzes the risk factors of big data implementation and utilization projects, in addition to finding risk factors that are highly important. To achieve this end, the study extracts project risk factors via literature review, after which they are grouped using affinity methodology and sifted through expert surveys. The deduced risk factors are structuralize using factor analysis to develop a table that categorizes various types of big data project risk factors. The current study is significant that in it provides a basis for developing basic control indicators related to risk identification, risk assessment, and risk analysis. The findings from the study contribute greatly to the success of big data projects, by providing theoretical basis regarding efficient big data project risk management.

• Korean Journal of Artificial Intelligence
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• v.8 no.2
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• pp.11-16
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• 2020

Among the innovative companies leading the era of the 4th industrial revolution, the world's largest Internet company is Google. Google has grown by providing convenient services such as Internet search, Android smartphone operating system, and video. Now, Google is leading the global IT industry by continuing to develop in various new business fields based on open service platforms, artificial intelligence, and big data. In this study, an exploratory discussion was conducted on Google's success factors and future directions. The purpose of the research is to understand the development process of the IT field from the successfactors of Google and to analyze the development direction of the future IT industry. Google's success factors were its open platform policy and successful acquisitions of external companies. In fact, most of the services Google offers come from companies that have acquired and acquired them. In addition, there was a corporate culture that values and supportsthe spirit of challenge and autonomy of members who are not afraid of failure. Based on this study's review of Google's direction analysis, the follow-up study will infer the direction of the IT industry in depth and look at the future technologies that IT majors need to prepare.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.38-43
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• 2022

In this study, there are many difficulties in defining and judging creative people because there is no systematic analysis method using accurate standards or numerical values. Analyze and judge whether In the previous study, A study on the application of rule success cases through machine learning algorithm extraction, a case study was conducted to help verify or confirm the psychological personality test and aptitude test. We proposed a solution to a research problem in psychology using machine learning algorithms, Data Mining's Cross Industry Standard Process for Data Mining, and CRISP-DM, which were used in previous studies. After that, this study proposes a solution that helps to judge creative people by applying the feature selection algorithm. In this study, the accuracy was found by using seven feature selection algorithms, and by selecting the feature group classified by the feature selection algorithms, and the result of deriving the classification result with the highest feature obtained through the support vector machine algorithm was obtained.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.978-984
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• 2020

In this study, the correlation between sports records and weather data was analyzed using the big data analysis method. To this end, data was collected by API and crawling, data was processed, statistics were performed, and data visualization was performed. The subject of this study was a player who entered the regular at-bat among outfielders in the 2019 KBO League. In addition, meteorological data were analyzed by using the unpleasant index and above 70 and below 70. As a result of the study, in the various hitting indicators, which are the records that pitchers intervene, the higher the unpleasant index, the better the outfielder's record, but pitchers, walks, pitches, pitching success rates, pitches per turn, pitches per game From the records of the back, it was found that the outfielder made the pitcher difficult. It is expected that this study will help the development of the sports data industry and the performance of baseball players, baseball teams, and coaching staff.