This paper proposes an integrative framework for determining a dominant design in the mobile operation systems. A dominant design has emerged as a de facto standard from traditional industries to ICT. ICT-related industries have been reorganized around the mobile industry in which the mobile operation system can be seen as a strategical keystone. In this paper, we develop a holistic approach for the emergence of a dominant design in the mobile operation systems. Firstly, we combined an integrative framework based on previous research findings with new determinants derived from cases of the mobile operation systems. Secondly, we categorized all determinants according to technological, firm-level and environmental factors within our proposed framework. Finally, we compared this framework to patterns coded from cases which include Android and iOS. This results show that a dominant design is likely to emerge as a result of the interaction of the determinants, not the influence of a single determinant. Furthermore, our proposed framework may extend the existing literature on dominant designs in both researchers and practitioners and provide implications to actors for establishing a competition strategy in the mobile telecommunication ecosystems.

This study attempts to explore the difference of innovation sources between high-tech industry and mid-tech industry through patent analysis. After extracting 119 corporates, commonly surveyed in 2007 HCCP(Human Capital Corporate Panel) and 2005~2006 Korea Innovation Survey, their patents applied for the Korean Intellectual Property Office in 2007~2012 are analysed mainly through negative binomial regression model. Analytical results shows that external information source could be opposite effects to technological innovation depending on technological level and industrial characteristics. The current results are still bounded in the statistical significance, mainly due to the limited observations and information.

Technological, policy and economic factors are both important variables in maximizing the results of a national R&D program and key indicators in evaluating an R&D program's eligibility for financial support. Economic analysis, in particular, is used when selecting R&D programs, setting priorities, and estimating economic effects. This paper examines a series of methodological issues related to the economic analysis of national R&D programs within the framework of the current preliminary feasibility evaluation system, and proposes alternative approaches to each of the issues discussed. The issues include the definition of R&D valuation and establishment of valuation factors; estimation of sales attributable to R&D investment; assessment of the total economic value of R&D as intellectual assets; estimation of R&D benefits and assumption of related to sales; and the application of discount rates based on the weighted average cost of capital. Finally, this study presents directions for future research on analytical procedures and methods of improving the reliability of the results of economic analysis within the national technology planning system.

With the rapid increase of social network usage, there are emerging trends of adopting social information among online users in building recommendation system. This study aims to investigate whether the additional usage of social information can improve recommendation performance in recommendation system and how much the improvement can be different according to the product involvement level. As an experiment result, social information does not affect positively to the recommendation accuracy but affect significantly to the recommendation quality. Also social information contributed more sensitively to the improvement of recommendation quality in high product involvement domain.

This study proposes the accurate economic effect (employment inducement coefficient, hiring inducement coefficient, index of the sensitivity of dispersion, index of the power of dispersion, and ratio of value added) of Korea software industry by analyzing the inter-industry relation using the modified inter-industry table. Some previous studies related to the inter-industry analysis were reviewed and the key problems were identified. First, in the current inter-industry table publishedby the Bank of Korea, the output of software industry includes not only the output of pure software industry (package software and IT services) but also the output of non-software industry due to the misclassification of the industry. This causes the output to become bigger than the actual output of the software industry. Second, during rewriting the inter-industry table, the output is changing. The inter-industry table is the table in the form of rows and columns, which records the transactions of goods and services among industries which are required to continue the activities of each industry. Accordingly, if only an output of a specific industry is changed, the reliability of the table would be degraded because the table is prepared based on the relations with other industries. This possibly causes the economic effect coefficient to degrade reliability, over or under estimated. This study tries to correct these problems to get the more accurate economic effect of the software industry. First, to get the output of the pure software section only, the data from the Korea Electronics Association(KEA) was used in the inter-industry table. Second, to prevent the difference in the outputs during rewriting the inter-industry table, the difference between the output in the current inter-industry table and the output from KEA data was identified and then it was defined as the non-software section output for the analysis. The following results were obtained: The pure software section's economic effect coefficient was lower than the coefficient of non-software section. It comes from differenceof data to Bank of Korea and KEA. This study hasa signification from accurate economic effect of Korea software industry.

Forecasting technology in economic activity is a quite intricate procedure so researchers should grasp the point of the data to use. Diffusion models have been widely used for forecasting market demand and measuring the degree of technology diffusion. However, there is a question that a model, explaining a certain market with goodness of fit, always shows good performance with markets of different conditions. The primary aim of this paper is to explore diffusion models which are frequently used by researchers, and to help readers better understanding on those models. In this study, Logistic, Gompertz and Bass models are used for forecasting Global Wireline Subscribers and the performance of models is measured by Mean Absolute Percentage Error. Logistic model shows better MAPE than the other two. A possible extension of this study may verify which model reflects characteristics of industry better.

With the advent of smart devices, users are able to connect to each other through the Internet without the constraints of time and space. Because the Internet has become increasingly important to users in their everyday lives, reliance on it has grown. As a result, the number of web sites constantly increases and the competition between these sites becomes more intense. Even those sites that operate successfully struggle to establish new strategies for customer retention and customer development in order to survive. Many companies use various customer information in order to establish marketing strategies based on customer group segmentation A method commonly used to determine the customer groups of individual sites is to infer customer characteristics based on the customers' demographic information. However, such information cannot sufficiently represent the real characteristics of customers. For example, users who have similar demographic characteristics could nonetheless have different interests and, therefore, different buying needs. Hence, in this study, customers' interests are first identified through an analysis of their Internet news inquiry records. This information is then integrated in order to identify each web category. The study then analyzes the possibilities for the practical use of the proposed methodology through its application to actual Internet news inquiry records and web site browsing histories.

Demand of spectrum resource is tremendously increasing and this trend will continue as more IT services such as cloud computing, smart devices, Internet of Things are provided through wireless network. Recent development of spectrum sharing technology has drawn attention to spectrum policy makers as a promising way to overcome the expected spectrum shortage problem. However, technology-based solution to spectrum shortage problem may not be sustainable since the solution affect only one aspect of spectrum sharing ecosystem. To understand the whole picture of spectrum shortage problem, policies to vitalize spectrum sharing ecosystem were proposed based on the analysis of System Dynamics causal map in the previous study. This study compares and analyzes the effect of those proposed vitalization policies by using System Dynamics simulation. Among seven alternative policies, combined application of demand acceleration policy and technology development policy was found to be more effective for better utilization of spectrum. The effect of demand acceleration policy was offset when other policies are applied together except supply acceleration policy which shows better spectrum sharing.

As mobile traffic is growing, the demand for spectrum is increasing but the deficiency of spectrum becomes serious as the supply is restricted essentially. For resolving the issue, spectrum sharing system is discussed from the technical and regulatory point of view, where multiple radio users occupy same frequency. In this paper, the policies and adoptions of spectrum sharing system in some countries are analyzed with a focus on TV white space and licensed shared access, which are based on unlicensed and licensed spectrum usage respectively. Some legal and regulatory plans to adopt and activate spectrum sharing in the Radio Waves Act system of Korea are proposed as well.

Data are dramatically increased and big data technology is spotlighted innovative technology among the latest information technologies. Organizations are interested in adoption of big data system to analyze various data format and to identify new business opportunity. The purpose of this study is to build a unified model for a system adoption through analysis of impact that affects behavioral intention and usage behavior of using big data. This study in addition to Technology-Organization-Environment (TOE), that is used the introduction of organizational studies, and Diffusion of Innovation (DOI) have implemented an extended unified model including the unified theory of acceptance and use of technology (UTAUT) that is usually used in personal level adoption study. The hypothesis was set up after implementing research model, and then got 411 effective survey data to target the member of organizations. As a result, all models (UTAUT, TOE, DOI) are affect to behavioral intention and usage behavior. It is verified that the suggested unified model was appropriate.

Sharing Economy is the modern main item with ICT Development. Of course sharing economic item is the old and long run mainstream, but by the ICT technological development sharing economy is the fostering and affluent factors in the world economic growth. Though, in Korea, till now sharing economy is minimal, that will growth sharply. We can track various business models of sharing economy. Sharing economy is to buy use right not ownership. With the sharing economic business model wee can make also financial sharing model. In finance model we can divide two kind models. First, we can trace small size lending model with p2p type. And second, we can make financial information transaction model. But till now sharing economic system is not activated, because of many reasons. To activate, first we have to set law and various standards, and also government actively support many sharing economy firms and institutions. To catch up developed countries in the field of sharing economy we have to make aggressive and flexible rules and standards.

Rapidly shifting to aging population is a global trend, and one of the challenging issue for the government, business and welfare perspective. In this paper, we focus on application potentials of information and communication technologies, to capture the insights for effectively coping with population aging issue. As the research for silver ICT field is rather limited, we adopt case study research method to extract policy implications and related foundation research agenda. As such, we first investigated comprehensive up-to-date trends, cases for innovative ICT applications, and policy initiatives mainly from the works of OECD nations. With reference to the review findings, we propose policy implications and guidelines for ICT innovations which contributes better quality of life and continuing job opportunities for silver population. The results provides insights for government policy initiative and further research in silver ICT area.