• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.175-191
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• 2011

With the MICE(Meeting, Incentive travel, Convention, Exhibition) industry coming into the spotlight, there has been a growing interest in the domestic exhibition industry. Accordingly, in Korea, various studies of the industry are being conducted to enhance exhibition performance as in the United States or Europe. Some studies are focusing particularly on analyzing visiting patterns of exhibition visitors using intelligent information technology in consideration of the variations in effects of watching exhibitions according to the exhibitory environment or technique, thereby understanding visitors and, furthermore, drawing the correlations between exhibiting businesses and improving exhibition performance. However, previous studies related to booth recommendation systems only discussed the accuracy of recommendation in the aspect of a system rather than determining changes in visitors' behavior or perception by recommendation. A booth recommendation system enables visitors to visit unplanned exhibition booths by recommending visitors suitable ones based on information about visitors' visits. Meanwhile, some visitors may be satisfied with their unplanned visits, while others may consider the recommending process to be cumbersome or obstructive to their free observation. In the latter case, the exhibition is likely to produce worse results compared to when visitors are allowed to freely observe the exhibition. Thus, in order to apply a booth recommendation system to exhibition halls, the factors affecting the performance of the system should be generally examined, and the effects of the system on visitors' unplanned visiting behavior should be carefully studied. As such, this study aims to determine the factors that affect the performance of a booth recommendation system by reviewing theories and literature and to examine the effects of visitors' perceived performance of the system on their satisfaction of unplanned behavior and intention to reuse the system. Toward this end, the unplanned behavior theory was adopted as the theoretical framework. Unplanned behavior can be defined as "behavior that is done by consumers without any prearranged plan". Thus far, consumers' unplanned behavior has been studied in various fields. The field of marketing, in particular, has focused on unplanned purchasing among various types of unplanned behavior, which has been often confused with impulsive purchasing. Nevertheless, the two are different from each other; while impulsive purchasing means strong, continuous urges to purchase things, unplanned purchasing is behavior with purchasing decisions that are made inside a store, not before going into one. In other words, all impulsive purchases are unplanned, but not all unplanned purchases are impulsive. Then why do consumers engage in unplanned behavior? Regarding this question, many scholars have made many suggestions, but there has been a consensus that it is because consumers have enough flexibility to change their plans in the middle instead of developing plans thoroughly. In other words, if unplanned behavior costs much, it will be difficult for consumers to change their prearranged plans. In the case of the exhibition hall examined in this study, visitors learn the programs of the hall and plan which booth to visit in advance. This is because it is practically impossible for visitors to visit all of the various booths that an exhibition operates due to their limited time. Therefore, if the booth recommendation system proposed in this study recommends visitors booths that they may like, they can change their plans and visit the recommended booths. Such visiting behavior can be regarded similarly to consumers' visit to a store or tourists' unplanned behavior in a tourist spot and can be understand in the same context as the recent increase in tourism consumers' unplanned behavior influenced by information devices. Thus, the following research model was established. This research model uses visitors' perceived performance of a booth recommendation system as the parameter, and the factors affecting the performance include trust in the system, exhibition visitors' knowledge levels, expected personalization of the system, and the system's threat to freedom. In addition, the causal relation between visitors' satisfaction of their perceived performance of the system and unplanned behavior and their intention to reuse the system was determined. While doing so, trust in the booth recommendation system consisted of 2nd order factors such as competence, benevolence, and integrity, while the other factors consisted of 1st order factors. In order to verify this model, a booth recommendation system was developed to be tested in 2011 DMC Culture Open, and 101 visitors were empirically studied and analyzed. The results are as follows. First, visitors' trust was the most important factor in the booth recommendation system, and the visitors who used the system perceived its performance as a success based on their trust. Second, visitors' knowledge levels also had significant effects on the performance of the system, which indicates that the performance of a recommendation system requires an advance understanding. In other words, visitors with higher levels of understanding of the exhibition hall learned better the usefulness of the booth recommendation system. Third, expected personalization did not have significant effects, which is a different result from previous studies' results. This is presumably because the booth recommendation system used in this study did not provide enough personalized services. Fourth, the recommendation information provided by the booth recommendation system was not considered to threaten or restrict one's freedom, which means it is valuable in terms of usefulness. Lastly, high performance of the booth recommendation system led to visitors' high satisfaction levels of unplanned behavior and intention to reuse the system. To sum up, in order to analyze the effects of a booth recommendation system on visitors' unplanned visits to a booth, empirical data were examined based on the unplanned behavior theory and, accordingly, useful suggestions for the establishment and design of future booth recommendation systems were made. In the future, further examination should be conducted through elaborate survey questions and survey objects.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.53-77
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• 2015

Mobile commerce provides a convenient shopping experience in which users can buy products without the constraints of time and space. Mobile commerce has already set off a mega trend in Korea. The market size is estimated at approximately 15 trillion won (KRW) for 2015, thus far. In the Korean market, social commerce and open market are key components. Social commerce has an overwhelming open market in terms of the number of users in the Korean mobile commerce market. From the point of view of the industry, quick market entry, and content curation are considered to be the major success factors, reflecting the rapid growth of social commerce in the market. However, academics' empirical research and analysis to prove the success rate of social commerce is still insufficient. Henceforward, it is to be expected that social commerce and the open market in the Korean mobile commerce will compete intensively. So it is important to conduct an empirical analysis to prove the differences in user experience between social commerce and open market. This paper is an exploratory study that shows a comparative analysis of social commerce and the open market regarding user experience, which is based on the mobile users' reviews. Firstly, this study includes a collection of approximately 10,000 user reviews of social commerce and open market listed Google play. A collection of mobile user reviews were classified into topics, such as perceived usefulness and perceived ease of use through LDA topic modeling. Then, a sentimental analysis and co-occurrence analysis on the topics of perceived usefulness and perceived ease of use was conducted. The study's results demonstrated that social commerce users have a more positive experience in terms of service usefulness and convenience versus open market in the mobile commerce market. Social commerce has provided positive user experiences to mobile users in terms of service areas, like 'delivery,' 'coupon,' and 'discount,' while open market has been faced with user complaints in terms of technical problems and inconveniences like 'login error,' 'view details,' and 'stoppage.' This result has shown that social commerce has a good performance in terms of user service experience, since the aggressive marketing campaign conducted and there have been investments in building logistics infrastructure. However, the open market still has mobile optimization problems, since the open market in mobile commerce still has not resolved user complaints and inconveniences from technical problems. This study presents an exploratory research method used to analyze user experience by utilizing an empirical approach to user reviews. In contrast to previous studies, which conducted surveys to analyze user experience, this study was conducted by using empirical analysis that incorporates user reviews for reflecting users' vivid and actual experiences. Specifically, by using an LDA topic model and TAM this study presents its methodology, which shows an analysis of user reviews that are effective due to the method of dividing user reviews into service areas and technical areas from a new perspective. The methodology of this study has not only proven the differences in user experience between social commerce and open market, but also has provided a deep understanding of user experience in Korean mobile commerce. In addition, the results of this study have important implications on social commerce and open market by proving that user insights can be utilized in establishing competitive and groundbreaking strategies in the market. The limitations and research direction for follow-up studies are as follows. In a follow-up study, it will be required to design a more elaborate technique of the text analysis. This study could not clearly refine the user reviews, even though the ones online have inherent typos and mistakes. This study has proven that the user reviews are an invaluable source to analyze user experience. The methodology of this study can be expected to further expand comparative research of services using user reviews. Even at this moment, users around the world are posting their reviews about service experiences after using the mobile game, commerce, and messenger applications.

• The Korean Nurse
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• v.20 no.4 s.112
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• pp.50-59
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• 1981

간호학생들이 당연하고 있는 문제점 미래의 간호학생들이 교육문제를 논하기 위하여는 간호학생들이 가지고 있는 문제점을 파악하고 또 이해하는 것이 우선순위가 될 것이다. 간호학생들이 문제점에 대한 연구는 한국에서 뿐아니라 미국에서도 꽤 많이 시행되어져 왔으며 특히 간호학과정에서 중간 탈락되는 중퇴자들에 대한 연구들 중에 이러한 문제점에 대해서 언급한 것이 많다. 고등학교를 졸업하고 곧 대학과정에 진학한 학생들을 대상으로 조사 보고될 Munro의 자료에 의하면 전문대학과정에서 27$\%$, 대학과정에서는 41$\%$의 간호학생들이 간호학과정에서 중간 탈락하고 있음이 보고되고 있다. 이들이 중간탈락하는 데에는 여러 가지 이유가 있으나 그 중 ''간호학에 흥미를 잃어서''가 가장 큰 이유로 보고되고 있다. 이곳 한국사회에서도 역시 비슷한 현상을 보이고 있다. 그러나 대학입시경쟁과 대학내에서의 전과가 거의 허용되지 않는 특수여건이기 때문에 학교를 중간 탈락하는 율은 미국이 보고만큼 높지는 않으나 역시 ''간호학에 흥미를 잃는다''는 것이 간호학생들의 가장 큰 문제점으로 대두되고 있다. 최근 한국에서 시행된 간호학생들에 관한 연구(표 1 참조)에 의하면 간호학생들의 학문에 대한 만족도는 조사자의 35$\~$50$\%$정도에 불과하였고 더우기 이 비율은 고학년에 올라갈수록 더욱 감소되고 있는 경향을 보이고 있다. 한국에서 시행된 어느 연구보고에 의하면 간호학에 실망했다고 생각하는 학생이 전체의 67$\%$였으며, 다른 학교로 전과를 희망한 경험이 있다는 학생이 71$\%$나 되는 것으로 보고되고 있다. 그러나 왜 흥미를 잃게 되는지 그 이유에 대하여 설명해 주는 연구는 많지 않았다. 미국의 한 저자는 간호학생들이 간호학에 흥미를 잃게 되는 원인을 간호원의 역할에 대한 이해가 정확하지 못한 것과 졸업 후 진로기회에 대한 인식부족 때문이라고 추측하고 있다. 간호학에 흥미를 잃게 되는 이유는 크게 다음의 세 가지로 분류 요약될 수 있다. 첫째, 간호학을 전공으로 택한 동기이다. 간호학의 특수성으로 인하여 학생들이 간호학을 전공으로 택한 동기도 다른 전공분야보다는 훨씬 다른 여러 종류를 보이고 있다. 즉, 종교적 이유, 다른 사람들에게 봉사할 수 있는 직업이기 때문에, 쉽게 취업을 할 수 있어서, 결혼 후에도 직업을 가질 수 있기 때문에, 외국으로 쉽게 취업할 수 있어서 등이 간호학을 선택한 이유로 보고되고 있다. 흥미나 적성에 맞다고 생각하기 때문에 간호학을 택한 학생의 수는 다른 과에 비하여 훨씬 적다. 이러한 흥미나 적성 때문이 아닌 여러 가지 다른 이유들로 인하여 간호학을 택한 경우에 특히 간호학에 쉽게 흥미를 잃어버리는 것을 볼 수 있다. 간호학에 현실적인 개념을 가지고 있는 학생들일수록 추상적이고 현실적인 개념을 가지고 있는 학생들보다 더 간호학에 지속적인 흥미를 가지며 중간에 탈락하는 율이 훨씬 적다는 것이 많은 연구에서 보고되었다. 또한 흥미나 적성 때문에 간호학을 택하였다는 학생들이 다른 과로 전과를 희망하는 율이 낮다는 것도 보고되었다. 둘째, 교과내용자체나 실습에 대한 불만족이다. 간호학에 대한 체계적인 교과내용의 결여, 과중한 과제물, 임상실습에서의 욕구불만, 실습으로 인한 부담, 지식과 실습의 차이점에 대한 갈등 등이 주요 이유로 보고되고 있다. 대부분의 연구들이 이 교과목이나 실습에 대한 불만족, 특히 실습경험에서의 갈등을 학생들이 흥미를 잃는 가장 중요한 요인이 되는 것으로 보고하고 있다. 어느 한 연구에서는 응답자의 90$\%$가 임상실습에 만족하지 못한다고 응답하였으며 그들 중의 88$\%$가 실습감독에 문제가 있다고 생각한다고 보고하였다. 셋째, 교수들에 대한 불만족이다. 대부분의 연구들이 학년이 올라가면 갈수록 교수에 대한 신뢰도가 낮아지며 또한 그에 비례하여 간호학에 대한 만족도가 낮아진다고 보고하고 있다. 교육내용에 대한 전문지식의 결여, 학생들과의 인간적인 관계의 결여, 교수법에 대한 불만족 등이 교수에 대한 불만의 주요내용으로 보고되었다. 미래의 간호에 부응할 학생교육 계속적인 사회적 변동과 더불어 급격하게 변화하고 있는 일반인들의 건강에 대한 요구도와 앞에서 기술한 문제점 등을 감안할 때 학생들에게 동기를 부여하고 간호학에 확신감을 가질 수 있도록 준비시키므로써 간호환경에서 실망하기보다는 오히려 그것을 받아들여 변화하는 사회요구에 책임감을 느낄 수 있도록 교육시키는 것이 미래의 간호학생을 준비시키는데 가장 중요한 요인이라고 할 수 있겠다. 이러한 교육을 위하여 다음의 두가지 안을 제시한다. 1. 교수와 학생간의 관계-서로의 좋은 동반자 : 교수들이 학생에게 미치는 영향, 특히 학생들의 성취도에 대한 영향에 대하여는 이미 많은 연구가 시행되었다. Tetreault(1976)가 간호학생들의 전문의식에 영향을 미치는 요인에 대하여 연구한 바에 의하면 다른 어느 것보다도 교수의 전문의식여부가 학생들의 전문의식 조성에 가장 큰 영향을 미친다고 하였다. 또한 학생들이 교수에게 신뢰감을 가지고 있을때, 교수들이 전문가로서의 행동을 하는 것을 보았을때 비로서 배움이 증가된다고 하였다. Banduras는 엄격하고 무서운 교수보다는 따뜻하고 인간적인 교수에게 학생들이 더 Role Model로서 모방하려는 경향을 나타낸다고 보고 하였다. 그러면 어떻게 학생에게 신뢰받는 교수가 될 수 있겠는가? apos;학생들의 요구에 부응할 때apos;라고 한마디로 표현할 수 있을 것이다. Lussier(1972)가 언급한 것처럼 학생들의 요구에 부응하지 못하는 교육은 Piaget이 언급한 교육의 기본 목표, 즉 개인에게 선배들이 한 것을 그대로 반복하여 시행하도록 하는 것이 아니라 새로운 것을 시도할 수 있는 능력을 가지게 하는 목표에는 도달할 수 없으며 이러한 목표는 간호학에도 가장 기본이 되어야 할 기본목표이기 때문이다. 학생들이 현재 어떤 요구를 가지고 있으며 또 어떤 생각을 하고 있는지 계속 파악하고 있는 것이 학생요구에 부응하는 교육을 할 수 있는 기본조건이 될 것이다. 의외로 많은 교수들이 학생들을 이해하고 있다고 생각하고 있으나 잘못 이해하고 있는 경우가 많다. 표 2는 현 간호학생들이 생각하고 있는 가치관과 문제점을 파악하고 또 교수가 그 가치관과 문제점을 어느 정도 파악하고 있는지 알아보기 위하여 일개 4년제 대학 200여명의 학생과 그 대학에 근무하는 18명의 교수진을 대상으로 질문한 결과를 간략하게 보고한 것이다. 또한 여기에서 학생이 보고하는 가치관, 문제점, 교수에게 바라는 점이 교수가 이해하고 있는 것과 차이가 있다는 것도 보여주고 있다. 우리가 학생들의 요구를 파악할 수 있도록 귀를 기울이고 이해하며, 그 요구에 부응하려고 노력할때 진정한 교수와 학생간의 관계가 이루어질 수 있을 것이며 이때 비로서 우리는 apos;partnershipapos;을 이룰 수 있을 것이다. 이때 간호학에 대한 실망은 줄어들 수 있을 것이며 우리도 학생들에게 전문가적인 태도를 함양시켜줄 수 있는 기회를 부여할 수 있을 것이다. 이렇게 될때 앞으로 기다리고 있는 미지의 의무에 효과적으로 또 적극적으로 대처할 수 있는 자질을 형성한 학생들을 준비해 낼 수 있을 것이다. 2. 간호모델에 의한 교과과정의 확립과 임상실습에의 적용 : 교과과정이 학생들의 모양을 만들어주는 하나의 기본틀이라고 말할 수 있다면 미래의 요구에 부응하는 학생들을 준비시키기 위하여 지금까지와는 다른 새로운 방향의 교과과정이 필요하다는 것은 재론할 필요가 없을 것이다. 이미 진취적인 간호대학에서는 guided design systems approach 또는 integrated curriculum 등의 새로운 교과과정을 시도하고 있음은 알려진 사실이다. 물론 간호모델에 준한 교과과정을 발전시키는데 대한 장점과 이에 수반되는 여러가지 새로운 문제점에 대하여 많은 논란이 있으나 모든 교과과정이 처음 시도될 때부터 완전한 것이 있을 수 없으며 시간이 지남에 따라 성숙되는 것임을 감안해 볼 때 이러한 새로운 교과과정에의 시도는 미래의 새로운 간호방향에 필수적인 사업이라고 하겠다. 이러한 교과과정을 개발하는데 몇가지 게안점을 첨부하려 한다. (1) 새로운 교과과정의 개발은 처음부터 끝까지 모든 교수진의 협력과 참여로 이루어져야 한다. (2) 비록 처음에는 어렵고 혼란이 있더라도 교과과정은 의학모델이 아닌 간호모델을 중심으로 이루어져야 한다. (3) 간호모델에서 다루어지는 개념들은 모두 직접 간호업무에 적용될 수 있는 것으로 선택되어야 한다. (4) 교과과정의 결과로 배출되는 학생들의 준비정도는 그 지역사회에 적합하여야 한다. (5) 그 지역사회의 고유한 문화적 요소가 포함되어야 한다. 아직 우리는 간호분야 내부의 갈등을 해결하지 못하고 있는 시기에 있다. 우리 내부의 문제점을 잘 해결할 수 있을때 외부와의 갈등에 잘 대처할 수 있을 것이다. 내부의 갈등을 잘 해결하기 위한 힘을 모으기 위하여는 동반자, 즉 교수와 학생, 간호교육자와 임상간호원 등이 서로 진정한 의미의 동반자 될때 가장 중요한 해결의 실마리가 될 것이다.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.71-84
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• 2013

Log data, which record the multitude of information created when operating computer systems, are utilized in many processes, from carrying out computer system inspection and process optimization to providing customized user optimization. In this paper, we propose a MongoDB-based unstructured log processing system in a cloud environment for processing the massive amount of log data of banks. Most of the log data generated during banking operations come from handling a client's business. Therefore, in order to gather, store, categorize, and analyze the log data generated while processing the client's business, a separate log data processing system needs to be established. However, the realization of flexible storage expansion functions for processing a massive amount of unstructured log data and executing a considerable number of functions to categorize and analyze the stored unstructured log data is difficult in existing computer environments. Thus, in this study, we use cloud computing technology to realize a cloud-based log data processing system for processing unstructured log data that are difficult to process using the existing computing infrastructure's analysis tools and management system. The proposed system uses the IaaS (Infrastructure as a Service) cloud environment to provide a flexible expansion of computing resources and includes the ability to flexibly expand resources such as storage space and memory under conditions such as extended storage or rapid increase in log data. Moreover, to overcome the processing limits of the existing analysis tool when a real-time analysis of the aggregated unstructured log data is required, the proposed system includes a Hadoop-based analysis module for quick and reliable parallel-distributed processing of the massive amount of log data. Furthermore, because the HDFS (Hadoop Distributed File System) stores data by generating copies of the block units of the aggregated log data, the proposed system offers automatic restore functions for the system to continually operate after it recovers from a malfunction. Finally, by establishing a distributed database using the NoSQL-based Mongo DB, the proposed system provides methods of effectively processing unstructured log data. Relational databases such as the MySQL databases have complex schemas that are inappropriate for processing unstructured log data. Further, strict schemas like those of relational databases cannot expand nodes in the case wherein the stored data are distributed to various nodes when the amount of data rapidly increases. NoSQL does not provide the complex computations that relational databases may provide but can easily expand the database through node dispersion when the amount of data increases rapidly; it is a non-relational database with an appropriate structure for processing unstructured data. The data models of the NoSQL are usually classified as Key-Value, column-oriented, and document-oriented types. Of these, the representative document-oriented data model, MongoDB, which has a free schema structure, is used in the proposed system. MongoDB is introduced to the proposed system because it makes it easy to process unstructured log data through a flexible schema structure, facilitates flexible node expansion when the amount of data is rapidly increasing, and provides an Auto-Sharding function that automatically expands storage. The proposed system is composed of a log collector module, a log graph generator module, a MongoDB module, a Hadoop-based analysis module, and a MySQL module. When the log data generated over the entire client business process of each bank are sent to the cloud server, the log collector module collects and classifies data according to the type of log data and distributes it to the MongoDB module and the MySQL module. The log graph generator module generates the results of the log analysis of the MongoDB module, Hadoop-based analysis module, and the MySQL module per analysis time and type of the aggregated log data, and provides them to the user through a web interface. Log data that require a real-time log data analysis are stored in the MySQL module and provided real-time by the log graph generator module. The aggregated log data per unit time are stored in the MongoDB module and plotted in a graph according to the user's various analysis conditions. The aggregated log data in the MongoDB module are parallel-distributed and processed by the Hadoop-based analysis module. A comparative evaluation is carried out against a log data processing system that uses only MySQL for inserting log data and estimating query performance; this evaluation proves the proposed system's superiority. Moreover, an optimal chunk size is confirmed through the log data insert performance evaluation of MongoDB for various chunk sizes.

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.443-472
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• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.

• Korean small business review
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• v.31 no.2
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• pp.85-102
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• 2009

With the continued globalization of world markets, transfer pricing has become one of the dominant sources of controversy in international taxation. Transfer pricing is the process by which a multinational corporation calculates a price for goods and services that are transferred to affiliated entities. Consider a Korean electronic enterprise that buys supplies from its own subsidiary located in China. How much the Korean parent company pays its subsidiary will determine how much profit the Chinese unit reports in local taxes. If the parent company pays above normal market prices, it may appear to have a poor profit, even if the group as a whole shows a respectable profit margin. In this way, transfer prices impact the taxable income reported in each country in which the multinational enterprise operates. It's importance lies in that around 60% of international trade involves transactions between two related parts of multinationals, according to the OECD. Multinational enterprises (hereafter MEs) exert much effort into utilizing organizational advantages to make global investments. MEs wish to minimize their tax burden. So MEs spend a fortune on economists and accountants to justify transfer prices that suit their tax needs. On the contrary, local governments are not prepared to cope with MEs' powerful financial instruments. Tax authorities in each country wish to ensure that the tax base of any ME is divided fairly. Thus, both tax authorities and MEs have a vested interest in the way in which a transfer price is determined, and this is why MEs' international transfer prices are at the center of disputes concerned with taxation. Transfer pricing issues and practices are sometimes difficult to control for regulators because the tax administration does not have enough staffs with the knowledge and resources necessary to understand them. The authors examine transfer pricing practices to provide relevant resources useful in designing tax incentives and regulation schemes for policy makers. This study focuses on identifying the relevant business and environmental factors that could influence the international transfer pricing of MEs. In this perspective, we empirically investigate how the management perception of related variables influences their choice of international transfer pricing methods. We believe that this research is particularly useful in the design of tax policy. Because it can concentrate on a few selected factors in consideration of the limited budget of the tax administration with assistance of this research. Data is composed of questionnaire responses from foreign firms in Korea with investment balances exceeding one million dollars in the end of 2004. We mailed questionnaires to 861 managers in charge of the accounting departments of each company, resulting in 121 valid responses. Seventy six percent of the sample firms are classified as small and medium sized enterprises with assets below 100 billion Korean won. Reviewing transfer pricing methods, cost-based transfer pricing is most popular showing that 60 firms have adopted it. The market-based method is used by 31 firms, and 13 firms have reported the resale-pricing method. Regarding the nationalities of foreign investors, the Japanese and the Americans constitute most of the sample. Logistic regressions have been performed for statistical analysis. The dependent variable is binary in that whether the method of international transfer pricing is a market-based method or a cost-based method. This type of binary classification is founded on the belief that the market-based method is evaluated as the relatively objective way of pricing compared with the cost-based methods. Cost-based pricing is assumed to give mangers flexibility in transfer pricing decisions. Therefore, local regulatory agencies are thought to prefer market-based pricing over cost-based pricing. Independent variables are composed of eight factors such as corporate tax rate, tariffs, relations with local tax authorities, tax audit, equity ratios of local investors, volume of internal trade, sales volume, and product life cycle. The first four variables are included in the model because taxation lies in the center of transfer pricing disputes. So identifying the impact of these variables in Korean business environments is much needed. Equity ratio is included to represent the interest of local partners. Volume of internal trade was sometimes employed in previous research to check the pricing behavior of managers, so we have followed these footsteps in this paper. Product life cycle is used as a surrogate of competition in local markets. Control variables are firm size and nationality of foreign investors. Firm size is controlled using dummy variables in that whether or not the specific firm is small and medium sized. This is because some researchers report that big firms show different behaviors compared with small and medium sized firms in transfer pricing. The other control variable is also expressed in dummy variable showing if the entrepreneur is the American or not. That's because some prior studies conclude that the American management style is different in that they limit branch manger's freedom of decision. Reviewing the statistical results, we have found that managers prefer the cost-based method over the market-based method as the importance of corporate taxes and tariffs increase. This result means that managers need flexibility to lessen the tax burden when they feel taxes are important. They also prefer the cost-based method as the product life cycle matures, which means that they support subsidiaries in local market competition using cost-based transfer pricing. On the contrary, as the relationship with local tax authorities becomes more important, managers prefer the market-based method. That is because market-based pricing is a better way to maintain good relations with the tax officials. Other variables like tax audit, volume of internal transactions, sales volume, and local equity ratio have shown only insignificant influence. Additionally, we have replaced two tax variables(corporate taxes and tariffs) with the data showing top marginal tax rate and mean tariff rates of each country, and have performed another regression to find if we could get different results compared with the former one. As a consequence, we have found something different on the part of mean tariffs, that shows only an insignificant influence on the dependent variable. We guess that each company in the sample pays tariffs with a specific rate applied only for one's own company, which could be located far from mean tariff rates. Therefore we have concluded we need a more detailed data that shows the tariffs of each company if we want to check the role of this variable. Considering that the present paper has heavily relied on questionnaires, an effort to build a reliable data base is needed for enhancing the research reliability.