• Proceedings of the Korea Society of Design Studies Conference
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• 1998.10a
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• pp.44-45
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• 1998

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.1
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• pp.261-268
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• 2017

The development of ICT technology centered on mobile smart platforms have been emerging as a shared economic platform based on collaborative consumption. In this study, we analyze what factors affect success and failure in commercialized shared economic platforms from 2008 to 2016, and present what policy factors are needed to activate shared economic platform. To do this, we analyze successful cases of shared economic platforms and failed cases, derive key variables that affect success and failure, and conduct inductive analysis based on ID 3 algorithm based on them. Through this, we present the policy factors for the commercial success of the shared economic platform by deriving the rules for the success and failure of the shared economic platform.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.343-352
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• 2020

Modular integrated construction (MiC) is an innovative construction method where components of a building are manufactured in an offsite factory, trucked to the job site in sections, set in place with cranes, and assembled together to form a whole building. Where circumstances merit, favorable conditions exist and implemented effectively; MiC improves project performance. However, several key factors need to converge during implementation to realize the full benefits of MiC. Thus, a thorough understanding of the factors which are critical to the success of MiC projects is imperative. Drawing on a systematic review of 47 empirical studies, this research identified 25 key success factors (KSFs) for MiC projects. Of these, the five topmost cited KSFs for MiC projects include effective working collaboration and communication among project participants; standardization, optimization, automation and benchmarking of best practices; effective supply chain management; early design freeze and completion; and efficient procurement method and contracting. The study further proposed a conceptual model of the KSFs, highlighting the interdependences of people, processes, and technology-related KSFs for the effective accomplishment of MiC projects. The set of KSFs is practically relevant as they constitute a checklist of items for management to address and deal with during the planning and execution of MiC projects. They also provide a useful basis for future empirical studies tailored towards measuring the performance and success of MiC projects. MiC project participants and stakeholders will find this research useful in reducing failure risks and achieving more desired performance outcomes. One potential impact of the study is that it may inform, guide, and improve the successful implementation of MiC projects in the construction industry. However, the rigor of the analysis and relative importance ranking of the KSFs were limited due to the absence of data.

• Plant Journal
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• v.5 no.2
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• pp.62-67
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• 2009

The capability of design and engineering of global EPC companies has long been equalized through past similar construction experiences. Among various key factors in the success of EPC project, the capability of engineering is considered to be the most important factor since the engineering is preceding activities of EPC contract. The failure of engineering may adversely affect the subsequent procurement & construction activities and in turn may cause cost overrun or schedule delay. Therefore, an EPC company needs to continue to improve the engineering capabilities for the success of project. The engineering capabilities can be further improved if the EPC company should prevent recurrence of similar design faults that were previously committed. This study is intended to present how to make the most of the failure examples from previous projects towards a success of project. Failure is but a stepping stone to success. The EPC company can obtain useful lessons from the analysis of past failure examples.

• International journal of advanced smart convergence
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• v.7 no.3
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• pp.79-91
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• 2018

Service Oriented Architecture (SOA) has appeared as an absorbing architectural approach that empowers the available systems to reveal their performance in the act of services, without creating important changes to the systems. This approach, due to its flexibility of adoption, has been widely recognized as an appropriate approach for implementing in organizations by many scholars and practitioners. Though, there are many studies that depict success factors of SOA; at the same time a few minor cases of failure has also been reported in the literature. In spite of the availability of rich material on SOA (in general), there is no systematic literature review on the potential aspect of SOA adoption factors. Hence, this article presents a systematic review of existing studies related to the SOA adoption and its success and failure factors from 2009 to 2015. The principle purpose of the study is to bring forward the existing issues and share our findings with researchers. Moreover, the findings of this paper would help IT experts in organizations to concentrate on the key factors highlighted in this study, so that they could decide whether it is advisable to adopt SOA or not in their context.

• Journal of Korea Multimedia Society
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• v.21 no.2
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• pp.281-288
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• 2018

Crowdfunding has seen an enormous rise, becoming a new alternative funding source for emerging startup companies in recent years. Despite the huge success of crowdfunding, it has been reported that only around 40% of crowdfunding campaigns successfully raise the desired goal amount. The purpose of this study is to investigate key factors influencing successful fundraising on crowdfunding platforms. To this end, we mainly focus on contents of project campaigns, particularly their linguistic cues as well as multiple features extracted from project information and multimedia contents. We reveal which of these features are useful for predicting success of crowdfunding campaigns, and then build a predictive model based on those selected features. Our experimental results demonstrate that the built model predicts the success or failure of a crowdfunding campaign with 86.15% accuracy.

• Journal of the Korean Society of Food Culture
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• v.34 no.4
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• pp.424-431
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• 2019

The purpose of this study is to analyze and evaluate the key success factors for the fast food industry in the region of Lahore Pakistan. Fast food concept developed very speedily in the last few years in Lahore region. The success or failure of a fast food industry based on some factors like Physical environment, Brand-name, Food quality, Price, Taste, Promotional activity, Habitual consumption, Health threats, Consumer expectation, and Family meal. To identify which of these factors has a greater influence on consumer satisfaction, four fast food restaurants such as McDonald's, PIZZA HUT, KFC, and subway were targeted randomly. The proposed research is quantitative in nature and for data collection; a random sampling technique was used. A questionnaire survey answered by 273 people was considered in this research. Data have been analyzed through statistical techniques. It is observed that Brand name, Food quality, Physical environment, Health threats, Price, Family meals, Habitual consumption, and Consumer expectation showed significant impacts on Fast food industry compared to other factors evaluated herein.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.65-75
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• 2021

This study explores multiple variables of an OTT service for discovering hidden relationship between rating and the other variables of each successful and failed content, respectively. In order to extract key variables that are strongly correlated to the rating across the contents, this work analyzes 170 Netflix original dramas and 419 movies. These contents are classified as success and failure by using the rating site IMDb, respectively. The correlation between the contents, which are classified via rating, and variables such as violence, lewdness and running time are analyzed to determine whether a certain variable appears or not in each successful and failure content. This study employs a regression analysis to discover correlations across the variables as a main analysis method. Since the correlation between independent variables should be low, check multicollinearity and select the variable. Cook's distance is used to detect and remove outliers. To improve the accuracy of the model, a variable selection based on AIC(Akaike Information Criterion) is performed. Finally, the basic assumptions of regression analysis are identified by residual diagnosis and Dubin Watson test. According to the whole analysis process, it is concluded that the more director awards exist and the less immatatable tend to be successful in movies. On the contrary, lower fear tend to be failure in movies. In case of dramas, there are close correlations between failure dramas and lower violence, higher fear, higher drugs.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.141-158
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• 2023

From the perspective of an entrepreneur, one of the most important factors for understanding the inherent limitations of a startup, reducing the risk of failure, and succeeding is the composition of the talent, that is, the founding team. Therefore, a common concern experienced by entrepreneurs in the pre-entrepreneurship stage or the early stage of startup is the choice between independent startups and co-founding start-up. Nonetheless, in Korea, the share of independent entrepreneurship is significantly higher than that of co-founding start-up. On the other hand, focusing on the fact that many successful global innovative companies are in the form of co-founding start-up, the success factors of co-founding start-up were examined. Most of the related preceding studies are studies that identify the capabilities and characteristics of individual entrepreneurs as factors influencing the survival and success of entrepreneurship, and there is a lack of research on partnerships, that is, co-founding start-up, which are common in the field of entrepreneurship ecosystems. Therefore, this study attempted a multi-case study through in-depth interviews, collection of relevant data, analysis of contextual information, and consideration of previous studies targeting co-founders of domestic startups that succeeded in opportunistic startups. Through this, a model for deriving the phased characteristics and key success factors of co-founding start-up was proposed. As a result of the study, the key element of the preliminary start-up stage was 'opportunity', and the success factors were 'opportunity recognition through entrepreneur's experience' and 'idea development'. The key element in the early stages of start-up is "start-up team," and the success factor is "trust and complement of start-up team," and synergy is shown when "diversity and homogeneity of start-up team" are harmonized. In addition, conflicts between co-founders may occur in the early stages of start-ups, which has a large impact on the survival of start-ups. The conflict between the start-up team could be overcome through constant "mutual understanding and respect through communication" and "clear division of work and role sharing." It was confirmed that the core element of the start-up growth stage was 'resources', and 'securing excellent talent' and 'raising external funds' were important factors for success. These results are expected to overcome the limitations of start-up companies, such as limited resources, lack of experience, and risk of failure, in entrepreneurship studies, and prospective entrepreneurs preparing for a start-up in a situation where the form of co-founding start-up is attracting attention as one of the alternatives to increase the success rate. It has implications for various stakeholders in the entrepreneurial ecosystem.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.4
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• pp.219-226
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• 2013

Feature selection is the one of important issues in the field of machine learning and pattern recognition. It is the technique to find a subset from the source data and can give the best classification performance. Ie, it is the technique to extract the subset closely related to the purpose of the classification. In this paper, we experimented to select the best feature subset for improving classification accuracy when classify success and failure factors in software reuse. And we compared with existing studies. As a result, we found that a feature subset was selected in this study showed the better classification accuracy.