• Journal of Information Technology Applications and Management
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• v.21 no.4_spc
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• pp.331-344
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• 2014

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.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.3
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• pp.371-385
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• 1995

The yield of semiconductor chips is dependent not only on the average defect density but also on the distribution of defects over a wafer. The distribution of defects leads to consider a cluster index. This paper briefly reviews the existing yield prediction models ad proposes a new cluster index, which utilizes the information about the defect location on a wafer in terms of the coefficient of variation. An extensive simulation is performed under a variety of defect distributions and a yield prediction model is derived through the regression analysis to relate the yield with the proposed cluster index and the average number of defects per chip. The performance of the proposed simulation-based yield prediction model is compared with that of the well-known negative binomial model.

• Asian Journal of Innovation and Policy
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• v.1 no.1
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• pp.50-70
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• 2012

This paper analyzes the factors that determine technology innovation in Korean manufacturing firms, focusing on the role of intra-firm knowledge diffusion and market strategy in patent production. For empirical analysis, zero-inflated negative binomial (ZINB) regression is applied to the 2009 Human Capital Corporate Panel data. The empirical findings confirm the critical role of intra-firm knowledge-sharing processes in technology innovation; firms with a market-leading strategy oriented to new product development also tend to be prolific in patent production.

• 한국벤처창업학회:학술대회논문집
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• 2022.04a
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• pp.129-134
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• 2022

This research investigates the effect of SMEs' digital transformation (DX) efforts in O2O platforms on customer engagement. Among the three DX stages (i.e., digitization, digitalization, and DX), this study focuses on digitalization, a practically viable DX phase for SMEs using O2O platforms. This study categorizes the DX efforts of SMEs into three: information diversity, responsiveness to customers, and the degree of functional use. To analyze the impact of these efforts on customer engagement, we conduct the zero-inflated negative binomial regression using the dataset of Naver Smartplace, one of the representative O2O platforms in South Korea. The analysis result confirms that all three factors have positive impacts on customer engagement. Therefore, this study demonstrates that employing O2O platforms can be an effective strategy for SMEs lacking resources to achieve successful DX.

• Asia pacific journal of information systems
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• v.32 no.3
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• pp.580-600
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• 2022

The purpose of this study is to investigates the effect of SMEs' digital transformation efforts in O2O platforms on customer engagement. This study focuses on digitalization, which is a practically viable phase for SMEs using O2O platforms among the three digital transformation stages (digitization, digitalization, and digital transformation). This study specifically categorizes digital transformation efforts into three categories: information diversity, responsiveness to customers, and the degree of functional use. To analyze the impact of these efforts on customer engagement, we conducted a zero-inflated negative binomial regression using the dataset provided by Naver SmartPlace, a representative O2O platform in South Korea. The results present that the positive relationship between these aforementioned factors and customer engagement. Thus, this study demonstrates that utilizing O2O platforms can be an effective strategy for SMEs that lack the resources to achieve a successful digital transformation.

• International Journal of Highway Engineering
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• v.13 no.1
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• pp.13-19
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• 2011

The purpose of this study is to analyze the characteristics of traffic accidents and to develop the models by day and night-time in the case of the arterial link sections. In pursuing the above, this study uses the 224 accident data occurred at the 24 arterial link sections in Cheongju. The main results analyzed are as follows. First, it was analyzed that the number of accidents during day was more than night, but the accidents rate during night was higher than day. Second, four models which were all statistically significant were developed. Finally, the differences between the day and night models were comparatively analyzed using independent variables.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2609-2626
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• 2023

The hotel industry is an example of experiential services. As consumers cannot fully evaluate the online review content and quality of their services before booking, they must rely on several online reviews to reduce their perceived risks. However, individuals face information overload owing to the explosion of online reviews. Therefore, consumer cognitive fluency is an individual's subjective experience of the difficulty in processing information. Information complexity influences the receiver's attitude, behavior, and purchase decisions. Individuals who cannot process complex information rely on the peripheral route, whereas those who can process more information prefer the central route. This study further discusses the influence of the complexity of review information on hotel ratings using online attraction review data retrieved from TripAdvisor.com. This study conducts a two-level empirical analysis to explore the factors that affect review value. First, in the Peripheral Route model, we introduce a negative binomial regression model to examine the impact of intuitive and straightforward information on hotel ratings. In the Central Route model, we use a Tobit regression model with expert reviews as moderator variables to analyze the impact of complex information on hotel ratings. According to the analysis, five-star and budget hotels have different effects on hotel ratings. These findings have immediate implications for hotel managers in terms of better identifying potentially valuable reviews.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.1
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• pp.85-93
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• 2015

Previous studies have estimated crash prediction models with the fixed effect model which assumes the fixed value of coefficients without considering characteristics of each intersections. However the fixed effect model would estimate under estimation of the standard error resulted in over estimation of t-value. In order to overcome these shortcomings, the random effect model can be used with considering heterogeneity of AADT, geometric information and unobserved factors. In this study, data collections from 89 intersections in Daejeon and estimates of crash prediction models were conducted using the random and fixed effect negative binomial regression model for comparison and analysis of two models. As a result of model estimates, AADT, speed limits, number of lanes, exclusive right turn pockets and front traffic signal were found to be significant. For comparing statistical significance of two models, the random effect model could be better statistical significance with -1537.802 of log-likelihood at convergence comparing with -1691.327 for the fixed effect model. Also likelihood ration value was computed as 0.279 for the random effect model and 0.207 for the fixed effect model. This mean that the random effect model can be improved for statistical significance of models comparing with the fixed effect model.

• Journal of Technology Innovation
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• v.26 no.4
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• pp.29-56
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• 2018

The purpose of this research is to examine whether investment portfolio composition affects the technological performance of corporate venture capital (CVC). The stages of investment are categorized from "start-up/seed", "early", and "expansion", to "later" stage. We posit and test that the investment stage composition in a portfolio is highly correlated with the growth potential and downside risk of the portfolio, which in turn influences an investor's innovation performance. To test this hypothesis, we used negative binomial panel regression with 21 years of deal data from 70 cases of CVC. The results show that there is an inverted U shaped relationship between investment portfolio composition and technological performance. This means that the more seed or early stage investment within the investment portfolio, the higher the innovation performance; however, if the amount of seed or early stage investment is over a certain level, the performance decreases. Further, this study finds that the external partners of a venture negatively moderate the inverted U shaped relationship between portfolio composition and innovation performance. We believe that corporate planners, venture capitalists, and policy makers will be helped by these results showing that companies can maximize their investment performance by considering the investment stage and progress of investments.

• Journal of the Korean Regional Science Association
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• v.38 no.1
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• pp.3-20
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• 2022

The purpose of this study is to exploratory analyze the transition pattern of establishments and workers in new growth industries in the metropolitan area from 2010 to 2019 and to identify regional factors affecting the inflow and outflow of new growth industry start-ups. As for the analysis, the original data of the Census on Establishments were used, and spatial data at the sigungu level were constructed based on the inflow and outflow data of the number of new growth industry businesses and workers. For the analysis, the degree centrality of connection to outflow inflow by region was calculated, and an empirical analysis was conducted on regional-level factors affecting the inflow and outflow of new growth industries by applying a negative binomial regression model. According to the results, the new growth industry manufacturing sector was actively relocated in southern Gyeonggi Province, and the new growth industry service sector in Gangnam and Guro-Geumcheon-gu, and the impact of regional-level factors on the inflow and outflow of new growth industry start-ups varies depending on the industry. This study presented implications for regional industrial policies to improve the competitiveness of the local economy by attracting new industries by identifying spatial transition patterns for new growth industries and conducting empirical analysis to identify influencing factors.