20 research outputs found

    Patterns of Catch-up in Technologies and Markets

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    학위논문 (박사)-- 서울대학교 대학원 : 경제학부(경제학전공), 2014. 2. 이근.Abstract This study focuses on two questions: how are latecomer firms in developing countries with low quality products and no brand recognition able to catch up with industry forerunners in developed countries with advantages in every aspect and do those firms follow any particular pattern achieving their success? Several previous studies have explored the process by which particular companies were able to catch up with industry forerunners, but thus far have provided only fragmentary explanations. As such we have divided our primary research question of what process latecomers follow in catching up with industry forerunners into the following four research questions. 1) Are latecomers able to catch up with forerunners in the market without technological capabilities? 2) Do latecomers utilize technologies that are similar to or distinct from those employed by forerunners? 3) Is it necessary for latecomers to invest in cutting-edge or more recent technologies in order to catch-up? 4) Do science-based technologies increase over time during the catch-up process? In seeking answers to the aforementioned research questions, we conducted an in-depth analysis of the catch-up phenomenon from the technological perspective primarily by using patent data, which has become more widely available in recent times, and reviewing existing catch-up theories. We reviewed several cases, in which latecomers in developing countries did catch-up with the leaders in developed countries in different sectors, in order to examine whether a set of patterns exits that are generally followed by latecomers in the catch-up process. In particular, we selected the case of Huawei and Ericsson in the telecommunications equipment sector, Samsung Electronics and Sony in the electronics sector, Hyundai Motors and Mitsubishi Motors in the automobile manufacturing sector, and POSCO and Nippon Steel Corporation in the steel production sector. Huawei, Samsung, Hyundai Motors and POSCO are all large companies from developing countries that successfully caught up with forerunners in their respective sectors. An in-depth analysis of each pair of companies was conducted using patent data and other technological indices to find the similarities and differences in the technological catch-up process followed by each latecomer. A review of the existing literature and examination of outcomes revealed possible common patterns in the technological catch-up processes followed in the different sectors studied. First, latecomers technological catch-up tends to precede a catch-up in the market. This reflects the fact that accumulated technological capabilities are the foundation of the catch-up process and a necessary condition for sustainablerather than temporarydominance over a longer period of time. Second, latecomers tend to catch-up by using technologies that differ from those employed by incumbents. This was determined, considering the level of technological dependence between two firms, self-citation ratio and the number of received citations of patents. Third, whether a latecomer can succeed in catching up with the forerunner by relying on more recent technologies depends on the technological nature of the sector, especially the typical length of the sectors technology cycle. This reflects the fact that during the catching-up process, latecomers depend on more recent technologies in the sector with short technological cycle and frequent generation change, while latecomers in the sector with less frequent technological generation change gradually tend to improve the existing technologies in a different way from forerunners rather than investing in up-to-date technologies, which can be verified by the measure of backward citation lag. Fourth, whether a latecomers patent has a higher proportion of science-based citations tends to depend on the nature of the sectors knowledge base. Whereas the knowledge base of the IT sector depends on radical innovation and explicit knowledge, the knowledge base of the automobile manufacturing sector depends on gradual innovation based on experience and experimentation as well as tacit knowledge. This study conducted an in-depth analysis and examination of the aforementioned specific research questions through patent data analysis and drew the following conclusions with regard to the catch-up process: A accumulated technological capacity is the base for the catch-up of latecomer firms with the forerunners, the latecomer catch-up with incumbents based on different technologies from the incumbents, latecomers in sectors with a short technological cycle try to catch up with the leaders by depending up-to-date technologies, and the share of basic science in their patents of latecomers tends to gradually increase in sectors with little tacit knowledge. Lastly, this paper can provide directions for firms as to what conditions are needed for to be able to catch up with forerunners by making explicit the existence of several possible patterns of catch-up within the sector from the technological perspective through the patent analysis data. In addition, this study provides practical and useful implications for both incumbents and latecomers in establishing their technological strategies in general and their patent strategies in particular. Key words: Patterns of catch-up, Technological catch-up, Catch-up in the market, Patents, Level of technological dependence, Self-citation ratio, The number of received citations, Backward citation lag, Science-base, Knowledge base, SectorChapter 1. Introduction………………………………………………………………………………1 Chapter 2. Literature and Motivation…………………………………………………………5 1. Previous Literature……………………………………………………………………………….5 2. Research Questions and Distinctives of the Current Study………………..8 Chapter 3. Methodology ……………………………………………………………………..…19 1. Introduction……………………………………………………………………………………..…19 2. Patent Data Analysis and Previous Literature …………………………….…....22 1) Making Sense of Comparison ………………………………………....……22 2) Catch-up in terms of the quantity of patents …………………....…25 3) Catch-up in terms of the quality of patents …………..………….…25 4) Technology cycle (Backward citation lag) …………………….…....…26 5) Level of technological dependence……………………………………….27 6) Self-citation ratio…………………………………………………………………….27 7) Citation to non-patent literature as science-base ……………..…27 Chapter 4. Analysis of Patent Data for Target Firms ………………………………28 1. Huaweis Catch-up with Ericsson…………………………………………………….…29 1) Introduction……………………………………………………………………………..29 2) Previous literature …………………………………………………………………..31 3) Huaweis Catch-up with Ericsson in the telecommunications equipment industry ……………………………………………………………...…32 3)-1 A brief introduction to Huawei and Ericsson ……………...…32 3)-2 Huaweis Catch-up in the telecommunications market….35 3)-3 Patent data analysis of Huawei and Ericsson ……………..….43 3.1 Making sense of Comparison ………………………………..……43 3.2 Catch-up in terms of the quantity of patents ……………46 3.3 Catch-up in terms of the quality of patents ……………...48 3.4 Forward and Backward citation lag ……………………………51 3.5 Level of technological dependence…………………………….52 3.6 Self-citation ratio …………………………………………………………53 3.7 Citation Citation of non-patent literature as science- base………………………………………………………………………………54 2. Hyundai Motors Catch-up with Mitsubishi ……………………………………56 1) Introduction…………………………………………………………………………...56 2) Literature Review……………………………………………………………….…..58 3) Hyundai Motors catch-up with Mitsubishi Motor in the Automobile industry ………………………………………………………………60 3)-1 A brief introduction to Hyundai Motors and Mitsubishi Motors …………………………………………………………………………………60 3)-2 Hyundai Motors Catch-up in the Market…………………………62 3)-3 Patent data analysis of Hyundai and Mitsubishi ……………..63 3.1 Catch-up in terms of the quantity of patents ……………...64 3.2 Catch-up in terms of the quality of patents ………………..66 3.3 Backward citation lag….…………………………………………………68 3.4 Level of technological dependence……………………………...76 3.5 Self-citation ratio…………………………………………………………..77 3.6 Citation to non-patent literature as science-base ………78 3. Samsung Electronics Catch-up with Sony ………………………………….85 1) Introduction …………………………………………………………………………..85 2) Previous literature …………………………………………………………………87 3) Samsungs catch-up with Sony in the electronics industry. ...89 3)-1 A brief introduction of Samsung and Sony…………………..89 3)-2 Samsungs catch-up in the market ……………………………….93 3)-3 Patent data analysis of Samsung and Sony (By sub-section of IPC analysis).. …………………………………94 3.1 Catch-Up in terms of the quality of patent….…………94 3.2 Technology of cycle (Backward citation lag) ……...…101 3.3 Citation to non-patent literature as science-base…108 4. POSCOs catch-up with Nippon Steel Corporation………………….…115 1) A brief introduction to POSCO and Nippon Steel Corporation……………………………………………………………………………115 2) POSCOs catch-up with Nippon Steel corporation in the market……………………………………………………………………………………118 3) Patent data and technological index analysis of POSCO and Nippon Steel corporation……………………………………………..120 4) The quality of patents of POSCO and Nippon Steel corporation…………………………………………………………………………. 128 5) The reason for the lack of patents in the technological catch-up of POSCO………………………………………………………………129 Chapter 5. Answers to the research questions and possible patterns of technological catch-up process from the four cases …………..132 Chapter 6. Summary and Strategic Implications ……………………………………160Docto

    Understanding Impacts of Aggressive Driving on Freeway Safety and Mobility: A Multi-agent Driving Simulation Approach

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    Considering that aggressive driving behavior significantly contributes to crash occurrences, it is necessary to establish appropriate safety strategies for managing and suppressing the risk factor of aggressive driving behavior. Understanding the characteristics of aggressive driving and its impact on traffic stream is fundamental to developing safety countermeasures. The main purpose of this study is to evaluate the crash potential under the various aggressive driving events on freeways based on both driving simulators and microscopic traffic simulation model, VISSIM. A novel feature of this study is the application of a multi-agent driving simulation facility, where two driving simulators are connected to establish a network that can render synchronized driving in the same space. The results of the driving simulation were used for modifying the driving behavior parameters of VISSIM. This approach will enable to effectively represent the driving behavior of aggressive drivers and normal drivers under various aggressive driving cases. Study results indicated that aggressive driving deteriorated not only the network safety performance represented by the crash potential index (CPI) but also the mobility represented by travel speeds. The outcomes of this study would be useful in developing well-informed countermeasures and supporting policy making-activities to prevent aggressive driving events. (C) 2019 Elsevier Ltd. All rights reserved.This work was supported by the National Research Foundation of Korea grant funded by the Korea Government (MSIP) (NRF-2017R1A2B4005835)

    A Risk-based Systematic Method for Fog-Related Crash Prone Locations

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    Fog is one of the most influential factors in fatal crashes because of reduced visibility. This study aims to propose a systematic safety analysis framework for selecting fog-crash-prone areas on freeways. To achieve these goals, the spatial analysis in ArcGIS was combined with the latent class cluster-based crash severity estimation models. Nine latent class cluster-based crash severity estimation models were built. Fog events led to a statistically significant increase in the likelihood of fatal crashes in two of the nine models. Comparing the ArcGIS spatial clusters of fog-related exposure with the fatal crash-prone freeway segments, 28 freeway segments were found to be fog-crash-prone areas where safety improvements are required, particularly in foggy weather. Based on the spatial patterns of the fog-crash-prone freeway segments, this study concludes that the current standard for fog-crash-prone area selection should be modified to apply spatially different standards over the Korean freeway network. This study is the first data-driven study to comprehensively examine the effects of fog visibility levels and frequencies on fatal crashes in the entire Korean freeway system. The findings provide meaningful insights to the policy decision making for fog-related policy changes, highway safety enhancement and active traffic management strategies.This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education [NRF-2016R1D1A1B03930700]

    Freeway Crashes Involving Drowsy Driving: Crash Characteristics and Severity in South Korea

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    Drowsy driving is a significant crash risk factor. In 2006–2012, 22.5% of all crashes and 33.3% of fatal crashes were caused by drowsy driving in South Korea. This study examined driver, vehicle, road, weather, and temporal characteristics associated with drowsy-driving crashes in South Korea. This study found that drowsy-driving crashes were often caused by drivers in their thirties through fifties unlike the United States and other Western countries. The multinomial logit model on the crash severity of drowsy-driving crashes showed that older drivers age 60+, male drivers, and vans were more likely to be involved in fatal crashes. Also, the fatal crashes were more likely to occur in work zones, freeway segments with concrete barriers or no shoulder, and the month of August. These findings indicate that it is critical to implement road safety measures, such as rumble strips, in work zones and the areas with a high frequency of drowsy-driving crashes as well as safe and accommodating rest areas to prevent drowsy driving

    습증기 물성치의 전산수식화에 관한 연구

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    ON-OFF 제어계통을 갖는 냉동기의 최적제어에 관한 연구

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    Developing Targeted Safety Strategies based on Traffic Safety Culture Indexes Identified in Stratified Fatality Prediction Models

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    The south korea transportation safety authority (KTSA) conducts the special traffic safety culture investigation (STSCI) every year to assist local governments in promoting traffic safety. To address the issue of diversity, the local agencies were grouped into four regions by administrative district unit and offered region-specific safety promotion strategies. However, it is unclear if such a classification truly reflects the underlying differences that contribute to traffic safety. The goal of this study is to identify the most relevant attributes that affect the safety performance of local agencies (called traffic safety culture indexes in the current study) so that targeted safety promotion strategies can be recommended. To accomplish the goal, latent class cluster-based negative binomial regressions were applied for a comprehensive list of factors such as demographics, socio-economic features, roadway conditions, traffic violations and road user driver behavior; resulting in seven clusters of local governments. The following indexes were found to significantly and strongly affect crash fatalities in the clusters: rate of wearing helmet, rate of pedestrian's signal compliance, the number of unlicensed driving violations, total paved road length, province, ratio of male to female, and population density. Further, stratified negative binomial regression models were developed to identify statistically significant factors for predicting fatal crashes within each cluster. These cluster-specific features allow the KTSA to design targeted strategies for effective safety promotion.This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2018R1D1A1A09083905)

    Estimation of the Safety Benefits of AEBS based on an Analysis of the KIDAS

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    Using the Korean In-Depth Accident Study (KIDAS) database, this study estimated the safety benefits of autonomous emergency braking systems (AEBS). We analyze crash severity using an ordered probit model to identify contributing factors based on the KIDAS database as well as the statistical relationship between collision speed and crush extent. We estimate the change in injury severity after AEBS installation using the results of both analyses. From the results, we identify that adolescence, fastened seatbelts, and crush extent are statistically significantly correlated with the dependent variable, injury severity score. Analysis of the relationship between crush extent and collision speed reveals that the explanatory power of the exponential model is higher than that of the linear model, while evaluating the effect of AEBS using the two relationships shows that it had a maximum injury reduction effect of 25% when the injuries were not minor. Results showing the effectiveness of installing an AEBS are presented, and a method to evaluate the potential safety benefits obtained from the analyses conducted in this study is proposed. The methods used in this study could be useful in promoting the rapid propagation of in-vehicle safety measures and developing relevant policies.This research was supported by a grant from the Transportation & Logistics Research Program funded by the Ministry of Land, Infrastructure, and Transport Affairs of the Korean government (Project No.: 16TLRP-B101406-02)
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