• Proceedings of the Korea Contents Association Conference
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• 2011.05a
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• pp.485-486
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• 2011

본 논문에서는 물품을 체계적이며, 빠르게 구입하고 쇼핑 시간을 단축할 수 있도록 웹페이지를 통해 미리 쇼핑 계획을 세울 수 있는 스마트 폰 환경에서 내비게이션과 장바구니 기능을 제공한다. 또한 RFID를 이용하여 빠른 시간 내에 자가 계산을 할 수 있도록 한다. 제안하는 시스템을 통해 소비자는 효율적인 쇼핑을 할 수 있고 사업자는 자가 계산대로 인해 인건비를 줄이고 소비자의 소비 패턴을 쉽게 수집 할 수 있어 광고 등을 통한 매출을 더욱 증대 시킬 수 있다.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.327-328
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• 2015

미국의 시장조사기관 파이크 리서치에 따르면, 마이크로그리드가 창출하는 연 매출은 2018년에 127억 달러에 달할 것으로 전망된다고 밝혔다. 세계적인 에너지 믹싱 추세에 따라 마이크로리드는 생각보다 우리에게 더 빠르고 가까이 다가오고 있다. 전문가가 아닌 수용가가 수요관리를 위하여 마이크로그리드를 설계하고자할 때 어떤 분산전원을 얼마나 설치해야할지 설계하는가하는 방법은 매우 복잡하며 수용가의 부하패턴, 운영목적, 운영방법 등에 따라 다르다. 본 논문에서는 부하를 산업용, 교육용, 일반용으로 일반화하여 마이크로그리드 구성요소의 용량결정 방법을 제시하고자한다.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2011.06a
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• pp.134-149
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• 2011

최근 제약 및 바이오 분야는 국내 외 환경변화로 인해 역동적인 모습을 보이고 있다. 국내외 매출규모 상위 제약회사(국외 10개, 국내 11개 기업)와 유망 바이오회사(국외 8개, 국내 7개 기업)를 분석해본 결과, 기존과 다른 혁신적인 모습이 관찰되었다. 즉 제약 및 바이오 분야 기업들의 기존 블록버스터 비즈니스 모델은 관련 특허가 곧 만료됨에 따라 붕괴되고, 새로운 신약개발을 위해 치열한 경쟁이 시작되어 새로운 차원의 비즈니스 모델이 구상되고 있다. 따라서 새로운 형태로 생명공학계와 제약 산업 간의 '협업' 및 '분업' 구조가 나타나게 되었으며, 이는 오픈 이노베이션이라는 개념과 함께 구체화되고 있다. 본 연구에서는 '91~'11년 동안의 제약 및 바이오 분야의 기술혁신 패턴과정을 Utterback & Abernathy의 시계열적 기술혁신 패턴의 개념으로 설명하고, 특허 전문 DB인 Thomson Reuters사의 Aureka를 활용하여 약 20년 동안의 주요 제약 및 바이오 기업들의 R&D 분야 변화 및 융합되는 모습 등을 분석하였다. 또한, 각 종 시장분석자료를 재종합하여 관련 기업의 M&A 및 라이센싱 규모를 파악하고, 더 나아가 새롭게 등장한 바이오-파마(Bio-Pharma)의 오픈 이노베이션의 유형을 분석하였다.

• Annual Conference of KIPS
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• 2016.04a
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• pp.382-385
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• 2016

본 논문에서는 오프라인의 장점인 고객방문, 실물전시 및 체험 구매를 위한 상품콘텐츠를 가상공간에 디지털화로 제작하고 실시간 제공함으로써 고객들의 구매욕구와 구매패턴의 변화수용과 서비스 만족도를 향상시키는 O2O수주시스템을 제안한다. 이 시스템은 오프라인 패턴에 익숙한 카탈로그 책자중심의 사용자경험을 디지털로 전환하여 온라인의 거부감과 불편함을 해소하였고 편리성을 높이기 위해 다양한 접근 디바이스환경 제공과 오프라인에서 할 수 없는 동영상에 의한 사용법, 제품 도면 등을 e-카탈로그로 제공하여 성공적인 매출확대를 창출하도록 설계, 구현하였다.

• Journal of Labour Economics
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• v.28 no.1
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• pp.29-60
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• 2005

This paper investigates how firms adjust wages, employment and hours in response to demand shifts. It focuses on rigidities and asymmetries in such adjustments. Major findings are as follows. First, wage adjustments are fairly small compared with worker adjustments. Second, wage adjustments are asymmetric with respect to sales growth: there is no responsiveness of wage growth when sales are declining, while adjustments are significantly positive when sales are rising. On the contrary, worker adjustments are symmetric with respect to demand shifts. Third, while workers are linearly adjusted to the sales growth, some nonlinearity is observed in the wage adjustment. Fourth, hours are generally nonresponsive to demand shocks. Finally, union firms cut wages rather than workers in the face of negative demand shocks.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.3
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• pp.98-105
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• 2009

It is important for firms to help customers find the products or information they need in order to increase sales and promote return visits to their websites. Hence, the presentation of product information is very important in e-commerce websites. In this research, we study how disposition styles can influence browsing patterns. The test results show that people are inclined to use feature information paths in the vertical disposition style and product information paths in the horizontal disposition style. With vertical disposition, users are more likely to follow feature information paths which may help them focus on comparisons across products.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.2
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• pp.51-78
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• 2021

Followed by 'start-up', the theme of 'scale-up' has been considered as an important agenda in both corporate and policy spheres. In particular, although it is a term commonly used in industry and policy fields, even a conceptual definition has not been achieved from the academic perspective. "Corporate Growth" in the academic aspect and "Business Growth" in the practical management field have different understandings (Achtenhagen et al., 2010). Previous research on corporate growth has not departed from Penrose(1959)'s "Firm as a bundle of resources" and "the role of managers". Based on the theory and background of economics, existing research has mainly examined factors that contribute to firms' growth and their growth patterns. Comparatively, we lack knowledge on the firms' growth with a focus on 'annual revenue growth rate'. In the early stage of the firms, they tend to exhibit a high growth rate as it started with a lower level of annual revenue. However, when the firms reach annual revenue of more than 100 billion KRW, a threshold to be classified as a 'middle-standing enterprise' by Korean standards, they are unlikely to reach a high level of revenue growth rate. In our study, we used our sample of 333 companies (6.7% out of 5,000 'fastest-growing' companies) which reached 15% of the compound annual growth rate in the last three years with more than USD 100 million. It shows that sustaining 'high-growth' above a certain firm size is difficult. The study focuses on firms with annual revenue of more than $100 billion (approximately 120 billion KRW) from the 'Inc. 2020 fast-growing companies 5,000' list. The companies have been categorized into 1) Fast-growing companies (revenue CAGR 15%~40% between 2016 and 2019), 2) Hyper-growing companies (40%~99.9%), and 3) Super-growing (100% or more) with in-depth analysis of each group's characteristics. Also, the relationship between the revenue growth rate, individual company's strategy choice (market orientation, generic strategy, growth strategy, pioneer strategy), industry/market environment, and firm age is investigated with a quantitative approach. Through conducting the study, it aims to provide a reference to the 'Hyper-Growing Model' that combines the paths and factors of growth strategies. For policymakers, our study intends to provide a reference to which factors or environmental variables should be considered for 'optimal effective combinations' to promote firms' growth.

• The KIPS Transactions:PartD
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• v.9D no.2
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• pp.215-226
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• 2002

Considering the rapid process of media's breakthrough and diverse patterns of consumptions's analysis, a uniform analysis might be much rooms to be desired for interpretation of new phenomena. In special, the products happening intensive sails on around an anniversary or fresh food have the restricted marketing hours. Moreover, traditional association rule discovery algorithms might not be appropriate for analysis of sales pattern given in a specific time because existing approaches require iterative scan operation to find association rule in large scale transaction databases. in this paper, we propose an incremental candidate set management model based on twin-hashing technique to find association rule in special sales pattern using database trigger and stored procedure. We also prove performance of the proposed model through implementation and experiment.

• Journal of Service Research and Studies
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• v.2 no.1
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• pp.39-46
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• 2012

It is growing in size of database in companies. This caused to develope data mining techniques to predictive information from the large database. Costs and other effects can give variety of sales exploding through the analysis of the differences. Analysis of the various classification techniques, various angle can be analyzed point of view of the area information. The analysis of rules and patterns associated with a large amount of useful information from the database can be analyzed effectively. Goods store were analyzed using association rules, one of the data mining analysis techniques. Through this type of existing products according to analyze customer buying patterns, data mining has been studied to establish strategic marketing analysis.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.360-375
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• 2019

This paper tries to study the ecosystem after constructing the network of the continuing transactions associated with distribution industry with the data of more than 50 thousands firms provided by the Korean enterprise data (KED) for 2015. After applying the clustering method, one of social network analysis tools, we find the firms in the network grouped into 732 clusters occupying about 80% of whole distribution industry sales in KED data. The firms in a cluster have most of their transactions with other firms in the cluster. But the clusters have smaller firm numbers in the cluster and sales portion of the biggest firms in the industry than the case of the manufacturing industry. The Input-output analysis for the biggest distribution firms show that the small and medium size enterprise(SME)s have very high sale dependency on a main firm in some clusters. This fact implies more efficient fair transaction policies within the clusters. And small number of big distribution firms have very high rear production linkage effects on SMEs or on the 10th or 31th group with high portion of SME employment. They should be considered important in the SME growth and employment policies.