• 한국IT서비스학회지
• /
• 제11권1호
• /
• pp.39-58
• /
• 2012

This study was carried out to figure out the relationship between EAmaturity, information management capacity, and information performance, and find the effect between these variables and the reciprocal causation. The study found that EAmaturity has a positive effect on information resource management and performance. In other words, the effect of input, calculation, management and utilization factors on information planning in EAmaturity showed that calculation, management and utilization factors have a significant effect on the information planning. While the effect of input, calculation, management and utilization factors on information introduction and management showed that only both calculation and utilization have a significant effect on the information management factor. It says that EAinput in EAmaturity does not play a big part in the planning stage, as well as not go through a series of process that is connected to the maturity stage by immediate field application. Consequently, EAmaturity varies from the level that EAcreates introduction and performance according to organization. This suggests that the maturity and performance can be also changed by the level that EAcreates information performance by accepting and using this capability within organization as well as the capability to introduce and fully perform the EAsystem presented in enterprise architecture framework of public sector.

• The Journal of Asian Finance, Economics and Business
• /
• 제9권5호
• /
• pp.225-237
• /
• 2022

The term "artificial intelligence" is considered a component of sophisticated technological developments, and several intelligent tools have been developed to assist organizations and entrepreneurs in making business decisions. Artificial intelligence (AI) is defined as the concept of transforming inanimate objects into intelligent beings that can reason in the same way that humans do. Computer systems can imitate a variety of human intelligence activities, including learning, reasoning, problem-solving, speech recognition, and planning. This study's objective is to provide responses to the questions: Which factors should be taken into account while deciding whether or not to use AI applications? What role do these elements have in AI application adoption? However, this study proposes a framework to explore the significance and relation of success factors to AI adoption based on the technology-organization-environment model. Ten critical factors related to AI adoption are identified. The framework is empirically tested with data collected by mail surveying organizations in Vietnam. Structural Equation Modeling is applied to analyze the data. The results indicate that Technical compatibility, Relative advantage, Technical complexity, Technical capability, Managerial capability, Organizational readiness, Government involvement, Market uncertainty, and Vendor partnership are significantly related to AI applications adoption.

• 지식경영연구
• /
• 제5권2호
• /
• pp.67-98
• /
• 2004

New knowledge is created through the dynamic interaction of knowledge that depends largely on a social context within the organization. Social processes influence the nature of knowledge and learning. This paper is rooted in the concept of social capital. Social capital theory emphasizes the importance of social relationship. Using social capital theory, this paper suggests three factors that must be satisfied for the development of knowledge combinative capability. The first factor is that the opportunity exists to make the exchange or combination of knowledge. The second factor is that people is motivated for the creation of new knowledge. The third factor is that people must share the common knowledge. This paper examines the change case of KIPO (Korean Intellectual Property Office). This case provides evidence that the three factors can develop social relationship, and build knowledge combinative capability. The man finding from this research is that social factors play an important part in the creation of knowledge, and processes of knowledge exchange and combination heavily rely upon social patterns, practices and processes in ways which emphasize the value and importance of collective action and knowledge sharing. This research may have several implications for the development of the knowledge creation mechanisms.

• 품질경영학회지
• /
• 제24권3호
• /
• pp.145-159
• /
• 1996

In today's organization, measurement plays a crucial role in helping improve process or quality. In this paper, we review the measurement error study, classical gauge repeatability and reproducibility study, and designed experiment suited for the determination of the measurement capability. Measurement error study is very simple to use but is rather crude. Hence, it should be used as a preliminary study to determine whether further study is necessary. Classical gauge repeatability and reproducibility (GR&R) study is the most common technique for evaluation of gauge capability. It calculates a percentage that relates the repeatability, reproducibility, and overall R&R to the specification range for the parameter measured. Hence, the individual repeatability and reproducibility statistics will indicate the area on which to concentrate. However, GR&R study only gives a point estimate of each component, which leaves a room for improvement. It is always good to integrate the use of control charts to ascertain the statistical stability of the measurement process. The tools of statistical experimental design are available for a comprehensive design and analysis of the measurement process. Hence, in this paper, we present gauge capability analysis as an experimental design problem and compare it with the classical GR&R study.

• 대한안전경영과학회지
• /
• 제7권4호
• /
• pp.141-163
• /
• 2005

The international SPICE (Software Process Improvement and Capability determination) Project ISO/IEC 15504(SPICE : Software Process Improvement and Capability determination) is an emerging International Standard on SPA(Software Process Assessment). A prime motivation for developing this standard has been the perceived need for an internationally recognized software process assessment framework that pulls together the existing public and proprietary models and methods. A SPICE assessment can be considered as one of representative SPA model since assessors assign ratings to indicators and metrics to measure the capability of software process. But this models doesn't provide a systematic measurement procedures and dynamic method for SPI(Software Process Improvement). Through the evaluation of SPICE is capable of providing a substantiated basis for using the notion of capability, as well as providing information for nacessary improvements to the standard using 6sigma process. As a result, this paper propose a measurement procedure and guidelines for application of 6sigma process to guarantee the reliability in SPI and suggest the structure to support SPI on overall organization.

• 벤처창업연구
• /
• 제7권1호
• /
• pp.73-86
• /
• 2012

본 사례에서는 국내 IT 벤처기업인 유니데이타커뮤니케이션(주)의 단계적인 국제화 경험이 학습역량 강화를 통해 경영성과에 기여하는 일련의 국제화 과정을 조직학습이론으로 설명하였다. 이는 조직의 국제화 경험이 국제화 성과의 중요한 결정요인이며 조직학습을 통해 배양된 학습역량은 경영성과에 기여한다는 기존 연구결과를 기반으로 하고 있다. 더불어, 창업기부터 꾸준히 국제화를 추진한 IT 벤처기업의 국제화학습 특성을 기존지식 활용(Exploitation)과 새로운 지식 탐색(Exploration)으로 구분하여 분석하였다. 분석결과, 대기업에 비해 내부자원이 취약한 벤처기업은 파트너 네트워크를 활용한 탐색과 활용을 통해 새로운 국제화 경험을 축적하였다. 축적된 국제화 경험은 학습 역량 강화를 통해 기업의 내부역량으로 배태(embedded)되어 궁극적으로 경영성과에 유의미하게 작용함을 사례를 통해 확인 할 수 있었다.

• 한국콘텐츠학회논문지
• /
• 제14권12호
• /
• pp.911-923
• /
• 2014

본 연구에서는 고객센터를 대상으로 고객센터의 중요한 조직자본이 무엇인가 밝혀내고, 조직자본이 고객센터의 어떠한 동적역량을 통하여 조직성과로 연결되는가에 대한 관계를 분석하였다. 이를 위해 고객센터 구성원을 대상으로 설문조사를 실시하여 389개의 데이터를 실증 분석에 이용하였다. 분석결과, 조직자본 중 관계적 자본과 조직문화가 조직의 동적역량 구성요소(구성원 협력, 자본공유, 자본변환) 모두에 긍정적 영향을 미치는 것으로 나타났으며, 구조적 자본은 동적역량 구성요소 중 협력에 유의한 영향관계가 있음을 밝혔다. 조직성과는 조직 동적역량 중 구성원의 협력과 조직자본공유가 긍정적 영향을 미치는 것으로 나타났다. 본 연구결과는 고객센터의 관리자들과 상담사원들에게 고객센터에서 과연 어떠한 조직자본이 보다 중점적으로 관리되고 부족한 부분이 보완되어야 하는가에 대한 실용적인 가이드라인을 제시하고, 앞으로 고객센터가 기업의 전략적이며 핵심적인 조직으로 발전하기 위해서는 어떠한 조직자본과 동적역량을 강화, 발전시켜야 하는가에 대한 시사점을 제공하였다.

• 한국건설관리학회논문집
• /
• 제10권1호
• /
• pp.146-155
• /
• 2009

건설산업은 수주산업으로서 사업기간 전반(Project Life Cycle)에 걸쳐서 발주자의 관여도가 크기 때문에 발주자의 역할과 기능이 사업의 성패에 미치는 영향이 매우 크다고 할 수 있다. 그러나 국내외 여러 연구에서 이미 발주자의 기능과 역할에 대한 중요성이 강조되고 있음에도 불구하고, 아직까지 발주자 조직이 수행하여야 할 역할과 기능에 대한 정의를 바탕으로 건설사업의 발주자 조직에 대한 조직 수준의 역량을 평가할 수 있는 포괄적이고 체계적인 연구는 미흡한 실정이다. 본 연구에서는 발주자 조직 역량요소를 이용한 발주역량 평가지표를 개발함으로써 발주역량평가의 기본체계(Framework)를 제시하고, 개발된 발주역량평가체계를 실제 발주자 조직에 적용하여 평가를 수행하고 그 결과를 제시함으로써 그 적용성을 검증한다. 건설공사 발주기관의 역량에 대한 정량화 가능한 측정 지표를 활용하여 객관적인 평가를 수행하고, 이를 통해 발주자 조직 역량의 현재 수준 진단과 부족한 역량에 대한 정확한 판단을 할 수 있다면, 미래지향적인 전략 수립 및 발주자 조직 관리의 효율성 향상을 기대할 수 있을 것이다.

• 한국콘텐츠학회논문지
• /
• 제12권12호
• /
• pp.627-638
• /
• 2012

본 연구에서는 대표적인 지식기반 산업이자 프로젝트기반 조직의 성격을 가진 방송 드라마 산업을 대상으로 드라마 제작자가 환경변화에 대응하여 기업 내 외부를 넘어 연출자, 작가, 배우 등의 자원을 재조합하는 역동적 능력을 실증하였다. 구체적으로 안정적인 환경에 속해있던 1994년-2002년 시기보다 불확실성이 높은 환경에 속해있던 2003년-2009년의 시기에 드라마 제작자들이 상대적으로 동일한 자원을 반복적으로 이용하는 정도가 낮을 것이라는 가설을 설정하고 검증하였다. 실증연구 결과는 작가와 배우를 제외한 환경변화에 따른 연출자의 반복적 이용정도차이에 대한 가설이 부분적으로 검증되었으나, 추가분석 결과 전반적으로 예측된 경향성을 보이는 것으로 나타났다. 즉, 프로젝트성 조직은 안정적인 환경에서는 동일한 자원을 반복적으로 활용하여 더욱 효율을 추구하는 행동을 하며, 불확실한 환경에서는 상대적으로 동일한 자원을 반복적으로 활용하는 경향을 낮게 가져가 다양한 인적자원의 조합을 시도하는 것으로 나타났다.

• 산업경영시스템학회지
• /
• 제39권2호
• /
• pp.54-63
• /
• 2016

As technology has developed and cost for data processing has reduced, big data market has grown bigger. Developed countries such as the United States have constantly invested in big data industry and achieved some remarkable results like improving advertisement effects and getting patents for customer service. Every company aims to achieve long-term survival and profit maximization, but it needs to establish a good strategy, considering current industrial conditions so that it can accomplish its goal in big data industry. However, since domestic big data industry is at its initial stage, local companies lack systematic method to establish competitive strategy. Therefore, this research aims to help local companies diagnose their big data capabilities through a reference model and big data capability assessment system. Big data reference model consists of five maturity levels such as Ad hoc, Repeatable, Defined, Managed and Optimizing and five key dimensions such as Organization, Resources, Infrastructure, People, and Analytics. Big data assessment system is planned based on the reference model's key factors. In the Organization area, there are 4 key diagnosis factors, big data leadership, big data strategy, analytical culture and data governance. In Resource area, there are 3 factors, data management, data integrity and data security/privacy. In Infrastructure area, there are 2 factors, big data platform and data management technology. In People area, there are 3 factors, training, big data skills and business-IT alignment. In Analytics area, there are 2 factors, data analysis and data visualization. These reference model and assessment system would be a useful guideline for local companies.