Earticle

국내적으로는 국방과학기술 수준 고도화 및 연구주체 다양화로 기술유출 발생 범위가 확대되고, 국외적으로는 기술획득 경 쟁 심화와 新 방산침해 등 사이버공격을 통한 기술유출 시도가 증가하고 있다. 대부분의 기술유출 유형은 내부자와 연계되어 발생한다. 따라서 이 논문에서는 방산업체 특성에 부합된 내부자위협 프로그램(InTP) 성숙도 프레임워크을 제시한다. InTP 는 프레임워크를 로드맵으로 사용하여 내부자 위협에 대응하는 현재와 미래의 과제를 해결하기 위해 방산업체 단위 기능, 프 로세스, 절차 및 자원을 발전시키기 위한 전략적 목표와 목적을 개발할 수 있다. 또한 InTP는 행동 방침 및 구현 계획을 개발 할 때 고유한 방산업체 사업영역, 인력 환경 및 기술 인프라에 대한 고려 사항을 통합해야 한다. InTP는 계획 프로세스 초기 에 방산업체 자체의 법률 자문, 개인 정보 보호 담당자, 감사(감찰)관을 참여시켜 개발된 제품이 모든 관련 법률, 개인 정보 보호 및 시민 자유 권리, 내부 고발자 보호를 준수하는지 확인 등의 조치가 필요하다.

In Korea, the scope of technology leakage is expanding due to the advancement of the level of defense science and technology and the diversification of research subjects, and overseas attempts to leak technology through cyberattacks such as intensifying competition for technology acquisition and infringement of new defense systems are increasing. Most types of technology leakage occur in relation to insiders. Therefore, this paper presents an insider threat program (InTP) maturity framework that matches the characteristics of defense companies. InTP can respond to insider threats by using the framework as a roadmap for function, process, procedure, resource advancement strategic goals and target development at the defense company level. In addition, InTP should integrate considerations for unique defense company business areas, manpower environment, and technology infrastructure when establishing action plans and action plans. In addition, InTP needs to take measures such as ensuring that products developed by the participation of defense companies' own legal advice, personal information protection officers, auditors, etc. at the beginning of the planning process comply with all related laws, privacy and civil liberties, and protection of whistleblowers.

Many cities in the world have increased initiative to realize smart tourism. There are unexplored challenges for the people which lead and manage smart tourism projects and realize its value in tourism (we call them as ‘Smart tourism initiatives’), such as orchestrating of tourism complexity, developing and sharing tourism strategy, sustaining tourism projects and innovation. Concerning these challenges, we aim to design a holistic capability maturity model for sustainable and smart tourism governance enabling sustainable tourism innovations via tackling the challenges above. We adopted Dynamic capability theory as a theoretical lens and introduced Design science research methodology in order to develop a new capability maturity governance model as a design artifact. As a result of the study, we could synthesize findings from iterations of the design research cycle based on the IT Capability Maturity Model. Our result proposes a potential capability maturity model supporting effective communication and strategic alignment for the initiatives with illuminating future paths with evaluation methods on tourism capabilities for the initiatives. Throughout this study, we contribute to the body of knowledge as well as practice by proposing a new tourism capability governance model.

Successful development of weapon systems requires a stringent verification and validation (V&V) process due to the nature of the weapons in which continual increase of operational capability makes the system requirements more complicated to meet. Thus, test and evaluation (T&E) of weapon systems is becoming more difficult. In such a situation, live fire tests appear to be effective and useful methods in not only carrying out V&V of the weapon systems under development, but also increasing the maturity of the end users operability of the system. However, during the process for live fire tests, a variety of accidents or mishaps can happen due to explosion, pyro, separation, and so on. As such, appropriate means to mitigate mishap possibilities should be provided and applied during the live fire tests. To study a way of how to accomplish it is the objective of this paper. To do so, top-level sources of hazard are first identified. A framework for T&E is also described. Then, to enhance the test range safety, it is discussed how test scenarios can be generated. The proposed method is based on the use of the anticipatory failure determination (AFD) and multiple event tree analysis (ETA) in analyzing range safety. It is intended to identify unexpected hazard components even in the environment with constraints. It is therefore expected to reduce accident possibilities as an alternative to the traditional root-cause analysis.

The Software product line engineering is an inter-disciplinary concept. It spans the dimensions of business, architecture, process, and the organization. Similarly, Educational System engineering is also an inter-disciplinary concept, which spans the dimensions of academic, infrastructure, facilities, administration etc. Some of the potential requirements and benefits of this engineering approach includes continuous improvements in educational quality and adhering to global standards. The increasing competency in IT and Educational Sectors necessitates a process maturity evaluation methodology for educational organization. Accordingly, this paper presents a new quality educational capability maturity model for evaluating the maturity of multi - dimension factors and attributes of an Educational System. Assessment questionnaires and a rating methodology comprise the framework of this Capability maturity model for quality Education (CMM-QE). The objective and design of the questionnaires are to collect information about the Education system engineering process from the multi perspectives of academic, infrastructure, administration, facilities etc. This model is validated using PLS-Graph tool, and the organizational maturity is validated by classifying the educational institutions into different levels by applying k-means Cluster analysis using SPSS and finally it is ranked for its maturity level accordingly.

글로벌 식품 안전사고는 지속적으로 발생하고 있으며 이에따라 식품이력추적의 중요성도 커지고 있다. 해외에서 AI, IOT 등 산업 4.0 기술을 접목한 식품이력추적 4.0이 활발이 연구되는 반면, 국내 식품이력추적의 디지털화에 대한 연구는 아직 초기 단계에 머무르고 있다. 본 연구는 이러한 배경 하에, 공급망 성숙도 모델 분석과 해외 식품 안전 기술 동향을 기반으로 국내 식품 기업에 적용가능한 식품이력추적 4.0 성숙도 프레임워크를 제시하는 것을 목적으로 한다. 본 연구는 기업이 자사의 디지털화 수준을 진단하고, 첨단 기술을 적용하여 식품이력추적관리의 시스템 고도화를 위해 필요한 과제를 종합적으로 진단하는 실무적 도구로 기여할 것으로 기대된다.

Global food safety incidents continue to occur, highlighting the critical importance of food traceability. While "Food Traceability 4.0," which incorporates Industry 4.0 technologies such as AI and IoT, is being actively researched globally, domestic research remains in its nascent stages. To bridge this gap, this study proposes a Food Traceability 4.0 maturity framework tailored for domestic food companies. Specifically, this study integrates the Supply Chain Maturity Assessment Test (SCMAT) with the World Economic Forum’s digital traceability strategies and the latest regulations such as FSMA 204. The proposed framework consists of 34 diagnostic items across 7 domains.This framework will serve as a practical tool for companies to diagnose their digitalization level and comprehensively identify necessary tasks for system advancement in food traceability management through the application of advanced technologies

본 연구의 목적은 기업의 효과적인 데이터 전략 수립과 효율적 투자를 위해 빅데이터 성숙도를 평가하기 위한 프레임워크를 개발하고 이를 실증하는데 있다. 이를 위해 현재까지 개발된 평가의 단점을 보완하여, 기업의 빅데이터 성숙도를 프로세스 통합적으로 평가할 수 있는 프레임워크를 개발하였다. 그 결과 ‘비전과 전략’, ‘관리’, ‘분석’, ‘활용’의 4가지 평가 영역과 각 영역별 평가항목, 세부내용 및 단계별 준거를 도출하였다. 이를 기업인 설문을 통해 실증하였으며 국내 기업의 빅데이터 성숙도를 진단하였다. 향후 연구방향으로 산업별 특성에 따른 세부 평가요소 개발, 평가 결과에 따른 데이터 활용 프레임워크의 발전, 검증 대상의 조정을 통한 추가적인 타당성 및 신뢰도 향상을 제안하였다.

The purpose of this study is to develop and demonstrate a framework for evaluating the maturity of big data for effective data strategy establishment and efficient investment of companies. By supplementing the shortcomings of the evaluation developed so far, a framework was developed to evaluate the maturity of a company’s big data in an integrated process. As a result, four evaluation areas of ‘Vision and Strategy’, ‘Management’, ‘Analysis’ and ‘Utilization’, assessment items for each area, detailed content, and criteria for each stage were derived. This was verified through a survey of entrepreneurs, and the maturity level of big data of domestic companies was confirmed. As a future research direction, it is proposed to develop detailed assessment factors according to the characteristics of each industry, to develop a data utilization framework according to the assessment results, and to improve validity and reliability through adjustment of verification targets.

스마트공장 등으로 변화하는 경쟁 환경 속에서 제조시스템의 현 수준을 측정하고 개선 목표와 과제를 도출, 추진하여 제조경쟁력의 수준을 높이는 것이 기업의 기본적 활동이 되고 있다. 그러나 기업의 미래 제조경쟁력을 갖추기 위한 구성요소 분석과 성숙도평가에 관한 연구는 부분적으로 진행되고 있고 초기단계에 있다. 본 연구는 제조시스템에 대한 다양한 관점의 모델, 개발프로세스, 프레임워크 등에 대한 기존 연구를 분석하였다. 또한 스마트공장 관련 성숙도평가 연구들을 통해 미래 제조시스템의 구성요소들을 도출하여 구조모델을 설계하였다. 평가모델, 변환모델까지 포함하는 메타모델을 설계하고 프레임워크 개발 프로세스를 도출하여 미래 제조시스템의 성숙도평가를 위한 통합적 프레임워크를 제안하였다. 또한 실제 스마트공장 평가에 적용하여 검증하였다. 제시된 프레임워크는 미래 제조시스템의 성숙도평가를 위한 기반 도구로 활용될 수 있을 것이다.

In an environment transformed by smart factories, measuring the current level of the manufacturing system, deriving improvement targets and tasks and increasing the level of manufacturing competitiveness become the basic activities of the company. However, research on the component analysis and maturity assessment to ensure the future competitiveness of the company is in progress and in the early stages. This study analyzed the existing research on various models, development process, and framework for manufacturing system. In addition, we designed a structural model by deriving the components of future manufacturing system through smart factory related maturity assessment studies. We designed a meta-model that includes an assesment model and a transformation model, and derived the framework development process to propose an integrated framework for the maturity assessment of the future manufacturing system. We verified it by applying it into an actual evaluation project of smart factory.

Despite massive investment in generative AI, most organizations face the 'AI Productivity Paradox'?the persistent failure to translate AI adoption into measurable performance gains. This study addresses this paradox by positioning AI governance maturity as a critical mediating mechanism: not merely a regulatory compliance tool, but a form of intangible asset investment that determines when organizations reach the J-Curve inflection point. The framework advances three propositions. First, governance maturity stages 1?2 correspond to the J-Curve's declining phase, stage 3 constitutes the inflection point, and stages 4?5 correspond to recovery and growth. Second, highly regulated financial institutions (HRFIs) experience a structurally modified J-Curve?deeper trough and delayed inflection?due to common factors (regulatory compliance burdens, data protection obligations, explainability requirements) and CRA-specific factors (network separation regulations, fiduciary-based data processing). Third, five governance design conditions enable early inflection: sensitivity-based dual-LLM architecture, four-layer documentation, formal AI committee operation, Regulatory Upward Harmonization, and explicit human oversight. This framework offers a transformation roadmap generalizable to other security-sensitive organizations.