• 제목/요약/키워드: Data Industry

검색결과 11,744건 처리시간 0.034초

A Study on the Development of E-Commerce Shipping Platform in China

  • Ying, Lou;Lee, Su-Ho;Shou, Jian-Min
    • 한국항해항만학회지
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    • 제40권2호
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    • pp.73-82
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    • 2016
  • With the advent of Internet era, e-commerce has become the focus of human's life. It leads a new direction of social development. As the representative of traditional industry, shipping industry is confronted with a series of difficulties, which have to break through the traditional and existing model to make their business for survival. With the increasing pricking up of market competition, shipping industry is now facing development bottle neck, but e-commerce provides a new way to solve the problem. This paper firstly describes the existing forms of the e-commerce shipping platform. Secondly analyzes the data for the situation of shipping industry in China, the data for expected functions of an e-commerce shipping platform and the data for how to choose a specific e-commerce shipping platform. Thirdly analyzes the potential risks of establishing e-commerce shipping platform in China. Based on the above researched, the paper provides a suggested model of the shipping e-commerce shipping platform in China.

건설업 보건관리자 선임 관련 비용편익분석 (Analysis of Cost Benefit Related to Appointing a Health Care Manager in the Construction Industry)

  • 정혜선;이지선;신인재;최은희
    • 한국직업건강간호학회지
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    • 제25권2호
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    • pp.130-140
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    • 2016
  • Purpose: The construction worker has diverse harmful factors such as noise, dust, and dealing with chemicals. Therefore this research aimed to examine the necessity of appointing a health manager in the construction industry by examining the cost-benefit analysis when the construction industry appoints a health manager. Methods: In order to calculate the healthcare staff employment cost and the benefits from their activities in 1,425 construction companies with the staff of 300 or more people during 2011, this study analyzed existing data and existing research data, as well as national data. Results: Total annual costs were 99,920,070,900 won and total annual benefits were 324,807,182,625 won. Benefits were found to be 224,887,111,725 won exceeding costs. Benefit/cost ratio resulting from appointing a health manager in the construction industry workplaces was 3.25 times. Conclusion: The findings of this research can be used as the base data to make rational decision to positively encourage the employment of healthcare staff in construction companies pursuant to relevant laws.

A Research on the Relationship between Accrual-based Earnings Management and Real Earnings Management in the Retail Industry

  • KANG, Shinae;KIM, Taejoong
    • 유통과학연구
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    • 제17권12호
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    • pp.5-12
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    • 2019
  • Purpose - In this paper, we examine the effect of accrual earnings management and real earnings management on the corporate value of retail corporations. Research design, data, and Methodology - The sample cover firms whose settlement is December among retail companies listed on the Korea Stock Exchange's securities market and KOSDAQ market from 2001 to 2016. Of these, the targets were companies with operating profit and equity capital of zero or higher and with sales data. The secondary data was collected through KIS-VALUE data base. The Jones model and the modified Jones model were used for the calculating the accrual-based earnings management and the real earnings management. Result - According to the empirical results, the relationship between accrual earnings management, real earnings management and firm value is positively significant in the retail industry as in manufacturing industry. These results are also significant when controlling the size, profitability, investment, debt ratio, dividend, and growth potential of a company. Conclusions - The characteristics of the distribution business can be identified and the influence of the various kinds of earnings management, which is being researched around the manufacturing industry, can be studied in the distribution industry to give practical implications to investors.

A study on changes in the food service industry about keyword before and after COVID-19 using big data

  • Jung, Sukjoon
    • International Journal of Internet, Broadcasting and Communication
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    • 제14권3호
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    • pp.85-90
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    • 2022
  • In this study, keywords from representative online portal sites such as NAVER, Google, and Youtube were collected based on text mining analysis technique using TEXTOM to check the changes in the restaurant industry before and after COVID-19. The collection keywords were selected as dining out, food service industry, and dining out culture. For the collected data, the top 30 words were derived, respectively, through the refinement process. In addition, comparative analysis was conducted by defining data from 2018 to 2019 before COVID-19, and from 2020 to 2021 after COVID-19. As a result, 8272 keywords before COVID-19 and 9654 keywords after COVID-19, a total of 17926 keywords, were derived. In order for the food service industry to develop after the COVID-19 pandemic, it is necessary to commercialize the recipes of restaurants to revitalize the distribution of home-use food products that replace home-cooked meals such as meal kits. Due to the social distancing caused by COVID-19, the dining out culture has changed and the trend has changed, and it has been confirmed that the consumption culture has changed to eating and delivering at home more safely than visiting restaurants. In addition, it has been confirmed that the consumption culture of existing consumers is changing to a trend of cooking at home rather than visiting restaurants.

Streamlining ERP Deployment in Nepal's Oil and Gas Industry: A Case Analysis

  • Dipa Adhikari;Bhanu Shrestha;Surendra Shrestha;Rajan Nepal
    • International Journal of Advanced Culture Technology
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    • 제12권3호
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    • pp.140-147
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    • 2024
  • Oil and gas industry is a unique sector with complex activities, long supply chains and strict rules for the business. It is important to use enterprise resource planning (ERP) systems to address these challenges as it helps in simplifying operations, improving efficiency and facilitating evidence-based decision making. Nonetheless, successful integration of ERP systems in this industry involves careful planning, customization and alignment with specific business processes including regulatory requirements. Several critical factors, such as strong change management, support of top managers and training that works have been identified in the study. Amongst the hurdles are employee resistance towards the changes, data migration complications and integration with existing systems. Nonetheless, NOCL's ERP implementation resulted in significant improvements in operating efficiency, better data visibility and compliance management. It also led to a decrease in financial reporting timeframes, more accurate inventory tracking and improved decision-making capabilities. The study provides useful insights on how to optimize oil and gas sector ERP implementations; key among them is practical advice including strengthening change management strategies, prioritizing data security and collaborating with ERP vendors. The research highlights the importance of tailoring ERP solutions to specific industry needs as well as emphasizes the strategic role of ongoing monitoring/feedback for future benefits sustainability.

환경서비스업과 물류서비스업의 예측 및 인과성 검정 (Prediction and Causality Examination of the Environment Service Industry and Distribution Service Industry)

  • 선일석;이충효
    • 유통과학연구
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    • 제12권6호
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    • pp.49-57
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    • 2014
  • Purpose - The world now recognizes environmental disruption as a serious issue when regarding growth-oriented strategies; therefore, environmental preservation issues become pertinent. Consequently, green distribution is continuously emphasized. However, studying the prediction and association of distribution and the environment is insufficient. Most existing studies about green distribution are about its necessity, detailed operation methods, and political suggestions; it is necessary to study the distribution service industry and environmental service industry together, for green distribution. Research design, data, and methodology - ARIMA (auto-regressive moving average model) was used to predict the environmental service and distribution service industries, and the Granger Causality Test based on VAR (vector auto regressive) was used to analyze the causal relationship. This study used 48 quarters of time-series data, from the 4th quarter in 2001 to the 3rd quarter in 2013, about each business type's production index, and used an unchangeable index. The production index about the business type is classified into the current index and the unchangeable index. The unchangeable index divides the current index into deflators to remove fluctuation. Therefore, it is easy to analyze the actual production index. This study used the unchangeable index. Results - The production index of the distribution service industry and the production index of the environmental service industry consider the autocorrelation coefficient and partial autocorrelation coefficient; therefore, ARIMA(0,0,2)(0,1,1)4 and ARIMA(3,1,0)(0,1,1)4 were established as final prediction models, resulting in the gradual improvement in every production index of both types of business. Regarding the distribution service industry's production index, it is predicted that the 4th quarter in 2014 is 114.35, and the 4th quarter in 2015 is 123.48. Moreover, regarding the environmental service industry's production index, it is predicted that the 4th quarter in 2014 is 110.95, and the 4th quarter in 2015 is 111.67. In a causal relationship analysis, the environmental service industry impacts the distribution service industry, but the distribution service industry does not impact the environmental service industry. Conclusions - This study predicted the distribution service industry and environmental service industry with the ARIMA model, and examined the causal relationship between them through the Granger causality test based on the VAR Model. Prediction reveals the seasonality and gradual increase in the two industries. Moreover, the environmental service industry impacts the distribution service industry, but the distribution service industry does not impact the environmental service industry. This study contributed academically by offering base line data needed in the establishment of a future style of management and policy directions for the two industries through the prediction of the distribution service industry and the environmental service industry, and tested a causal relationship between them, which is insufficient in existing studies. The limitations of this study are that deeper considerations of advanced studies are deficient, and the effect of causality between the two types of industries on the actual industry was not established.

의료 데이터 산업을 위한 비정형 데이터 비식별화 정책에 관한 연구 (A study on the policy of de-identifying unstructured data for the medical data industry)

  • 이선진;박태림;김소희;오영은;이일구
    • 융합보안논문지
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    • 제22권4호
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    • pp.85-97
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    • 2022
  • 빅데이터 기술이 발전하면서 데이터가 전 산업의 혁신 성장을 가속하는 초연결 지능화 사회로 빠르게 진입하고 있다. 고품질의 다양한 데이터를 보유하고 활용하는 융복합 산업이 새로운 성장 동력으로 자리매김하고 있으며, 다양한 전통 산업군에 빅데이터가 융합되어 데이터 기반의 혁신을 통해 디지털 전환이 이루어지고 있다. 특히 의료 분야에서는 전자의무기록 데이터와 같은 정형 데이터와 CT, MRI 등의 비정형 의료 데이터를 함께 활용함으로써, 질병 예측 및 진단의 정확도를 높이고 있다. 현재 의료 산업에서 비정형 데이터의 중요성과 규모는 나날이 증가하고 있지만, 종래의 데이터 보안 기술과 정책은 정형 데이터 중심이며, 비정형 데이터의 보안성과 활용성에 대한 고려는 미비하다. 향후 빅데이터를 활용한 진료가 활성화되려면 데이터의 다양성과 보안성이 데이터 구축, 유통, 활용 단계에서 내재화되고 유기적으로 연계되어야 한다. 본 논문에서는 국내외 데이터 보안 제도와 기술 현황을 분석한다. 이후 의료 분야에서 비정형 데이터가 활발히 사용될 수 있도록 비식별조치 가이드라인에 비정형 데이터 중심의 비식별 기술과 산업에서의 기술 적용 사례를 추가하고, 비정형 데이터에 대한 개인정보 판단 기준을 수립할 것을 제안한다. 더 나아가 개인정보를 침해하지 않고, 비정형 데이터에 활용할 수 있는 객체 특징 기반의 식별 ID를 제안한다.

The Effects of Industry Classification on a Successful ERP Implementation Model

  • Lee, Sangmin;Kim, Dongho
    • Journal of Information Processing Systems
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    • 제12권1호
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    • pp.169-181
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    • 2016
  • Organizations in some industries are still hesitant to adopt the Enterprise Resource Planning (ERP) system due to its high risk of failures. This study examined how industry classification affects the successful implementation of the ERP system. To achieve this goal, we reinvestigated the existing ERP Success Model that was developed by Chung with the data from various industry sectors, since Chung validated the model only in the engineering and construction industries. In order to test to see if the Chung model can be applicable outside the engineering and construction industries, the relationships between the ERP success indicators and the critical success factors in the Chung model and those in the sample data collected from ten different industry sectors were compared and investigated. The ten industry sectors were selected based on the Global Industry Classification Standard (GICS). We found that the impact of success factors on the success of implementing an ERP system varied across industry sectors. This means that the success of ERP system implementation can be industry-specific. Thus, industry classification should be considered as another factor to help IT decision makers or top-management avoid ERP system failures when they plan to implement a new ERP system.

공급사슬 관점에서 기업 위험의 계량적 추정 (Quantitative Estimation of Firm's Risk from Supply Chain Perspective)

  • 박근영;한현수
    • Journal of Information Technology Applications and Management
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    • 제22권2호
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    • pp.201-217
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    • 2015
  • In this paper, we report computational testing result to examine the validity of firm's bankruptcy risk estimation through quantification of supply chain risk. Supply chain risk in this study refers to upstream supply risk and downstream demand risk, To assess the firm's risk affected by supply chain risk, we adopt unit of analysis as industry level. since supply and demand relationships of the firm could be generalized by the industry input-output table and the availability of various valid economic indicators which are chronologically calculated. The research model to estimate firm's risk level is the linear regression model to assess the industry bankruptcy risk estimation of the focal firm's industry with the independent variables which could quantitatively reflect demand and supply risk of the industry. The publicly announced macro economic indicators are selected as the candidate independent variables and validated through empirical testing. To validate our approach, in this paper, we confined our research scope to steel industry sector and its related industry sectors, and implemented the research model. The empirical testing results provide useful insights to further refine the research model as the valid forecasting mechanism to capture firm's future risk estimation more accurately by adopting supply chain industry risk aspect, in conjunction with firm's financial and other managerial factors.

수산업 빅데이터 플랫폼 구축 방안에 대한 연구 (Study on the Big Data Platform Construction of Fisheries)

  • 최주원;정재욱;김영애;신용태
    • 정보처리학회논문지:컴퓨터 및 통신 시스템
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    • 제9권8호
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    • pp.181-188
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    • 2020
  • 수산업은 현재 전통어로어업에서 양식업으로 패러다임이 급속히 전환되고 있으며, 수산자원 고갈, 어촌 공동화에 따른 기반 약화 등 다양한 문제점에 직면하여 있다. 이를 타개하기 위한 수산업의 기반 강화, 어촌 6차산업화, 관련 기술표준 수립, 신산업 발굴 등을 위해서 수산업의 중심산업, 주변 산업의 데이터와 공공 및 민간의 유관 데이터를 모두 포함하는 수산업 빅데이터 플랫폼의 구축이 필요하다. 데이터 센터기관이 수집, 연계, 전처리를 수행하고, 플랫폼 주관 기관이 빅데이터 플랫폼 구축, 운영 및 데이터마켓을 통한 수산업 데이터 선순환 체계를 조성하여 당면 위기 극복 및 스마트 수산업 헤게모니 확보, 가치이동의 핵심열쇠로 활용하여야 한다. 본 연구를 통하여 이를 성공적으로 추진하기 위한 정책적·기술적 빅데이터 플랫폼 구축 방안에 대하여 제안하고자 한다.