• Title/Summary/Keyword: Technical Indicators

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Formation of the Strategy of Digital Marketing of the Enterprise in the Conditions of the Competitiveness Intensification in the International Market

  • Solntsev, Sergii;Smerichevskyi, Serhii;Skyba, Halyna;Zabashtanska, Tetiana;Bazaliyska, Natalia;Kolbushkin, Yuriy
    • International Journal of Computer Science & Network Security
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    • v.22 no.2
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    • pp.47-56
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    • 2022
  • The article defines the principles of formation of digital marketing strategy of enterprises in the conditions of intensification of competition on the international market. The stages of development of digital marketing strategy of enterprises in the conditions of intensification of competition in the international market are substantiated, which includes: setting goals, which envisages observance of the principles of SMART-scheme; product or service analysis; monitoring of competitors; analytics of definition and segmentation of the target audience of the enterprise; selection of digital marketing tools and channels for promotion on the international market of products or services; formation of a unique, unique trade offer, selection of indicators for evaluating the effectiveness of digital marketing strategy and its tools. It is proved that according to the principle of SMART method of goal setting it is necessary that the goals have: specificity, measurability, achievability, relevance, achievement of the goal should be limited in time, have specific deadlines. To increase the effectiveness of digital marketing strategy, it is necessary to analyze the internal and external environment using the method of SWOT-analysis, the advantage of which is a comprehensive assessment of the company, competitors and the industry as a whole in the face of competition in the international market. The main indicators of evaluation of the effectiveness of digital marketing strategy in the conditions of intensification of competition on the international market are substantiated.

SWOT Analysis and Expert Assessment of the Effectiveness of the Introduction of Healthcare Information Systems in Polyclinics in Aktobe, Kazakhstan

  • Lyudmila, Yermukhanova;Zhanar, Buribayeva;Indira, Abdikadirova;Anar, Tursynbekova;Meruyert, Kurganbekova
    • Journal of Preventive Medicine and Public Health
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    • v.55 no.6
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    • pp.539-548
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    • 2022
  • Objectives: The purpose of this study was to assess the organizational effectiveness of the introduction of a healthcare information system (electronic medical records and databases) in healthcare in Kazakhstan. Methods: The authors used a combination of 2 methods: expert assessment and strengths, weaknesses, opportunities, and threats (SWOT) analysis. SWOT analysis is a necessary element of research, constituting a mandatory preliminary stage both when drawing up strategic plans and for taking corrective measures in the future. The expert survey was conducted using 2 questionnaires. Results: The study involved 40 experts drawn from specialists in primary healthcare in Aktobe: 15 representatives of administrative and managerial personnel (chief doctors and their deputies, heads of medical statistics offices, organizational and methodological offices, and internal audit services) and 25 general practitioners. Conclusions: The following functional indicators of the medical and organizational effectiveness of the introduction of information systems in polyclinics were highlighted: first, improvement of administrative control, followed in descending order by registration and movement of medical documentation, statistical reporting and process results, and the cost of employees' working time. There has been no reduction in financial costs, namely in terms of the costs of copying, delivery of information in paper form, technical equipment, and paper.

6th Industry Management Body Develop Managerial and Technical Level Metrics - by Applying AHP Analysis - (6차산업화 경영체 경영.기술수준 평가지표 개발 -AHP 분석을 적용하여-)

  • Seo, Yoon Jeong;Park, Jeong Woon;Han, Sang Yeon;Hwang, Dae Yong;Yang, Jung Hyun
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.8 no.4
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    • pp.177-191
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    • 2013
  • 6th Industry reduced agricultural income and rural areas, the economic downturn is going to be activated is attracting attention as an alternative. 6th industry means that the integrated or linked, the manufacture and processing of secondary industry based on primary industry, the distribution and service of tertiary industry. Park Geun-hye government to realize the creative economy in agriculture as an alternative to specifically evaluate the 6th industries and suggests various policy alternatives. In addition, to support the development of models and analysis of best practices, including sleep studies are in progress. However, the 6th Industry management body for performing management level, technical level, the leader in comprehensive evaluation of competencies and indicators on the development of an evaluation study is insufficient. In this regard, the present study performed 6th industry management body for the management level, technical level, the leader competency evaluation indicators to develop a comprehensive evaluation by utilizing AHP method was developed indicators. The results achieved in Korea As different countries and the FTA as cheap agricultural imports increased 6th industry revenues associated with the management body is very likely to be worse. The endless competition to survive in the most important of the strategy for each individual project management body to operate on their own, rather than to strengthen internal capacity by strengthening linkages with other industries, products, and services that promote the sale will be. This also is that you need to improve revenue management body. Thus, all 6th industry management body at the location of their efforts to gain the trust of consumers will require, moreover, for each management body to build cooperation between the various measures will be sought. In addition to the smart era rapidly changing needs of customers, depending on the life cycle of products and services are getting faster and the new consumer is getting more and more tend to find new products. Thus, customers and management body 6th industry changes quickly and accurately predict market trends, and also to market new products and services that further efforts would be needed.

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Collaborative Planning Model for Brownfield Regeneration (브라운필드 재생을 위한 협력적 계획 모델 연구)

  • Kim, Eujin Julia;Miller, Patrick
    • Journal of the Korean Institute of Landscape Architecture
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    • v.43 no.3
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    • pp.92-100
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    • 2015
  • Unlike most other planning processes, brownfield planning generally requires a high level of technical and legal expertise due to potential site contamination. To successfully engage in inclusionary decision making, an adaptive collaboration strategy for brownfield planning is therefore critical. This study examines how a communicative planning approach can be used to overcome the challenge of enabling experts from different fields to work alongside lay people from the local community to achieve a properly balanced collaboration in brownfield planning. After identifying appropriate indicators for collaboration through a literature review of established communicative planning theory, these indicators are applied to the brownfield planning process, highlighting critical points of collaboration such as site prioritization, assessment, remediation, and redevelopment throughout. The results suggest the critical need for an adaptive model focusing on three aspects: 1. Facilitation of a balanced dialogue between the experts with social, cultural, and design-based knowledge and the ones with scientific and engineering-based knowledge, 2. Preparation of an appropriate tool for risk communication with the lay people, 3. Development of decision support system for the integration of expert-oriented technical data and public opinion-oriented subjective data.

Development of an Intelligent Trading System Using Support Vector Machines and Genetic Algorithms (Support Vector Machines와 유전자 알고리즘을 이용한 지능형 트레이딩 시스템 개발)

  • Kim, Sun-Woong;Ahn, Hyun-Chul
    • Journal of Intelligence and Information Systems
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    • v.16 no.1
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    • pp.71-92
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    • 2010
  • As the use of trading systems increases recently, many researchers are interested in developing intelligent trading systems using artificial intelligence techniques. However, most prior studies on trading systems have common limitations. First, they just adopted several technical indicators based on stock indices as independent variables although there are a variety of variables that can be used as independent variables for predicting the market. In addition, most of them focus on developing a model that predicts the direction of the stock market indices rather than one that can generate trading signals for maximizing returns. Thus, in this study, we propose a novel intelligent trading system that mitigates these limitations. It is designed to use both the technical indicators and the other non-price variables on the market. Also, it adopts 'two-threshold mechanism' so that it can transform the outcome of the stock market prediction model based on support vector machines to the trading decision signals like buy, sell or hold. To validate the usefulness of the proposed system, we applied it to the real world data-the KOSPI200 index from May 2004 to December 2009. As a result, we found that the proposed system outperformed other comparative models from the perspective of 'rate of return'.

A Two-Phase Stock Trading System based on Pattern Matching and Automatic Rule Induction (패턴 매칭과 자동 규칙 생성에 기반한 2단계 주식 트레이딩 시스템)

  • Lee, Jong-Woo;Kim, Yu-Seop;Kim, Sung-Dong;Lee, Jae-Won;Chae, Jin-Seok
    • The KIPS Transactions:PartB
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    • v.10B no.3
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    • pp.257-264
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    • 2003
  • In the context of a dynamic trading environment, the ultimate goal of the financial forecasting system is to optimize a specific trading objective. This paper proposes a two-phase (extraction and filtering) stock trading system that aims at maximizing the rates of returns. Extraction of stocks is performed by searching specific time-series patterns described by a combination of values of technical indicators. In the filtering phase, several rules are applied to the extracted sets of stocks to select stocks to be actually traded. The filtering rules are automatically induced from past data. From a large database of daily stock prices, the values of technical indicators are calculated. They are used to make the extraction patterns, and the distributions of the discretization intervals of the values are calculated for both positive and negative data sets. We assumed that the values in the intervals of distinctive distribution may contribute to the prediction of future trend of stocks, so the rules for filtering stocks are automatically induced from the data in those intervals. We show the rates of returns when using our trading system outperform the market average. These results mean rule induction method using distributional differences is useful.

The Prediction of Cryptocurrency Prices Using eXplainable Artificial Intelligence based on Deep Learning (설명 가능한 인공지능과 CNN을 활용한 암호화폐 가격 등락 예측모형)

  • Taeho Hong;Jonggwan Won;Eunmi Kim;Minsu Kim
    • Journal of Intelligence and Information Systems
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    • v.29 no.2
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    • pp.129-148
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    • 2023
  • Bitcoin is a blockchain technology-based digital currency that has been recognized as a representative cryptocurrency and a financial investment asset. Due to its highly volatile nature, Bitcoin has gained a lot of attention from investors and the public. Based on this popularity, numerous studies have been conducted on price and trend prediction using machine learning and deep learning. This study employed LSTM (Long Short Term Memory) and CNN (Convolutional Neural Networks), which have shown potential for predictive performance in the finance domain, to enhance the classification accuracy in Bitcoin price trend prediction. XAI(eXplainable Artificial Intelligence) techniques were applied to the predictive model to enhance its explainability and interpretability by providing a comprehensive explanation of the model. In the empirical experiment, CNN was applied to technical indicators and Google trend data to build a Bitcoin price trend prediction model, and the CNN model using both technical indicators and Google trend data clearly outperformed the other models using neural networks, SVM, and LSTM. Then SHAP(Shapley Additive exPlanations) was applied to the predictive model to obtain explanations about the output values. Important prediction drivers in input variables were extracted through global interpretation, and the interpretation of the predictive model's decision process for each instance was suggested through local interpretation. The results show that our proposed research framework demonstrates both improved classification accuracy and explainability by using CNN, Google trend data, and SHAP.

Technological Cooperation Network Analysis through Patent Analysis of Autonomous Driving Technology (자동차 자율주행 기술 특허분석을 통한 기술협력 네트워크 분석)

  • Lim, Ho-Geun;Kim, Byungkeun;Jeong, Euiseob
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.12
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    • pp.688-701
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    • 2020
  • This study analyzes the characteristics and change factors of technological cooperation networks in the automotive industry. Using Social Network Analysis (SNA) of 112,009 autonomous driving-related patents filed from 2000 to 2017 by major automotive firms in the world, we investigate the structure of the technological cooperation network. Network characteristics such as density are analyzed through structural characteristic analysis among the network analysis indicators. The structural characteristics of the technology cooperation network are confirmed through analysis of status characteristic indicators, such as the degree of centrality, betweenness centrality, and closeness centrality. Results show that car makers such as Toyota and Hyundai Motors, as well as parts suppliers such as Bosch and Continental, have high-performance technology developments related to autonomous driving. The structural characteristics of the network show that companies participating in cooperative networks for autonomous driving technology development have increased in number and are diversified, and all of the status characteristics indicators have decreased. This can be interpreted as an increasing number of horizontal and complementary forms of technological cooperation between firms. In addition, it was confirmed that the number of participants in the field of autonomous driving technology has increased, and the networks have become more complex.

A Study on Correlation Analysis between TCB Evaluation Indicator and Technology Rating (기술신용평가기관(TCB) 효율성 제고 및 기업기술력 강화를 위한 평가지표간 상관관계 분석연구)

  • Son, Seokhyun;Kim, Jaeyoung;Kim, Jaechun
    • Journal of Technology Innovation
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    • v.25 no.4
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    • pp.1-15
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    • 2017
  • In 2014, the Financial Services Commission designated the Tech Credit Bureaus(TCB) to issue technical credit evaluation reports. The Five credit rating agencies, KEB Hana Bank and others have issued the technical credit reports since the summer in 2014. Meanwhile, the technology evaluation model of KEB Hana Bank consists of 25 detailed evaluation items. These item classes are weighted and the technology rating is systematically. The technology rating is combined with the credit rating to calculate the technology-credit rating. In this paper, we analyzed the 406 evaluation results issued by KEB Hana Bank. Based on the number of years of work experience, company managerial years, technical personnel score, the possession of R&D department, the amount of R&D investment, the number of certifications, and the number of patents, the Correlation between the above items and the technical grade was analyzed. It was found that quantitative indicators such as the presence of R&D department, patent numbers, and R&D investment expenses had a significant effect on the company's technology grade, and in particular, the presence of R&D department was shown a high correlation with the technology rating.

A Study on Evaluation System of Risk Assessment at Coastal Activity Areas (연안활동장소의 위험도 평가체계 수립 연구)

  • Park, Seon Jung;Park, Seol Hwa;Seo, Heui Jung;Park, Seung Min
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.33 no.6
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    • pp.226-237
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    • 2021
  • Coastal safety accidents are characterized by a high proportion of human negligence and repeated occurrences of accidents caused by the same factors. The Korea Coast Guard prepares and implements various countermeasures to prevent accidents at coastal safety accident sites. However, there is a shortage of safety facilities and safety management personnel according to the limited budget. In addition, the ability to be proactively and proactively respond is low due to the limitations of the coastal safety accident risk forecasting system, which relies on the meteorological warning of the Korea Meteorological Administration. In this study, as part of preparing the foundation for establishing a preemptive and active coastal safety management system that can manage accident-causing factors, predict and evaluate risk, and implement response and mitigation measures after an accident occurs before coastal safety accidents occur. The establishment of a risk assessment system was proposed. The main evaluation factors and indicators for risk assessment were established through the analysis of the status of coastal safety accidents. The risk assessment methodology was applied to 40 major hazardous areas designated and managed by the Korea Coast Guard.