• Title/Summary/Keyword: Interdependence model

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Modularization of Automotive Product Architecture: Evidence from Passenger Car (자동차 아키텍처의 모듈화: 승용차 사례를 중심으로)

  • Kwak, Kiho
    • Journal of Technology Innovation
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    • v.27 no.2
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    • pp.37-71
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    • 2019
  • How has the passenger car's architecture evolved? In the meantime, the discussions on the car architecture have been mixed, i.e., integral, modular, and the coexistence of two types. Therefore, in this study, we aim to develop two indices can measure the degree of modularization of passenger car and its all modules using global trade data. By applying the indices to the framework of architecture positioning that reflects the hierarchical structure of a product, we examined that the degree of modularization of the passenger car architecture has been enhanced. Meanwhile, the degree of modularization differs across the modules that make up the car. Specifically, we observed the higher degree of modularization in front-end, cockpit and seat modules. Whereas, we found that body module had a relatively low degree of modularization. In particular, we observed that the platform of passenger car has notably modularized due to carmakers' efforts to achieve model diversification and reduction of cost and period in new product development at the same time. Interestingly, we showed that three modules, i.e., engine, chassis (relatively less modularized), and transmission (relatively highly modularized), had a different level of modularization, even if they commonly make up the platform. We contribute to the suggestion for analytical approaches that examine the degree of modularization and its progress longitudinally. In addition, we propose the necessity of decomposition of a system into elements in a study of product architecture, considering the possibly distinctive progress of modularization across the elements.

The Effect of Settlement Inclusivity on Older People's Mental Health (정주환경 포용성이 고령층의 정신건강에 미치는 효과)

  • Lee, Sae Rom;Park, In Kwon
    • Journal of the Korean Regional Science Association
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    • v.36 no.4
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    • pp.3-23
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    • 2020
  • This study aims to conceptualize the settlement inclusivity for overcoming social exclusion and the decline in quality of life of older people and to examine its effects on their mental health. The concept of the settlement inclusivity for older people focuses on the immediate environment around the place where they live. We proposed two domains for the conceptual framework; social domain that provides opportunities for community cohesion; spatial domain that provides security of residential area and access to basic services within walking distance. The social domain was represented by participation and interdependence, while the spatial domain by security and accessibility in the settlement inclusivity. Zero-inflated negative binomial regression model was constructed with 2017 National Survey of Older Koreans data to analyze the factors influencing depressive symptoms of older adults. The empirical results demonstrate that increased level of neighborhood network and social participation is associated with a decrease in the number of depressive symptoms. In addition, higher satisfaction in neighborhood environment and good accessibility to public transport/stores are associated with fewer depressive symptoms. Finally, housing condition and home ownership have a moderating effect on the relationship between social network/participation and depressive symptoms level, whereas they have no direct effects on depressive symptoms. This study demonstrates multi-dimensionally and mutually significant associations between settlement inclusivity and depressive symptoms for older people providing implications for urban planning and policies to improve mental well-being of older population.

A Study on Collaborative Governance: Focusing on the Cultural Heritage Guardians (문화재지킴이 정책의 협력적 거버넌스 운영 체계 연구)

  • Jang, Youngki
    • Korean Journal of Heritage: History & Science
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    • v.54 no.1
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    • pp.184-205
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    • 2021
  • Governance is valued as a new concept and principle of social operation and public policy management, and its influence is gradually expanding. Among the various governance theories being put into practice and in case analysis studies, collaborative governance embracing various governance concepts has been found to increase interdependence and responsibility beyond participation and compromise, and create new public values by integrating and utilizing optimal social coordination forms. In the field of cultural assets, governance-related research is also being conducted for the efficiency, sustainability, and scalability of public policy enforcement. This study explored the government's role (promotion, arbitration, and condition creation) in collaborative governance, focusing on the "Cultural Heritage Guardians" to understand how collaborative governance operates in the cultural heritage sector. Regarding governance policies in the cultural asset sector, the cultural asset guardians highlighted the status, role, and characteristics of policies by examining their introduction, development, and implementation. The results of the analysis revealed that private-led, horizontal public-private cooperation, collaborative governance, policy introduction, solidarity, professionalism, resource/knowledge imbalance, cooperation precedence, etc., facilitate increased participation. The government has accordingly proposed measures to establish comprehensive legal stability centered on cooperation; strategic reorganization of dedicated organizations; strengthened, supportive intermediate organizations; and individual and multi-party consultative bodies.

The Influence of Work-Family Conflict on the Marital Satisfaction of Dual-Earner Couples: Moderating effect of three types of coping strategies (맞벌이 부부의 일-가정 갈등이 결혼만족에 미치는 영향에서 스트레스 대처의 조절효과)

  • Lim, In-Hye;Yoo, Sung-Kyung
    • Korean Journal of Culture and Social Issue
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    • v.26 no.4
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    • pp.551-578
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    • 2020
  • The purpose of this study is to identify the moderating effect of each of the three stress response (problem-centered treatment, pursuit of social support, and positive thinking) in the effect of work-family conflict between dual-earner couples on marriage satisfaction. To this end, 369 married couples (369 wives, 369 husbands) who raise children under the age of 6 were surveyed on stress coping (problem-centered, social support, and positive thinking), work-family conflicts, and marriage satisfaction. Based on the Actor-Partner Interdependence Model (APIM), the collected data verified six research models by distinguishing the moderating effects of each of the three coping strategies from the direction of Work to Family conflict and Family to Work conflict. Interaction graphs were also presented to determine the pattern of significant buffering effects. As a result, first of all, the problem-oriented strategy of the wife buffer the negative impact of the husband's WFC on the husband's own and wife's marriage satisfaction. It was also found that problem-oriented strategy that husband himself uses to buffer the negative impact of the husband's FWC on his wife's marriage satisfaction. Second, the pursuit of social support confirmed that the negative effects of the husband's WFC on the husband's marriage satisfaction were mitigated by the pursuit of social support used by his wife. Third, in the case of positive thinking, the effect of the positive thinking on the husband's WFC on the marriage satisfaction of the husband and wife was shown, and the positive response effect of the wife's FWC conflict was also shown. Finally, based on the results of this study, the discussion and implications of the study were presented.

Discovering Promising Convergence Technologies Using Network Analysis of Maturity and Dependency of Technology (기술 성숙도 및 의존도의 네트워크 분석을 통한 유망 융합 기술 발굴 방법론)

  • Choi, Hochang;Kwahk, Kee-Young;Kim, Namgyu
    • Journal of Intelligence and Information Systems
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    • v.24 no.1
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    • pp.101-124
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    • 2018
  • Recently, most of the technologies have been developed in various forms through the advancement of single technology or interaction with other technologies. Particularly, these technologies have the characteristic of the convergence caused by the interaction between two or more techniques. In addition, efforts in responding to technological changes by advance are continuously increasing through forecasting promising convergence technologies that will emerge in the near future. According to this phenomenon, many researchers are attempting to perform various analyses about forecasting promising convergence technologies. A convergence technology has characteristics of various technologies according to the principle of generation. Therefore, forecasting promising convergence technologies is much more difficult than forecasting general technologies with high growth potential. Nevertheless, some achievements have been confirmed in an attempt to forecasting promising technologies using big data analysis and social network analysis. Studies of convergence technology through data analysis are actively conducted with the theme of discovering new convergence technologies and analyzing their trends. According that, information about new convergence technologies is being provided more abundantly than in the past. However, existing methods in analyzing convergence technology have some limitations. Firstly, most studies deal with convergence technology analyze data through predefined technology classifications. The technologies appearing recently tend to have characteristics of convergence and thus consist of technologies from various fields. In other words, the new convergence technologies may not belong to the defined classification. Therefore, the existing method does not properly reflect the dynamic change of the convergence phenomenon. Secondly, in order to forecast the promising convergence technologies, most of the existing analysis method use the general purpose indicators in process. This method does not fully utilize the specificity of convergence phenomenon. The new convergence technology is highly dependent on the existing technology, which is the origin of that technology. Based on that, it can grow into the independent field or disappear rapidly, according to the change of the dependent technology. In the existing analysis, the potential growth of convergence technology is judged through the traditional indicators designed from the general purpose. However, these indicators do not reflect the principle of convergence. In other words, these indicators do not reflect the characteristics of convergence technology, which brings the meaning of new technologies emerge through two or more mature technologies and grown technologies affect the creation of another technology. Thirdly, previous studies do not provide objective methods for evaluating the accuracy of models in forecasting promising convergence technologies. In the studies of convergence technology, the subject of forecasting promising technologies was relatively insufficient due to the complexity of the field. Therefore, it is difficult to find a method to evaluate the accuracy of the model that forecasting promising convergence technologies. In order to activate the field of forecasting promising convergence technology, it is important to establish a method for objectively verifying and evaluating the accuracy of the model proposed by each study. To overcome these limitations, we propose a new method for analysis of convergence technologies. First of all, through topic modeling, we derive a new technology classification in terms of text content. It reflects the dynamic change of the actual technology market, not the existing fixed classification standard. In addition, we identify the influence relationships between technologies through the topic correspondence weights of each document, and structuralize them into a network. In addition, we devise a centrality indicator (PGC, potential growth centrality) to forecast the future growth of technology by utilizing the centrality information of each technology. It reflects the convergence characteristics of each technology, according to technology maturity and interdependence between technologies. Along with this, we propose a method to evaluate the accuracy of forecasting model by measuring the growth rate of promising technology. It is based on the variation of potential growth centrality by period. In this paper, we conduct experiments with 13,477 patent documents dealing with technical contents to evaluate the performance and practical applicability of the proposed method. As a result, it is confirmed that the forecast model based on a centrality indicator of the proposed method has a maximum forecast accuracy of about 2.88 times higher than the accuracy of the forecast model based on the currently used network indicators.

The Causes of Conflict and the Effect of Control Mechanisms on Conflict Resolution between Manufacturer and Supplier (제조-공급자간 갈등 원인과 거래조정 방식의 갈등관리 효과)

  • Rhee, Jin Hwa
    • Journal of Distribution Research
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    • v.17 no.4
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    • pp.55-80
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    • 2012
  • I. Introduction Developing the relationships between companies is very important issue to ensure a competitive advantage in today's business environment (Bleeke & Ernst 1991; Mohr & Spekman 1994; Powell 1990). Partnerships between companies are based on having same goals, pursuing mutual understanding, and having a professional level of interdependence. By having such a partnerships and cooperative efforts between companies, they will achieve efficiency and effectiveness of their business (Mohr and Spekman, 1994). However, it is difficult to expect these ideal results only in the B2B corporate transaction. According to agency theory which is the well-accepted theory in various fields of business strategy, organization, and marketing, the two independent companies have fundamentally different corporate purposes. Also there is a higher chance of developing opportunism and conflict due to natures of human(organization), such as self-interest, bounded rationality, risk aversion, and environment factor as imbalance of information (Eisenhardt 1989). That is, especially partnerships between principal(or buyer) and agent(or supplier) of companies within supply chain, the business contract itself will not provide competitive advantage. But managing partnership between companies is the key to success. Therefore, managing partnership between manufacturer and supplier, and finding causes of conflict are essential to improve B2B performance. In conclusion, based on prior researches and Agency theory, this study will clarify how business hazards cause conflicts on supply chain and then identify how developed conflicts have been managed by two control mechanisms. II. Research model III. Method In order to validate our research model, this study gathered questionnaires from small and medium sized enterprises(SMEs). In Korea, SMEs mean the firms whose employee is under 300 and capital is under 8 billion won(about 7.2 million dollar). We asked the manufacturer's perception about the relationship with the biggest supplier, and our key informants are denied to a person responsible for buying(ex)CEO, executives, managers of purchasing department, and so on). In detail, we contact by telephone to our initial sample(about 1,200 firms) and introduce our research motivation and send our questionnaires by e-mail, mail, and direct survey. Finally we received 361 data and eliminate 32 inappropriate questionnaires. We use 329 manufactures' data on analysis. The purpose of this study is to identify the anticipant role of business hazard (environmental dynamism, asset specificity) and investigate the moderating effect of control mechanism(formal control, social control) on conflict-performance relationship. To find out moderating effect of control methods, we need to compare the regression weight between low versus. high group(about level of exercised control methods). Therefore we choose the structural equation modeling method that is proper to do multi-group analysis. The data analysis is performed by AMOS 17.0 software, and model fits are good statically (CMIN/DF=1.982, p<.000, CFI=.936, IFI=.937, RMSEA=.056). IV. Result V. Discussion Results show that the higher environmental dynamism and asset specificity(on particular supplier) buyer(manufacturer) has, the more B2B conflict exists. And this conflict affect relationship quality and financial outcomes negatively. In addition, social control and formal control could weaken the negative effect of conflict on relationship quality significantly. However, unlikely to assure conflict resolution effect of control mechanisms on relationship quality, financial outcomes are changed by neither social control nor formal control. We could explain this results with the characteristics of our sample, SMEs(Small and Medium sized Enterprises). Financial outcomes of these SMEs(manufacturer or principal) are affected by their customer(usually major company) more easily than their supplier(or agent). And, in recent few years, most of companies have suffered from financial problems because of global economic recession. It means that it is hard to evaluate the contribution of supplier(agent). Therefore we also support the suggestion of Gladstein(1984), Poppo & Zenger(2002) that relational performance variable can capture the focal outcomes of relationship(exchange) better than financial performance variable. This study has some implications that it tests the sources of conflict and investigates the effect of resolution methods of B2B conflict empirically. And, especially, it finds out the significant moderating effect of formal control which past B2B management studies have ignored in Korea.

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The Effect of Structured Information on the Sleep Amount of Patients Undergoing Open Heart Surgery (계획된 간호 정보가 수면량에 미치는 영향에 관한 연구 -개심술 환자를 중심으로-)

  • 이소우
    • Journal of Korean Academy of Nursing
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    • v.12 no.2
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    • pp.1-26
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    • 1982
  • The main purpose of this study was to test the effect of the structured information on the sleep amount of the patients undergoing open heart surgery. This study has specifically addressed to the Following two basic research questions: (1) Would the structed in formation influence in the reduction of sleep disturbance related to anxiety and Physical stress before and after the operation? and (2) that would be the effects of the structured information on the level of preoperative state anxiety, the hormonal change, and the degree of behavioral change in the patients undergoing an open heart surgery? A Quasi-experimental research was designed to answer these questions with one experimental group and one control group. Subjects in both groups were matched as closely as possible to avoid the effect of the differences inherent to the group characteristics, Baseline data were also. collected on both groups for 7 days prior to the experiment and found that subjects in both groups had comparable sleep patterns, trait anxiety, hormonal levels and behavioral level. A structured information as an experimental input was given to the subjects in the experimental group only. Data were collected and compared between the experimental group and the control group on the sleep amount of the consecutive pre and post operative days, on preoperative state anxiety level, and on hormonal and behavioral changes. To test the effectiveness of the structured information, two main hypotheses and three sub-hypotheses were formulated as follows; Main hypothesis 1: Experimental group which received structured information will have more sleep amount than control group without structured information in the night before the open heart surgery. Main hypothesis 2: Experimental group with structured information will have more sleep, amount than control group without structured information during the week following the open heart surgery Sub-hypothesis 1: Experimental group with structured information will be lower in the level of State anxiety than control group without structured information in the night before the open heart surgery. Sub-hypothesis 2 : Experimental group with structured information will have lower hormonal level than control group without stuctured information on the 5th day after the open heart surgery Sub-hypothesis 3: Experimental group with structured information will be lower in the behavioral change level than control group without structured information during the week after the open heart surgery. The research was conducted in a national university hospital in Seoul, Korea. The 53 Subjects who participated in the study were systematically divided into experimental group and control group which was decided by random sampling method. Among 53 subjects, 26 were placed in the experimental group and 27 in the control group. Instruments; (1) Structed information: Structured information as an independent variable was constructed by the researcher on the basis of Roy's adaptation model consisting of physiologic needs, self-concept, role function and interdependence needs as related to the sleep and of operational procedures. (2) Sleep amount measure: Sleep amount as main dependent variable was measured by trained nurses through observation on the basis of the established criteria, such as closed or open eyes, regular or irregular respiration, body movement, posture, responses to the light and question, facial expressions and self report after sleep. (3) State anxiety measure: State Anxiety as a sub-dependent variable was measured by Spi-elberger's STAI Anxiety scale, (4) Hormornal change measure: Hormone as a sub-dependent variable was measured by the cortisol level in plasma. (5) Behavior change measure: Behavior as a sub-dependent variable was measured by the Behavior and Mood Rating Scale by Wyatt. The data were collected over a period of four months, from June to October 1981, after the pretest period of two months. For the analysis of the data and test for the hypotheses, the t-test with mean differences and analysis of covariance was used. The result of the test for instruments show as follows: (1) STAI measurement for trait and state anxiety as analyzed by Cronbachs alpha coefficient analysis for item analysis and reliability showed the reliability level at r= .90 r= .91 respectively. (2) Behavior and Mood Rating Scale measurement was analyzed by means of Principal Component Analysis technique. Seven factors retained were anger, anxiety, hyperactivity, depression, bizarre behavior, suspicious behavior and emotional withdrawal. Cumulative percentage of each factor was 71.3%. The result of the test for hypotheses show as follows; (1) Main hypothesis, was not supported. The experimental group has 282 minutes of sleep as compared to the 255 minutes of sleep by the control group. Thus the sleep amount was higher in experimental group than in control group, however, the difference was not statistically significant at .05 level. (2) Main hypothesis 2 was not supported. The mean sleep amount of the experimental group and control group were 297 minutes and 278 minutes respectively Therefore, the experimental group had more sleep amount as compared to the control group, however, the difference was not statistically significant at .05 level. Thus, the main hypothesis 2 was not supported. (3) Sub-hypothesis 1 was not supported. The mean state anxiety of the experimental group and control group were 42.3, 43.9 in scores. Thus, the experimental group had slightly lower state anxiety level than control group, howe-ver, the difference was not statistically significant at .05 level. (4) Sub-hypothesis 2 was not supported. . The mean hormonal level of the experimental group and control group were 338 ㎍ and 440 ㎍ respectively. Thus, the experimental group showed decreased hormonal level than the control group, however, the difference was not statistically significant at .05 level. (5) Sub-hypothesis 3 was supported. The mean behavioral level of the experimental group and control group were 29.60 and 32.00 respectively in score. Thus, the experimental group showed lower behavioral change level than the control group. The difference was statistically significant at .05 level. In summary, the structured information did not influence the sleep amount, state anxiety or hormonal level of the subjects undergoing an open heart surgery at a statistically significant level, however, it showed a definite trends in their relationships, not least to mention its significant effect shown on behavioral change level. It can further be speculated that a great degree of individual differences in the variables such as sleep amount, state anxiety and fluctuation in hormonal level may partly be responsible for the statistical insensitivity to the experimentation.

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Development of a complex failure prediction system using Hierarchical Attention Network (Hierarchical Attention Network를 이용한 복합 장애 발생 예측 시스템 개발)

  • Park, Youngchan;An, Sangjun;Kim, Mintae;Kim, Wooju
    • Journal of Intelligence and Information Systems
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    • v.26 no.4
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    • pp.127-148
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    • 2020
  • The data center is a physical environment facility for accommodating computer systems and related components, and is an essential foundation technology for next-generation core industries such as big data, smart factories, wearables, and smart homes. In particular, with the growth of cloud computing, the proportional expansion of the data center infrastructure is inevitable. Monitoring the health of these data center facilities is a way to maintain and manage the system and prevent failure. If a failure occurs in some elements of the facility, it may affect not only the relevant equipment but also other connected equipment, and may cause enormous damage. In particular, IT facilities are irregular due to interdependence and it is difficult to know the cause. In the previous study predicting failure in data center, failure was predicted by looking at a single server as a single state without assuming that the devices were mixed. Therefore, in this study, data center failures were classified into failures occurring inside the server (Outage A) and failures occurring outside the server (Outage B), and focused on analyzing complex failures occurring within the server. Server external failures include power, cooling, user errors, etc. Since such failures can be prevented in the early stages of data center facility construction, various solutions are being developed. On the other hand, the cause of the failure occurring in the server is difficult to determine, and adequate prevention has not yet been achieved. In particular, this is the reason why server failures do not occur singularly, cause other server failures, or receive something that causes failures from other servers. In other words, while the existing studies assumed that it was a single server that did not affect the servers and analyzed the failure, in this study, the failure occurred on the assumption that it had an effect between servers. In order to define the complex failure situation in the data center, failure history data for each equipment existing in the data center was used. There are four major failures considered in this study: Network Node Down, Server Down, Windows Activation Services Down, and Database Management System Service Down. The failures that occur for each device are sorted in chronological order, and when a failure occurs in a specific equipment, if a failure occurs in a specific equipment within 5 minutes from the time of occurrence, it is defined that the failure occurs simultaneously. After configuring the sequence for the devices that have failed at the same time, 5 devices that frequently occur simultaneously within the configured sequence were selected, and the case where the selected devices failed at the same time was confirmed through visualization. Since the server resource information collected for failure analysis is in units of time series and has flow, we used Long Short-term Memory (LSTM), a deep learning algorithm that can predict the next state through the previous state. In addition, unlike a single server, the Hierarchical Attention Network deep learning model structure was used in consideration of the fact that the level of multiple failures for each server is different. This algorithm is a method of increasing the prediction accuracy by giving weight to the server as the impact on the failure increases. The study began with defining the type of failure and selecting the analysis target. In the first experiment, the same collected data was assumed as a single server state and a multiple server state, and compared and analyzed. The second experiment improved the prediction accuracy in the case of a complex server by optimizing each server threshold. In the first experiment, which assumed each of a single server and multiple servers, in the case of a single server, it was predicted that three of the five servers did not have a failure even though the actual failure occurred. However, assuming multiple servers, all five servers were predicted to have failed. As a result of the experiment, the hypothesis that there is an effect between servers is proven. As a result of this study, it was confirmed that the prediction performance was superior when the multiple servers were assumed than when the single server was assumed. In particular, applying the Hierarchical Attention Network algorithm, assuming that the effects of each server will be different, played a role in improving the analysis effect. In addition, by applying a different threshold for each server, the prediction accuracy could be improved. This study showed that failures that are difficult to determine the cause can be predicted through historical data, and a model that can predict failures occurring in servers in data centers is presented. It is expected that the occurrence of disability can be prevented in advance using the results of this study.