• 한국사회복지학회:학술대회논문집
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• 2003.10a
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• pp.185-216
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• 2003

This study was aimed at investigating important factors influencing career success among regular workers. The current researcher scrutinized the degree to which variables and factors affect the career success and occupational turnover rates of the research participants. At the same tune, two hypothetical path models established by the researcher were examined using linear multiple regression methods and the LISREL. After examining the differences among the factors of career success, a comparison was made between the disabled worker group and the non-disabled worker group. A questionnaire using the 5-point Likert scale was distributed to a group of 374 workers with disabilities and 463 workers without disabilities. For the data analysis purpose, the structural equation model, factor analysis, correlation analysis, and multiple regression analysis were carried out. The results of this study ran be summarized as follows. First, the results of factor analysis showed important categories of conceptual themes of career success. The initial conceptual factor model did not accord with the empirical one. A three-factorial model revealed categories of personal, family, and organizational factor respectively. The personal factor was composed of the self-esteem and self-efficiency. The family factor was consisted of the multi-roles stress and the number of children. Finally, the organizational factor was composed of the capacity for utilizing resources, networking, and the frequency of mentoring. In addition, the total 10 sub areas of career success were divided by two important aspects; the subjective career success and the objective career success. Second, both research participant groups seemed to be influenced by their occupational types. However, all predictive variables excluding the wage rate and the average length of work years had significant impact on job success for the disabled work group, while all the variables excluding the frequency of advice and length of working years had significant impact on job success for the non-disabled worker group. Third, the turnover rate was significantly influenced by the age and the experience of turnover of the research participants. However, the number of co-workers was the strongest predictive variable for the worker group with disabilities, but the occupation choice variable for the worker group without disabilities. For the disabled worker group, the turnover rate was differently influenced by the type of occupation, the length of working years, while multi-role stress and the average working years at the time of turnover for the worker group without disabilities. Fifth, as a result of verifying the hypothetical path model, it showed that the first model was somewhat proper and could predict the career success on both research participant groups. In the second model, the Chi-square, the degree of freedom (($x^2=64.950$, df=61, P=0.341), and the adjusted Goodness of Fit Index (AGFI) were .964, and the Comparative Fit Index (CFI) were .997, and the Root Mean Squared Residual (RMR) was respectively. .038. The model was best fitted and could predict the career success more highly because the goodness of fit index in the whole models was within the allowed range. In conclusion, the following research implications can be suggested. First, the occupational type of research participants was one of the most important variables to predict the career success for both research participant groups. It means that people with disabilities require human development services including education. They need to improve themselves in this knowledge-based society. Furthermore, for maintaining the career success, people with disabilities should be approached by considering the subjective career success aspects including wages and the promotion opportunities than the objective career success aspects.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.1
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• pp.40-53
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• 2015

To train the manpower to meet the requirements of the industrial field, the introduction of the National Qualification Frameworks(hereinafter referred to as NQF) was determined in 2001 by National Competency Standards(hereinafter referred to as NCS) centrally of the Office for Government Policy Coordination. Also, for landscape architecture in the construction field, the "NCS -Landscape Architecture" pilot was developed in 2008 to be test operated for 3 years starting in 2009. Especially, as the 'realization of a competence-based society, not by educational background' was adopted as one of the major government projects in the Park Geun-Hye government(inaugurated in 2013) the NCS system was constructed on a nationwide scale as a detailed method for practicing this. However, in the case of the NCS developed by the nation, the ideal job performing abilities are specified, therefore there are weaknesses of not being able to reflect the actual operational problem differences in the student level between universities, problems of securing equipment and professors, and problems in the number of current curricula. For soft landing to practical curriculum, the process of clearly analyzing the gap between the current curriculum and the NCS must be preceded. Gap analysis is the initial stage methodology to reorganize the existing curriculum into NCS based curriculum, and based on the ability unit elements and performance standards for each NCS ability unit, the discrepancy between the existing curriculum within the department or the level of coincidence used a Likert scale of 1 to 5 to fill in and analyze. Thus, the universities wishing to operate NCS in the future measuring the level of coincidence and the gap between the current university curriculum and NCS can secure the basic tool to verify the applicability of NCS and the effectiveness of further development and operation. The advantages of reorganizing the curriculum through gap analysis are, first, that the government financial support project can be connected to provide quantitative index of the NCS adoption rate for each qualitative department, and, second, an objective standard is provided on the insufficiency or sufficiency when reorganizing to NCS based curriculum. In other words, when introducing in the subdivisions of the relevant NCS, the insufficient ability units and the ability unit elements can be extracted, and the supplementary matters for each ability unit element per existing subject can be extracted at the same time. There is an advantage providing directions for detailed class program and basic subject opening. The Ministry of Education and the Ministry of Employment and Labor must gather people from the industry to actively develop and supply the NCS standard a practical level to systematically reflect the requirements of the industrial field the educational training and qualification, and the universities wishing to apply NCS must reorganize the curriculum connecting work and qualification based on NCS. To enable this, the universities must consider the relevant industrial prospect and the relation between the faculty resources within the university and the local industry to clearly select the NCS subdivision to be applied. Afterwards, gap analysis must be used for the NCS based curriculum reorganization to establish the direction of the reorganization more objectively and rationally in order to participate in the process evaluation type qualification system efficiently.

• The Korean Society of Law and Medicine
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• v.16 no.2
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• pp.87-130
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• 2015

In a case in which National Health Insurance Corporation (NHIC) pays medical care expenses to a victim of a traffic accident resulting in injury or death and asks the assailant for compensation of its share in the medical care expenses, as the precedent treats the subrogation of a claim set by National Health Insurance Act the same as that set by Industrial Accident Compensation Insurance Act, it draws the range of its compensation from the range of deduction, according to the principle of deduction after offsetting and acknowledges the compensation of all medical care expenses borne by the NHIC, within the amount of compensation claimed by the victim. However, both the National Health Insurance Act and the Industrial Accident Compensation Insurance Act are laws that regulate social insurance, but medical care expenses in the National Health Insurance Act have a character of 'an underinsurance that fixes the ratio of indemnification,' while insurance benefit on the Industrial Accident Compensation Insurance Act has a character of full insurance, or focuses on helping the insured that suffered an industrial accident lead a life, approximate to that in the past, regardless of the amount of damages according to its character of social insurance. Therefore, there is no reason to treat the subrogation of a claim on the National Health Insurance Act the same as that on the Industrial Accident Compensation Insurance Act. Since the insured loses the right of claim acquired by the insurer by subrogation in return for receiving a receipt, there is no benefit from receiving insurance in the range. Thus, in a suit in which the insured seeks compensation for damages from the assailant, there is no room for the application of the legal principle of offset of profits and losses, and the range of subrogation of a claim or the amount of deduction from compensation should be decided by the contract between the persons directly involved or a related law. Therefore, it is not reasonable that the precedent draws the range of the NHIC's compensation from the principle of deduction after offsetting. To interpret Clause 1, Article 58 of the National Health Insurance Act that sets the range of the NHIC's compensation uniformly and systematically in combination with Clause 2 of the same article that sets the range of exemption, if the compensation is made first, it is reasonable to fix the range of the NHIC's compensation by multiplying the medical care expenses paid by the ratio of the assailant's liability. This is contrasted with the range of the Korea Labor Welfare Corporation's compensation which covers the total amount of the claim of the insured within the insurance benefit paid in the interpretation of Clauses 1 and 2, Article 87 of the Industrial Accident Compensation Insurance Act. In the meantime, there are doubts about why the profit should be deducted from the amount of compensation claimed, though it is enough for the principle of deduction after offsetting that the precedent took as the premise in judging the range of the NHIC's compensation to deduct the profit made by the victim from the amount of damages, so as to achieve the goal of not attributing profit more than the amount of damage to a victim; whether it is reasonable to attribute all the profit made by the victim to the assailant, while the damages suffered by the victim are distributed fairly; and whether there is concrete validity in actual cases. Therefore, the legal principle of the precedent concerning the range of the NHIC's compensation and the legal principle of the precedent following the principle of deduction after offsetting should be reconsidered.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.231-252
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• 2021

Artificial intelligence (AI) is a key technology that will change the future the most. It affects the industry as a whole and daily life in various ways. As data availability increases, artificial intelligence finds an optimal solution and infers/predicts through self-learning. Research and investment related to automation that discovers and solves problems on its own are ongoing continuously. Automation of artificial intelligence has benefits such as cost reduction, minimization of human intervention and the difference of human capability. However, there are side effects, such as limiting the artificial intelligence's autonomy and erroneous results due to algorithmic bias. In the labor market, it raises the fear of job replacement. Prior studies on the utilization of artificial intelligence have shown that individuals do not necessarily use the information (or advice) it provides. Algorithm error is more sensitive than human error; so, people avoid algorithms after seeing errors, which is called "algorithm aversion." Recently, artificial intelligence has begun to be understood from the perspective of the augmentation of human intelligence. We have started to be interested in Human-AI collaboration rather than AI alone without human. A study of 1500 companies in various industries found that human-AI collaboration outperformed AI alone. In the medicine area, pathologist-deep learning collaboration dropped the pathologist cancer diagnosis error rate by 85%. Leading AI companies, such as IBM and Microsoft, are starting to adopt the direction of AI as augmented intelligence. Human-AI collaboration is emphasized in the decision-making process, because artificial intelligence is superior in analysis ability based on information. Intuition is a unique human capability so that human-AI collaboration can make optimal decisions. In an environment where change is getting faster and uncertainty increases, the need for artificial intelligence in decision-making will increase. In addition, active discussions are expected on approaches that utilize artificial intelligence for rational decision-making. This study investigates the impact of artificial intelligence on decision-making focuses on human-AI collaboration and the interaction between the decision maker personal traits and advisor type. The advisors were classified into three types: human, artificial intelligence, and human-AI collaboration. We investigated perceived usefulness of advice and the utilization of advice in decision making and whether the decision-maker's personal traits are influencing factors. Three hundred and eleven adult male and female experimenters conducted a task that predicts the age of faces in photos and the results showed that the advisor type does not directly affect the utilization of advice. The decision-maker utilizes it only when they believed advice can improve prediction performance. In the case of human-AI collaboration, decision-makers higher evaluated the perceived usefulness of advice, regardless of the decision maker's personal traits and the advice was more actively utilized. If the type of advisor was artificial intelligence alone, decision-makers who scored high in conscientiousness, high in extroversion, or low in neuroticism, high evaluated the perceived usefulness of the advice so they utilized advice actively. This study has academic significance in that it focuses on human-AI collaboration that the recent growing interest in artificial intelligence roles. It has expanded the relevant research area by considering the role of artificial intelligence as an advisor of decision-making and judgment research, and in aspects of practical significance, suggested views that companies should consider in order to enhance AI capability. To improve the effectiveness of AI-based systems, companies not only must introduce high-performance systems, but also need employees who properly understand digital information presented by AI, and can add non-digital information to make decisions. Moreover, to increase utilization in AI-based systems, task-oriented competencies, such as analytical skills and information technology capabilities, are important. in addition, it is expected that greater performance will be achieved if employee's personal traits are considered.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.55-78
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• 2021

Tosolve complex and diverse social problems and ensure the quality of life of individuals, social robots that can interact with humans are attracting attention. In the past, robots were recognized as beings that provide labor force as they put into industrial sites on behalf of humans. However, the concept of today's robot has been extended to social robots that coexist with humans and enable social interaction with the advent of Smart technology, which is considered an important driver in most industries. Specifically, there are service robots that respond to customers, the robots that have the purpose of edutainment, and the emotionalrobots that can interact with humans intimately. However, popularization of robots is not felt despite the current information environment in the modern ICT service environment and the 4th industrial revolution. Considering social interaction with users which is an important function of social robots, not only the technology of the robots but also other factors should be considered. The design elements of the robot are more important than other factors tomake consumers purchase essentially a social robot. In fact, existing studies on social robots are at the level of proposing "robot development methodology" or testing the effects provided by social robots to users in pieces. On the other hand, consumer emotions felt from the robot's appearance has an important influence in the process of forming user's perception, reasoning, evaluation and expectation. Furthermore, it can affect attitude toward robots and good feeling and performance reasoning, etc. Therefore, this study aims to verify the effect of appearance of social robot and consumer emotions on consumer's attitude toward social robot. At this time, a social robot design evaluation model is constructed by combining heterogeneous data from different sources. Specifically, the three quantitative indicator data for the appearance of social robots from the ABOT Database is included in the model. The consumer emotions of social robot design has been collected through (1) the existing design evaluation literature and (2) online buzzsuch as product reviews and blogs, (3) qualitative interviews for social robot design. Later, we collected the score of consumer emotions and attitudes toward various social robots through a large-scale consumer survey. First, we have derived the six major dimensions of consumer emotions for 23 pieces of detailed emotions through dimension reduction methodology. Then, statistical analysis was performed to verify the effect of derived consumer emotionson attitude toward social robots. Finally, the moderated regression analysis was performed to verify the effect of quantitatively collected indicators of social robot appearance on the relationship between consumer emotions and attitudes toward social robots. Interestingly, several significant moderation effects were identified, these effects are visualized with two-way interaction effect to interpret them from multidisciplinary perspectives. This study has theoretical contributions from the perspective of empirically verifying all stages from technical properties to consumer's emotion and attitudes toward social robots by linking the data from heterogeneous sources. It has practical significance that the result helps to develop the design guidelines based on consumer emotions in the design stage of social robot development.

• Korean Journal of Animal Reproduction
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• v.24 no.1
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• pp.1-18
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• 2000

Eighty dairy farms in Palmers ton North area in New Zealand were surveyed on 1) general characteristics (10 Questions), 2) milk yield and feed supplementary (7 questions), 3) reproductive efficiencies (12 questions) and 4) reproductive disorders (12 questions) by mail questions from February to July, 1998. Among those 4 items from 38 dairy farms (47.5%), especially in items 1) and 2), overall dairy farming situation, supplementary feeding and milk yields were surveyed and analyzed for Korean dairy farmers (especially in Cheju island) to have better understanding or higher economical gains. The results were as follows. 1. In dairy experience, 21 (45%) among 38 dairy farms surveyed were answered that farming less than 15 years, 15~19 year, 20~25 years and over 26 years experience were 3 (7.9%), 7 (18.4%), 6 (15.8%) and 5 (13.2%) which generally showed longer experience compare to Korean dairy farming situation. In survey of labour input and business goal of dairy farming, self-managing farms, sharemilkers, unpaid family manpowering farms, manager running farms, farms with hired worker, farms with part time helper and other type was 21 (55.3%), 10 (26.3%), 2 (3.5%), 3 (5.3%), 18 (31.6%), 2 (3.5%), and 1 (1.8%), respectively. 2. Analyzing pasture and tillable land, pasture according to feeding scale (200, 300 and 400 heads) were 56, 90 and 165.3 ha, and tillable lands were 51, 78 and 165 ha which showed some differences among feeding scale. In recording methods in 38 farms replied, 36 (95%) dairy handbook and 23 (70%) dual methods taking farms were higher than that of 10 (26.3%) computer and 15(39.5%) well-recorder methods. 3. Dairy waste processing facilities in environmental field were almost perfect except of metropolitan area, and so no problem was developed in its control so far. Hence, 26 farm (68.4%) of pond system was higher rather than those in 8 (21.2%) of using as organic manure after storing feces of dairy cattle, 1(2.6%) bunker system and 3 (7.9%) other type farms. 4. In milking facilities, 33 farms (86.9%) of Harringbone types were higher than those in 3 (7.9%) of Walkthrough types, 1 (2.6%) of Rotary system and other types. Although the construction facilities was not enough, this system show the world-leveled dairy country to attempted to elevate economic gains using the advantage of climatic condition. 5. In milking day and yearly yield per head, average 275 milking days and 87 drying days were longer than that of 228 average milking days in New Zealand. Annual total milk yield per head and milk solid (ms) was 3,990 kg and approximately 319 kg. Dairy milk solid (ms) per head, milk yield, fat percentage was 1.2 kg, 15.5 kg and average 4.83% which was much higher than in other country, and milk protein was average 3.75%. 6. In coclusion, Palmerstone North has been a center of dairy farming in New Zealand for the last 21 years. Their dairy farming history is 6~9 year longer than ours and the average number of milking cows per farm is 355, which is much greater than that (35) of Korea. They do not have dairy barn, but only milking parlors. Cows are taken care of by family 0.5 persons), are on a planned calving schedule in spring (93%) and milked for 240~280 days a year, avoiding winter. Cows are dried according to milk yield and body condition score. This management system is quite different from that of Korean dairy farms. Cows are not fed concentrates, relying entirely on pasture forages and the average milk yield per cow is 3,500 kg, which is about 1/2 milk yield of Korean dairy farms. They were bred to produce high fat milk with an average of 4.5%. Their milk production cost is the lowest in the world and the country's economy relies heavily on milk production. We Korean farmers may try to increase farming size, decreasing labor and management costs.

• Journal of the Korean Society of Food Science and Nutrition
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• v.37 no.6
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• pp.729-737
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• 2008

The purposes of this study were to investigate supporting status and subsidy for school food service and to analyze the perception of school food service officials at the educational board on using rice bread to the school food service menu. The questionnaire was developed by content analysis, situation analysis, in-depth interview and checked by the school food service officials at the educational board. The questionnaires were responded by 33 officials (respondent rate: 86.8%) during September 1 to October 26 in 2007. The major findings of this study were as follows: First, most of the respondents were women (93.9%), and worked an average of 104.36 months at school-related work. The metropolitan & provincial office of education had prevalently jurisdiction over 272.3 rural and self-operation type of elementary schools, 115.50 rural and self-operation type of middle schools and 73.0 rural and self-operation type of high schools. In the case of the district office of education, 23.3 urban and self-operation type of elementary schools, 11.6 urban and self-operation type of middle schools and 5.3 urban and contracted type of high schools were averagely managed. Second, all the respondents supported meal cost for low-income group and 50.5% provided reimbursement for organic environmental agricultural products. The highest subsidy was 16.8 billion won as meal cost for low-income group in metropolitan & provincial office and 1,050 million won as labor cost in district office. Third, the experience of performing policies for using rice was relatively lower than perception of rice bread application to school food service menu. Fourth, the advantages of using rice bread were acceleration of consuming rice (32.0%), excellence of nutrition (24.0%) and promotion of healthy image (22.7%). On the other hand, the difficulties of using rice bread were lack of facilities (72.7%), higher cost compared to wheat bread (54.5%), limitation of menu application and cooking method (15.7% each). Fifth, the opinion of utilizing rice and that of applying rice bread were significantly correlated (p<0.001). Desirability and willingness were correlated with reality for applying rice bread to the school food service menu (p<0.001). Also, comparative analysis between divided groups by perception of utilizing rice showed that willingness and experience were significantly different.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.3
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• pp.89-98
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• 1965

The experimental studies were intended to clarify the effects of selection, and also aimed at estimating the heritabilities, the genotypic correlations among some agronomic characters, and at calculating the selection index on some selective characters for the selection of desirable lines, under different climatic conditions. Finally practical implications of these studies, especially on the selection index, were discussed. Twenty-two varieties, determinate growing habit type, were selected at random from the 138 soybean varieties cultivated the year before, were grown in a randomized block design with three replicates at Chinju, Korea, under May and June sowing conditions. The method of estimating heritabilities for the eleven agronomic characters-flowering date, maturity date, stem length, branch numbers per plant, stem diameter, plant weight, pod numbers per plant, grain numbers per plant and 100 grain weight, shown in Table 3, was the variance components procedures in a replicated trial for the varieties. The analysis of covariance was used to obtain the genotypic correlations and phenotypic correlations among the eight characters, and the selection indexes for some agronomic characters were calculated by Robinson's method. The results are summarized as follows: Heritabilities : The experiment on the genotype-environment interaction revealed that in almost all of the characters investigated the interaction was too large to be neglected and materially affected the estimates of various genotypic parameters. The variation in heritability due to the change of environments was larger in the characters of low heritability than in those of high heritability. Heritability values of flowering date, fruiting period (days from flowering to maturity), stem length and 100 grain weight were the highest in both environments, those of yield(grain weight) and other characters were showed the lower values(Table 3). These heritability values showed a decreasing trend with the delayed sowing in the experiments. Further, all calculated heritability values were higher than anticipated. This was expected since these values, which were the broad sense heritability, contain the variance due to dominance and epistasisf in addition to the additive genetic variance. Genotypic correlations : Genotypic correlations were slightly higher than the corresponding phenotypic correlations in both environments, but the variation in values due to the change of environment appeared between grain weight and some other characters, especially an increase between grain weight and flowering date, and the total growing period(Table 6). Genotypic correlations between grain weight and other characters indicated that high seed yield was genetically correlated with late flowering, late maturity, and the other five characters namely branch numbers per plant, stem diameter, plant weight, pod numbers per plant and grain numbers per plant, but not with 100 grain weight of soybeans. Pod numbers and grain numbers per plant were more closely correlated with seed yields than with other characters. Selection index : For the comparison and the use of selection indexes in the selection, two kinds of selection indexes were calculated, the former was called selection index A and the later selection index B as shown in Table 7. Selection index A was calculated by the values of grain weight per plant as the character of yield(character Y), but the other, selection index B, was calculated by the values of pod numbers per plant, instead of grain weight per plant, as the character of yield'(character Y'). These results suggest that selection index technique is useful in soybean breeding. In reality, however, as the selection index varies with population and environment, it must be calculated in each population to which selection is applied and in each environment in which the population is located. In spite of the expected usefulness of selection index technique in soybean breeding, unsolved problems such as the expense, time and labor involved in calculating the selection index remain. For these reasons and from these experimental studies, it was recognized that in the breeding of self-fertilized soybean plants the selection for yield should be based on a more simple selection index such as selection index B of these experiments rather than on the complex selection index such as selection index A. Furthermore, it was realized that the selection index for the selection should be calculated on the basis of the data of some 3-4 agronomic characters-maturity date(X$_1$), branch numbers per plant(X$_2$), stem diameter(X$_3$) and pod numbers per plant etc. It must be noted that it should be successful in selection to select for maturity date(X$_1$) which has high heritability, and the selection index should be calculated easily on the basis of the data of branch numbers per plant(X$_2$), stem diameter(X$_3$) and pod numbers per plant, directly after the harvest before drying and threshing. These characters should be very useful agronomic characters in the selection of Korean soybeans, determinate growing habit type, as they could be measured or counted easily thus saving time and expense in the duration from harvest to drying and threshing, and are affected more in soybean yields than the other agronomic characters.

• Korean small business review
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• v.32 no.1
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• pp.65-87
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• 2010

With the advent of knowledge-based society, the revitalization of technological innovation type SMEs, termed "inno-biz" hereafter, has been globally recognized as a government policymakers' primary concern in strengthening national competitiveness, and much effort is being put into establishing polices of boosting the start-ups and innovation capability of SMEs. Especially, in that the inno-biz enables national economy to get vitalized by widening world markets with its superior technology, and thus, taking the initiative of extremely competitive world markets, its growth and development has greater significance. In the case of Korea, the government has been maintaining the policies since the late 1990s of stimulating the growth of SMEs as well as building various infrastructures to foster the start-ups of the SMEs such as venture businesses with high technology. In addition, since the enactment of "Innovation Promotion Law for SMEs" in 2001, the government has been accelerating the policies of prioritizing the growth and development of inno-biz. So, for the sound growth and development of Korean inno-biz, this paper intends to offer effective management strategies for SMEs and suggest proper policies for the government, by researching into the effect of technological innovation capability and technology commercialization capability as the primary business resources on business performance in Korean SMEs in the light of market information orientation. The research is carried out on Korean companies characterized as inno-biz. On the basis of OSLO manual and prior studies, the research categorizes their status. R&D capability, technology accumulation capability and technological innovation system are categorized into technological innovation capability; product development capability, manufacturing capability and marketing capability into technology commercialization capability; and increase in product competitiveness and merits for new technology and/or product development into business performance. Then the effect of each component on business performance is substantially analyzed. In addition, the mediation effect of technological innovation and technology commercialization capability on business performance is observed by the use of the market information orientation as a parameter. The following hypotheses are proposed. H1 : Technology innovation capability will positively influence business performance. H1-1 : R&D capability will positively influence product competitiveness. H1-2 : R&D capability will positively influence merits for new technology and/or product development into business performance. H1-3 : Technology accumulation capability will positively influence product competitiveness. H1-4 : Technology accumulation capability will positively influence merits for new technology and/or product development into business performance. H1-5 : Technological innovation system will positively influence product competitiveness. H1-6 : Technological innovation system will positively influence merits for new technology and/or product development into business performance. H2 : Technology commercializing capability will positively influence business performance. H2-1 : Product development capability will positively influence product competitiveness. H2-2 : Product development capability will positively influence merits for new technology and/or product development into business performance. H2-3 : Manufacturing capability will positively influence product competitiveness. H2-4 : Manufacturing capability will positively influence merits for new technology and/or product development into business performance. H2-5 : Marketing capability will positively influence product competitiveness. H2-6 : Marketing capability will positively influence merits for new technology and/or product development into business performance. H3 : Technology innovation capability will positively influence market information orientation. H3-1 : R&D capability will positively influence information generation. H3-2 : R&D capability will positively influence information diffusion. H3-3 : R&D capability will positively influence information response. H3-4 : Technology accumulation capability will positively influence information generation. H3-5 : Technology accumulation capability will positively influence information diffusion. H3-6 : Technology accumulation capability will positively influence information response. H3-7 : Technological innovation system will positively influence information generation. H3-8 : Technological innovation system will positively influence information diffusion. H3-9 : Technological innovation system will positively influence information response. H4 : Technology commercialization capability will positively influence market information orientation. H4-1 : Product development capability will positively influence information generation. H4-2 : Product development capability will positively influence information diffusion. H4-3 : Product development capability will positively influence information response. H4-4 : Manufacturing capability will positively influence information generation. H4-5 : Manufacturing capability will positively influence information diffusion. H4-6 : Manufacturing capability will positively influence information response. H4-7 : Marketing capability will positively influence information generation. H4-8 : Marketing capability will positively influence information diffusion. H4-9 : Marketing capability will positively influence information response. H5 : Market information orientation will positively influence business performance. H5-1 : Information generation will positively influence product competitiveness. H5-2 : Information generation will positively influence merits for new technology and/or product development into business performance. H5-3 : Information diffusion will positively influence product competitiveness. H5-4 : Information diffusion will positively influence merits for new technology and/or product development into business performance. H5-5 : Information response will positively influence product competitiveness. H5-6 : Information response will positively influence merits for new technology and/or product development into business performance. H6 : Market information orientation will mediate the relationship between technology innovation capability and business performance. H7 : Market information orientation will mediate the relationship between technology commercializing capability and business performance. The followings are the research results : First, as for the effect of technological innovation on business performance, the technology accumulation capability and technological innovating system have a positive effect on increase in product competitiveness and merits for new technology and/or product development, while R&D capability has little effect on business performance. Second, as for the effect of technology commercialization capability on business performance, the effect of manufacturing capability is relatively greater than that of merits for new technology and/or product development. Third, the mediation effect of market information orientation is identified to exist partially in information generation, information diffusion and information response. Judging from these results, the following analysis can be made : On Increase in product competitiveness, directly related to successful technology commercialization of technology, management capability including technological innovation system, manufacturing capability and marketing capability has a relatively strong effect. On merits for new technology and/or product development, on the other hand, capability in technological aspect including R&D capability, technology accumulation capability and product development capability has relatively strong effect. Besides, in the cast of market information orientation, the level of information diffusion within an organization plays and important role in new technology and/or product development. Also, for commercial success like increase in product competitiveness, the level of information response is primarily required. Accordingly, the following policies are suggested : First, as the effect of technological innovation capability and technology commercialization capability on business performance differs among SMEs; in order for SMEs to secure competitiveness, the government has to establish microscopic policies for SMEs which meet their needs and characteristics. Especially, the SMEs lacking in capital and labor are required to map out management strategies of focusing their resources primarily on their strengths. And the government needs to set up policies for SMEs, not from its macro-scaled standpoint, but from the selective and concentrative one that meets the needs and characteristics of respective SMEs. Second, systematic infrastructures are urgently required which lead technological success to commercial success. Namely, as technological merits at respective SME levels do not always guarantee commercial success, the government should make and effort to build systematic infrastructures including encouragement of M&A or technology trade, systematic support for protecting intellectual property, furtherance of business incubating and industrial clusters for strengthening academic-industrial network, and revitalization of technology financing, in order to make successful commercialization from technological success. Finally, the effort to innovate technology, R&D, for example, is essential to future national competitiveness, but its result is often prolonged. So the government needs continuous concern and funding for basic science, in order to maximize technological innovation capability. Indeed the government needs to examine continuously whether technological innovation capability or technological success leads satisfactorily to commercial success in market economic system. It is because, when the transition fails, it should be left to the government.