• Journal of Distribution Science
• /
• v.8 no.3
• /
• pp.27-35
• /
• 2010

As the population, buying power, and intensity of self-expression of the elderly generation increase, its importance as a market segment is also growing. Therefore, the mass marketing strategy for the elderly generation must be changed to a micro-marketing strategy based on the results of sub-segmentation that suitably captures the characteristics of this generation. Furthermore, as a customer access strategy is decided by sub-segmentation, proper segmentation is one of the key success factors for micro-marketing. Segments or sub-segments are different from sectors, because segmentation or sub-segmentation for micro-marketing is based on the homogeneity of customer needs. Theoretically, complete segmentation would reveal a single voice. However, it is impossible to achieve complete segmentation because of economic factors, factors that affect effectiveness, etc. To obtain a single voice from a segment, we sometimes need to divide it into many individual cases. In such a case, there would be a many segments to deal with. On the other hand, to maximize market access performance, fewer segments are preferred. In this paper, we use the term "sub-segmentation" instead of "segmentation," because we divide a specific segment into more detailed segments. To sub-segment the elderly generation, this paper takes their lifestyles and life stages into consideration. In order to reflect these aspects, various surveys and several rounds of expert interviews and focused group interviews (FGIs) were performed. Using the results of these qualitative surveys, we can define six sub-segments of the elderly generation. This paper uses five rules to divide the elderly generation. The five rules are (1) mutually exclusive and collectively exhaustive (MECE) sub-segmentation, (2) important life stages, (3) notable lifestyles, (4) minimum number of and easy classifiable sub-segments, and (5) significant difference in voices among the sub-segments. The most critical point for dividing the elderly market is whether children are married. The other points are source of income, gender, and occupation. In this paper, the elderly market is divided into six sub-segments. As mentioned, the number of sub-segments is a very key point for a successful marketing approach. Too many sub-segments would lead to narrow substantiality or lack of actionability. On the other hand, too few sub-segments would have no effects. Therefore, the creation of the optimum number of sub-segments is a critical problem faced by marketers. This paper presents a method of evaluating the fitness of sub-segments that was deduced from the preceding surveys. The presented method uses the degree of homogeneity (DoH) to measure the adequacy of sub-segments. This measure uses quantitative survey questions to calculate adequacy. The ratio of significantly homogeneous questions to the total numbers of survey questions indicates the DoH. A significantly homogeneous question is defined as a question in which one case is selected significantly more often than others. To show whether a case is selected significantly more often than others, we use a hypothesis test. In this case, the null hypothesis (H0) would be that there is no significant difference between the selection of one case and that of the others. Thus, the total number of significantly homogeneous questions is the total number of cases in which the null hypothesis is rejected. To calculate the DoH, we conducted a quantitative survey (total sample size was 400, 60 questions, 4~5 cases for each question). The sample size of the first sub-segment-has no unmarried offspring and earns a living independently-is 113. The sample size of the second sub-segment-has no unmarried offspring and is economically supported by its offspring-is 57. The sample size of the third sub-segment-has unmarried offspring and is employed and male-is 70. The sample size of the fourth sub-segment-has unmarried offspring and is not employed and male-is 45. The sample size of the fifth sub-segment-has unmarried offspring and is female and employed (either the female herself or her husband)-is 63. The sample size of the last sub-segment-has unmarried offspring and is female and not employed (not even the husband)-is 52. Statistically, the sample size of each sub-segment is sufficiently large. Therefore, we use the z-test for testing hypotheses. When the significance level is 0.05, the DoHs of the six sub-segments are 1.00, 0.95, 0.95, 0.87, 0.93, and 1.00, respectively. When the significance level is 0.01, the DoHs of the six sub-segments are 0.95, 0.87, 0.85, 0.80, 0.88, and 0.87, respectively. These results show that the first sub-segment is the most homogeneous category, while the fourth has more variety in terms of its needs. If the sample size is sufficiently large, more segmentation would be better in a given sub-segment. However, as the fourth sub-segment is smaller than the others, more detailed segmentation is not proceeded. A very critical point for a successful micro-marketing strategy is measuring the fit of a sub-segment. However, until now, there have been no robust rules for measuring fit. This paper presents a method of evaluating the fit of sub-segments. This method will be very helpful for deciding the adequacy of sub-segmentation. However, it has some limitations that prevent it from being robust. These limitations include the following: (1) the method is restricted to only quantitative questions; (2) the type of questions that must be involved in calculation pose difficulties; (3) DoH values depend on content formation. Despite these limitations, this paper has presented a useful method for conducting adequate sub-segmentation. We believe that the present method can be applied widely in many areas. Furthermore, the results of the sub-segmentation of the elderly generation can serve as a reference for mature marketing.

• Health Policy and Management
• /
• v.14 no.1
• /
• pp.65-88
• /
• 2004

In general, empowerment is defined as the motivational concept of autonomy and self-efficacy. Recently, the concept of empowerment is applied to improve organizational staff's job satisfaction and organizational commitment in many organizations. Empower-ment in service organizations, i.e., hospitals, has certainly generated more publicity than any other organizations. The objectives of this study are, first, to measure the degree of hospital employees' empowerment using Spreitzer(1995)'s empowerment theory, second, to analyze the causal relationship of organizational and job characteristics, a degree of empowerment, and organizational performance(job satisfaction and organizational commitment), and third, to offer the strategy for the improvement of job satisfaction and organizational commitment. Spreitzer insists that the empowerment is composed of 4 dimensions(meaning, competence, self-determination, and impact). And he argues that various work-related characteristics is a direct cause of empowerment and the indirect cause of job satisfaction and organizational commitment, mediated by the empowerment latent variable. In order to perform this study, data were collected by self-administered questionnaires from hospital employees working in administrative department of 3 university hospitals in Inchon and Kyunggi-Do region. The number of cases is 181(response rate; 86%). The Collected data were analyzed with SPSS Ver. 10.0 and AMOSV Ver. 4.0. First, to test validity of variables, the factor analysis was used. Second, to test reliability, Cronbach's alpha coefficients was calculated. Cronbach's alpha of empowerment variable is 0.8323 showing that there's no problem in regard to the internal consistency. Also the Cronbach's alpha of other variables are 0.8301 of the degree of perceived control, 0.6705 of job characteristics, O.8787 of compensation, 0.9254 of job satisfaction, and 0.8389 of organizational commitment, respectively. Among the questions of job characteristics, two survey questions are deleted due to lowering the reliability. Third, to test multicollinearity and correlation of variables, the correlation analysis was performed. There was no problem of multicollinearity. Finally structural equation modelling (SEM) analysis was conducted to find the causal relationship of organizational and job Characteristics, empowerment, job satisfaction and organizational commitment. The 16 variables are included for the SEM analysis. The major results of this study are as follows: First, in the case of model fitness, the condition of x$^2$ statistic(92.187) is not fully satisfied, but the indices of GFI(0.912), AGFI(0.863), NFI(0.917) and CFI(0.928) are partially satisfied, which needs to upper 0.90. Second, in the result of hypotheses testing, all hypotheses are accepted and have a positive effect in 95% or 99% confidence interval(P<0.05 or P<0.001) except the effect of compensation variable on empowerment(P=0.082). Third, in regard to the direct, indirect, and total effect of variables, the direct effect of perceived control, task characteristics, and compensation on job satisfaction are 0.728, 2.264, 0.328 and on organizational commitment are 0.094, 1.411, 0.418, respectively. Also the indirect effect of perceived control, task characteristics, and compensation on job satisfaction are 0.311, 0.196, 0.028 and on organizational commitment are 0.210, 0.132, 0.019, respectively. Thus, these findings imply that various work-related factors are direct effect of empowerment and indirect effect of result variables, job satisfaction and organizational commitment. Also These results showed that the workplace empowerment is significant mediating factor of employee's job satisfaction and organizational commitment.

• Fire Science and Engineering
• /
• v.15 no.3
• /
• pp.21-35
• /
• 2001

By rearing private experts to design hazardous facilities, Safety property is obstained. So it is necessary to limit within the designer of hazardous materials facilities who has some degree skill. After permission progress about the inspection of the design ascertain whether it is safety property Mayor/Do governor permits within the laws and their qualification. Accordingly, Korea Fire Equipment Inspection Corporation be come specialization about the design, inspection of construction completion. A inquire purpose of Fire Service Act be considered fitness. Subject by which the Korea Fire Equipment Inspection Corporation is entrusted, subject by which the a non-probit corporation in The Civil Law be possible to entrusted in separate. In this case, because of the level of one's technique and facilities are important, to limit as a nonprobit corporation in The Civil Law give rise to trouble. Consequently; established a business corporation, which the level of one's technique and facilities, in accordance with The Commercial Law can assign inspection of construction completion. The contents of the Fire Services Act is caused by the historic growth of hazardous facilities's safety management. Because we decide on a course about completed inspection of hazardous substance, it is needed that adjust the task performed by a corporation of the exert skill and the duty performed by the task that a authorized corporation on the civil law or the commercial law To adjust the duty, the Fire Service Act, that is suitable to the purpose and principle, should constitute a measure of the duty. With the object of insure the safety of the hazardous substance, when the fire survice act establish a corporation of the expert skill. There is the will of lawmakers that need organization to have the power of the professional technology. The state excise the will that insure the safety of hazardous materials facilities on the basis of the professional technology and facilities, and construct to establish a corporation of the expert skill. Therefore as concentrate on the technology to need to insure the safety of the facilities of hazardous substance to be suitable on the purpose of laws and take responsibility and reports to a corporation of the expert skill. The task to be given to the state will be done.

• Korean Journal of Social Welfare
• /
• v.54
• /
• pp.5-33
• /
• 2003

This study is about the re-validation evaluation of the family Relationship Scale (FRS), developed to measure the family relationship in the social work practice. This study aims at re-validating the FRS, developed and validated in by Yang in 2001 for more general utilization. The sample was married mates and females residing in Seoul. For Face Validity, the content analysis was performed, and the FRS was re-validated in the dimensions of Love & Caring, Acceptance, and Recognition, positive affection, empathy, and autonomy and flexibility for each area. Internal reliability was .93, and internal consistency among three dimensions was 93%. For Empirical Validity, the Construct validity, the Criterion validity, and the Discriminant validity were performed. Construct Validity was validated through factor analyses. Commonalities for the factor analysis was 54%, and the factor loading for each factor was over .45. The confirmative factor analysis also confirmed the fitness of the scale. For Predictive Validity of Criterion Validity, regression analysis showed that the family stress scores became lower as the scores of the family relationship became higher; the discriminant analysis revealed that the family stress turned low ill tile group of high scores of family relationship. The Correlation analysis for Concurrent Validity was performed and the results showed the positive and significant relationship with a couple communication level (r=54) and a parent-child communication level (r=64). Life satisfaction and mental health level also revealed significantly positive correlation to prove Convergent Validity. Physical health level revealed a weak relationship with family relationship providing the evidence of Discriminant Validity. Discriminance was also proved by the analysis of variance with demographics. Thus, Cross Validation was confirmed the validation of the FRS through the various analyses with the married population. This study result improved the validity generalization of the Scale and verify the generalized usage of this sociometric scale in the field of social work practice.

• Journal of Intelligence and Information Systems
• /
• v.16 no.4
• /
• pp.99-112
• /
• 2010

Ensemble learning is a method for improving the performance of classification and prediction algorithms. It is a method for finding a highly accurateclassifier on the training set by constructing and combining an ensemble of weak classifiers, each of which needs only to be moderately accurate on the training set. Ensemble learning has received considerable attention from machine learning and artificial intelligence fields because of its remarkable performance improvement and flexible integration with the traditional learning algorithms such as decision tree (DT), neural networks (NN), and SVM, etc. In those researches, all of DT ensemble studies have demonstrated impressive improvements in the generalization behavior of DT, while NN and SVM ensemble studies have not shown remarkable performance as shown in DT ensembles. Recently, several works have reported that the performance of ensemble can be degraded where multiple classifiers of an ensemble are highly correlated with, and thereby result in multicollinearity problem, which leads to performance degradation of the ensemble. They have also proposed the differentiated learning strategies to cope with performance degradation problem. Hansen and Salamon (1990) insisted that it is necessary and sufficient for the performance enhancement of an ensemble that the ensemble should contain diverse classifiers. Breiman (1996) explored that ensemble learning can increase the performance of unstable learning algorithms, but does not show remarkable performance improvement on stable learning algorithms. Unstable learning algorithms such as decision tree learners are sensitive to the change of the training data, and thus small changes in the training data can yield large changes in the generated classifiers. Therefore, ensemble with unstable learning algorithms can guarantee some diversity among the classifiers. To the contrary, stable learning algorithms such as NN and SVM generate similar classifiers in spite of small changes of the training data, and thus the correlation among the resulting classifiers is very high. This high correlation results in multicollinearity problem, which leads to performance degradation of the ensemble. Kim,s work (2009) showedthe performance comparison in bankruptcy prediction on Korea firms using tradition prediction algorithms such as NN, DT, and SVM. It reports that stable learning algorithms such as NN and SVM have higher predictability than the unstable DT. Meanwhile, with respect to their ensemble learning, DT ensemble shows the more improved performance than NN and SVM ensemble. Further analysis with variance inflation factor (VIF) analysis empirically proves that performance degradation of ensemble is due to multicollinearity problem. It also proposes that optimization of ensemble is needed to cope with such a problem. This paper proposes a hybrid system for coverage optimization of NN ensemble (CO-NN) in order to improve the performance of NN ensemble. Coverage optimization is a technique of choosing a sub-ensemble from an original ensemble to guarantee the diversity of classifiers in coverage optimization process. CO-NN uses GA which has been widely used for various optimization problems to deal with the coverage optimization problem. The GA chromosomes for the coverage optimization are encoded into binary strings, each bit of which indicates individual classifier. The fitness function is defined as maximization of error reduction and a constraint of variance inflation factor (VIF), which is one of the generally used methods to measure multicollinearity, is added to insure the diversity of classifiers by removing high correlation among the classifiers. We use Microsoft Excel and the GAs software package called Evolver. Experiments on company failure prediction have shown that CO-NN is effectively applied in the stable performance enhancement of NNensembles through the choice of classifiers by considering the correlations of the ensemble. The classifiers which have the potential multicollinearity problem are removed by the coverage optimization process of CO-NN and thereby CO-NN has shown higher performance than a single NN classifier and NN ensemble at 1% significance level, and DT ensemble at 5% significance level. However, there remain further research issues. First, decision optimization process to find optimal combination function should be considered in further research. Secondly, various learning strategies to deal with data noise should be introduced in more advanced further researches in the future.