• Journal of dental hygiene science
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• v.8 no.4
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• pp.267-274
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• 2008

The purpose of this study was to examine the use of dentifrice among children in a bid to provide information on dentifrice including its function to children's parents, the major consumers of dentifrice for child. And it's additionally meant to offer useful information on the production of toothpaste for kid. The subjects in this study were parents with children, who dwelled in Seoul and Gyeonggi province. After a self-administered survey was conducted for about three months from May to July 2007 to gather data on their use of dentifrice for child, a comparative analysis was implemented. The findings of the study were as follows: 1. Concerning the state of the use of their children's dentifrice, the largest number of the children(58.1%) started to use toothpaste at the age of one or down, and the most common first toothpaste they used was dentifrice for preschooler(86.8%). As for whether to use fluoride-containing toothpaste, the largest group of the parents(58.1%) gave an affirmative answer. Regarding the form of the toothpaste in use, the majority of their children used toothpaste of cream type(86.2%). The greatest group of the children used the amount of toothpaste that was as large as the three-tenths or four-tenths of the bristles(35.9%). 2. As for the state of the use of dentifrice for kid, the greatest group used that kind of toothpaste(81.4%). In the event of those who didn't use it, the last time when their children used toothpaste for kid was when they were at the western age of 3(33.9%) and 4(33.9%). Concerning the reason why they replaced toothpaste for kid with one for adult, the largest group of the parents did that on their own judgment(58.1%). As to the right time for replacing toothpaste for kid by one for adult, the greatest group considered it advisable for children to start using toothpaste for adult at the western age of 4 or 5(43.2%). 3. In relation to the state of the purchase of toothpaste for their children, the largest group was under the moderate influence of the children when they bought it(45.2%). The greatest group attached importance to the ingredients of toothpaste(41.6%), and the most preferred ingredient was fluoride(56.3%). 53.0 percent took consideration on the content of ingredients or the instructions. 4. In regard to priorities for the choice of toothpaste for their children, they gave top priority to brand(16.7%), followed by quality(14.6%) and ingredients(13.5%). The age of the parents made a statistically significant difference to the children's age when they started using toothpaste, and how they started to do that and whether they used fluoride-containing toothpaste were statistically significantly different according to that as well(p < 0.01). In regard to the impact of the occupation of the parents, the use of fluoride-containing toothpaste was more common among the stay-at-home mothers(p < 0.01).

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