• Fashion & Textile Research Journal
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• v.17 no.4
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• pp.626-634
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• 2015

This study analyzes the wearing and purchasing conditions of outdoor jackets by senior men who are over 50s, and examines product sizes of outdoor jackets in the market. A total of 134 questionnaires and sizing systems (or product size) of 10 outdoor brands were used as analytical data. The results were: a high number of senior men enjoyed hiking as an outdoor activity, with most of them following this activity1-3 times per month and as a preferred personal activity for over 5 years. Most needed outdoor wear suitable for these daily life activities. Outdoor wear satisfaction tends to decrease as people age. The major reason for the dissatisfaction with outdoor wear was price. Senior men aged 50s and 60s emphasize design and color when purchasing outdoor wear; however, men in their 70s considered price a priority. Senior men preferred outdoor brands based on a comfortable fit. An investigation on 10 outdoor brands indicated that they had not designated a specific target customer. A comparison of the product size of outdoor jackets with a similar silhouette indicated some deviations among sizes; however, the age of customers was not considered. The human body tends to shrink in stature and increase in girth as a person ages; consequently, we need to reflect body shape changes and senior's size in outdoor wear.

• Journal of Korea Technology Innovation Society
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• v.2 no.2
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• pp.169-186
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• 1999

This study empirically investigates innovative behaviors of the firm. In so doing, a Probit was employed and estimated. We used the raw data of the "corporate innovation survey"(CIS), which, in consent with OECD efforts, is regularly undertaken by the Science and Technology Policy Institute(SIEPI). The data set includes more than 3400 firms in the manufacturing sector. Three types of innovation, i.e., new product, product improvement and process innovation, are studied, assuming that determinants of innovation are firm′s age. number of employees as the size of firm, ratio of foreign ownership and innovation costs. To investigate the relationship between firm′s innovation behavior and the size, we estimate the Probit including the quadratic term of the firm size. Empirical findings showed that the sign of the quadratic term of the firm size turned out to be negative. It means that the probability of firm's making innovation shows the inversed-U relationship with the firm size. Such an empirical result may have a significant implication for the industrial policy.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.49
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• pp.11-21
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• 1999

The purpose of this study is to present the method to select optimal size for the industrial products which are closely related to human's body size. For this purpose, human factors such as body characteristics, body features, and preference in product selection which needs to be considered in setting standards were analyzed. This analysis is to select optimal size to minimize losses caused by the difference of size between demand by the customers and supply from the manufacturers. Using loss function, repetitive calculation process algorithm by using bisearch method was applied in selecting the sizes of demand and supply which minimize the total expected losses. For cumulative normal distribution probability, IMSL routine DNORDF was used. In case study, comparison has been made between the result which was calculated using presented algorithm and the results calculated by the process currently used by KS and ISO by measuring aged women's body size in human factors side and sorting them through the factor analysis and cluster analysis for feature factor extraction. Thus, they can be used as a basis for establishing industrial product standards.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.3 no.3
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• pp.67-74
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• 1980

The importance of market segmentation for success in marketing new products cannot be overemphasized. The benefits of new product segmentation are many, particularly when the proper conditions for product segmentation are met. The markets for the new product can be segmented according to demographic, geographic, psychological, and product-related variables and the use of market grids. To be ultimately useful in the successful marketing of the new product, the segmentations must be of sufficient size, related to the firm's capabilities, and quantifiable.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Journal of the Ergonomics Society of Korea
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• v.3 no.1
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• pp.3-11
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• 1984

This study aims to investigate the effects of the size of operator's hand and the use of foot on the production quantity and product quality. To find out the facts the survey is conducted by measuring the hand size for the worker who is randomly chosen and by grouping them into the large hand size group and small hand size group on the base of the measuring data. The grouped operators are assigned to their job as usual, and their daily production quantities and qualities are measured. The survey shows that the production quantity of the small hand group are higher than the large hand group, and the number of defects of the small hand group are less than the large hand group.

• Journal of the Korean Society of Clothing and Textiles
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• v.48 no.1
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• pp.108-119
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• 2024

In this study, we aimed to propose enhancements to the dimensions and design of walking aids tailored for elderly women. Specifically, we focused on wheeled walking assistance devices and aligned each structural component with the appropriate human body dimensions to suggest appropriate product dimensions organized by size clusters, aiming to maximize the practicality of the results. We extracted essential factors required for product design, including human body size elements. The dimension extraction method was clustered to establish connections between key human body parameters-such as height, weight, and age groups-and product dimensions. We conducted a comparative analysis of walking aid product dimensions according to the design elements and sizes of models currently available in the market. The outcomes of this study offer objective, data-driven insights into areas where existing models on the market could benefit from improvement and we anticipate that the findings of this study will provide a solid, quantitative foundation for individuals when selecting the most suitable model for their needs.

• Journal of the Korean Home Economics Association
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• v.40 no.10
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• pp.113-121
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• 2002

The purpose of this study was to investigate the effect of the depth of fashion product line on sales. The depth of the fashion product line was defined as the variety of style, color, and size in the outwear line for this study. Data were collected from the 98 brands in 4 department stores located in Seoul and Pusan. The result showed the significant impact of the variety of the outwear style on sales. Even after controlling the effect of advertising and the level of price in each brand, significant effect of the variety of outwear style were noticed on sales.

• Communications of the Korean Mathematical Society
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• v.25 no.1
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• pp.19-25
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• 2010

$3{\times}3{\times}3$ is the meaningful smallest product of three chains of each size 2n+1 since $1{\times}1{\times}1$ is a 1-element poset. The linear discrepancy of the product of three chains $2n{\times}2n{\times}2n$ is found as $6n^3-2n^2-1$. But the case of the product of three chains $(2n + 1){\times}(2n + 1){\times}(2n + 1)$ is not known yet. In this paper, we determine ld$(3{\times}3{\times}3)$ as a case to determine the linear discrepancy of the product of three chains of each size 2n + 1.

• Proceedings of the Safety Management and Science Conference
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• 2007.11a
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• pp.319-322
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• 2007

This paper presents geometrical product specifications of acceptance and verification tests for coordinate measuring machines(CMM). These specifications include vocabulary, measuring size, rotary table with fourth axis, scanning measuring mode, multiple-stylus probing systems, measuring, and, estimation of errors in computing Gaussian associated features.