A study on the Environmental Factors of the Fitting Room Affecting Fashion Product Purchase Decisions (패션제품 구매결정에 영향을 미치는 피팅룸 환경 요인에 관한 연구)
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- Fashion & Textile Research Journal
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- v.24 no.6
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- pp.756-765
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- 2022
The purchase-related responses of MZ generation consumers may vary depending on the environmental factors of the fitting room. Therefore, this study extracted and systematized fitting room characteristics in the retail fashion environment. In-depth interviews were conducted with a total of 50 informants to collect data on the experience of using the fitting room. Then, a qualitative analysis was performed. First, results confirmed that the environmental factors of the fitting room include physical (spatiality, functionality, comfort, and convenience) and human (interactivity and congestion) aspects. Next, additional analysis was performed on functionality and interactivity to clarify the influence of environmental characteristics of the fitting room. These factors were classified into qualitative categories. The study results confirmed that, in the case of functionality, preferred lighting and mirror factors vary depending on the clothing product type, the place and situation for wearing, and individual characteristics. Furthermore, regarding interactivity, the preference for the presence of sales staff or companions differed according to personal traits and the need for additional information and evaluation. The study provides valuable information for effective fitting room space planning for offline fashion stores to meet the needs of MZ generation consumers.
With the advent of industrialization, consumers and end-users demand more reliable products. Meeting these demands requires a comprehensive approach, involving tasks such as market information collection, planning, reliable raw material procurement, accurate reliability design, and prediction, including various reliability tests. Moreover, this encompasses aspects like reliability management during manufacturing, operational maintenance, and systematic failure information collection, interpretation, and feedback. Improving product reliability requires prioritizing it from the initial development stage. Failure mode and effect analysis (FMEA) is a widely used method to increase product reliability. In this study, we reanalyzed using the FMEA method and proposed an improved method. Domestic railways lack an accurate measurement method or system for maintenance, so maintenance decisions rely on the opinions of experienced personnel, based on their experience with past faults. However, the current selection method is flawed as it relies on human experience and memory capacity, which are limited and ineffective. Therefore, in this study, we further specify qualitative contents to systematically accumulate failure modes based on the Failure Modes Table and create a standardized form based on the Master FMEA form to newly systematize it.
Purpose - Despite the importance of price, many companies do not implement pricing policies smoothly, because typical price management strategies insufficiently consider logistics efficiency and an increase in logistics costs due to logistics waste. This study attempts to examine the effect of product line pricing, which corresponds to product mix pricing, on logistics efficiency in the case of manufacturer A, and analyzes how logistics performance changes in response to these variables. Research design, data, and methodology - This study, based on the case of manufacturer A, involved research through understanding the current status, analyses, and then proposing improvement measures. Among all the products of manufacturer A, product group B was selected as the research object, and its distribution channel and line pricing were examined. As a result of simulation, for products with low loading efficiency, improvement measures such as changing the number of bags in the box were suggested, and a quantitative analysis was conducted on how these measures influence logistics costs. The TOPS program was used for the Pallet loading efficiency simulation tool in this study. To prevent products from protruding out of the pallet, the maximum measurement was set as 0.0mm, and loading efficiency was based on the pallet area, and not volume. In other words, its size (length x width) was focused upon, following the purpose of this study and, then, the results were obtained. Results - As a result of the loading efficiency simulation, when the number of bags in the box was changed for 36 products with low average loading efficiency of 73.7%, as shown in