• Journal of the Korean Society of Food Culture
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• v.34 no.6
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• pp.739-747
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• 2019

This study investigated the effect of offering eco-friendly fashion items on consumers' perceived image of stores and their intention to purchase food in a hybrid cafe setting. The data were collected using an online survey of 465 adults aged 20 to 49 years. In order to compare 'a general cafe' where only food is sold and 'a hybrid cafe' which offers eco-friendly fashion items as well as food, we developed two store types (general×hybrid) with two store designs (modern×eco-friendly) as stimuli, resulting in four scenarios. The results indicated that offering eco-friendly fashion items at a cafe did not significantly affect consumers' perceived eco-friendly image of the store. Further, this negatively affected consumers' perceived healthy and tasty images of the store and intention to purchase food. Such negative effects on the healthy and tasty images of the store increased in the store with a modern design. In conclusion, offering eco-friendly fashion items at cafes may not contribute to enhancing the stores' images or sales.

• Journal of Distribution Science
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• v.20 no.2
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• pp.91-100
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• 2022

Purpose: The sports industry is a major form of leisure and entertainment, but the industry was tremendously affected by the Covid-19 pandemic. This study gives solutions for sports leisure retail stores to the effects of the Covid-19 crisis on consumers' sports products purchasing habits and then gives a logical conclusion regarding the findings of the topic. Research design, data and methodology: Scant research is available to feedback for owners and managers of sports leisure retail stores which elements could be considered to recover their business prior to the pandemic. For achieving this, this study investigated total 284 responses in the retail stores and conducted the ANOVA analysis to compare the level of intensity on the impact Covid 19 pandemic. Results: Our findings suggests that there was a statistically recognizable difference at the significance level of probability between the mean value of the impact index of Covid 19 pandemic and key recovery strategies, indicating the high degree of Covid 19 impact can be reducing by four solutions. Conclusions: Finally, this study concludes the specific entertainment elements that influence the purchasing behavior of consumers will ensure that the Sports industry deals with its internal problems first without necessarily looking at the outside factors such as the pandemic.

• Management & Information Systems Review
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• v.38 no.3
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• pp.227-243
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• 2019

The purpose of this study was to examine the influence of experience characteristics of cosmetics brand stores on purchase intention through brand value and product in-store expectations. In addition, by identifying the effects of gender regulation, the study aimed to supplement theoretical studies and to provide practical implications on the experience of cosmetics brand stores. First, we presented educational experiences, aesthetic experiences, and playful experiences as experience characteristics in stores. And we assumed the effect of these experience characteristics on the brand value and the expectation of the product in the store, and the effect of the brand value and the expectation on the purchase intention of the product in the store. 279 data were collected from consumers who had visited cosmetics brand stores, and we analyzed them using structural equation analysis. As a result, both experience characteristics have positive effects on brand value and in-store product expectations, and brand value has positive effects on expectations. In addition, brand value and in-store product expectations have a positive effect on in-store product purchase intention. In moderating effects of gender, the effect of playful experience on brand value is greater in male group, and the impact of educational and aesthetic experience on product expectations is greater in female group. These results contribute to the theoretical expansion of experience research on cosmetic brand stores, and provide strategic implications for experience marketing of cosmetic stores.

• 한국전산유체공학회:학술대회논문집
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• 2008.03a
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• pp.374-377
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• 2008

The prediction of the separation trajectories of the external stores released from a military aircraft is an important task in the aircraft design area having the objective to define the operational and release envelopes. This paper presents the results obtained for store separation by employing commercial sorftwares, FLUENT and CFD-FASTRAN. FLUENT treats the rigid body motion by employing the remeshing scheme. CFD-FASTRAN uses the chimera(overset) grid and interpolations. It was found that, for the prediction of the trajectories and behavior of the stores separated from the wing, both codes shows the good agreement with the experimental results.

• 한국전산유체공학회:학술대회논문집
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• 2008.10a
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• pp.374-377
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• 2008

The prediction of the separation trajectories of the external stores released from a military aircraft is an important task in the aircraft design area having the objective to define the operational and release envelopes. This paper presents the results obtained for store separation by employing commercial sorftwares, FLUENT and CFD-FASTRAN. FLUENT treats the rigid body motion by employing the remeshing scheme. CFD-FASTRAN uses the chimera(overset) grid and interpolations. It was found that, for the prediction of the trajectories and behavior of the stores separated from the wing, both codes shows the good agreement with the experimental results.

• Industrial Engineering and Management Systems
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• v.15 no.4
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• pp.318-323
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• 2016

In the current study, factors affecting cheese brands products in grocery stores were evaluated with an emphasis on diversity. The sample data were collected from Noushad and Pegah Milk Industry in 2015 and data were extracted, reviewed, and analyzed from 435 grocery stores in Mashhad using seemingly unrelated regression model and particle swarm optimization algorithm. Results showed that optimum amount of Kalleh product diversity is higher than other competitors in the market, and Kalleh UF diversity is 100 to 250 grams, and Kalleh UF diversity with weight of 300 to 500 grams is more than other modes of diversity, and Kalleh brand must remove tin cheese from the market. Sabah Brand also should eliminate its glass and creamy diversity from market, UF diversity is mostly welcomed in market.

• Soft Computing and Machine Intelligence
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• v.1 no.1
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• pp.11-23
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• 2021

House price prediction is a significant financial decision for individuals working in the housing market as well as for potential buyers. From investment to buying a house for residence, a person investing in the housing market is interested in the potential gain. This paper presents machine learning algorithms to develop intelligent regressions models for House price prediction. The proposed research methodology consists of four stages, namely Data Collection, Pre Processing the data collected and transforming it to the best format, developing intelligent models using machine learning algorithms, training, testing, and validating the model on house prices of the housing market in the Capital, Islamabad. The data used for model validation and testing is the asking price from online property stores, which provide a reasonable estimate of the city housing market. The prediction model can significantly assist in the prediction of future housing prices in Pakistan. The regression results are encouraging and give promising directions for future prediction work on the collected dataset.

• Journal of Distribution Science
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• v.14 no.11
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• pp.83-90
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• 2016

Purpose - During the last two years, convenient stores (CS) are emerging as one of the most fast-growing retail trades in Korea. The goal of this work is to forecast and to analyze sales at CS using ARIMA-Intervention model (IM) and exponential smoothing method (ESM), together with sales at supermarkets in South Korea. Considering that two retail trades above are homogeneous and comparable in size and purchasing items on off-line distribution channel, individual behavior and characteristic can be detected and also relative superiority of future growth can be forecasted. In particular, the rapid growth of sales at CS is regarded as an everlasting external event, or step intervention, so that IM with season variation can be examined. At the same time, Winters ESM can be investigated as an alternative to seasonal ARIMA-IM, on the assumption that the underlying series shows exponentially decreasing weights over time. In case of sales at supermarkets, the marked intervention could not be found over the underlying periods, so that only Winters ESM is considered. Research Design, Data, and Methodology - The dataset of this research is obtained from Korean Statistical Information Service (1/2010~7/2016) and Survey of Service Trend of Korea Statistics Administration. This work is exploited time series analyses such as IM, ESM and model-fitting statistics by using TSPLOT, TSMODEL, EXSMOOTH, ARIMA and MODELFIT procedures in SPSS 23.0. Results - By applying seasonal ARIMA-Intervention model to sales at CS, the steep and persisting increase can be expected over the next one year. On the other hand, we expect the rate of sales growth of supermarkets to be lagging and tied up constantly in the next 2016 year. Conclusions - Based on 2017 one-year sales forecasts for CS and supermarkets, we can yield the useful information for the development of CS and also for all retail trades. Future study is needed to analyze sales of popular items individually such as tobacco, banana milk, soju and so on and to get segmented results. Furthermore, we can expand sales forecasts to other retail trades such as department stores, hypermarkets, non-store retailing, so that comprehensive diagnostics can be delivered in the future.

• The Journal of Society for e-Business Studies
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• v.25 no.2
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• pp.65-98
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• 2020

The adoption of artificial intelligence technology is continuously increasing in online stores. However, there have been no empirical studies that examine whether each of the artificial intelligence functions affects consumers' continuance intent to shop online. This study aims to understand the effect of the main function of artificial intelligence on the continuance intention of online store via empirical analysis. In particular, we focus on how artificial intelligence as a resource affects the heterogeneity of online stores in terms of resource-based views. We also analyzed the mediating effect of online store's image (product and service) between artificial intelligence (AI) functions and continuance intention. The results suggest that the presence of AI function on online stores positively influence the continuance intention from the resource-based perspective. Furthermore, it was found that AI technology positively affects the image of a product and service. We also found that there was a difference in the way of influencing the intention to use online stores by AI functions.

• Journal of Distribution Science
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• v.14 no.10
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• pp.153-164
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• 2016

Purpose - In general, large companies have larger organizations, funds, and systems to provide more effective and efficient services in the market. However, development needs to support the livelihood of ordinary citizens who work for small businesses as well. This research suggests that a new distribution channel, called a "foothold style Kosa mart," that cooperates jointly with a distribution center and a large discount mart can provide direct solutions to small and mid-size distributors. This new distribution channel can achieve a limited type of "Nadle shop (small supermarket) foster project" related to building a joint distribution center and improvement in wholesale supply. Research design, data, and methodology - Data about the Korea distribution situation, the Nadle stores, and the logistics centers were collected from literature, Statistics Korea, journals, and reports. Specifically, we investigated information about Kosa Mart and Nadle stores. We focused on the redesign of the distribution center for the Nadle store. Results - The Kosa Mart distribution center now includes 18 warehouses, and has been handling 2000-3000 items. Most of the warehouses have been simply designed and items loaded and stored without refrigeration; thus, it is possible to store only products of certain manufactured goods. The current logistics center has no wholesale function because it failed to resolve the joint purchasing and product supply issues of competitively priced products. Conclusions - This study aimed to identify ways to strengthen the competitiveness of small- and medium-sized retailers. A Kosa Mart redesign aims to unifying the logistics center, stores, and customers. First, the joint wholesale logistics system, equipped with an integrated ordering system, needs to process customer orders and store orders at the same time. Second, excellent small business product development has to connect with production. Third, the store composition needs to support a shipping hub. Fourth, the Mart differentiates itself from convenience store goods by supplying regional and specialized products to customers. Fifth, a service buying agent and direct transactions between producers and consumers need to be established, and exhibits and displays of goods need to be improved.