• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.2
• /
• pp.353-358
• /
• 2020

The new sales method of social commerce in food service market is growing steadily. Over 50 percent of the social commerce market is food service product. Food service companies are using social commerce, which is discount sales, as a marketing tool. There are many food service companies using social commerce as a sales and marketing tool. However, little research has investigated food service customers. Thus, this study suggests how food service customer's purchasing factor affects customer's satisfaction and loyalty of the supplier and business operator. Social commerce's purchasing characteristic factors are selected based on a previous study. Purchasing factor is divided into supplier and business operator side and the impact of the relationships between its subordinate factors (price discount, offering diversity, mutual action, brand intimacy) and customer's satisfaction is analyzed. As a result, price discount and brand intimacy show higher results. Offering diversity and brand intimacy of purchasing factor on business operator side shows a higher impact on the relationship between loyalty and ?? (Ed- 'the relationship between A and B'; what is B?). The study implications are as follows. The food service industry should establish different marketing strategies to apply social commerce and compare with social commerce business operators, because the actual place where customers use food service is food service restaurants and not just social commerce websites.

• Journal of Distribution Science
• /
• v.9 no.1
• /
• pp.39-48
• /
• 2011

One of the major reasons for fierce competition among firms is that they strive to increase their own market shares in the same market with similar and apparently undifferentiated products in terms of quality and perceived benefit. Due to such changes in the marketing environment, differentiated after-sales service and diversified promotion strategies have become more important in the race to gain a competitive advantage. Price discount is one of the popular promotion strategies that most retailers use, especially to increase sales, but offering a price discount does not always lead to the expected result. If marketers apply an identical price-promotion strategy without considering the characteristic differences in products and consumer preferences, the discounted price itself may make people skeptical about the quality of the product. Moreover, the changes in perceived value may appear differently depending on factors such as consumer involvement. This implies that variables such as the level of consumer involvement, brand loyalty, and external reference prices, in reality, would have different effects on how consumers perceive the value of price discounts. The variables that affect consumers' perceived values and buying decisions are diverse and complicated. Several studies have examined the effects of such variables as external reference price, selling price, and brand on consumers' perceived value of products. Results have not shown consistent patterns. Therefore, we must note that the factors affecting consumers' value perceptions and buying behaviors are diverse and that the results of studies on the same dependent variable come out differently depending on what that variable is. This study focused on the level of consumer involvement as a salient variable that supposedly affects the perceived value of a product, willingness to buy, and search intentions. We tried to examine whether a price discount affects the perceived value-such as perceived acquisition value and perceived transaction value-in different ways depending on the level of consumer involvement. In addition, we proposed managerial implications that marketers need to consider as a whole, for instance, product attributes, brand loyalty, and involvement and then established a differentiated pricing strategy, case by case, in order to effectively enhance consumers' perceived values. As a result, we found that perceived transaction value positively affects perceived acquisition value and when discounting the price of a high-involvement product enhances the consumer's willingness to buy, but perceived acquisition value does not affect the search intentions significantly. In the case of discounting prices of low-involvement products, on the other hand, the perceived transaction value has a positive effect on the willingness to buy, but the negative effect of perceived acquisition value on the search intentions was not significant. We suppose that people doubt a product's quality because of a declined perceived quality derived from a price discount. Even though the price discount enhanced the transaction value, people eventually increased their level of searching for additional product information. From the results of this study, we suggest that marketers ought to establish an appropriate value-enhancing strategy based on the understanding of which perceived value consumers rely on more when they conduct purchasing behavior because consumers perceive the degree of importance of acquisition value or transaction value differently, depending on their level of involvement.

• The Journal of Society for e-Business Studies
• /
• v.16 no.3
• /
• pp.191-209
• /
• 2011

In a buyer-seller transaction process, 'value for money,' a measure of quality-price-ratio, is one of the most important criteria for buyers' purchasing decisions. The purpose of this paper is to suggest a method which helps online shoppers choose the best of several sellers offering homogeneous goods. We suggest FDH (free disposal hull) model, an applied model of data envelopment analysis (DEA), for online buyer-seller transactions and verify it with the data from an Internet comparison shopping site. For this purpose, we analyze consumer choice behaviors by examining how consumers respond to different sale conditions such as price, brand, or delivery time. Then, we implement a seller recommendation system to support buyers' purchasing decisions. We expect our FDH model to provide valuable information for rational buyers who want to pay the least price for high quality products/services and to be used in implementing automated evaluation processes in micro transactions. Moreover, we expect that our results can be utilized for sellers' benchmarking strategies which help sellers be more competitive by showing them how to attract buyers.

• Journal of the Korea Fashion and Costume Design Association
• /
• v.15 no.4
• /
• pp.29-45
• /
• 2013

The purpose of this study is to provide base line data required to establish a viable knitwear marketing strategy targeting young people by comparing and analyzing preference and buying behavior of customers in their twenties. A survey was conducted in 2009 and 2013 on people in their 20's male and female living in Busan. The total of 362 people participated in the survey and the results are as follows: Firstly, the seeking factors for knitwear were utilization factor, functionality factor, care for clothing factor, economics factor and vogue factor. Secondly, a differentiated marketing strategy targeting 20-something customers needs to be established as there was a steep rise in the number of customers purchasing clothes on online shopping malls using smart phone devices according to the survey.'Low-price, broad-line strategy'is also required as those surveyed preferred stores offering a wide choice of designs with reasonable price. Considering the survey results that a growing number of people tended to buy a variety of knitwear items regardless of the seasons, knitwear production needs to be diversified in terms of designs and materials. Thirdly, the survey revealed that pastel-colored knitwear was preferred for spring/summer season whereas knitwear with achromatic colors was voted the most-preferred one during the autumn and winter season. In terms of knitwear shapes, the gap between genders continues to narrow and tendency sensitive to fashion trend became more apparent reflecting the change of the times.

• The Research Journal of the Costume Culture
• /
• v.20 no.2
• /
• pp.169-183
• /
• 2012

This study was aimed at finding out the preferences and satisfaction levels regarding the type of fashion retailer's sales promotion based on consumers' empirical characteristics. A total of 223 questionnaires were used for the survey of this study. The methods of this study were descriptive analysis, factor analysis, reliability tests, one-way ANOVA, $t$-tests and ${\chi}^2$-test. The consumer groups were divided by habitual experience and self-evaluated knowledge relate to apparel product. The results of this study showed that consumers have different preferences and post-utilization satisfaction regarding the type of sales promotion offered by fashion retailers. Consumers with more experiences in apparel product and with higher self-evaluated knowledge were more active in utilizing the benefits offered through the value-added type of sales promotions, such as the gift certificate or coupon. Consumers with more experience in apparel product also showed higher satisfaction with both the utilitarian and hedonic types of sales promotions, such as gift certificate offer, special price, price discount event, and coupon or courtesy card offer. Furthermore, consumers with higher self-evaluated knowledge showed higher satisfaction with the utilitarian types of sales promotion, such as gift certificate offer and regular sale. Therefore, by identifying the accurate understanding of consumers'empirical characteristics, an enterprise might be able to satisfy consumer by offering more appropriate and subdivided types of sales promotion.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.46 no.4
• /
• pp.152-159
• /
• 2023

This study endeavors to enrich investment prospects in cryptocurrency by establishing a rationale for investment decisions. The primary objective involves evaluating the predictability of four prominent cryptocurrencies - Bitcoin, Ethereum, Litecoin, and EOS - and scrutinizing the efficacy of trading strategies developed based on the prediction model. To identify the most effective prediction model for each cryptocurrency annually, we employed three methodologies - AutoRegressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM), and Prophet - representing traditional statistics and artificial intelligence. These methods were applied across diverse periods and time intervals. The result suggested that Prophet trained on the previous 28 days' price history at 15-minute intervals generally yielded the highest performance. The results were validated through a random selection of 100 days (20 target dates per year) spanning from January 1st, 2018, to December 31st, 2022. The trading strategies were formulated based on the optimal-performing prediction model, grounded in the simple principle of assigning greater weight to more predictable assets. When the forecasting model indicates an upward trend, it is recommended to acquire the cryptocurrency with the investment amount determined by its performance. Experimental results consistently demonstrated that the proposed trading strategy yields higher returns compared to an equal portfolio employing a buy-and-hold strategy. The cryptocurrency trading model introduced in this paper carries two significant implications. Firstly, it facilitates the evolution of cryptocurrencies from speculative assets to investment instruments. Secondly, it plays a crucial role in advancing deep learning-based investment strategies by providing sound evidence for portfolio allocation. This addresses the black box issue, a notable weakness in deep learning, offering increased transparency to the model.

• Journal of Distribution Research
• /
• v.17 no.5
• /
• pp.59-83
• /
• 2012

Agriculture is a primary industry that influenced by the weather or meterological factors more than other industry. Global warming and worldwide climate changes, and unusual weather phenomena are fatal in agricultural industry and human life. Therefore, many previous studies have been made to find the relationship between weather and the productivity of agriculture. Meterological factors also influence on the distribution of agricultural product. For example, price of agricultural product is determined in the market, and also influenced by the weather of the market. However, there is only a few study was made to find this link. The objective of this study is to investigate the effects of meterological factors on the distribution of agricultural products, focusing on the distribution of chinese cabbages. Chinese cabbage is a main ingredient of Kimchi, and basic essential vegetable in Korean dinner table. However, the production of chinese cabbages is influenced by weather and very fluctuating so that the variation of its price is so unstable. Therefore, both consumers and farmers do not feel comfortable at the unstable price of chinese cabbages. In this study, we analyze the real transaction data of chinese cabbage in wholesale markets and meterological factors depending on the variety and geography. We collect and analyze data of meterological factors such as temperatures, humidity, cloudiness, rainfall, snowfall, wind speed, insolation, sunshine duration in producing and consuming region of chinese cabbages. The result of this study shows that the meterological factors such as temperature and humidity significantly influence on the volume and price of chinese cabbage transaction in wholesale market. Especially, the weather of consuming region has greater correlation effects on transaction than that of producing region in all types of chinese cabbages. Among the whole agricultural lifecycle of chinese cabbages, 'seeding - harvest - shipment - wholesale', meterological factors such as temperature and rainfall in shipment and wholesale period are significantly correlated with transaction volume and price of crops. Based on the result of correlation analysis, we make a regression analysis to verify the meterological factors' effects on the volume and price of chines cabbage transaction in wholesale market. The results of stepwise regression analysis are shown in