• Journal of Distribution Science
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• v.13 no.9
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• pp.59-70
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• 2015

Purpose - This study aims to suggest strategies for Korean enterprises advancing into the Vietnam bakery market by analyzing the effects of perceived values on brand preference and purchase intention among Korean and Vietnamese consumers. Research design, data, and methodology - The perceived value model designed includes functional (price, quality), emotional, and social values. The survey collected data from 500 consumers in Seoul (Korea) and HoChiMinh (Vietnam). The SPSS 18.0 package was used for analysis. Results - First, among Vietnamese consumers, perceived value had a positive (+) effect on global brand preference in the order of functional value of quality, social value, and the functional value of price. However, from an ethnocentric trend and brand image origin, emotional value had a negative effect on global brand preference. In contrast, among Korean consumers, perceived value had a positive (+) effect on global brand preference in the order of functional value of quality, the functional value of price, and the social value. However, emotional value had no effect on global brand preference. Second, for both Korean and Vietnamese consumers, perceived value had a significant positive effect on purchase intention. Third, unlike the Korean consumer, for the Vietnamese consumer, global brand preference had a significant effect on purchase intention. Conclusions - The study implies the following. First, the Vietnamese bakery market has a high proportion of middle-aged customers in their 40s (64%). In terms of monthly income, there was a large proportion (40%) of high-income earners (over $325). Therefore, bakery consumption can be seen as concentrated among middle-aged and high-income consumers. Based on this, bakery strategies should include efforts to increase purchase prices as well as ways to attract local consumers (large cities). Second, unlike Korean consumers, among Vietnamese consumers, the resistance to a global brand based on emotional value (the ethnocentric tendency and brand image origin) can be seen as relatively low. Thus, in the case of the Vietnam bakery market, to increase a global brand's preference, the company should develop a differentiated strategy so that Vietnamese consumers can recognize it better, focusing on product quality, good service quality, and price in the local environment and on social value for social development. Third, in the case of the Vietnamese customer, we found that social value exerts the greatest influence on purchase intention. Therefore, a brand that engenders an image of building the local Vietnamese community can achieve a higher social value and influence purchase intention. In addition, although Vietnamese consumers have ethnocentric tendencies in terms of products, we found that if it is a preferred global brand then there are intentions to purchase. Fourth, in the case of Vietnam, if the preference for global brands is formed, consumer awareness may be connected to purchase intention. Therefore, global brands operating in Vietnam should pay attention to how to improve consumer preferences for global brands in order to increase purchase intention.

• Culinary science and hospitality research
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• v.14 no.2
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• pp.30-45
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• 2008

The objective of this study is to examine how the factors influence each other by determining the appropriate measurement standard in fast food restaurants based on the evaluation of attributes, perceived pricing, value, satisfaction and intention of revisit, and present an effective marketing strategy for fast food restaurants based on the analytical results by patrons and market segmentations. The study surveyed 195 subjects and processed the result using SPSS for Win. V. 12.0. For statistical analysis, Frequency, Factor Analysis, Reliability Analysis, and Regression Analysis were put into operation. As a result of the Factor Analysis of the evaluation of attributes, 3 factors have been extracted. The results showed that restaurant attribution evaluation had a positive effect on the perceived value($R^2adj=0.357$, p=0.000), satisfaction($R^2adj=0.346$, p=0.000) and intent of revisiting($R^2adj=0.389$, p=0.000); perceived pricing had a positive affect on the perceived value($R^2adj=0.464$, p=0.000), satisfaction($R^2adj=0.113$, p=0.000) and intention of revisit($R^2adj=0.276$, p=0.000); perceived value had a positive affect on satis-faction($R^2adj=0.327$, p=0.000) and intention of revisit($R^2adj=0.515$, p=0.000); and satisfaction had a positive affect on intention of revisit($R^2adj=0.442$, p=0.000).

• Journal of Information Technology Services
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• v.20 no.2
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• pp.13-31
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• 2021

Recently, delivery app services based on the O2O platform are increasing rapidly. Accordingly, various studies on O2O service have been conducted. Most of the studies are on consumer behavior in O2O services, and few studies on platform vendors have been conducted. Therefore, this study empirically analyzed the factors affecting the vender's intention to continuous use in the O2O delivery app platform service. Based on prior researches, we set the quality characteristics and network characteristics of the O2O platform as independent variables. The quality characteristics of the O2O platform consisted of system quality, information quality, and service quality, and the O2O platform network characteristics consisted of network externality and platform reputation. Perceived value and switching cost were set as mediated variables, and vender's intention to continuous use was set as dependent variables. For empirical analysis, we conducted a survey targeting vendors of O2O delivery app platform service, and conducted frequency analysis, factor analysis, reliability analysis, and regression analysis. As a result of the analysis, the quality characteristics of the O2O platform, such as system quality, information quality, service quality, and O2O platform network characteristics, showed that network externality and platform reputation had a positive effect on perceived value. The perceived value was found to have a positive effect on the switching cost and the intention to continuous use, and the switching cost was found to mediate the perceived value and the intention to continuous use. This study can contribute to the establishment of platform operation strategy as an empirical analysis on the factors that influence the intention of O2O platform vendors to use the platform continuously.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.269-278
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• 2022

Recently, the travel and lodging industries have been suffering from the spread of COVID-19. But Airbnb recovered its profits with a differentiated strategy. This study identified the characteristics of Airbnb and examined their effects on customer's revisit intention in the Airbnb context. Perceived value, trust about Airbnb, and social norms were considered as the key factors of revisit intention. In addition, the effects of relative attractiveness, brand identification, and enjoyment on perceived value and trust about Airbnb were examined. The proposed research model was tested based on 285 consumers who had Airbnb experience more than twice. The analysis results showed that relative attractiveness, brand identification, and enjoyment had a significant influence on perceived value and trust. Perceived value had a significant influence on revisit intention. However, trust about Airbnb and social norms did not significantly affect revisit intention. Moreover, ths analysis results found no significant moderating effect of share of wallet. Based on the results of this study, Airbnb would establish effective marketing and operation strategies by understanding the formation mechanism of consumer's revisit intention toward Airbnb.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.12
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• pp.329-342
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• 2021

The pharmaceutical industry is experiencing a productivity crisis with a low probability of success despite a long period of time and enormous cost. As a strategy to solve the productivity crisis, the use cases of Artificial Intelligence(AI) and Bigdata are increasing worldwide and tangible results are coming out. However, domestic pharmaceutical companies are taking a wait-and-see attitude to adopt AI platform for drug research. This study proposed a research model that combines the Value-based Adoption Model and the Innovation Resistance Model to empirically study the effect of value perception and resistance factors on adopting AI Platform. As a result of empirical verification, usefulness, knowledge richness, complexity, and algorithmic opacity were found to have a significant effect on perceived values. And, usefulness, knowledge richness, algorithmic opacity, trialability, technology support infrastructure were found to have a significant effect on the innovation resistance.

• Korea Trade Review
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• v.45 no.5
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• pp.239-260
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• 2020

This research was conducted on 176 GVCs-related research papers listed in the Index of Korean Academic Writers. The analysis methodology used the keyword network analysis methodology of big data analysis. For the comprehensive analysis of research trends, the research trends through word frequency (TF), important topic (TF-IDF), and topical modeling were analyzed in 176 papers. In addition, the research period of GVCs was divided into the early stages of the first study (2003-2014), the second phase of the study (2015-2017), and the third phase of the study (2018-2020). According to the comprehensive analysis, the GVCs research was conducted with the keyword 'value added' as the center, focusing on the keywords of export (trade), Korea, business, influence, and production. Major research topics were 'supporting corporate cooperation and capacity building' and 'comparative advantage with added value of overseas direct investment'. According to the analysis of major period-specific research trends, GVCs were studied in the early stages of the first phase of the study with global value chain trends and corporate production strategies. In the second research propulsion period, research was done in terms of trade value added. In the recent third phase of the study, small and medium-sized enterprises actively participated in the global value chain and actively researched ways to support the government. Through this study, the importance of the global value chain has been confirmed quantitatively and qualitatively, and it is recognized as an important factor to be considered in the strategy of enhancing industrial competitiveness and entering overseas markets. In particular, small and medium-sized companies' participation in the global value chain and support measures are being presented as important research topics in the future.

• Journal of Information Technology Applications and Management
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• v.15 no.4
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• pp.21-36
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• 2008

As the great disturbance from abusing credit cards in Korea becomes stabilized, credit card companies need to interpret credit-card delinquents classification models from the viewpoint of profit. However, hit ratio which has been used as a measure of goodness of classification models just tells us how much correctly they classified rather than how much profits can be obtained as a result of using classification models. In this research, we tried to develop a new utility-based measure from the viewpoint of profit and then used this new measure to analyze two classification models(Neural Networks and Decision Tree models). We found that the hit ratio of neural model is higher than that of decision tree model, but the utility value of decision tree model is higher than that of neural model. This experiment shows the importance of utility based measure for credit-card delinquents classification models. We expect this new measure will contribute to increasing profits of credit card companies.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.7
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• pp.607-612
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• 2002

An automatic design method of behaviors in behavior-based robotics is proposed. With this method, a robot can design its behaviors by itself without aids of human designer. Automating design procedure of behaviors can make the human designer free from somewhat tedious endeavor that requires to predict all possible situations in which the robot will work and to design a suitable behavior for each situation. A simple reinforcement learning strategy is the main frame of this method and the key parameter of the learning process is significant change of reward value. A successful application to mobile robot navigation is reported too.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1586-1592
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• 2017

Voltage sourced converter (VSC) based direct-current (DC) grid has the ability to control power flow flexibly and securely, thus it has become one of the most valid approaches in aspect of large-scale renewable power generation, oceanic island power supply and new urban grid construction. To solve the optimal power flow (OPF) problem in DC grid, an adaptive particle swarm optimization (PSO) algorithm based on fuzzy control theory is proposed in this paper, and the optimal operation considering both power loss and voltage quality is realized. Firstly, the fuzzy membership curve is used to transform two objectives into one, the fitness value of latest step is introduced as input of fuzzy controller to adjust the controlling parameters of PSO dynamically. The proposed strategy was applied in solving the power flow issue in six terminals DC grid model, and corresponding results are presented to verify the effectiveness and feasibility of proposed algorithm.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.77-87
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• 1996

Existing area-based stereo matching algorithms utilize a single rectangular correlation area for computing cross-correlation between corresponding points in stereo images, and compute disparity by finding the peak in the vicinity of depth discontinuity, since, because of inconstnat disparities around discontinuities, the cross-correlation becomes low in such area. Inthis paper, a new area-based matching strategy is proposed exploiting multiple directional correlation masks instead of a single one. The proposed technique computes multiple cross-covariance functions using each oriented mask. Peaks are detected from each covariance function and the disparity is computed by choosing the location with the highest covariance value. Proposed approach can also be applied to compute disparity gradients without obtaining dense depth data. A number of examples are presented using synthetic and natural stereo images.