• Journal of Digital Convergence
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• v.10 no.11
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• pp.287-293
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• 2012

The present paper attempts to account for customers' purchase intention of counterfeit goods. Based on some previous analyses, we have set up a structured model for analysis with a hope to identify the relationship between benefits from using counterfeit goods and motivational factors to purchase them. It is found, first of all, that motivation for ostentation significantly influences personal benefits from using the counterfeit goods. Second, we also find that motivation for satisfaction does not exert any direct influence on the factors of benefits, though it affects decisions to purchase. Third, motivation for practicability has significant influence on personal and, more strongly, on economic benefits. Fourth, quality has significant influence on both personal and economic benefits. Again, this factor is also more closely related with economic benefits than with personal ones. We hope that we will be able to provide practical tips for those who design and plan public service advertisements that intend to reduce purchasing of counterfeit products.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.251-256
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• 2013

In the past, customers utilize a secondhand book market as a major counter for their purchasing used books. With expansion of internet and IT devices, many customers would like to buy their used books in an on-line secondhand book store which has more price competitiveness and ease. Nowadays a new concept off-line secondhand book market which has the advantages of both on-line and off-line is a growing trend instead of existing secondhand book markets in the economic recession. In this study, we established customer service satisfaction for 'Aladin store', which is the advanced concept off-line secondhand book store, with the most typical service quality test technique SERVQUAL. First, we selected appropriate service quality factor for the advanced concept off-line secondhand book market such as Aladin store. After that, we analyzed which factors are influencing repurchase intentions, through customer survey. The conclusion provides the secondhand book store's service quality improvement and strategy toward customer satisfaction including the existing used book stores.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.5
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• pp.193-203
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• 2014

This study was to highlight the importance of elements of flower fair to organizer who organize flower fair in local community, to increase of participancy in flower fair exhibition with informing experience element and finally to increase incomes of flower farmhouse. To investigate degrees of interest of visitors on experience marketing of exhibition factors in flower fair, survey was conducted for 278 target audiences and data was analyzed to find the effect of experience marketing of exhibition factors in flower fair on the interest of purchasing. To population statistics, female took majority, 61.9% in sex, twenties, 34.5% in ages, married, 50.7% in marriage and students, 36.7% in job. University graduation occupied 58.3% in education, one million something, 48.6% in average income, seoul showed 38.1% in resident cities and 1st time visit was 79.9% in flower fair visit. For statistical categories, technology statistics analysis and reliability analysis were conducted. To check validity, factor analysis was conducted, and to see interrelationship of factors, using regression analysis, fluence among factors was analyzed. Results showed that exhibition environment of flower fair was effected by cultural elements, exhibition quality and exhibition service were effected by event and cultural element, exhibition marketing was effected by cultural and image element and purchasing interest was effected by image element.

• Korean Journal of Poultry Science
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• v.43 no.3
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• pp.129-134
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• 2016

This study was conducted to investigate the sensory properties of chicken meat products, such as color, flavor, tenderness, juiciness, taste, and so on, in multi-cultural families. Questionnaires were collected from multi-cultural families, for a total of 80 consumers. H-4, which contained 80.2% chicken meat ham out of the 5 hams was shown to score 7.00 of 10 points on the Likert scale compared to the others products (P<0.05). Loyalty purchasing of chicken ham showed the middle level, 6.50 points (P<0.05). Preferences for color, flavor, tenderness, juiciness and taste of chicken breast ham in South East-Asia showed higher values than those in Korea and Vietnam (P<0.05). The preferences of dakgalbi for sensory properties among multi-cultural families did not show significant differences. The color preferences of chicken mixed press ham showed higher values in South East-Asia than those in Vietnam (P<0.05). The purchase intension of chicken press ham after manufacturing was the highest, 4.12 points, for chicken meat products.

• Journal of Animal Science and Technology
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• v.51 no.5
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• pp.433-440
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• 2009

This study was conducted to investigate the experience of purchasing a specific livestock farm product brand, loyalty to a brand, reasons of loyalty, reasons of nonloyalty and intension of paying a premium for a preferred brand according to gender, occupation of parents, a place of residence and income of parents with 408 university students by using a questionnaire and to provide measures for development of livestock farm product brands satisfying both to producers and consumers. According to the results, only the students (25.7%, 105) had bought a specific livestock farm product brand and more female students (33.6%) had purchased a specific brand than male students (21.4%) (p<0.01). For loyalty to a brand, males were more loyal by recording 3.83 points, and students whose parents were farmer showed the highest or 4.17 points (p<0.05). As reasons of loyalty to a brand, female students answered quality (76.6%, 36) and a price (12.8%, 6) in that order and male students considered its name value as the most important reason (26.4%, 14) (p<0.05). In conclusion, experience of buying a livestock farm product brand was found to be a factor increasing university students‘ loyalty to a brand. Although quality and a price affected largely the purchase of a brand, a place to buy it and a price were major factors hindering the purchase.

• Journal of Global Scholars of Marketing Science
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• v.18 no.1
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• pp.1-31
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• 2008

Trust is central to human relationships, at all times and places. The importance of trust is fundamental in all areas of human life, not only in the area of business administration. 2,500 years ago in China, Confucius taught that the foundation of politics was the trust of the people, more important even than military strength or the supply of food. Shakespeare's play, "Much Ado about Nothing' is about trust and deception. These days, trust and transparency in a commercial organization's business culture form the basis of the 'social capital' by which that organization increases its productivity. A successful company raises productivity by the accumulation of social capital, derived from a trust relationship between business partners, and between the company and consumers. Trust is the crucial factor. At the national level, building trust determines a nation's competitiveness. For a company, long term trust relationships with customers are essential for its survival in a business environment of rapid change. Such relationships, based on trust, are important assets to ensure a company's competitive advantage, and need to be organic to that company's business culture. Because of this importance, trust relationships have been studied in diverse areas within business administration, and especially within marketing, where they form the basis of a successful relationship between producer and consumer. However, what has been lacking is a unified definition of trust. Research has been conducted on the basis of various definitions and models. The majority of researchers have not considered the multidimensional character of the concept of trust until now. Approaches based on a one dimensional model have undermined the value of research results. Furthermore, researchers have only considered trust and trustworthiness as a single component. The majority of research has explored the consequences of perceived trust for outcomes such as loyalty or cooperation, but has neglected the effects of trustworthiness upon the mechanisms of consumer trust. This study focuses on the dimension of trust from such a perspective. It seeks to verify the effect of trust on customer intentions by breaking it down into three separate components: 1) the salesperson, 2) the product/service, and 3) the company. The purposes of this paper are as follows: Firstly, we review the multidimensional nature of trust objects: the salesperson, the product/service, and the company. Secondly, we analyze the relationship between multidimensional trust and trustworthiness. Thirdly, we analyze the connection between trust and repeat purchase intentions for the maintenance of long term relationships. For these purposes the author has developed several hypotheses as follows: H1-1: The competence of a salesperson is positively associated with the trust given by the consumer to the salesperson. H1-2: The benevolence of a salesperson is positively associated with the trust given by the consumer to the salesperson. H2-1: The competence of product/service is positively associated with the trust given by the consumer to the product/service. H2-2: The benevolence of product/service is positively associated with the trust given by the consumer to the product/service. H3-1: The reputation of a company is positively associated with the trust given by the consumer to the company. H3-2: The physical environment of a company is positively associated with the trust given by the consumer to the company. H4-1: Trust in a salesperson is positively associated with repeat purchase intentions. H4-2: Trust in a product/service is positively associated with repeat purchase intentions. H4-3: Trust in a company is positively associated with repeat purchase intentions. The data was compiled from 366 questionnaires. 500 questionnaires were collected, but some of the data was considered unsuitable and inappropriate. The subjects of the survey were male and female customers purchasing products at department stores in Seoul, Daegu and Gyeongbuk. It was carried out between Oct. 25 and 29, 2007. The data was analyzed by frequency analysis using SPSS 12.0 and structural equation modeling using LISREL 8.7. The result of the overall model analysis is as follows: Chi-Square=445.497, d.f.=185, p-value=0.0, GFI=.901, RMSEA=.0617, NNFI=.986, NFI=.981, CFI=.989, AGFI=.864, RMR=.0872. The results of the overall model analysis were coherent. It was found that trust is a multi-dimensional construct, that each of the dimensions of trust are meaningful influences on customer's repurchase intention. Trust in a company may be the most relevant, while trust in a product/service and a salesperson may be less relevant to repurchase intentions. The effective factors in determining trust in a salesperson and a company's product/service were found to be competence and benevolence. Factors in determining trust in a company were its reputation and physical environment, and the relationship of each effective trust factor has been verified in this research. As a result, it was found that competence and benevolence have a meaningful influence on trust in a salesperson and in product/service. It was also found that a company's reputation influences the overall trust in the company significantly but a company's physical environment does not have much effect.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.1-20
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• 2013

Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.