• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.67-86
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• 2020

Recommender Systems have been huge influence users and business more and more. Recently the importance of E-commerce has been reached rapid growth greatly in world-wide COVID-19 pandemic. Recommender system is the center of E-commerce lively. Top ranked E-commerce managers mentioned that recommender systems have a major influence on customer's purchase such as about 50% of Netflix, Amazon sales from their recommender systems. Most algorithms have been focused on improving accuracy of recommender system regardless of novelty, diversity, serendipity etc. Recommender systems with only high accuracy cannot satisfy business long-term profit because of generating sales polarization. In addition, customers do not experience enjoyment of shopping from only focusing accuracy recommender system because customer's preference is changed constantly. Therefore, recommender systems with various values need to be developed for user's high satisfaction. Reranking is the most useful methodology to realize diversity of recommender system. In this paper, diversity of recommender system is represented through constructing high similarity with users who have different preference using each user's purchased item's category algorithm. It is distinguished from past research approach which is changing the algorithm of recommender system without user's diversity preference level. We tried to discover user's diversity preference level and observed the results how the effect was different according to user's diversity preference level. In addition, graph-based recommender system was used to show diversity through user's network, not collaborative filtering. In this paper, Amazon Grocery and Gourmet Food data was used because the low-involvement product, such as habitual product, foods, low-priced goods etc., had high probability to show customer's diversity. First, a bipartite graph with users and items simultaneously is constructed to make graph-based recommender system. However, each users and items unipartite graph also need to be established to show diversity of recommender system. The weight of each unipartite graph has played crucial role changing Jaccard Distance of item's category. We can observe two important results from the user's unipartite network. First, the user's diversity preference level is observed from the network and second, dissimilar users can be discovered in the user's network. Through the research process, diversity of recommender system is presented highly with small accuracy loss and optimalization for higher accuracy is possible controlling diversity ratio. This paper has three important theoretical points. First, this research expands recommender system research for user's satisfaction with various values. Second, the graph-based recommender system is developed newly. Third, the evaluation indicator of diversity is made for diversity. In addition, recommender systems are useful for corporate profit practically and this paper has contribution on business closely. Above all, business long-term profit can be improved using recommender system with diversity and the recommender system can provide right service according to user's diversity level. Lastly, the corporate selling low-involvement products have great effect based on the results.

• Culinary science and hospitality research
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• v.18 no.3
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• pp.18-31
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• 2012

The current study aimed to analyze data conducting a survey with 211 females in Ulsan Gyeongnam province in order to understand what influence lifestyle types of female customers exert on eating-out behaviors from the perspective of eating-out motivation. So as to achieve research purpose, we conducted factor analysis, reliability analysis, t-test, ANOVA analysis, multiple regression analysis, correlation analysis and frequency analysis through SPSS 12.0 program. Findings of analyses indicated that items of lifestyle involve d 4 factors, and the item of eating out behaviors was extracted to be 1 factor. As a result of testing differences in lifestyle depending on residential areas, both type of chasing fashion and type of extroverted dependence have significant differences in variables, and both factors indicated that females living in Ulsan have higher mean values than those of females living in Gyeongnam. As a result of analyzing lifestyle depending on age, which was adopted in part, females at the ages of 31~40 had higher mean values than those in other ages in the type of chasing fashion, and females above the age of 51 had higher mean values than those in other ages in type of chasing health. As a result of lifestyle depending on academic backgrounds, university students or graduates had higher mean values than those in other academic backgrounds. For the influence of lifestyle types on eating-out behaviors depending on eating-out motivation, the type of chasing fashion, the type of purchasing the quality of life, and the type of chasing health were p<0.001, having significant effects.

• The Korean Journal of Franchise Management
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• v.13 no.2
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• pp.17-31
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• 2022

Purpose: With the development of the Internet, consumers can quickly access the electronic word-of-mouth. Consumers seek to reduce uncertainty by referring to the opinions of other consumers about products and services when making purchase decisions. In the food service industry, evaluating a restaurant before an actual visitation is difficult. Therefore, electronic word-of-mouth is important to interact with the customer in restaurants. as it can be used as an exchange of information in which consumers participate and interact with other customers. This study was conducted to verify how online word-of-mouth characteristics (Consensus, Vividness, Neutrality) on attitudes and visit intention from the perspective of social exchange theory. And it was performed to verify the structural relationship between short-term visit intention, mid-term visit and long-term visit intention. Research design, data, and methodology: A survey was conducted on customers who have visited restaurants. Of a total of 312 responses, 306 responses were used, excluding insincere responses and missing values for factors analysis. SPSS 25.0 and AMOS 25.0 were used for statistical analysis, and hypothesis testing was conducted after verifying the validity and reliability of the questionnaire items. Result: The result of the analysis showed that, consensus and neutrality have a positive effect on attitude but not much on vividness. In addition, consensus, vividness, and neutrality have no effect on the short-term visit intention. Finally, the short-term visit intention has a positive effect on mid-term visit intention, and mid-term visit intention has a positive effect on long-term visit intention. Conclusions: Based on the results, this study suggested that it is necessary to have practical implications for marketing and monitoring restaurant reviews in consideration of the characteristics of electronic word-of-mouth. When managing electronic-word-of-mouth, it is necessary to manage the consensus and neutrality is essential to provide sufficient information about the restaurant. The focus should not only be on vividness, such as photos and videos. In addition, restaurants should also provide a good experience for first-time visitors as the short-term visit intention positively affects mid-term and long-term visit intention.

• The Korean Journal of Franchise Management
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• v.13 no.2
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• pp.53-66
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• 2022

Purpose: How to build the attitude on brand is very important, because it affects the positive word of mouth and revisit intention. Brand attachment, brand name, and image congruence play important role on consumer behavior in terms of reinforcing consumers' perception of food service companies and differentiating them from competing brands. Following the planned behavior theory, this paper examines the effect of linking brand attitude to word-of-mouth and revisit intentions in the restaurant sector. Research design, data, and methodology: This paper examines the structural relationship among brand attachment, brand name, image congruence, brand attitude, WOM, and revisit intention. In order to test the purposes of this study, research model and hypotheses were developed. The questionnaire items were modified and used according to the content of this study based on previous studies. All constructs were measured by multiple items tested and developed in the previous research. The study is based on the quantitative method and considered 519 questionnaires fulfilled by customers of restaurants. The data were explored employing the partial least square-structural equation modelling (PLS-SEM). Frequency analysis was conducted to identify the general characteristics of the survey subjects. To measure the reliability and validity of the measurement tools, confirmatory factor analysis was conducted. Structural model analysis was conducted to verify the research model. Result: The findings demonstrate that brand attachment and brand name had positive effects on attitude while image congruence did not have. Also, attitude had positive effect on WOM and revisit intention. Conclusions: This study expands the literature about WOM and revisit intentions. This study expands prior research in a similar field to which the theory of planned behavior (TPB) is applied, and reveals that brand attachment, brand name, and brand image congruence play an important role in developing brand attitude that affect revisit intention and WOM. And provide guidelines on how to enhance competitiveness in the restaurant sector based on understanding of linking brand attitude to customer loyalty and repeat business. By putting into practice these suggestions in the restaurant industry, brands can easily build up their attitude and boost a positive WOM and the intention to revisit.

• Journal of the East Asian Society of Dietary Life
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• v.21 no.6
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• pp.934-947
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• 2011

The purpose of this study is to analyze products for good taste and convenience, which become an engine to constantly create customers. In addition, this study is aimed at investigating the relationship between the selective attributes of Home Meal Replacement, the perceived utilitarian value, and the repurchase intention, and drawing new suggestions on the Home Meal Replacement market from a new marketing perspective. Based on a total of 215 samples, this study reviewed the reliability and fitness of the research model and verified a total of 5 hypothesized using the Amos program. The result of study modeling was GFI=0.905, AGFI=0.849, NFI=0.889, CFI=0.945, and RMR=0.0.092 at the level of $x^2$=230.22 (df=126, p<0.001). First, the food quality (${\beta}$=0.221), convenience (${\beta}$=0.334), packing (${\beta}$=0.278), and employee service (${\beta}$=0.204) of home meal replacement consideration attributes had a positive (+) influence on perceived utilitarian value. Second, perceived utilitarian value (${\beta}$=0.584) had a positive (+) influence on repurchase intention. The factors to differentiate one company from other competitors in terms of the utilitarian value are the quality of food, convenience, wrapping, and services by employees. This study has illustrated the need to focus on the development of a premium menu to compete with other companies and to continue to research and develop nutritious foods that are easy to cook. Moreover, the key factors to have a distinct and constant competitive edge over other companies are the alleviation of consumer anxiety over wrapping container materials, the development of more designs, and the accumulation of service know-how. Therefore, it is necessary for a company to strongly develop the key factors based on its resources as a core capability.

• Culinary science and hospitality research
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• v.22 no.5
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• pp.231-251
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• 2016

This study examined the effect of brand experience and personality on customer-brand relationships, brand attachment, and brand loyalty in domestic and global coffee shop brands. By comparing inter-structural relationships among factors between domestic brands and global brands, this study also provided strategic implications and directions for the effective marketing strategy of coffee shop brands. Data were collected through a self-administered survey of the consumers aged 20's to early 40's who used domestic and global brand coffee shops in Seoul and Kyunggi between August 1, 2014 and August 30, 2014. 500 surveys were distributed and 495 surveys were returned. Among them, data from 493 surveys were used for the analysis. The results from this study are as follows. First, it was found that the Think of experiences in coffee shop had a greater effect on consumer-brand relationship than the Sense-Feel. Second, the Sophistication of brand personality in coffee shop had a greater effect on consumer-brand relationship than the Excitement. Third, only Think of experience in coffee shop significantly impacted brand attachment, but Sense-Feel did not impact brand attachment. Fourth, only Excitement of brand personality in coffee shop significantly impacted brand attachment, but Sophistication did notact on brand attachment. Fifth, the consumer-brand relationship had a greater effect on brand loyalty than did brand attachment. Finally, the differences from a comparison analysis of domestic brands and global brands of coffee shop are as follows. In domestic brands, only the Sophistication of brand personality in coffee shop significantly impacted consumer-brand relationship. In global brands, the brand personality in coffee shop did not impact on consumer-brand relationship.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.85-109
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• 2018

Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.