• Title/Summary/Keyword: Brand ecommendation

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Effect of Brand Personality, Brand-Self-image Congruence and Brand Affect on SNS Brand Recommendation (SNS 브랜드개성, 자아동일시, 브랜드감정이 SNS 추천의향에 미치는 영향)

  • Ha, Ju-Yong;Han, Youngju
    • The Journal of the Korea Contents Association
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    • v.15 no.7
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    • pp.389-402
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    • 2015
  • Due to tough competition among social network services, technological specification alone could not be an adoption factor by the users. Instead, emotional factors such as a brand image and feeling towards an SNS brand became important factors in service differentiation. This study examined Korean young users perception of brand personalities of three social network services, Facebook, Kakao Story, and Band. It also analyzed the influence of the perception of brand personality, brand-self-image congruence, and brand affect on brand recommendation to others. The authors conducted a survey of Korean college students. The results indicate that SNS users perceived three SNS's brand personalities differently, and the positive perception of an SNS service has a positive effect on brand recommendation. Brand personality, brand-self-image congruence, and brand affect combined determine brand recommendation. When the brand personality variable is statistically controlled, brand affect has strong effect on brand recommendation.

A Study on Customized Brand Recommendation based on Customer Behavior for Off-line Shopping Malls (오프라인 쇼핑몰에서 고객 행위에 기반을 둔 맞춤형 브랜드 추천에 관한 연구)

  • Kim, Namki;Jeong, Seok Bong
    • Journal of Information Technology Applications and Management
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    • v.23 no.4
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    • pp.55-70
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    • 2016
  • Recently, development of indoor positioning system and IoT such as beacon makes it possible to collect and analyze each customer's shopping behavior in off-line shopping malls. In this study, we propose a realtime brand recommendation scheme based on each customer's brand visiting history for off-line shopping mall with indoor positioning system. The proposed scheme, which apply collaborative filtering to off-line shopping mall, is composed of training and apply process. The training process is designed to make the base brand network (BBN) using historical transaction data. Then, the scheme yields recommended brands for shopping customers based on their behaviors and BBN in the apply process. In order to verify the performance of the proposed scheme, simulation was conducted using purchase history data from a department store in Korea. Then, the results was compared to the previous scheme. Experimental results showd that the proposed scheme performs brand recommendation effectively in off-line shopping mall.