• 지능정보연구
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• 제23권4호
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• pp.77-110
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• 2017

최근 인터넷 기반의 웹 및 모바일 기기를 통한 소비 패턴의 다양화와 개성화가 급진전됨에 따라 전통적 유통채널인 오프라인 매장의 효율적 운영이 더욱 중요해졌다. 매장의 매출과 수익 모두를 제고하기 위해 매장은 소비자에게 가장 매력적인 상품을 적시에 공급-판매 해야 하는데 많은 상품들 중에서 어떤 SKU를 취급하는 것이 판매 확률을 높이고 재고 비용을 낮출 수 있는지에 대한 연구가 부족한 실정이다. 특히, 여러 지역에 걸쳐 다수의 오프라인 매장을 통해 상품을 판매하는 기업의 경우 고객에게 매력적인 적절한 SKU를 추천 받아 취급할 수 있다면 매장의 매출 및 수익률 제고에 도움이 될 것이다. 본 연구에서는 개인화 추천에 이용되어 왔던 협업 필터링과 하이브리드 필터링 등의 추천 시스템(Recommender System)을 국가별, 지역별로 복수의 판매 매장을 통해 동종 브랜드를 취급하는 유통 기업의 매장 단위 취급 SKU 추천 방식을 제안하였다. 각 매장의 취급 품목별 구매 데이터를 활용하여 각 매장 별 유사성(Similarity)을 계산하고 각 매장의 SKU별 판매 이력에 따라 협업 필터링을 하여 최종적으로 매장에 개별 SKU를 추천하였다. 또한 매장 프로파일 데이터를 활용하여 주변수 분석 (PCA : Principal Component Analysis) 및 군집 분석(Clustering)을 통하여 매장을 4개의 군집으로 분류한 뒤 각 군집 내에서 협업 필터링을 적용한 하이브리드 필터링 방식으로 추천 시스템을 구현하고 실제 판매 데이터를 바탕으로 두 방식의 성능을 측정하였다. 현존하는 대부분의 추천 시스템은 사용자에게 영화, 음악 등의 아이템을 추천하는 방식으로 연구가 진행되어 왔고 실제로 산업계에서의 적용 또한 개인화 추천 시스템이 주류를 이루고 있다. 그 동안 개인화 서비스 영역에서 주로 다루어져 왔던 이러한 추천 시스템을 동종 브랜드를 취급하는 유통 기업의 매장 단위에 적용하여 각 매장의 취급 SKU를 추천하는 방식에 대한 연구는 거의 이루어지지 않고 있는 실정이다. 기존 추천 방법론의 추천 적용 대상이 '개인의 영역이었다면 본 연구에서는 국가별, 지역별로 복수의 판매 매장을 통해 개인의 영역을 넘어 매장의 영역으로 확대하여 동종 브랜드를 취급하는 유통 기업의 매장 단위 취급 SKU 추천 방식을 제안하고 있다. 또한 기존의 추천시스템은 온라인에 한정되었다면 이를 오프라인으로 활용 범위를 넓히고, 기존 개인을 기반으로 분석을 하는 것보다 매장영역으로 확대 적용하기에 적합한 알고리즘을 개발하기 위해 데이터마이닝 기법을 적용하여 추천 방법을 제안한다. 본 연구의 결과가 갖는 의의는 개인화 추천 알고리즘을 동일 브랜드를 취급하는 복수의 판매 매장에 적용하여 의미 있는 결과를 도출하고 실제 기업을 대상으로 시스템으로 구축하여 활용할 수 있는 구체적 방법론을 제시했다는 데에 있다. 개인화 영역을 위주로 이루어졌던 기존의 추천 시스템과 관련한 학계의 연구 영역을 동종 브랜드를 취급하는 기업의 판매 매장으로 확장시킨 첫 시도라는 데에도 의미가 있다. 2014년 03주차 ~ 05주차 전(全) 매장 판매 수량 실적 Top 100개 SKU로 추천의 대상을 한정하여 협업 필터링과 하이브리드 필터링 방식으로 52개 매장 별로 취급 SKU를 추천하고, 추천 받은 SKU에 대한 2014년 06주차 매장별 판매 실적을 집계하여 두 추천 방식의 성과를 비교하였다. 두 추천 방식을 비교한 이유는 본 연구의 추천 방법이 기존 추천 방식 보다 높은 성과를 입증하기 위해 단순히 오프라인에 협업필터링을 적용한 것을 기준 모델로 정의하였다. 이 기준 모델에 오프라인 매장 관점의 특성을 잘 반영한 본 연구 모델인 하이브리드 필터링 방법과 비교 함으로써 성과를 입증한다. 연구에서 제안한 방식은 기존 추천 방식보다 높은 성과를 나타냈으며, 이는 국내 대기업 의류업체의 실제 판매데이터를 활용하여 입증하였다. 본 연구는 개인 수준의 추천시스템을 그룹수준으로 확장하여 효율적으로 접근하는 방법을 이론적인 프레임 워크를 만들었을 뿐 아니라 실제 데이터를 기반으로 분석하여 봄으로써 실제 기업들이 적용해 볼 수 있다는 점에서 연구의 가치가 크다.

• 마케팅과학연구
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• 제20권3호
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• pp.231-238
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• 2010

本研究的焦点是品牌的拟人化. 品牌拟人化被定义为将品牌看作是人类. 具体来说, 本研究的目标是理解如何将品牌拟人化的方法. 通过分析消费者对食品包装上的故事的阅读, 我们试图展示行销者和消费者如何将一系列品牌拟人化并创造意义. 我们的研究问题是一个品牌对不同的消费者具有多个或单一意义, 联想, 个性的可能性. 我们首先强调了本研究在理论和实践方面的重要性, 解释了为什么我们关注作为品牌意义传递工具的包装. 然后我们阐述了我们量性研究方法, 讨论了结果. 最后总结了管理方面的启示和对未来研究的建议. 本研究先让消费者直接阅读品牌意义传递的工具然后让这些消费者口头自由表达他们所感受到的意义. 具体来说, 为了获得有关感知意义的数据, 我们要求参与者去阅读选择的品牌食品包装上的非营养的故事. 包装在消费者研究方面还没有得到足够的关注(Hine, 1995). 直到现在, 研究还是仅关注包装的实用功能并形成了探索营养信息的影响的研究主体. (例如Lourei ro, McCluskey and Mittelhammer, 2002; Mazis and Raymond, 1997; Nayga, Lipinski and Savur, 1998; Wansik, 2003). 一个例外是最近的研究, 将注意力转向非营养信息的包装说明, 并视其为文化产品和将品牌神话的工具(Kniazeva and Belk, 2007). 下一步就是探索这些神话活动如何影响品牌个性感知以及这些感知如何与消费者相关. 这些都是本研究所要强调的. 我们用深度访谈来帮助消除量性研究的局限性. 我们的便利样本的构成具有人口统计和消费心态学的多样化以达到获得消费者对包装故事的不同的感知. 我们的参与者是美国的中产居民, 并没有表现出Thompson(2004)所描述的 "文化创造者" 的极端生活方式. 九名参与者被采访关于他们食品消费偏好和行为的问题. 他们被要求看看12个展示的食品产品包装并阅读包装上的文字信息. 之后, 我们继续进行关注消费者对阅读材料的解释的问题. (Scott and Batra, 2003). 平均来看, 每个参与者感知4-5个包装. 我们的深度访谈是一对一的并长达半个小时. 采访内容被录音下来并转录, 最后有140页的文字. 产品赖在位于美国西海岸的当地食品杂货店, 这些产品代表了食品产品类别的基本范围, 包括零食, 罐装食品, 麦片, 婴儿食品和茶. 我们使用Strauss和Corbin (1998)提出的发展扎根理论的步骤来分析数据. 结果表明, 我们的研究不支持先前的研究所假设的一个品牌/一个个性的概念. 因此我们展示了在消费者看来多个品牌个性可以在同一品牌身上很好的共存, 尽管行销者试图创造更多单一的品牌个性. 我们延伸了Fournier's (1998) 的假设, 某人的人生计划可以形成与品牌关系的强度和本质. 我们发现这些人生计划也影响感知的品牌拟人化和意义. Fournier提出了把消费者人生主题(Mick和Buhl, 1992)和拟人化产品的相关作用联系在一起的概念框架. 我们发现消费者人生计划形成了把品牌拟人化和品牌与消费者现有的关注相关联的方式. 我们通过参与者发现了两种品牌拟人化的方法. 第一种, 品牌个性通过感知的人口统计, 消费心态学和社会个性所创造. 第二, 第二, 在我们的研究还涉及到品牌的消费者所存在的问题与消费者的个性被混合, 以连接到他们(品牌为朋友, 家庭成员, 隔壁邻居)或远离自己的品牌个性和疏远他们(品牌作为二手车推销员, "一群高管".) 通过关注食品产品包装, 我们阐明了非常具体的, 被广泛使用, 但很少深入研究的营销传播工具: 品牌故事. 近期的研究已经视包装为神话制造者. 对行销者来说要创作出和产品及消费它们的消费者相连的文字故事的挑战越来越大, 并建议 "为创造需求的消费者神话的构成材料的多样化是后现代消费者可论证的需求"(Kniazeva和Belk, 2007). 作为叙述故事的的工具, 食品包装可以食品包装可以用理性和感性的方式, 为消费者提供无论是 "讲座" 或 "戏剧"(Randazzo, 2006), 神话(Kniazeva and Belk, 2007; Holt, 2004; Thompson, 2004), 或意义(McCracken, 2005) 作为他们拟人化产品的构成材料. 孕育工艺品牌个性掌握在作家/营销人员手中, 在读者/消费者心目中. 这些消费者会赋予品牌有意义的脸谱.

• 마케팅과학연구
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• 제18권3호
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• pp.59-88
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• 2008

Digital Convergence means integration between industry, technology, and contents, and in marketing, it usually comes with creation of new types of product and service under the base of digital technology as digitalization progress in electro-communication industries including telecommunication, home appliance, and computer industries. One can see digital convergence not only in instruments such as PC, AV appliances, cellular phone, but also in contents, network, service that are required in production, modification, distribution, re-production of information. Convergence in contents started around 1990. Convergence in network and service begins as broadcasting and telecommunication integrates and DMB(digital multimedia broadcasting), born in May, 2005 is the symbolic icon in this trend. There are some positive and negative expectations about DMB. The reason why two opposite expectations exist is that DMB does not come out from customer's need but from technology development. Therefore, customers might have hard time to interpret the real meaning of DMB. Time is quite critical to a high tech product, like DMB because another product with same function from different technology can replace the existing product within short period of time. If DMB does not positioning well to customer's mind quickly, another products like Wibro, IPTV, or HSPDA could replace it before it even spreads out. Therefore, positioning strategy is critical for success of DMB product. To make correct positioning strategy, one needs to understand how consumer interprets DMB and how consumer's interpretation can be changed via communication strategy. In this study, we try to investigate how consumer perceives a new product, like DMB and how AD strategy change consumer's perception. More specifically, the paper segment consumers into sub-groups based on their DMB perceptions and compare their characteristics in order to understand how they perceive DMB. And, expose them different printed ADs that have messages guiding consumer think DMB in specific ways, either cellular phone or personal TV. Research Question 1: Segment consumers according to perceptions about DMB and compare characteristics of segmentations. Research Question 2: Compare perceptions about DMB after AD that induces categorization of DMB in direction for each segment. If one understand and predict a direction in which consumer perceive a new product, firm can select target customers easily. We segment consumers according to their perception and analyze characteristics in order to find some variables that can influence perceptions, like prior experience, usage, or habit. And then, marketing people can use this variables to identify target customers and predict their perceptions. If one knows how customer's perception is changed via AD message, communication strategy could be constructed properly. Specially, information from segmented customers helps to develop efficient AD strategy for segment who has prior perception. Research framework consists of two measurements and one treatment, O1 X O2. First observation is for collecting information about consumer's perception and their characteristics. Based on first observation, the paper segment consumers into two groups, one group perceives DMB similar to Cellular phone and the other group perceives DMB similar to TV. And compare characteristics of two segments in order to find reason why they perceive DMB differently. Next, we expose two kinds of AD to subjects. One AD describes DMB as Cellular phone and the other Ad describes DMB as personal TV. When two ADs are exposed to subjects, consumers don't know their prior perception of DMB, in other words, which subject belongs 'similar-to-Cellular phone' segment or 'similar-to-TV' segment? However, we analyze the AD's effect differently for each segment. In research design, final observation is for investigating AD effect. Perception before AD is compared with perception after AD. Comparisons are made for each segment and for each AD. For the segment who perceives DMB similar to TV, AD that describes DMB as cellular phone could change the prior perception. And AD that describes DMB as personal TV, could enforce the prior perception. For data collection, subjects are selected from undergraduate students because they have basic knowledge about most digital equipments and have open attitude about a new product and media. Total number of subjects is 240. In order to measure perception about DMB, we use indirect measurement, comparison with other similar digital products. To select similar digital products, we pre-survey students and then finally select PDA, Car-TV, Cellular Phone, MP3 player, TV, and PSP. Quasi experiment is done at several classes under instructor's allowance. After brief introduction, prior knowledge, awareness, and usage about DMB as well as other digital instruments is asked and their similarities and perceived characteristics are measured. And then, two kinds of manipulated color-printed AD are distributed and similarities and perceived characteristics for DMB are re-measured. Finally purchase intension, AD attitude, manipulation check, and demographic variables are asked. Subjects are given small gift for participation. Stimuli are color-printed advertising. Their actual size is A4 and made after several pre-test from AD professionals and students. As results, consumers are segmented into two subgroups based on their perceptions of DMB. Similarity measure between DMB and cellular phone and similarity measure between DMB and TV are used to classify consumers. If subject whose first measure is less than the second measure, she is classified into segment A and segment A is characterized as they perceive DMB like TV. Otherwise, they are classified as segment B, who perceives DMB like cellular phone. Discriminant analysis on these groups with their characteristics of usage and attitude shows that Segment A knows much about DMB and uses a lot of digital instrument. Segment B, who thinks DMB as cellular phone doesn't know well about DMB and not familiar with other digital instruments. So, consumers with higher knowledge perceive DMB similar to TV because launching DMB advertising lead consumer think DMB as TV. Consumers with less interest on digital products don't know well about DMB AD and then think DMB as cellular phone. In order to investigate perceptions of DMB as well as other digital instruments, we apply Proxscal analysis, Multidimensional Scaling technique at SPSS statistical package. At first step, subjects are presented 21 pairs of 7 digital instruments and evaluate similarity judgments on 7 point scale. And for each segment, their similarity judgments are averaged and similarity matrix is made. Secondly, Proxscal analysis of segment A and B are done. At third stage, get similarity judgment between DMB and other digital instruments after AD exposure. Lastly, similarity judgments of group A-1, A-2, B-1, and B-2 are named as 'after DMB' and put them into matrix made at the first stage. Then apply Proxscal analysis on these matrixes and check the positional difference of DMB and after DMB. The results show that map of segment A, who perceives DMB similar as TV, shows that DMB position closer to TV than to Cellular phone as expected. Map of segment B, who perceive DMB similar as cellular phone shows that DMB position closer to Cellular phone than to TV as expected. Stress value and R-square is acceptable. And, change results after stimuli, manipulated Advertising show that AD makes DMB perception bent toward Cellular phone when Cellular phone-like AD is exposed, and that DMB positioning move towards Car-TV which is more personalized one when TV-like AD is exposed. It is true for both segment, A and B, consistently. Furthermore, the paper apply correspondence analysis to the same data and find almost the same results. The paper answers two main research questions. The first one is that perception about a new product is made mainly from prior experience. And the second one is that AD is effective in changing and enforcing perception. In addition to above, we extend perception change to purchase intention. Purchase intention is high when AD enforces original perception. AD that shows DMB like TV makes worst intention. This paper has limitations and issues to be pursed in near future. Methodologically, current methodology can't provide statistical test on the perceptual change, since classical MDS models, like Proxscal and correspondence analysis are not probability models. So, a new probability MDS model for testing hypothesis about configuration needs to be developed. Next, advertising message needs to be developed more rigorously from theoretical and managerial perspective. Also experimental procedure could be improved for more realistic data collection. For example, web-based experiment and real product stimuli and multimedia presentation could be employed. Or, one can display products together in simulated shop. In addition, demand and social desirability threats of internal validity could influence on the results. In order to handle the threats, results of the model-intended advertising and other "pseudo" advertising could be compared. Furthermore, one can try various level of innovativeness in order to check whether it make any different results (cf. Moon 2006). In addition, if one can create hypothetical product that is really innovative and new for research, it helps to make a vacant impression status and then to study how to form impression in more rigorous way.