• Title/Summary/Keyword: the product categorization model

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A Study on the Product Categorization Model for Efficient Search in On-line Chartering

  • Choi, Hyung-Rim;Park, Nam-kyu;Park, Young-Jae;Park, Yong-Sung;Kang, Si-Hyeob
    • Journal of Navigation and Port Research
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    • v.27 no.3
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    • pp.307-313
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    • 2003
  • Off-line ship chartering is done nearly through the brokers. Because of the international scale of chartering market, brokers spend too much times and costs on searching the most appropriate product which the consumers want. In this research, we propose the on-line Charter Product Categorization Model to search the products efficiently in the Cyber Chartering System. This Model will make concerned parties of the ship chartering to get unified product information efficiently, and the select the most appropriate product. In this research, we classified the ship chartering products into categories of cargo, ship type, and sea routes, and defined mutual relation of each products, and we verified that this classification is necessary to search the products through the product searching experiment.

A Study on the Effect of Complementary Bundling Based on the Categorization of the New Hybrid IT Product (하이브리드 IT신제품의 범주화에 따른 보완재 번들링의 효과성에 관한 연구)

  • Park, Yoonseo;Kim, Yongsik
    • Journal of Information Technology Services
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    • v.13 no.4
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    • pp.19-43
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    • 2014
  • Categorization means the process labeling or identifying an object based on what people already know or its similarity for people to be easily perceptible in external environment. If it is categorized, it is schematically conjectured from typical characteristic of the category. In this sense, the categorization of new products has an important effect upon the market performance. Nevertheless, the categorization of innovative new products is not easy and occasionally very ambiguous. In this study, we discuss how to strengthen the categorization strategy of new hybrid IT products through complementary bundling. The model of this study is based on Technology Acceptance Model (TAM) with resistance variable and verifies the statistical significance by undertaking a survey on consumers' awareness. In addition, we review the moderating effects of prior knowledge in the adoption process of complementary bundling. Through this analysis, we find out the structural relationship among the factors affecting adoption of complementary bundling. Also, it show that the influence of prior knowledge in respect of the adoption process is greater than others in case that there exists significant heterogeneity among strategic categories and complements. In conclusion, these findings suggest the following managerial implication. The categorization strategy of new hybrid IT product can be enhanced by complementary bundling, but the suitability among strategic category and complements should be evaluated exhaustively.

A study on The Product Categorization Model based efficient search in on-line chartering (온라인 용선거래에서 상품분류체계 기반의 검색 효율성에 관한 연구)

  • 최형림;박남규;박영재;박용성;강시협
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2003.05a
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    • pp.265-272
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    • 2003
  • Off-line ship chartering is done nearly through(by) the brokers. Because of the international scale of chartering marker, brokers spend too much times and costs on searching the most appropriate product which the consumers want. In this research, we propose the on-line Charter Product Categorization Model to search the products efficiently in the Cyber Chartering System. This Model will make concerned parties of the ship chartering to get efficient and unific product information. and to select the most appropriate product. In this research, we classified the ship chartering products into categories of cargo, ship type, and sea routes, and formed the definition of mutual relation of each products. Moreover we verified that this classification is necessary to search the products by the product searching experiment.

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A Deep Learning Model for Extracting Consumer Sentiments using Recurrent Neural Network Techniques

  • Ranjan, Roop;Daniel, AK
    • International Journal of Computer Science & Network Security
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    • v.21 no.8
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    • pp.238-246
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    • 2021
  • The rapid rise of the Internet and social media has resulted in a large number of text-based reviews being placed on sites such as social media. In the age of social media, utilizing machine learning technologies to analyze the emotional context of comments aids in the understanding of QoS for any product or service. The classification and analysis of user reviews aids in the improvement of QoS. (Quality of Services). Machine Learning algorithms have evolved into a powerful tool for analyzing user sentiment. Unlike traditional categorization models, which are based on a set of rules. In sentiment categorization, Bidirectional Long Short-Term Memory (BiLSTM) has shown significant results, and Convolution Neural Network (CNN) has shown promising results. Using convolutions and pooling layers, CNN can successfully extract local information. BiLSTM uses dual LSTM orientations to increase the amount of background knowledge available to deep learning models. The suggested hybrid model combines the benefits of these two deep learning-based algorithms. The data source for analysis and classification was user reviews of Indian Railway Services on Twitter. The suggested hybrid model uses the Keras Embedding technique as an input source. The suggested model takes in data and generates lower-dimensional characteristics that result in a categorization result. The suggested hybrid model's performance was compared using Keras and Word2Vec, and the proposed model showed a significant improvement in response with an accuracy of 95.19 percent.

AraProdMatch: A Machine Learning Approach for Product Matching in E-Commerce

  • Alabdullatif, Aisha;Aloud, Monira
    • International Journal of Computer Science & Network Security
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    • v.21 no.4
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    • pp.214-222
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    • 2021
  • Recently, the growth of e-commerce in Saudi Arabia has been exponential, bringing new remarkable challenges. A naive approach for product matching and categorization is needed to help consumers choose the right store to purchase a product. This paper presents a machine learning approach for product matching that combines deep learning techniques with standard artificial neural networks (ANNs). Existing methods focused on product matching, whereas our model compares products based on unstructured descriptions. We evaluated our electronics dataset model from three business-to-consumer (B2C) online stores by putting the match products collectively in one dataset. The performance evaluation based on k-mean classifier prediction from three real-world online stores demonstrates that the proposed algorithm outperforms the benchmarked approach by 80% on average F1-measure.

The Design.Marketing Strategies for Korean Traditional Sauces by emotion-oriented Categorization (감성지향적 범주화를 통한 장류제품의 디자인.마케팅 전략)

  • Lee, Yu-Ri;Yang, Jong-Youl;Park, Sang-June
    • Science of Emotion and Sensibility
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    • v.10 no.3
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    • pp.491-502
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    • 2007
  • Categorization is very important for product design. Consumer's emotion become different according to a type of categorization, so design concept and design elements must be combined differently with difference of the emotion. Specially, categorization process is necessary if nowadays product line is enlarged, and a product differentiation is not clear. That is, designers decide on correct categories and a design concept based on similarity of emotion and have to provide to consumer-oriented design. The purpose of this study is to provide a design direction for Korean traditional sauce products after extracting consumers' sensitivity from the whole image of Korean traditional sauce and each images of the sauces-korean hot pepper paste, soybean paste, fermented soybeans paste, SsamJang, and soy sauce- and deciding categories of the each sauces based on the extracted sensitivities' similarity. In the result of this study, we knew that Korean traditional sauces didn't differentiate from consumers' preference images. In our empirical research, the research - emotional image survey on sauces - have conclusion that emotional image of "well-being", "tasty" have positive influence, but emotional image of "messy and dirty", "smelly" have negative influence. Therefore, we suggest that positive emotional images like "tasty" should be emphasized, but negative emotional images like "messy" should be eliminated for design and marketing strategy of Korean traditional sauces. This research will suggest the guideline for product design with respect to academic aspects and working-level aspects.

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Identification of Demand Type Differences and Their Impact on Consumer Behavior: A Case Study Based on Smart Wearable Product Design

  • Jialei Ye;Xiaoyou He;Ziyang Liu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.4
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    • pp.1101-1121
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    • 2024
  • Thorough understanding of user demands and formulation of product development strategies are crucial in product design, and can effectively stimulate consumer behavior. Scientific categorization and classification of demands contribute to accurate design development, design efficiency, and success rates. In recent years, e-commerce has become important consumption platforms for smart wearable products. However, there are few studies on product design and development among those related to promoting platform product services and sales. Meanwhile, design strategies focusing on real consumer needs are scarce among smart wearable product design studies. Therefore, an empirical consumer demand analysis method is proposed and design development strategies are formulated based on a categorized interpretation of demands. Using representative smart bracelets from wearable smart products as a case, this paper classifies consumer demands with three methods: big data semantic analysis, KANO model analysis, and satisfaction analysis. The results reveal that analysis methods proposed herein can effectively classify consumer demands and confirm that differences in consumer demand categories have varying impacts on consumer behavior. On this basis, corresponding design strategies are proposed based on four categories of consumer demands, aiming to make product design the leading factor and promote consumer behavior on e-commerce platforms. This research further enriches demand research on smart wearable products on e-commerce platforms, and optimizes products from a design perspective, thereby promoting consumption. In future research, different data analysis methods will be tried to compare and analyze changes in consumer demands and influencing factors, thus improving research on impact factors of product design in e-commerce.

Online Purchase Intentions for Product Categories -The Functions of Internet Motivations and Online Buying Tendencies- (상품 범주별 온라인 구매도 -인터넷 동기와 온라인 구매성향 기능-)

  • Kim, Eun-Young
    • Journal of the Korean Society of Clothing and Textiles
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    • v.32 no.6
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    • pp.890-901
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    • 2008
  • This study explores an initial framework for online product categorization by examining the relationships among Internet motivations, buying tendencies, and online purchase intentions for product categories. A total of 217 usable questionnaires were obtained from respondents in a southwestern state in the United States. A path model using a correlation matrix with maximum likelihood was estimated using LISREL 8.53. Findings indicated that Internet motivations consisted of four factors: Diversion, Economic, Information, and Social motivations. In addition, online products were classified into three categories based on purchase intentions: Sensory, Cognitive, and Search products. Estimated path model showed that diversion and economic motivations affected impulse buying tendency, whereas economic, information and social motivations influenced planned buying tendency in the online context. Also, the buying tendencies were significantly related to online purchase intentions for the product categories. Purchase intentions for sensory products were more strongly affected by impulse buying tendency, whereas purchase intentions for cognitive and search products were more strongly affected by planned buying tendency. Theoretical and managerial implications were discussed for devising an appropriate e-market strategy for specific product categories.

Perceptional Change of a New Product, DMB Phone

  • Kim, Ju-Young;Ko, Deok-Im
    • Journal of Global Scholars of Marketing Science
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    • v.18 no.3
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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.

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Categorization of UX method based on UX expert's competence model (UX 전문가의 역량 모델에 기반한 수행역량유사도에 따른 UX 방법론 분류에 대한 연구)

  • Lee, Ahreum;Kang, Hyo Jin;Kwon, Gyu Hyun
    • Design Convergence Study
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    • v.16 no.4
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    • pp.1-16
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    • 2017
  • As the local manufacturing industry has entered a phase of stagnation, service and product design based on user experience has been highlighted as an alternative for the innovation. However, SMEs(Small and Medium-sized Enterprises) are still struggling to overcome the current crisis. One of the reasons is that SMEs do not have enough contact points with the validated UX firms and experts. Thus, SMEs has a high barrier to invest in new opportunity area, user experience. In this study, we aim to figure out UX experts' competence to perform the UX method to solve the UX problems based on the KSA framework(Knowledge, Skill, Attitude). Based on the literature review and expert workshop, we grouped the UX method according to the similarity of the competence required to conduct the method. With cluster analysis, 5 different groups of UX method were defined based on the competence, Panoramic Analysis, Meticulous Observation and Analysis, Intuitive Interpretation, Agile Visualization, and Logical Inspection. The results would be applied to compose a portfolio of UX experts and to implement a mechanism that could recommend the professional experts to the company.