• The Korean Journal of Community Living Science
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• v.16 no.4
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• pp.47-57
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• 2005

To investigate the characteristics of edible flowers as a food material, we have examined the kinds, colors, sizes, fresh weights, pigments and shipping periods of edible flowers marketed on the cropping farms, selling agencies and Internet shopping malls from February through September, 2005. Thirty six kinds of edible flowers were marketed in Korea, and all but the chrysanthemum were introduced species. The characteristics of edible flowers were shown differently by the varieties following the same kinds of flowers. Those colors were yellow (twenty five kinds), red (twenty three), pink (twenty), white (eighteen), and orange (sixteen). Flower diameters were measured and showed that seven kinds of edible flowers were 1.0 to 2.0cm, fourteen 2.0 to 3.0cm, sixteen 3.0 to 4.0cm, eight 4.0 to 5.0cm, and nine over 5.0cm. Flower fresh weights were measured as follows: twenty one kinds of edible flowers were under 0.5g ($58.3\%$), eight were $0.6\∼1.0g(22.2\%$), and six were $1.1{\∼}1.5g(16.7\%$). The taste of edible flowers was often bitter (twenty one kinds), sweet and sour (seven), somewhat fragrant (six), fishy (three), and others (nine). The pigments of edible flowers were anthoxanthin (twenty seven kinds), flavonoid (twenty three), carotenoid (seventeen), and betanidin (four).

• The Journal of Information Systems
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• v.25 no.1
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• pp.1-23
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• 2016

Purpose Self-congruity deals with the effect of symbolic value-expressive attributes on consumer decision and behavior, which is the theoretical foundation of the "non-utilitarian destination positioning". Functional congruity refers to utilitarian evaluation of a product or service by consumers. In addition, recent years, social network services, especially mobile social network services have created many opportunities for e-WOM communication that enables consumers to share personal consumption related information anywhere at any time. Moreover, self-construal is a hot and popular topic that has been discussed in the field of modem psychology as well as in marketing area. This study aims to examine the moderating effect of self-construal on the relationship between self-congruity, functional congruity and tourists' positive electronic word of mouth (e-WOM). Design/methodology/approach In order to verify the hypotheses, we developed a questionnaire with 32 survey items. We measured all the items on a five-point Likert-type scale. We used Sojump.com to collect questionnaire and gathered 218 responses from whom have visited Korea before. After a pilot test, we analyzed the main survey data by using SPSS 20.0 and AMOS 18.0, and employed structural equation modeling to test the hypotheses. We first estimated the measurement model for its overall fit, reliability and validity through a confirmatory factor analysis and used common method bias test to make sure that whether measures are affected by common-method variance. Then we tested the hypotheses through the structural model and used regression analysis to measure moderating effect of self-construal. Findings The results reveal that the effect of self-congruity on tourists' positive e-WOM is stronger for tourists with an independent self-construal compared with those with interdependent self-construal. Moreover, it shows that the effect of functional congruity on tourists' positive e-WOM becomes salient when tourists' self-construal is primed to be interdependent rather than independent. We expect that the results of this study can provide important implications for academic and practical perspective.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.239-250
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• 2020

The purpose of this paper is to explore the influence of the "contextualization" effect of web celebrity live broadcast on the e-commerce platform on consumers' perception of product value, risk and purchase intention. Live in this paper, using Taobao shopping consumers as the research object, the survey method, questionnaire survey is adopted, the form through the questionnaire and distributed network, a live in order to further validation of web celebrity effect of contextualized actual influence on consumer purchase intention, questionnaire design the Likert scale, seven and recycling questionnaire analysis using the statistical software SPSS 23.0 and AMOS 22.0 after processing the data. After determining the reliability and validity of the questionnaire, the exploratory factor analysis was used to verify the hypothesis and calculate the actual adjustment degree of the "contextualization" effect of web celebrity live broadcasting on consumers' purchase intention. The research results of this paper are summarized as follows :(1) consumers' perceived value of products can significantly positively affect their purchase intention, while perceived risk has a significantly negative impact on their purchase intention; (2) consumers' trust and purchase intention to products are regulated by the "contextualization" of web celebrity live broadcast. Specifically, for web celebrity live broadcasting with good "contextualization" effect, the perceived value of consumer products has a positive impact on product trust, which is higher than that of web celebrity live broadcasting with poor "contextualization" effect. In terms of resolving consumers' perceived risks to products, web celebrity live broadcast with good "contextualization" effect is also significantly better than web celebrity live broadcast with poor "contextualization" effect. Based on empirical analysis, this paper concludes that web celebrity live broadcasting will become a new breakthrough for the sustainable growth of the e-commerce industry, and puts forward Suggestions on the e-commerce marketing mode and the transformation of web celebrity live broadcasting industry.

• The Korean Journal of Archival Studies
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• no.16
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• pp.147-200
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• 2007

Archives provide users with easier and more convenient access to and use of archival data through their Internet websites. Now, archival websites function not only as a tool of information provision or marketing, or as a gateway of Internet-based materials, but also as cyber space for all services of archives, providing users with information and knowledge and direct accessibility to the services in the archives. At present, Korean archives are proceeding with establishing websites or upgrading existing websites, and the use rates and reliability of web services by users are becoming higher. However, although there have been various studies for the evaluation of general websites, few are found with regard to the evaluation of archival websites. It is necessary for archival websites that provide information service to users of every stripe to make more efforts and have more interest in user-centered convenience, right to know, and information provision-centered service. Accordingly, needless to say, it is necessary to study evaluation criteria of websites so that high quality archival websites can be established. With this background, this study establishes evaluation criteria for archival websites, which are appropriate to their objectives and functions and directly evaluates archives, presenting ways to establish and redevelop archival websites. More detailed purposes are as follows: First, analyzes existing theories of evaluation through reviews on previous literature and elicits evaluation criteria for websites, which are appropriate to archives; Second, based on the elicited evaluation criteria for archival websites, examines the current state of domestic archival websites through analytic evaluation; and Third, presents ways to improve archival websites that may be helpful in establishing or improving them in the future. The expectancy effects of this study are as follows: First, it will be helpful when one wishes to identify the current state of archival websites and to improve or redevelop existing websites, or to develop online service through website; Second, it will function as a checklist when a developer who is to establish an archival website wishes to develop evaluation criteria; and Third, it may be used as an inspection tool when an archives contracts out the establishment of its website.

• Management & Information Systems Review
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• v.38 no.2
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• pp.183-208
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• 2019

The purpose of this study is to examine the effects of the transformational leadership on helping behaviors and deviant behaviors of organizational members and to verify the control effect of value consistency and to suggest a process for effective business management and human resource management. For this purpose, questionnaires were distributed to employees working in office management, area marketing, and manufacturing industries in Seoul, Gyeonggi and Chungcheong provinces, and the final 334 copies were used for empirical analysis. Data were analyzed using SPSS 18.0, and reliability analysis, factor analysis for validity, correlation analysis, and regression analysis were conducted to verify the research hypothesis. The results of the empirical analysis based on the questionnaire based on the object are as follows. First, charisma of transformational leadership showed negative impact on helping behavior, and intellectual stimulation of transformational leadership and individual care showed positive influence on helping behavior. Second, charisma of transformational leadership showed negative influence on deviant behavior, whereas intellectual stimulation of transformational leadership and sub - constitutional factor of individual care did not show significant influence on deviant behavior. Third, as a result of confirming the moderating role of transformational leadership and helping behavior on the level of value consistency, it showed moderating effects on charisma and individual consideration of transformational leadership. Through this study, we proved the effectiveness of transformative leadership which increases the helping behaviors of the members and reduces the deviant behavior. Based on this, we proposed the necessity of developing managers' transformational leadership improvement program to enhance the sustainability of the organization. And we confirmed the partial influence relationship on the adjustment effect of value consistency. In addition, negative influence of charisma suggests a significant point in the management process design.

• Journal of Global Scholars of Marketing Science
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• v.19 no.2
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• pp.68-79
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• 2009

The interplay between hedonic and utilitarian attributes has assumed special significance in recent years; it has been proposed that consumption offerings should be viewed as experiences that stimulate both cognitions and feelings rather than as mere products or services. This research builds on previous work on hedonic versus utilitarian benefits, regulatory focus theory, customer satisfaction to address two question: (1) Is the shopping goal at the point of purchase different from the shopping value? and (2) Is the customer loyalty after the use different from the shopping value and shopping goal? We surveyed 345 peoples those who have bought the electronic-goods within 6 months. This research dealt with the shopping value which is consisted of 2 types, hedonic and utilitarian. Those who pursue the hedonic shopping value may prefer the pleasure of purchasing experience to the product itself. They tend to prefer atmosphere, arousal of the shopping experience. Consistent with previous research, we use the term "hedonic" to refer to their aesthetic, experiential and enjoyment-related value. On the contrary, Those who pursue the utilitarian shopping value may prefer the reasonable buying. It may be more functional. Consistent with previous research, we use the term "utilitarian" to refer to the functional, instrumental, and practical value of consumption offerings. Holbrook(1999) notes that consumer value is an experience that results from the consumption of such benefits. In the context of cell phones for example, the phone's battery life and sound volume are utilitarian benefits, whereas aesthetic appeal from its shape and color are hedonic benefits. Likewise, in the case of a car, fuel economics and safety are utilitarian benefits whereas the sunroof and the luxurious interior are hedonic benefits. The shopping goals are consisted of the promotion focus goal and the prevention focus goal, based on the self-regulatory focus theory. The promotion focus is characterized into focusing ideal self because they are oriented to wishes and vision. The promotion focused individuals are tend to be more risk taking. They are more sensitive to hope and achievement. On the contrary, the prevention focused individuals are characterized into focusing the responsibilities because they are oriented to safety. The prevention focused individuals are tend to be more risk avoiding. We wanted to test the relation among the shopping value, shopping goal and customer loyalty. Customers show the positive or negative feelings comparing with the expectation level which customers have at the point of the purchase. If the result were bigger than the expectation, customers may feel positive feeling such as delight or satisfaction and they would want to share their feelings with other people. And they want to buy those products again in the future time. There is converging evidence that the types of goals consumers expect to be fulfilled by the utilitarian dimension of a product are different from those they seek from the hedonic dimension (Chernev 2004). Specifically, whereas consumers expect the fulfillment of product prevention goals on the utilitarian dimension, they expect the fulfillment of promotion goals on the hedonic dimension (Chernev 2004; Chitturi, Raghunathan, and Majahan 2007; Higgins 1997, 2001) According to the regulatory focus theory, prevention goals are those that ought to be met. Fulfillment of prevention goals in the context of product consumption eliminates or significantly reduces the probability of a painful experience, thus making consumers experience emotions that result from fulfillment of prevention goals such as confidence and securities. On the contrary, fulfillment of promotion goals are those that a person aspires to meet, such as "looking cool" or "being sophisticated." Fulfillment of promotion goals in the context of product consumption significantly increases the probability of a pleasurable experience, thus enabling consumers to experience emotions that result from the fulfillment of promotion goals. The proposed conceptual framework captures that the relationships among hedonic versus utilitarian shopping values and promotion versus prevention shopping goals respectively. An analysis of the consequence of the fulfillment and frustration of utilitarian and hedonic value is theoretically worthwhile. It is also substantively relevant because it helps predict post-consumption behavior such as the promotion versus prevention shopping goals orientation. Because our primary goal is to understand how the post consumption feelings influence the variable customer loyalty: word of mouth (Jacoby and Chestnut 1978). This research result is that the utilitarian shopping value gives the positive influence to both of the promotion and prevention goal. However the influence to the prevention goal is stronger. On the contrary, hedonic shopping value gives influence to the promotion focus goal only. Additionally, both of the promotion and prevention goal show the positive relation with customer loyalty. However, the positive relation with promotion goal and customer loyalty is much stronger. The promotion focus goal gives the influence to the customer loyalty. On the contrary, the prevention focus goal relates at the low level of relation with customer loyalty than that of the promotion goal. It could be explained that it is apt to get framed the compliment of people into 'gain-non gain' situation. As the result, for those who have the promotion focus are motivated to deliver their own feeling to other people eagerly. Conversely the prevention focused individual are more sensitive to the 'loss-non loss' situation. The research result is consistent with pre-existent researches. There is a conceptual parallel between necessities-needs-utilitarian benefits and luxuries-wants-hedonic benefits (Chernev 2004; Chitturi, Raghunathan and Majaha 2007; Higginns 1997; Kivetz and Simonson 2002b). In addition, Maslow's hierarchy of needs and the precedence principle contends luxuries-wants-hedonic benefits higher than necessities-needs-utilitarian benefits. Chitturi, Raghunathan and Majaha (2007) show that consumers are focused more on the utilitarian benefits than on the hedonic benefits of a product until their minimum expectation of fulfilling prevention goals are met. Furthermore, a utilitarian benefit is a promise of a certain level of functionality by the manufacturer or the retailer. When the promise is not fulfilled, customers blame the retailer and/or the manufacturer. When negative feelings are attributable to an entity, customers feel angry. However in the case of hedonic benefit, the customer, not the manufacturer, determines at the time of purchase whether the product is stylish and attractive. Under such circumstances, customers are more likely to blame themselves than the manufacturer if their friends do not find the product stylish and attractive. Therefore, not meeting minimum utilitarian expectations of functionality generates a much more intense negative feelings, such as anger than a less intense feeling such as disappointment or dissatisfactions. The additional multi group analysis of this research shows the same result. Those who are unsatisfactory customers who have the prevention focused goal shows higher relation with WOM, comparing with satisfactory customers. The research findings in this article could have significant implication for the personal selling fields to increase the effectiveness and the efficiency of the sales such that they can develop the sales presentation strategy for the customers. For those who are the hedonic customers may be apt to show more interest to the promotion goal. Therefore it may work to strengthen the design, style or new technology of the products to the hedonic customers. On the contrary for the utilitarian customers, it may work to strengthen the price competitiveness. On the basis of the result from our studies, we demonstrated a correspondence among hedonic versus utilitarian and promotion versus prevention goal, WOM. Similarly, we also found evidence of the moderator effects of satisfaction after use, between the prevention goal and WOM. Even though the prevention goal has the low level of relation to WOM, those who are not satisfied show higher relation to WOM. The relation between the prevention goal and WOM is significantly different according to the satisfaction versus unsatisfaction. In addition, improving the promotion emotions of cheerfulness and excitement and the prevention emotion of confidence and security will further improve customer loyalty. A related potential further research could be to examine whether hedonic versus utilitarian, promotion versus prevention goals improve customer loyalty for services as well. Under the budget and time constraints, designers and managers are often compelling to choose among various attributes. If there is no budget or time constraints, perhaps the best solution is to maximize both hedonic and utilitarian dimension of benefits. However, they have to make trad-off process between various attributes. For the designers and managers have to keep in mind that without hedonic benefit satisfaction of the product it may hard to lead the customers to the customer loyalty.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.95-108
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• 2017

Recently, AlphaGo which is Bakuk (Go) artificial intelligence program by Google DeepMind, had a huge victory against Lee Sedol. Many people thought that machines would not be able to win a man in Go games because the number of paths to make a one move is more than the number of atoms in the universe unlike chess, but the result was the opposite to what people predicted. After the match, artificial intelligence technology was focused as a core technology of the fourth industrial revolution and attracted attentions from various application domains. Especially, deep learning technique have been attracted as a core artificial intelligence technology used in the AlphaGo algorithm. The deep learning technique is already being applied to many problems. Especially, it shows good performance in image recognition field. In addition, it shows good performance in high dimensional data area such as voice, image and natural language, which was difficult to get good performance using existing machine learning techniques. However, in contrast, it is difficult to find deep leaning researches on traditional business data and structured data analysis. In this study, we tried to find out whether the deep learning techniques have been studied so far can be used not only for the recognition of high dimensional data but also for the binary classification problem of traditional business data analysis such as customer churn analysis, marketing response prediction, and default prediction. And we compare the performance of the deep learning techniques with that of traditional artificial neural network models. The experimental data in the paper is the telemarketing response data of a bank in Portugal. It has input variables such as age, occupation, loan status, and the number of previous telemarketing and has a binary target variable that records whether the customer intends to open an account or not. In this study, to evaluate the possibility of utilization of deep learning algorithms and techniques in binary classification problem, we compared the performance of various models using CNN, LSTM algorithm and dropout, which are widely used algorithms and techniques in deep learning, with that of MLP models which is a traditional artificial neural network model. However, since all the network design alternatives can not be tested due to the nature of the artificial neural network, the experiment was conducted based on restricted settings on the number of hidden layers, the number of neurons in the hidden layer, the number of output data (filters), and the application conditions of the dropout technique. The F1 Score was used to evaluate the performance of models to show how well the models work to classify the interesting class instead of the overall accuracy. The detail methods for applying each deep learning technique in the experiment is as follows. The CNN algorithm is a method that reads adjacent values from a specific value and recognizes the features, but it does not matter how close the distance of each business data field is because each field is usually independent. In this experiment, we set the filter size of the CNN algorithm as the number of fields to learn the whole characteristics of the data at once, and added a hidden layer to make decision based on the additional features. For the model having two LSTM layers, the input direction of the second layer is put in reversed position with first layer in order to reduce the influence from the position of each field. In the case of the dropout technique, we set the neurons to disappear with a probability of 0.5 for each hidden layer. The experimental results show that the predicted model with the highest F1 score was the CNN model using the dropout technique, and the next best model was the MLP model with two hidden layers using the dropout technique. In this study, we were able to get some findings as the experiment had proceeded. First, models using dropout techniques have a slightly more conservative prediction than those without dropout techniques, and it generally shows better performance in classification. Second, CNN models show better classification performance than MLP models. This is interesting because it has shown good performance in binary classification problems which it rarely have been applied to, as well as in the fields where it's effectiveness has been proven. Third, the LSTM algorithm seems to be unsuitable for binary classification problems because the training time is too long compared to the performance improvement. From these results, we can confirm that some of the deep learning algorithms can be applied to solve business binary classification problems.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.53-77
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• 2015

Mobile commerce provides a convenient shopping experience in which users can buy products without the constraints of time and space. Mobile commerce has already set off a mega trend in Korea. The market size is estimated at approximately 15 trillion won (KRW) for 2015, thus far. In the Korean market, social commerce and open market are key components. Social commerce has an overwhelming open market in terms of the number of users in the Korean mobile commerce market. From the point of view of the industry, quick market entry, and content curation are considered to be the major success factors, reflecting the rapid growth of social commerce in the market. However, academics' empirical research and analysis to prove the success rate of social commerce is still insufficient. Henceforward, it is to be expected that social commerce and the open market in the Korean mobile commerce will compete intensively. So it is important to conduct an empirical analysis to prove the differences in user experience between social commerce and open market. This paper is an exploratory study that shows a comparative analysis of social commerce and the open market regarding user experience, which is based on the mobile users' reviews. Firstly, this study includes a collection of approximately 10,000 user reviews of social commerce and open market listed Google play. A collection of mobile user reviews were classified into topics, such as perceived usefulness and perceived ease of use through LDA topic modeling. Then, a sentimental analysis and co-occurrence analysis on the topics of perceived usefulness and perceived ease of use was conducted. The study's results demonstrated that social commerce users have a more positive experience in terms of service usefulness and convenience versus open market in the mobile commerce market. Social commerce has provided positive user experiences to mobile users in terms of service areas, like 'delivery,' 'coupon,' and 'discount,' while open market has been faced with user complaints in terms of technical problems and inconveniences like 'login error,' 'view details,' and 'stoppage.' This result has shown that social commerce has a good performance in terms of user service experience, since the aggressive marketing campaign conducted and there have been investments in building logistics infrastructure. However, the open market still has mobile optimization problems, since the open market in mobile commerce still has not resolved user complaints and inconveniences from technical problems. This study presents an exploratory research method used to analyze user experience by utilizing an empirical approach to user reviews. In contrast to previous studies, which conducted surveys to analyze user experience, this study was conducted by using empirical analysis that incorporates user reviews for reflecting users' vivid and actual experiences. Specifically, by using an LDA topic model and TAM this study presents its methodology, which shows an analysis of user reviews that are effective due to the method of dividing user reviews into service areas and technical areas from a new perspective. The methodology of this study has not only proven the differences in user experience between social commerce and open market, but also has provided a deep understanding of user experience in Korean mobile commerce. In addition, the results of this study have important implications on social commerce and open market by proving that user insights can be utilized in establishing competitive and groundbreaking strategies in the market. The limitations and research direction for follow-up studies are as follows. In a follow-up study, it will be required to design a more elaborate technique of the text analysis. This study could not clearly refine the user reviews, even though the ones online have inherent typos and mistakes. This study has proven that the user reviews are an invaluable source to analyze user experience. The methodology of this study can be expected to further expand comparative research of services using user reviews. Even at this moment, users around the world are posting their reviews about service experiences after using the mobile game, commerce, and messenger applications.

• Journal of Distribution Research
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• v.16 no.4
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• pp.1-27
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• 2011

Introduction: Sales of private labels(PU have been growing m recent years. Globally, PLs have already achieved 20% share, although between 25 and 50% share in most of the European markets(AC. Nielson, 2005). These products are aimed to have comparable quality and prices as national brand(NB) products and have been continuously eroding manufacturer's national brand market share. Stores have also started introducing premium PLs that are of higher-quality and more reasonably priced compared to NBs. Worldwide, many retailers already have a multiple-tier private label architecture. Consumers as a consequence are now able to have a more diverse brand choice in store than ever before. Since premium PLs are priced higher than regular PLs and even, in some cases, above NBs, stores can expect to generate higher profits. Brand extensions and private label have been extensively studied in the marketing field. However, less attention has been paid to the private label extension. Therefore, this research focuses on private label extension using the Multi-Attribute Attitude Model(Fishbein and Ajzen, 1975). Especially there are few studies that consider the hierarchical effect of the PL's two parent brands: store brand and the original PL. We assume that the attitude toward each of the two parent brands affects the attitude towards the extended PL. The influence from each parent brand toward extended PL will vary according to the perceived fit between each parent brand and the extended PL. This research focuses on how these two parent brands act as reference points to one another in the consumers' choice consideration. Specifically we seek to understand how store image and attitude towards original PL affect consumer perceptions of extended premium PL. How consumers perceive extended premium PLs could provide strategic suggestions for retailer managers with specific suggestions on whether it is more effective: to position extended premium PL similarly or dissimilarly to original PL especially on the quality dimension and congruency with store image. There is an extensive body of research on branding and brand extensions (e.g. Aaker and Keller, 1990) and more recently on PLs(e.g. Kumar and Steenkamp, 2007). However there are no studies to date that look at the upgrading and influence of original PLs and attitude towards store on the premium PL extension. This research wishes to make a contribution to this gap using the perceived fit difference between parent brands and extended premium PL as the context. In order to meet the above objectives, we investigate which factors heighten consumers' positive attitude toward premium PL extension. Research Model and Hypotheses: When considering the attitude towards the premium PL extension, we expect four factors to have an influence: attitude towards store; attitude towards original PL; perceived congruity between the store image and the premium PL; perceived similarity between the original PL and the premium PL. We expect that all these factors have an influence on consumer attitude towards premium PL extension. Figure 1 gives the research model and hypotheses. Method: Data were collected by an intercept survey conducted on consumers at discount stores. 403 survey responses were attained (total 59.8% female, across all age ranges). Respondents were asked to respond to a series of Questions measured on 7 point likert-type scales. The survey consisted of Questions that measured: the trust towards store and the original PL; the satisfaction towards store and the original PL; the attitudes towards store, the original PL, and the extended premium PL; the perceived similarity of the original PL and the extended premium PL; the perceived congruity between the store image and the extended premium PL. Product images with specific explanations of the features of premium PL, regular PL and NB we reused as the stimuli for the Question response. We developed scales to measure the research constructs. Cronbach's alphaw as measured each construct with the reliability for all constructs exceeding the .70 standard(Nunnally, 1978). Results: To test the hypotheses, path analysis was conducted using LISREL 8.30. The path analysis for verification of the model produced satisfactory results. The validity index shows acceptable results(${\chi}^2=427.00$(P=0.00), GFI= .90, AGFI= .87, NFI= .91, RMSEA= .062, RMR= .047). With the increasing retailer use of premium PLBs, the intention of this research was to examine how consumers use original PL and store image as reference points as to the attitude towards premium PL extension. Results(see table 1 & 2) show that the attitude of each parent brand (attitudes toward store and original pL) influences the attitude towards extended PL and their perceived fit moderates these influences. Attitude toward the extended PL was influenced by the relative level of perceived fit. Discussion of results and future direction: These results suggest that the future strategy for the PL extension needs to consider that positive parent brand attitude is more strongly associated with the attitude toward PL extensions. Specifically, to improve attitude towards PL extension, building and maintaining positive attitude towards original PL is necessary. Positioning premium PL congruently to store image is also important for positive attitude. In order to improve this research, the following alternatives should also be considered. To improve the research model's predictive power, more diverse products should be included in study. Other attributes of product should also be included such as design, brand name since we only considered trust and satisfaction as factors to build consumer attitudes.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.221-241
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• 2018

Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.