• Journal of Distribution Science
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• v.13 no.9
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• pp.81-93
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• 2015

Purpose - "Showrooming" refers to the phenomenon where a shopper visits a store to see and compare products but makes the purchase online at a lower price. Surveys on showrooming activities at home and abroad indicate that a significant number of consumers pursue showrooming activities. The advent of "showroomers," who engage in buying activities, hovering both on and offline, while selectively choosing sales channels to suit their needs, is powerful enough to erode the borders between channels and bring about seismic changes in the distribution industry. However, surprisingly, there has been no in-depth discussion on showrooming. This study seeks to theoretically investigate what impact personal characteristics have on showrooming preferences and attitudes in a multi-channel environment. Specifically, assumptions have been made that price perception, perceived performance risk, and trust in online shopping not only have a direct impact on showrooming attitudes but also indirectly affect it through the means of contact motivation. Research design, data, and methodology - To test the hypotheses, this study conducted a survey of male and female shoppers, ages 20 through 40s, who live in metropolitan areas, and have actively showroomed fashion items in the last six months. A clothing item usually purchased after a careful decision-making process was chosen as the target product of the study. The survey was conducted between October and November 2014, using a professional survey service provider. A total of 200 surveys were collected, of which 198 were used for analysis. Conceptual model Structural Equation Modeling (SEM) and Amos 18.0 were employed for data analysis and model verification. In addition, following the confirmatory factor analysis and measurement model analysis, the theoretical model that corresponds to the research model was analyzed. Results - Analysis results show that price perception, perceived performance risk, and trust in online shopping have a statistically significant and positive (+) impact on showrooming attitudes. In addition, in terms of the indirect influence of price perception and perceived performance risk on showrooming attitudes through means of contact motivation, price perception had a statistically significant and positive impact on means of contact motivation, whereas perceived performance risk did not have a statistically significant impact on it, with the relevant hypothesis rejected. Conclusions - These analysis results imply that the ultimate goal of consumers is to maximize their shopping benefits by selectively and strategically taking advantage of different channels in a complementary manner. This study presents many implications for distributors to encourage a deep understanding of showrooming consumers who have complicated consumption behaviors and to build channel integration strategies. This study has limitations in theoretical and practical implications. Therefore, subsequent studies need to focus on verifying that showrooming activities are based on reasonable and planned decisions by applying the theory of reasoned or planned behavior. In addition, the scope of the study should expand to include web showrooming, where consumers conduct product research online and purchase offline.

• Journal of Information Technology Services
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• v.7 no.4
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• pp.1-19
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• 2008

This study began with the proposition that, compared to the impulse buying in the conventional offline market, consumers will exhibit a different process of decision-making for impulse buying on the Internet as it has become easier to acquire information and purchase goods which are offered online like digital contents goods. To verify this roposition, this study attempted to find out the external and internal factors as that affect the impulse buying behavior by incorporating Theory of Planned Behavior In addition, this study seeks to confirm the role of alternative's attractiveness in terms of mediating between internal and internal factors affecting impulse buying. The major purpose of this study was to understand Impulse Buying Intention(IBI) for digital contents on the internet. The results of the this study showed that the behavior of impulse buying can be explained with the information searching in which the external factors for the marketing of digital contents affect the internal stimulation factors. It was also found that the impulse buying of digital contents on the Internet starts with non-planned impulse at the problem recognition stage, but planned decision-making will take over when it is proven to be effective with information searching.

• Knowledge Management Research
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• v.23 no.2
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• pp.253-276
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• 2022

Online reviews attract much attention because they play an essential role in consumer decision-making. Therefore, it is necessary to investigate the review attributes that affect the perceived helpfulness of consumers. However, most previous studies on the helpfulness of online reviews mainly focus on quantitative factors such as review volume and reviewer attributes. Recently, some studies have investigated the impact of review content and linguistic style matching on consumers' purchase decision-making. Those studies show that consumers consider additional review attributes when evaluating reviews in decision-making. To fill the research gap with existing literature, we investigated the impact of review content and linguistic style matching on review helpfulness. Moreover, this study investigated how the reviewers' expertise moderates the effect of the review content and linguistic style matching on the review helpfulness. The empirical results show that positive affective content has a negative effect on the review helpfulness. The negative affective content and linguistic style matching positively affect review helpfulness. Review expertise relieved the impact of negative affective content and linguistic style matching on review helpfulness. According to the mechanism confirmed in this study, online e-commerce companies can achieve corporate sales growth by identifying factors affecting review helpfulness and reflecting them in their marketing strategies.

• Journal of Information Technology Applications and Management
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• v.26 no.2
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• pp.41-60
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• 2019

O2O(Online-to-Offline) commerce, a kind of multi-channel, is used in various industries such as accommodation, food and beverage, transportation, and real estate. The O2O commerce, a channel of integrating online and offline, overcomes the limitations of traditional online commerce, where a customer made a purchase decision without direct experience. Despite this advantage of O2O, if the online-offline channel is not effectively linked, customer's complaints would occur due to service failure. This study, with regard to O2O service failure circumstances, intends to investigate the effect of customer's perceived justice on their emotional response, recovery satisfaction, followed by intention to repurchase. Perceived justice in this study is composed of distributive justice, interactional justice, and procedural justice. Furthermore, this study explores the moderation effect of O2O industry types in the relationship between perceived justice and emotion. An O2O industry type is classified into accommodation, food and beverage, and transportation. A hypothesized research model was empirically tested using a structural equation model. The current study collected 433 questionnaires and the target respondents are customers who have experienced service failure in O2O commerce. The empirical results showed that O2O commerce more effectively conducts service recovery strategy and causes positive customer response by integrating online and offline channel. One of the ultimate purposes of O2O service providers is to reduce the likelihood of service failures and to recover more quickly and efficiently by linking two channels rather than using a single channel. This study suggested that the O2O channel is effective in influencing customer satisfaction and loyalty by inducing customer's positive emotions in recovering service failure.

• Journal of the Korean Society of Clothing and Textiles
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• v.41 no.1
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• pp.170-183
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• 2017

The rapid growth of digital consumption has significantly changed the shopping behavior of consumers. The consumption paradigm is changing; subsequently, an omni-channel has been introduced that empowers consumers to interact with firms through a myriad of touch points in multiple channels. This study is to understand the perceptions and behavioral characteristics of consumers in the purchase process (e.g., information search and purchase phase). A qualitative method was adopted for this study and data were collected through semi-structured in-depth interviews with 15 omni-channel consumers. The results of this study were as follows. At the information search stage, consistency was the most important consideration for consumers who also wanted to retain channel-specific benefits. Consumers also searched for differentiated information among distribution channels. At the purchase stage, participants choose a shopping channel according to shopping values. They utilized newly introduced services (e.g., "online purchase, offline pick-up", FinTech) that combine retail channels. Our findings provide significance in managing omni-channel services. First, it is recommended that fashion retailers provide seamlessly integrated experience to consumer and adopt a consumer-centered channel choice strategy. Second, fashion retailers must maintain a constant attitude toward shopping experience to fashion, such as shopping enjoyment and exclusiveness.

• International Journal of Advanced Culture Technology
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• v.5 no.4
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• pp.15-19
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• 2017

With the increased economic profit in China, people tend to give more attention to the nurturing of children. The change in the food markets directly connected to the infants' health seem to have brought various consumption patterns different than before. Based on the actual condition survey operated by this research, the expansion in the scale of consumption and preference to the imported food for infants appeared in the Chinese food markets for infants. The rapidly increased amount of the online purchases of the food for Chinese infants was checked through the condition survey. Based on the analysis results, with the purpose of increasing the purchase opportunities of the Korean food for infants to the Chinese consumers, it should not only perform the promotion activities such as the promotion for the product's superiority and various promotional event, but also establish the pricing strategy for each entry step to the Chinese market. Because the purchase experience of the Korean food for infant plays the important role for the additional payments decision, it is estimated that there is a need to expand the opportunities for the Chinese consumers to approach the Korean food for infants both directly and indirectly.

• Journal of Korean Society for Quality Management
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• v.39 no.2
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• pp.217-233
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• 2011

This paper introduces service failure management on internet shopping environment. The purpose of this study is to find and improve service failure modes at the time of customer's complaint thereby reducing that. To achieve this purpose, this study combines the Service Blueprint which describes the online shopping process and FMEA which finds each encounter of service failures and proposes how to recover them. First of all this study generates internet shopping process using Service Blueprint then matches customer's purchase decision making process and company's service provide process. After this process customer complaint types in real purchasing process are fell in according to their occurrence and more frequently occurred complaint is more risky. Finally 6 Risk Priority Numbers(unfair exchange/return policies, slow response/poor customer service support, purchase arrived later than promised/deliverly service dissatisfaction, dissatisfaction short period to take back/exchange/cancels order, A/S or handle defective item) are extracted and suggest their improvement.

• CRM연구
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• v.2 no.2
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• pp.71-88
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• 2009

The purpose of this thesis is to examine the effects of e-CRM activities by the internet shopping mall companies on the purchase activities of purchase customers and the potential customers. The internet shopping companies utilize e-CRM to systematically identify customers' varying demands, and to utilize the results as marketing tools, thus producing a significant effect on the potential customers by generating customer feedback through e-Community. Contrary to their intention, however, cognitive dissonance can occur through e-Community, which may lead to customers' complaints. If these complaints are not properly managed and settled in a timely manner, they can be transferred to other potential customers, and the conformity phenomenon could be created by other complaining customers. Findings obtained through this thesis are as follows: If cognitive disharmony is created by customers who purchased products through the internet shopping malls, this can lead to private complaining behaviors, and subsequently, these behaviors are formed through e-Community. If the internet shopping mall companies do not take any timely and proper measures to intervene in the stage of private complaining behaviors in the first place, these behaviors will immediately escalate into the public complaining behaviors. Furthermore, the complaints will be transferred to other potential customers, ultimately resulting in their swift expansion. In other words, contrary to intention of the internet shopping mall companies, e-CRM does not facilitate the potential customers purchase decision, it rather affects them to postpone or withdraw their purchase decision. Accordingly, the internet shopping mall companies are required to manage e-Community with extreme care, and they should promptly respond to the complaining customers so that e-Community can function properly.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Journal of Distribution Science
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• v.13 no.4
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• pp.45-53
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• 2015

Purpose - Online shopping enables consumers to conveniently purchase products irrespective of the time and place. As a result, several online shopping companies have emerged to cater to this growing market and, therefore, the competition among them has become increasingly intense. This paper evaluates the comparative efficiency of online shopping companies for a multi-year period (2009-2013), in order to help online shopping managers identify major drivers for enhancing management efficiency and the subsequent competitiveness. Research design, data, and methodology - The researchers collected the data from 2009 to 2013 from the distribution yearbook. This paper analyzes the marketability (sales figures), profitability (business profits), and management conditions (net profits) of domestic online shopping enterprises by incorporating information on human resources (number of employees) and material resources (total assets and capital). Therefore, the number of employees, total assets, and capital are selected as input variables, and sales figures, business profits, and net profits as the output variables. In this study, Data Envelopment Analysis (DEA) was used to measure the comparative efficiency of domestic online shopping companies. In addition, the Malmquist Productivity Index was used to evaluate the trend of change of Decision Making Units' (DMUs') efficiency for a multi-year period. Results - First, as of 2013, Interpark (2.415) was found to be the most efficient online shopping enterprise, followed by Aladdin Communications (2.117), Hyundai Home shopping (1.867), Home&Shopping (1.176), NS Home shopping (1.170), Commerce Planet (1.126), CJ O Shopping (1.105), Ebay Korea (1.088), and GS Home Shopping (1.051). Second, this study recognizes how the management efficiency has changed for the period 2009-2013. Third, the lesser the capital and employees, the more are the net profits, and the better is the management efficiency of domestic online shopping companies. Lastly, the productivity of such companies is influenced by endogenous factors rather than exogenous factors such as shifts in business environment and technological advances. Conclusions - DHC Korea influenced various distribution channels to reach customers through the Internet. Consequently, this helped in increasing the awareness about its products, in addition to an increase in sales. These achievements can be attributed to the characteristics of online shopping companies. Although it is easy for these companies to suggest goods for one-off purchases, they however have difficulties in retaining customers. Overcoming this challenge can be one of the ways to benchmark a successful case of an efficient company. For example, an online shopping company can attract customers by developing a corresponding mobile application as a convenient way to shop online. Additionally, they can satisfy customers by quick delivery of purchased products, which is possible by building an effective logistics network. Our study indicates that the productivity of an online shopping company was influenced by endogenous factors driven by improvements in managerial practices rather than exogenous factors. Accordingly, online shopping companies should adopt strategies to improve their operational efficiency rather than sales volume-oriented management.