• Title/Summary/Keyword: Internet group buying

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Consumer Segmentation by Lifestyle and Development of e-CRM Strategies (라이프스타일에 따른 고객세분화 및 e-CRM 전략제안)

  • Ko Eunju;Kwon Joon Hee;Yun Sun Young
    • Journal of the Korean Society of Clothing and Textiles
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    • v.29 no.6
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    • pp.847-858
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    • 2005
  • The purpose of this study was to examine consumer purchasing behavior of the online shoppers particularly using online clothing shopping mall and to analyze the key factors of both satisfaction and dissatisfaction of their purchase and to compare the both group by lifestyle segmentation in order to provide the e-CRM strategies. Focus group interviews and survey were conducted in December, 2003 with 30 online shoppers who have an experience of online clothing purchasing. The data analysis included the content analysis, descriptive statistics, K-means and factor analysis. Key findings of the study were as follows: First, online shoppers spent average 3.5 hours on internet and usually purchased clothing while surfing the web. Second, consumers were satisfied with reasonable price and customized service but dissatisfied with delayed delivery, limited product availability in both size and color and return policy. Third, according to the lifestyle segmentation, online shoppers could be characterized as 'Luxurious', 'Trendy' and 'Prudent' 'Luxury-oriented consumers', who value fashion, diet and social activity, tended to purchase basic yet high quality products. However, 'Trend-oriented consumers', to whom fashion trend was most important, purchased various latest fashion products with reasonable price and showed generally positive response to emails sent by e-retailers. And lastly 'Prudence-oriented consumers', whose buying decision was based solely on practicality, appeared to be reluctant to purchase clothing online while seeking more credible information and competitive price. In conclusion, this study has its significance in that it helps promote relationships between customers and e-retailers by providing differentiated e-CRM strategies through each customer groups 'lifestyle segmentation and consumer purchasing behavior analysis.

The Impacts of Need for Cognitive Closure, Psychological Wellbeing, and Social Factors on Impulse Purchasing (인지폐합수요(认知闭合需要), 심리건강화사회인소대충동구매적영향(心理健康和社会因素对冲动购买的影响))

  • Lee, Myong-Han;Schellhase, Ralf;Koo, Dong-Mo;Lee, Mi-Jeong
    • Journal of Global Scholars of Marketing Science
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    • v.19 no.4
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    • pp.44-56
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    • 2009
  • Impulse purchasing is defined as an immediate purchase with no pre-shopping intentions. Previous studies of impulse buying have focused primarily on factors linked to marketing mix variables, situational factors, and consumer demographics and traits. In previous studies, marketing mix variables such as product category, product type, and atmospheric factors including advertising, coupons, sales events, promotional stimuli at the point of sale, and media format have been used to evaluate product information. Some authors have also focused on situational factors surrounding the consumer. Factors such as the availability of credit card usage, time available, transportability of the products, and the presence and number of shopping companions were found to have a positive impact on impulse buying and/or impulse tendency. Research has also been conducted to evaluate the effects of individual characteristics such as the age, gender, and educational level of the consumer, as well as perceived crowding, stimulation, and the need for touch, on impulse purchasing. In summary, previous studies have found that all products can be purchased impulsively (Vohs and Faber, 2007), that situational factors affect and/or at least facilitate impulse purchasing behavior, and that various individual traits are closely linked to impulse buying. The recent introduction of new distribution channels such as home shopping channels, discount stores, and Internet stores that are open 24 hours a day increases the probability of impulse purchasing. However, previous literature has focused predominantly on situational and marketing variables and thus studies that consider critical consumer characteristics are still lacking. To fill this gap in the literature, the present study builds on this third tradition of research and focuses on individual trait variables, which have rarely been studied. More specifically, the current study investigates whether impulse buying tendency has a positive impact on impulse buying behavior, and evaluates how consumer characteristics such as the need for cognitive closure (NFCC), psychological wellbeing, and susceptibility to interpersonal influences affect the tendency of consumers towards impulse buying. The survey results reveal that while consumer affective impulsivity has a strong positive impact on impulse buying behavior, cognitive impulsivity has no impact on impulse buying behavior. Furthermore, affective impulse buying tendency is driven by sub-components of NFCC such as decisiveness and discomfort with ambiguity, psychological wellbeing constructs such as environmental control and purpose in life, and by normative and informational influences. In addition, cognitive impulse tendency is driven by sub-components of NFCC such as decisiveness, discomfort with ambiguity, and close-mindedness, and the psychological wellbeing constructs of environmental control, as well as normative and informational influences. The present study has significant theoretical implications. First, affective impulsivity has a strong impact on impulse purchase behavior. Previous studies based on affectivity and flow theories proposed that low to moderate levels of impulsivity are driven by reduced self-control or a failure of self-regulatory mechanisms. The present study confirms the above proposition. Second, the present study also contributes to the literature by confirming that impulse buying tendency can be viewed as a two-dimensional concept with both affective and cognitive dimensions, and illustrates that impulse purchase behavior is explained mainly by affective impulsivity, not by cognitive impulsivity. Third, the current study accommodates new constructs such as psychological wellbeing and NFCC as potential influencing factors in the research model, thereby contributing to the existing literature. Fourth, by incorporating multi-dimensional concepts such as psychological wellbeing and NFCC, more diverse aspects of consumer information processing can be evaluated. Fifth, the current study also extends the existing literature by confirming the two competing routes of normative and informational influences. Normative influence occurs when individuals conform to the expectations of others or to enhance his/her self-image. Whereas informational influence occurs when individuals search for information from knowledgeable others or making inferences based upon observations of the behavior of others. The present study shows that these two competing routes of social influence can be attributed to different sources of influence power. The current study also has many practical implications. First, it suggests that people with affective impulsivity may be primary targets to whom companies should pay closer attention. Cultivating a more amenable and mood-elevating shopping environment will appeal to this segment. Second, the present results demonstrate that NFCC is closely related to the cognitive dimension of impulsivity. These people are driven by careless thoughts, not by feelings or excitement. Rational advertising at the point of purchase will attract these customers. Third, people susceptible to normative influences are another potential target market. Retailers and manufacturers could appeal to this segment by advertising their products and/or services as products that can be used to identify with or conform to the expectations of others in the aspiration group. However, retailers should avoid targeting people susceptible to informational influences as a segment market. These people are engaged in an extensive information search relevant to their purchase, and therefore more elaborate, long-term rational advertising messages, which can be internalized into these consumers' thought processes, will appeal to this segment. The current findings should be interpreted with caution for several reasons. The study used a small convenience sample, and only investigated behavior in two dimensions. Accordingly, future studies should incorporate a sample with more diverse characteristics and measure different aspects of behavior. Future studies should also investigate personality traits closely related to affectivity theories. Trait variables such as sensory curiosity, interpersonal curiosity, and atmospheric responsiveness are interesting areas for future investigation.

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Criteria of Evaluating Clothing and Web Service on Internet Shopping Mall Related to Consumer Involvement (인터넷 쇼핑몰 이용자의 소비자 관여에 따른 의류제품 및 웹 서비스 평가기준에 관한 연구)

  • Lee, Kyung-Hoon;Park, Jae-Ok
    • Journal of the Korean Society of Clothing and Textiles
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    • v.30 no.12 s.159
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    • pp.1747-1758
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    • 2006
  • Rapid development of the information technology has influenced on the changes in every sector of human environments. One prominent change in retail market is an increase of electronic stores, which has prompted practical and research interest in the product and store attributes that include consumer to purchase products from the electronic shopping. Therefore many marketers are paying much attention to the criteria of evaluating clothing and web service on internet shopping malls. The purpose of this study is to examine differences of clothing and web service criteria of consumer groups (High-Involvement & High-Ability, Low-Involvement & High-Ability, High-Involvement & Low-Ability, and Low-Involvement & Low-Ability) who are classified into consumer involvement and internet use ability. The subjects of this study were 305 people aged between 19 and 39s, living in Seoul and Gyeonggi-do area, and having experiences in buying products on the internet shopping. Statistical analyses used for this study were the frequency, percentage, factor analysis, ANOVA and Duncan test. The results of this study were as follows: Regarded on the criteria of evaluating clothing, the low different groups had significant differences in the esthetic, the quality performance and the extrinsic criterion. Both HIHA group and HILA group showed the similar results. They considered every criterion of evaluating clothing more important, compared with other groups. Regarded on the criteria of evaluating web service related to the low different groups, there were significant differences in the factors related to the shopping mall reliance, the product, the satisfaction after purchase, and the promotion and policy criterion. Both HIHA group and HILA group showed the similar results as well. They considered every criterion of evaluating web service more important, compared with other groups. In conclusion, HI groups perceive relatively more dangerous factors which can be occurred during internet shopping. Therefore, internet shopping malls need to provide clothing that can satisfy the HI groups as well as make efforts to remove the dangerous factors on the internet.

Fashion Trend Acceptance and Fashion Information Sources according to Clothing Shopping Orientation among Digital Generation Male Consumers (디지털세대 남성소비자의 의복쇼핑성향에 따른 패션트렌드 수용도와 패션정보원)

  • Kim, Yeo-Won;Choi, Jong-Myoung
    • The Research Journal of the Costume Culture
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    • v.17 no.2
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    • pp.238-254
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    • 2009
  • The purpose of this study were to examine fashion information acceptance and fashion information sources and to analyze the difference according to clothing shopping orientation among digital generation male consumers. The subject were 349 male who were belonging to digital generation as the digital era's new consumers familial with internet and various kinds of digital media. A self-administrated questionnaire was developed based on the results of previous researches. The data were analyzed by using frequency analysis, factor analysis, cluster analysis, ANOVA, Duncan test, $\chi^2$ test, multiple regression analysis by SPSS WIN 12.0 package. The results of this study are as follows: First, clothing shopping orientation of digital generation males were classified into 6 factors: fashion oriented, impulse buying, aesthetic pursuit, individuality pursuit, practical type and reasonable economy. Based on the factor scores, 3 clusters were identified; independent, unconcern, high involvement. Second, the high involvement shopping group utilized various information sources. On the other hand, the unconcerned shopping group was passive in utilizing information sources. Third, the fashion information acceptance of digital generation was classified into 5 factors: searching, leading, following, non-accepting, and delaying acceptance. All fashion information acceptance factors were affected by the information and communication media. Finally, The high involved type of shopping group accepted fashion information at its most and actively.

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Online to Offline Convergent Ecosystem: a Case Study of Dianping.com (온라인과 오프라인을 융북합 생태계: Dianping.com 사례연구)

  • Zhang, Chao;Wan, Lili
    • Journal of Digital Convergence
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    • v.13 no.6
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    • pp.105-111
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    • 2015
  • In this highly competitive century, selling products and service through Internet and smart phones offers both opportunities and challenges. Online commerce is expanding it's wings to the offline market. The connection between online market and offline market is called O2O(Offline to Online) market. In this study we examine the best practice case study of an Internet company's successful efforts to connect users and offline merchants. Based on Dianping.com success story in China, a successful framework for building online to offline ecosystem is examined. Dianping.com successful experience may provide suggestions for other online companies operate in the convergent field.

Designing Intelligent Agent System for Purchase Decision Making in Retail Electronic Commerce (전자상거래에서의 소비자 구매의사결정을 지원하는 지능형 에이전트 시스템의 설계)

  • Chu Seok Chin;Hong June S.
    • Journal of Intelligence and Information Systems
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    • v.10 no.2
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    • pp.147-163
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    • 2004
  • For the purchase of a cheaper product on the Internet, many customers have been trying to search online shopping mall sites and visit comparison-pricing shops that compare prices and other criteria of the product. Others have been participating into online auction markets or group-buying markets. However, a lot of online shopping malls, auction markets, and group-buying markets provide the same product with different prices. Since these marketplaces have different price settlement mechanism, it is very difficult for the customers to determine marketplace to purchase, considering different kinds of marketplaces at the same time. To overcome such limitations, decision rules and solution procedures for purchase decision making are necessary, which can cover multiple marketplaces simultaneously. For this purpose, purchase decision making in each market must be conducted to maximize customer's utility, and conflicts with other marketplaces must be resolved. Therefore, we have developed the rules and methods that can negotiate cooperatively the purchase decision making in several marketplaces, and designed an architecture of Intelligent Buyer Agent and a message structure to support the idea.

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Design and Implementation of Chronic Disease Risk Analysis System according to Personalized Food Intake Preferences (개인 식품섭취 선호도에 따른 만성질환 발생 위험도 분석 시스템 설계 및 구현)

  • Jeon, So Hye;Kim, Nam Hyun
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.3
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    • pp.147-155
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    • 2014
  • While variety of content on the internet has increased with the development of IT and person's needs about suitable information are increasing rapidly, studies for personalized service have been actively performed. In the study, we proposed the Hypertension and Diabetes risk analysis system according to personal food intake preference using the analysis method of buying preferences in product recommendation system. For the analysis of food intake preference, the Pearson correlation coefficient is used to calculate similarity weights between each reference analysis data and sample data and then reference data should be grouping into the similarity weights and calculating risk of hypertension and diabetes each group. To evaluate the significance of this system, 1,021 subjects are applied the system. Hypertension and diabetes groups' risk is significant higher than normal group statistically so, it is confirmed that food intake preference and the diseases were relevant. In this paper, we verify the validity of hypertension and diabetes risk analysis system using a personal food intake preference.

An Integrated QoS Management System for Large-Scale Heterogeneous IP Networks : Design and Prototype Implementation (대규모 이기종 IP 망의 통합품질관리 시스템의 설계 및 구현)

  • Choi, Tae-Sang;Chung, Hyung-Seok;Choi, Hee-Sook;Kim, Chang-Hoon;Jeong, Tae-Soo
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.11S
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    • pp.3633-3650
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    • 2000
  • Internet is no longer a network for special communities but became a global means of communication infrastructure for everyday life. People are exchanging their personal messages using e-mails, students are getting their educational aids through the web, people are buying a variety of goods from cyber shopping malls, and companies are conducting their businesses over the Internet. Recently, such an explosive growth of the traffic in the Internet raised a big concern on how to accommodate ever-changing user's needs in terms of an amount of the traffic, characteristics of the traffic, and various service quality requirements, Over provisioning can be a simple solution but it is too expensive and inefficient. Thus many new technologies to solve this very difficult puzzle have bcen introduced recently, Any single solution, however, can be insufficient and a carefully designed architecture, which integrates a group of solutions, is required. In this paper, we propose a policy-based Internet QoS provisioning, traffic engineering and perfonnance management system as our solution to this problem. Our integrated management QoS solution can provide highly responsive flow-through service provisioning, more realistic service and resource policy control based on the real network performance information, and centralized control of traffic engineering for heterogeneous networks.

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A Study on the Purchasing Behavior and Usage of Environmentally Friendly Clothing and the Disposal of Clothing (친환경적 의복구매행동과 의복활용 및 처분행동에 관한 연구)

  • Han, Sung-Hee
    • Journal of Families and Better Life
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    • v.27 no.3
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    • pp.61-77
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    • 2009
  • This study investigates the disposal of clothing and the purchasing behavior and usage of environmentally friendly clothing. After compiling data from 500 consumers who reside in Seoul, it was analyzed by ANOVA, t-test, Chi-square, and multiple regression analysis. The behavioral score for buying environmentally friendly clothing was lower than the average value of the three. The lowest value was for the purchase of used clothing, but the purchase of environmentally friendly clothing was also shown to have a low value. For the usage and disposal of clothing, unused clothing, which was mostly just left in dresser drawers, was the most preferable method. Also, exchange or resale via anInternet mall was shown to be lower than the other methods. The analysis between clothing purchase and usage as well as the disposal of clothing with socio-demographics, consumption tendencies, opinions of friends and groups, commercials and advertisements, and environmental perceptions points out differences among groups. There are statistically significant differences in the purchasing intentions of slow fashion according to socio-demographics. Female consumers between $20{\sim}25$ years of age were more likely to purchase slow fashion clothing. Consumers with a high consumption tendency who were highly influenced by commercials, friends, and groups were more likely to purchase slow fashion clothing. The influence of the average clothing expenditure on an environmentally friendly purchasing behavior and the influence of the age group on repairing and usagewas the most effective. All in all, contribution to an environmentally friendly perception was the most effective variable.

The Research on Recommender for New Customers Using Collaborative Filtering and Social Network Analysis (협력필터링과 사회연결망을 이용한 신규고객 추천방법에 대한 연구)

  • Shin, Chang-Hoon;Lee, Ji-Won;Yang, Han-Na;Choi, Il Young
    • Journal of Intelligence and Information Systems
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    • v.18 no.4
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    • pp.19-42
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    • 2012
  • Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.