• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.27-42
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• 2020

Traditional companies with offline stores were unable to secure large display space due to the problems of cost. This limitation inevitably allowed limited kinds of products to be displayed on the shelves, which resulted in consumers being deprived of the opportunity to experience various items. Taking advantage of the virtual space called the Internet, online shopping goes beyond the limits of limitations in physical space of offline shopping and is now able to display numerous products on web pages that can satisfy consumers with a variety of needs. Paradoxically, however, this can also cause consumers to experience the difficulty of comparing and evaluating too many alternatives in their purchase decision-making process. As an effort to address this side effect, various kinds of consumer's purchase decision support systems have been studied, such as keyword-based item search service and recommender systems. These systems can reduce search time for items, prevent consumer from leaving while browsing, and contribute to the seller's increased sales. Among those systems, recommender systems based on association rule mining techniques can effectively detect interrelated products from transaction data such as orders. The association between products obtained by statistical analysis provides clues to predicting how interested consumers will be in another product. However, since its algorithm is based on the number of transactions, products not sold enough so far in the early days of launch may not be included in the list of recommendations even though they are highly likely to be sold. Such missing items may not have sufficient opportunities to be exposed to consumers to record sufficient sales, and then fall into a vicious cycle of a vicious cycle of declining sales and omission in the recommendation list. This situation is an inevitable outcome in situations in which recommendations are made based on past transaction histories, rather than on determining potential future sales possibilities. This study started with the idea that reflecting the means by which this potential possibility can be identified indirectly would help to select highly recommended products. In the light of the fact that the attributes of a product affect the consumer's purchasing decisions, this study was conducted to reflect them in the recommender systems. In other words, consumers who visit a product page have shown interest in the attributes of the product and would be also interested in other products with the same attributes. On such assumption, based on these attributes, the recommender system can select recommended products that can show a higher acceptance rate. Given that a category is one of the main attributes of a product, it can be a good indicator of not only direct associations between two items but also potential associations that have yet to be revealed. Based on this idea, the study devised a recommender system that reflects not only associations between products but also categories. Through regression analysis, two kinds of associations were combined to form a model that could predict the hit rate of recommendation. To evaluate the performance of the proposed model, another regression model was also developed based only on associations between products. Comparative experiments were designed to be similar to the environment in which products are actually recommended in online shopping malls. First, the association rules for all possible combinations of antecedent and consequent items were generated from the order data. Then, hit rates for each of the associated rules were predicted from the support and confidence that are calculated by each of the models. The comparative experiments using order data collected from an online shopping mall show that the recommendation accuracy can be improved by further reflecting not only the association between products but also categories in the recommendation of related products. The proposed model showed a 2 to 3 percent improvement in hit rates compared to the existing model. From a practical point of view, it is expected to have a positive effect on improving consumers' purchasing satisfaction and increasing sellers' sales.

• Journal of Global Scholars of Marketing Science
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• v.18 no.3
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• pp.115-132
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• 2008

Metal industry is one of the most representative heavy industries and the median sales volume of steel and nonferrous metal companies is over one billion dollars in the case America [Forbes 2006]. As seen in the recent business market situation, an increasing number of industrial manufacturers and suppliers are moving from adversarial to cooperative exchange attitudes that support the long-term relationships with their customers. This article presents the results of an empirical study of the antecedent factors of business relationships in metal industry of the United States. Commitment has been reviewed as a significant and critical variable in research on inter-organizational relationships (Hong et al. 2007, Kim et al. 2007). The future stability of any buyer-seller relationship depends upon the commitment made by the interactants to their relationship. Commitment, according to Dwyer et al. [1987], refers to "an implicit or explicit pledge of relational continuity between exchange partners" and they consider commitment to be the most advanced phase of buyer-seller exchange relationship. Bonds are made because the members need their partners in order to do something and this integration on a task basis can be either symbiotic or cooperative (Svensson 2008). To the extent that members seek the same or mutually supporting ends, there will be strong bonds among them. In other words, the principle that affects the strength of bonds is 'economy of decision making' [Turner 1970]. These bonds provide an important idea to study the causes of business long-term relationships in a sense that organizations can be mutually bonded by a common interest in the economic matters. Recently, the framework of structural bonding has been used to study the buyer-seller relationships in industrial marketing [Han and Sung 2008, Williams et al. 1998, Wilson 1995] in that this structural bonding is a crucial part of the theoretical justification for distinguishing discrete transactions from ongoing long-term relationships. The major antecedent factors of buyer commitment such as technology, CLalt, transaction-specific assets, and importance were identified and explored from the perspective of structural bonding. Research hypotheses were developed and tested by using survey data from the middle managers in the metal industry. H1: Level of technology of the relationship partner is positively related to the level of structural bonding between the buyer and the seller. H2: Comparison level of alternatives is negatively related to the level of structural bonding between the buyer and the seller. H3: Amount of the transaction-specific assets is positively related to the level of structural bonding between the buyer and the seller. H4: Importance of the relationship partner is positively related to the level of structural bonding between the buyer and the seller. H5: Level of structural bonding is positively related to the level of commitment to the relationship. To examine the major antecedent factors of industrial buyer's structural bonding and long-term relationship, questionnaire was prepared, mailed out to the sample of 400 purchasing managers of the US metal industry (SIC codes 33 and 34). After a follow-up request, 139 informants returnedthe questionnaires, resulting in a response rate of 35 percent. 134 responses were used in the final analysis after dropping 5 incomplete questionnaires. All measures were analyzed for reliability and validity following the guidelines offered by Churchill [1979] and Anderson and Gerbing [1988]., the results of fitting the model to the data indicated that the hypothesized model provides a good fit to the data. Goodness-of-fit index (GFI = 0.94) and other indices ( chi-square = 78.02 with p-value = 0.13, Adjusted GFI = 0.90, Normed Fit Index = 0.92) indicated that a major proportion of variances and covariances in the data was accounted for by the model as a whole, and all the parameter estimates showed statistical significance as evidenced by large t-values. All the factor loadings were significantly different from zero. On these grounds we judged the hypothesized model to be a reasonable representation of the data. The results from the present study suggest several implications for buyer-seller relationships. Theoretically, we attempted to conceptualize the antecedent factors of buyer-seller long-term relationships from the perspective of structural bondingin metal industry. The four underlying determinants (i.e. technology, CLalt, transaction-specific assets, and importance) of structural bonding are very critical variables of buyer-seller long-term business relationships. Our model of structural bonding makes an attempt to systematically examine the relationship between the antecedent factors of structural bonding and long-term commitment. Managerially, this research provides industrial purchasing managers with a good framework to assess the interaction processes with their partners and, ability to position their business relationships from the perspective of structural bonding. In other words, based on those underlying variables, industrial purchasing managers can determine the strength of the company's relationships with the key suppliers and its state of preparation to be a successful partner with those suppliers. Both the supplying and customer companies can also benefit by using the concept of 'structural bonding' and evaluating their relationships with key business partners from the structural point of view. In general, the results indicate that structural bonding gives a critical impact on the level of relationship commitment. Managerial implications and limitations of the study are also discussed.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.57-78
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• 2020

With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.

• Journal of Korean Ophthalmic Optics Society
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• v.7 no.1
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• pp.45-50
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• 2002

The 'hands-on' craftsmanship of the 20th century has came and gone. Today, we are dealing with whole new, 'cerebral approach,' to concept and design with this new approach, design and function are very much dependant upon planning, sales, promotion, and the formative technique of the design industry. The innovative process of design constantly change as it reflects the needs and wants of society. It is and industry that constantly change as it reflects the needs and wants of society. It is and industry that constantly remakes and reshapes itself to suit current trend and outlook. The current idea being that consumers are looking for quality over quantity. Due to the 20th centuries dominant philosophy of functionalism, production intended to standardize the individual's purchasing choice. Aesthetic, or philosophic qualities played a second fiddle to the functional bias of a product, With production, Marketing, and research and development are integrated into the management process. This translates as good which include efficiency, quality, durability, and credibility an trademark and style. There is a definite 'post-modernist' movement and style in 21st century. Every possibility is available as the old boundaries of the 20th century are laid aside. There is a new, transformative quality to the current paradigm of design. The old "should" and "should not" of design no longerapplies. The integrated rative of design solves the usual disparity between aesthetic qualities and production. Design and profirability need not be stranger to one another. It can differentiate the image perceived of both enterprises and consumers by making use of integrated goods services. With an integrated system. both producers and designers win. While design gets full access to design in turn. All consumers make decisions based upon the evaluation of quality, service, and image ; even though it may not be a conscious decision to do so. Consumers are fully integrated human beings ; therefore producers who apply the new, integrated paradigmatic approach to concept, design, and production will reap the harvest of making a true relationship with individual buyer.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.91-108
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• 2020

Korea's famous soccer players are steadily performing well in international leagues, which led to higher interests of Korean fans in the international leagues. Reflecting the growing social phenomenon of rising interests on international leagues by Korean fans, the study examined the overall consumer perception in the consumption of uniform by domestic soccer fans and compared the changes in perception following the transfers of the players. Among others, the paper examined the consumer perception and purchase factors of soccer fans shown in social media, focusing on periods before and after the recruitment of Heung-Min Son to English Premier League's Tottenham Football Club. To this end, the EPL uniform is the collection keyword the paper utilized and collected consumer postings from domestic website and social media via Python 3.7, and analyzed them using Ucinet 6, NodeXL 1.0.1, and SPSS 25.0 programs. The results of this study can be summarized as follows. First, the uniform of the club that consistently topped the league, has been gaining attention as a popular uniform, and the players' performance, and the players' position have been identified as key factors in the purchase and search of professional football uniforms. In the case of the club, the actual ranking and whether the league won are shown to be important factors in the purchase and search of professional soccer uniforms. The club's emblem and the sponsor logo that will be attached to the uniform are also factors of interest to consumers. In addition, in the decision making process of purchase of a uniform by professional soccer fan, uniform's form, marking, authenticity, and sponsors are found to be more important than price, design, size, and logo. The official online store has emerged as a major purchasing channel, followed by gifts for friends or requests from acquaintances when someone travels to the United Kingdom. Second, a classification of key control categories through the convergence of iteration correlation analysis and Clauset-Newman-Moore clustering algorithm shows differences in the classification of individual groups, but groups that include the EPL's club and player keywords are identified as the key topics in relation to professional football uniforms. Third, between 2002 and 2006, the central theme for professional football uniforms was World Cup and English Premier League, but from 2012 to 2015, the focus has shifted to more interest of domestic and international players in the English Premier League. The subject has changed to the uniform itself from this time on. In this context, the paper can confirm that the major issues regarding the uniforms of professional soccer players have changed since Ji-Sung Park's transfer to Manchester United, and Sung-Yong Ki, Chung-Yong Lee, and Heung-Min Son's good performances in these leagues. The paper also identified that the uniforms of the clubs to which the players have transferred to are of interest. Fourth, both male and female consumers are showing increasing interest in Son's league, the English Premier League, which Tottenham FC belongs to. In particular, the increasing interest in Son has shown a tendency to increase interest in football uniforms for female consumers. This study presents a variety of researches on sports consumption and has value as a consumer study by identifying unique consumption patterns. It is meaningful in that the accuracy of the interpretation has been enhanced by using a cluster analysis via convergence of iteration correlation analysis and Clauset-Newman-Moore clustering algorithm to identify the main topics. Based on the results of this study, the clubs will be able to maximize its profits and maintain good relationships with fans by identifying key drivers of consumer awareness and purchasing for professional soccer fans and establishing an effective marketing strategy.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.115-130
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• 2011

Many online stores bring features that can build trust in their customers. More so, the number of products or content services on online stores has been increasing rapidly. Hence, personalization on online stores is considered to be an important technology to companies and customers. Recommender systems that provide favorable products and customer product reviews to users are the most commonly used features in this purpose. There are many studies to that investigated the relationship between social presence as an antecedent of trust and provision of recommender systems or customer product reviews. Many online stores have made efforts to increase perceived social presence of their customers through customer reviews, recommender systems, and analyzing associations among products. Primarily because social presence can increase customer trust or reuse intention for online stores. However, there were few studies that investigated the interactions between recommendation type, product type and provision of customer product reviews on social presence. Therefore, one of the purposes of this study is to identify the effects of personalized recommender systems and compare the role of customer reviews with product types. This study performed an experiment to see these interactions. Experimental web pages were developed with $2{\times}2$ factorial setting based on how to provide social presence to users with customer reviews and two product types such as hedonic and utilitarian. The hedonic type was a ringtone chosen from Nate.com while the utilitarian was a TOEIC study aid book selected from Yes24.com. To conduct the experiment, web based experiments were conducted for the participants who have been shopping on the online stores. Participants were a total of 240 and 30% of the participants had the chance of getting the presents. We found out that social presence increased for hedonic products when personalized recommendations were given compared to non.personalized recommendations. Although providing customer reviews for two product types did not significantly increase social presence, provision of customer product reviews for hedonic (ringtone) increased perceived social presence. Otherwise, provision of customer product reviews could not increase social presence when the systems recommend utilitarian products (TOEIC study.aid books). Therefore, it appears that the effects of increasing perceived social presence with customer reviews have a difference for product types. In short, the role of customer reviews could be different based on which product types were considered by customers when they are making a decision related to purchasing on the online stores. Additionally, there were no differences for increasing perceived social presence when providing customer reviews. Our participants might have focused on how recommendations had been provided and what products were recommended because our developed systems were providing recommendations after participants rating their preferences. Thus, the effects of customer reviews could appear more clearly if our participants had actual purchase opportunity for the recommendations. Personalized recommender systems can increase social presence of customers more than nonpersonalized recommender systems by using user preference. Online stores could find out how they can increase perceived social presence and satisfaction of their customers when customers want to find the proper products with recommender systems and customer reviews. In addition, the role of customer reviews of the personalized recommendations can be different based on types of the recommended products. Even if this study conducted two product types such as hedonic and utilitarian, the results revealed that customer reviews for hedonic increased social presence of customers more than customer reviews for utilitarian. Thus, online stores need to consider the role of providing customer reviews with highly personalized information based on their product types when they develop the personalized recommender systems.

• Korean journal of food and cookery science
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• v.18 no.2
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• pp.225-231
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• 2002

This study was carried out to investigate the possibility of improving the texture and flavor of Dasik by adding various types of sugar (syrup, honey) and flavor ingredients (omija, chija, coffee, green tea extract) to rice powder. Dasik samples were prepared, and the sensory quality and physical characteristics of those were compared. The moisture content of Dasik added with syrup was higher than that of honey. Coffee Dasik with syrup was the highest (23.6) in moisture content. In sensory quality, the omija and coffee Dasik showed the highest score in flavor quality (p<.001). Omija Dasik with honey and coffee Dasik with syrup showed the highest scores in overall acceptability (6.4, 6.2). Green tea Dasik with syrup showed the highest value in the lightness (L) of color. Omija Dasik with syrup showed the highest value in the redness (a) of color Chija Dasik was the highest in the yellowness(b) of color. In physical characteristics, the hardness was negatively correlated with the moistness, tenderness, and texture acceptability in sensory quality(p〈0.001). The cohesiveness was positively correlated with the overall acceptability in sensory quality (p〈0.01). In the relation of texture characteristics and sensory quality, the higher the moisture content, the lower the hardness and springiness were, but the higher the brittleness and the cohesiveness were(p〈.001). Overall, omija and coffee Dasik appeared to have desirable flavor, taste and overall acceptability.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.89-105
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• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• Journal of Global Scholars of Marketing Science
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• v.20 no.2
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• pp.208-218
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• 2010

Internet has grown fast and become one of the most important retail channels now. Various types of Internet retailers, hereafter etailers, have been introduced so far and as one type of Internet shopping mall, 'surrogate Internet shopping mall' has been prosperous and attracting consumers in the domestic market. Surrogate Internet shopping mall is a unique type of etailer that globally purchases well-known brand goods that are not imported in the market, completes delivery in the favor of individual buyers, and collects fees for these specific services. The consumers, who are usually interested in purchasing high-end and unique but not eligible brands, have difficulties to purchase these items overseas directly from the retailers or brands in other countries due to worries of payment failure and no address available for their usually domestic only delivery. In Korea, both numbers of surrogate Internet shopping malls and the magnitude of sales have been growing rapidly up to more than 430 active malls and 500 billion Korean won in 2008 since the population of consumers who want this agent shopping service is also expending. This etail business concept is originated from 'surrogate-mediated purchase' and this type of shopping agent has existed in many different forms and also in wide ranges of context level for quite a long time. As marketers face their individual buyers' representatives instead of a direct contact with them in many occasions, the impact of surrogate shoppers on consumer's decision making has been enormously important and many scholars have explored various range of agent's impact on consumer's purchase decisions in marketing and psychology field. However, not much rigorous research in the Internet commerce has been conveyed yet. Moreover, since as one of the shopping agent surrogate Internet shopping malls specifically connect overseas brands or retailers to domestic consumers, one specific character of the mall's, image of surrogate buying country, where surrogate purchases are conducted in, may play an important role to form consumers' attitude and purchase intention toward products. Furthermore it also possibly affects various dimensions of perceived risk in consumer's information processing. However, though tremendous researches have been carried exploring the effects of diverse dimensions of country of origin, related studies in Internet context has been rarely executed. There have been some studies that prove the positive impact of country of origin on consumer's evaluations as one of information clues in product manufacture descriptions, yet studies detecting the relationship between country image of surrogate buying origin and product evaluations rarely undertaken regarding this specific mall type. Thus, the authors have found it well-worth investigating in this specific retail channel and explored systematic relationships among focal constructs and elaborated their different paths. The authors have proven that country image of surrogate buying origin in the mall, where surrogate malls purchase products in and brings them from for buyers, not only has a positive effect on consumers' product evaluations including attitude and purchase intention but also has a negative effect on all three dimensions of perceived risk: product-related risk, shipping-related risk, and post-purchase risk. Specifically among all the perceived risk, product-related risk which is arisen from high uncertainty of product performance is most affected (${\beta}$= -.30) by negative country image of surrogate buying origin, and also shipping-related risk (${\beta}$= -.18) and post-purchase risk (${\beta}$= -.15) get influenced in order. Its direct effects on product attitude (${\beta}$= .10) and purchase intention (${\beta}$= .14) are also secured. Each of perceived risk dimension is proven to have a negative effect on purchase intention through product attitude as a mediator (${\beta}$= -.57: product-related risk ${\rightarrow}$ product attitude; ${\beta}$= -.24: shipping-related risk ${\rightarrow}$ product attitude; ${\beta}$= -.44: post-purchase risk ${\rightarrow}$ product attitude) as well. From the additional analysis, the paths of consumers' information processing are shown to be different based on their levels of product knowledge. While novice consumers with low level of knowledge consider only perceived risk important, expert consumers with high level of knowledge take both the country image, where surrogate services are conducted in, and perceived risk seriously to build their attitudes and formulate decisions toward products more delicately and systematically, which is in line with previous studies. This study suggests several pieces of academic and practical advice. Precisely, country image of surrogate buying origin does affect on consumer's risk perceptions and behavioral consequences. Therefore a careful selection of surrogate buying origin is recommended. Furthermore, reducing consumers' risk level is required to blossom this new type of retail business whether its consumer are novices or experts. Additionally, since consumer take different paths of elaborating information based on their knowledge levels, sophisticated marketing approaches to each group of consumers are required. For novice buyers strong devices for risk mitigation are needed to induce them to form better attitudes and for experts selections of better and advanced countries as surrogate buying origins are advised while endorsement strategy for the site might work as a reliable information clue to all consumers to mitigate the barriers to purchase goods online. The authors have also explained that the study suffers from some limitations, including generalizability. In future studies, tests of and comparisons among different types of etailers with relevant constructs are recommended to broaden the findings.

• Journal of Distribution Research
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• v.16 no.2
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• pp.1-24
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• 2011

1. Introduction: Contrast to the offline purchasing environment, online store cannot offer the sense of touch or direct visual information of its product to the consumers. So the builder of the online shopping mall should provide more concrete and detailed product information(Kim 2008), and Alba (1997) also predicted that the quality of the offered information is determined by the post-purchase consumer satisfaction. In practice, many fashion and apparel online shopping malls offer the picture information with the product on the real person model to enhance the usefulness of product information. On the other virtual product experience has been suggested to the ways of overcoming the online consumers' limited perceptual capability (Jiang & Benbasat 2005). However, the adoption and the facilitation of the virtual reality tools requires high investment and technical specialty compared to the text/picture product information offerings (Shaffer 2006). This could make the entry barrier to the online shopping to the small retailers and sometimes it could be demanding high level of consumers' perceptual efforts. So the expensive technological solution could affects negatively to the consumer decision making processes. Nevertheless, most of the previous research on the online product information provision suggests the VR be the more effective tools. 2. Research Model and Hypothesis: Presented in