• Asia pacific journal of information systems
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• v.20 no.3
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• pp.139-166
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• 2010

The supply chain management (SCM) systems have emerged as strong managerial tools for manufacturing firms in enhancing competitive strength. Despite of large investments in the SCM systems, many companies are not fully realizing the promised benefits from the systems. A review of literature on adoption, implementation and success factor of IOS (inter-organization systems), EDI (electronic data interchange) systems, shows that this issue has been examined from multiple theoretic perspectives. And many researchers have attempted to identify the factors which influence the success of system implementation. However, the existing studies have two drawbacks in revealing the determinants of systems implementation success. First, previous researches raise questions as to the appropriateness of research subjects selected. Most SCM systems are operating in the form of private industrial networks, where the participants of the systems consist of two distinct groups: focus companies and vendors. The focus companies are the primary actors in developing and operating the systems, while vendors are passive participants which are connected to the system in order to supply raw materials and parts to the focus companies. Under the circumstance, there are three ways in selecting the research subjects; focus companies only, vendors only, or two parties grouped together. It is hard to find researches that use the focus companies exclusively as the subjects probably due to the insufficient sample size for statistic analysis. Most researches have been conducted using the data collected from both groups. We argue that the SCM success factors cannot be correctly indentified in this case. The focus companies and the vendors are in different positions in many areas regarding the system implementation: firm size, managerial resources, bargaining power, organizational maturity, and etc. There are no obvious reasons to believe that the success factors of the two groups are identical. Grouping the two groups also raises questions on measuring the system success. The benefits from utilizing the systems may not be commonly distributed to the two groups. One group's benefits might be realized at the expenses of the other group considering the situation where vendors participating in SCM systems are under continuous pressures from the focus companies with respect to prices, quality, and delivery time. Therefore, by combining the system outcomes of both groups we cannot measure the system benefits obtained by each group correctly. Second, the measures of system success adopted in the previous researches have shortcoming in measuring the SCM success. User satisfaction, system utilization, and user attitudes toward the systems are most commonly used success measures in the existing studies. These measures have been developed as proxy variables in the studies of decision support systems (DSS) where the contribution of the systems to the organization performance is very difficult to measure. Unlike the DSS, the SCM systems have more specific goals, such as cost saving, inventory reduction, quality improvement, rapid time, and higher customer service. We maintain that more specific measures can be developed instead of proxy variables in order to measure the system benefits correctly. The purpose of this study is to find the determinants of SCM systems success in the perspective of vendor companies. In developing the research model, we have focused on selecting the success factors appropriate for the vendors through reviewing past researches and on developing more accurate success measures. The variables can be classified into following: technological, organizational, and environmental factors on the basis of TOE (Technology-Organization-Environment) framework. The model consists of three independent variables (competition intensity, top management support, and information system maturity), one mediating variable (collaboration), one moderating variable (government support), and a dependent variable (system success). The systems success measures have been developed to reflect the operational benefits of the SCM systems; improvement in planning and analysis capabilities, faster throughput, cost reduction, task integration, and improved product and customer service. The model has been validated using the survey data collected from 122 vendors participating in the SCM systems in Korea. To test for mediation, one should estimate the hierarchical regression analysis on the collaboration. And moderating effect analysis should estimate the moderated multiple regression, examines the effect of the government support. The result shows that information system maturity and top management support are the most important determinants of SCM system success. Supply chain technologies that standardize data formats and enhance information sharing may be adopted by supply chain leader organization because of the influence of focal company in the private industrial networks in order to streamline transactions and improve inter-organization communication. Specially, the need to develop and sustain an information system maturity will provide the focus and purpose to successfully overcome information system obstacles and resistance to innovation diffusion within the supply chain network organization. The support of top management will help focus efforts toward the realization of inter-organizational benefits and lend credibility to functional managers responsible for its implementation. The active involvement, vision, and direction of high level executives provide the impetus needed to sustain the implementation of SCM. The quality of collaboration relationships also is positively related to outcome variable. Collaboration variable is found to have a mediation effect between on influencing factors and implementation success. Higher levels of inter-organizational collaboration behaviors such as shared planning and flexibility in coordinating activities were found to be strongly linked to the vendors trust in the supply chain network. Government support moderates the effect of the IS maturity, competitive intensity, top management support on collaboration and implementation success of SCM. In general, the vendor companies face substantially greater risks in SCM implementation than the larger companies do because of severe constraints on financial and human resources and limited education on SCM systems. Besides resources, Vendors generally lack computer experience and do not have sufficient internal SCM expertise. For these reasons, government supports may establish requirements for firms doing business with the government or provide incentives to adopt, implementation SCM or practices. Government support provides significant improvements in implementation success of SCM when IS maturity, competitive intensity, top management support and collaboration are low. The environmental characteristic of competition intensity has no direct effect on vendor perspective of SCM system success. But, vendors facing above average competition intensity will have a greater need for changing technology. This suggests that companies trying to implement SCM systems should set up compatible supply chain networks and a high-quality collaboration relationship for implementation and performance.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.127-138
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• 2011

The core service of most research portal sites is providing relevant research papers to various researchers that match their research interests. This kind of service may only be effective and easy to use when a user can provide correct and concrete information about a paper such as the title, authors, and keywords. However, unfortunately, most users of this service are not acquainted with concrete bibliographic information. It implies that most users inevitably experience repeated trial and error attempts of keyword-based search. Especially, retrieving a relevant research paper is more difficult when a user is novice in the research domain and does not know appropriate keywords. In this case, a user should perform iterative searches as follows : i) perform an initial search with an arbitrary keyword, ii) acquire related keywords from the retrieved papers, and iii) perform another search again with the acquired keywords. This usage pattern implies that the level of service quality and user satisfaction of a portal site are strongly affected by the level of keyword management and searching mechanism. To overcome this kind of inefficiency, some leading research portal sites adopt the association rule mining-based keyword recommendation service that is similar to the product recommendation of online shopping malls. However, keyword recommendation only based on association analysis has limitation that it can show only a simple and direct relationship between two keywords. In other words, the association analysis itself is unable to present the complex relationships among many keywords in some adjacent research areas. To overcome this limitation, we propose the hybrid approach for establishing association network among keywords used in research papers. The keyword association network can be established by the following phases : i) a set of keywords specified in a certain paper are regarded as co-purchased items, ii) perform association analysis for the keywords and extract frequent patterns of keywords that satisfy predefined thresholds of confidence, support, and lift, and iii) schematize the frequent keyword patterns as a network to show the core keywords of each research area and connecting keywords among two or more research areas. To estimate the practical application of our approach, we performed a simple experiment with 600 keywords. The keywords are extracted from 131 research papers published in five prominent Korean journals in 2009. In the experiment, we used the SAS Enterprise Miner for association analysis and the R software for social network analysis. As the final outcome, we presented a network diagram and a cluster dendrogram for the keyword association network. We summarized the results in Section 4 of this paper. The main contribution of our proposed approach can be found in the following aspects : i) the keyword network can provide an initial roadmap of a research area to researchers who are novice in the domain, ii) a researcher can grasp the distribution of many keywords neighboring to a certain keyword, and iii) researchers can get some idea for converging different research areas by observing connecting keywords in the keyword association network. Further studies should include the following. First, the current version of our approach does not implement a standard meta-dictionary. For practical use, homonyms, synonyms, and multilingual problems should be resolved with a standard meta-dictionary. Additionally, more clear guidelines for clustering research areas and defining core and connecting keywords should be provided. Finally, intensive experiments not only on Korean research papers but also on international papers should be performed in further studies.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.23-48
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• 2021

The Korean economy has achieved continuous economic growth for the past several decades thanks to the government's export strategy policy. This increase in exports is playing a leading role in driving Korea's economic growth by improving economic efficiency, creating jobs, and promoting technology development. Traditionally, the main factors affecting Korea's exports can be found from two perspectives: economic factors and industrial structural factors. First, economic factors are related to exchange rates and global economic fluctuations. The impact of the exchange rate on Korea's exports depends on the exchange rate level and exchange rate volatility. Global economic fluctuations affect global import demand, which is an absolute factor influencing Korea's exports. Second, industrial structural factors are unique characteristics that occur depending on industries or products, such as slow international division of labor, increased domestic substitution of certain imported goods by China, and changes in overseas production patterns of major export industries. Looking at the most recent studies related to global exchanges, several literatures show the importance of cultural aspects as well as economic and industrial structural factors. Therefore, this study attempted to develop a forecasting model by considering cultural factors along with economic and industrial structural factors in calculating the import volume of each country from Korea. In particular, this study approaches the influence of cultural factors on imports of Korean products from the perspective of PUSH-PULL framework. The PUSH dimension is a perspective that Korea develops and actively promotes its own brand and can be defined as the degree of interest in each country for Korean brands represented by K-POP, K-FOOD, and K-CULTURE. In addition, the PULL dimension is a perspective centered on the cultural and psychological characteristics of the people of each country. This can be defined as how much they are inclined to accept Korean Flow as each country's cultural code represented by the country's governance system, masculinity, risk avoidance, and short-term/long-term orientation. The unique feature of this study is that the proposed final prediction model can be selected based on Design Principles. The design principles we presented are as follows. 1) A model was developed to reflect interest in Korea and cultural characteristics through newly added data sources. 2) It was designed in a practical and convenient way so that the forecast value can be immediately recalled by inputting changes in economic factors, item code and country code. 3) In order to derive theoretically meaningful results, an algorithm was selected that can interpret the relationship between the input and the target variable. This study can suggest meaningful implications from the technical, economic and policy aspects, and is expected to make a meaningful contribution to the export support strategies of small and medium-sized enterprises by using the import forecasting model.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.123-138
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• 2017

Since the stock market is driven by the expectation of traders, studies have been conducted to predict stock price movements through analysis of various sources of text data. In order to predict stock price movements, research has been conducted not only on the relationship between text data and fluctuations in stock prices, but also on the trading stocks based on news articles and social media responses. Studies that predict the movements of stock prices have also applied classification algorithms with constructing term-document matrix in the same way as other text mining approaches. Because the document contains a lot of words, it is better to select words that contribute more for building a term-document matrix. Based on the frequency of words, words that show too little frequency or importance are removed. It also selects words according to their contribution by measuring the degree to which a word contributes to correctly classifying a document. The basic idea of constructing a term-document matrix was to collect all the documents to be analyzed and to select and use the words that have an influence on the classification. In this study, we analyze the documents for each individual item and select the words that are irrelevant for all categories as neutral words. We extract the words around the selected neutral word and use it to generate the term-document matrix. The neutral word itself starts with the idea that the stock movement is less related to the existence of the neutral words, and that the surrounding words of the neutral word are more likely to affect the stock price movements. And apply it to the algorithm that classifies the stock price fluctuations with the generated term-document matrix. In this study, we firstly removed stop words and selected neutral words for each stock. And we used a method to exclude words that are included in news articles for other stocks among the selected words. Through the online news portal, we collected four months of news articles on the top 10 market cap stocks. We split the news articles into 3 month news data as training data and apply the remaining one month news articles to the model to predict the stock price movements of the next day. We used SVM, Boosting and Random Forest for building models and predicting the movements of stock prices. The stock market opened for four months (2016/02/01 ~ 2016/05/31) for a total of 80 days, using the initial 60 days as a training set and the remaining 20 days as a test set. The proposed word - based algorithm in this study showed better classification performance than the word selection method based on sparsity. This study predicted stock price volatility by collecting and analyzing news articles of the top 10 stocks in market cap. We used the term - document matrix based classification model to estimate the stock price fluctuations and compared the performance of the existing sparse - based word extraction method and the suggested method of removing words from the term - document matrix. The suggested method differs from the word extraction method in that it uses not only the news articles for the corresponding stock but also other news items to determine the words to extract. In other words, it removed not only the words that appeared in all the increase and decrease but also the words that appeared common in the news for other stocks. When the prediction accuracy was compared, the suggested method showed higher accuracy. The limitation of this study is that the stock price prediction was set up to classify the rise and fall, and the experiment was conducted only for the top ten stocks. The 10 stocks used in the experiment do not represent the entire stock market. In addition, it is difficult to show the investment performance because stock price fluctuation and profit rate may be different. Therefore, it is necessary to study the research using more stocks and the yield prediction through trading simulation.

• Journal of Global Scholars of Marketing Science
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• v.20 no.3
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• pp.262-268
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• 2010

Virtual communities (VCs) have developed rapidly, with more and more people participating in them to exchange information and opinions. A virtual community is a group of people who may or may not meet one another face to face, and who exchange words and ideas through the mediation of computer bulletin boards and networks. A business-to-consumer virtual community (B2CVC) is a commercial group that creates a trustworthy environment intended to motivate consumers to be more willing to buy from an online store. B2CVCs create a social atmosphere through information contribution such as recommendations, reviews, and ratings of buyers and sellers. Although the importance of B2CVCs has been recognized, few studies have been conducted to examine members' word-of-mouth behavior within these communities. This study proposes a model of involvement, statistics, trust, "stickiness," and word-of-mouth in a B2CVC and explores the relationships among these elements based on empirical data. The objectives are threefold: (i) to empirically test a B2CVC model that integrates measures of beliefs, attitudes, and behaviors; (ii) to better understand the nature of these relationships, specifically through word-of-mouth as a measure of revenue generation; and (iii) to better understand the role of stickiness of B2CVC in CRM marketing. The model incorporates three key elements concerning community members: (i) their beliefs, measured in terms of their involvement assessment; (ii) their attitudes, measured in terms of their satisfaction and trust; and, (iii) their behavior, measured in terms of site stickiness and their word-of-mouth. Involvement is considered the motivation for consumers to participate in a virtual community. For B2CVC members, information searching and posting have been proposed as the main purpose for their involvement. Satisfaction has been reviewed as an important indicator of a member's overall community evaluation, and conceptualized by different levels of member interactions with their VC. The formation and expansion of a VC depends on the willingness of members to share information and services. Researchers have found that trust is a core component facilitating the anonymous interaction in VCs and e-commerce, and therefore trust-building in VCs has been a common research topic. It is clear that the success of a B2CVC depends on the stickiness of its members to enhance purchasing potential. Opinions communicated and information exchanged between members may represent a type of written word-of-mouth. Therefore, word-of-mouth is one of the primary factors driving the diffusion of B2CVCs across the Internet. Figure 1 presents the research model and hypotheses. The model was tested through the implementation of an online survey of CTrip Travel VC members. A total of 243 collected questionnaires was reduced to 204 usable questionnaires through an empirical process of data cleaning. The study's hypotheses examined the extent to which involvement, satisfaction, and trust influence B2CVC stickiness and members' word-of-mouth. Structural Equation Modeling tested the hypotheses in the analysis, and the structural model fit indices were within accepted thresholds: ${\chi}^2^$/df was 2.76, NFI was .904, IFI was .931, CFI was .930, and RMSEA was .017. Results indicated that involvement has a significant influence on satisfaction (p<0.001, ${\beta}$=0.809). The proportion of variance in satisfaction explained by members' involvement was over half (adjusted $R^2$=0.654), reflecting a strong association. The effect of involvement on trust was also statistically significant (p<0.001, ${\beta}$=0.751), with 57 percent of the variance in trust explained by involvement (adjusted $R^2$=0.563). When the construct "stickiness" was treated as a dependent variable, the proportion of variance explained by the variables of trust and satisfaction was relatively low (adjusted $R^2$=0.331). Satisfaction did have a significant influence on stickiness, with ${\beta}$=0.514. However, unexpectedly, the influence of trust was not even significant (p=0.231, t=1.197), rejecting that proposed hypothesis. The importance of stickiness in the model was more significant because of its effect on e-WOM with ${\beta}$=0.920 (p<0.001). Here, the measures of Stickiness explain over eighty of the variance in e-WOM (Adjusted $R^2$=0.846). Overall, the results of the study supported the hypothesized relationships between members' involvement in a B2CVC and their satisfaction with and trust of it. However, trust, as a traditional measure in behavioral models, has no significant influence on stickiness in the B2CVC environment. This study contributes to the growing body of literature on B2CVCs, specifically addressing gaps in the academic research by integrating measures of beliefs, attitudes, and behaviors in one model. The results provide additional insights to behavioral factors in a B2CVC environment, helping to sort out relationships between traditional measures and relatively new measures. For practitioners, the identification of factors, such as member involvement, that strongly influence B2CVC member satisfaction can help focus technological resources in key areas. Global e-marketers can develop marketing strategies directly targeting B2CVC members. In the global tourism business, they can target Chinese members of a B2CVC by providing special discounts for active community members or developing early adopter programs to encourage stickiness in the community. Future studies are called for, and more sophisticated modeling, to expand the measurement of B2CVC member behavior and to conduct experiments across industries, communities, and cultures.

• Journal of Global Scholars of Marketing Science
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• v.20 no.2
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• pp.188-198
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• 2010

This study attempts to examine the influence that negative WOM (NWOM) has in an online context. It specifically focuses on the impact of the service failure description and the perceived intention of the communication provider on consumer evaluations of firm competence, attitude toward the firm, positive word of mouth and behavioral intentions. Studies of communication persuasiveness focus on "who says what; to whom; in which channel; with what effect (Chiu 2007)." In this research study, we examine electronic web posting, particularly focusing on two aspects of "what": the level of service failure communicated and perceived intention of the individual posting. It stands to reason electronic NWOM that appears to be trying to damage a product’s or firm's reputation will be viewed as more biased and will thus be considered as less credible. According to attribution theory, people search for the causes of events especially those that are negative and unexpected (Weiner 2006). Hennig-Thurau and Walsh (2003) state "since the reader has only limited knowledge and trust of the author of an online articulation the quality of the contribution could be expected to serve as a potent moderator of the articulation-behavior relationship. We therefore posit the following hypotheses: H1. Subjects exposed to electronic NWOM describing a high level of service failure will provide lower scores on measures of (a) firm competence, (b) attitude toward the firm, (c) positive word of mouth, and (d) behavioral intention than will subjects exposed to electronic NWOM describing a low level of service failure. H2. Subjects exposed to electronic NWOM with a warning intent will provide lower scores on measures of (a) firm competence, (b) attitude toward the firm, (c) positive word of mouth, and (d) behavioral intention than will subjects exposed to electronic NWOM with a vengeful intent. H3. Level of service failure in electronic NWOM will interact with the perceived intention of the electronic NWOM, such that there will be a decrease in mean response on measures of (a) firm competence, (b) attitude toward the firm, (c) positive word of mouth, and (d) behavioral intention from electronic NWOM with a warning intent to a vengeful intent. The main study involved a2 (service failure severity) x2 (NWOM with warning versus vengeful intent) factorial experiment. Stimuli were presented to subjects online using a mock online web posting. The scenario described a service failure associated with non-acceptance of a gift card in a brick-and-mortar retail establishment. A national sample was recruited through an online research firm. A total of 113 subjects participated in the study. A total of 104 surveys were analyzed. The scenario was perceived to be realistic with 92.3% giving the scenario a greater than average response. Manipulations were satisfactory. Measures were pre-tested and validated. Items were analyzed and found reliable and valid. MANOVA results found the multivariate interaction was not significant, allowing our interpretation to proceed to the main effects. Significant main effects were found for post intent and service failure severity. The post intent main effect was attributable to attitude toward the firm, positive word of mouth and behavioral intention. The service failure severity main effect was attributable to all four dependent variables: firm competence, attitude toward the firm, positive word of mouth and behavioral intention. Specifically, firm competence for electronic NWOM describing high severity of service failure was lower than electronic NWOM describing low severity of service failure. Attitude toward the firm for electronic NWOM describing high severity of service failure was lower than electronic NWOM describing low severity of service failure. Positive word of mouth for electronic NWOM describing high severity of service failure was lower than electronic NWOM describing low severity of service failure. Behavioral intention for electronic NWOM describing high severity of service failure was lower for electronic NWOM describing low severity of service failure. Therefore, H1a, H1b, H1c and H1d were all supported. In addition, attitude toward the firm for electronic NWOM with a warning intent was lower than electronic NWOM with a vengeful intent. Positive word of mouth for electronic NWOM with a warning intent was lower than electronic NWOM with a vengeful intent. Behavioral intention for electronic NWOM with a warning intent was lower than electronic NWOM with a vengeful intent. Thus, H2b, H2c and H2d were supported. However, H2a was not supported though results were in the hypothesized direction. Otherwise, there was no significant multivariate service failure severity by post intent interaction, nor was there a significant univariate service failure severity by post intent interaction for any of the three hypothesized variables. Thus, H3 was not supported for any of the four hypothesized variables. This study has research and managerial implications. The findings of this study support prior research that service failure severity impacts consumer perceptions, attitude, positive word of mouth and behavioral intentions (Weun et al. 2004). Of further relevance, this response is evidenced in the online context, suggesting the need for firms to engage in serious focused service recovery efforts. With respect to perceived intention of electronic NWOM, the findings support prior research suggesting reader's attributions of the intentions of a source influence the strength of its impact on perceptions, attitude, positive word of mouth and behavioral intentions. The implication for managers suggests while consumers do find online communications to be credible and influential, not all communications are weighted the same. A benefit of electronic WOM, even when it may be potentially damaging, is it can be monitored for potential problems and additionally offers the possibility of redress.

• Asia Marketing Journal
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• v.14 no.1
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• pp.99-130
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• 2012

Service failure and a poor service recovery may lead loyal customers to try to aggressively punish the service firm. We use perceived betrayal and desire for vengeance as the key constructs to understand customer retaliation. Perceived betrayal is defined as a customer's belief that a firm has intentionally violated what is normative in the context of their relationship. And the desire for vengeance is defined as the retaliatory feelings that consumers feel toward a firm, such as the desire to exert harm on the firm. The perceived betrayal and the desire for vengeance are key antecedents of retaliatory behaviors such as vindictive complaining, negative WOM and third-party complaining for publicity. The empirical results suggest that betrayal is a key motivational factor that lead customers to restore fairness by making use of all means, including retaliation. We also find that relationship quality has effect on a customer's response to a failure in service recovery. As the levels of relationship increases, a violation of the proper fairness has a stronger effect on the sense of betrayal experienced by customers. Considerable research has investigated consumer responses to dissatisfaction. But our study examine the response of outraged and highly frustrated consumers. We focus on emotional and behavioral processes that have not been covered by previous dissatisfaction researches and which are unique to outraged consumers caused by extremely dissatisfied purchase experience. It has recently been pointed out by various mass media that the customers not only have positive effects on the company performance but also put the company in crisis. It has often been reported that one customer's dissatisfaction, for example, never ends as it is, and it tends to grow for retaliating upon the company, depending on the level of seriousness of the dissatisfaction. This sometimes leads to a lawsuit against the company. Our study focuses on the customers' emotional and behavioral responses induced by their extreme dissatisfactions. We divided the customer groups into the customers with high relationship quality and the customers with low relationship quality, and the difference between two groups is examined. The objective of this study is to comprehend the causal relationship between the feeling of betrayal caused by the service failure and the retaliatory behavior triggered by the desire of revenge. Our study is divided into three parts. First, a causal relationship between perceived unfairness and the perceived betrayal and desire for revenge. Second, the effect of the perceived betrayal and desire for revenge on the retaliatory behavior is investigated. Finally, the moderating role of relationship quality in the causal relationship between the unfairness in service recovery and the perceived betrayal is analyzed. This study finds the following empirical results. The distributive unfairness, procedural unfairness and interactional unfairness had significant effects on the perceived betrayal. Especially, the perceived distributive unfairness results in the highest perceived betrayal. When the service company does not provide customers proper and sufficient compensation for the failure, they feel the strong sense of betrayal. And in the causal relationship between the perceived betrayal, desire for revenge and retaliatory behavior, the perceived betrayal has significant effects on e desire for revenge. In addition desire for revenge has significant effects on negative word of mouth, retaliatory complaining behavior and publicity of complaints through third group. Therefore the perceived unfairness has effects on retaliatory behavior through the mediation of the perceived betrayal and desire for revenge. Finally the moderating role of relationship quality was examined in the relationship between the unfairness and perceived betrayal. If the customers experienced the perceived unfairness in the process of service recovery, the customers with high relationship quality feel the stronger perceived betrayal than the customers with low relationship quality do. When they experience the double service failure, the customer group with high relationship quality accumulating the sense of trust feel the more perceived betrayal than the customer with low relationship quality who do not have strong trust. The contribution of this study is to find the effect of the service failure on the retaliatory behavior with the moderating roles of relationship quality. The dimensions of unfairness in service recovery is found to have differential effects on the perceived betrayal, desire for revenge. And these differential effect is moderated by the level of relationship quality.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.12
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• pp.6133-6145
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• 2013

With the increasing number of online wine stores, customers are increasingly seeking to purchase wine online. On the other hand, purchasing wine online is prohibited by law or regulation in Korea. Therefore, customers mainly search for wine information, inquire about wine products, and make a pre-purchase at an online wine store. Online wine stores play important roles in customer's purchase decision-making, and are likely to be a useful wine distribution channel in the near future. Therefore, the aim of this study was to identify the determinants of the online wine purchase intention, and examine the structural relationships between the determinants and online wine purchase intention. The site quality of online wine stores (information quality, system quality, service quality), and perceived value (quality value, price value, emotional value, social value) were selected as the determinants of online wine purchase intention based on literature review. The data was collected from those who had experience using an online wine store to purchase wine, and the data was used to test the proposed research model. The findings showed that the information quality was not related to the perceived value (quality value, price value, emotional value, social value). The system quality was proven to be positively and significantly related to the quality value, price value, and emotional value, whereas it had no impact on the social value. In addition, the service quality was found to affect the perceived value (quality value, price value, emotional and social value). Finally, the results showed that the quality value, emotional value, and social value have a positive impact on the online wine purchase intention, whereas the price quality is not related to the online wine purchase intention. These results are expected to make a contribution to a better understanding of how the quality of online wine stores and the customer's perceived value affect the online wine purchasing intention.

• Journal of Distribution Research
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• v.15 no.1
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• pp.25-47
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• 2010

CS is one of the major concerns of managers in the world because it is well known to be a key medium construct for firms' superior outcome. One of the major agents for CS management is retailers. Firms try to manage not only employees but also retailers to promote CS behaviors. And so diverse incentives are used to promote their CS behaviors under diverse channel setting such as multi-channel. However in spite of the rising needs there has been scarce studies on the optimal incentive structure for a manufacturer to offer competing retailers at the multi-channel. In this paper, we try to find better way for a manufacturer to promote the competing retailers' CS behaviors. We investigated how to promote the retailers' CS behavior via game-theoretic modeling. Especially, we focus on the possible incentive, CS bonus type reward introduced in the studies of Hauser, Simester, and Wernerfelt(1994) and Chu and Desai(1995). We build up a multi stage complete information game and derive a subgame perfect equilibrium using backward induction. Stages of the game are as following. (Stage 1) Manufacturer sets wholesale price(w) and CS bonus($\eta$). (Stage 2) Both retailers in competition set CS effort level($e_i$) and retail price($p_i$) simultaneously. (Stage 3) Consumers make purchasing decisions based on the manufacturer's initial reputation and retailers' CS efforts.

• Journal of Distribution Science
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• v.10 no.5
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• pp.37-44
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• 2012

In this paper, we investigate several factors that affect the locational decision of discount stores by using previous studies on the marketing area and the location of commercial facilities. We selected 21 primary variables that are expected to influence the decision of store location and, by factor analysis, grouped them into five underlying factors. Among these, the demographic factor, which shows the potential purchasing power level, had the greatest impact on the locational decision for the store. However, we found individual stores positioned according to unique locational characteristics in addition to the demographic factor. It means that we have to additionally consider if the vicinity of the market is based on any physical properties. Many previous studies proposed four decision factors for store location: the economic factor, the demographic factor, the land utilization factor, and traffic factor. However, the fivefold factors-our distinctive contribution-are more concrete and persuasive according to Korean reality. We show that location preference is based on the following criteria: (1) the area is densely populated, (2) houses stand close together, (3) residents have a high income level, (4) road traffic is developed and easy to access, and (5) public transportation is well developed. The demographic factor has the greatest impact on the location of a discount store. The number of households has a greater relevance to the demographic factor than does the individual consumer. Second, discount stores relatively prefer places where houses are located close together because such places offer easy access to the market. Third, a place whose residents have a high income level will be preferred, with its large cars and excellent traffic conditions. Fourth, a location would be highly rated if the roads around commercial facilities are well developed and their accessibility is good. Finally, discount stores must be located close to bus stops because female consumers, including housewives-the most important customers-evaluate stores based on distance. In this research, the variable of consumer attitude and preference was excluded, and the location factors of discount stores were analyzed according to a microscopic view through physical spatial data. In the future, the opening of new discount stores based on the five factors indicated above will require a comparatively shorter time from the first project feasibility analysis. In addition, the result of our study can be applied to the field of public policy for constructing and attracting large-scale distribution facilities.