• Korea Trade Review
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• v.42 no.2
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• pp.345-367
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• 2017

A bank payment obligation(BPO) has been introduced as a new alternative instrument for trade payments based on a technology and data-driven mechanisms aimed at facilitating an electronic trading in international trade transactions. The BPO is governed by URBPO which was in effect as of July 1, 2013. The URBPO only applies to inter-bank relationships because the BPO is bank-to-bank payment obligation, not a bank-to-customer obligation. The URBPO does not cover the interaction between a bank and their customer. For this reason, the standard bank-customer guidelines on BPO agreements were required to prepare the agreements between the banks and their customers. Accordingly, the International Chamber of Commerce established "ICC Guidelines for the creation of BPO Customer Agreements" for the settlement and development of the BPO by supporting banks in creating contracts or agreements with their customers. So, This study is to review its establishment purpose and to present the implications by analyzing the ICC guidelines. This study was based on documentary research focusing mainly on the ICC Guidelines and the appendix.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.43-61
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• 2016

Customer reviews help potential customers make purchasing decisions. However, the prevalence of reviews on websites push the customer to sift through them and change the focus from a mere search to identifying which of the available reviews are valuable and useful for the purchasing decision at hand. To identify useful reviews, websites have developed different mechanisms to give customers options when evaluating existing reviews. Websites allow users to rate the usefulness of a customer review as helpful or not. Amazon.com uses a ratio-type helpfulness, while Yelp.com uses a count-type usefulness index. This usefulness index provides helpful reviews to future potential purchasers. This study investigated the effects of sentiment and readability on useful votes for customer reviews. Similar studies on the relationship between sentiment and readability have focused on the ratio-type usefulness index utilized by websites such as Amazon.com. In this study, Yelp.com's count-type usefulness index for restaurant reviews was used to investigate the relationship between sentiment/readability and usefulness votes. Yelp.com's online customer reviews for stores in the beverage and food categories were used for the analysis. In total, 170,294 reviews containing information on a store's reputation and popularity were used. The control variables were the review length, store reputation, and popularity; the independent variables were the sentiment and readability, while the dependent variable was the number of helpful votes. The review rating is the moderating variable for the review sentiment and readability. The length is the number of characters in a review. The popularity is the number of reviews for a store, and the reputation is the general average rating of all reviews for a store. The readability of a review was calculated with the Coleman-Liau index. The sentiment is a positivity score for the review as calculated by SentiWordNet. The review rating is a preference score selected from 1 to 5 (stars) by the review author. The dependent variable (i.e., usefulness votes) used in this study is a count variable. Therefore, the Poisson regression model, which is commonly used to account for the discrete and nonnegative nature of count data, was applied in the analyses. The increase in helpful votes was assumed to follow a Poisson distribution. Because the Poisson model assumes an equal mean and variance and the data were over-dispersed, a negative binomial distribution model that allows for over-dispersion of the count variable was used for the estimation. Zero-inflated negative binomial regression was used to model count variables with excessive zeros and over-dispersed count outcome variables. With this model, the excess zeros were assumed to be generated through a separate process from the count values and therefore should be modeled as independently as possible. The results showed that positive sentiment had a negative effect on gaining useful votes for positive reviews but no significant effect on negative reviews. Poor readability had a negative effect on gaining useful votes and was not moderated by the review star ratings. These findings yield considerable managerial implications. The results are helpful for online websites when analyzing their review guidelines and identifying useful reviews for their business. Based on this study, positive reviews are not necessarily helpful; therefore, restaurants should consider which type of positive review is helpful for their business. Second, this study is beneficial for businesses and website designers in creating review mechanisms to know which type of reviews to highlight on their websites and which type of reviews can be beneficial to the business. Moreover, this study highlights the review systems employed by websites to allow their customers to post rating reviews.

• International Commerce and Information Review
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• v.17 no.3
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• pp.359-378
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• 2015

This study intends to provide strategic implication for enhancing trade show's competitiveness by analyzing its structural relationships among service quality, customer satisfaction and customer loyalty. In order to measure service quality factors influencing customer satisfaction and customer loyalty, the empirical analysis was conducted on three kinds of service quality (physical environment quality, interaction quality, outcome quality). The study results indicated that all of the physical environment quality, interaction quality and outcome quality had positive impacts on customer satisfaction. In relationship between service quality factors and customer loyalty, interaction quality and outcome quality showed positive impacts on customer loyalty, whereas physical environment quality did not. The customer satisfaction turned out to have positive impact on customer loyalty.

• Management & Information Systems Review
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• v.12
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• pp.17-35
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• 2003

In the customer-centered era, financial institutions have understood the importance of Customer Relationship Management(CRM), and heavily invested into building the required technology infrastructure more than ever. In a competitive environment that are changing fast, knowledge management is necessary. To know customers' needs and desire, we have to approach their environment and mind, and the method by estimating in terms of supposing or imitating. Applying customers' knowledge is effective and will come up with a stepping-stone to get rid of threatening factors by having competitiveness in a competitive environment and extending and changing the corporation. This purpose, the study has identified knowledge-oriented infra that corporations know and customer relations by conducting a poll of local corporations and have presented motives that can effectively carry out knowledge-based customer relations. To gain competitive advantage, these Institutions need to understand their customers' potential value to find out more and to recognize the significant changes of customer. Then the CRM implementation will help Financial Institutions move to more of a sales culture away from product and closer to the customer.

• Korean Management Science Review
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• v.20 no.1
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• pp.149-163
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• 2003

The emergence of Internal has established a huge virtual exchange market, and the innovative e-commerce has changed a way of distributing goods and services. This paper concerns the issues of customer's loyalty to maintain the customer retention between individual and Internet shopping mall. We use the concept of customer's perceived value, satisfaction, and trust, in order to explore and explain the formation process of customer loyalty. A survey data has been collected through the hep of internet research institution. A statistical analysis shows that a subset of customer's perceived value has positive Impact on satisfaction, which in turn has also positive influence on trust, Increasing the level of customer's loyalty. We also provide a brief discussion of strategic guidelines about analytic results.

• Korean Management Science Review
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• v.21 no.3
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• pp.55-69
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• 2004

This study analyzes customer buying-behavior patterns in a department store as time goes on, and predicts moving patterns of its customers. Through them, it suggests in this paper short-term and long-term marketing promotion strategies. RFM techniques are utilized for customer segmentation. Customers are clustered by using the Kohonen's Self Organizing Map as a method of data mining techniques. Then C5.0, a decision tree analysis technique, is used to predict moving patterns of customers. Using real world data, this study evaluates the prediction accuracy of predictive models.

• Korean Management Science Review
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• v.23 no.3
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• pp.133-156
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• 2006

The ubiquitous technology, leading the stream of change in telecommunication market, makes VoIP a foundation technology to enter NGN era. With this trend in mind, VoIP providers try to satisfy customer needs and invest on R&D in order to survive in this emerging market. The critical issues to VoIP providers are two fold the first one is to find out the quality attributes of Internet telephony service; and the second one is to assess the impact they have on customer satisfaction, customer loyalty and customer performance. In this study, we attempt to empirically answer the above two issues employing SEM (structural equation modeling) and AHP (analytic hierarchy process), and suggest strategic guidelines for successful deployment of Internet telephony service.

• Korean Management Science Review
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• v.19 no.2
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• pp.205-220
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• 2002

As the business structure of many industries changes under IT progress and internet economy, the customer information has emerged a key factor in setting up the management policy. The customer has come to replace the product as a central figure in business competition. The domestic life insurance market has also experienced the rapid structural changes in IT time. The competition in the insurance industry to maintain the existing membership and to attract the new members gets stronger under such a new business circumstance. Accordingly, it is necessary for an individual insurance company to develop a systematic marketing plan, based on the customer information, to be competitive in the market. Unlike other studies in which customer characteristics are neglected, this study attempts to utilize the customer information by applying the data mining technique, and then suggests an efficient marketing strategy that could prevail in the competitive business environment.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.41-63
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• 2023

As the online e-commerce market growing, the need for a recommender system that can provide suitable products or services to customer is emerging. Recently, many studies using the sentiment score of online review have been proposed to improve the limitations of study on recommender systems that utilize only quantitative information. However, this methodology has limitation in extracting specific preference information related to customer within online reviews, making it difficult to improve recommendation performance. To address the limitation of previous studies, this study proposes a novel recommendation methodology that applies deep learning technique and uses various linguistic factors within online reviews to elaborately learn customer preferences. First, the interaction was learned nonlinearly using deep learning technique for the purpose to extract complex interactions between customer and product. And to effectively utilize online review, cognitive contents, affective contents, and linguistic style matching that have an important influence on customer's purchasing decisions among linguistic factors were used. To verify the proposed methodology, an experiment was conducted using online review data in Amazon.com, and the experimental results confirmed the superiority of the proposed model. This study contributed to the theoretical and methodological aspects of recommender system study by proposing a methodology that effectively utilizes characteristics of customer's preferences in online reviews.

• Smart Media Journal
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• v.2 no.2
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• pp.20-27
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• 2013

The concept of social media is top of the agenda for many business executives and decision makers, as well as consultants try to identify ways where companies can make profitable use of applications such as Netflix, Flixster. The social media is playing an increasingly important role as the information sources for customers making product choices etc. With the flourish of Web 2.0 technology, customer reviews are becoming more and more useful and important information resources for people to save their time and energy on purchasing products that they want. This paper proposes the Bayesian Probabilistic Classification algorithm to mine the social media review, and evaluates it by different splits and cross validation mechanism from the real data set. The explored study experimental results show the robustness and effectiveness of proposed approach for mining the social media review.