• Journal of Distribution Science
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• v.14 no.7
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• pp.83-90
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• 2016

Purpose - This study focuses on new type distribution channel that named as Omnichannel. Omnichannel is developed from Multichannel which is used in many distribution channels to buy or selling goods. Omnichannel basically needs an Information and Communications Technologies(ICT) to use, so researcher conduct a Technology Acceptance Model(TAM) to research model. Customer-brand relationship was used as dependent variable to focus on the role of Omnichannel. Research design, data, and methodology - The subject of this study is customer who purchase goods or service through omnichannel. Based on the literature from the preceding research analysis of TAM and customer-brand relationship, this study was constructed by the reference to previous studies, final research model design for figure out casual relationship among perceived ease of use, perceived usefulness, omnichannel use and customer-brand relationship. From 2016 February 3 to March 17, questionnaire survey targeted customers who use online and offline channels. 273 questionnaire survey had conducted, then, 252 survey data were available for empirical analysis. Researcher provide descriptive statistics for checking generality. Cronbach's alpha value was used to check the reliability of data. Exploratory factor analysis was used for purification of values and eigenvalue checking. After EFA, Confirmatory factor analysis was used to prepare structural equation modeling with executing structural equation modeling for confirming hypothesis which developed by researcher. Results - The main results of this empirical study are as follows. First, omnichannel's perceived ease of use has positive significant effect on perceived usefulness(estimate: 0.579). Moreover, omnichannel's perceived ease of use and perceived usefulness has positive significant effect on omnichannel use(estimate: 0.325,0.648). Second, using omnichannel has positive significant effect on brand-customer relationship(estimate: 0.521). Every hypothesis adopted as researcher designed. This study found out the intermediate relationship between perceived ease of use and omnichannel use by investigating hypothesis. Conclusions - Base on the empirical result, this study confirmed that TAM theory perceived has relation with omnichannel. First, factors of TAM has positive effect on omnichannel use, so it highlights the important role of customer based interface and usefulness. Especially, perceived usefulness has high indirect influence on ease of use and use of omnichannel. It seems that when customers try to decide use or not use omnichannel, customers focus on percept benefits from omnichannel. Thus, a provider should applicate attractive price table, accurate product or service information and high switching cost strategy to emphasize the usefulness of omnichannel. Second, using omnichannel enhances the relationship between customers and brand, because there are more time and frequency to serve customers. It is important because good relationship between customers can increase the future's financial performance through word of mouse, positive brand image and loyalty to brand or company. Finally, despite of empirical result and implications, this study has limitations. First, there are only a few previous studies about omnicahnnel, so literature reviews are restricted. While set up the factors which can affect the use of omnichannel, next study should be considered with broader theories or models(ex: contingency theory). Second, omnichannel has developed from multichannel, so comparative analysis is needed between these methods because there is a possibility about different forte character of each distribution system on customer's consuming patterns.

• Journal of Distribution Science
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• v.13 no.8
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• pp.91-96
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• 2015

Purpose - This study reviews the delivery of child welfare service quality and examines how the dimensions of the variables of customer satisfaction impact the results from a service distribution perspective. This study differs from existing research since it proposes that a recognized level of child welfare service quality is necessary to achieve customer satisfaction from the perspective of service distribution. Research design, data, and methodology - This study explores child welfare service quality factors that affect customer satisfaction. The study examines and analyzes demographic variables, service quality dimensions, and the causal relationships between child welfare service quality and customer satisfaction. Data from 300 child welfare cases were collected from organizations in Korea in the areas of Busan and Gyeongsangnamdo. The methods of analysis are as follow. First, using descriptive analysis frequency, the percentages were evaluated to assess the demographic variables. Second, Cronbach's α was used to test reliability and to evaluate the internal consistency of the measuring of items. Third, multiple regression analysis was conducted to find out how much the independent variable can affect customer satisfaction. Results - Five factors of child welfare service quality were identified in three categories: process quality (assurance, empathy), results quality (reliability, caring), and physical environment quality (tangibles). There were significant differences among the effects of the child welfare service quality factors on customer satisfaction. A multiple regression analysis was done with process quality (assurance, empathy), results quality (reliability, caring) and physical environment quality (tangibles) to test the hypothesis: assurance (t=2.434, p<0.05), empathy (t=3.677, p<0.001), reliability (t=3.271, p<0.05), caring (t=4.380, p<0.000), and tangibles (t=3.654, p<0.01) had a positive influence on child welfare service quality from a service distribution perspective. Therefore, hypotheses 1, 2, 3, 4, and 5 were supported. In addition, multiple regression analysis on the effects of the variables showed that caring (β=0.273), empathy (β=0.246), tangibles (β=0.265), reliability (β=0.152), and assurance (β=0.131) all had a positive and strong influence on child welfare service quality from a service distribution perspective. Therefore, all child welfare service quality categories (process, results and physical environment quality) were positively statistically significant. Conclusion - In this study, the main findings can be summarized as follows. First, the quality of service of child welfare consists of three dimensions of quality: process quality, results quality, and physical environment quality. The results of the multiple regression analysis also showed that caring and reliability were confirmed as more meaningful variables by the increasing loading factors. Second, the family members involved in child welfare proposed caring as the most important variable among the dimensions of service quality. Third, the results of the hypothesis testing using regression showed that all child welfare service quality factors had a positive impact on customer satisfaction. The results of the study could provide useful information to help increase the effectiveness of delivery strategies for child welfare service quality from a service distribution perspective.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.71-89
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• 2016

Sentiment analysis is used for identifying emotions or sentiments embedded in the user generated data such as customer reviews from blogs, social network services, and so on. Various research fields such as computer science and business management can take advantage of this feature to analyze customer-generated opinions. In previous studies, the star rating of a review is regarded as the same as sentiment embedded in the text. However, it does not always correspond to the sentiment polarity. Due to this supposition, previous studies have some limitations in their accuracy. To solve this issue, the present study uses a supervised sentiment classification model to measure a more accurate sentiment polarity. This study aims to propose an advanced sentiment classifier and to discover the correlation between movie reviews and box-office success. The advanced sentiment classifier is based on two supervised machine learning techniques, the Support Vector Machines (SVM) and Feedforward Neural Network (FNN). The sentiment scores of the movie reviews are measured by the sentiment classifier and are analyzed by statistical correlations between movie reviews and box-office success. Movie reviews are collected along with a star-rate. The dataset used in this study consists of 1,258,538 reviews from 175 films gathered from Naver Movie website (movie.naver.com). The results show that the proposed sentiment classifier outperforms Naive Bayes (NB) classifier as its accuracy is about 6% higher than NB. Furthermore, the results indicate that there are positive correlations between the star-rate and the number of audiences, which can be regarded as the box-office success of a movie. The study also shows that there is the mild, positive correlation between the sentiment scores estimated by the classifier and the number of audiences. To verify the applicability of the sentiment scores, an independent sample t-test was conducted. For this, the movies were divided into two groups using the average of sentiment scores. The two groups are significantly different in terms of the star-rated scores.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.9
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• pp.1153-1158
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• 2018

Online customer evaluations and social media information among a variety of information sources are critical for businesses as it influences the customer's decision making. There are limitations on the time and money that the survey will ask to identify a variety of customers' needs and complaints. The customer review data at online shopping malls provide the ideal data sources for analyzing customer sentiment about their products. In this study, we collected product reviews data on the smartphone of Samsung and Apple from Amazon. We applied five classification algorithms which are used as representative sentiment analysis techniques in previous studies. The five algorithms are based on support vector machines, bagging, random forest, classification or regression tree and maximum entropy. In this study, we proposed entropy score which can comprehensively evaluate the performance of classification algorithm. As a result of evaluating five algorithms using an entropy score, the SVMs algorithm's entropy score was ranked highest.

• Information Systems Review
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• v.20 no.2
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• pp.111-137
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• 2018

Considering the increase in health insurance benefits and the elderly population of the baby boomer generation, the amount consumed by health care in 2020 is expected to account for 20% of US GDP. As the healthcare industry develops, competition among the medical services of hospitals intensifies, and the need of hospitals to manage the quality of medical services increases. In addition, interest in online reviews of hospitals has increased as online reviews have become a tool to predict hospital quality. Consumers tend to refer to online reviews even when choosing healthcare service providers and after evaluating service quality online. This study aims to analyze the effect of sentiment score of healthcare service quality on hospital rating with Yelp hospital reviews. This study classifies large amount of text data collected online primarily into five service quality measurement indexes of SERVQUAL theory. The sentiment scores of reviews are then derived by SERVQUAL dimensions, and an econometric analysis is conducted to determine the sentiment score effects of the five service quality dimensions on hospital reviews. Results shed light on the means of managing online hospital reputation to benefit managers in the healthcare and medical industry.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.2
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• pp.213-219
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• 2020

Studies related to Electronic Word-of-Mouth (eWOM) show that the acceptance of eWOM information is an important factor in customer purchase decisions. When consumers accept eWOM information, they tend to use that information in considering before making purchase decisions. In Viet Nam, there are few studies about eWOM information, especially on the acceptance of eWOM information. Research is conducted to test the influence of consumers on the perception of the senders' identity to the acceptance of online reviews (a kind of eWOM) in Viet Nam - a case study in Ho Chi Minh City. Using adjustment techniques, inspecting the scales and a theoretical model represent the relationship among the influential factors. The research is based on a sample of 522 consumers who use the Internet to search for product reviews before buying and used Structural Equation Modeling (SEM) to test the relationships among the variables. The research results show that the scales of the variables: Message Quality, Source Credibility, Perceived Message Usefulness, Perceived Senders' Identity, Perceived Message Credibility, Message Acceptance attain the validity and reliability in the research. The research contributes to the understanding of the determinants that influence the acceptance of eWOM information, which are informational factors, and factors related to consumer skepticism.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.693-700
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• 2023

Sentiment analysis, a branch of natural language processing that classifies and identifies subjective opinions and emotions in text documents as positive or negative, can be used for various promotions and services through customer preference analysis. To this end, recent research has been conducted utilizing various techniques in machine learning and deep learning. In this study, we propose an optimal language model by comparing the accuracy of sentiment analysis for movie, product, and game reviews using existing RNN-based models and recent Transformer-based language models. In our experiments, LMKorBERT and GPT3 showed relatively good accuracy among the models pre-trained on the Korean corpus.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.1
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• pp.91-107
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• 2023

With the recent expansion of the commerce ecosystem, a large number of user evaluations have been produced. Accordingly, attempts to create business insights using user evaluation data have been actively made. However, since user evaluation can change after the user experiences the product, it is difficult to say that the analysis based only on reviews immediately after purchase fully reflects the user's evaluation of the product. Moreover, studies conducted so far on user evaluation have overlooked the fact that the length of time a user has used a product can affect the user's product evaluation. Therefore, in this study, we build a model that predicts the direction of change in the user's rating after use from the user's rating and reviews immediately after purchase. In particular, the proposed model reflects the product's period of use in predicting the change direction of the star rating. However, since the posterior information on the duration of product use cannot be used as input in the inference process, we propose a structure that utilizes information about the product's period of use using an auxiliary classifier. As a result of an experiment using 599,889 user evaluation data collected from the shopping platform 'N' company, we confirmed that the proposed model performed better than the existing model in terms of accuracy.

• Asia pacific journal of information systems
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• v.18 no.1
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• pp.1-23
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• 2008

As managing customer relationship gets more important, companies are strengthening information service using multi-channels to their customers as a part of their customer relationship management (CRM) initiatives. It means companies are now accepting such information services not as simple information -delivering tools, but as strategic initiatives for acquiring and maintaining customer loyalty. In this paper, we attempt to validate whether or not such various information services would impact on organizational performance in terms of CRM strategy. More specifically, our research objective is to answer the next three questions: first, how to construct the instruments to measure not information quality but information service quality?; second, which attributes of information service quality can influence corporate image and customer loyalty?; finally, does each information service type have unique characteristics compared with others in terms of influencing corporate image and customer loyalty? With respect to providing answers to those questions, the previous studies had been limited in that those studies failed to consider the variety of types of information service or restricted the quality of information service to information quality. An appropriate research model answering the above questions should consider the fact that most companies are utilizing multi channels for their information services, and include the recent strategic information service such as customer online community. Moreover, since corporate information service could be regarded as a type of products or services delivered to customer, it is necessary to adopt the criteria for assessing customer's perceived value when to measure the quality of information service. Therefore, considering both multi-channels and multi-traits may enable us to tell the detailed causal routes showing which quality attributes of which information service would affect corporate image and customer loyalty. As information service channels, we include not only homepage and DM (direct mail), which are the most frequently applied information service channels, but also online community, which is getting more strategic importance in recent years. With respect to information service quality, we abstract information quality, convenience of information service, and timeliness of information service through a wide range of relevant literature reviews. As our dependant variables, we consider corporate image and customer loyalty that both of them are the critical determinants of organizational performance, and also attempt to grasp the relationship between the two constructs. We conducted a huge online survey at the homepage of one of representative dairy companies in Korea, and gathered 367 valid samples from 407 customers. The reliability and validity of our measurements were tested by using Cronbach's alpha coefficient and principal factor analysis respectively, and seven hypotheses were tested through performing correlation test and multiple regression analysis. The results from data analysis demonstrated that timeliness and convenience of homepage have positive effects on both corporate image and customer loyalty. In terms of DM, its' information quality was represented to influence both corporate image and customer loyalty, but we found its' convenience have a positive effect only on corporate image. With respect to online community, we found its timeliness contribute significantly both to corporate image and customer loyalty. Finally, as we expected, corporate image was revealed to provide a great influence to customer loyalty. This paper provides several academic and practical implications. Firstly, we think our research reinforces CRM literatures by developing the instruments for measuring information service quality. The previous relevant studies have mainly depended on the measurements of information quality or service quality which were developed independently. Secondly, the fact that we conducted our research in a real situation may enable academics and practitioners to understand the effects of information services more clearly. Finally, since our study involved three different types of information service which are most frequently applied in recent years, the results from our study might provide operational guidelines to the companies that are delivering their customers information by multi-channel. In other words, since we found that, in terms of customer loyalty, the key areas would be different from each other according to the types of information services, our analysis would help to make decisions such as selecting strengthening points or allocating resources by information service channels.

• Journal of Industrial Convergence
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• v.21 no.8
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• pp.23-33
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• 2023

Consumer review analysis is important for product development, customer satisfaction, competitive advantage, and effective marketing. Increased use of wireless earphones is expected to reach $45.7 billion by 2026 with growth in lifestyle. Therefore, in consideration of the growth and importance of the market, consumer reviews of wireless earphones from Apple and Samsung were analyzed. In this study, 11,320 wireless earphone reviews from Apple and Samsung sold on Coupang were collected to analyze consumers' purchase intentions and analyze consumer satisfaction through analysis of the frequency, sensitivity, and LDA topic model of text mining. As a result of topic modeling, 16 topics were derived and classified into sound quality, connection, shopping mall service, purchase intention, battery, delivery, and price. As a result of brand comparison, Samsung purchased a lot for gift purposes, had a high positive sentiment for price, and Apple had a high positive sentiment for battery, sound quality, connection, service, and delivery. The results of this study can be used as data for related industries as a result of research that can obtain improvements and insights on customer satisfaction, quality and market trends, including manufacturing, retail, marketers, and consumers.