• Management & Information Systems Review
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• v.36 no.5
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• pp.45-60
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• 2017

This study aims to elucidate the key improvements through the current state of customer support for smart home services based on the Internet of things and the evaluation of user's usage. Smart home services typically provide a wide range of value in terms of security, safety, manageability (electricity and water use), convenience, and remote management accessibility. In this study, we analyzed the current state of smart home service based on Internet of Samsung, SKT and LG U + companies in Korea. However, since LG U+ is the only company providing user reviews, there is a limit to generalization, but we are trying to figure out whether the customer value is conveyed properly or not, and in which part the customer support is focused to support the service. As a result of analyzing the results of the study, we found that the smart home service is commercialized and marketed in various forms. However, it is questionable whether the technological level and user satisfaction level are sufficiently satisfied. The results of this study are as follows. First, although each company provides usage guidance, they still ask many questions about joining products and using products. Second, there are many defects in the product itself, and it is found that the companies are not satisfied with the overall response. Third, the three companies are focusing on switches, outlets, sensors, and lamps. This is an individual intelligent product rather than an interlocking or linking level, and it can be seen that there are many parts that are not compatible with the concept of the original Internet of things. In conclusion, this study shows that there are still many areas to improve on the level of customer service provision of smart home service, in particular, the ease of use is low and the quality of products is not reliable. We would like to present the improvement of this in detail through this study and reflect the companies that provide it and the service providers.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.9-15
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• 2019

Large global online shopping malls, such as Amazon, offer services in English or in the language of a country when their products are sold. Since many customers purchase products based on the product reviews, the shopping malls actively utilize the sentimental analysis technique in judging preference of each product using the large amount of review data that the customer has written. And the result of such analysis can be used for the marketing to look the potential shoppers. However, it is difficult to apply this English-based semantic analysis system to different languages used around the world. In this study, more than 500,000 data from Amazon fine food reviews was used for training a deep learning based system. First, sentiment analysis evaluation experiments were carried out with three models of English test data. Secondly, the same data was translated into seven languages (Korean, Japanese, Chinese, Vietnamese, French, German and English) and then the similar experiments were done. The result suggests that although the accuracy of the sentimental analysis was 2.77% lower than the average of the seven countries (91.59%) compared to the English (94.35%), it is believed that the results of the experiment can be used for practical applications.

• The Journal of the Korea Contents Association
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• v.14 no.8
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• pp.416-430
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• 2014

As the online word-of-mouth(WOM) using SNS has significant influence on consumer decision-making, the hospitality industry including the restaurant industry has actively used SNSs as one of major marketing tools. While researchers have focused on impacts of the online WOM, there is little research on motivations to provide WOM and its impacts on the WOM providers. The purpose of this study is to examine whether sharing the restaurant experience on Facebook, the representative SNSs, can change customer satisfaction and intentions to revisit and recommended and whether the type of motivations to share the restaurant experiences on Facebook affects customer satisfaction and intentions to revisit and recommend. The total of 260 college students volunteered to participate in this study. They first visited a restaurant and completed surveys twice before and after sharing their restaurant experience on Facebook. According to the study results, the levels of satisfaction, intention to revisit and intention to recommend after sharing the restaurant experience were found to be higher than before sharing the experience. This study also found that people who shared their restaurant experience for nostalgia were more likely to be satisfied with the restaurant services and have a higher level of intentions to revisit and recommend the restaurant. Theoretical and managerial implications as well as limitations and future research directions are discussed.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.3
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• pp.97-111
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• 2013

This study reviews preceding research for detailed factors to establish development strategies for Korean Hidden Champion firms and classifies strategy factors into internal ones and external ones through specialists' opinions to draw strengths, weaknesses, opportunities and threats of each factor. It also sets hierarchical model to draw up a survey, distributes the survey to groups of specialists and enterprises respectively and then examines consistency ratio. Fifty-four copies of survey whose reliability on responses is secured through examining the consistency ratio are evaluated with their relative importance in factors by using SWOT/AHP technique and their order of priority is determined. Based on their results, development strategies for Korean Hidden Champion firms are established. SWOT/AHP analyses results show that external factors are with the opportunity of industry growth and the threat of intensified competition and market uncertainty and internal factors are with the strength in order of technological competence, construction competence in customer relation and marketing competence. The weakness in the lack of funds, lack of brand awareness in order. This result suggests that external environments of enterprises that more emphasis should be put on the industry growth and aggressive strategies cannot help but be adopted even in a global competition getting fiercer every day are seen more important. Then, it also seems to be thought that the technological competence including R&D and specialization, construction competence in customer relation and marketing competence should internally chosen for strategies to support strategies. The order of priority in development strategies for Korean Hidden Champion firms is drawn as; (i) aggressive S/O strategy which utilizes opportunities by taking advantage of strengths, (ii) W/O strategy which utilizes opportunities by supplementing weaknesses, (iii) diversified S/T strategy which utilizes strengths to make up for threats and (iv) defensive W/T strategy which supplements weaknesses to overcome threats.

• The Journal of Society for e-Business Studies
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• v.24 no.2
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• pp.71-89
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• 2019

In order to come up with satisfying product and improvement, firms use traditional marketing research methods to obtain consumers' opinions and further try to reflect them. Recently, gathering data from consumer communication platforms like internet and SNS has become popular methods. Meanwhile, with the development of information technology, mobile companies are launching new digital products for children to protect them from harmful content and provide them with necessary functions and information. Among these digital products, Kids Phone, which is a wearable device with safe functions that enable parents to learn childern's location. Kids phone is relatively cheaper and simpler than smartphone but it is noted that there are several problems such as some useless functions and frequent breakdowns. This study analyzes the reviews of Kids phones from domestic mobile companies, identifies the characteristics, strengths and weaknesses of the products, proposes improvement methods strategies for devices and services through SNS consumer analysis. In order to do that customer review data from online shopping malls was gathered and was further analyzed through text mining methods such as TF/IDF, Sentiment Analysis, and network analysis. Customer review data was gathered through crawling Online shopping Mall and Naver Blog/$Caf\acute{e}$. Data analysis and visualization was done using 'R', 'Textom', and 'Python'. Such analysis allowed us to figure out main issues and recent trends regarding kids phones and to suggest possible service improvement strategies based on sentiment analysis.

• Information Systems Review
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• v.24 no.1
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• pp.157-181
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• 2022

As competition in the airline industry intensifies, effective airline service quality evaluation has become one of the main challenges. In particular, as big data analytics has been touted as a new research paradigm, new research on service quality measurement using online review analysis has been attempted. However, these studies do not use review titles for analysis, relyon supervised learning that requires a lot of human intervention in learning, and do not consider airline characteristics in classifying service quality dimensions.To overcome the limitations of existing studies, this study attempts to measure airlines service quality and to classify it into the AIRQUAL service quality dimension using online review text as well as title based on self-trainingand sentiment analysis. The results show the way of effective extracting service quality dimensions of AIRQUAL from online reviews, and find that each service quality dimension have a significant effect on service satisfaction. Furthermore, the effect of review title on service satisfaction is also found to be significant. This study sheds new light on service quality measurement in airline industry by using an advanced analytical approach to analyze effects of service quality on customer satisfaction. This study also helps managers who want to improve customer satisfaction by providing high quality service in airline industry.

• Information Systems Review
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• v.25 no.2
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• pp.181-203
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• 2023

With the fierce competition of companies for the attraction of outstanding individuals, job satisfaction of employees has been of importance. In this circumstance, many companies try to invest in job satisfaction improvement by finding employees' everyday experiences and difficulties. However, due to a lack of understanding of the employee experience, their investments are not paying off. This study examined the relationship between employee experience and job satisfaction using employee reviews and company ratings from Glassdoor, one of the largest employee communities worldwide. We use text mining techniques such as K-means clustering and LDA topic-based sentiment analysis to extract key experience factors by job level, and DistilBERT sentiment analysis to measure the sentiment score of each employee experience factor. The drawn employee experience factors and each sentiment score were analyzed quantitatively, and thereby relations between each employee experience factor and job satisfaction were analyzed. As a result, this study found that there is a significant difference between the workplace experiences of managers and general employees. In addition, employee experiences that affect job satisfaction also differed between positions, such as customer relationship and autonomy, which did not affect the satisfaction of managers. This study used text mining and quantitative modeling method based on theory of work adjustment so as to find and verify main factors of employee experience, and thus expanded research literature. In addition, the results of this study are applicable to the personnel management strategy for improving employees' job satisfaction, and are expected to improve corporate productivity ultimately.

• Asia Marketing Journal
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• v.15 no.4
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• pp.61-101
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• 2014

This study investigates when and how disagreements in online customer ratings prompt more favorable product evaluations. Among the three metrics of volume, valence, and variance that feature in the research on online customer ratings, volume and valence have exhibited consistently positive patterns in their effects on product sales or evaluations (e.g., Dellarocas, Zhang, and Awad 2007; Liu 2006). Ratings variance, or the degree of disagreement among reviewers, however, has shown rather mixed results, with some studies reporting positive effects on product sales (e.g., Clement, Proppe, and Rott 2007) while others finding negative effects on product evaluations (e.g., Zhu and Zhang 2010). This study aims to resolve these contradictory findings by introducing preference heterogeneity as a possible moderator and causal attribution as a mediator to account for the moderating effect. The main proposition of this study is that when preference heterogeneity is perceived as high, a disagreement in ratings is attributed more to reviewers' different preferences than to unreliable product quality, which in turn prompts better quality evaluations of a product. Because disagreements mostly result from differences in reviewers' tastes or the low reliability of a product's quality (Mizerski 1982; Sen and Lerman 2007), a greater level of attribution to reviewer tastes can mitigate the negative effect of disagreement on product evaluations. Specifically, if consumers infer that reviewers' heterogeneous preferences result in subjectively different experiences and thereby highly diverse ratings, they would not disregard the overall quality of a product. However, if consumers infer that reviewers' preferences are quite homogeneous and thus the low reliability of the product quality contributes to such disagreements, they would discount the overall product quality. Therefore, consumers would respond more favorably to disagreements in ratings when preference heterogeneity is perceived as high rather than low. This study furthermore extends this prediction to the various levels of average ratings. The heuristicsystematic processing model so far indicates that the engagement in effortful systematic processing occurs only when sufficient motivation is present (Hann et al. 2007; Maheswaran and Chaiken 1991; Martin and Davies 1998). One of the key factors affecting this motivation is the aspiration level of the decision maker. Only under conditions that meet or exceed his aspiration level does he tend to engage in systematic processing (Patzelt and Shepherd 2008; Stephanous and Sage 1987). Therefore, systematic causal attribution processing regarding ratings variance is likely more activated when the average rating is high enough to meet the aspiration level than when it is too low to meet it. Considering that the interaction between ratings variance and preference heterogeneity occurs through the mediation of causal attribution, this greater activation of causal attribution in high versus low average ratings would lead to more pronounced interaction between ratings variance and preference heterogeneity in high versus low average ratings. Overall, this study proposes that the interaction between ratings variance and preference heterogeneity is more pronounced when the average rating is high as compared to when it is low. Two laboratory studies lend support to these predictions. Study 1 reveals that participants exposed to a high-preference heterogeneity book title (i.e., a novel) attributed disagreement in ratings more to reviewers' tastes, and thereby more favorably evaluated books with such ratings, compared to those exposed to a low-preference heterogeneity title (i.e., an English listening practice book). Study 2 then extended these findings to the various levels of average ratings and found that this greater preference for disagreement options under high preference heterogeneity is more pronounced when the average rating is high compared to when it is low. This study makes an important theoretical contribution to the online customer ratings literature by showing that preference heterogeneity serves as a key moderator of the effect of ratings variance on product evaluations and that causal attribution acts as a mediator of this moderation effect. A more comprehensive picture of the interplay among ratings variance, preference heterogeneity, and average ratings is also provided by revealing that the interaction between ratings variance and preference heterogeneity varies as a function of the average rating. In addition, this work provides some significant managerial implications for marketers in terms of how they manage word of mouth. Because a lack of consensus creates some uncertainty and anxiety over the given information, consumers experience a psychological burden regarding their choice of a product when ratings show disagreement. The results of this study offer a way to address this problem. By explicitly clarifying that there are many more differences in tastes among reviewers than expected, marketers can allow consumers to speculate that differing tastes of reviewers rather than an uncertain or poor product quality contribute to such conflicts in ratings. Thus, when fierce disagreements are observed in the WOM arena, marketers are advised to communicate to consumers that diverse, rather than uniform, tastes govern reviews and evaluations of products.

• The Journal of Information Systems
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• v.15 no.3
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• pp.1-34
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• 2006

The purpose of this study Is to develop empirically validated instrument for business model. The previous researches related to business model were almost taxonomies. And the focus of those researches were the classification by the degree of integration and innovation the origin, and the main source of revenue etc. In the emerging fields such as IT, e-commerce, and e-business, it tends to overlook methodological issue in its substantive relationships and also measurement. Business model is taken an interest in recent years. However, as the non-establishment of construct on business model has made no empirical study, this, study tries to develop an empirical validated instrument that identifies the dimensions of business model by uncovering meaningful group or categories. For this, the outlined domain of business model are defined as an organizational level that competes in the industry through the literature reviews. And the traits such as process integration, value chain reconstruction, strategic alliance with another business model, specialty in a certain wet sustainability of essential capabilities, differentiation, convertibility, customer orientation, revenue stream, newness, innovation leadership: and vision sharing are identified in those respective domains, and then the traits are classified into five dimensions such as interlinkageableness, valueness, functionalness, preemptiveness, and goalness by their characteristics. Generating items are continued on the basis of operationalization. Confirmatory factor analysis is performed in order to develop validated instrument with LISREL measurement model. Finally the instrument is developed through the previous procedure. The implication of this study is the first empirical effort to assess business model. The resulting instrument can be used with dependent variables in the future study related to business model. And the establishment of construct of business model is able to make a basis to rise an additional issue consequently. In the practical side, the instrument also can be employed as an assessment framework that can assess whether the expected value success or not. The instrument with the measurement can be used on competitor's business model, In. When an investment into a i-m with a specific business model, these instrument developed can be presented as the basic framework of assessment.

• Fashion & Textile Research Journal
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• v.22 no.5
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• pp.617-627
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• 2020

This study investigates the apparel sizing communication presented in online retail websites focusing on women's ready-to-wear tailored jackets and to analyze the meaning of these information as the actual product size guide factor. A total of 34 retail websites were selected based on the highest growth fashion companies list and the best fashion brands list. We collected size information in two types: size specifications including sizing code, body measurements, garment measurements, and size references including customized size guide tools, size information in customer reviews, model size information, and others. Most websites prefer to present garment measurements rather than body measurements that are recommended notations under Korean standards and related regulations. In addition, there was the absence of consistency in presenting measurements list and terms that can confuse consumers in size communication. This study found that the stature measurement was a key factor in size reference despite that it did not represent a proper garment size. The obsolete Korean numbering sizing code such as '55 and '66 was still used in many ways such as idiomatic expressions for body shape. It also implied that we can take advantage of the old sizing code for accessible size information. The finding of this study gives an in-depth diagnosis of current online sizing information problems and suggests useful basic data for developing online apparel size standards and marketing strategies.