• The Journal of Information Systems
• /
• v.31 no.2
• /
• pp.1-18
• /
• 2022

Purpose Customer review is a major factor in choosing certain restaurants. This study investigates the key factors affecting customer's evaluation about restaurants. With the recent intensification of competition among restaurants in the service industry, the analysis results are expected to provide in-depth insights for enhancing customer experiences. Design/methodology/approach We collected information and reviews provided at the restaurants in the Kakao Map platform. The information collected is based on the information of 3,785 restaurants in Daegu registered on Kakao Map. Based on the information collected, seven independent variables, including number of rating registered, number of reviews, presence or absence of safe restaurants, presence or absence of a posting about holding facilities, presence or absence of a posting about business hours, presence or absence of a posting about hashtags, and presence or absence of break times, were used. Dependent variable is restaurant rating. Multiple regression between independent variables and restaurant rating was carried out. Findings The results of the study confirmed that number of rating registered, presence or absence of a posting about business hours, and presence or absence of a posting about hash tags have an positive effects on the restaurant rating. The number of reviews had a negative effect on the restaurant rating. In addition, in order to confirm the role of customer's reviews, we carried out LDA topic modeling. We divided the topics into the positive review and the negative reviews.

• Korean Management Science Review
• /
• v.26 no.1
• /
• pp.183-196
• /
• 2009

Customer retention has been a pressing issue for companies to get and maintain the loyal customers in the competing environment. Lots of researchers make effort to seek the characteristics of the churning customers and the loyal customers using the data mining techniques such as decision tree. However, such existing researches don't consider relationships among customers. Social network analysis has been used to search relationships among social entities such as genetics network, traffic network, organization network and so on. In this study, a customer network is proposed to investigate the differences of network characteristics of churning customers and loyal customers. The customer networks are constructed by analyzing the real purchase data collected from a Korean cosmetic provider. We investigated whether the churning customers and the loyal customers have different degree centralities and densities of the customer networks. In addition, we compared products purchased by the churning customers and those by the loyal customers. Our data analysis results indicate that degree centrality and density of the churning customer network are higher than those of the loyal customer network, and the various products are purchased by churning customers rather than by the loyal customers. We expect that the suggested social network analysis is used to as a complementary analysis methodology with existing statistical analysis and data mining analysis.

• Korean Management Science Review
• /
• v.19 no.2
• /
• pp.1-23
• /
• 2002

It has been considered as a means for sustaining a competitive advantage for companies to build and maintain long-term relationships with customers. It is without any doubt that many companies have tried to initiate Customer Relationship Management (CRM). For the effective management of customer relationships, it is critical that they acquire. share and use customer information and knowledge. In this paper, we deduced 9 important factors affecting the qualify of customer information and knowledge from the literature reviews on CRM, and developed the questionnaire to measure these factors. The factors are again categorized into organizational system, employees and IT. We analyzed data collected from 30 companies in service industries such as the finance. distribution and communication industries. The result of data analysis demonstrates that the employees' analytical shills and appraisal and reward systems are closely related to the quality of customer information, and analytical skills and IT support for communications with customers are associated with the quality of customer knowledge. implications of findings and future research directions are discussed.

• Journal of Information Technology Services
• /
• v.15 no.3
• /
• pp.223-245
• /
• 2016

This study defines copyrighted public records in broad sense including open government data and public domain except for some private records. Additionally, this study aims to investigate improvement plan for maximizing utilization of copyrighted public records in web-sites using customer side, without consideration of supplier side. For this purpose, qualitative study method was used with grounded theory on analyzed problems from literature review and case study. Literature review was concentrated on definition of open data and abroad utilization indicators whereas case study analyzed current situation of four web-sites providing copyrighted public records. Converged opinions from in-depth interview and various statistical data was analyzed as a basis for grounded theory, then a paradigm model was constructed and future improvement plans were presented. The findings imply that opening of copyrighted public records is not just important for quantitative results, rather it requires qualitative improvement providing latest credible information that is consistent with the demand of the customer. Thus, development of service platform and business models for copyrighted public records are urgent task.

• Korea Trade Review
• /
• v.47 no.5
• /
• pp.253-272
• /
• 2022

As the digital era accelerates, traditional perspectives have limitations in explaining the success or failure of export performance. The purpose of this study is to analyze new factors affecting export performance from the perspective of customer experience, which has emerged as an important factor in securing a competitive advantage and generating organizational performance. After deriving hypotheses based on literature review and discussion, a research model is designed in which three factors of customer experience such as understanding customer's objectives, customer value creation capability, and customer journey management are the antecedents, and export performance is the dependent variable. This model also includes organizational agility and personal contact as the moderating variables. To verify the hypotheses, multiple regression analysis was conducted on the collected data drawn from 198 SME exporters. According to the analysis results, it was found that all three antecedents positively affected export performance. In particular, the organizational agility and personal contact were confirmed to have a moderating effect that creates better export performance by interacting with customer value creation capability. The theoretical significance of this study is to find that effective customer experience management can be a key factor in creating export performance. The results suggest that checking the overall customer journey, exporters should select and intervene to intensively manage key touch points that can have a decisive impact on the quality of customer experience. At the end of the paper, practical implications to be considered in creating export performance through effective customer experience management are presented.

• Korean Management Science Review
• /
• v.21 no.3
• /
• pp.85-99
• /
• 2004

The retention of customer is an increasingly pressing issue in today's competitive environment. The proposes of this paper is a personalized defection detection and the procedure of prevention based on economic analysis of customer defection possibility, and behaviour state transition cost. This procedure is based on the observation that potential defectors have a tendency to take a couple of months or weeks to gradually change their behaviour before their eventual withdrawal. In this procedure, the SOM(Self-Organizing Map) is used to determine the possible states of customer behaviour from past behaviour data, and to prevent the defection of potential defectors, the proposed procedure recommends the desirable behaviour state for the next period based on the analysis of transition cost. and likelihood of defection. The case study has been conducted for a Korean on-line game provider to evaluate of this procedure.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.8
• /
• pp.443-451
• /
• 2021

The classification standards for hotels in Vietnam are different from many other hotel classification standards in the world. This study aims to analyze customer reviews on the TripAdvisor website to develop a new algorithm for hotel rating that is independent of Vietnam's hotel classification standards. This method can be applied to individual hotels, or hotels of a region or the whole country, while online booking sites only rate individual hotels. Data was crawled from TripAdvisor with 22,287 reviews of 5 cities in Vietnam. This study used a statistical model to analyze the review dataset and build an algorithm to rate hotels according to aspects or hotel overall. The results have less rating deviation when compared to the TripAdvisor system. This study also supports hotel managers to regularly update the status of their hotels using data from customer reviews, from which, managers can strategize long-term solutions to improve the quality of the hotel in all aspects and attract more travelers to Vietnam. Moreover, this method can be developed into an automatic system to rate hotels and update the status of service quality more quickly, thus, saving time and costs.

• Journal of Information Technology Applications and Management
• /
• v.30 no.2
• /
• pp.1-18
• /
• 2023

Recently, as technology development has accelerated and product life cycles have been shortened, it is necessary to derive key product features from customers in the R&D planning and evaluation stage. More companies want differentiated competitiveness by providing consumer-tailored products based on big data and artificial intelligence technology. To achieve this, the need to correctly grasp the required quality, which is a requirement of consumers, is increasing. However, the existing methods are centered on suppliers or domain experts, so there is a gap from the actual perspective of consumers. In other words, product attributes were defined by suppliers or field experts, but this may not consider consumers' actual perspective. Accordingly, the demand for deriving the product's main attributes through reviews containing consumers' perspectives has recently increased. Therefore, we propose a review data analysis-based required quality methodology containing customer requirements. Specifically, a pre-training language model with a good understanding of Korean reviews was established, consumer intent was correctly identified, and key contents were extracted from the review through a combination of KeyBERT and topic modeling to derive the required quality for each product. RevBERT, a Korean review domain-specific pre-training language model, was established through further pre-training. By comparing the existing pre-training language model KcBERT, we confirmed that RevBERT had a deeper understanding of customer reviews. In addition, all processes other than that of selecting the required quality were linked to the automation process, resulting in the automation of deriving the required quality based on data.

• The Korean Journal of Health Service Management
• /
• v.14 no.1
• /
• pp.31-42
• /
• 2020

Objectives: The purpose of this study was to explore how service quality in specialized hospitals influences customer loyalty under the mediating effects of customer trust and customer value. Methods: A statistical review was done based on the survey results of patients who had used a specialized hospital in Gyeonggi Province, South Korea. A total of 209 questionnaires were collected. After data collection, an empirical analysis was performed using SPSS 21.0 and AMOS 21.0 software. Results: Interaction quality (β = 0.254, p < 0.05) and result quality (β = 0.179, p < 0.05) significantly influenced customer trust, while physical environmental quality (β = 0.121, p > 0.05) did not. Customer trust (β = 0.571, p < 0.01) influenced customer value (β = 0.136, p < 0.05) and customer value influenced customer loyalty. In addition, customer confidence (β = 0.668, p < 0.05) was shown to have directly impacted customer loyalty without the mediating effect of customer value (0.078). Conclusions: The findings showed that interaction quality and resulting quality had important implications for customer loyalty. We therefore suggest compliance with appointment times, training to improve work-related skills for employees, improving customer satisfaction, and enhancing communication skills.

• Korean Business Review
• /
• v.15
• /
• pp.79-97
• /
• 2002

In this study, an analytical CRM for customer segmentation is exercised by integrating and analyzing the customer profile data and the access data to a particular web site. We believe that effective customer segmentation will be possible with a basis of the understanding of customer characteristics as well as behavior on the web. One of the critical tasks in the web data-mining is concerned with both 'how to collect the data from the web in an efficient manner?' and 'how to integrate the data(mostly in a variety of types) effectively for the analysis?' This study proposes a panel approach as an efficient data collection method in the web. For the customer data analysis, OLAF and a tree-structured algorithm are applied in this study. The results of the analysis with both techniques are compared, confirming the previous work which the two techniques are inter-complementary.