• 제목/요약/키워드: Customer Review

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A Study on the Customer-based Pricing Approach for Railway Fare of Express Train

  • KIM, Gyu-Bae;KANG, Sung-Wook
    • 동아시아경상학회지
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    • 제9권4호
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    • pp.93-102
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    • 2021
  • Purpose - Among the various pricing approaches used to set fares for express trains, this study explores a method of utilizing a customer-based pricing approach. The purpose of this study is to figure out how to apply the customer-based pricing approach to fares of new railway services using express trains. Research design, data, and methodology - This study was conducted through a literature review and case studies. In the literature review, we examined three approaches, focusing on the customer-based pricing approach and its application. In the case studies, we show how a customer-based pricing approach can be applied to determining the fares for railway services. Result - Some studies have used a customer-based pricing approach to set railway service rates, adapting the concepts of customer-based pricing such as demand, elasticity, value and willingness to pay. When setting fares of new railway services, it is recommended to use the customer-based approach in conjunction with other pricing approaches. Conclusion - This study demonstrates that a customer-based pricing approach is a promising tool in making decisions on railway fares. By applying a customer-based pricing approach to fares for new railway services using express trains, railway operators can utilize new service rates and increase the profitability of the railway business.

인터넷 쇼핑몰에서 차원별 서비스 품질과 관계의 질(고객만족) 미래의도간의 관계 (The Study of Dimension of Service Quality of Internet Shopping Mall on Quality of Customer Relationship(Customer Satisfaction) and Relationship of between Future Intention)

  • 이덕재;전동매
    • 통상정보연구
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    • 제8권2호
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    • pp.37-58
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    • 2006
  • The purpose of this study were to empirically examine the effect of dimension of service quality of internet shopping mall on quality of customer relationship(customer satisfaction) and Relationship of between Future Intention. This study first extracted environment, general interaction between customer and internet shopping mall, personalized interaction between customer and internet shopping mall, interaction between customers and outcome from service quality of internet shopping mall. Then established study model and hypotheses through the review of the effect of service quality of internet shopping mall on quality of customer relationship. and the effect of customer relationship quality on future intention. The results were as follows: At among of the six hypotheses, four hypotheses were accepted and two hypotheses were rejected First, for the relationship between dimensions of service quality of internet shopping mall and Customers satisfaction, only the environment had not significant influence on Customers satisfaction, other dimensions had significant positive influence on satisfaction. second, for the relationship between quality factors of customer relationship and future intention, only Customers satisfaction had not significant influence on future intention.

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Factors Affecting Online Purchase Decision, Customer Satisfaction, and Brand Loyalty: An Empirical Study from Indonesia's Biggest E-Commerce

  • HARTANTO, Nico;MANI, La;JATI, Mustika;JOSEPHINE, Ruth;HIDAYAT, Z.
    • 유통과학연구
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    • 제20권11호
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    • pp.33-45
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    • 2022
  • Purpose: The development of online shopping trends in Indonesia is increasing, and Tokopedia is becoming one of the most popular e-commerce websites. The purpose of this study is to obtain empirical evidence whether mobile shopping, customer review, perceived credibility, and Korean celebrity endorsement affect online purchase decision, whether online purchase decision affects customer satisfaction, and whether customer satisfaction affects brand loyalty of customers in Tokopedia e-commerce. Research Design, data and methodology: Quantitative survey with data was collected using an online questionnaire with sample characteristics were Tokopedia customers who lived in Jakarta by 385 samples using the purposive sampling method, and data analysis was conducted using the Smartpls application program version 3.0. Results: Mobile shopping, customer review, and perceived credibility had positive effects on online purchase decision at Tokopedia in Jakarta. However, Korean celebrity endorsement did not have a positive effect on online purchase decision at Tokopedia in Jakarta. Furthermore, online purchase decision had a positive effect on customer satisfaction at Tokopedia in Jakarta, and customer satisfaction had a positive effect on brand loyalty at Tokopedia in Jakarta. Conclusions: This study proposes significant implications for maintaining customer relationships to achieve purchasing decision, customer satisfaction, and brand loyalty in the e-commerce industry.

골프장 서비스품질, 고객만족과 재이용 의도간의 관계 (The Relationship of the Service Quality, Customer Satisfaction and Re-use Intention in Golf Culb)

  • 이상석
    • 품질경영학회지
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    • 제32권3호
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    • pp.10-28
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    • 2004
  • This research analysed the Interaction which focus on service quality perception, customer satisfaction, re-use intention in the golf club. First of all, we review the existing literature on measurement of service quality and management. As a result of this review and survey of the employer in golf club, thirteen factors emerged as important to the service management of the golf club; Reservation and Access(RSNA), Golf Course and Convenience Facilities(GCNF), Personal Services(PSER) and After Services(ASER). The structural equation model was utilized for analyzing the influence of service quality factors upon the customer satisfaction and re-use intention. Results show that service quality factors have a statistically significant impact on the customer satisfaction of the golf club. RSNA and GCNF investigated the factors influencing on the satisfaction degree of the customers. But the GCNF and PSER were not significant. Especially, GCNF factors directly influenced on the customer satisfaction and also indirectly impact on the intention of using again.

The Impact of Nonconforming Items on (s, S) Inventory Model with Customer Order Reservation and Cancellation

  • Takemoto, Yasuhiko;Arizono, Ikuo
    • Industrial Engineering and Management Systems
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    • 제8권2호
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    • pp.72-79
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    • 2009
  • The ultimate goal of inventory management is to decide the timing and the quantity of ordering in response to uncertain demands. Recently, some researchers have focused upon an impact of distortions in the information, e.g., customer order cancellation, on an economical inventory policy. The customer order cancellation is considered a kind of distortions in demands, because a demand that is eventually cancelled is equivalent to a phony demand. Also, there are some additional distortions in the inventory information. For instance, the procurement of suppliers may include some nonconforming items as a result of imperfect production and inspection by the suppliers, and/or damage in transit. The nonconforming item should be considered a kind of distortions in the inventory information, because the nonconforming item is equivalent to a phony stock. In this article, we consider an inventory model under the situation that customers can cancel their orders and the procurement of suppliers may include some nonconforming items. Then, we introduce the customer order reservation into the inventory model for the purpose of avoiding the costly backlogs, because the customer order reservation gives retailers a period to fulfill customer's requests. We formulate a periodic review (s, S) inventory model and investigate the economical operation under the situation mentioned above. Further, through the sensitivity analysis, we show the impact of these distortions and the effect of the customer order reservation on the inventory policy.

Hierarchical Attention Network를 활용한 주제에 따른 온라인 고객 리뷰 분석 모델 (Analysis of the Online Review Based on the Theme Using the Hierarchical Attention Network)

  • 장인호;박기연;이준기
    • 한국IT서비스학회지
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    • 제17권2호
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    • pp.165-177
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    • 2018
  • Recently, online commerces are becoming more common due to factors such as mobile technology development and smart device dissemination, and online review has a big influence on potential buyer's purchase decision. This study presents a set of analytical methodologies for understanding the meaning of customer reviews of products in online transaction. Using techniques currently developed in deep learning are implemented Hierarchical Attention Network for analyze meaning in online reviews. By using these techniques, we could solve time consuming pre-data analysis time problem and multiple topic problems. To this end, this study analyzes customer reviews of laptops sold in domestic online shopping malls. Our result successfully demonstrates over 90% classification accuracy. Therefore, this study classified the unstructured text data in the semantic analysis and confirmed the practical application possibility of the review analysis process.

FEROM: Feature Extraction and Refinement for Opinion Mining

  • Jeong, Ha-Na;Shin, Dong-Wook;Choi, Joong-Min
    • ETRI Journal
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    • 제33권5호
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    • pp.720-730
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    • 2011
  • Opinion mining involves the analysis of customer opinions using product reviews and provides meaningful information including the polarity of the opinions. In opinion mining, feature extraction is important since the customers do not normally express their product opinions holistically but separately according to its individual features. However, previous research on feature-based opinion mining has not had good results due to drawbacks, such as selecting a feature considering only syntactical grammar information or treating features with similar meanings as different. To solve these problems, this paper proposes an enhanced feature extraction and refinement method called FEROM that effectively extracts correct features from review data by exploiting both grammatical properties and semantic characteristics of feature words and refines the features by recognizing and merging similar ones. A series of experiments performed on actual online review data demonstrated that FEROM is highly effective at extracting and refining features for analyzing customer review data and eventually contributes to accurate and functional opinion mining.

온라인 북 리뷰 공신력의 구매 수용자 의사결정에 미치는 영향 (The Credibility of Online Book Review on Customer's Purchasing Decision)

  • 최재영;최재웅;한만용
    • 디지털산업정보학회논문지
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    • 제8권1호
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    • pp.191-205
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    • 2012
  • A book review is one of the most important sources of information which provide the descriptive and evaluative contents about books. Reviews have great influence on consumer behavior because they are believed to be more reliable than information provided by sellers. Readers who read a book review includes information about book decide whether they will buy or not. This study examines customer attitude change by book reviews with regarding to different type of information sources(experts and prior customers) and different directions of messages. We address the following research questions: (1) Can positive book reviews with credibility have a positive impact on acceptance of books? (2) Can negative book reviews with credibility have a negative impact on acceptance of books? The results shows that a credibility is an essential factor for affecting customers' mind. When positive book reviews were written, both expert and customer opinions have a positive impact on acceptance of customers. Given negative book reviews of experts, trustworthiness is more important than expertise. However, a objectivity of customer's reviews is more important.

중소기업의 해외마케팅에서 고객경험이 수출성과에 미치는 영향: 인적접촉과 민첩성의 조절효과 (The Effect of Customer Experience on Export Performance in Overseas Marketing of SMEs: Moderating Effects of the Personal Contacts and Agility)

  • 안세화
    • 무역학회지
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    • 제47권5호
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    • pp.253-272
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    • 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.

B2B 거래에서 서술모델과 예측모델을 이용한 고객가치 산정 (Estimating Customer Value under B2B Environment Using Description and Prediction Models)

  • 박찬주;박윤선;주상호;유우연
    • 경영과학
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    • 제20권2호
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    • pp.135-149
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    • 2003
  • Developing a proper program for customer evaluation is one of the most imminent tasks to implement CRM (Customer Relationship Management). Design of the Customer Value model is an important key to the customer evaluation progrgm. This paper proposes two models for estimating Customer Value. The first one is a Description Model for Customer Value based on customer CSI (Customer Satisfaction Index) data. This model represents as quantitative numbers what customers feel from the company or the service. The second one is a Prediction Model which employs factor analysis and regression to predict customer value. This paper exploits the two models to evaluate Customer Value as well as for customer behavior prediction.