• Asia pacific journal of information systems
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• v.25 no.3
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• pp.519-539
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• 2015

Customers are now demanding ever better service from customer service representatives (CSRs) to create superior customer service. Accordingly, CSRs are required to have more specialized knowledge and abilities of customer service. This study examines the roles of accumulated customer knowledge in electronic knowledge repositories (EKRs), which a firm has developed for customer service over time to enhance CSRs' work capabilities and work performance, in the context of call centers. To test the proposed research model and hypotheses, we conducted LISREL analysis using 261 responses collected on CSRs working for inbound call centers. The key results are as follows. First, accumulated customer knowledge in EKRs enhances CSRs' knowledge utilization and service expertise during the customer contact. Second, CSRs' knowledge utilization reinforces service expertise. Finally, service quality depends on CSRs' knowledge utilization and service expertise, but it is not directly related to accumulated customer knowledge. Overall, the findings suggest that accumulated customer knowledge in EKRs enhances CSRs' knowledge utilization and service expertise, and thereby leading to superior service quality.

• Journal of Information Technology Services
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• v.16 no.3
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• pp.185-203
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• 2017

Call center service is enabled by the use of a firm's various information technologies (IT) and accumulated knowledge. IT and knowledge resources have been considered a fundamental infrastructure for developing a firm's business capabilities. Recognizing this, this study examines whether a firm's IT and customer knowledge resources enhance its customer service process capability and thereby contribute to creating superior customer service, at the level of customer service representatives (CSRs). That is, constructs in this study were measured on a basis of CSRs' perception. Moreover, this study verifies the moderating role of CSRs' computer self-efficacy on the relationships between IT and customer knowledge resources and customer service process capability. To test the proposed hypotheses, this study conducted partial least squares (PLS) analysis with a total of 234 data which were collected on CSRs working at four call centers. The key findings are as follows: first, IT infrastructure integration and customer knowledge integration are positively associated with customer service process capability. Second, customer service process capability is a key determinant of customer service performance. Finally, CSRs' computer self-efficacy has a moderating effect on the relationship between IT infrastructure integration and customer service process capability. The details of the findings and implications are presented.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.222-229
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• 2022

Through this technology development, companies that operate online shopping malls and prospective startups will support education, consulting and expert group matching so that they can solve various issues that may arise in the course of the entire business life cycle, from startups to closures. It is expected that differentiated consulting programs will be designed for companies that currently operate shopping malls and start ups, and customized consulting programs will be provided to improve the effectiveness of consulting while improving customer satisfaction. It is planning to develop a "successful start-up and operation helper" that helps successful start-ups. It is a system that primarily diagnoses problems of prospective entrepreneurs and operators through an automation system at the start-up and operation stage, and professional consultants participate to derive and solve problems, and takes care of all stages of shopping mall birth and growth. In this paper Metaverse based shopping mall Creation is also discussed. Through Big Data creation these accumulated data, we intend to help operators start and operate shopping malls through accurate information by managing all knowledge of shopping malls as a system in the long run.

• Knowledge Management Research
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• v.22 no.3
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• pp.273-293
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• 2021

Due to the COVID-19 pandemic, the size of the e-commerce has been increased rapidly. This pandemic, which made contact-less communication culture in everyday life made the e-commerce market to be opened even to the consumers who would hesitate to purchase and pay by electronic device without any personal contacts and seeing or touching the real products. Consumers who have experienced the easy access and convenience of the online purchase would continue to take those advantages even after the pandemic. During this time of transformation, however, the size of information source for the consumers has become even shrunk into a flat screen and limited to visual only. To provide differentiated and competitive information on products, companies are adopting AR/VR and steaming technologies but the reviews from the honest users need to be recognized as important in that it is regarded as strong as the well refined product information provided by marketing professionals of the company and companies may obtain useful insight for product development, marketing and sales strategies. Then from the consumer's point of view, if the ratings of reviews are widely diverged how consumers would process the review information before purchase? Are non-converged ratings always unreliable and worthless? In this study, we analyzed how consumer's regulatory focus moderate the attitude to process the diverged information. This experiment was designed as a 2x2 factorial study to see how the variance of product review ratings (high vs. low) for cosmetics affects product attitudes by the consumers' regulatory focus (prevention focus vs. improvement focus). As a result of the study, it was found that prevention-focused consumers showed high product attitude when the review variance was low, whereas promotion-focused consumers showed high product attitude when the review variance was high. With such a study, this thesis can explain that even if a product with exactly the same average rating, the converged or diverged review can be interpreted differently by customer's regulatory focus. This paper has a theoretical contribution to elucidate the mechanism of consumer's information process when the information is not converged. In practice, as reviews and sales records of each product are accumulated, as an one of applied knowledge management types with big data, companies may develop and provide even reinforced customer experience by providing personalized and optimized products and review information.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.91-110
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• 2011

This paper analyzes the cases where the hotels have increased their services and enhanced their work process through IT solutions to cope with computerization globalization. Also the cases have been studies where national hotels use the CRM solution internally to respond effectively to customers requests, increase customer analysis, and build marketing strategies. In particular, this study discusses the introduction of the CRM solutions and CRM sales business and marketing services using a process for utilizing the presumed, CRM by introducing effective DEA(Data Envelopment Analysis). First, the comparison has done regarding the relative efficiency of L Company with the CCR model, then compared L Company's restaurants and facilities' effectiveness through BCC model. L Company reached a conclusion that it is important to precisely create and manage sales data which are the preliminary data for CRM, and for that reason it made it possible to save sales data generated by POS system on each sales performance database. In order to do that, it newly established Oracle POS system and LORIS POS system concerned with restaurants for food and beverage as well as rooms, and made it possible to stably generate and manage sales data and manage. Moreover, it set up a composite database to control comprehensively the results of work processes during a specific period by collecting customer registration information and made it possible to systematically control the information on sales performances. By establishing a system which unifies database and managing it comprehensively, impeccability of data has been greatly enhanced and a problem which generated asymmetric data could be thoroughly solved. Using data accumulated on the comprehensive database, sales data can be analyzed, categorized, classified through data mining engine imbedded in Polaris CRM and the results can be organized on data mart to provide them in the form of CRM application data. By transforming original sales data into forms which are easy to handle and saving them on data mart separately, it enabled acquiring well-organized data with ease when engaging in various marketing operations, holding a morning meeting and working on decision-making. By using summarized data at data mart, it was possible to process marketing operations such as telemarketing, direct mailing, internet marketing service and service product developments for perceived customers; moreover, information on customer perceptions which is one of CRM's end-products could feed back into the comprehensive database. This research was undertaken to find out how effectively CRM has been employed by comparing and analyzing the management performance of each enterprise site and store after introducing CRM to Hotel enterprises using DEA technique. According to the research results, efficiency evaluation for each site was calculated through input and output factors to find out comparative CRM system usage efficiency of L's Company four sites; moreover, with regard to stores, the sizes of workforce and budget application show a huge difference and so does the each store efficiency. Furthermore, by using the DEA technique, it could assess which sites have comparatively high efficiency and which don't by comparing and evaluating hotel enterprises IT project outcomes such as CRM introduction using the CCR model for each site of the related enterprises. By using the BCC model, it could comparatively evaluate the outcome of CRM usage at each store of A site, which is representative of L Company, and as a result, it could figure out which stores maintain high efficiency in using CRM and which don't. It analyzed the cases of CRM introduction at L Company, which is a hotel enterprise, and precisely evaluated them through DEA. L Company analyzed the customer analysis system by introducing CRM and achieved to provide customers identified through client analysis data with one to one tailored services. Moreover, it could come up with a plan to differentiate the service for customers who revisit by assessing customer discernment rate. As tasks to be solved in the future, it is required to do research on the process analysis which can lead to a specific outcome such as increased sales volumes by carrying on test marketing, target marketing using CRM. Furthermore, it is also necessary to do research on efficiency evaluation in accordance with linkages between other IT solutions such as ERP and CRM system.

• Information Systems Review
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• v.11 no.2
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• pp.183-207
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• 2009

In general, the introduction of information technology to domestic small and middle size firms is depending on the governmental supporting policy. However, even under this situation there is also a case that the building up of information technology is initiated by the management of small and middle size firms. An accumulated know-how for information technology and powerful leadership in such firms are considered as success factors. This study attempts to analyze a case for 'THEFACESHOP', in which MIS is successfully built. To achieve corporate goals, the CEO of THEFACESHOP based on the extensive knowledge of information technology drove to build up information system. Also, the board of directors supported him, and employees committed to their organization. Through the strong leadership of the CEO, the information system of THEFACESHOP became sufficient and efficient. And it led the organization and the information system to be competitive. In particular, the systematic approach of THEF ACESHOP reinforcing its competitiveness can be summarized as follows: First, it tried to construct basic information systems as like ERP etc. to increase work-efficiency. Second, it completed CRM related systems for analysis to maximize its customer orientation and marketing effect. Third, the last step can be stated as the building up of operation related CRM systems to improve the responsiveness of target marketing activities and the profitability of its agencies. Such endeavors of THEFACESHOP contributed to increase productivity and performance of the organization. As a result, THEFACESHOP has had its own 'Natural Story' and price competitiveness. For that reason THEFACESHOP became the best of brand-shop cosmetic firms. This success based on the strong leadership and the systematic investment on the information system.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.99-120
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• 2010

Due to the wide spread of customers' frequent access of non face-to-face services, there have been many attempts to improve customer satisfaction using huge amounts of data accumulated throughnon face-to-face channels. Usually, a call center is regarded to be one of the most representative non-faced channels. Therefore, it is important that a call center has enough agents to offer high level customer satisfaction. However, managing too many agents would increase the operational costs of a call center by increasing labor costs. Therefore, predicting and calculating the appropriate size of human resources of a call center is one of the most critical success factors of call center management. For this reason, most call centers are currently establishing a department of WFM(Work Force Management) to estimate the appropriate number of agents and to direct much effort to predict the volume of inbound calls. In real world applications, inbound call prediction is usually performed based on the intuition and experience of a domain expert. In other words, a domain expert usually predicts the volume of calls by calculating the average call of some periods and adjusting the average according tohis/her subjective estimation. However, this kind of approach has radical limitations in that the result of prediction might be strongly affected by the expert's personal experience and competence. It is often the case that a domain expert may predict inbound calls quite differently from anotherif the two experts have mutually different opinions on selecting influential variables and priorities among the variables. Moreover, it is almost impossible to logically clarify the process of expert's subjective prediction. Currently, to overcome the limitations of subjective call prediction, most call centers are adopting a WFMS(Workforce Management System) package in which expert's best practices are systemized. With WFMS, a user can predict the volume of calls by calculating the average call of each day of the week, excluding some eventful days. However, WFMS costs too much capital during the early stage of system establishment. Moreover, it is hard to reflect new information ontothe system when some factors affecting the amount of calls have been changed. In this paper, we attempt to devise a new model for predicting inbound calls that is not only based on theoretical background but also easily applicable to real world applications. Our model was mainly developed by the interactive decision tree technique, one of the most popular techniques in data mining. Therefore, we expect that our model can predict inbound calls automatically based on historical data, and it can utilize expert's domain knowledge during the process of tree construction. To analyze the accuracy of our model, we performed intensive experiments on a real case of one of the largest car insurance companies in Korea. In the case study, the prediction accuracy of the devised two models and traditional WFMS are analyzed with respect to the various error rates allowable. The experiments reveal that our data mining-based two models outperform WFMS in terms of predicting the amount of accident calls and fault calls in most experimental situations examined.