• Asia pacific journal of information systems
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• v.25 no.4
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• pp.763-783
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• 2015

Online customer reviews (i.e., electronic word-of-mouth) has gained considerable interest over the past years. However, a knowledge gap exists in explaining the mechanisms among the factors that determine the product sales in online retailing environment. To fill the gap, this study adopts a principal-agent perspective to investigate the effect of customer reviews and customer incentives on product sales in online retail stores. Two customer review factors (i.e., average review ratings and the number of reviews) and two customer incentive factors (i.e., price discounts and special shipping offers) are used to predict product sales in regression analysis. The sales ranking data collected from the video game titles at Amazon.com are used to analyze the direct effects of the four factors and the interaction effects between customer review and customer incentive factors to product sales. Result reveals that most relationships exist as hypothesized. The findings support both the direct and interaction effects of customer reviews and incentive factors on product sales. Based on the findings, discussions are provided with regard to the academic and practical contributions.

• Knowledge Management Research
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• v.24 no.4
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• pp.153-176
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• 2023

Generative AI, especially conversational AI like ChatGPT, has recently gained traction as a technological alternative for automating customer service. However, there is still a lack of research on whether current generative AI technologies can effectively replace traditional human managers in customer service automation, and whether they are advantageous in some situations and disadvantageous in others, depending on the conditions and environment. To answer the question, "Can generative AI replace human managers in customer service activities?", this study conducted experiments and surveys on customer online reviews of a food delivery platform. We applied the perspective of the elaboration likelihood model to generate hypotheses about whether there is a difference between positive and negative online reviews, and analyzed whether the hypotheses were supported. The analysis results indicate that for positive reviews, generative AI can effectively replace human managers. However, for negative reviews, complete replacement is challenging, and human managerial intervention is considered more desirable. The results of this study can provide valuable practical insights for organizations looking to automate customer service using generative AI.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.3 no.3
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• pp.178-186
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• 2022

In order to support biomimicry technology development, it is necessary to develop an omnidirectional service platform which can recommend principles of biomimicry and business ideas, providing experts' networks and carrying out their relevant education and promotion on the ground of baseline data and application research materials related to biomimicry. This study was conducted to establish any probable plans for construction and utilization of the future open-platform which will collect and serve the technology of biomimicry. Accordingly, biological and ecological information databases were examined along with the appreciation of construction and management of major biomimicry DB, and, based on the materials from the interview of related experts, a customer journey map was schematized. Lastly, in order to suggest a mid-to-long-term target-model, the roles of a future biomimicry knowledge service-platform were determined along with the potential plans for its construction and management based on case analysis and customers' needs.

• Proceedings of the Safety Management and Science Conference
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• 2000.11a
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• pp.299-306
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• 2000

General definition of data mining is the knowledge discovery or is to extract hidden necessary information from large databases. Its technique can be applied into decision making, prediction, and information analysis through analyzing of relationship and pattern among data. One of the most important work is to find association rules in data mining. The objective of this paper is to find customer's trend using association rule from analysis of database and the result can be used as fundamental data for CRM(Customer Relationship Management). This paper uses Apriori algorithm and FoodMart data in order to find association rules.

• Journal of the Ergonomics Society of Korea
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• v.29 no.4
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• pp.631-637
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• 2010

The aim of affective engineering is to develop a new product by translating customer affections into design factors. Affective data have so far been analyzed using a multivariate statistical analysis, but the affective data do not always have linear features assumed under normal distribution. Rough sets model is an effective method for knowledge discovery under uncertainty, imprecision and fuzziness. Rough sets model is to deal with any type of data regardless of their linearity characteristics. Therefore, this study utilizes rough sets model to extract affective knowledge from affective data. Four types of scent alternatives and four types of sounds were designed and the experiment was performed to look into affective differences in subject's preference on air conditioner. Finally, the purpose of this study also is to extract knowledge from affective data using rough sets model and to figure out the relationships between rough sets based affective engineering method and statistical one. The result of a case study shows that the proposed approach can effectively extract affective knowledge from affective data and is able to discover the relationships between customer affections and design factors. This study also shows similar results between rough sets model and statistical method, but it can be made more valuable by comparing fuzzy theory, neural network and multivariate statistical methods.

• Knowledge Management Research
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• v.12 no.1
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• pp.53-76
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• 2011

This study aims to examine the effects of on premium convergence products buying behavior. This paper analyzed the positive attitude formation using the basic and extended TAM and also revealed how the positive premium convergence product attitude relate to relationship purchasing intention and word of mouth intention. The samples of 562 consumer indicate that the antecedents are consist of four dimension(perceived usefulness, perceived ease of use, social value) and attitude is developed into buying intention and word of mouth intention. We have reached the following conclusion about the antecedents and outcomes factors of customer attitude for the launch of premium convergence product. First, perceived usefulness, perceived delight, and social value had a positive effect on customer attitude but perceived ease of use did not. Second, we found that customer attitude had a positive effect on purchase intention and word-of mouth intention. Finally, interaction effect of perceived usefulness/perceived delight and social value had a positive effect on customer attitude. Our findings suggested that adoptian and diffusion of premium convergence product is influenced by several behavior factors. Managerially, our result emphasize that premium convergence products must satisfy not only the perceived usefulness/delight but also social value that consumers are seeking in order to be successful in the market. The theoretical and practical implications of these findings are discussed as well.

• Knowledge Management Research
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• v.16 no.4
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• pp.17-34
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• 2015

Mobile causal games have unique features differentiating itself with video or online games and a good understanding of user experience is important to save time, effort and money by focusing on key features. The purpose of this study is to empirically investigate relationships among flow experience, customer satisfaction, and customer loyalty in the context of mobile casual games. Fun, skillfulness, ease of use, instant connectivity, challenge were suggested as important characteristics of mobile casual games and included in the research model to see what factors might influence flow experience of mobile casual game users.

• Knowledge Management Research
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• v.12 no.3
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• pp.73-96
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• 2011

Recent market saturation makes the local retailers consider an attempt to innovate the market with the retailer's brand. This is the retailers' efforts to expand the market control through the enhancement of private brands. As the competition among manufacturers extends to the competition between manufacturers and retailers, the marketing knowledges of manufacturers need to be diversified to the ones that can be applied to the manufacturers and retailers due to their bilateral competition. This research concentrates on the customer acquisition strategy (attack strategy) and customer retention strategy (defense strategy) in the place of both sides of manufacturers and retailers. Also this research targets to develop the differential marketing strategies for target market's National Brand(NB)/Private Brand(PB) purchase by analyzing individual customer's purchase probability on repurchase and switch-purchase of NB and PB. This study is based on the data of frequently consumed product, tomato ketchup on scanner panel from the ERIM data of University of Chicago, USA. This study compares and analyzes the NB and PB repurchases and switch-purchase of 4 types. The comparisons provide the informations that which factors should be managed for the attack strategy, the defense strategy, and the differential marketing strategies both for manufacturers and retailers. This research is expected to contribute on cumulating the industrial knowledges of retailers' and manufacturers' survival strategy, expecially focusing on the effect of marketing factors and consumer-characteristic factors.

• Health Policy and Management
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• v.21 no.2
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• pp.263-278
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• 2011

As the competition among hospitals become intensified, hospital management is required to carry out more effective marketing and positioning of the hospital. Successful positioning of a hospital requires the knowledge about how the concrete attributes inherent in the medical service associated with the customer values that customers seek eventually in the medical service. Thus, it is required for hospital management to understand which hospital attributes should be emphasized in order to improve the customer values. The hierarchical structure of service attributes can provide valuable information about effective positioning and advertising. To obtain such knowledge, we employed the order analysis technique as an objective means-end chain method. Order analysis is useful for identifying the causal structure among attributes. Thus, we can examine the underlying causal relationship and eventually the vertical structure of hospital selection attributes. For this study, we conducted a survey to obtain 370 responses for the analysis. The result suggests that hospital management had better increase the scale of hospital, improve the services of health care providers, and modernize the hospital facilities and equipments so as to enhance customer values and eventually to lead them to recommend the hospital to others. Our findings would provide the valuable information for hospital management to develop the more effective hospital positioning and marketing strategies.

• Knowledge Management Research
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• v.18 no.1
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• pp.159-176
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• 2017

Recently, the popularity of smartphones has led to a dramatic increase in the frequency of use of App(Application) services. LBS (Location-Based Service) App service adopts various methods such as push marketing and useful information by region through providing location-based service based on the location of the consumer. In particular, an enterprise or an App management company can provide necessary information to the consumer through the necessary information among the customer related knowledge information obtained by utilizing the location information of the consumer in real time. Nevertheless, since LBS is a service that can be performed only when the company obtains consent to provide location information voluntarily by the consumer, there is a case of privacy infringement due to consumers' use of personal information. The purpose of this study is to identify the characteristics of privacy related variables and the knowledge structure for consumer value formation based on the theory of privacy calculation. We also compared the characteristics of Korea with those of China in privacy issue. As a result of the analysis, it was confirmed that factors such as information utilization ability and information control ability were influential as a key factor of privacy calculation. In addition, perceived value influences the reputation of the LBS App service.