• Asia Marketing Journal
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• v.22 no.3
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• pp.87-105
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• 2020

With the development of Information Technology, customers require promptly higher quality products and services. Companies try to make newly digital marketing strategies, but there are no empirical researches on them. This article empirically presents a new perspective that companies can shape the customer decision journey ahead by coordinating customer experience. In this article, based on Elaborated Likelihood Model (ELM) theory, customer experience consists of the emotional or cognitive experience. We surveyed about 200 subjects (N = 217) in their 20s and 30s based on the International Music Industry Association's Music Listening 2019 report, then analyzed four different models (before personalization-cognitive experience, before personalization-emotional experience, after personalization- cognitive experience, after personalization-emotional experience) by JASP and R Studio. We conducted Structural Equation Model (SEM) and paired t-test. Personalization factors are about recommendation systems in Spotify. The results of survey represent that companies can shape the Customer Decision Journey (CDJ) ahead especially through enhance cognitive experience. It empirically proves Elaborated Likelihood Model (ELM). The conclusion can be drawn that 'pulling' customer experience can be a new marketing strategies in the digital era.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.1 no.3
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• pp.53-60
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• 2008

Recently, the application of internet services has been realized by effort for an offer of various informations and personalization services. So in this paper, we propose the web service application model for service integration and personalization based on internet multimedia subsystems. For this services integration and personalization, we need to establish a policy of supporting personalization service. And It's required to analyze information of service users and to extract the components for the personalization services. With the process, It will provide the efficient integration between the exist services and the external services and It can be realized detail services for personal with construction of new services model.

• Journal of the Korean Society of Costume
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• v.58 no.4
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• pp.58-71
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• 2008

The demand for personalized products and service of apparel product has increased dramatically. In order to acquire a personalized apparel product, consumers may have to sacrifice more expense or time. The purpose of this study was to investigate various personalization strategies in apparel business and to identify antecedents that influence the process. Clothing involvement and two price related variables (clothing expense and willingness to pay more) were included in the study as antecedents. Four personalization strategies were included in the study: design selection, size customization, in-store service and promotion personalization. For an empirical study, a conceptual model was designed and research questionnaire was developed. A measure of personalization of apparel shopping was developed based on existing scale items of prior research and a pilot study. Data from 766 men and women in their twenties to forties were used for statistical analysis. Structural Equation Modeling was used for the data analysis. Results indicated that the conceptual model was a good fit to data. Structural paths indicated that there was significant influence of clothing involvement on design selection and sales promotion personalization strategies. Involved consumers spent more on chothing products and were likely to pay more on personalized products and services. Monthly clothing expense influenced size customization significantly. It also had negative influence on service related personalization strategies. Consumers were willing to pay more when it comes to product related personalization strategies such as design and size but not necessarily to service related strategies. This study was an attempt to provide an in-depth and synthesized approach on consumer attitudes toward personalization of apparel products.

• Asian Journal of Innovation and Policy
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• v.10 no.3
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• pp.274-293
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• 2021

Utilizing outside knowledge for innovation is an important task for companies in the competitive economy. Due to the rapid advance in the internet communication technology, the number and quality of innovation sourcing methods are increasing. We select co-creation, personalization and in-house R&D as the representative forms of innovation sourcing and suggest a game theory model that enables the comparative analysis between them. The decision and surplus outcome of the innovation mechanisms are compared under various settings of the input parameters of the model. The stakeholders voluntarily participate into all mechanisms when the product price is moderately high and the participation cost is low, while co-creation is the only feasible one when the product quality is niche. When the participation cost is relatively high, personalization outperforms co-creation.

• Journal of Information Technology Applications and Management
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• v.17 no.4
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• pp.57-82
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• 2010

Many companies today use information systems to maintain competitive advantage and to give immediate responses to customer requests. Over time, however, many of these companies failed to make the most of such information systems because the users stopped utilizing the system. While many reasons offer explanations to the phenomenon, this study analyzes how usage intention of information system can be enhanced by changing the environment and usefulness of the system from the user's perspective. Active and wide-ranging researches using the Technology Acceptance Model (TAM) have been carried out on an individual's tendency to using new technology. But, many of the studies remain focused on improving user intention by enhancing the ease of use and usefulness of the system under PC applications or Enterprise applications. The personalized intranet system is not only bringing about sweeping changes to a company's information systems environment but also providing users with freedom to design their own working environment, personalization, to Corporate Information Systems (CIS). Results from empirical tests on intranet systems verify that through personalization, a more voluntary information system environment can be created and that by increasing the ease of use and usefulness of the system, users can become more favorable to accepting new technologies and ultimately result in improved usage intention. This study suggests personalization variables and model for implementing a voluntary CIS for information system developers.

• Journal of the Korea Safety Management & Science
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• v.5 no.3
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• pp.107-119
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• 2003

Expectation and interest about e-CRM are rising for more efficient customer management in on-line including electronic commerce. The decision-making tree can be used usefully as the data mining technology for e-CRM. In this paper, the representative decision making techniques, CART, C4.5, CHAID analyzed the differences in personalization point of view with actuality customer data through an experiment. With these analysis data, it is proposed a new decision-making tree system that has big advantage in personalization techniques. Through new system, it can get following advantage. First, it can form superior model more qualitatively in personalization by adding individual's weight value. Second it can supply information personalized more to customer. Third, it can have high position about customer's loyalty than other site of similar types of business. Fourth, it can reduce expense that cost marketing and decision-making. Fifth, it becomes possible that know that customer through smooth communication with customer who use personalized service wants and make from goods or service's quality to more worth thing.

• 한국IT서비스학회:학술대회논문집
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• 2008.05a
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• pp.364-367
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• 2008

Cyber office is a personalized enterprise portal model for knowledge workers. The key services of cyber office are both personalization and emergent collaboration. Personalization service is provided by choosing service from service repository and then dropping it in the cyber office. Service repository contains various kinds of services supporting business activities. Cyber office provides blog service and profile service for knowledge workers to participate in knowledge based collaboration voluntarily.

• Fashion & Textile Research Journal
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• v.18 no.1
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• pp.38-47
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• 2016

This research analyzes the influence of mobile commerce characteristics on consumer's purchase intention using a theoretical Technology Acceptance Model (TAM) constructed on previous studies and a review of the literature to explain the effect of mobile fashion shopping characteristics on consumer's purchase intention. In constructing structural equation model, Mobile commerce characteristics variables such as 'security', 'enjoyment', and 'personalization' were selected as external variables affecting TAM. A questionnaire was distributed to consumers in their 20's-30's who had purchased fashion products using a mobile shopping channel. Statistical methods of confirmatory factor analysis, correlation, and covariance structural analysis using Amos 19.0 package were employed for the analysis of 453 effective data responses. The results were as follows. First, extended TAM was shown be the appropriate model to explain the influence of mobile commerce characteristics on consumer's purchase intention in mobile fashion shopping. Second, 'security' had a significant positive influence on perceived usefulness (PU), however it affected perceived ease of use (PEOU) negatively. Third, 'enjoyment' had a significant influence only on PEOU, while 'personalization' was found to affect both PEOU and PU significantly. Fourth, PEOU affected PU significantly. Finally, both PEOU and PU had a significant influence on consumer's purchase intention.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.2
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• pp.31-45
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• 2023

This study deals with exploring qualitative steps and paths that appear as YouTube users' usage time increases quantitatively. For the study, I applied theories from psychology and neuroscience, subdivided the interval between the personalization algorithm of the recommendation system, and active use and analyzed the relationship between variables in this process. According to the theory behavioral model theory (FBM), variable reward, and dopamine addiction were applied. Personalization algorithms easy clicks as triggers according to associated content presentation functions in behavioral model theory (FBM). Variable rewards increase motivational effectiveness with unpredictability of the content you search, and dopamine nation is summarized as stimulating the dopaminergic nerve to continuously and actively consume content. This study is expected to make an academic and practical contribution in that it divides the purpose of use of content in the personalization algorithm and active use section into four stages from a psychological perspective: first use, reuse, continuous use, and active use, and analyzes the path.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.3
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• pp.19-29
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• 2010

A marketing model is changed from a customer acquisition to customer retention and it is being moved to a way that enhances the quality of customer interaction to add value to our customers. Such personalization is emerging from this background. The Web site is accelerate the adoption of a personalization, and in contrast to the rapid growth of data, quantitative analytical experience is required. For the automated analysis of large amounts of data and the results must be passed in real time of personalization has been interested in technical problems. A recommendation algorithm is an algorithm for the implementation of personalization, which predict whether the customer preferences and purchasing using the database with new customers interested or likely to purchase. As recommended number of users increases, the algorithm increases recommendation time is the problem. In this paper, to solve this problem, a recommendation system based on clustering and dimensionality reduction is proposed. First, clusters customers with such an orientation, then shrink the dimensions of the relationship between customers to low dimensional space. Because finding neighbors for recommendations is performed at low dimensional space, the computation time is greatly reduced.