• The Journal of Society for e-Business Studies
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• v.12 no.4
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• pp.165-184
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• 2007

Recently, blogging has been regarded as a promising media for information sharing and relationship building. However, it is not quite sure if the technology acceptance model could be completely adopted also in relationship-based system such as blog. Hence, the purpose of this paper is to identify the factors affecting the usage of blogs. To do so, content analysis methodology is applied to extract meaningful factors affecting the usage of blogs in the opinions of the bloggers in a Korean portal site : Naver. We investigates the causal relationship among three factors ; perceived usefulness, perceived encouragement, and actual use in blogging. Moreover, public self-consciousness, self disclosure and telepresence are also considered as the determinants. The results show that public self-consciousness and self disclosure are significant elements affecting perceived usefulness and perceived encouragement, while perceived usefulness and perceived encouragement both affecting the actual use of blogs.

• The Journal of Society for e-Business Studies
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• v.17 no.4
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• pp.117-140
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• 2012

This study focuses on the use of competitive analysis to identify the effective benchmarking target through consulting techniques to derive improvements. After developed using DEA(Date Envelopment Analysis) the relative efficiency analysis tool for competitor analysis to apply in consulting on-site or within the organization, this study compared the new techniques and the existing techniques. This study was carried out as follows. First, through a review of the literature, consulting competitive analysis techniques and methodologies relative efficiency analysis technique DEA for research scholars examined. Second, DEA-based competitive analysis, multidimensional efficiency analysis is presented. Third, The case study was conducted to determine the suitability and practicality of this analysis method for public company "A".

• The Journal of Society for e-Business Studies
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• v.13 no.4
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• pp.49-69
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• 2008

Recently, ubiquitous computing technology becomes available to develop advanced electronic commerce：u-commerce. Hence, it is the very time to perform feasibility analysis in applying ubiquitous computing technology, especially estimating economical value of the on-going technology. Hence, the purpose of this paper is to propose a financial value estimating methodology in performing feasibility test on ubiquitous computing technology. To do so, Black and Scholes model is basically adopted. To show the feasibility if the idea proposed in this paper, actual case study through focused group interview with those who are actually performing on-going ubiquitous computing projects. As the result, we validated the possibility of applying Black-Sholes model to assessing feasibility analysis for ubiquitous technology development with the price of call option, volatility, and the comparison with other similar technologies.

• The Journal of Society for e-Business Studies
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• v.18 no.4
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• pp.67-82
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• 2013

Railway is paid attention as a means of environment-friendly transportation and logistics. Efforts to enhance the competitiveness by IT convergence, for railway vehicle market share of the world, has been promoted. This study proposes a technology development plan of railway IT convergence. We analyzed the results of legacy researches and technology patents related with railway IT convergence and derived the target tasks in accordance with our technologies classification. By adopting the multi-attributes utility theory methodology and using survey of experts, we selected the core research issues. The result of this study could help policy making and R&D planning about railway IT convergence.

• Korea Journal of Hospital Management
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• v.23 no.3
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• pp.87-103
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• 2018

Purpose: This study investigates the best appointment pattern which can enhance customer's satisfaction and hospital's efficient management reflecting plastic surgery clinic's service characteristics. Methodology: The data of this study is obtained from Plastic surgery Clinic which is located in the civic center. By collecting and analyzing the data, we build the simulation model using ARENA. Based on 5 appointment patterns that was suggested in formal appointment scheduling studies, we experiment 3 simulation models; 'Basic Appointment Pattern' that has no restriction, 'Restriction on Second Customer' that restricts the number of second customer's in each slot, 'Restriction on Process Time' that restricts the number of second customer who has long process time in each slot. We can check robustness of the appointment patterns by experimenting on off-peak day and peak day, during peak season. Findings: This study confirms that these 2 restrictions can give a better result than 'Basic Appointment Pattern' that just simply distributes customers by number. Especially, the performance of Triangle-like pattern which is the best appointment pattern in the formal study has been improved by adding restrictions. Based on 'DET', 'Restriction on Second Customer' shows a better result. Meanwhile, based on 'E(WT)', 'Restriction on Process Time' shows a better result. Overall, based on 'DET+E(WT)', 'Restriction on Second Customer' shows a better result. Practical Implications: The purpose of each hospital may alter as demand for plastic surgery grows increasingly. Thus, each hospital should be always prepared to introduce appointment pattern for changed purpose. In order to respond flexibly to these changes, it is necessary for medical personnel to improve the awareness or for hospital to create an environment by constructing appointment program so that medical personnel does not need to put more labor on work.

• The Journal of Society for e-Business Studies
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• v.16 no.2
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• pp.129-142
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• 2011

Traditionally research in Service Oriented Architecture(SOA) security has focused primarily on exploiting standards and solutions separately. There exists no unified methodology for SOA security to manage risks at the enterprise level. It needs to analyze preliminarily security threats and to manage enterprise risks by identifying vulnerabilities of SOA. In this paper, we propose a metric-based vulnerability assessment method using dynamic properties of services in SOA. The method is to assess vulnerability at the architecture level as well as the service level by measuring run-time dependency between services. The run-time dependency between services is an important characteristic to understand which services are affected by a vulnerable service. All services which directly or indirectly depend on the vulnerable service are exposed to the risk. Thus run-time dependency is a good indicator of vulnerability of SOA.

• Journal of Distribution Science
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• v.18 no.8
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• pp.113-125
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• 2020

Purpose: The purpose of this paper is to investigate the effect of interaction between product category (fresh vs. indulgent product) and shopping options (shipping charge and delivery time) on customer satisfaction and purchase intent in an e-commerce context. When ordering groceries online, consumers begin to allocate a larger share of their grocery budget toward product categories that generally contain healthier items at the expense of product categories that generally contain more indulgent products. Moreover, customers are extremely sensitive to shipping options such as shipping charges and delivery time. Therefore, this research investigates the issue at a more segmented level to focus on the impact that one dimension of logistics service quality - product category, shipping charge, and delivery time have on customer satisfaction and purchase intent. Research design, data, and methodology: To test the theoretically derived priori hypotheses concerning product category, shipping charges, delivery time, satisfaction, and purchase intent, this research presented a scenario-based experiment. Eight treatment groups were assigned by the method of product category (fresh produce vs. indulgent product), shipping charge (free vs. paid), and delivery time (one-day vs. two to three days). A total of 240 subjects were divided into groups and exposed to one of the eight scenarios. Participant's purchase intention was the dependent variable, and ANOVA and L-matrix were used to analyze for main and interactive effects between factors. Conclusions: Results indicated that in tests 1 and 2, free shipping and fast delivery time increased consumer satisfaction as well as purchase intent, and fast delivery moderated the impact of free shipping on consumer satisfaction and purchase intent. Test 3 showed that the effect of free shipping on consumer satisfaction and purchase intent moderated by fast delivery for indulgent products. In contrast, fast delivery for fresh products moderated the effect of paid shipping on consumer satisfaction and purchase intent. Consistent with this proposed mechanism, the relative importance of fresh produce versus indulgent products highlights the effect of shipping options on consumer satisfaction and purchase intent when ordering the target product in an e-commerce context. We conclude with a discussion of the theoretical and practical implications of our findings.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.21-32
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• 2021

Due to the recent development in electronic financial services, transactions of electronic prepayment are rapidly increasing. The increased transactions of electronic prepayment, however, also leads to the increased fraud attempts. It is mainly because electronic prepayment can easily be converted into cash. The objective of this paper is to develop a methodology that can effectively detect fraud transactions in electronic prepayment, by using sequential pattern mining techniques. To validate our approach, experiments on real transaction data were conducted and the applicability of the proposed method was demonstrated. As a result, the accuracy of the proposed method has been 95.6 percent, showing that the proposed method can effectively detect fraud transactions. The proposed method could be used to reduce the damage caused by the fraud attempts of electronic prepayment.

• The Journal of Industrial Distribution & Business
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• v.12 no.11
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• pp.17-31
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• 2021

Purpose: Despite the fact that face (i.e. Chemyon) is deeply-rooted in Korean culture and significantly affects the behavior of Korean people, the effect of face on leisure consumers' consumption behavior has only reported mixed findings, that is, significant and/or insignificant face effects have been reported. It is necessary to integrate prior research findings, and comprehensively examine the effect of face on leisure consumers' consumption behavior. The purpose of this study was to investigate the effect (i.e. effect size, and moderating variables) of face on leisure consumers' consumption behavior through meta-analysis. Research design, data and methodology: Among 1,019 face-related academic studies, retrieved from the academic research information services (RISS), 34 studies and 300 cases examining the effect of face on leisure consumers' consumption behavior were finally included for meta-analysis. Face measured as face sensitivity and/or a face sensitivity sub-component (shame-consciousness, formality-consciousness, and other-consciousness) were integrated in the meta-analysis. Leisure consumers' consumption behavior was classified as antecedents of purchase (overall conspicuous consumption tendency, overall symbolic consumption tendency, personality, high price, high quality, brand seeking, fashion seeking, enjoyment, other person (interpersonal) consideration, position, reference group, and attitude), purchase (purchase intention, unplanned purchase, purchase, and expenditure), and post-purchase (satisfaction, repurchase, and post-purchase). The data used in the meta-analysis was comprised of correlation coefficients, and the meta-analysis was performed using the R-program. Results: The overall mean effect size of face on leisure consumers' consumption behavior was .248. It was found that the effect size was the largest in the order of shame-consciousness face, formality-consciousness face, and other-consciousness face. Among the types of leisure consumers' consumption behavior categorized as dependent variables, the effect size was found to be largest in the order of position, attitude, reference group, post-purchase behavior, brand seeking, personality, trend seeking, etc. In addition, it was found that the leisure types moderated the effect size of face on leisure consumers' consumption behavior. The effect size was found to be largest in the order of skin diving, baseball, various leisure participation, dance, gambling, golf, etc. Conclusions: Face moderately or significantly influence leisure consumers' consumption behavior.

• The Journal of Society for e-Business Studies
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• v.26 no.1
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• pp.29-41
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• 2021

Recently, there are increasing attempts to utilize deep learning methodology in the fashion industry. Accordingly, research dealing with various fashion-related problems have been proposed, and superior performances have been achieved. However, the studies for fashion style classification have not reflected the characteristics of the fashion style that one outfit can include multiple styles simultaneously. Therefore, we aim to solve the multi-label classification problem by utilizing the dependencies between the styles. A multi-label recognition model based on a graph convolution network is applied to detect and explore fashion styles' dependencies. Furthermore, we accelerate model training and improve the model's performance through transfer learning. The proposed model was verified by a dataset collected from social network services and outperformed baselines.