• Journal of Information Technology Services
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• v.13 no.3
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• pp.183-200
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• 2014

Online brand communities have become a major component of marketing strategy given that these communities encourage participation and share the culture of Web 2.0 core concepts to Internet users. This study investigated the effects of social capital and knowledge quality on the success of online brand communities. A research model suggests that trust among members and the identification derived from social capital theory and knowledge quality influence individual community participation; knowledge quality also influences brand trust. In turn, community participation and brand trust develop brand loyalty. The model was empirically analyzed using structural equation modeling with data from online brand community members in Korea. The results indicate that identification and knowledge quality significantly affects brand trust and brand loyalty through community participation. This study provides a basis for developing a success model for online brand communities. Also, this study identifies a new role of knowledge quality in an online brand community context.

• The Journal of Information Systems
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• v.12 no.1
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• pp.47-66
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• 2003

This study was examined the relationship between the exogenous and endogenous variables in our model to measure ERP system performance using path analysis. The exogenous variables are system quality, user participation, user training, top management support and self-efficacy, and the endogenous variables are system usage, user satisfaction, and work efficiency. The results of the study are shown as follows. First, all the exogenous variables in our model have a direct effect on user satisfaction, and system quality, training, and self-efficacy have a direct effect on system usage. Second, system usage has a direct effect on user satisfaction and user satisfaction has a direct effect on work efficiency. The findings show that the exogenous variables in the model are important to increase ERP implementation success.

• Journal of Information Technology Applications and Management
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• v.14 no.1
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• pp.117-135
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• 2007

Globalization changes in market structures and consumer needs, as well as technology innovations force organizations to adopt new structures and collaborative networks to cope with rapidly changing environments. These Collaborative Networks are based on the Idea of virtual enterprise. A virtual enterprise(VE) is a temporary alliance of globally distributed independent enterprises that share core competencies and computer networks. This paper presents a proposal for a methodology to measure a key factor of success and risk First of all, we chose thirty experts' defines on virtual enterprise, fifteen are academic specialist and other fifteen are from industry. For this study we define twenty two factors determining VE's success and seventeen factors determining VE's risk using by Delphi method. And we built the influence model on virtual enterprise. A research model was established according to preceeding research and consensus on experts then the revised model of key factors on virtual enterprise. This survey was based on the Analytical Hierarchy Process (AHP). AHP is an approach to decision making that involves structuring multiple choice criteria into a hierarchy, the assessing the relative important of these criteria, comparing alternative for each criteria, and determining an overall ranking of the alternatives. A model was constructed as 3 level hierarchy. The hierarches are organizational, strategic, technical criteria. for success model on VE has 22 factors and 17 factors for risk model. They are selected by all 30 experts. 14 copies among 30 copies distributed to carry out on the Analytical Hierarchy Process (AHP). Consistency ratio confirm high validity and reliability of instrument and support theoretical model. The results of this study are summarized as follows. (1) This study presented success on VE influenced strategic criteria, and essential factor is Creating a value. Risk on VE influenced strategic criteria, and essential factor is Outcome/Distribution. (2) Its enable that ranking the criteria influence on VE. These are supported VE management and using guideline of VE.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.9
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• pp.1153-1160
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• 2010

The detection algorithm for loss of balance had three main parts: one for processing data, another for constructing an internal model, and a third for detecting the loss of balance. The part related to the internal model is the most important part of the algorithm. The purpose of this study is to evaluate the effect of variables associated with the internal model on the success rate of the algorithm. The internal model depends on the type of linearization adopted and the operating period of the algorithm. The design variables were evaluated by performing sensitivity analysis of the variables of the internal model in order to obtain the success rate of the algorithm. The results showed that the most sensitive variable was the period and the period of 0.3 s yielded the highest success rate of 97.1%. Further, the ranges of the design variables that can facilitate a success rate of over 95% are presented.

• Proceedings of the Korean Society for Quality Management Conference
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• 2010.04a
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• pp.435-439
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• 2010

The purpose of this paper is to design a new management model based on the grill-formed product charscteristic area(PCA) which specify the position of products classified by the level of market and technology. This product characteristic area is composed of 9 cells and the cases sorted by market and technology are analyzed by each cell. Conclusion of this study based on many significant results gained by the various multi-variate analysis is summarized as follows; First, it can be noted that success/failure factor and progress stages are different by each cell. Second, a new management model is designed by combining the Motive Resource, Success/Failure(S/F) factors, and Progress Stages of New Product Development. Third, success products featured a balance between marketing oriented and technically oriented activities. A new attemp that combine S/F factors with development stages by each product cell will be of great usefulness for further study.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.123-128
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• 2010

To increase the chance of the success of project, it is necessary to identify the important factors influencing the performance of project. Cognitive map has been used for analysing by investigating causal links among relevant factors. A fuzzy cognitive map (FCM) is an extension of a cognitive map with the additional capability of representing feedback through weighted causal links. Project performance is influenced by several factors such as input resources, possibility of achievement, concern of others and so on. The object of this paper is to develop the project success model of enterprise using a fuzzy cognitive map approach to investigate the degree of causal relationship between project performance and these factors.

• Animal Bioscience
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• v.34 no.7
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• pp.1100-1104
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• 2021

Objective: The objective of present study was to estimate heritability of non-return rate (NRR) and success of first insemination (SFI) by using the Bayesian approach with Gibbs sampling. Methods: Heifer Traits were denoted as NRR-h and SFI-h, and cow traits as NRR-c and SFI-c. The variance covariance components were estimated using threshold model under Bayesian procedures THRGIBBS1F90. Results: The SFI was more relevant to evaluating success of insemination because a high percentage of animals that demonstrated no return did not successfully conceive in NRR. Estimated heritability of NRR and SFI in heifers were 0.032 and 0.039 and the corresponding estimates for cows were 0.020 and 0.027. The model showed low values of Geweke (p-value ranging between 0.012 and 0.018) and a low Monte Carlo chain error, indicating that the amount of a posteriori for the heritability estimate was valid for binary traits. Genetic correlation between the same traits among heifers and cows by using the two-trait threshold model were low, 0.485 and 0.591 for NRR and SFI, respectively. High genetic correlations were observed between NRR-h and SFI-h (0.922) and between NRR-c and SFI-c (0.954). Conclusion: SFI showed slightly higher heritability than NRR but the two traits are genetically correlated. Based on this result, both two could be used for early indicator for evaluate the capacity of cows to conceive.

• Journal of Korean Society for Quality Management
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• v.42 no.3
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• pp.509-522
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• 2014

Purpose: The purpose of this paper is to identify Six Sigma success factors and analyse the effects of Six Sigma success factors and innovation capability on innovation performance. Methods: The study build a research framework which include the variables of Six Sigma success factors, innovation capability, and innovation performance. A sample of 127 survey questionnaires is taken to test the proposal theoretical model through structural equations modeling using AMOS 20.0. Results: This study proves that there are the positive relationship between Six Sigma success factors, innovation capability, and innovation performance. It also confirms that there are the partial mediating effects of innovation capability between Six Sigma success factors and innovation performance. Conclusion: There are various factors affecting innovation performance of firms. This study provide the mechanism transformed from Sig Sigma to innovation performance.

• The Journal of Information Technology and Database
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• v.8 no.2
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• pp.17-40
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• 2001

The purpose of this study is to empirically identify the critical success factors of MRO e-marketplace. The research model presented in this study suggests that the success of MRO e-marketplace depends on environment of organization, type of product and service, and system of MRO e-marketplace. The major empirical findings of a survey of 38 firms in Korea are as follows: 1) The managers of firms have a deep concern on the effectiveness of MRO e-marketplace and are satisfied with the time saving provided by the transaction through MRO e-marketplace. 2) The variables affecting the success of MRO e-marketplace are classified into eight factors representing the characteristics of environment of organization, type of product and service, and system of MRO e-marketplace. 3) Among eight factors extracted from factor analysis, three factors are highly associated with the success of MRO e-marketplace. More specifically, the three factors, such as inside environment of company, capability of product supply, and basic function of MRO e-marketplace system, are the most Important factors affecting the success of MRO e-marketplace. The implications of the study are discussed and furlher research directions are proposed.

• Journal of Digital Convergence
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• v.1 no.1
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• pp.45-67
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• 2003

Developing user success metric will make it possible to evaluate the effectiveness of different electronic government systems and will help produce empirical data relating user success to task performance in electronic government environments. The purpose of this study is that combining output-oriented and interaction-oriented variables together into a single model might explain more of the variance in the dependent variable user success in a electronic government than either type of variable could have explained alone. The hypothesized reason is that user success is the result of the reciprocal effects of the properties of the information system and several facets of psychological functioning. Thus, the complex interplay between the system and the user in certain situational contorts may produce different degrees of user success with electronic governments.