• Journal of Korean Society of Transportation
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• v.11 no.2
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• pp.5-26
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• 1993

In order to analyze travel mode choice behavior, behavioral models including logit model, based on revealed preference theory, have been using easily measurable variables such as individual socioeconomic characteristics and physical attributes of travel modes. But some recent attitudinal models of travel choice behavior have implied that the negligence of individual psychological variables and individual choice constraints in travel mode choice might preclude better prediction of individual travel mode choice behavior. In this context, this study was attempted to reconstruct an attitudinal model(AM), especially focused on the decision rules in travel mode choice decision making process, consistent with the conceptual framework relating individual attitude and choice constraints to choice behavior. And to evaluate the strengths of the AM to other comparative models(logit, linear-additive, conjunctive, lexicographic model) in predicting travel mode choice bebavior, an empirical study of the mode choice in work-trip to CBD in Seoul was performed. According to the results the percent of correct prediction(PCP) derived from the AM was higher than those derived from comparative models by at least 7 to 20% in predicting travel mode choice. But each model produced a different prediction accuracy depending on market segmentation by travel modal users, individual socioeconomic characteristics, transportation system characteristics, and satisfaction levels. The finding that different groups divided by a certain criterion employ different decision rules supports the necessity of developing a choice model such as the AM combining compensatory and noncompensatory decision rules, and suggests that a proposed transportation system management plan or policy may have different effects on each group.

• Asia pacific journal of information systems
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• v.15 no.4
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• pp.89-107
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• 2005

As new information technology(IT) adoption continues to produce many investment opportunities, imperfectly informed IT managers keep trying to acquire credible external signals to update their knowledge on new technologies. Such learning processes usually help them to reach better IT adoption decisions. In some cases, however, the opposite of the goal is achieved. Most IT managers quickly converge to the same adoption decision independent of their private information. Interestingly, such information cascade is the outcome of each individual decision maker's rational choice. A technology acceptance model(TAM) is adopted that has been widely used to predict the end-user's acceptance of a new technology. A model with individual charact-eristics and information cascade variables is constructed to explain user's intention in adopting blogging. The model is empirically tested with surveyed data. The results show that individual characteristics and information cascades have significant impacts in the case of blogging.

• Journal of the Korean Society of Child Welfare
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• no.36
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• pp.261-288
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• 2011

This study focuses on adolescent prosocial behavior as one of the necessary elements for youth to grow as a healthy member of the society. The purpose of this study is to examine the effects of peer group on adolescent prosocial behavior by comparing the peer influence model and the individual characteristics model. For the study, we conducted hierarchical multiple regression analyses using the data from the Korean Youth General Survey 2008, administered by the Ministry of Health and Welfare. Results show that friends' prosocial behavior had a positive impact, but friends' antisocial behavior had a negative impact on adolescent prosocial behavior. When individual characteristics including self-esteem and empathy were analyzed simultaneously, empathy, self-esteem, friends' prosocial behavior, and friends' antisocial behavior were found to be statistically significant. The strength of association between individual characteristics and adolescent prosocial behavior was greater than that of friends' behaviors. Also, significant moderating effects of individual characteristics on the relationships between adolescent prosocial behavior and friends' behaviors were found. For example, the positive effect of friends' prosocial behavior on adolescent prosocial behavior increased as adolescent's level of self-esteem increased. On the other hand, the negative effect of friends' antisocial behavior on adolescent prosocial behavior decreased as adolescent's level of empathy increased. Based on the findings, both the peer influence model and the individual characteristics model were considered valid in explaining prosocial behavior of Korean adolescents. Finally, implications of this study for positive youth development were discussed.

• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.512-520
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• 2021

Purpose: The purpose is to analyze a relationship between urban characteristics and individual characteristics on the health level of individuals. Method: This study analyzed the relationship between urban characteristics and individual characteristics on individual health level in 2016 for local governments in Korea using a hierarchical linear model. Results: It was found that urban characteristics, along with individual characteristics, have a significant effect on the health level of individuals. Although the degree of influence is very large, some variables are not statistically significant, so more detailed research is needed for future urban policy. Conclusion: Although urban characteristics affect an individual's health level, additional research is needed on the variables of individual urban policies.

• Asia pacific journal of information systems
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• v.14 no.3
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• pp.1-22
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• 2004

Technology acceptance model(TAM) has been widely used to predict the end-user's acceptance of a new IT/IS. We used TAM as a theoretical foundation to explain user's intention to use an Internet shopping mall. The theoretical model is tested with the questionnaires from 308 users of an Internet shopping mall. Results show that several individual characteristics such as Internet skills and self-efficacy have a significant impact on user's perception of usefulness and ease of use. Results also show that both perceived enjoyment and perceived usefulness of Internet shopping mall strongly predict intention to use the Internet shopping mall. However, perceived ease of use has no direct influence on intention to use the Internet shopping mall. Personal innovativeness and Internet skills also have a positive effect on perceived enjoyment. Therefore, Internet shopping mall managers have to consider intrinsic motivational factor(enjoyment) as well as extrinsic motivational factor(usefulness). In addition, individual characteristics should be emphasized to form the positive beliefs about using the Internet shopping mall.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.5
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• pp.1407-1413
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• 2008

Individual consumer characteristics change as the individual lifestyle changes. Each individual's unique lifestyle influences substantially the individual consumer behavior. Individual consumer's behavioral pattern varies significantly depending on the individual consumer's use of credit cards. Each individual's lifestyle or individual's perception of credit cards' brands and perceptual difference in qualities of credit cards' brands influence the individual's credit card selection. Credit card companies have been doing several researches in analyzing credit card users' lifestyle characteristics and consumer behavioral characteristics. However, researches on the relation of model structure among variables such as individual lifestyle, credit cards brand, quality perception of credit cards and credit card selection are not quite noticeable. Therefore, in this research we aim at providing a theoretical foundation with credit card companies by analyzing the relation of model structure among these factors.

• The Journal of Information Systems
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• v.26 no.2
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• pp.43-62
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• 2017

Purpose This study provided empirical support for the model that explain the formation of privacy concerns in the perspective of Information Boundary Theory. This study investigated an integrated model suggesting that privacy concerns are formed by the individual's disposition to value privacy, privacy awareness, awareness of privacy policy, and government legislation. The Information Boundary Theory suggests that the boundaries of information space dependends on the individual's personal characteristics and environmental factors of e-commerce. When receiving a request for personal information from e-commerce websites, an individual assesses the risk depending on the risk-control assessment, the perception of intrusion give rise to privacy concerns. Design/methodology/approach This study empirically tested the hypotheses with the data collected in a survey that included the items measuring the constructs in the model. The survey was aimed at university students. and a causal modeling statistical technique(PLS) is used for data analysis in this research. Findings The results of the survey indicated significant relationships among environmental factors of e-commerce websites, individual's personal privacy characteristics and privacy concerns. Both individual's awareness of institutional privacy assurance on e-commerce and the privacy characteristics affect the risk-control assessment towards information disclosure, which becomes an essential components of privacy concerns.

• IE interfaces
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• v.17 no.3
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• pp.314-329
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• 2004

The rapid growth of investments in mobile service to reach a large and growing body of customers, coupled with low communication costs, has made user acceptance an increasingly critical management issue. The study draws upon the task-technology fit (TTF) model as its theoretical basis and its empirical findings to pragmatically explain the key factors that affect the performance and user acceptance of mobile service in medical field. A total of 110 usable responses were obtained. The findings indicate that the task, technology, and individual user characteristics positively affect task-technology fit and mobile service usage. The task-technology fit and mobile service usage are the dominant factors that affect mobile service performance. The result points out the importance of the fit between technologies and users' tasks in achieving individual performance impact from mobile service in medical arena.

• Proceedings of the Safety Management and Science Conference
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• 2000.11a
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• pp.251-254
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• 2000

The critical problem in dealing with multiple characteristics is how to compromise the conflict among the selected levels of the design parameters for each individual characteristic. In this study, First, Methodology using SN ratio optimized by univariate technique is proposed and a parameter design procedure to achieve the optimal compromise among several different response variables is developed. Second, to solve the issue on the optimal design for multiple quality characteristics, this study modelled the expected loss function with cross-product terms among the characteristics and derived range of the coefficients of the terms. The model will be used to determine the global optimal design parameters where there exists the conflict among the characteristics, which shows difference in optimal design parameters for the individual characteristics. Third, this paper propose a decision model to incorporates the values assigned by a group of experts on different factors in weighting decision of characteristic. Using this model, SN ratio of taguchi method for each of subjective factors as well as values of weights are used in this comprehensive method for weighting decision of characteristic.

• Journal of information and communication convergence engineering
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• v.11 no.2
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• pp.95-102
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• 2013

This paper presents a stochastic driver behavior modeling framework which takes into account both individual and general driving characteristics as one aggregate model. Patterns of individual driving styles are modeled using a Dirichlet process mixture model, as a non-parametric Bayesian approach which automatically selects the optimal number of model components to fit sparse observations of each particular driver's behavior. In addition, general or background driving patterns are also captured with a Gaussian mixture model using a reasonably large amount of development data from several drivers. By combining both probability distributions, the aggregate driver-dependent model can better emphasize driving characteristics of each particular driver, while also backing off to exploit general driving behavior in cases of unseen/unmatched parameter spaces from individual training observations. The proposed driver behavior model was employed to anticipate pedal operation behavior during car-following maneuvers involving several drivers on the road. The experimental results showed advantages of the combined model over the model adaptation approach.