• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.2
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• pp.107-117
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• 2013

The main objective of this study lies at examining economic features of IT security investment and comparing alternative mechanisms to achieve optimal provision of IT security resources within a firm. There exists a paucity of economic analysis that provide useful guidelines for making critical decisions regarding the optimal level of provision of IT security and how to share the costs among different users within a firm. As a preliminary study, this study first argues that IT security resources share some unique characteristics of pure public goods, namely nonrivalry of consumption and nonexcludability of benefit. IT security provision problem also suffers from information asymmetry problem with regard to the valuation of an individual user for IT security goods. Then, through an analytical framework, it is shown that the efficient provision condition at the overall firm level is not necessarily satisfied by individual utility maximizing behavior. That is, an individual provision results in a suboptimal solution, especially an underprovision of the IT security good. This problem is mainly due to the nonexcludability property of pure public goods, and is also known as a free-riding problem. The fundamental problem of collective decision-making is to design mechanisms that both induce the revelation of the true information and choose an 'optimal' level of the IT security good within this framework of information asymmetry. This study examines and compares three alternative demand-revealing mechanisms within the IT security resource provision context, namely the Clarke-Groves mechanism, the expected utility maximizing mechanism and the Groves-Ledyard mechanism. The main features of each mechanism are discussed along with its strengths, weaknesses, and different applicability in practice. Finally, the limitations of the study and future research are discussed.

• Journal of Agricultural Extension & Community Development
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• v.21 no.3
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• pp.271-305
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• 2014

There is an inescapable requirement in public policy to provide evidence. For the evaluation of the EU Rural Development Policy, the European Commission has designed a Common Monitoring and Evaluation Framework(CMEF). The principal objectives of evaluations are to improve decision-making, resource allocation and accountability. In Korea, howerver, the opinion-based policy by expert is still rural development evaluation system. It does not provide the objective quantitative indicators for impact of rural development project. According to this, the budget-making body (parliament, government, etc.) have questioned the effectiveness of rural development projects, rural development projects often reduced or changed. To improve the accountability of rural development policy, it is necessary to build a reliable monitoring and evaluation system based on the evidence. First, rural development evaluation indicators should be considered the multipul goal of rural development, namely economic development, social development. Second, the purpose of the evaluation is necessary to be designed for the learning rather than reward. Third, the participation by local residents should be strengthened in evaluation process. Finally, it is necessary to establish rural development monitoring and evaluation system, such as CMEF of the EU (CMEF).

• Journal of Korean Academy of Nursing Administration
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• v.4 no.1
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• pp.193-214
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• 1998

The purpose of the present study was to examine the causal model of nurses' organizational commitment. Based on literature review and Fishbein's behavioral intentions model ((Fishbein. 1967: Fishbein & Ajzen. 1975). the organizational commitment was conceptualized within a motivational framework that mediate between antecedents variables and outcome variables. Antecedent variables were pay, promotional chances. continuing education opportunity. rigidity of the administration. paticipative decision making, latitude, group support, role conflict, work load, need for achievement. experience and pride for professional nursing. Outcome variable was turnover intention. The subjects were 373 nurses who were working at 2 large general hospitals located in Seoul. It represents a response rate of 94%. Data for this study was collected from August 29 to September 22 in 1997 by Questionnaire. Path analysis with LISREL 7.16 prigram was used to test the fit of the proposed conceptual model to data and to examine the causal relationships among variables. The result showed that both the proposed model and the modified model fit the data excellently. It needs to be notified, however. that path analysis can not count measurment errors: measurement error can attenuate estimates of coefficient and explanatory power. Nontheless the model revealed considerable explanatory power for organizational commitment (58%), pride for professional nursing (50%) and turnover intention(40%). In predicting nurses' organizational commitment, the findings of this study clearly demonstrated 'the pride for professional nursing' might be the most important variables of all the antecedent variables. Group support, role conflict, need for achievement were also found to be important determinants for the organizational commitment and turnover intention, The result showed experience might be a predictor for 'pride for professional nursing' and 'turnover intention' but not 'organizational commitment', 'Rigidity of the administration' and latitude were also found to have important roles in predictingr the organizational commitment, while participative decision making might have an impact on turnover intention. On the other hand promotional chance had an influence on all the outcome variables, while pay only on turnover intention. In predicting turnover intention, the result clearly revealed 'the pride for professional nursing' and 'organizational commitment' might be the most powerful predictors among all the variables. Theses results were discussed, including directions for the future research and practical implications drawn from the research were suggested.

• Journal of Korean Academy of Nursing Administration
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• v.4 no.1
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• pp.183-214
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• 1998

The purpose of the present study was to examine the causal model of nurses' organizational commitment. Based on literature review and Fishbein's behavioral intentions model ((Fishbein, 1967;Fishbein & Ajzen. 1975), the organizational commitment was conceptualized within a motivational framework that mediate between antecedents variables and outcome variables. Antecedent variables were pay, promotional chances, continuing education opportunity, rigidity of the administration, paticipative decision making, latitude, group support, role conflict, work load, need for achievement, experience and pride for professional nursing. Outcome variable was turnover intention. The subjects were 373 nurses who were working at 2 large general hospitals located in Seoul. It represents a response rate of 94%. Data for this study was collected from August 29 to September 22 in 1997 by Questionnaire. Path analysis with LISREL 7.16 prigram was used to test the fit of the proposed conceptual model to data and to examine the causal relationships among variables. The result showed that both the proposed model and the modified model fit the data excellently. It needs to be notified, however, that path analysis can not count measurement errors; measurement error can attenuate estimates of coefficient and explanatory power. Nontheless the model revealed considerable explanatory power for organizational commitment (58%). pride for professional nursing (50%) and turnover intention(40%). In predicting nurses' organizational commitment. the findings of this study clearly demonstrated 'the pride for professional nursing' might be the most important variables of all the antecedent variables. Group support. role conflict, need for achievement were also found to be important determinants for the organizational commitment and turnover intention. The result showed experience might be a predictor for 'pride for professional nursing' and 'turnover intention' but not 'organizational commitment'. 'Rigidity of the administration' and latitude were also found to have important roles in predictor for the organizational commitment, while participative decision making might have an impact on turnover intention. On the other hand promotional chance had an influence on all the outcome variables, while pay only on turnover intention. In predicting turnover intention, the result clearly revealed 'the pride for professional nursing' and 'organizational commitment' might be the most powerful predictors among all the variables. Theses results were discussed, including directions for the future research and practical implications drawn from the research were suggested.

• Journal of Global Scholars of Marketing Science
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• v.15 no.3
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• pp.211-231
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• 2005

It is important for marketers to understand both individual resistance and group resistance in order to successfully bring innovations into global markets. We suggest that consumers resist innovations as individuals and as members of a group and that they do this in different ways at different stages of decision-making. The individual resistance begins with forms of initial resistance, develops into emergent resistance and mature or belated resistance at the individual level. In addition, personal moral standards can influence decision making in relation to the adoption of innovations. Individual resistance is sometimes accompanied by or evolves into group resistance. We introduce a framework for thinking about consumer resistance to innovations that sees it as a consequence of social identity, which has functions for the individual, the group to which one belongs, and other individuals and groups. Consumers with membership in a certain group try to increase their self-esteem through the process of social comparison. The more consumers strongly identify with and bond with a certain group, the more in-group solidarity and out-group hostility will occur. Out-group hostility gives group members strong resistance toward products and services related to the out-group. Individual resistance and group resistance are threats to marketers and dampen performance. By considering the existence of resistance to innovations and seeking strategies to overcome it, marketers can transform these threat into new opportunities. A better understanding of consumer resistance can complement research on the adoption of innovations and help in the development of a universal model of consumer behavior.

• Journal of Gifted/Talented Education
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• v.22 no.3
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• pp.639-662
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• 2012

The purpose of this study is to develop the evaluation model of gifted curriculum in visual art. For this purpose, first, it discusses about what kinds of issues raised about gifted education in visual art. Second, it critically reviews the evaluation models of gifted curriculum, and investigates the suitable model for developing curriculum evaluation model of gifted in visual art. Third, it suggests the appropriate perspective and evaluation model of gifted curriculum in visual art. Along with the change in the concept of creativity, recent studies on gifted education in visual art concentrate that gifted learners who have the potential find their own way of creating art. Also they emphasize the contextual implementation which recognizes the significance of interaction among field, domain and individual. Based of these inquiry, existing evaluation models of gifted curriculum have limitations in suitability as a evaluation model of gifted curriculum in visual art. This study suggests that the curriculum evaluation of visual art gifted programs should be approached from the decision-making perspective. Also it develops the conceptual framework and the evaluation model of gifted curriculum in visual art based on the CIPP model, which is the representative model of decision-making approach. It concludes with its implications and the discussion about the role of evaluators.

• The Journal of the Convergence on Culture Technology
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• v.5 no.4
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• pp.329-337
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• 2019

It is true that many tales delivered in an 'Story-telling' auditorium or theater have not so much exquisite and refined forms as distorted and deteriorated ones. Furthermore, when false interpretations of tale-performers added into the category of the texts of tales, the problems can be made worse. In case of oral folk tales, there can be discordance between the standpoint of a tale-performer and the contents of a tale. This thesis is directly aimed at pointing out the 'Behavior Economics' problems concerned with the reading and interpretation of tales through investigating the missing parts of a text in reading tales. Man's rationality is meant to be confined to bounded rationality. Instead of making best choices, bounded rationality leads consumers to make a decision which they think suffices themselves to the point requiring no more consideration on the given item. It is the very Heuristic that does work in the process of this simplified decision making process. Heuristic utilizes established empirical notion and specific information, and that's why there can be cognitive 'Biases' sometimes leading to inaccurate judgment. As Oral Literature is basically based on heavy guesswork and perceptual biases of general public, it is imperative to contemplate oral literature in the framework of Heuristic of behavior economics. This thesis deals with thinking types and behavioral patterns of the general public in the perspective of heuristic by examining 'Story-tellings' on the basis of personal or public memory. In addition, heuristic involves how to deal with significant but intangible content such as the errors of oral story teller, the deviations of the story, and responses of the audience.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.117-137
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• 2009

Recently, intelligent traffic information systems have enabled people to forecast traffic conditions before hitting the road. These convenient systems operate on the basis of data reflecting current road and traffic conditions as well as distance-based data between locations. Thanks to the rapid development of ubiquitous computing, tremendous context data have become readily available making vehicle route planning easier than ever. Previous research in relation to optimization of vehicle route planning merely focused on finding the optimal distance between locations. Contexts reflecting the road and traffic conditions were then not seriously treated as a way to resolve the optimal routing problems based on distance-based route planning, because this kind of information does not have much significant impact on traffic routing until a a complex traffic situation arises. Further, it was also not easy to take into full account the traffic contexts for resolving optimal routing problems because predicting the dynamic traffic situations was regarded a daunting task. However, with rapid increase in traffic complexity the importance of developing contexts reflecting data related to moving costs has emerged. Hence, this research proposes a framework designed to resolve an optimal route planning problem by taking full account of additional moving cost such as road traffic cost and weather cost, among others. Recent technological development particularly in the ubiquitous computing environment has facilitated the collection of such data. This framework is based on the contexts of time, traffic, and environment, which addresses the following issues. First, we clarify and classify the diverse contexts that affect a vehicle's velocity and estimates the optimization of moving cost based on dynamic programming that accounts for the context cost according to the variance of contexts. Second, the velocity reduction rate is applied to find the optimal route (shortest path) using the context data on the current traffic condition. The velocity reduction rate infers to the degree of possible velocity including moving vehicles' considerable road and traffic contexts, indicating the statistical or experimental data. Knowledge generated in this papercan be referenced by several organizations which deal with road and traffic data. Third, in experimentation, we evaluate the effectiveness of the proposed context-based optimal route (shortest path) between locations by comparing it to the previously used distance-based shortest path. A vehicles' optimal route might change due to its diverse velocity caused by unexpected but potential dynamic situations depending on the road condition. This study includes such context variables as 'road congestion', 'work', 'accident', and 'weather' which can alter the traffic condition. The contexts can affect moving vehicle's velocity on the road. Since these context variables except for 'weather' are related to road conditions, relevant data were provided by the Korea Expressway Corporation. The 'weather'-related data were attained from the Korea Meteorological Administration. The aware contexts are classified contexts causing reduction of vehicles' velocity which determines the velocity reduction rate. To find the optimal route (shortest path), we introduced the velocity reduction rate in the context for calculating a vehicle's velocity reflecting composite contexts when one event synchronizes with another. We then proposed a context-based optimal route (shortest path) algorithm based on the dynamic programming. The algorithm is composed of three steps. In the first initialization step, departure and destination locations are given, and the path step is initialized as 0. In the second step, moving costs including composite contexts into account between locations on path are estimated using the velocity reduction rate by context as increasing path steps. In the third step, the optimal route (shortest path) is retrieved through back-tracking. In the provided research model, we designed a framework to account for context awareness, moving cost estimation (taking both composite and single contexts into account), and optimal route (shortest path) algorithm (based on dynamic programming). Through illustrative experimentation using the Wilcoxon signed rank test, we proved that context-based route planning is much more effective than distance-based route planning., In addition, we found that the optimal solution (shortest paths) through the distance-based route planning might not be optimized in real situation because road condition is very dynamic and unpredictable while affecting most vehicles' moving costs. For further study, while more information is needed for a more accurate estimation of moving vehicles' costs, this study still stands viable in the applications to reduce moving costs by effective route planning. For instance, it could be applied to deliverers' decision making to enhance their decision satisfaction when they meet unpredictable dynamic situations in moving vehicles on the road. Overall, we conclude that taking into account the contexts as a part of costs is a meaningful and sensible approach to in resolving the optimal route problem.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.43-57
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• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.744-747
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• 2008

Quantity information focused on a design drawing plays a critical role in a decision making related to cost for project participants during project life cycles. Related participants absolutely depend on quantity take-off working which produces the quantity information by hand, and then a worker's mistake often causes many errors. The difference of quantity by the know-how of the person in charge of the estimation also occurs. In addition, the worker passes through the whole quantity take-off processes again in case of re-working for quantity take-off produced by a change order. The requirements about the automated estimation increase because of the needs for the accurate quantity take-off and dealing with the change order and recently, the studies about the automated estimation working process based on 34 cad model from 3d cad modeler are attempted in various viewpoints. However, the existing studies reach the limits such as common quantity data type framework for getting Quantity information. Focused on a certain 34 cad modeler and BIM based automation of estimation using it Therefore, the objective of this study is to develop the a series of system which can extract, analyze, and verify Quantity Data Type in modeler to automate quantity take-off originated from various 3d cad modelers as a foundation study for BIM based automation of estimation framework.