• Asia pacific journal of information systems
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• v.17 no.4
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• pp.207-228
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• 2007

Measuring Information Technology(IT) organizations' activities have been limited to mainly measure financial indicators for a long time. However, according to the multifarious functions of Information System, a number of researches have been done for the new trends on measurement methodologies that come with financial measurement as well as new measurement methods. Especially, the researches on IT Balanced Scorecard(BSC), concept from BSC measuring IT activities have been done as well in recent years. BSC provides more advantages than only integration of non-financial measures in a performance measurement system. The core of BSC rests on the cause-and-effect relationships between measures to allow prediction of value chain performance measures to allow prediction of value chain performance measures, communication, and realization of the corporate strategy and incentive controlled actions. More recently, BSC proponents have focused on the need to tie measures together into a causal chain of performance, and to test the validity of these hypothesized effects to guide the development of strategy. Kaplan and Norton[2001] argue that one of the primary benefits of the balanced scorecard is its use in gauging the success of strategy. Norreklit[2000] insist that the cause-and-effect chain is central to the balanced scorecard. The cause-and-effect chain is also central to the IT BSC. However, prior researches on relationship between information system and enterprise strategies as well as connection between various IT performance measurement indicators are not so much studied. Ittner et al.[2003] report that 77% of all surveyed companies with an implemented BSC place no or only little interest on soundly modeled cause-and-effect relationships despite of the importance of cause-and-effect chains as an integral part of BSC. This shortcoming can be explained with one theoretical and one practical reason[Blumenberg and Hinz, 2006]. From a theoretical point of view, causalities within the BSC method and their application are only vaguely described by Kaplan and Norton. From a practical consideration, modeling corporate causalities is a complex task due to tedious data acquisition and following reliability maintenance. However, cause-and effect relationships are an essential part of BSCs because they differentiate performance measurement systems like BSCs from simple key performance indicator(KPI) lists. KPI lists present an ad-hoc collection of measures to managers but do not allow for a comprehensive view on corporate performance. Instead, performance measurement system like BSCs tries to model the relationships of the underlying value chain in cause-and-effect relationships. Therefore, to overcome the deficiencies of causal modeling in IT BSC, sound and robust causal modeling approaches are required in theory as well as in practice for offering a solution. The propose of this study is to suggest critical success factors(CSFs) and KPIs for measuring performance for IT organizations and empirically validate the casual relationships between those CSFs. For this purpose, we define four perspectives of BSC for IT organizations according to Van Grembergen's study[2000] as follows. The Future Orientation perspective represents the human and technology resources needed by IT to deliver its services. The Operational Excellence perspective represents the IT processes employed to develop and deliver the applications. The User Orientation perspective represents the user evaluation of IT. The Business Contribution perspective captures the business value of the IT investments. Each of these perspectives has to be translated into corresponding metrics and measures that assess the current situations. This study suggests 12 CSFs for IT BSC based on the previous IT BSC's studies and COBIT 4.1. These CSFs consist of 51 KPIs. We defines the cause-and-effect relationships among BSC CSFs for IT Organizations as follows. The Future Orientation perspective will have positive effects on the Operational Excellence perspective. Then the Operational Excellence perspective will have positive effects on the User Orientation perspective. Finally, the User Orientation perspective will have positive effects on the Business Contribution perspective. This research tests the validity of these hypothesized casual effects and the sub-hypothesized causal relationships. For the purpose, we used the Partial Least Squares approach to Structural Equation Modeling(or PLS Path Modeling) for analyzing multiple IT BSC CSFs. The PLS path modeling has special abilities that make it more appropriate than other techniques, such as multiple regression and LISREL, when analyzing small sample sizes. Recently the use of PLS path modeling has been gaining interests and use among IS researchers in recent years because of its ability to model latent constructs under conditions of nonormality and with small to medium sample sizes(Chin et al., 2003). The empirical results of our study using PLS path modeling show that the casual effects in IT BSC significantly exist partially in our hypotheses.

• International Journal of Contents
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• v.10 no.3
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• pp.41-46
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• 2014

A cause-effect graph considers only the desired external behavior of a system by identifying input-output parameter relationships in the specification. When testing a software system with cause-effect graphs, it is important to derive a moderate number of tests while avoiding loss in fault detection ability. Pairwise testing is known to be effective in determining errors while considering only a small portion of the input space. In this paper, we present a new testing technique that generates pairwise tests from a cause-effect graph. We use a Boolean Satisbiability (SAT) solver to generate pairwise tests from a cause-effect graph. The Alloy language is used for encoding the cause-effect graphs and its SAT solver is applied to generate the pairwise tests. Using a SAT solver allows us to effectively manage constraints over the input parameters and facilitates the generation of pairwise tests, even in the situations where other techniques fail to satisfy full pairwise coverage.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.2
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• pp.159-167
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• 2003

This study suggests the hybrid fault diagnosis method of signed digraph (SDG) and partial least squares (PLS). SDG offers a simple and graphical representation for the causal relationships between process variables. The proposed method is based on SDG to utilize the advantage that the model building needs less information than other methods and can be performed automatically. PLS model is built on local cause-effect relationships of each variable in SDG. In addition to the current values of cause variables, the past values of cause and effect variables are inputted to PLS model to represent the Process armies. The measured value and predicted one by dynamic PLS are compared to diagnose the fault. The diagnosis example of CSTR shows the proposed method improves diagnosis resolution and facilitates diagnosis of masked multiple-fault.

• Safety and Health at Work
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• v.12 no.4
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• pp.505-510
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• 2021

Background: Factors related to root causes can cause commonly occurring accidents such as falls, slips, and jammed injuries. An important means of reducing the frequency of occupational accidents in small- to medium-sized enterprises (SMSEs) of South Korea is to perform intensity analysis of the root cause factors for accident prevention in the cause and effect model like decision models, epidemiological models, system models, human factors models, LCU (life change unit) models, and the domino theory. Especially intensity analysis in a robot system and smart technology as Industry 4.0 is very important in order to minimize the occupational accidents and fatal accident because of the complexity of accident factors. Methods: We have developed the modern cause and effect model that includes factors of root cause through statistical testing to minimize commonly occurring accidents and fatal accidents in SMSEs of South Korea and systematically proposed educational policies for accident prevention. Results: As a result, the consciousness factors among factors of root cause such as unconsciousness, disregard, ignorance, recklessness, and misjudgment had strong relationships with occupational accidents in South Korean SMSEs. Conclusion: We conclude that the educational policies necessary for minimizing these consciousness factors include continuous training procedures followed by periodic hands-on experience, along with perceptual and cognitive education related to occupational health and safety.

• Journal of the Korean Geographical Society
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• v.44 no.6
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• pp.797-812
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• 2009

The purpose of this study is to analyze cause-and-effect relationships between patterns of the road network and socio-economic factors such as population, industry, and land use of Seoul during the period of 1970~2000. In this study, Structural Equation Model (SEM) is used to estimate simultaneously the cause-and-effect relationships between many independent variables and dependent variables. For the observed variables, variables related to population, industry, land price, land use, and road variables were included; these variables were classified by exploratory factor analysis. The analysis using the SEM showed that the structure of the model changed around the 1980's. In general, socio-economic factors such as population, industry, and land use affected construction of the road network of the city during the 1970's and the 1980's. Especially, it was analyzed that the industrial development had the greatest impact on formation of the road network. In the 1990's, the effect that the road network exerts on socio-economic factors proved to be more appropriate than the other way round. At that time, the road-related factors had the greatest effect on the land price and industrial development, and that tendency has continued until now.

• Korean Management Science Review
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• v.12 no.2
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• pp.165-188
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• 1995

The conversion processes from traditional job shops to cellular manufacturing systems can be viewed as an aggregation of cause-and-effect relationships among many strategic, managerial, and technical variables. Therefore, management needs to fully understand these interacting variables and possible relationships between the variables to successfully convert their plants to cellular manufacturing systems. The purpose of this study is to assist such management's needs in part. The objectives of this research are i) investigating contingency variables that may affect the conversion processes and outcomes to cellular manufacturing systems and ii) examining relationships between the variables and the conversion processes and outcomes. In this paper, particularly three categories of variables are examined: product, process routing, and process technology / facilities characteristics. Literature review and the mail survey method are used. The results are compared and synthesized with the findings of previous studies for useful discussions. Some previous arguments and propositions are empirically supported.

• Journal of Fisheries and Marine Sciences Education
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• v.25 no.6
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• pp.1306-1314
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• 2013

The purpose of this study is to find the structural relationships among major satisfaction, career search efficacy, and career exploration behavior with marine science high school students. For investigating this topic, 524 students were surveyed from the marine science high schools. In order to find out the structural relationships among major satisfaction, career search efficacy, and career exploration behavior, structural equation modeling was used. Followings were the results of the research: (a) Major satisfaction effected significantly on the career search efficacy. (b) Career search efficacy effected significantly on the career exploration behavior. (C) There was not significant direct cause and effects from major satisfaction to career exploration behavior, but indirect effect was significant. Some recommendations were suggested for increasing career exploration behavior of marine science high school students.

• Knowledge Management Research
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• v.17 no.3
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• pp.23-44
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• 2016

This study examined the cause-and-effect relationships among developmental network characteristics, developmental functions, and career identity. The study analyzed the data of employees with more than two years of experience and a college degree or over qualifications, from domestic companies. For analysis, the structural equation model was applied. Most of all, it was substantiated that the structural relationships among the developmental network characteristics, developmental functions, and career identity. The specific results were as follows. First, tie strength had a positive effect on all of developmental functions but psychosocial support mediated the relationship between the tie strength and career identity. Second, an indirect relationship between indicators of network diversity and identity was not found or the indirect relationship was very weak.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.1
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• pp.87-101
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• 2018

The purpose of this study is to develop the measuring instruments for evaluation criteria for Malcolm Baldrige National Quality Award(MBNQA), suitable for ICT Industries, and to analyze the cause-effect relationship between those criteria through aforementioned instruments. MBNQA is formed with seven categories: Leadership, Strategic planning, Focus on patients, other customers and markets, Measurement, analysis and knowledge management, Human resource focus, Process management and Results. As excluding the Human Resource Focus category, this study empirically examined the cause-effect relationship among six categories. In order to empirically examine the research model, this study calculated Cronbach's alpha and reliability index, thus examined the reliability and executed Exploratory Factor Analysis. Furthermore, Average Variance Extracted(AVE) is used to verify the discriminant validity. Lastly, the hypothesis testing was made complete through significance test on the paths between variables. The result of this study shows that both leadership and social responsibility have direct cause-effect relationship with Measurement, analysis and knowledge management, Human resource focus, Process management and also that this relationship has direct impact on Human resource focus, Measurement, analysis and knowledge management as well, consequently exerting influence on the result through Process management, Finance and Market data.

• Journal of Korean Society for Quality Management
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• v.26 no.1
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• pp.11-26
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• 1998

A key aspect of theoretical and practical development of quality management is articulation of the distinction between quality management practices(input) and quality performance (output), which to date has been blurred under the broad heading of 'quality'. Recent literature primarily addressed measurement of quality performance but very little empirical research focuses specifically on quality management practices. In order to understand quality cause and effect, it is necessary to specify and measure quality management practices (cause) as well as quality performance (effect). This paper identifies and substantiates the key areas of quality management that must be implemented to achieve effective quality management, then analyzes relationships among those areas. In doing so, it establishes the basis for subsequent research by producing a profile of organization-wide quality manage-ment and provides the direction and priority of quality management practices for practitioners.