• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.761-771
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• 2020

This study discusses the role of Board Monitoring Effectiveness (BME) on managers' decisions regarding the business strategies that fit the external business environmental conditions by using a contingency analysis approach. Furthermore, this study will examine how fit strategies affect Sustainability Reporting (SR) of listed companies on the Indonesia Stock Exchange (IDX) from 2014 to 2017. This study uses Conditional Mixed Process (CMP) technique. This CMP method is claimed to be more efficient in analyzing the TSL models. This study found that in highly uncertain conditions, BME had a positive influence on the probability of managers to choose prospector and defender strategies rather than analyzers. These results indicate that BME shows positive impact on the contingency fit between business strategies and environmental uncertainty. In addition, the study documents that only prospectors have a positive impact on SR, however this study failed to document that defenders have positive impact on SR. Meanwhile the unexpected result is analyzers have a significantly positive effect on SR. This study is the first study to investigate the role of BME in contingency fit between business strategies and environmental uncertainties and how it produces effects up to the level of SR.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.39-49
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• 2001

When an appropriate model is fitted to explain a certain categorical data, outlying cell detection plays very important role to reduce the lack of fit. There exist many statistical methods to identify outlying cells in contingency table. In this paper, correspondence analysis is applied to identify one or two outlying cells. When corresponding relationships between categories of the row and columns are explored, we find that outlying cells could be identified via the correspondence analysis map.

• Journal of Information Technology Applications and Management
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• v.21 no.4
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• pp.225-245
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• 2014

ICT based convergence application is one of the most prevalent industrial issue these days. Despite of criticalness and potential economic opportunities of the ICT based convergence, theoretical research to analyze the feasibility and estimate the economic impact of the application is rather limited. This paper is intended to fill this research gap. In this respect, we develop theoretical framework to quantitatively estimate the differential benefits of convergent applications, which necessarily include underling ICT technology's contribution attributes extractions, and resulting value increments engendered from user's process effectiveness when ICT based service application is adopted. The research model to assess the differential value of the ICT based service application is developed, grounded on theoretical framework of TPC (Technology-to-performance chain) and contingency fit theories. Scenario based survey method is adopted, and SmartPLS 2.0. is used for statistical analysis of the structural equation model using 312 questionnaire. Valid statistical results are presented to provide useful insight.

• Journal of Information Technology Applications and Management
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• v.16 no.2
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• pp.1-21
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• 2009

The balanced scorecard(BSC) framework is a tool for strategic decision making and task support that aims for efficiency in performance management and strategy execution. BSC evolved from an old performance management practice, which tended to be limited to a finance-only perspective, to a new system of corporate management looking at corporate tasks from a multi-dimensional, future-inclined value perspective. This form of BSC amounts to a framework capable of driving management innovation and renewing the ways in which companies conceive their strategy and perform their operations. Since BSC draws integrally on user participation, it can be expected that users' satisfaction with BSC systems is an important factor in systems' success or failure. However, previous studies of the BSC system have not yet considered it as a theoretical model, specifically examining BSC system and task characteristics. To date, only a few studies have put forward plans for the implementation and use of BSC systems, and these studies have the common limitation of failing to consider the circumstances or theoretical structure of the companies for which a BSC system is being proposed. This paper then begins to fill some of this gap by characterizing the BSC system from the perspective of contingency theories. Contingency theories can be particularly useful in the Korean context in exploring how different companies use the BSC system in ways determined by their unique environmental characteristics, which may also determine the performance factors behind the application of a company's particular BSC system. In order to provide concrete suggestions for implanting and using the BSC system from a contingency theory perspective, this study sets out to determine the relationships between the contingency variables affecting BSC system performance and BSC system property variables(in given cases) through an empirical analysis. The study takes into account the perspective from which contingency theory is to be applied in individual cases, sets contingency and BSC property variables with reference to the BSC system user's environment and BSC system's character, and frames initial hypotheses concerning corporate structure and environmental variables and BSC system performance variables with reference to previous studies. A survey was then conducted on users in Korean companies that have implemented the BSC system in order to verify the research model and understand results.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.375-382
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• 1999

Linear-by-linear association models are commonly used to analyze ordered categorical data. To fit these models appropriate scores need to be chosen. In this paper we perform sensitivity analyses in two-way contingency tables to investigate the effect of scores on goodness-of-fits and on tests of significance. In addition we show that the best score which yields the best fit of data can be selected based on the sensitivity analysis results.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.403-418
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• 2012

In this paper, we attempted to theorize the synergy effect between the value creating attributes for digital convergence model in the service industry. Our investigation is based upon contingency fit theory to understand the strategic fit for the two inherent value attributes of fixed and mobile value, as well as resolving fundamental limitations of service processes. Empirical validation of the derived research model is analyzed using hierarchical regression method. The results indicate that the relative advantage of each value creating attributes are strongly associated with the characteristics of domain service industries, and compatibility is critical to user adoption of convergent service model. Moreover, the less significant statistical impact of the synergy between mobile and fixed value attributes and others implies that each value attribute uniquely contributes to particular IT convergence model, which thereby offers critical insight that focusing the convergent value in conjunction with specific application domain is the most appealing managerial focus. The findings provide useful insight for the further research in IT based industry convergent business model areas.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1547-1555
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• 2015

We study the problem of nonignorable nonresponse in a two-way contingency table and there may be one or two missing categories. We describe a nonignorable nonresponse model for the analysis of two-way categorical table. One approach to analyze these data is to construct several tables (one complete and the others incomplete). There are nonidentifiable parameters in incomplete tables. We describe a hierarchical Bayesian model to analyze two-way categorical data. We use a nonignorable nonresponse model with Bayesian uncertainty analysis by placing priors in nonidentifiable parameters instead of a sensitivity analysis for nonidentifiable parameters. To reduce the effects of nonidentifiable parameters, we project the parameters to a lower dimensional space and we allow the reduced set of parameters to share a common distribution. We use the griddy Gibbs sampler to fit our models and compute DIC and BPP for model diagnostics. We illustrate our method using data from NHANES III data to obtain the finite population proportions.

• Journal of the Korean Data and Information Science Society
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• v.27 no.1
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• pp.245-254
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• 2016

Many surveys provide categorical data and there may be one or more missing categories. We describe a nonignorable nonresponse model for the analysis of two-way contingency tables from small areas. There are both item and unit nonresponse. One approach to analyze these data is to construct several tables corresponding to missing categories. We describe a hierarchical Bayesian model to analyze two-way categorical data from different areas. This allows a "borrowing of strength" of the data from larger areas to improve the reliability in the estimates of the model parameters corresponding to the small areas. Also we use a nonignorable nonresponse model with Bayesian uncertainty analysis by placing priors in nonidentifiable parameters instead of a sensitivity analysis for nonidentifiable parameters. We use the griddy Gibbs sampler to fit our models and compute DIC and BPP for model diagnostics. We illustrate our method using data from NHANES III data on thirteen states to obtain the finite population proportions.

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.197-212
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• 2002

When assessing goodness-of-fit of a model, a small subset of deviating observations can give rise to a significant lack of fit. It is therefore important to identify such observations and to assess their effects on various aspects of analysis. A Cook's distance measure is usually used to detect influential observation. But it sometimes is not fully effective in identifying truly influential set of observations because there may exist masking or swamping effects. In this paper we confine our attention to influential subset In GLMs such as logistic regression models and loglinear models. We modify a backwards stepping algorithm, which was originally suggested for detecting outlying cells in contingency tables, to detect influential observations in GLMs. The algorithm consists of two steps, the identification step and the testing step. In identification step we Identify influential observations based on influencial measures such as Cook's distances. On the other hand in testing step we test the subset of identified observations to be significant or not Finally we explain the proposed method through two types of dataset related to logistic regression model and loglinear model, respectively.

• The Journal of Society for e-Business Studies
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• v.16 no.4
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• pp.283-299
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• 2011

In this paper, we draw upon Task-Technology Fit theory to investigate the fit attributes which impacted on customer preference over three virtual shopping channels which included TV home shopping, Internet shopping, and broadband applications, i.e. IPTV. The fit attributes also reflected the product category contingency, which is classified based on the degree of quality assessing difficulty on the web, such as quasi-commodity, look and feel goods, and look and feel with variable quality goods. Using the collected survey data, we employed stepwise regression analysis to validate the fit attributes in the context of performing virtual shopping task via those three distinctive media technologies. Furthermore, through ANOVA test with Duncan statistics, we reported comparative intensity of the valid fit attributes across the product categories and distinct media technologies. The results validated four critical fit attributes and significant distinctions among product categories and three virtual shopping channels. The findings provide practical insights in distribution channel design exploiting digital convergence technologies.