• The Journal of Asian Finance, Economics and Business
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• v.9 no.6
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• pp.33-44
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• 2022

Women entrepreneurs play a vital role in employment creation, economic development, and growth. Women entrepreneurship is deep-rooted in the social and cultural norms and values of society. Women's entrepreneurship contribution is still invisible and needs to be properly investigated. The current research study explores "how institutions affect women's entrepreneurial performance in Pakistan" by using institutional and social cognitive theories. Focusing on the Formal and informal institutions, this research examines how institutions are affecting women's entrepreneurial performance by taking the mediating role of women's entrepreneurial self-efficacy and ethical decision making. A 7-point Likert scale research questionnaire is used to collect primary data. Data on active entrepreneurs are collected from the Peshawar, Mardan, and Abbottabad divisions of KPK's Women Chambers of Commerce. The data is empirically tested through the path analysis technique of structural equation modeling (SEM) through SMART PLS 3. The results indicated that women's entrepreneurial self-efficacy and ethical decision-making strongly mediate both institutions and significantly affect women's entrepreneurial performance. The study suggests that government and concerned departments should pay due attention to determinants like informal institutions and social constraints to boost women's entrepreneurial performance.

• Journal of the Korean earth science society
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• v.31 no.5
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• pp.437-447
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• 2010

Spatial estimation of environmental variables has been regarded as an important preliminary procedure for decision-making. A minimum variance criterion, which has often been adopted in traditional kriging algorithms, does not always guarantee the optimal estimates for subsequent decision-making processes. In this paper, a geostatistical framework is illustrated that consists of uncertainty modeling via stochastic simulation and risk modeling based on loss functions for the selection of optimal estimates. Loss functions that quantify the impact of choosing any estimate different from the unknown true value are linked to geostatistical simulation. A hybrid loss function is especially presented to account for the different impact of over- and underestimation of different land-use types. The loss function-specific estimates that minimize the expected loss are chosen as optimal estimates. The applicability of the geostatistical framework is demonstrated and discussed through a case study of copper mapping.

• Communications of Mathematical Education
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• v.22 no.4
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• pp.459-469
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• 2008

We give a mathematical approach using Linear Algebra, especially largest eigenvalue and eigenvector on decision making support system. We find a mathematical modeling on decision making problem which could be solved by AHP(Analytic Hierarchy Process) method. Especially, we give a new approach to change evaluation indicator weight on assessing research proposals.

• Industrial Engineering and Management Systems
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• v.15 no.2
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• pp.156-172
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• 2016

Complex and uncertain issues in supply chain result in integrated decision making processes in supply chains. So decentralized (distributed) decision making (DDM) approach is considered as a crucial stage in supply chain planning. In this paper, an uncertain DDM through coordination mechanism is addressed for a multi-product supply chain planning problem. The main concern of this study is comparison of DDM approach with centralized decision making (CDM) approach while some parameters of decision making are assumed to be uncertain. The uncertain DDM problem is modeled through fuzzy mathematical programming in which products' demands are assumed to be uncertain and modeled using fuzzy sets. Moreover, a CDM approach is customized and developed in presence of fuzzy parameters. Both approaches are solved using three fuzzy mathematical optimization methods. Hence, the contribution of this paper can be summarized as follows: 1) proposing a DDM approach for a multi-product supply chain planning problem; 2) Introducing a coordination mechanism in the proposed DDM approach in order to utilize the benefits of a CDM approach while using DDM approach; 3) Modeling the aforementioned problem through fuzzy mathematical programming; 4) Comparing the performance of proposed DDM and a customized uncertain CDM approach on multi-product supply chain planning; 5) Applying three fuzzy mathematical optimization methods in order to address and compare the performance of both DDM and CDM approaches. The results of these fuzzy optimization methods are compared. Computational results illustrate that the proposed DDM approach closely approximates the optimal solutions generated by the CDM approach while the manufacturer's and retailers' decisions are optimized through a coordination mechanism making lasting relationship.

• Knowledge Management Research
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• v.22 no.2
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• pp.189-208
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• 2021

The purpose of this study was to identify the effect of education service quality (quality of professor service, quality of curriculum service) on career decision-making, self-efficacy, career decision level, and career preparation behavior. Appropriate measures were developed and tested on 426 respondents of Gyeongnam province in South Korea with a cross-sectional questionnaire survey. To ensure the reliability and validity of the questionnaire, frequency analysis, reliability analysis, and validity analysis were conducted. To ensure the reliability and validity of the measurement model, the CFA(confirmatory factor anlaysis) were conducted. The SEM(structural equation modeling) analysis was undertaken to perform the path analysis among the variables and to assess the suitability of the model. MCFA(multi group CFA) and MSEM(multi group SEM) were performed to confirm the moderation effect. Results of the study are summarized as follows: Firstly, education service quality has positive effects on career decision-making self-efficacy. Second, career decision-making self-efficacy has positive effects on career decision level and career reparation behavior. Third, career decision level has positive effects on career reparation behavior. Finally, it was found there exists a moderating effect of freshman/registered student between education service quality, career decision-making self-efficacy, career decision level, career preparation behavior. As a result of this study, it is suggested that investigation of extraneous variables which help to improve career preparation behavior and career decision level as for career of university student will contribute to university education.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2016.05a
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• pp.285-286
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• 2016

We aim to propose the prediction modeling method of ship's position with extracting ship's trajectory model through pattern recognition based on the data that are being collected in VTS centers at real time. Support Vector Machine algorithm was used for data modeling. The optimal parameters are calculated with k-fold cross validation and grid search. We expect that the proposed modeling method could support VTS operators' decision making in case of complex encountering traffic situations.

• Korean Management Science Review
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• v.29 no.1
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• pp.153-168
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• 2012

Order allocation is one of the most important decision-making problems of firms having significant influences on performances of themselves and the whole supply chain. Existing researches about order allocation have mainly focused on evaluating capabilities of directly connected suppliers so that it is hard to consider effects and interactions from undirected connections over multiple lower-layers. To alleviate the limitation, this paper proposed a novel approach to order allocation using structural hole. By applying the concept of structural hole to the supply network, we could evaluate the structural supplying powers of firms with respect to both of direct and indirect connections. In the proposed approach, we derived a methodology to measure the potential supplying power of each firm by modifying the effective size as one of the measurements of structural hole and then, proposed its application, the structural hole based order allocation strategy. Furthermore, we conducted the agent based modeling of supply chain to perform the decision-making process of order allocation and simulated the proposed strategy. As a results, by coping with the variance of demand more stably, it could improve the performance of supply chain from the aspects of fill rate, inventory level and demand-supply balance.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.591-597
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• 2001

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). Immune system is living body's self-protection and self-maintenance system. These features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For applying immune system to DARS, a robot is regarded as a B-cell, each environmental condition as an antigen, a behavior strategy as an antibody and control parameter as a T-cell respectively. The executing process of proposed method is as follows. When the environmental condition changes, a robot selects an appropriate behavior strategy. And its behavior strategy is stimulated and suppressed by other robot using communication. Finally much stimulated strategy is adopted as a swarm behavior strategy. This control school is based on clonal selection and idiotopic network hypothesis. And it is used for decision making of optimal swarm strategy. By T-cell modeling, adaptation ability of robot is enhanced in dynamic environments.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.1
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• pp.115-129
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• 2003

This paper Is concerned with a new techno-economic model Ing of ATM based h19h-speed networks. Coupled with advances of technology, the rapid development of new telecommunication services significantly increases the magnitude of risk in making an Investment decision. Naturally, the success of techno-economic modeling depends on how effectively we manage underlying risk factors such as cost and technology To deal with risk factors, we need to rely on modern decision and risk analysis while Implementing mathematical optimization for solving a complex capacity expansion problem of telecommunication systems during the planning period. We provide a case study that will enhance our understanding of the techno-economic analysis for emerging telecommunication systems.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.3
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• pp.170-177
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• 2010

Poker is a game of imperfect information where competing players must deal with multiple risk factors stemming from unknown information while making the best decision to win, and this makes it an interesting test-bed for artificial intelligence research. This paper introduces a new learning AI algorithm with embedded opponent modeling that can be used for these types of situations and we use this AI and apply it to a poker program. The new AI will be based on several graphs with each of its nodes representing inputs, and the algorithm will learn the optimal decision to make by updating the weight of the edges connecting these nodes and returning a probability for each action the graphs represent.