This study aims to develop a comprehensive predictive model for Digital Quality Management (DQM) and to analyze the impact of various quality activities on different levels of DQM. By employing the Classification And Regression Tree (CART) methodology, we are able to present predictive scenarios that elucidate how varying quantitative levels of quality activities influence the five major categories of DQM. The findings reveal that the operation level of quality circles and the promotion level of suggestion systems are pivotal in enhancing DQM levels. Furthermore, the study emphasizes that an effective reward system is crucial to maximizing the effectiveness of these quality activities. Through a quantitative approach, this study demonstrates that for ventures and small-medium enterprises, expanding suggestion systems and implementing robust reward mechanisms can significantly improve DQM levels, particularly when the operation of quality circles is challenging. The research provides valuable insights, indicating that even in the absence of fully operational quality circles, other mechanisms can still drive substantial improvements in DQM. These results are particularly relevant in the context of digital transformation, offering practical guidelines for enterprises to establish and refine their quality management strategies. By focusing on suggestion systems and rewards, businesses can effectively navigate the complexities of digital transformation and achieve higher levels of quality management.

본 연구는 서울교육청 교육연구정보원의 「서울교육종단연구(SELS)」에 서 수집된 자료를 활용하여, 고등학생 3학년인 9차(2018년) 자료에서 학 생 2,793명을 연구 대상자로 정하였다. 청소년의 학교만족도와 관련한 예측요인을 확인하기 위해 SPSS 26.0을 사용하여 의사결정나무모형 분 석을 실시하였다. 연구결과를 살펴보면, 첫째, 청소년의 학교만족도의 분 류에서 개인적인 요인으로는 성별, 자아개념, 자기평가, 사회적 관계 요 인으로 보호자, 학교교사, 학교 특성/문화 요인으로는 학교에 대한 평가, 학교풍토가 유의한 변인으로 확인되었다. 둘째, 학교만족도 분류에 영향 을 주는 변인들 중에서는 학교에 대한 평가가 가장 영향력을 가진 변인 으로 나타났다. 셋째, 학교교사 수치가 높은 집단에서는 학교풍토, 자아 개념이 분류의 중요한 의미 있는 변인이었고, 학교교사 수치가 낮은 집 단에서는 자기평가, 학교풍토, 학교에 대한 평가가 영향력 있는 변인이었 다. 넷째, 학교에 대한 평가 수준 및 학교풍토가 바람직하고 좋으면 학교 만족도가 긍정적으로 상승하는 것으로 확인되었다. 본 연구결과는 청소 년의 학교만족도 증진을 위한 방안 모색, 교육정책 수립 및 프로그램 운 영에 도움이 될 것으로 사료된다.

Selecting suppliers in the global supply chain is the very difficult and complicated decision making problem particularly due to the various types of supply risk in addition to the uncertain performance of the potential suppliers. This paper proposes a multi-phase decision making model for supplier selection under supply risks in global supply chains. In the first phase, the model suggests supplier selection solutions suitable to a given condition of decision making using a rule-based expert system. The expert system consists of a knowledge base of supplier selection solutions and an “if-then” rule-based inference engine. The knowledge base contains information about options and their consistency for seven characteristics of 20 supplier selection solutions chosen from articles published in SCIE journals since 2010. In the second phase, the model computes the potential suppliers’ general performance indices using a technique for order preference by similarity to ideal solution (TOPSIS) based on their scores obtained by applying the suggested solutions. In the third phase, the model computes their risk indices using a TOPSIS based on their historical and predicted scores obtained by applying a risk evaluation algorithm. The evaluation algorithm deals with seven types of supply risk that significantly affect supplier’s performance and eventually influence buyer’s production plan. In the fourth phase, the model selects Pareto optimal suppliers based on their general performance and risk indices. An example demonstrates the implementation of the proposed model. The proposed model provides supply chain managers with a practical tool to effectively select best suppliers while considering supply risks as well as the general performance.

한우 사육두수는 한우 암소의 번식 정도가 어느 정도인지에 따라서 결정된다. 한우 암소의 번식 여부 는 산지가격에 대한 기대가격에 따라 결정된다. 이 논문은 한우 암소 번식농가의 의사결정 행위를 분석 한 것이다. 이를 위해 네 가지 기대모형이론을 적용하여 어느 모형이 보다 적합한 모형인지를 비교하였 다. 산지가격에 대한 기대가격을 형성함에 있어서 순수기대모형, 적응적기대모형, 부분조정모형, 합리적 기대모형 등 네 가지 모형을 적용하였다. 그리고 이들 네 가지 기대모형을 근거로 실제 암소도축과 송 아지공급함수를 추정하였다. 그 결과 한우 암소 번식농가의 의사결정은 상대적으로 복잡한 적응적기대 모형이나 부분조정모형보다는 순수기대모형이나 합리적기대모형으로 잘 설명되는 것으로 분석되었다. 또한, 모형 전체의 적합도에서는 합리적기대모형이 가장 우수한 것으로 나타났다.

공원일몰제 시한이 다가옴에 따라 미집행 시설용지에 대한 해제·매입 여부 결정이 시급해지고 있다. 따라서 미집행 도시공원시설용지의 해제·매입과 관련하여 입지 의사결정을 수행할만한 객관적 기준마련이 시급한 상황이다. 이 연구의 목적은 효율성과형평성이라는 계획적 규범 가치를 새롭게 조명하고 여기에 비용이라는 현실적 제약조건을 반영하여 입지 의사결정 지원을 위한 입지모형을 제안하는 것이다. 이를 위해 형평성과 효율성 기준을 결합하여 입지 우선순위 지수를 정의하고, 이를 바탕으로 지자체의 한정된 예산이라는 제약조건을 반영하기 위한 시뮬레이션 틀을 마련하였다. 작성된 모형의 구체적 활용성 제고를 위하여 원형 프로그램을 구축한 뒤 이를 대구시 미집행 도시공원 용지에 적용하여 시뮬레이션을 수행하였다. 그 결과 미집행 시설용지의 해제‧매입 관련입지 우선순위 의사결정에 있어서 작성된 모형이 폭넓은 정책적 함의를 가지는 것으로 판단된다.

본 연구는 불특정 다수의 도로이용자들이 경로우회 시 갖는 의사결정과정속에 내포된 비선형성과 불확실성을 고려한 정도 있는 모형구축으로 주요 우회결정요인을 분석하는 것이 주요 목적이다. 이를 위하여 고속도로 및 국도를 이용하는 운전자를 대상으로 우회여부에 관련된 SP조사를 실시하였고, 조사결과에 대하여 의사결정나무와 신경망이론의 결합된 모형을 구축하여 운전자 우회결정요인을 분석하였다. 분석결과 운전자 우회여부결정에 영향을 미치는 요인은 우회도로 인지여부, 교통정보 신뢰도 및 이용빈도, 경로전환빈도, 나이순으로 나타났다. 또한 오분류표를 통한 기존 모형과의 예측력의 비교결과 결합된 모형의 오분류율이 8.7%로 기존 모형인 로짓모형 12.8%, 의사결정나무 단독 모형 13.8%와 비교했을 때 가장 예측력이 높은 것으로 나타나 운전자 우회결정요인 분석에 관한 모형의 적용 타당성을 확인할 수 있었다. 본 연구의 결과는 향후 교통량 분산효과와 도로망 효율 증대를 위한 효과적인 우회관리전략 수립 시 기초 자료로 활용가능하리라 사료된다.

The bullwhip effect is known as the significant factor which causes unnecessary inventory, lost sales or cost increase in supply chains. Therefore, the causes of the bullwhip effect must be examined and removed. In this paper, we develop two analytical to

  In this paper the economic value of weather forecasts is valuated for profit-oriented enterprise decision-making situations. Value is estimated in terms of monetary profits (or benefits) resulted from the forecast user’s decision under the specific payo

Multi-criteria decision making is deducing the relative importance in the criterion of decision making and each alternative which is able to making a variety of choices measures the preferred degree in the series of town ranking criterions. Moreover, this is possible by synthesizing them systematically. In general, a fundamental problem decision maker solve for multi-criteria decision making is evaluating a set of activities which an considered as the target logically, and this kind of work is evaluated and synthesized by various criterions of the value which a chain of activities usually hold in common. In this paper, we use the compensatory models for the optimal decision making. For the purpose of optimal decision making, the data of five different car models are used in Europe.

This paper is intended to develop a Bayesian decision model for the repair of deteriorating system. A non-homogeneous Poisson process with a power law failure intensity function is used to describe the behavior of the deteriorating repairable system. The decision on whether to have minimal repair or imperfect repair should be made on the occurrence of a failure. However, it is difficult to make a reasonable decision due to many uncertainties intrinsic in repair actions. In this paper, prior distributions are used in order to analyze the uncertainties embedded in the decision alternatives. Especially, a prior distribution for imperfect repair with probabilistic reduction in the failure intensity is proposed. In addition, mathematical expressions to calculate the expected prior loss of each repair alternative are proposed.

In this paper we extend the classical decision model under uncertainty to a more general case. We propose an expected utility-uncertainty model and we can make a decision by trading off between a measure of uncertainty and a measure of expected value. As a risk analysis model, the expected utility-uncertainty model can be seen to be reasonable and flexible for states of nature or individuals' preferences. Moreover, the model can explain some decision paradoxes.

In this paper we extend the classical decision model under uncertainty to a more general case. We propose an expected utility-uncertainty model and we can make a decision by trading off between a measure of uncertainty and a measure of expected value. As a risk analysis model, the expected utility-uncertainty model can be seen to be reasonable and flexible for states of nature or individuals' preferences. Moreover, the model can explain some decision paradoxes.

This paper is intended to develop a Bayesian decision model for the repair of deteriorating system. A non-homogeneous Poisson process with a power law failure intensity function is used to describe the behavior of the deteriorating repairable system. The decision on whether to have minimal repair or imperfect repair should be made on the occurrence of a failure. However, it is difficult to make a reasonable decision due to many uncertainties intrinsic in repair actions. In this paper, prior distributions are used in order to analyze the uncertainties embedded in the decision alternatives. Especially, a prior distribution for imperfect repair with probabilistic reduction in the failure intensity is proposed. In addition, mathematical expressions to calculate the expected prior loss of each repair alternative are proposed.

This study aims to examine the usefulness on the Evaluation Process for the Feasibility & Priority of A Certain Public Projects. and the Methodology used AHP(Analytic Hierarchy Process) which used pairwise comparisons of the alternatives and criteria for solving discrete alternative multicriteria decision problems. In this paper, we present a similar phenomenon, rank reversal problem, when we apply the AHP to group decision making process. The problem is identified by an example problem in that the previous rank order of Public Projects choices. we also present three different methods to prevent the undesirable characteristic of the original AHP in appling to Decision Making Process.

Finding an optimal solution in MADM(Multi-Attribute Decision-Making) problems is difficult, when the number of alternatives, or that of attributes is relatively large. Most of the existing mathematical approaches arrive at a final solution on the basis of many unrealistic assumptions, without reflecting the decision-maker's preference structure exactly. In this paper we suggest a model that helps us find a group consensus without assessing these parameters in specific cardinal values. Therefore, This research provides a comprehensive Decision Making of the theory and methods applicable to the analysis of decisions that involve risk and multiple criteria attributes. after, The emphasis of the procedure will be on developments from the fields of decisions analysis and utility theory of Taguchi Method. This theoretical development will be illustrated through the discussion of several real-world application and a case study. When the multiple number of decision makers are involved in the decision making procedure, the problem of uncertainties invariably occurs, because of the different views between them. In this paper, New decision making model using Taguchi Method is applied to effectively model the multi-attribute-decision making(MADM) procedure in the uncertainties dominated two area(quantitative and qualitative factors), Quantitative factors evaluation is used Loss Function of Taguchi, qualitative factors evaluation is used S₩N ratio by each specialist. thus it can be used for aiding of preferable alternative. as a result, We will be proved efficiency about New decision making model of applied Taguchi Method with Analytical presentation of all the expecting outcomes when a specific strategy or an alternative plan is selected under expecting future environment.

Finding an optimal solution in MADN[(Multi-Attribute Decision-Making) problems is difficult, when the number of alternatives, or that of attributes is relatively large Most of the existing mathematical approaches arrive at a final solution on the basis of many unrealistic assumptions, without reflecting the decision-maker's preference structure exactly. In this paper we suggest a model that helps us find a group consensus without assessing these parameters in specific cardinal values. Therefore, This research provides a comprehensive Decision Making of the theory and methods applicable to the analysis of decisions that involve risk and multiple criteria attributes. after, The emphasis of the procedure will be on developments from the fields of decisions analysis and utility theory of Taguchi Method. This theoretical development will be illustrated through the discussion of several real-world application and a case study. When the multiple number of decision makers are involved in the decision making procedure, the problem of uncertainties invariably occurs, because of the different views between them. In this paper, New decision making model using Taguchi Method is applied to effectively model the multi-attribute-decision making(MADM) procedure in the uncertainties dominated two area(quantitative and qualitative factors), Quantitative factors evaluation is used Loss Function of Taguchi, qualitative factors evaluation is used 50 ratio by each specialist. thus it can be used for aiding of preferable alternative. as a result, We will be proved efficiency about New decision making model of applied Taguchi Method with Analytical presentation of all the expecting outcomes when a specific strategy or an alternative plan is selected under expecting future environment.

Information systems(IS) outsourcing has become a very important management strategy of implementing IS and many studies on the IS outsourcing approach had been performed in the organizations. But it isn't still show how to out source the IS functions and how to offer quantitative magnitude for judgement. To offer a quantitative decision model that can help practitioners set priority and reap the most benefits from outsourcing, we show outsourcing structure including 3 factors (strategic, economic and technological benefit) and sub-levels which is different from the Yang and Huang's model. Also, we compute the weight of alternatives using analytic hierarchy process to find a priority of the IS outsourcing. As a result of analysis, we suggest systematic steps and quantitative model to increase the precision of decision making. 1)

Recently, information systems(IS) outsourcing has become a very important management strategy of implementing IS and many studies on the IS outsourcing approach had been largely performed in the organizations, but it isn't still show how to outsource the IS functions and how to decide quantitative magnitude for judgement. To offer a quantitative decision model that can help practitioners set priority and reap the most benefits from outsourcing, we show outsourcing structure including 3 factors(strategic benefit, economic benefit and technological benefit) and sub-levels which. is different from the Yang and Huang's model. Also, we compute the weight of alternatives using analytic hierarchy process to find a priority of the IS outsourcing. As a result of analysis, we suggest systematic steps and quantitative model to increase the precision of decision making.