Modern Research in Decision Making

Abstract In an era where rapid and increasing change is one of its characteristics, the pace of decision-making has also created conditions that have shortened the time for interaction, reflection and decision-making for managers.In fact, today's managers find themselves forced to make more decisions about a wider variety of issues and problems in a shorter period of time. Therefore, the purpose of this study is to provide a model to explain the decision-making system in government organizations in Kurdistan province. The present research, descriptive-correlational which is of survey research type, is among applied ones that was done as a field study. The population of this research included all senior managers, managers and experts of Government organizations To do the research, 358 persons were chosen as our research Statistical population. Based on the findings of literature review and interviews with experts of government organizations, theme analysis and the use of four rounds of Delphi method, the final conceptual model of the research including 5 main dimensions and 76 sub-dimensions was extracted. Then, using the structural equation modeling method, the model of measuring the components of the model and the structural model of the whole model were validated. Based on the research findings, the dimensions of "individual factors (I)", "structural and process factors (S)", "executive factors (A)", "organizational factors" and "environmental factors (E)" explain the model of the decision-making system in government organizations in Kurdistan province.

Abstract Abstract
Today, the use of game theory in supply chain management is very common. Game theory is used not only in pricing goods in the supply chain, but also in advertising discussions and examining the interaction of supply chain members. In this paper, the competition between two supply chains, each of which includes a manufacturer and a distributor, is considered. Demand for goods is a function of price and lead time. Competition under the game scenario is considered nonecooperation and with cooperation. Three types of scenarios have been developed under the game theory none cooperation (Nash-Stackelberg) and with different for analysis and decision-making related to price, lead time and shipping size. A unique equilibrium is shown in all games and detailed formulas are provided to calculate the optimal decisions of each chain. Numerical examples and analysis of the results of useful management insight to select the best strategies for chains in different market and operational environments.

Abstract The complexity of designing a strategy for the Thermal Power Plant Holding, leads to many fifficulties and inappropriateness of previous strategies. Problem structuring methods, facilitate the process of identifying the problems in a coherent and logical context. A process that takes various steps to identify the problem and its complexities, and ultimately, the result is the formulation of the organization's main strategies based on real conditions. The result of such an effort is to formulate a strategy that has the least confrontations and complexities while implementing. In this research, a PSM approach called JOURNEY MAKING is used.
The research method is developed and applied. Also, the data gathered from 20 experts, consultants and senior experts of Thermal Power Plant Holding with interview and questionnaire. Finally, 10 steps of JOURNEY MAKING were implemented and 8 major scenarios were designed in 2 phases of operation and development. At the end, suggestions were made for the implementation of the scenarios.

Abstract Designing a Model for Forecasting Product Life Cycle with Thermodynamics Approach
Abstract
The aim of this study is to integrate marketing models and create a model for hierarchical marketing activities to identify the different levels of activities required in the various stages of the product life cycle. In this study, in order to explain the phenomenon of product life cycle, mixed marketing activities have been used as a factor in changing the quality of entropy. In this study, ceramic tiles have been selected as the desired product to examine the validity of experimental theories. Brand, sales and marketing managers of 3 ceramic tile companies were asked to answer the questions. Through hierarchical analysis and simulation processes, simulations are simulated that show that if more mixed marketing activities are used, the product life will be longer and the sales volume will be higher.
Keywords: Thermodynamics, Product life cycle, AHP, Tile and ceramic industry

Abstract Supplier selection is one of the most critical problems in the supply chain management that helps firms to evaluate and select appropriate suppliers. Different conflicting objectives could be considered in these kinds of problems. Most important objectives are: minimizing the cost, maximizing the quality, and maximizing the reliability. In this paper the set of suppliers are considered as a system and they are selected so that maximizing the reliability of the selected set and maximizing the quality of the received products, and also minimizing the purchasing cost. On the other hand, in practice exact data are not accessible, therefore, fuzzy theory is utilized to evaluate the suppliers. In addition, suppliers usually use discount mechanism to attract more buyers and to achieve more profits. In this paper supplier selection problem is modeled considering all unit discount. Additionally, satisfaction of the demand depends on the risk attitude of the buyer. The satisfaction of the demand is considered as a fuzzy-probabilistic constraint. Finally, a numerical example is solved based on different risk attitudes of the buyer and related results are reported.

Abstract Due to the vital role resources play in the project's success or failure, in the last 60 years, much research has been done in the field of resource-leveling. The first studies considered the conditions of the project to be definite, but the following researches led to the uncertainty of the project conditions. Some of these uncertain studies assumed that the project conditions were only fuzzy, and some assumed that they were only stochastic. After introducing fuzzy-stochastic theory, project management research considered the conditions for a project to be fuzzy-stochastic. Due to the gap of this approach in resource leveling, this quantitative and developing research developed a multi-objective fuzzy-random resource-leveling model. In this research, the project execution time is considered as a fuzzy-random variable. Finally, the proposed model, which is among the NP-hard models, was solved by an NSGA-II algorithm in Matlab software. Two other algorithms developed this algorithm, namely control algorithm and variable decision preparation algorithm, and a control-memory, to solve the problem of project's diversity. The innovation of this research is noteworthy in two cases. The first is that the multi-objective resource-leveling model was presented in a fuzzy-random manner, and the second is that the NSGA-II algorithm was developed to solve it. Finally, the proposed algorithm's reproducibility, convergence, efficiency, and validity were discussed and approved.

Abstract The complexity of the production systems and increasing competition in the business environment has made uncertainty a crucial problem in supply chain design. In this regard, this study aims to develop an optimization model to configure multi-period, multi-product and multi-echelon supply chains, managing the demand and supply uncertain parameters simultaneously to maximize the profit of the entire chain. In this model, the uncertainty of the parameters was regulated by robust optimization and dynamic pricing approaches. First, the developed model was solved using the GAMS software, then the appropriate performance of the proposed model was compared with a certain base model, the validation of results were performed using sensitivity analysis. In the next step, through simulating supply and demand fluctuations, the model's performance under different conditions of uncertainty was evaluated. The results indicate that the model's optimal solution could resist this random uncertainty, even exposing a high level of supply and demand fluctuations.

Abstract Higher education centers are the axis of the sustainable social, economic, political, cultural, and scientific development of human societies; as a result, their efficiency evaluation has attracted a lot of attention at the international level. Data envelopment analysis models (DEA) are one of the most successful, efficient and practical efficiency measurement techniques due to their special features and advantages. DEA models, in addition to measuring relative efficiency, are also able to provide the necessary planning to improve efficiency. Hence, so far, a lot of research has used DEA models to measure the efficiency of higher education centers. In this study, in order to measure the quality of performance of higher education centers, one of the DEA models called Input efficiency profiling model (IEP) has been used, as well. The proposed model is a new evaluation model called Improved input efficiency profiling – Super efficiency model (IIEP – SE), which has improved the performance of IEP model by addressing some of its shortcomings. It has been shown by a numerical example and comparing the proposed model with other DEA models that the proposed model has necessary reliability and desirable performance. In order to plan for achieving the efficiency of the inefficient units, pattern and reference units and the amount of necessary change in the input and output criteria for each of the inefficient units have also been determined.

Abstract The management of production processes in order to reduce costs and increase revenue and profits is one of important and essential factors to achieve success in economic affairs and then the satisfaction of managers and customers. In this regard, using an appropriate approach to evaluate the performance and to manage complex systems with network structure is important and necessary. Network Data Envelopment Analysis (NDEA) is a suitable and effective non parametric programming method for assessing the performance of decision-making units with multiple inputs and outputs, as well as taking into account internal processes. In this research, based on the DEA technique, considering the appropriate role for intermediate factors of processes as well as the weak disposability for undesirable factors, the efficiency of systems with a two - stage network structure in the presence of undesirable factors is evaluated. To further explain and analyze the proposed method, a case study is also examined.

Abstract Collective decision-making is the process by which a group of people makes a single decision on a particular issue to achieve improvement by realizing their goal. Collective decision-making is known as one of the most important ways to achieve optimal decision-making. This paper aims to provide a comprehensive picture of the dimensions of collective decision-making and to answer a set of related questions in this field via a systematic literature review (SLR). In this regard, in the first part, the collective decision-making will be introduced and the SLR protocol will be examined in 5 steps. In the next section, the most important keywords and areas of research are identified and a co-word analysis map in the field of collective decision-making is drawn for the period between 1990 and March 2021 on the Web of Science. In the following, research questions will be answered. In response to these questions, the need for use and examples of the use of collective decision-making is stated. Then, effective factors in collective decision-making are examined and the way to reach a collective decision is explained. Finally, the advantages and disadvantages of collective decision-making are discussed and its methods and tools are described. Also, models of collective decision-making are given as a sample and an analysis of the results is provided.