نشریه پژوهش های نوین در تصمیم گیری
سال چهارم شماره 3 (پاییز 1398)

Activity-based costing since it's introduction has attracted so much attention. There are, however, practical problems in implementing this costing system, which, in spite of the computational superiority of activity-based costing compared to traditional costing, organizations and companies are still not interested in using this costing method. In the present study, implementation problems that are practically related to implementation of activity-based costing have been investigated and artificial neural networks have been used to solve the problem of estimating the cost-activity relationship (CER) as well as reducing the costs of doing timing in organizations. The statistical population of the research is all branches of Maskan Bank which has been clustered using CI-DEA Data Envelopment Analysis (CI-DEA) and based on performance similarity in 1395. 450 branches were selected as samples and used to train and test the model of neural networks. The distinctive feature of this pattern is to consider non-linear relationship between cost-activity and other patterns. The proposed architecture of network makes it possible, in addition to the cost-of-activity forecast, to be extrapolated from the model, the amount of cost-driven input (time) used as a cost-sharing actuator to the activity in the conventional executive model. The results of the RMSE and MAE models showed that the proposed model has the capability to estimate the cost-activity relationship.

Statistical arbitrage is a common investing strategy in inefficient markets which is market neutral and profits from both sides of the market without the need for initial capital. This research aims at designing suitable models for stock statistical arbitrage using deep neural network, random forest, gradient-boosted trees and equal-weighted ensemble of these methods whilst analyzes the returns and risks of the designed models. For this purpose, the information of all listed companies in Tehran Stock Exchange from 1385 until 1396 has been used to generate trading signals. The design of the research models and required coding also the testing of the research hypotheses which is analyzed by t-test were performed in R software. The research findings show that the highest daily return is 4.24% for k = 5 (prior transaction costs) which is for the simple equal-weighted ensemble (ENS). Also deep neural network (DNN) has the lowest value at risk (- 4.45%) and the lowest expected shortfall (- 5.57%) for k = 20. The highest value of the return to standard deviation ratio is 1.072 which belongs to the RAF model for k = 20. Moreover, research results show that recent returns have higher predictive power than previous returns.

Supply chain management is a systematic analysis and logical decision-making system among the various functions of an organization, which results in cost effective in the flow of resources, raw materials, information, and liquidity. One of the few issues that are being considered is quantitative models for the buyer and supplier cooperation. In this paper, we try to formulate the buyer-supplier relationship with the game theory approach in two models non-cooperative and cooperative. In non-cooperative games, when the buyer has more power, he is considered to be the leader (Buyer Stackelberg) and in the second place the supplier is considered as the leader (supplier Stackelberg). The numerical analysis of the comparison between the existing models and the sensitivity analysis of the model shows the effect of the change of parameters on the cost and income. In non-cooperative games, when the buyer has more power, he is considered to be the leader (Buyer Stackelberg) and in the second place the supplier is considered as the leader (supplier Stackelberg). The numerical analysis of the comparison between the existing models and the sensitivity analysis of the model shows the effect of the change of parameters on the cost and income.

In the real world, in every problem, decision making of stakeholder of that problem is very important. Sometimes, at first, the definition of the problem is ambiguous, and the stakeholders of the problem, even at the stage of definition, are in conflict. The subject of stakeholders with different thoughts and sometimes incompatible thoughts has not been considered in traditional operational research (hard) and to structure these problems, it is necessary to use the new approaches to operational research that address the disparate categories of stakeholders (emancipating / critical and postmodern paradigms). If the nature of the problem is complex, choosing an appropriate approach among the above mentioned approaches is of particular importance. In the present study, after introducing various state of stakeholders, bring together the concept of paradigm in operational research and introducing relevant methodologies, describes the paradigm selection model and problem-solving methodology in the framework of the SOSM which proposes a postmodern paradigm for complex problems with coercive stakeholder. After reviewing the postmodern basics, a brief overview of postmodern thinking in the operational research is presented and after introducing the basics of postmodern operational research and its corresponding methodology, describes how it works based on that.

Pointing out the ever increasing importance and necessity of improving business models, a systematic approach has been proposed to develop a new business model according to the organization strategy. In this problem solving approach, various business elements were first identified by using morphological analysis and also a broad literature review on the business model frameworks. According to the more importance of the subject in Telecom industry, in the following, along with morphological analysis steps, possible options for each element were suggested and eventually, business models were achieved by synthesis them. Finally, several suggested business models were evaluated and prioritized according to organization strategy by multi criteria decision making tools. By literature review and summarizing the contents of the business model frameworks, the comprehensive elements of the business model were identified. Also, in a systematic approach, the sequence and the manner of separate development of these elements, synthesis and achieving to the superior business model according to the organization strategy has been determined. In order to illustrate the application of proposed approach, it’s been used to develop a business model in Shatel Company, and in the following seven proposed models and among them the preferred options have been identified. Creating appropriateness between the steps of general morphological analysis and the issue of developing a business model under the proposed framework reduced the complexity of business model development. The strategy of the organization was considered in the component development section as well as in the evaluation and prioritization of proposed business models.

The application of neural networks in estimating and describing the structure of decision makers' priorities has been very much considered in solving multi-objective decision problems in recent years. The neural network is a new approach to estimate the decision-making function of a multi-objective problem. Developing and improving the teaching methods of these types of networks facilitate to find the preferred solution in multi-dimensional issues, especially large-scale issues. In this paper, the educational method is developed to increase the efficiency of a neural network. In addition, a genetic algorithm is used to train this neural network. Furthermore, an improved cost function is proposed to adjust the parameters of the neural network and based on this function the cost parameters of the neural network are optimized. The efficiency of the proposed method is shown in solving several practical examples, including linear/nonlinear and discrete/continuous optimization problems. The efficiency of the proposed method is shown in solving several practical examples, including linear/nonlinear and discrete/continuous optimization problems.

Nowadays, the implementation of corporate banking as one of the new methods of banking in order to realize the goals of organizational excellence is an indispensable necessity and the proceeds from its proper implementation will increase the profitability of banks. The present research investigates and analyzes the corporate banking for a deep and radical overview, with the approach of critical innovative systems. Using this approach, the perception and reflection of the (hidden) stakeholders' views in the form of twelve border questions and in two state of the" Is "state and state "must". In this paper, we will use the critical thinking system and the concepts of border critique and ongoing structural conflicts in order to provide a critical analysis of a case study on corporate banking in Mellat Bank. Accordingly, we propose that the CSH approach has theoretical and practical effectiveness in improving corporate banking performance. The results of the study provide suggestions for the discovery and understanding of Boundary Critiques (initial Critiques about the system) and a general look at it in order to redesign and implement key changes in the banking system of the Mellat Bank.

The research was conducted at SAPCO, which manages the Iran Khodro Industrial Group (IKCO) supply chain, and uses the DEMATEL-ANP combination to determine the importance of third-party logistics services evaluation, ranking and selection and used for outsourcing. The results of the study, which were obtained by examining 15 logistic criteria and based on the views of experts in the field of logistics, show that the weight of criteria such as experience in the same industry, customer line stops, price, flexibility, defective delivery ratio and on time delivery is important than other criteria, and criteria such as waiting time for return, inventory turnover and environmental sustainability are less important than other indicators. Also, using the ANP-PROMETHEE combination, three logistic services companies were evaluated. The results show the company's No 3 performance is better than other companies. There is also present a way to assess the performance of logistics services companies during the cooperation period based on measurable indicators by the customer.