فهرست مطالب

Iranian Journal Of Operations Research
Volume:11 Issue: 1, 2020

  • تاریخ انتشار: 1400/04/26
  • تعداد عناوین: 10
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  • Fateme Seihani Parashkouh, Sohrab Kordrostami*, Alireza Amirteimoori, Armin Ghane-Kanafi Pages 1-24

    In this paper, two non-linear technologies are proposed based on weak disposability definitions: weak disposability with non-uniform abatement factors and new weak disposability. Both technologies are applied to Spanish airport systems and the existing technologies are modified. To remove the computational complexity of non-linear approaches, the linearization methods are proposed. Then, in order to evaluate the efficiency measure of decision making units (DMUs), a directional distance function (DDF) is applied to the linear technologies and the analysis of the results is presented.

    Keywords: Data envelopment analysis (DEA), Efficiency, Network DEA, Undesirable outputs, Weak Disposability
  • Jafar Pourmahmoud*, Naser Bafek Sharak Pages 25-42

    Cost efficiency models evaluate the ability of decision-making units (DMUs) to produce current outputs at minimal cost. In real applications, the observed values of the input-output data and their corresponding input prices are imprecise and vague. This paper employs a fuzzy data envelopment analysis (Fuzzy DEA) method to study cost efficiency of DMUs. In previous studies on the cost efficiency, no attention has been paid to the issue of ranking problem in fuzzy environment. In addition, adequate accuracy is ignored in regards toappropriate range of fuzzy cost efficiency scores. In this study, the proposed method is applied to assess fuzzy cost efficiency in accordance with the -level based approach. In this method, data information is considered as triangular fuzzy numbers. The main idea is to convert the fuzzy DEA model into a family of parametric crisp models to estimate the lower and upper bounds of the -cut of the membership functions of the cost efficiency measures. Moreover, the problem of ranking DMUs is investigated based on the fuzzy cost efficiency, using a new method. Finally, the proposed method is illustrated applying a numerical example, and then comparisons between the proposed method and previous approaches are carried out.

    Keywords: Data Envelopment Analysis, Cost Efficiency, Fuzzy Sets, The -level Based Approach
  • Jafar Pourmahmoud*, Maedeh Gholam Azad Pages 43-58

    Predictive analytics is an area of statistics that deals with extracting information from data and using that to predict trends and behavioral patterns. Many mathematical models have been developed and used for prediction, and in some cases, they have been found to be very strong and reliable. This paper studies different mathematical and statistical approaches for events prediction. The main goal of this research is to design and construct a hybrid prediction method for events prediction, based on Logistic Regression (LR) method and Data Envelopment Analysis (DEA) technique. In this study, a novel hybrid algorithm was developed, and considering the kind of collected data, LR method was applied for input selection, and the capability of the additive (ADD) model of DEA was examined to predict the occurrence or non-occurrence of the events. To apply the proposed approach, the selected disease for the case study was a stroke. The results showed that any patient who was placed on the frontier has had a stroke by one or more risk factors.  On the other hand, the observations that were not on the frontier had not suffered from a stroke. The overall accuracy of 88.5 percentages was obtained for the developed method.

    Keywords: Data Envelopment Analysis, Logistic Regression, Additive Model, Risk Factor, Stroke Disease
  • Bahareh Feizi, Ahmad Pourdarvish* Pages 59-75

    A branch of researches is devoted to semiparametric and nonparametric estimation of stochastic frontier models to employ the advantages in the operations research technique of data envelopment analysis. The stochastic frontier model is the parametric competition of data envelopment technique. This paper focused on a nonlinear autoregressive stochastic frontier production model that covers dynamic technical inefficiency. We consider a semiparametric method for the model ‎by combining a parametric regression estimator with a nonparametric adjustment‎. The unknown parameters are estimated using the full maximum likelihood and pairwise composite likelihood methods‎. After the parameters are estimated by parametric methods‎, ‎the obtained regression function is adjusted by a nonparametric factor‎, ‎and the nonparametric factor is obtained through a natural consideration of the local -fitting criterion‎. ‎Some asymptotic and simulation results for the semiparametric method are discussed‎.

    Keywords: Technical inefficiency‎, ‎Stochastic frontier models‎, ‎Nonparametric adjustment‎, ‎Panel data‎
  • Hamid Reza Yousefzadeh*, Davood Darvishi, Arezoo Sayadi Salar Pages 76-92

    Ant colony optimization (ACOR) is a meta-heuristic algorithm for solving continuous optimization problems (MOPs). In the last decades, some improved versions of ACOR have been proposed. The UACOR is a unified version of ACOR that is designed for continuous domains. By adjusting some specified components of the UACOR, some new versions of ACOR can be deduced. By doing that, it becomes more practical for different types of MOPs. Based on the nature of meta-heuristic algorithms, the performance of meta-heuristic algorithms are depends on the exploitation and exploration, which are known as the two useful factors to generate solutions with different qualities. Since all the meta-heuristic algorithms with random parameters use the probability functions to generate the random numbers and as a result, there is no any control over the amount of diversity; hence in this paper, by using the best parameters of UACOR and making some other changes, we propose a new version of ACOR to increase the efficiency of UACOR. These changes include using chaotic sequences to generate various random sequences and also using a new local search to increase the quality of the solution. The proposed algorithm, the two standard versions of UACOR and the genetic algorithm are tested on the CEC05 benchmark functions, and then numerical results are reported. Furthermore, we apply these four algorithms to solve the utilization of complex multi-reservoir systems, the three-reservoir system of Karkheh dam, as a case study. The numerical results confirm the superiority of proposed algorithm over the three other algorithms.

    Keywords: Ant colony algorithm, Continuous optimization, Chaotic sequences, Multi-reservoir systems, Genetic algorithm
  • Yasaman Modabberniya*, Hossein Vazifehdust, Mohammad Ali Abdolvand Pages 93-106

    The present study aims to identify the factors affecting the behavior of customers’ use of e-banking services of Tejarat Bank in Tehran. A qualitative method and an in-depth interview have been applied to achieve the research goal. The information and data collected from the interviews have been analyzed using open coding and axial coding. Then, the initial indicators of the model of using e-banking services were identified. In the next step, e-banking experts and specialists were asked to comment on the indicators obtained from the interviews, using the Delphi technique. The final results demonstrated that trust in banks, perceived security, ease of use, perceived utility, the impact of society, and perceived risk are considered as indicators affecting users’ behavioral intentions and ultimately their use behavior.

    Keywords: Impact of society, e-banking, perceived risk, ease of use, behavioral intentions, perceived utility
  • Yaser Rouzpeykar, Roya Soltani*, Mohammad Ali Afashr Kazemi Pages 107-121

    The hub location and revenue management problem are two research topics in the field of network design and transportation. The hub location model designs the structure of the transportation network, while the revenue management model allocates network capacity to different customer categories according to their price sensitivity. Revenue management determines which products to sell to which customers and at what price. On the other hand, due to the limited number of aircraft seats, the revenue management problem has been widely used in the aviation industry. In this study, a robust optimization model is developed for the hub location and revenue management problem. For this purpose, a real-world case study with a central hub and six airports is presented and solved using CPLEX solver in GAMS software. Finally, a sensitivity analysis was performed on the key parameters of the problem, and their effects on the objective functions of the problem was investigated. Results show that the proposed model achieved the feasible solution in reasobale time for real case problem by exact method.

    Keywords: Hub location, revenue management, robust optimization, aviation industry
  • Mani Shojaie*, Hamidreza Saeednia, Zahra Alipour Darvish Pages 122-143

    Brand personality has always been considered by researchers as an important factor in branding studies. Therefore, the present study has been conducted to evaluate the effect of brand personality on factors related to the brand-customer relationship (brand commitment, attachment and trust). The research model is based on the data collected from 400 questionnaires that have been distributed and collected among the costumers of Irtoya brand - Toyota representative in Iran - in Tehran by sampling method. Its validity been confirmed by various methods including factor validity, content validity, and face validity, and its reliability by Cronbachchr('39')s alpha method, test-retest, and split half method. It has been tested based on structural equation modeling (SEM). The results of this study show that brand personality affects brand trust and attachment directly and affects loyalty indirectly. Also, the results show that brand attachment and brand trust directly affect brand loyalty. However, in this study, the effect of brand trust on brand commitment, as well as the effect of brand commitment on brand loyalty, was not confirmed.  The factors studied in this study are known as the main factors of customer relationship with the brand, so if marketers need to create this relationship, it is better to use these factors in a great way.

    Keywords: brand personality, brand loyalty, branding factors, structural equation modeling
  • Mohammad Fallah *, Farhad Hosseinzadeh Lotfi, Mohammad Mehdi Hosseinzadeh Pages 144-156

    Using the experiences of successful and unsuccessful companies can be a criterion for predicting the situation of emerging companies. Each company can have a vector include both financial and non-financial characteristics. Accordingly, for an active or emerging company, it is possible to determine the characteristic vector and predict which group it is likely to belong to. The techniques used in this research are discriminant analysis and data envelopment analysis. Based on this technique, discriminant functions are designed to separate known sets. The main idea for finding discriminant functions is from data envelopment analysis, which makes a limit of efficiency for separating efficient units from inefficient ones. The discriminant functions of this method are used to predict the state of the company. Hyper planes are obtained as discriminant functions to separate companies. These hyper planes are based on multiple indicators. Each of these indicators can also apply in certain situations. The modeling used in this paper was used on oil companies listed on the Iran Stock Exchange. 15 indicators and criteria have been defined for each company. The data were for 2015 and 2016, and the number of oil companies was 18, of which 9 were successful and 9 were bankrupt. In this paper, with the help of data envelopment analysis and discriminant analysis, a new modeling was designed to find hyper planes for separating two sets. Modeling has been performed based on the different criteria that have existed, and each one applies in certain circumstances. In the following, the properties of the designed model are expressed and proved. The specific conditions of the criteria have become limitations that have been added to the multiplicative form of the designed model.

    Keywords: Discriminant Analysis, Data Envelopment Analysis, Efficiency, Stock Exchanges, OTC (Over the Counter)
  • Keivan Goodarzi, Mohammadreza Kashefi Neishabori, Abdollah Naami, Mojtaba Dastoori Pages 157-171

    This study was conducted with the aim of designing and explaining a content marketing pattern with a brand reinforcement approach in the country's banking industry. This research is applied in terms of objective, exploratory in terms of approach, and mixed in terms of data analysis. In the qualitative phase of the research and in order to design a model based on methodology of data foundation theory, a group of experts including senior managers of the banking industry, university professors in the field of marketing, and marketing consultants familiar with the banking industry were considered as the statistical population. Snowball sampling method was used in this phase, and this process continued until reaching the theoretical saturation. 9 interviews were conducted in total. Also in quantitative phase, the customers of the banking industry in the city of Tehran were considered as population and 450 people were selected among them as the statistical sample based on equal size cluster sampling. In the qualitative phase of the research, due to using the data foundation theory, the main data collection tool was unstructured in-depth interviews with experts. In the quantitative phase of the research, the main data collection tool was a closed-ended researcher-made questionnaire consisting of 37 items that were designed based on the initial conceptual model. The SPSS, LISREL, and smart-PLS pieces of software were used to perform descriptive and inferential analyzes in the quantitative phase of the research. Finally, the research results led to designing a content marketing pattern with a brand reinforcement approach in the country's banking industry with 11 main variables and the hypothetical relationships of the model were tested and approved in a large population.

    Keywords: Content Marketing, Brand Reinforcement, Banking Industry, Data Foundation Theory