Management Research in Iran
Year:2014 | Volume:17 | Issue:4|Papers Count:10

Credit institutions to provide variety of granted facilities to their customers, need to conduct comprehensive studies in order to know qualitative and quantitative aspects of their applicants. By this way, they can accomplish a complete evaluation of repay ability measure and calculate the refund facilities probability and finance services (generally called as validation).The purpose of this study was ranking the customer groups and specifying the best part of them until brokerage firms can do their credit allocation process mechanically. Here, after the preprocessing of the data, we converted them into RFM model. Then SOM neural network as one of the clustering algorithms changed the customers into 10 clusters. Using the proposed model, the clusters were ranked. The top clusters were identified and facilities grant operations were done to the members of these clusters.Finally, three clusters 5, 1 and 7 were defines as top clusters, which are the target customers. Coefficient facilities granted to the top three clusters are 0.271, 0.173 and 0.556, respectively.

In traditional covering problem, the covering level of receiving the services is independent of distances between nodes and facilities. However, in gradual covering location problem (GCLP), the covering objective depends on the distance of customers from the service centers. Hence, increasing in customer-facility distances will result in decreasing of the covering level. In most of covering problems, researchers only consider the distance factor.However; in the real word, there are some other important elements such as population, availability, distance and others, which affect the location of service centers. Increasing the number of demand nodes and criteria will result in increasing of the nodes´ evaluating computational time and inconsistency rate. This paper proposes a combined approach of Simulated Annealing (SA) and Artificial Neural Network (ANN) to solve the multicriteria GCLP. In the presence of few nodes, the score of nodes is calculated using Analytic Hierarchy Process (AHP) method. Moreover, by increasing the number of nodes, the score of every node will be calculated using ANN instead of AHP. Statistical test of signed rank test shows that there is not a significant difference between the results of ANN and AHP methods.Comparison of results between the exact solution method and the proposed algorithm confirms the efficiency of the proposed solution approach.

The necessity of restructuring university budgeting from program-based to performance-based budgeting (PBB) leads many studies to be conducted. Reviewing the literature, we observed that there is no mathematical model including Dual PBB structure in university.The purpose of this paper is to construct a PBB model for university so that the budget is allocated not only to the plans based on their priorities, but also to the faculties based on approved student per capita by the Ministry of Sciences, Researches and Technology. Considering the various criteria in the university system and because of fuzzy and stochastic uncertainties in the problem parameters, two scenarios were analyzed.1) Crisp Lower Bound Robust Fuzzy PBB (CLB-RFPPB) model.2) Fuzzy Lower Bound Robust Fuzzy PBB (FLB-RFPPB) model.A significant point in both of them was using performance indicators-- calculated based on the data envelopment analysis approach (DEA) regarding a basic model of input-oriented CCR, and determining the important coefficients for each educational groups in order to allocating budget. In addition, the weights of goals and the priority of each plan were determined using some paired comparison questionnaires completed by the experts. The RFPBB model has 5 goals, 1142 constraints and 994 decision variables.The results of models solution presented on two macro and operational levels- and simulation of Crisp and two RFPBB models, demonstrated the high level capabilities of RFPBB models in response to the uncertainty in the parameters of problem and also in managing the level of decision risk.

After the industrial economy span that caused many changes in the human life and the human systems, now we are facing a new era, namely "electronic revolution". One of the symbols of this electronic revolution is Mobile Commerce. Nowadays, this new style of trading is being used in many parts of the globe especially, in the countries with poor infrastructures. Now the fundamental question is how to design and explain the business development model. To solve this issue, the present exploratory study was conducted.Through scoring and weighting the extracted factors and making items for them by the Delphi panel of experts (during four rounds), the researcher found three dimensions (technological, social and personality) and twelve new variables. These variables formed the conceptual model of Mobile Commerce.The conceptual model was examined in the Iranian Virtual Society with research designed questionnaire and using AMOS software. The collected data were analyzed using Structural Equation Modeling. For this purpose, initially the structural relationships were tested by using Confirmatory Factor Analysis.Then using a Path Analysis approach the hypotheses were examined. At the end, by employing the future studies approach and adding the time dimension to the three dimensions, the model was made more dynamic.

In modern business environments, Agility is advocated as the fundamental characteristics for competitiveness. Little research, however, exists, which provides integrated methodologies suitable to be practically adopted to enhance the agility of companies. In this research, we utilized an original approach, which, by linking competitive bases, agile attributes and agile enablers, aims at identifying the most appropriate enablers effective on increasing the companies agility. The approach is based on the quality function deployment methodology, and in particular, on the house of quality, which has been successfully adopted in the new product development field.The whole scaffold exploits fuzzy logic to translate linguistics judgements required for relationships and correlations matrixes into numerical values. In point, this approach was applied in Auto Part industry and identified suitable enablers in this industry. Supply chain management in this industry was recognized as the most important enabler. Knowledge management, information technology, concurrent engineering, team building, project management and hardware were placed in the other ranks. The main limitation of this research is time consuming due to the calculation of the QFD cited. Dependencies and correlations at HOQ fuzzy numbers were used to describe the relationship accurately.

Determining how to assess learners and contents of e-learning is essential, which is conducted by a professor or teaching assistant. As a result they can determine student assessment methods, such as holding an online test or periodic homework assignment. If the organizers know the effect of each activity in the quality of learning, then besides saving considerable time and resources to stakeholders courses, they can transfer the useful content, make a realistic assessment of students and will ultimately improve e-learning.In this paper, first we use unsupervised techniques of data mining for clustering, describe the present status of learners, extract the hidden rules in e-learning data using rule mining, and discover the effective contents in desired results. Next, using supervised methods, we predict the results of courses. Using real data of an electronic course provided and with designing four different methods for data sampling and training system, predictions are performed and the methods are validated with an accuracy rate of 92.86%.Our findings show that the methods of this study can help teachers for a better understanding of learners and the impact of training activities required such as describing the characteristics of learners based on the discovery of hidden patterns in their acquired scores. They can also determine the most effective learning activities and decide about the real measures of learners.

Introduction: High death rate as a result of Road Traffic Collision (TRC) in Iran and the concomitant financial and economic damages are alarming and requires an immediate attention and proper solution. Taking the culture of safety into consideration, this research aims to offer a model for enhancing road safety.Methods: In a comparative study, the strategies used by successful countries in this regard and the factors derived from theoretical studies were inverting ated and a model consisting of three rounds of the Delphi panel, dimensions, components and parameters needed to determine the extent significance was determined using AHP. Panel members are experts in the field of road safety.Reasults: Findings of this research show that adoption of any and each of the above mentioned components would enhance the road safety culture.Conclution: Adopting a flexible approach at any circumstance constitutes the most important aspect of this model. It is possible that under certain conditions, reinforceing of each factor can promote the safety culture.

Along with the tremendous growth of mobile telecommunications in the 21st century, ITU defined wireless communications as the driver of ICT in the world. Advent of this technology to Iran, like every other new technology, led to superior changes in economic, socio-cultural, political, defensive and security aspects.None of the researches conducted so far regarding the national security has directly focused on mobile telecommunications. The aim of this paper is to propose a structural model for the development of mobile telecommunications with regards to the national security interests. Hence, we first define the research question and problem solving method using a systematic approach.The research guidelines are then studied accordingly. After identifying the influential elements and their interrelations, the development model, which is a directed graph, is extracted using Interpretive Structural Modeling (ISM) method. Key elements of the model include: national security, national interests, foresight, environmental analysis, “design approach” for problem solving, breakthrough thinking, apt theory for development, communications regulatory agency, strategic intentions and upstream documents/acts, and macro trends. The final model presents how strategic intentions turn into action plans under the influence of global macro trends. Categorizing the layers of the model for better implementation and long-term influence of national decisions and accomplishments on global drivers constitute other achievements of this study.

Football is an industry in which Branding and its foundation, i.e., brand identity, is extremely important to the extent that researchers have proposed specific brand models in the countries where football has a high profile. In this research, using descriptive analytic methods, in terms of application, the data were collected by means of quantitative method. The statistical population consisted of 10 professionals, experts of the subject, and also fans of six soccer teams in Iran´s Premier League, who are usually present in the stadium to watch the matches. The sample size included of 300 fans in Phase I, and 720 fans in Phase II. The fans were selected by means of the simple random sampling method; the fans were equal in numbers from different teams. In order to present the brand identity model for the existing soccer teams in Iran´s Premier League in the season 2012/2013, the researchers in this study decided that it is necessary to use the novel models of brand identity, the viewpoints and ideas of football professionals and fans in our country, and the association models, as well as the brand identity models, which are currently used in the countries, (for example, Germany, France, Spain, S. Korea), in which soccer has a high profile. Finally, using CFA and SEM models, we provided a new perspective on the dimensions of football brand identity in Iran on the basis of the factor loading: Success (./96), Color (./95), Name and Mark (./94), Delivery (/.93), Uniform (./92), Fans and Rival (./88), Geographical Ties and History (/.87), Star Player and Tradition (/.84), Performance (./83), Stadium (./73) and Non-Player Personnel (./59).

Nowadays, reverse logistics is one of the major activities of supply chain management that include, all of the physical activities related to returned products (e.g., collection, recovery and recycling). So that designing and implementing of appropriate reverse logistics, not only leads to the increase of customer loyalty, but also reduces the inventory and transportation costs.This paper presents a mixed-integer linear programming (MILP) model for the network design of forward and reverse logistics, which minimizes the costs consisting of the fixed cost, material cost and construction cost of a potential center. To validate this model, a number of test problems are generated, and then its parameters are determined. The presented model is solved by the Lingo software, and the associated computational results along with the sensitivity analysis are illustrated. Additionally, the returned products with different demands for one and two products are illustrated. Finally, a remarkable conclusion is presented.